Improving Chronic Disease Management With Pieces (ICD-Pieces)
Phase: NA
Conditions: Chronic Kidney Disease, Diabetes, Hypertension, High BP, Type 2 Diabetes
Sponsor: University of Texas Southwestern Medical Center

1 
 
Title 
 
 
 
 
 
Improving Chronic Disease Management with Pieces (ICD-Pieces)  
Sponsor National Institutes of Health/National Institute of Diabetes in Digestive and Kidney 
Diseases 
 
NIDDK Funding Mechanism: Exploratory/Development Cooperative Agreement 
 
Study Protocol Version 1.8  
October 31, 2018 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

2 
 
Statement of Compliance 
This study will be carried out in accordance with good clinical practice (GCP). This study will be 
conducted in accordance to NIH clinical terms of award. 
All key personnel (all individuals responsible for the design and conduct of this study) have 
completed human subjects protection training. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

3 
 
Table of Contents 
Title ........................................................................................................................................... 1 
Statement of Compliance ........................................................................................................ 2 
Table of Contents ..................................................................................................................... 3 
List of Abbreviations ............................................................................................................... 7 
PROTOCOL SUMMARY ........................................................................................................... 8 
1. 
Key Roles ..................................................................................................................................... 12 
2. 
Background and Rationale ........................................................................................................ 13 
2.1 
Background on Condition .................................................................................................... 13 
2.2 
Study Rationale .................................................................................................................... 15 
2.3 
Potential Risks and Benefits ............................................................................................... 20 
3. 
Objectives ..................................................................................................................................... 21 
3.1 
Study Objectives ................................................................................................................... 21 
3.2 
Study Outcome Measures .................................................................................................. 22 
3.2.1 
Primary Outcome Measures ....................................................................................... 22 
3.2.2 
Secondary Outcome Measures .................................................................................. 23 
4. 
Study Design ................................................................................................................................ 24 
5. 
Selection and Enrollment of Participants ................................................................................. 26 
5.1 
Subject Inclusion Criteria .................................................................................................... 26 
5.2 
Subject Exclusion Criteria ................................................................................................... 28 
5.3 
Strategies for Recruitment and Retention ........................................................................ 28 
5.4 
Treatment Assignment Procedures ................................................................................... 28 
6. 
Study Interventions ..................................................................................................................... 29 
6.1 
Healthcare System Collaboratory ...................................................................................... 29 
6.2 
Informatics Architecture ....................................................................................................... 30 
6.3 
Practice Facilitator ................................................................................................................ 32 
6.4 
Selection of Study Sites and Subjects .............................................................................. 33 
6.5 
Implementation Collaborative Model of Care ................................................................... 34 
6.6 
Maintenance of Provider and Facilitator Engagement ................................................... 36 
6.7 
Separation Control and Intervention Group ..................................................................... 36 
7.  
Study Schedule ........................................................................................................................... 38 
7.1  
Screening ............................................................................................................................... 38 

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7.2 
Enrollment/Baseline ............................................................................................................. 38 
7.3 
Follow up Visits ..................................................................................................................... 38 
7.4  
Final Study Visit .................................................................................................................... 38 
7.5  
Unscheduled Visits ............................................................................................................... 38 
7.6  
Early Termination Visits ....................................................................................................... 39 
8. 
Study Procedures/Evaluations .................................................................................................. 40 
8.1  
Clinical Evaluations .............................................................................................................. 40 
8.2 
Laboratory Evaluations ........................................................................................................ 40 
8.3  
Special Measures ................................................................................................................. 40 
8.4  
Special Measures ................................................................................................................. 40 
8.5      Substudy at ProHealth of Connecticut…………………………………………………..41 
8.6 
Substudy: Testing Computable Definitions of Acute Kidney Injury (AKI) in the ICD-Pieces 
Clinical Trial…………………………………………………………………………………………………………………………………….42 
8.7 
Substudy: Understanding Decisions to Opt-Out of Pragmatic Clinical Trials……...…43 
9 
Assessment of Safety ................................................................................................................. 46 
9.1 
Specification of Safety Parameters ................................................................................... 46 
9.2 
Methods and Timing for Assessing, Recording and Analyzing Safety Parameters ... 47 
9.2.1 
Adverse Events ............................................................................................................. 47 
9.2.2 
Expected Adverse Reactions ..................................................................................... 47 
9.2.3 
Serious Adverse Events .............................................................................................. 47 
9.2.4 
Unanticipated Problems .............................................................................................. 47 
9.2.5 
Procedures to be Followed in the Event of Abnormal Laboratory Test Values or 
Abnormal Clinical Findings ......................................................................................................... 48 
9.3 
Reporting Procedures .......................................................................................................... 48 
9.4 
Type and Duration of Follow-up of Subjects after Adverse Events .............................. 48 
9.5 
Halting Rules ......................................................................................................................... 48 
9.6 
Safety Oversight (DSMB) .................................................................................................... 48 
10. Clinical Monitoring ....................................................................................................................... 49 
10.1 
Site Monitoring Plan ............................................................................................................. 49 
11. Statistical Considerations ........................................................................................................... 50 
11.1  
Study Hypothesis: ............................................................................................................ 50 

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11.2  
Sample size consideration: ............................................................................................. 50 
11.3  
Statistical Analysis Plan: ................................................................................................. 51 
12.  Source Documents and Access to Source Data/Documents ............................................... 52 
13. Quality Control and Quality Assurance .................................................................................... 53 
13.1  
Development of MOP and Training ............................................................................... 53 
13.2 
 Site Visit ................................................................................................................................ 53 
13.3 
Pieces Functionality ............................................................................................................. 54 
13.4 
Monitoring Data Quality ....................................................................................................... 54 
13.5 
Routine Progress Reports ................................................................................................... 54 
14. Ethics/Protection of Human Subjects ....................................................................................... 54 
14.1 
Ethical Standards ................................................................................................................. 54 
14.2 
Institutional Review Board .................................................................................................. 54 
14.3 
Informed Consent Process ................................................................................................. 54 
14.4 
Exclusion of Women, Minorities, and Children (Special Populations) ......................... 55 
14.5 
Subject Confidentiality ......................................................................................................... 55 
14.6 
Study Discontinuation .......................................................................................................... 55 
14.7 
Future Use of Study Specimens ........................................................................................ 55 
15. Data Handling and Record Keeping ......................................................................................... 56 
15.1    Data Collection ..................................................................................................................... 56 
15.2     Data Management and Reports ........................................................................................ 57 
16. Study Administration ................................................................................................................... 59 
16.1 
Study Leadership and Governance ................................................................................... 59 
16.1.1 
Steering Committee ..................................................................................................... 59 
16.1.2 
Executive Committee ................................................................................................... 59 
16.1.3 
Conflict of Interest Policy ............................................................................................. 60 
16.2  
Subcommittees ................................................................................................................. 60 
16.2.1 
Technical Workgroup ................................................................................................... 60 
16.2.2 
Biostatistics and Research Design Core .................................................................. 60 
16.2.3  
Diabetes Advisory Workgroup ................................................................................ 60 
16.2.4 
Evaluation Workgroup ................................................................................................. 60 
17.  Literature References ................................................................................................................. 61 

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Appendix I: 
CHRONIC KIDNEY DISEASE (CKD) HYPERTENSION MANAGEMENT 
PROTOCOL 
69 
Appendix II: 
DIABETES MANAGEMENT PROTOCOL ...................................................... 82 
 

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List of Abbreviations 
ACEI  
Angiotensin Converting Enzyme Inhibitor 
ACO 
 
Accountable Care Organization 
AKI 
 
Acute Kidney Injury 
ARB 
 
Angiotensin II Receptor Blockers 
CHF 
 
Congestive Heart Failure 
CKD 
 
Chronic Kidney Disease 
CV 
 
Cardiovascular 
DFW  
Dallas Fort Worth 
DM 
 
Diabetes Mellitus 
DSMB  
Data Safety Monitoring Board 
eGFR  
estimated Glomerular Filtration Rate 
EHR 
 
Electronic Health Record 
ICD-10  
International Classification of Diabetes 10 
ICD-9  
International Classification of Diabetes 9 
ICD-Pieces 
Improving Chronic Disease Management with Pieces 
 
MCC  
Multiple Chronic Conditions 
NKDEP 
National Kidney Disease Education Program 
NLP 
 
National Language Processing 
PCCI  
Parkland Center Clinical Innovation 
PCP 
 
Primary Care Providers 
PHHS  
Parkland Health and Hospital System 
Pieces  
Parkland Intelligent e-Coordination and Evaluation System 
PROs  
Patient Reported Outcomes 
SUNY  
State University of New York 
THR 
 
Texas Health Resources 
UTSW  
University of Texas Southwestern Medical Center 
VA 
 
Veterans Administration 
 

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PROTOCOL SUMMARY 
Improving Chronic Disease Management with Pieces (ICD-Pieces) 
Objectives 
The overall goal of the study, Improving Chronic Disease Management with Pieces (ICD-
Pieces) is to improve the care of patients who have the triad of coexistent chronic kidney 
disease, diabetes and hypertension. The primary objective of the study is to test the 
hypothesis that patients who receive care with a collaborative model of primary care and 
subspecialty care interventions enhanced by novel information technology and practice 
facilitators to leverage data from the electronic health records will allow   accurate identification 
of patients with a triad of CKD, diabetes and hypertension using objective and reproducible 
criteria, and provide clinician support for implementation of best practices of care, monitoring 
clinical measures, adjusting treatments and reduce 12-month all-cause unplanned 
hospitalization rate for CKD, diabetes and hypertension. 
Secondary objectives as follows: 
a) 
To test if implementation of the collaborative model of primary care-subspecialty care 
interventions will reduce 30-day readmissions (for patients who have an index 
hospitalization), emergency room visits, cardiovascular events or deaths from any cause 
and  disease-specific hospitalizations pre-specified in this study as cardiovascular 
complications, 
congestive 
heart 
failure, 
volume 
overload, 
accelerated/malignant/uncontrolled 
hypertension, 
acute 
coronary 
syndromes, 
myocardial 
infarction, 
coronary/peripheral 
revascularization, 
stroke, 
limb 
ischemia/amputations, diabetes complications, uncontrolled diabetes or hypoglycemia, 
acute kidney injury, hyperkalemia, electrolyte disturbances, drug toxicity, medication 
errors and infections. 
 
b) 
To develop and validate predictive models for risks of disease-specific hospitalizations, 
all-cause hospitalizations, 30-day readmissions, emergency room visits, cardiovascular 
events and deaths for all patients with coexistent CKD, diabetes and hypertension.  
 
c) 
To collect demographic data and clinical descriptive data to assist phenotyping patients 
with a triad of CKD, diabetes and hypertension.  
 
d) 
To obtain important safety data for patients with CKD, diabetes and hypertension 
including acute kidney injury, progression of chronic kidney disease (changes in eGFR), 
development of electrolyte disturbances and medication errors and drug toxicity (even if 
not leading to hospitalization).  
 
e) 
To collect information on resource utilization including not only hospitalizations but 
emergency room visits, outpatient visits and procedures completed (both diagnostic or 
therapeutic). 
Design and Outcomes 
The study will employ a prospective stratified cluster randomization design. The stratum is each 
of the four large healthcare systems participating in the study. The unit of randomization will be 
primary care clinics. In some healthcare systems several primary care clinics share the same 
geographic location and personnel and they will be randomized as a single unit.  

9 
 
The primary outcome of this trial is all cause hospitalizations for patients with a triad of CKD, 
diabetes and hypertension. Specifically, the outcome will be hospitalization rates at 12 months 
for all study participants. We will capture all cause unplanned hospitalizations including both 
regular hospitalizations as currently defined by CMS and observation status overnight (to avoid 
uncertainties related to variations in applications of definitions based on the recent 
implementation of the two midnight rule). Hospitalizations will be ascertained from electronic 
healthcare records with assistance of electronic tools in each of the participating healthcare 
system. To maximize completeness of outcome data acquisition we will also track study 
patients with outcome data from the Dallas Fort Worth Hospital Council which is a cooperative 
regional-sharing initiative that allows to match patients with any hospitalizations in any hospital 
in Dallas Fort Worth. Patients in ProHealth in Connecticut are part of an accountable care 
organization (ACO) and outcomes are also captured in a database from reports received by 
ACO. There will be also special attention to capture outcome information from VA database 
patients followed at the VA of North Texas who may not be part of the group identified through 
the Dallas Fort Worth Hospital Council.  
Secondary outcomes captured in the study will include 30-day all cause readmissions (for those 
patients who have an index hospitalization), emergency room visits, cardiovascular events and 
deaths, and disease-specific hospitalizations for  cardiovascular complications, congestive heart 
failure, volume overload, hypertension complications, acute coronary syndrome, myocardial 
infarction, coronary/peripheral revascularization, stroke, amputation/limb ischemia, uncontrolled 
diabetes, hypoglycemia, diabetes complications, acute kidney injury, hyperkalemia, electrolyte 
disturbances, medication errors, drug toxicity and infections.. Data for secondary outcomes will 
be obtained as outlined above with the primary outcomes. In addition, we will verify if enrolled 
patients who do not have an encounter in our systems within two years of study participation 
are classified as dead or alive using the Social Security Index.  
Other secondary outcomes captured from the electronic health records will include descriptive 
patient characteristics including demographic and clinical data from patients with CKD, diabetes 
and hypertension as well as information on patient comorbidities, changes in renal function 
(eGFR), episodes of acute kidney injury as well as safety/adverse events. Resource utilization 
will be captured from careful evaluation of hospitalization events, clinic visits and diagnostic and 
therapeutic procedures completed.  
 
Interventions and Duration 
Figure: Schematic Design ICD-Pieces Trial summarizes main components of the study 

10 
 
 
There will be two study groups: An active intervention group randomized to the collaborative 
model of care facilitated by information technology and practice facilitators and a group 
randomized to standard/usual care. Pieces will screen electronic health records of participating 
healthcare systems to detect patients with a triad of CKD, type 2 diabetes and hypertension 
according to established inclusion criteria for the study. The candidate cohort of potential sites 
will then be randomized to active intervention (collaborative care model enhanced by Pieces) or 
control group (standard of care). Interventions available for implementation in the active group 
include maintaining blood pressure less than 140/90mmHg, use of angiotensin converting 
enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARB), treatment with statins, aiming 
for hemoglobin A1C at recommended target for coexistent comorbidities, avoidance of 
nephrotoxic medications including nonsteroidal anti-inflammatory drugs (NSAID). Other 
interventions available include education on CKD for both primary care providers and for 
patients. There will also be available material on lifestyle modification and immunizations.  
After a patient is enrolled, the primary care practitioner activates the CKD, diabetes and 
hypertension collaborative model of care. Primary care practitioners will have the option to 

11 
 
initiate protocols for CKD management, hypertension management, lipid management and 
diabetes management. Protocols can be initiated via smart sets in the electronic health record. 
Practice facilitators working together with primary care practitioners can also assist with 
activation of protocols, smart sets, responses to information on clinical measures and overall 
implementation of the collaborative model. 
Sample Size and Population 
The sample size for this study is 10,991 patients. The stratum will be healthcare systems and 
unit of randomization is primary care/practice site. Men and women ages 18-85 years will be 
study participants. 
Study Duration  
Enrollment of study participants from selected clinics will occur over a period of 2 years. The 
study duration for each participating subject will be 12 months.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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1. 
Key Roles 
1.1 
Principal Investigator 
Miguel A. Vazquez, MD 
Professor of Internal Medicine 
UT Southwestern Medical Center 
5323 Harry Hines Boulevard 
Dallas, TX 75390-8856 
 
1.2 
See Appendix for a list of co-Investigators and Study Staff 
 
1.3 
Collaborating Institutions 
 
 
 
 
 
 
 
University of Texas Southwestern Medical 
Center (Central Academic Partner) 
5323 Harry Hines Boulevard 
Dallas, TX 75390-8856 
Cheryl L. Anderson 
214.648.4494 
PCCI 
8435 Stemmons Freeway Suite 1150 
Dallas, Texas 75247 
Ruben Amarasingham, MD, MBA 
214.590.1168 
The State University of New York at Buffalo 
Sponsored Projects Services 
402 Crofts Hall 
Buffalo, NY  
Jeffrey Schieder 
716.645.4408 
Parkland Health and Hospital Systems 
(PHHS) 
5200 Harry Hines Blvd 
Dallas, TX 75235 
Liz McMullen 
214.590.4128 
Dallas VA Research Corporation  
4500 South Lancaster Road, Bldg. 43, Suite 
124  
Dallas, TX 75216 
Phyllis A. Bilbrey 
214.857.2090 
Connecticut Center for Primary Care, Inc. 
P.O. Box 762 
Farmington CT 06034 
Tom Meehan, MD 
860-284-5288 
Texas Health Resources 
Texas Health Resources 
612 E. Lamar Blvd. Pavillion 3 
Arlington, TX 76011 
Ferdinand Velasco, MD  
682-236-6061 
 

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2. 
Background and Rationale 
2.1 
Background on Condition 
Chronic kidney disease (CKD), diabetes and hypertension are three common chronic medical 
conditions in the general population. It is estimated that 31% of US adults have hypertension, 
14% have CKD, and almost 10% have diabetes[1-4]. Diabetes and hypertension are among the 
most prevalent chronic medical conditions in adults of all ages[1,5]. Diabetes and hypertension 
are the two leading causes of CKD in the United States, which has now become a major public 
health problem[77]. The triad of CKD, diabetes and hypertension conspires to promote 
particularly adverse outcomes[9,10,16,18,17]. Moreover, CKD disproportionately affects vulnerable 
populations including the elderly, Hispanics, African-Americans and those who reside in 
socioeconomically deprived areas[1,2,3]. 
In patients with CKD, the kidneys are not able to filter blood normally and have reduced 
glomerular filtration rate (GFR) and/or abnormal leakage of albumin in the urine. Compelling 
data indicates that graded reductions in GFR are strongly associated with higher risks of death, 
cardiovascular events, and hospitalizations, independent of traditional cardiovascular risk 
factors [5,12]. Premature death, both from cardiovascular disease and from all causes, is higher in 
adults with CKD compared to adults without CKD[6,7].  
Multimorbidity or the coexistence of multiple chronic conditions (MCC) is especially significant 
for patients with the triad of CKD, diabetes, and hypertension. Specifically, the coexistence of 
kidney disease and diabetes is associated with considerably higher mortality than the excess 
risk with either risk factor alone[10] (Figure 2.1). Similar relationships are observed with CKD and 
hypertension and with diabetes and hypertension[11,12]. While risk prediction models for 
progression from CKD to ESRD among those with CKD, diabetes and hypertension are 
clinically useful, they are very limited in predicting cardiovascular events and mortality[13,20,50]. 
 
 
 
Figure 2.1 

14 
 
Given the increasing prevalence of the triad of CKD, diabetes and hypertension, and the 
excessive risk for cardiovascular morbidity and mortality, there is an urgent need to deeply 
phenotype this group of patients, identify risks for adverse outcomes, and develop and 
implement best practices to care for these patients. 
Challenges in the care of CKD, diabetes and hypertension 
Care for patients with multi-morbidities is challenging and often suboptimal. Appropriate care for 
patients with CKD, diabetes and hypertension includes early detection and institution of 
strategies to slow progression and treat associated complications and cardiovascular risks [5,77]. 
 
Early diagnosis of CKD allows for the institution of effective therapies that can prevent the onset 
and progression of irreversible kidney damage. Detection of CKD can be accomplished with 
relatively simple tests, such as serum creatinine and urine for protein and/or albumin. 
Unfortunately, a large proportion of patients with high risk conditions for CKD, such as diabetes 
and/or hypertension, do not have basic tests of kidney function or urine albumin performed.[14] 
Progressive CKD is a catastrophic condition that leads to end-stage kidney disease requiring 
very expensive therapies including dialysis and transplantation. These patients suffer from 
excessive rates of depression, catastrophic cardiovascular events such as stroke, heart attack 
and 
heart 
failure 
and 
other 
comorbidities 
that 
are 
difficult 
and 
expensive 
to 
manage.[1,2,4,48,49,47,46,45] CKD detection and documentation is low even across health care 
systems with sophisticated electronic health records (EHR) [83].  
Catastrophic consequences result from lack of detection of CKD, diabetes and 
hypertension 
 
More than 25% of adults with Type II diabetes are undiagnosed. Moreover, based on fasting 
glucose or hemoglobin A1C values, around 35% of adults in the US have pre-diabetes, and a 
large proportion are not aware of the risk[56]. Among adults with hypertension, about 22% are 
not aware of their condition[1,21]. The consequence of missed detection of CKD, diabetes and 
hypertension is higher morbidity, mortality and financial cost to our healthcare system. 
Failure of implementation of strategies to treat CKD, diabetes and hypertension and 
associated complications 
Several strategies are proven effective to treat CKD, diabetes, and hypertension. Recent 
guidelines from medical groups have included specific recommendations for patients who have 
CKD coexisting with diabetes and/or hypertension.[5,25,24,65,67-71,31,34,11] Appropriate interventions, 
including treatment of hypertension, blocking the renin-angiotensin-aldosterone system, 
improving glycemic control and managing dyslipidemia can slow the progression of CKD and 
reduce the risk of cardiovascular disease for most patients with CKD, hypertension, and 
diabetes.[26,27,28,29,30,32,33,22,23,19,57,58,59,60,62,63] 
Unfortunately, many of these strategies are not implemented in patients with CKD, diabetes and 
hypertension. Less than half of adults with CKD have blood pressure values within 
recommended targets[14]. About one half of patients with diabetes do not meet targets for 
glycemic control, BP or LDL cholesterol levels [35]. The use of recommended medications and 
achievement of targets for risk factor management are also unacceptably low for patients with 
CKD [1,2,5,14]. Furthermore, patients with CKD, diabetes and hypertension suffer from excessive 
morbidity and mortality from adverse safety events.[76,79,80,81] 

15 
 
2.2 
Study Rationale 
The need for new strategies to improve care for patients with CKD, diabetes and 
hypertension 
There are some effective ways to treat chronic medical conditions, but implementation of 
recommended treatments is a major challenge.  
Surveys have revealed that most primary care physicians and subspecialists (e.g., 
nephrologists) favor collaborative care for patients with CKD[36]. However, implementation of 
care for those with CKD, diabetes and hypertension among practitioners remains fragmented, 
and delayed care is common. Education and efforts to facilitate communication among patients 
and providers about chronic disease management are effective in removing patient-related and 
physician-related barriers to CKD care. Health services research suggests that the design of the 
care system is a primary determinant of the quality of care in most chronic conditions[84,85]. 
Some large health care systems have reported success identifying large numbers of patients 
with CKD and providing comprehensive CKD care[37,38,83]. The most promising strategies to 
improve CKD care emphasize multidisciplinary care models[39,40,41,42]. Integration of nephrology 
care and diabetes care in the chronic care model within existing health care systems has 
achieved some success in vulnerable populations with CKD, including those served by the 
Indian Health Service[43,44]. Low recognition of CKD, limited resources, and lack of familiarity 
with CKD care have limited wider application of these approaches.  
Recent studies have reinforced the need for new strategies to improve care for patients with 
CKD. The introduction of automated eGFR reporting has led to higher detection of CKD in some 
healthcare systems but limited improvements in CKD care.[83] Electronic CKD checklists have 
improved adherence to some CKD guidelines but limited in scope.[75] Ongoing studies are 
evaluating the role of novel interventions including implementation strategies to promote patient 
safety through care transitions, patient-directed education and self-management tools, 
utilization of patient navigators, utilization of clinician decision support models and patient-
decision support for selection of modalities of renal replacement therapy[74]. 
2.2.1 Implementing a new model of care for multiple chronic conditions 
At Parkland Health and Hospital System, we have had the opportunity to address the challenge 
of caring  for patients with CKD in and underserved safety-net hospital system by putting in 
place a collaboratory model of primary care and subspecialty interventions using a novel 
technology platform (Pieces) in a pilot study supported by NIDDK [74]. (see figure 2.2.1 CKD 
Implementation Study) 

16 
 
 
2.2.2 Using a novel information technology to improve care of patients with multiple 
chronic conditions 
PIECES (Parkland Intelligent e-Coordination Evaluation System) is an IT-enabled e-monitoring 
and coordination software platform that sits on top of the electronic health record. Pieces has 
been developed and assembled by Dr. Ruben Amarasingham who is a co-investigator in our 
study. PiecesTM is comprehensive and can identify patients with specific clinical conditions, such 
as heart failure, using natural language processing (NLP), apply a clinical predictive model for 
risk stratification, allow for secure messaging to clinical and case management staff, provide a 
dashboard to track completion of intervention activities, and monitor patient outcomes (Figure 
2.2.2). In this particular setting, PiecesTM facilitates identification of patients in real time, ranking 
patients into risk categories, notification of care team, establishing of plans, monitoring of 
inpatient and outpatient activity, and evaluation and coordination of tasks for improvement.  
Figure 2.2.1 

17 
 
 
 
 
Preliminary Data: 
Our team at Parkland Health and Hospital System developed and validated a model to predict 
the risk of readmissions in congestive heart failure (CHF) with PiecesTM, using information 
available in the first 24 hours of admission in the EHR and other computerized data sets, 
including clinical factors (ICD-9 codes, vital signs, lab values, etc.) and electronically derived 
measures of social disadvantage (housing stability, census track, etc.), and adherence 
(pharmacy refills, outpatient appointment follow-up, etc.). This model demonstrated greater 
predictive probability for 30 day-readmission (C-statistic of 0.72) than prior models, including the 
ones used by Medicare and in multi-site heart failure trials, and has the advantage that it can be 
calculated in real time within 24 hours of admission.[51]  
In a prospective, interrupted time-series trial with concurrent controls involving all CHF 
admissions to Parkland Memorial Hospital from December 2008 to November 2010, Pieces™ 
real-time risk stratification and a patient-tailored CHF intervention significantly reduced 30-day 
readmissions in patients from 26% to 21%, and the subset of Medicare patients fell from 20% to 
14% (p< .01), putting Parkland Hospital among the top decile of hospitals nationally on this 
metric.[52]  
Pieces™ software is flexible and can be adapted to track and coordinate a broad variety of 
electronically ascertainable inpatient and outpatient activities and protocols. PiecesTM has been 
used to develop several clinical predictive models. These include but are not limited to 
predicting out-of-ICU cardio-pulmonary arrest, sepsis, risk of surgical complications, 30-day 
readmission risk for diabetes, HIV, MI and pneumonia, risk of long-term diabetes complication 
and hospital risk surveillance. The automated out of ICU cardiac arrest model had excellent 
discrimination (c-statistic=0.85) and calibration and was more sensitive (51.6% and 42.2%) and 
specific (94.3% and 91.3%) than MEWS (a previously published risk score based on the 
Figure 2.2.2 

18 
 
number and degree of vital sign and level of consciousness abnormalities) alone. The 
automated model predicted resuscitation event and death (RED) 15.9 hours before they 
occurred and earlier than Rapid Response Team (RRT) activation (5.7 hours prior to an event, 
p=0.003) and showed excellent discrimination, sensitivity and specificity.[53]  Pieces has also 
been successfully used to electronically identify patients with diabetes to place in an e-registry 
within the Pieces system[54]. 
2.2.3 Preliminary data: CKD Collaboratory Study 
Our group has conducted an NIDDK-funded study (Improving CKD Detection and Care in a 
High Risk Underserved Population/R34DK094115) at Parkland Health and Hospital System. 
This is a prospective study to identify patients with previously undiagnosed CKD and implement 
established therapies for these patients. The primary outcome of this study was blood pressure 
control for patients followed in primary care clinics with a collaborative primary care-nephrology 
care model enhanced by PiecesTM. In this study we defined CKD by eGFR less than 60 ml/min 
or proteinuria/albuminuria and confirmed with repeat values more than 3 months apart. Figure 
2.2.3.1 summarizes the study design using Pieces. 
 
 
When comparing detection of CKD based on the established diagnostic criteria described above 
to cases previously diagnosed with CKD by ICD-9 diagnostic codes or inclusion in the problem 
list, we found 46-64% of patients with newly detected CKD. Treatment efforts focused on blood 
pressure control which was the primary outcome of the study. The results on achieving the 
primary outcome of blood pressure control were encouraging. BP control improved from 34.6% 
at baseline to 44% at most recent analysis. This accomplishment is particularly relevant given 
the low prevalence of blood pressure control in patients from high risk populations similar to our 
study group. Final collection and data analysis will be available in near future. (see table 
2.2.3.2) 
Figure 2.2.3.1 

19 
 
Using our collaborative model of CKD care enhanced by PiecesTM we have been able to identify 
a significant proportion of patients with previously undiagnosed CKD. Primary care physicians 
were notified of the diagnosis and eligibility of patients to participate in the study. The majority of 
patients approached agreed to participate in the study. This model and technology can also be 
applied to management of diabetes and other risk factors in CKD such as diabetes, 
hypertension and dyslipidemia. 
 
 
Addressing the impact of multimorbidity from CKD, Diabetes and Hypertension 
Given the major impact of CKD, diabetes, and hypertension, and the large gap between proven 
effective therapies and their application in day-to-day care, it is critical that we develop better 
ways to implement effective therapies in the regular care of patients with multiple chronic 
conditions. The 2012 Kidney Disease: Improving Global Outcomes (KDIGO) guidelines state 
that "people with CKD are an ideal target for interventions aimed at reduction of morbidity, 
hospitalizations, mortality and costs."[5] 
  
We have recently implemented successfully a collaboratory primary care and nephrology care 
model for patients with CKD in a predominantly minority population using an novel technology 
platform that facilitates implementation of CKD care within the context of primary care practices 
and medical homes in the community. ICD-Pieces is a randomized, pragmatic clinical trial in 
four large healthcare systems in patients with coexistent CKD, diabetes and hypertension. Our 
hypothesis is that patients who receive care with a collaborative model of primary care-
subspecialty care enhanced by novel information technology (Pieces) and practice facilitators 
will have fewer all-cause hospitalizations, readmissions, disease-specific hospitalizations, ER 
visits, cardiovascular events and deaths than patients receiving standard medical care. We will 
also aim to develop a better understanding of risk predictors in patients with CKD, diabetes and 
Figure 2.2.3.2 

20 
 
hypertension to guide future recommendations of therapies that are tailored to individual 
patients.  
2.3 
Potential Risks and Benefits 
Potential risks in this study could relate to the interventions to be implemented and to data 
security. The control group will receive usual standard of care. The intervention group will 
receive interventions that are already accepted as best practices. None of the proposed 
interventions are experimental. The study team will capture important safety data as part of the 
study outcomes: hospitalizations, 30-day readmissions, ER visits, cardiovascular events and 
death. In addition to outcome data and to maximize patient safety the study team will capture, 
review monthly and report quarterly to the DSMB data on the following events in the intervention 
group: 
hypotension, 
syncope, 
hyperkalemia, 
electrolyte 
disturbances, 
angioedema, 
hypoglycemia, rhabdomyolysis, myositis, drug toxicity, pregnancy while treated with ACEI of 
ARB, acute kidney injury, reductions in eGFR 50% or higher initiation of dialysis. 
There are inherent risks associated with use of patient data the study and careful attention has 
been put in place to maximize data safety and protect patient privacy and confidentiality. 
Transmission of identifiable patient data will occur through secure FTP of HL7. Patient data will 
be stored in a secure database on the FISMA compliant VAZATA cloud. Access to the database 
will be password protected. Communication and files will be encrypted. Patient data will be de-
identified prior to submitting for analysis. The approach has been already used safely at 2 of the 
participating healthcare systems. At this time it is anticipated that the VA North Texas Health 
Care System will carry out study implementation within their firewall and that patient identified 
data from the VA will not be transferred to the cloud at least in early stages of the study. 
There are several important benefits that may result from this study. Implementation of best 
care practices for patients with CKD, diabetes and hypertension may improve very important 
clinical outcomes. Furthermore, successful implementation of this model can lead to more 
effective strategies to care for patients with other multiple chronic medical conditions and 
improve strategies for population health management. Finally, the research infrastructure 
developed for this study can be a model for future pragmatic trials.    
 
 
 
 
 
 
 
 
 
 
 

21 
 
3. 
Objectives 
The overall goal of the study Improving Chronic Disease Management with Pieces (ICD-Pieces) 
is to improve the care of patients who have the triad of chronic kidney disease, diabetes, and 
hypertension. The general hypothesis is that patients who receive care with a collaborative 
model of primary care-subspecialty care interventions enhanced by novel information 
technology and practice facilitators will have fewer disease-specific hospitalizations, 
readmissions, all-cause hospitalizations, cardiovascular events and deaths than patients 
receiving standard medical care. 
3.1 
Study Objectives 
3.1.1 Primary Objective 
The primary objective of the study is to test the hypothesis that a collaborative model of primary 
care enhanced by novel information technology and practice facilitators to leverage data from 
electronic health records will allow accurate identification of patients with the triad of CKD, 
diabetes and hypertension using objective and reproducible criteria, and provide clinician 
support for implementation of best practices of care, monitoring clinical measures, adjusting 
treatments and reduce 12-month hospitalization rates. In this study disease-specific 
hospitalizations for CKD, diabetes and hypertension include hospitalizations due to 
cardiovascular 
complications, 
congestive 
heart 
failure, 
volume 
overload, 
accelerated/malignant/uncontrolled hypertension, acute coronary syndromes, myocardial 
infarction, stroke, coronary/peripheral revascularization, limb ischemia/amputations, diabetes 
complications, uncontrolled diabetes, hypoglycemia, acute kidney injury, hyperkalemia, 
electrolyte disturbances, medication errors, drug toxicity, and infections. 
3.1.2 Secondary Objectives 
3.1.2.1 
The study will test if implementation of the collaborative model of primary care-subspecialty care 
interventions will reduce 30-day readmissions (for patients who are hospitalized), emergency 
room visits, cardiovascular events, deaths or disease-specific hospitalizations. In this study 
disease-specific hospitalizations for CKD, diabetes and hypertension include hospitalizations 
due 
to 
cardiovascular 
complications, 
congestive 
heart 
failure, 
volume 
overload, 
accelerated/malignant/uncontrolled hypertension, acute coronary syndromes, myocardial 
infarction, stroke, coronary/peripheral revascularization, limb ischemia/amputations, diabetes 
complications, uncontrolled diabetes, hypoglycemia, acute kidney injury, hyperkalemia, 
electrolyte disturbances, medication errors, drug toxicity, and infections. 
3.1.2.2 
Develop and validate predictive models for risks of hospitalizations, emergency room visits, 
cardio vascular events and deaths for all patients with coexistent CKD, diabetes and 
hypertension and predict risks of 30-day disease-specific readmissions for patients who are 
hospitalized. 
3.1.2.3 
Capture data (demographic, clinical, medications, laboratories, procedures) to phenotype 
patients with a triad of CKD, diabetes and hypertension. 
3.1.2.4 

22 
 
Obtain important safety data for patients with CKD, diabetes and hypertension including 
adverse safety events, acute kidney injury and progression of chronic kidney disease (even for 
patients not hospitalized). 
3.1.2.5 
Obtain information on resource utilization including not only hospitalizations but also all 
emergency room visits, outpatient visits and diagnostic and therapeutic procedures. 
3.1.2.6 
Patient Reported Outcomes (PROs) are increasingly recognized as key outcomes of clinical 
studies challenges of obtaining direct consent from study patients and obtaining data from the 
control group prevent us from complete capture of PRO at this stage. We do plan to submit a 
proposal to capture PROs for both intervention and control groups at completion of the study. 
The objective will be to evaluate the impact of the collaboratory model of care on patient related 
outcomes (PROs) including health-related quality of life, patient satisfaction, patient perspective 
on quality of their care and measures of patient perception of burden related to care of their 
CKD, diabetes and hypertension. 
3.1.2.7 
Evaluate the impact of the collaborative primary care-subspecialty care model on provider 
satisfaction with resources and ability to manage patients with coexistent CKD, diabetes and 
hypertension. 
3.2 
Study Outcome Measures 
3.2.1 Primary Outcome Measures 
The primary outcome of this trial is all cause hospitalizations for patients with a triad of CKD, 
diabetes and hypertension. Specifically, the outcome will be hospitalization rates at 12 months 
for study participants. We will include both regular hospitalizations as defined by CMS and 
observation status overnight (to avoid variations related to definition of inpatient 
status/hospitalization using the recent implementation of the “two midnight rule” CMS-1599-F). 
Hospitalizations can be ascertained objectively from the electronic healthcare record with 
assistance of electronic tools in each of the participating healthcare systems. If there is difficulty 
with adjudication of hospitalization, the steering committee will review and make a final 
recommendation. It is possible that some patients may be seen at a healthcare system other 
than one of the participating sites in this study. To maximize completeness of outcome data 
acquisition we will also track study patients with data from the Dallas Fort Worth Hospital 
Council that is a cooperative regional-sharing initiative that allows matching patients with any 
hospitalizations in any hospital in Dallas-Fort Worth. Patients in ProHealth in Connecticut are 
part of an Accountable Care Organization that receives regular and detailed reports from all 
hospitalizations for their members. Patients followed at the VA of North Texas may have 
hospitalizations outside the VA System and not tracked by the DFW Hospital Council. We will 
address this challenge in several ways. First, VA internal databases capture if payments have 
been initiated for outside hospitalizations. Second, we plan to include a standard question to the 
clinic workflow to ask patients about recent hospitalizations. Third, we have initiated discussions 
about the possibility of tracking hospitalizations of patients from the VA of North Texas via the 
DFW Hospital Council. 

23 
 
3.2.2 Secondary Outcome Measures 
Secondary outcomes will include 30-day all cause readmissions (for those patients who have an 
index hospitalization), emergency room visits, cardiovascular events and deaths, and disease-
specific hospitalizations for cardiovascular complications, congestive heart failure, volume 
overload, accelerated/malignant/uncontrolled hypertension, acute coronary syndromes, 
myocardial infarction, stroke, coronary/peripheral revascularization, limb ischemia/amputations, 
diabetes complications, uncontrolled diabetes, hypoglycemia, acute kidney injury, hyperkalemia, 
electrolyte disturbances, medication errors, drug toxicity, and infections. For those patients who 
are hospitalized all readmissions within 30 days of the index hospitalization will be captured 
from the electronic health records of the participating healthcare sites, Dallas Fort Worth 
Hospital Council or ACO database (for ProHealth, Connecticut) and VA of North Texas. 
Emergency room visits will be similarly captured from the electronic health records, DFW 
Hospital Council, ProHealth database and VA database.  
Cardiovascular events include congestive heart failure, acute coronary syndromes, myocardial 
infarction, coronary and peripheral revascularization, stroke and limb ischemia/amputation. 
Deaths from any cause will be captured. Deaths will be classified as cardiovascular or non-
cardiac related. Deaths will be captured from the electronic health records of the participating 
healthcare systems as well as from the Dallas Fort Worth Hospital Council and ACO database 
(for ProHealth, Connecticut), and VA EHR. We will also verify if enrolled patients who do not 
have an encounter in our systems within two year of study participation are classified as dead or 
alive using the Social Security Index.  
Other secondary outcomes captured in the study from the electronic health records will include 
descriptive patient characteristics for patients with a triad of CKD, diabetes and hypertension 
including demographic data, information of patient comorbidities clinical data, medications, 
laboratories, and procedures, and changes in renal function (eGFR) and episodes of acute 
kidney injury as well as safety/adverse events. We will use the wealth of information available in 
the EHR to advance disease-specific phenotyping of our patient population.[72] Resource 
utilization will also be measured capturing not only hospitalization but also clinic visits and 
procedures (diagnostic and therapeutic). 
As previously noted, Patient Reported Outcomes will not be captured initially but will be 
addressed as part of a future proposal in the study. Patient Reported Outcomes (PROs) are 
assessments directly reported by patients without interpretations by others and are increasingly 
recognized as key and valuable components of clinical trials[87]. A PRO survey derived for core 
domains and corresponding measures by the PCOR Net Reported Outcomes Common 
Measures Working Group (CMWG) will be used to measure health related quality of life and 
physical and emotional well-being of patients. Primary care practitioner reported outcomes and 
satisfaction with resources and ability to manage patients with coexistent CKD, diabetes and 
hypertension will be measured with a survey adapted from collaborative disease management 
initially developed for late-life depression in primary care[88]. 
 
 
 
 
 

24 
 
4. 
Study Design 
The study will employ a prospective stratified cluster randomization design. The stratum is each 
of the four large healthcare systems participating in the study. The unit of randomization will be 
primary care practices. In some healthcare systems (Parkland and North Texas VA) primary 
care practices are defined by an individual primary care practitioner caring for a unique group of 
patients with a permanently designated team of one RN and one medical assistant with no 
overlap with the practices of other primary care practitioners.   In other healthcare systems 
(THR and ProHealth) clinical practices are defined as group of patients cared by practitioners 
sharing personnel and workflows in the same physical location and randomized as a single unit.      
The cluster design of the study is best suited to detect important differences in outcomes 
between the intervention and control groups[8,55]. The decision to use primary care practices as 
a unit for randomization in the study is based on the ability to implement different models of care 
in the active intervention sites as compared to the control sites. The collaborative model of care 
which includes novel information technology, subject identification, facilitation of patient care, 
monitoring of outcomes and participation from facilitators can be most efficiently applied to the 
workflow of practices when they are fully randomized to active intervention. The cluster 
randomization design with practices receiving collaborative primary care-subspecialty care 
versus standard care also limits the risk of cross-contamination between intervention and 
control groups in the study. 
Primary care practices will be stratified by healthcare systems and randomly allocated to either 
intervention group or standard medical care group using a randomized permutation block within 
stratum. Based on the assignment of the practice where a patient receives medical care each 
patient will be assigned either to the intervention group or the standard medical care group. 
All eligible patients of practices who are randomized to the study will be included in the 
comparison of the two intervention groups regardless of intervention compliance (intention-to-
treat analysis) to investigate if patients in intervention group have significantly less all-cause 
hospitalizations than those in the standard medical care group. Evaluation will also be 
performed to determine treatment effects on disease-specific hospitalizations, ER visits, 
cardiovascular events and deaths.  
There will be two study groups: active intervention group randomized to the collaborative model 
of care facilitated by novel information technology and practice facilitators and standard/usual 
care group.  
The total number of patients to be studied is 10,991. (see study table 4) 

25 
 
  
 
Study enrollment will occur over a period of two years. The expected duration of subject 
participation is 12 months.  
The intervention in the active group is implementation of a collaborative model of care that 
facilitates delivering best care practices to patients who have coexistent CKD, type 2 diabetes 
and hypertension. The model uses a novel information technology platform and practice 
facilitators with the purpose of allowing for early identification of patients with objective criteria 
and to implement best practices of care, monitor important clinical measures, adjust treatments 
and achieve improved outcomes. The intervention will be delivered in the outpatient setting. 
The primary outcome measured during the trial is 12-month all-cause hospitalization rate for all 
the study participants. Secondary outcomes measured during the trial include 30-day disease-
specific readmissions (for all patients with an index hospitalization), emergency room visits, 
cardiovascular event, deaths and disease-specific hospitalizations. 
Other secondary outcomes measured in the study include adverse safety events, episodes of 
acute kidney injury and changes in estimated GFR. 
Data collection for assessment of study objectives will be mainly based on information 
technology tools to capture data from the electronic health record. Some data fields will require 
collection of data from Dallas Fort Worth Regional Hospital Council, ProHealth ACO databases, 
VA of North Texas and Social Security Death Files Index. 
There will be an interim analysis for efficacy of the intervention when 50% of the primary 
outcome data is available. This the consensus recommendation after review of the protocol and 
incorporating input from NIH, DSMB and OHRP. The study biostatisticians will review trends 
quarterly including patient volumes compared to goals from power calculations and inform study 
team and DSMB of any concerns based on trends of findings. 
A DSMB (Data Safety Monitoring Board) has been assembled by the NIDDK and will oversee 
study planning and implementation of the study. 
 
 
 
Table 4 

26 
 
 
 
 
 
 
 
 
5. 
Selection and Enrollment of Participants 
The total sample size of patients with the triad of CKD, type 2 diabetes and hypertension among 
participating sites in the four large healthcare systems in our study exceeds 28,118. The actual 
number of patients to be studied is 10,991.  
The study will include patients 18-85 years old with CKD, diabetes and hypertension. Men, 
women, and minorities will participate in the study. Children will not participate as this study is 
focused on adults with multiple chronic conditions. 
The outpatient population to be studied will be drawn from four large healthcare systems 
participating in the study. Parkland Health and Hospital System is the safety-net health system 
for Dallas County. Texas Health Resources is a large private, non-profit healthcare system 
network in North Texas. The North Texas Veterans Administration Healthcare System provides 
care for US veterans. ProHealth Physicians is Connecticut’s largest network of primary care 
physicians.  
5.1 
Subject Inclusion Criteria 
In order to participate in the study, patients should be 18-85 years of age and have coexistent 
CKD, type 2 diabetes and hypertension.  
5.1.1 CKD Inclusion Criteria (present at least ≥ 3 months apart) [12,5,86] 
1. There will be two or more eGFRs less than 60ml/minute or 
2. Two or more positive tests for albuminuria and/or proteinuria 
Albuminuria/proteinuria can be defined by quantitative criteria with albumin/creatinine ratio 
greater than 30, urine protein creatinine ratio greater than 200 or positive dipstick with protein 
detection (adjusted for urinary concentration/specific gravity) .[12,5,86] 
Figure 5.1.1 summarizes identification of CKD candidate pool 
5.1.2 Diabetes Inclusion Criteria [69,25] 
Only patients with type 2 diabetes will be enrolled in this study.  
1. Random blood glucose greater than 200mg/dL 
2. Hemoglobin A1C greater than 6.5% 
3. Use of hypoglycemic agents except Metformin or 
4. Type 2 diabetes included in problem list 
 
Figure 5.1.2 summarizes identification Diabetes candidate pool  

27 
 
 
5.1.3 Hypertension Inclusion Criteria [65] 
1. Systolic blood pressure greater than 140mmHg on two different occasions at least one 
week apart 
2. Diastolic blood pressure greater than 90 on two occasions at least more than one week 
apart 
3. Use of antihypertensive agents except thiazide diuretics  or 
4. Hypertension included in problem list 
 
Figure 5.1.3 summarizes identification Hypertension candidate pool 
 
 
 
 
 
 
Figure 5.1.1 Identification CKD Candidate Pool 
Figure 5.1.2 Identification Diabetes Candidate Pool 

28 
 
 
 
5.2 
Subject Exclusion Criteria 
All eligible patients from clinics randomized to the study will be included in the comparison of 
the two groups regardless of intervention compliance (intention-to-treat analysis).  
Exclusion criteria will be minimal in this pragmatic trial. The collaborative model of care will not 
be implemented in patients younger than 18 years or older than 85 years of age or patients who 
have CKD stage 5/ERSD. Primary care practitioners have the option of not implementing the 
intervention on any of their patients if they believe benefit to be minimal or risk too high due to 
patient comorbidities. Patients also have the option to opt-out from the facilitated collaborative 
model of care. 
5.3 
Strategies for Recruitment and Retention 
Prior to initiation of the study there will be information materials and education sessions 
provided to all participating sites. This will include both written material and electronic 
information. Resources from National Kidney Disease Education Program (NKDEP) will be 
provided to all practitioners.[82] There will also be special attention to selection of study 
champions at each participating site. In addition, there will be plans to visit most of the 
participating healthcare sites by members of the study team. These efforts will continue not only 
early in the study but throughout the study to promote study retention. 
Participating healthcare systems will be provided with advance notice of possible study 
participants prior to upcoming appointments.  
There will be review of actual enrollment of patients versus enrollment goals for every 
participating site. Reviews will occur monthly and reported quarterly. 
5.4 
Treatment Assignment Procedures 
This is a prospective stratified cluster randomized trial. Primary care practices will be stratified 
by healthcare system and randomly allocated to active intervention or control using standard 
Figure 5.1.3 Identification Hypertension Candidate Pool 

29 
 
medical care using a randomized permutation block within stratum. There will be no masking of 
sites randomized to active intervention. 
Practitioners and/or patients can choose to withdraw for the study at any time. They can choose 
not to follow the intervention model (any or all of the components or tools of care).  Patient can 
request their data be not included for analysis of outcomes. 
The study can be terminated by the DSMB for various reasons including concerns about 
adherence to protocols, study enrollment or patient safety. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6. 
Study Interventions 
6.1 
Healthcare System Collaboratory 
The pragmatic trial ICD Pieces is part of the NIH Collaboratory for Healthcare Systems 
Research with a special emphasis on multiple chronic conditions. The study will be conducted 
by a collaborative network of UT Southwestern and several other cores and four large 
healthcare systems that provide care to more than 2.5 million patients. (see figure 6.1) 

30 
 
 
 
The University of Texas Southwestern Medical Center is the central academic partner for this 
collaboratory and has a strong commitment to both patient care and research. Parkland Health 
and Hospital System is an integrated healthcare system that serves as a safety net hospital for 
the underserved and uninsured residents of Dallas County. Texas Health Resources is one of 
the largest non-profit health systems in the United States serving a population close to 1 million 
individuals in North Central Texas. The Veterans Administration Healthcare System is the 
largest integrated health care system in the United States and the largest provider of care for 
patients with CKD in the country. The North Texas VA Healthcare System serves more than 
100,000 patients in North Texas. Pro Health Physicians of Connecticut is one of the largest 
healthcare providers in Connecticut providing care to more than 250,000 adults every year 
across multiple practices.  
6.2 
Informatics Architecture 
Pieces will be deployed through the cloud to the participating healthcare systems. (see figure 
6.2.1) The Parkland Center for Clinical Innovation will provide specifications for data extraction 
using batch files and the data from each hospital will be mapped to relevant fields in the 
electronic health records systems. The Pieces system will access electronic health records for 
all patients who receive care at the participating sites for the study and to specifically detect 
patients with a triad of CKD, diabetes and hypertension and to detect eligible participants, 
facilitate management and monitor outcomes. Each healthcare system will have some 
differences in their electronic health records and data flow. This is being addressed with backup 
systems in place to access data and allow for safe and secure transmission. The North Texas 
VA will not be transmitting patient specific information via the cloud at least in the early stages 
of the trial. Data from each site will be programmed to be de-identified in the cloud and sent 
securely to the Biostatistics and Research Design Core at UT Southwestern. Please see figure 
6.2.2 for a model of information flow based on deployment of Pieces at participating sites of the 
Figure 6.1 

31 
 
healthcare systems in the study. Section 15 Data Handling and Record Keeping provides 
additional details on data capture and transmission 
 
 
 
 
 
 
 
 
Figure 6.2.1 

32 
 
 
 
 
6.3 
Practice Facilitator 
A key component of the collaborative model of care for the intervention group is the introduction 
of practice facilitators. In order to maximize the successful implementation of care in the 
intervention group the role training of the practice facilitator will be standardized across sites. 
We will use a curriculum developed following principles detailed in the Practice Facilitation 
Handbook from the Agency for Healthcare Research and Quality and especially adapted for 
ICD-PIECES.[89] We have two content experts that will lead these efforts. Dr. Andrew Narva 
from NIDDK has developed educational programs which have been successfully used by 
NKDEP to successfully train healthcare professionals to care for thousands of patients who 
have CKD, diabetes and hypertension. Dr. Chet Fox from SUNY directs a training program at 
SUNY for practice facilitators working in primary care practices.  
There will be an initial on-site course for practice facilitators led by Dr. Narva and Dr. Fox. After 
that initial meeting ICD-PIECES will continue to provide scheduled events by teleconference, 
written material and webinars to disseminate study relevant material to practice facilitators. All 
practice facilitators will also participate in regularly scheduled calls to review study progress. It is 
anticipated that these call will be at least weekly early in the study with additional calls and site 
visits to each site over the duration of the study. 
Practice facilitators may defer in professional qualifications among the different healthcare sites. 
Practice facilitators will have some clearly defined responsibilities including the following: 
• 
Receive initial and on-going training from the study team about the study, study protocol 
and proposed intervention 
• 
Ensure training of designated clinic staff on clinic level activities and expectations 
• 
Ensure necessary participation of designated clinic staff in CKD, diabetes, and 
hypertension care 
Figure 6.2.2 

33 
 
• 
Coordinates with study clinic staff to ensure the following activities: 
– 
List of eligible patients scheduled for clinic visit weekly are received through the 
EHR weekly 
– 
Site-specific enrollment protocol are activated for eligible patients 
– 
Smart/Order set in the EHR are triggered for enrolled patients 
– 
Holds weekly conference calls with clinic representatives to answer any 
questions and monitor enrollment number for each clinic 
• 
In-person visit to observe processes of enrollment and Smart/Order set trigger and other 
intervention activities 
• 
Provides regular update to the site PI and monthly update to the study team on 
enrollment number, performance of study clinic and on-going challenges 
 
6.4 
Selection of Study Sites and Subjects 
Pieces will screen electronic health records of participating healthcare systems to detect 
patients with a triad of CKD, diabetes and hypertension according to established inclusion 
criteria for the study. (see figure 6.3.1 Detection for CKD, Diabetes and Hypertension) 
The candidate cohort of potential sites will then be randomized to active intervention 
(collaborative care model enhanced by Pieces) or control group (standard of care) (see figure 
6.3.2 Detection CKD, Diabetes and Hypertension). 
Within clinics randomized to intervention, Pieces will confirm patients meet inclusion criteria. 
(see figure 6.3.3 Patient Identification Workflow).  
 
 
 
Figure 6.4.1 Detection for CKD, Diabetes and Hypertension 

34 
 
 
 
 
 
6.5 
Implementation Collaborative Model of Care 
The interventions selected for this pragmatic trial are supported by prior studies, clinical 
evidence and/or guidelines for treatment of CKD, diabetes and hypertension.[5,25,24,65,67-71,31,34,11] 
Specific interventions include maintaining blood pressure less than 140/90mmHg, use of 
angiotensin-converting enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARB), 
treatment with statins, aiming for hemoglobin A1C at the recommended target for coexisting 
Figure 6.4.2 Detection CKD, Diabetes and Hypertension 
Figure 6.4.3 Patient Identification Workflow  

35 
 
comorbidities, and avoiding nephrotoxic medications including non-steroidal anti-inflammatory 
drugs (NSAIDS). Other interventions will include education on CKD for both primary care 
providers and for patients using material prepared by NKDEP. Material on lifestyle modification 
and immunizations will also be included. (see figure 6.5.1) 
After a patient is enrolled, the primary care practitioner activates the CKD, diabetes and 
hypertension collaborative model of care. The primary care practitioner will also have the option 
to activate smart forms already constructed and available from our team (see appendix section) 
from the electronic heath record. Primary care practitioners will have the option to initiate 
protocols for CKD management, hypertension management, lipid and diabetes management. 
Protocols can be initiated via smartsets in the EHR. (see figures 6.5.2 Initiation of Protocol from 
SmartSets and Links to SmartSets). The specific and detailed protocols for hypertension 
management and diabetes/lipid management are included in appendices. 
 
 
 
 
 
 
Figure 6.5.1  

36 
 
 
6.6 
Maintenance of Provider and Facilitator Engagement  
Engagement of primary care providers at the time of study initiation and throughout the entire 
duration will be focus of special attention by the study team. Educational materials on CKD, 
diabetes and hypertension will be provided to practitioners and facilitators. Materials developed 
by NKDEP are readily available for distribution to study sites. Primary care providers will be 
offered the opportunity to participate in continuing education (CME) provided as part of their 
participation in ICD-PIECES. In addition, efforts are underway to determine if it is possible to 
link active participation in the study with Quality Initiatives (QI) that could fulfill maintenance of 
certification (MOC) requirements. 
As previously noted practice facilitators will be integrated into the study at all times including 
participation in the initial training curriculum, ongoing educational options and regularly 
scheduled study visits, conferences and reports. 
6.7 
Separation Control and Intervention Group 
Several steps will be in place to maintain separation between groups and to assess fidelity to 
assigned regimen. First and foremost the selection of clinics/geographic clusters as unit of 
randomization for the study should reduce the risk of cross-contamination by completely 
separating not only providers but also facilitators, nurses, clerks and other professionals in the 
intervention groups from those in control groups. 
We are aware that the healthcare systems in the study may at various times develop and bring 
for implementation competing initiatives and will review quarterly any new initiatives that the 
clinical leadership is planning across the healthcare systems. We will also work closely with the 
QI teams to be aware of any new initiatives that could overlap with ICD-PIECES. Our study 
team will also conduct quarterly reviews of any new national guidelines (from ASN, NKF, ADA) 
that could be relevant for the study population in ICD-PIECES. Any potential changes wil be 
discussed with Steering Committee and reported to DSMB. 
Figure 6.5.2 Initiation of Protocol from SmartSets 

37 
 
We are also planning to monitor the following as indirect measures of separation between 
implementation and control groups: 
• 
Activation of Smart sets 
• 
Referrals to educators (diabetes) 
• 
Selection of education modules (for providers and for patients) 
• 
Linkage to pharmacy (recommended medications) 
• 
Immunization rates 
A possible consequence of the facilitated protocol is increased utilization of health services and 
resources. We will monitor and compare utilization rates in control and intervention groups. 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

38 
 
7.  
Study Schedule  
7.1  
Screening 
Potential study participants from each healthcare system followed in primary care clinics 
randomized to the study will be screened for inclusion according to the pre-established criteria 
for CKD, diabetes and hypertension (see section 5.1) and as illustrated in figure 6.3.1 
There are no plans to obtain individual informed consent for patients screened or randomized in 
the study. (see section 14.3) Information about the study will be available to all patients in 
participating clinics and who have the triad of CKD, diabetes and hypertension. There will be an 
opt-out opportunity from the interventions or from use of information from any patient who 
requests their data not to be used for analysis.  
Screening of participants will occur at an initial stage to identify a candidate cohort of patients in 
various eligible clinics (see figure 6.3.2). Patients who do not fulfill required diagnostic criteria on 
initial review and require a separate determination to confirm any of the three diagnosis will be 
rescreened at the time of a future visit (figure 6.3.3)  
7.2 
Enrollment/Baseline 
Primary care practitioners will receive advanced notice (electronic and/or patient list) of eligible 
patients for the intervention group prior to their initial visit (visit 1). That visit will mark the first 
opportunity for initiation of the study by the primary care practitioner and to activate study 
interventions (see figure 6.4.1). The primary care practitioner will have the option of activating 
the study protocol and following recommendations using study tools/available smart forms. 
7.3 
Follow up Visits 
Measures of blood pressure, blood glucose, kidney function (creatinine, eGFR), lipid levels, 
urine protein/urine albumin as well as pre-specified safety events will be captured from 
electronic health records at the time of patient contacts with the healthcare system for 
scheduled or unexpected visits for patients. Information will be then directed to primary care 
teams per study protocol. 
Main study outcomes will be captured throughout the study for both intervention and control 
groups using the same tools in the electronic health record and access to DFW Regional 
Hospital Council, ProHealth database and VA electronic information systems. 
The study does not specify the frequency of visits for study participants. It is anticipated that 
patients with the triad of CKD, diabetes and hypertension will usually be seen at a minimum of 
every 3-6months in most participating clinics. 
7.4  
Final Study Visit 
 The final study visit will be the patient visit closest to 12 months after initiation of the study for 
that patient. As previously stated, visits will be for ongoing care and not mandated for 
study/research interventions. 
7.5  
Unscheduled Visits 
Acquisition of data/facilitation of care at the time of unscheduled visits will follow the schedule 
described in section 7.3. This is, however, an outpatient study. There will be capture of relevant 
data from hospitalizations (including major outcome measures) but study interventions and 
application of study tools will not be actively implemented during hospitalizations. 

39 
 
7.6  
Early Termination Visits 
Patients and/or primary care practitioners may decide at any time to discontinue participation in 
the facilitated collaborative model of care. Outcomes will still be captured for intention-to-treat 
analysis unless participants request their data/information not to be used. Table 7.1 summarizes 
the visits in the study. 
 
 
 
 
 
 
 
 
 
 
Table7.1 Schedule of Visits/Events 

40 
 
8. 
Study Procedures/Evaluations 
8.1  
Clinical Evaluations 
The study does not mandate interventions or evaluations considered experimental or outside of 
those recommended as part of optimal evidence-based care for patients with CKD, diabetes 
and hypertension.  
• 
Medical history and emphasis on problem list and diagnostic codes. 
• 
Medications including lists of all medications from electronic health record and 
medication reconciliation  
• 
Physical examination with special emphasis to blood pressure readings. 
• 
Education/counseling procedures. There will be emphasis on lifestyle modifications and 
confirmation of immunizations and interventions related to healthcare interventions. This 
will also be an opportunity to insure distribution of education on chronic kidney disease 
and diabetes. See information from NKDEP.[82] 
• 
Criteria for dose adjustment. Recommended goals for clinical measures and 
suggestions for recommendations are included in the specific protocols for CKD, 
hypertension, dyslipidemia, lipid management and diabetes management. (see 
appendix)] 
 
8.2 
Laboratory Evaluations 
• 
Serum chemistries including creatinine and electrolytes, GFR estimations (eGFR)   
• 
Glucose and hemoglobin A1C  
• 
Urine protein and urine albumin quantitative, urine creatinine and urine protein 
dipstick/with specific gravity 
• 
Microalbumin/creatinine ratio and protein/creatinine ratio in urine 
• 
 Lipids. 
 
8.3  
Special Measures 
• 
Health related quality of life and physical and emotional well-being from surveys to a 
small subset of participants. 
• 
Primary care practitioner satisfaction with model of care for coexistent CKD, diabetes 
and hypertension 
 
8.4  
Special Measures 
• 
All-cause hospitalizations 
• 
Disease-specific hospitalizations for CKD, diabetes and hypertension: cardiovascular 
complications, heart failure, volume overload, hypertension, acute coronary syndrome, 
myocardial 
infarction, 
coronary/peripheral 
revascularization, 
stroke, 
limb 
ischemia/amputations, acute kidney injury, hyperkalemia, electrolyte disturbances, 
uncontrolled diabetes, hypoglycemia, diabetes complications, medication errors and 
drug toxicity, infections 
• 
30-day disease-specific readmissions (for patients with an index hospitalization) 
• 
Emergency room visits  
• 
Cardiovascular events  
• 
Deaths 

41 
 
 
8.5 
Sub-Study 1 
 
Yield of Pharmacist Medication Reviews and Clinician Acceptance of Pharmacist 
Recommendations for Enrolled Patients at ProHealth 
 
Background 
ProHealth Physicians is an intervention site for a large, multisite, NIH-sponsored pragmatic clinical trial 
(“Improving Chronic Disease Management with PIECES”) which offers virtual pharmacist support for 
clinicians in the care of patients with the disease triad of chronic kidney disease (CKD), type 2 diabetes 
mellitus (DM), and hypertension (HTN). To date, our pharmacist has conducted over 300 medication 
reviews for these patients. Reviews assess: a) recommended practices in CKD (e.g. use of ACEi/ARB 
and statins), b) glycemic and blood pressure control, and, c) medication safety, which includes avoidance 
of nephrotoxic agents and renal dosing. The pharmacist makes patient-centered recommendations to 
clinicians to optimize and improve safety of regimens. Reviews and recommendations are entered as a 
Clinical Pharmacist Note in the electronic health record prior to primary care appointments. The 
pharmacist communicates electronically with clinicians for salient issues.  
 
Objectives  
The primary objectives of the proposed sub-study are to characterize a) medication-related problems 
(MRPs), and b) pharmacist recommendations among outpatients over 65 years old with chronic kidney 
disease, diabetes, and hypertension. A secondary objective is to evaluate the acceptance of virtual clinical 
pharmacist support in a large Primary Care Accountable Care Organization by evaluating clinician 
implementation of a pharmacist’s medication recommendations.  
 
Methods 
In this retrospective cohort study of 200 patients, medication-related problems and recommendations will 
be extracted from Clinical Pharmacist notes dated January 2017-May 2017 within the EHR.  
 
Medication-related-problems and pharmacist recommendations will be classified as follows: 
 
Category  
Medication-related problem  
Pharmacist 
recommendation 
I. 
Safety 
1. Contradindication 
2. High dose 
3. Adverse Drug Event (ADE)  
4. Drug interaction 
5. High risk medication  
(e.g. Beers List, anticholinergics) 
a. Discontinue  
b. Decrease dose 
c. Renal dose 
adjustment 
d. Lab test / 
monitoring 
 
II. 
Appropriateness 
1. Needs additional medication 
2. Unnecessary medication  
a. Start medication  
b. Discontinue  
III. 
Effectiveness  
1. Ineffective 
2. Low dose 
a. Increase dose 
b. Alternative 
medication 
 
This classification is based on a well-established taxonomy of MRPs. It was adapted to align with the 
focus of our medication reviews and patient population. Medication names and dosages will be collected 
to identify drug classes and specific medicines associated with MRPs.  
 

42 
 
Clinician acceptance of medication recommendations will be evaluated by review of medication profiles 
and Primary Care notes within one month after the timestamp of the Clinical Pharmacist Note.  
 
Variables for the primary objective include: number of medication reviews, baseline patient 
characteristics (age, gender, mean eGFR and A1c, number of medications), number of medication related 
problems, and classification of MRPs and associated medicines. Variables for the secondary objective 
include number of medication recommendations accepted by primary care clinicians and acceptance rate.  
 
Data Sources  
Data will be extracted from the electronic health record; no patients will be contacted. 
• 
Demographics – patient age, gender  
• 
Clinical Pharmacist notes – MRPs, recommendations 
• 
Primary Care progress notes –acknowledgment of pharmacist recommendations, documentation 
of medication changes  
• 
Medication profile – medication and dose, medication changes  
• 
Laboratory results – serum creatinine, eGFR, A1c, lipids, urine microalbumin, LFTs 
• 
Vitals – blood pressure, heart rate  
 
Impact  
This study is important to identify common medication-related problems among these vulnerable patients 
with the disease triad of chronic kidney disease, diabetes, and hypertension. Results have potential to 
improve decision support for clinicians at the point of prescribing. This work also highlights the 
feasibility and value of adding virtual Clinical Pharmacist support for primary care teams in a large 
primary care-based Accountable Care Organization.  
 
8.5 
Substudy 2: Testing Computable Definitions of Acute Kidney Injury (AKI) in the ICD-Pieces 
Clinical Trial 
Acute kidney injury (AKI) refers to an abrupt decrease in kidney function, resulting in the retention of 
waste products and in the dysregulation of electrolytes and extracellular volume1.   In the United 
States, about 300,000 people die from AKI each year, and the presence of AKI increases the length of 
a patient's hospital stay by 3.5 days.2   Furthermore, it is recognized that there is an association 
between AKI and chronic kidney disease (CKD) and end-stage renal disease (ESRD) .3 There is evidence 
of marked variation in the management of AKI, which is, to a large extent, due to a lack of awareness 
and an absence of standards for prevention, early recognition, and intervention. Emerging data point 
to an urgent need to change the treatment paradigm of CKD and other AKI risk factors by educating 
practitioners on how to prevent AKI (including the treatment of CKD), and modify its course with 
modalities and treatments that can improve outcomes. 
 
Defined criteria to document AKI for research criteria (KDIGO, RIFLE,AKIN) have been used in research 
studies and compared to  billing diagnostic codes for identification of AKI. In two recent studies the 
use of billing codes to identify AKI had low sensitivity compared with current KDIGO consensus 
definition or modified KDIGO definition (not counting urine output decrease as a criterion). 4,5   In one 
study of 
~34,000 hospitalized patients only 17.2% (95% CI 13.2%-21.2%) of AKI cases that were identified 
using serum creatinine were also identified using AKI billing codes.4   In a more recent report using 

43 
 
electronic health records, the ICD-10 code corresponding to AKI (N17) was recorded in 30% of the 
cases documented by a laboratory based approach to find Hospital Associated-AKI identified in a 
reported study.5    Furthermore, in a mini-sentinel pilot project sponsored by the US Food and Drug 
Administration (FDA) to improve  electronic safety surveillance, the positive predictive values of ICD-
9 diagnoses in identifying AKI ranged from 48%-84% at best.6 
Improved standardized approaches to detect AKI in clinical trial adverse event reporting would 
improve safety monitoring and build the evidence base for defining subtypes of AKI in current 
studies and for future biomarker and precision medicine initiatives. We propose an additional 
substudy of the incidence of laboratory-defined AKI compared to administrative coding as an 
extension research question for the current ICD-Pieces pragmatic clinical trial. The ICD-Pieces study 
is focused mostly on capturing outpatient events. It is notable that 1/3 of AKI cases in a large 
epidemiological study were community acquired.7 
Specific Aim 1: 
Test the performance of laboratory based criteria for AKI compared to coded ICD-10 documentation of 
AKI in the outcomes data set of the ICD Pieces trial -UH3DK104655 
As the ICD-Pieces trial will be following AKI as a subset of inpatient hospitalizations captured as part of 
the primary endpoint of the one-year unplanned hospitalization rate, a natural data set will be 
available to test for concordance of the laboratory only- based definition of AKI compared to ICD- 10 
code documentation within a well- defined cohort with established baseline eGFR. AKI will be 
defined using KDIGO laboratory criteria.   Although routine collection of information of urine output is 
not part of the trial,  laboratory based data will be available along with the hospitalization data will be 
available for a section of the clinical sites including the North Texas VA hospital system, Parkland 
Health & Hospital System, and Texas Health Physicians Group of Texas Health Resources. This would 
demonstrate the feasibility of improved monitoring for adverse events, specifically AKI, in a large 
cluster randomized pragmatic clinical trial of patients with chronic kidney disease. 
Specific Aim 2: 
Document modern mappings of AKI based on the KDIGO criteria to current LOINC and SNOMED-CT 
Ontologies 
In order to promulgate a standard modern definition of AKI based on computable laboratory values 
and related medical concepts and to allow exploration of concordance of alternate methods of 
detection of AKI based on Natural Language Processing, the investigators propose a mapping exercise 
to the available modern medical ontologies. This definition can be circulated at both the NKDEP 
Health Information Technology Working Group and through the NIH Collaboratory Living Textbook as 
well as other publications. To the investigators’ knowledge, no such modern mapping has been 
published, and exhaustive mapping of the SNOMED CT ontology is unlikely to happen as part of 
routine clinical workflows. This resource map would allow exploration of documentation of clinical 
findings and concerns in routine clinical notes as an alternative method for surveillance of AKI as a 
clinical event. 

44 
 
 
References: 
1. Palevsky PM, Liu KD, Brophy PD, et al. KDOQI US Commentary on the 2012 KDIGO Clinical 
Practice for Acute Kidney Injury. Am J Kidney Dis. 2013 May;61(5):649-72. 
2. Lewington AJ, Cerda J, Mehta RL. Raising awareness of acute kidney injury: a global perspective of 
a silent killer. Kidney Int 2013;84:457-467. 
3. Coca SG, Singanamala S, Parikh CR. Chronic kidney disease after acute kidney injury: a 
systematic review and meta-analysis. Kidney Int 2012;81:442-448. 
4. Grams ME, Waikar SS, MacMahon B, et al. Performance and limitations of administrative data in 
the identification of AK.  Clin J Am Soc Nephrol 2014, 9:682-9. 
5. Jannot AS, Burgun A, Thervet E, Pallet N.  The diagnosis-wide landscape of hospital- acquired 
AKI. Clin J Am Soc Nephrol. 2017 Jun 7;12(6):874-884. 
6. Patel UD, Hardy NC, Liu KD, et al. Validation of acute kidney injury cases in the mini-
sentinel distributed database. US Food and Drug Administration.   Sept 2013 
7. Hackworth LA, Wen X, Clermont G, et al. Hospital vs. community-acquired acute kidney injury 
in the critically ill: differences in epidemiology. J Am Soc Nephrol 2009; 20:115A. 
 
 
8.7  
Substudy 3: Understanding Decisions to Opt-Out of Pragmatic Clinical Trials 
Jeremy Sugarman, MD, MPH, MA 
Kevin Weinfurt, PhD 
Miguel Vazquez, MD 
 
1. 
Abstract 
Patients may sometimes be given the option to opt-out of pragmatic clinical research, 
which may mean not receiving a particular intervention based upon a study protocol or 
not having their data used for analyses. Yet, there is minimal information available about 
the reasons why patients opt-out, which may prove to very useful in assessing the ethical, 
scientific, and practical aspects of pragmatic clinical trials. This project involves pilot 
testing a short survey instrument among patients who opt-out of ICD-PIECES, a 
pragmatic clinical trial currently being fielded to develop a preliminary understanding of 
reasons for opting-out as well as assemble a cohort of patients who may be interviewed 
in a possible qualitative interview study in the future. 
 
2. 
Objectives 
a. To pilot test a short survey instrument regarding reasons for opting-out of 
pragmatic clinical trials. 
b. To develop a preliminary understanding of reasons for opting-out of ICD-
PIECES, a pragmatic clinical trial currently enrolling participants. 
c. To obtain permission from patients who opt-out of ICD-PIECES for a 
possible in-depth interview regarding decisions related to opting-out that may 
be designed and conducted in the future.  
 
3. 
Background  

45 
 
Pragmatic clinical trials and comparative effectiveness research are becoming increasing 
commonplace as a means of generating real-world information to guide medical decision 
making among patients, clinicians, payers and other stakeholders. This type of research 
typically poses minimal incremental risks to those involved and may be done without an 
explicit informed consent process. However, in such trials patients may be given the 
option to opt-out of the research, which may mean not receiving a particular intervention 
based upon a study protocol or not having their data used for analyses. Yet, there is 
minimal information available about the reasons why patients opt-out of pragmatic 
research, which may prove to very useful in assessing the ethical, scientific, and practical 
aspects of pragmatic clinical trials. Accordingly, the proposed research will pilot test a 
short survey instrument among patients who opt-out of ICD-PIECES, a pragmatic 
clinical trial currently being fielded. The estimated opt-out rate in ICD-PIECES is 
currently 1.5% of those approached.  
 
4. 
Study Procedures 
a. Study design. Patients who opt-out of ICD-PIECES will be approached by the ICD-
PIECES study coordinator immediately following their decision to opt-out and ask 
them if they would be willing to answer some questions about their decision. 
Answering these questions will be considered to indicate consent. The information 
will be captured on a form that will include only basic demographic and site 
information unless the patient voluntarily provides permission to be contacted. 
Primary data will be retained by the ICD-PIECES study team. Aggregate information 
will be provided without any patient identifiers to the study team at the NIH 
Collaboratory Coordinating Center (Drs. Sugarman and Weinfurt).  
b. Study duration and number of study visits. The study will take 5-15 minutes at a 
single encounter.  
 
5. 
Inclusion/Exclusion Criteria. 
a. Adult, competent patients who opt-out of ICD-PIECES 
b. Willing and able to answer questions related to their decision to opt-out 
c. Able to converse in English 
 
6. 
Sample Size: 10-15 patients 
 
7. 
Study Statistics 
 
Data will be analyzed using standard descriptive statistics. We will endeavor to continue 
to enroll patients who opt-out of ICD-PIECES until enrollment for that study ceases.  
 
 
8. 
Risks 
 
There are no anticipated physical, financial or social risks for participating. Patients may 
feel uncomfortable discussing their reasons for opting-out. If this occurs, the survey can 
be stopped. If any unanticipated problems occur, the PI will be notified immediately and 
intervene as appropriate.  

46 
 
 
 
9. 
Benefits 
 
There are no anticipated benefits to the participants. The information learned in this study 
should help assess and perhaps improve future pragmatic clinical trials and those who 
might participate in them.  
 
 
10. 
Payment and Remuneration 
 
None. 
 
 
 
9 
Assessment of Safety 
9.1 
Specification of Safety Parameters 
Adverse safety events will be captured and monitored as part of the study. The primary 
outcome of this trial is all-cause hospitalizations for patients with a triad of CKD, diabetes and 
hypertension and all unplanned hospitalizations will be captured. The main secondary outcomes 
that will be captured in the study also include safety events including 30-day all cause 
readmissions (for those patients who have an index hospitalization), emergency room visits, 
cardiovascular events, deaths, and disease-specific hospitalizations. In this study disease-
specific hospitalizations include all those hospitalizations for cardiovascular complications, 
congestive heart failure, volume overload, hypertension complications, acute coronary 
syndrome, myocardial infarction, coronary/peripheral revascularization, stroke, amputation/limb 
ischemia, uncontrolled diabetes, hypoglycemia, diabetes complications, acute kidney injury, 
hyperkalemia, electrolyte disturbances, medication errors, drug toxicity, and infections. 
In this study the control group will receive standard of care. The intervention group will receive 
interventions that are already accepted as best practices. Primary care providers will make 
ultimate decisions regarding implementation of any of the interventions for both groups. In 
addition to the study outcome measures detailed above the following events will be captured 
and reported (whether they lead to hospitalizations or not) as they could be related to potential 
study interventions: hypotension, syncope, hyperkalemia, electrolyte disturbances, angioedema, 
hypoglycemia, rhabdomyolysis, myositis, drug toxicity, pregnancy while treated with ACEI or 
ARB, acute kidney injury, reductions in eGFR 50% or higher, or initiation of dialysis. 
 The study will monitor for any malfunctions on the decision support software system and SFTP 
used for data transmission to and from electronic health records of the study sites for Parkland, 
THR, ProHealth and VA of North Texas. There will also be monitoring for adherence to Manual 
of Procedure interventions including identification and enrollment of eligible patients, activation 
of study protocols and recommended follow up.  

47 
 
9.2 
Methods and Timing for Assessing, Recording and Analyzing Safety Parameters 
9.2.1 Adverse Events 
The study outcomes and adverse/safety events detailed in Section 9.1 will be captured directly 
from the electronic health records of the participating healthcare systems, DFW Hospital 
Council and internal databases and event tracking forms from ProHealth and VA of North Texas 
as previously described. In this pragmatic trial capture of unsolicited events can occur in most 
instances from the electronic health records and databases. As noted above there will be 
confirmation for solicited adverse event including hospitalizations for patients from the VA of 
North Texas who may be seen in other institutions in Dallas/Fort Worth. 
Adverse events will be collected throughout the entire participation of subjects in the study (12 
months from enrollment to completion of the study participations for each subject). The study 
coordinating team will review adverse events to determine relatedness to study interventions 
and to grade severity as needed. 
Adverse events will be classified as severe or mild/moderate. For the purposes of this study 
severe adverse events will include those leading to death, hospitalizations, or permanent 
disability/incapacity. Other safety events will be classified as mild/moderate. As the study relies 
heavily on event capture via the electronic health records it may not be possible in all instances 
to accurately differentiate between mild and/or moderate severity within the context of this 
pragmatic trial. 
The study team will make determinations on whether serious adverse events are possibly/likely 
related to study interventions.  
9.2.2 Expected Adverse Reactions  
A list of possible safety events detailed in Section 9.1 includes most of the safety signals that 
could be associated with the study interventions. The study group will regularly review events 
capture to determine relationship to study interventions. In order to maximize patient safety we 
do plan to conduct a manual review of the initial 100 subjects enrolled in the study from each 
healthcare site. We will also review a minimum of 10 subjects from each participating healthcare 
system every quarter to monitor for adverse events and relatedness to study interventions. 
9.2.3 Serious Adverse Events 
Hospitalizations and deaths are serious events in this study. It should be noted that these 
adverse events classified as serious are already primary and secondary outcomes for this study 
(hospitalizations and deaths). Other serious events are those leading to incapacity and/or 
permanent disability and will also be captured as noted above. 
9.2.4 Unanticipated Problems 
The study team will remain vigilant for unanticipated problems. Trends of increasing frequency 
or rate of safety events in the intervention group will prompt review of individual cases by the 
study team and reporting to the oversight group (DSMB). 
Other possible unanticipated problems including malfunctioning of the decision support system 
or non-adherence to recommended clinic protocols as well as possible mitigations are 
discussed in Section 13 Quality Control and Quality Assurance. 

48 
 
9.2.5 Procedures to be Followed in the Event of Abnormal Laboratory Test Values or 
Abnormal Clinical Findings 
All participating subjects in the study including in both control group and intervention group will 
be under the direct care of primary care providers who will make final decisions on all 
interventions and direct patient care. Abnormal laboratory findings or clinical findings will be 
brought to the attention of the primary care provider according to the existing protocols in each 
healthcare system for appropriate clinical response.  
9.3 
Reporting Procedures 
The study group will collect adverse events from all the participating healthcare systems and 
review at least monthly. There will be reports prepared for submission to the DSMB quarterly. 
It should be noted that there will be some delay on the acquisition of data regarding some 
adverse events/outcomes. Hospitalizations which are not captured via the electronic health 
record but require reporting from the DFW Hospital Council may not be known by the study 
team for several months. Furthermore, information on other serious adverse events such as 
deaths may not be available to the study team until after review of the Social Security Death 
files. 
9.4 
Type and Duration of Follow-up of Subjects after Adverse Events 
All study subjects in the intervention and control group will be followed according to best 
practices by their primary care providers in following established protocols in each healthcare 
system. As part of participation in the study, the intervention group will continue to be monitored 
by PIECES and practice facilitators during the 12 months of their participation in the study. 
9.5 
Halting Rules 
The study can be halted at any time by the DSMB recommendations if there are concerns about 
patient safety, lack of enrollment or poor adherence to study plans and poor adherence to 
protocol.  
9.6 
Safety Oversight (DSMB) 
The study has approval from the IRB at UT Southwestern which will oversee the study for 
Parkland Health and Hospital Systems and ProHealth of Connecticut. There is also IRB 
approval from the  from the Texas Health Resources IRB and the North Texas VA IRB. NIDDK 
has constituted a DSMB that will review and approve final study protocol, address any major 
changes in protocol and have ultimate authority to halt the study according to the concerns 
detailed in Section 9.5. 
 
 
 
 
 
 
 

49 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
10. 
Clinical Monitoring 
10.1 
Site Monitoring Plan 
There will be several levels of monitoring in the study. Members of the study team will monitor 
the four healthcare systems to ensure compliance with human subject protection, study 
procedures, and interventions. There will be an initial site visit for each healthcare system for 
training and assurance of compliance. Practice facilitators at each site will report patient 
enrollment and intervention for eligible patients every three months. Pieces will monitor 
interventions provided to eligible patients and progress towards achievement of enrollment 
targets and implementation of interventions. In addition to capture of events from the EHR, the 
study team will review the records involving enrollment and adherence to protocol outcomes 
and safety events for the first 100 patients enrolled from each healthcare system as well as a 
minimum of 10 patients every 3 months. There will also be similar review of the first 10 patients 
enrolled from every participating study site (cluster) in each healthcare system. We will also 
verify the functionality of the clinical decision support system by reviewing a sample of patients 
enrolled in the study from each site every quarter.  
 
 
 
 
 
 

50 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
11. 
Statistical Considerations 
11.1  Study Hypothesis:  
It is hypothesized that the PIECES-based interventions can reduce one-year (12 months) 
unplanned all-cause hospitalizations for patients with a triad of CKD, diabetes and hypertension.  
Study Design:  
A prospective stratified cluster randomization design will be employed. Patients are clustered by 
clinics, which are stratified by healthcare systems, and randomly allocated to either the 
PIECES-based intervention or a control (standard medical care) group using a randomized 
permutation block within each stratum. Based on assignment of his or her clinic, each patient 
will be assigned either to the Pieces group or a standard medical care group. Stratified 
randomization log will be created using SAS PROC PLAN with variable block sizes. 
11.2  Sample size consideration:  
We determined sample size based on the comparison of one-year unplanned all-cause 
hospitalization rates between the control and PIECES-based intervention groups.  
The sample size formula developed by Donner [64] for stratified randomized trials was 
employed. From preliminary data we observe that the rate of unplanned all-cause 
hospitalization during the 1-year follow-up period is 14% across all four large health care 
systems in standard medical care group. We expect that the hospitalization rate in PIECES 
group will be 3% lower than that in the standard medical care group. Electronic health records 
show that the number of patients with coexistent CKD, hypertension and diabetes are 4,419, 
4,738, 4,175 and 1,093 in Parkland, Texas Health Resources, ProHealth, and VA North Texas, 
respectively. The numbers of clinics are 25, 40, 50, and 9 in Parkland, Texas Health Resources, 
ProHealth, and VA North Texas, respectively. From a preliminary dataset extracted from 

51 
 
Parkland Healthcare System and THR Healthcare System, we obtained an intracluster 
correlation coefficient (ICC) of 0.015.  
If we assumed ICC = 0.015 to detect a 3% difference in the rate of unplanned all-cause 
hospitalization, a total of 10,991 patients are needed to achieve 80% power at a two-sided 5% 
significance level. We would need to enroll 3,367, 3,610, 3,181, and 833 patients from Parkland, 
THR, ProHealth, and VA North Texas, respectively.  Here, 10,991 patients are 76.2% of 14,425 
patients from the 4 healthcare systems participating in the study. Waiver of consent has been 
obtained from all IRBs overseeing the study and no informed consent will be obtained from 
patients.  There is an opt-out option available for patients in the implementation and in the 
control groups and based on the nature of the interventions a small number of opt-out requests 
is expected.  Additional practice sites/ clinics will be available at 3 of the 4 participating health 
care systems as enrollment sites for additional patients if required in the future.  
  
11.3  Statistical Analysis Plan:  
Standard descriptive analysis will be performed where we summarize continuous variables by 
mean and standard deviation, and categorical variables by count and percentage. The one-year 
unplanned all-cause hospitalization rates will be compared using the generalized Mantel-
Haenszel procedure as presented by Donner [64], which is suitably adjusted for clustering. 
Furthermore, we will use generalized linear mixed model (GLMM) to examine if there is a 
significant difference in hospitalization rates between two intervention groups after controlling 
for potential confounding patient, clinician and clinic factors. The mixed model includes clinic 
random effects to account for within-cluster correlation. Univariate mixed models will be 
employed to assess the marginal association between the outcome and individual covariates. 
The final multivariate model will include covariates identified by the stepwise variable selection 
procedure as well as those considered to be clinically important a priori. Similar analysis will be 
performed to compare the rates of disease-specific hospitalization. As secondary analyses, the 
Kaplan-Meier plots will be generated to explore the difference in time to hospitalization between 
the two arms. Cox models with frailty will be implemented to evaluate the treatment effect on the 
event times of hospitalization, CV, and death events, controlling for confounding factors. 
Random effects for clinics are also included. Similar strategy of univariate and stepwise variable 
selection procedure in mixed model will be implemented to the Cox models with frailty. 
Statistical significance will be reported for p-value<0.05. All statistical analyses are performed 
using statistical software SAS 9.4 (SAS Institute, NC, Gary). 
To construct and evaluate predictive models for unplanned all-cause hospitalizations, disease-
specific hospitalizations, 30-day readmissions, cardiovascular events and deaths, the total 
cohort will be randomly separated into derivation and validation datasets (2/3 and 1/3 sample, 
respectively). Based on the derivation set, we will select independent variables with p-
value<0.20 from univariate analysis as candidate variables for multivariate analysis. We will 
explore possible contributions to models from interactions of independent variables and from 
splines, transformations, and recursive partitioning for continuous variables. We will use the 
stepwise variable selection procedure on generalized linear mixed model (GLMM) to identify 
variables that are significantly associated with outcome variables such as hospitalization, 30 
day readmissions, cardiovascular events and deaths. The goodness of fit criteria and the Bayes 
Information Criterion (BIC) will be used for model selection.  
 
The resulting model will be externally validated based on the validation dataset. We will 
evaluate calibration through the Hosmer-Lemeshow test; we will measure discrimination by the 

52 
 
c-statistic, the area under the curve (AUC) for the receiver operating characteristic (ROC) curve 
and by the range of predicted risks. We will divide the patients into five groups based on the 
quintiles of their predicted risk by the model. We will compare the true event rate among the 
quintile groups to examine how well the predictive model separate patients at different levels of 
risk. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
12.  
Source Documents and Access to Source Data/Documents 
The main source of data will be through Pieces extraction of patient data from the EHRs of all 
study sites. Only the PI and study team members who are HIPAA certified will have access to 
this data. The data will be de-identified before transfer to the statistical team for analysis. Other 
sources of data is readmission data from the DFW Hospital Council, Pro Health databases and 
VA of North Texas databases/information. 
 
 
 
 
 
 
 
 

53 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
13. 
Quality Control and Quality Assurance 
 
13.1  Development of MOP and Training 
The main thrust of our quality control and assurance program is to prepare a comprehensive 
manual of operation with sections specific to each study site and train study site staff in its 
operations. Study site personnel to be trained are the site PI, the Practice Facilitator and 
Primary Care Providers at each clinic. The site PI will provide oversight to the conduct of the 
study at their institution, responsible for recruitment of appropriate staff to serve as Practice 
Facilitator and engaging PCPs in the clinics randomized to study group. The Practice Facilitator 
will receive the list of eligible patients along with their PCPs to ensure that the patients are 
enrolled into the study and provided recommended care through triggering of the Smart Set and 
following protocol. The PCPs will be primarily responsible for providing recommended care to 
their eligible patients and determine the level of care for each patient. Training will provided to 
these staff by members in person meetings, web-based training and the manual of operation 
that outlines their expected roles, clinical workflow, opt-out consent and patient follow up. A 
refresher training course will be provided every three months to ensure compliance with the 
manual of operations. 
13.2 
 Site Visit  
We will develop a timetable to visit the clinics in the study group at least one time per year to 
observe the clinical workflow and adherence to the MOP. Other visits may occur if requested by 
clinic staff or if there are concerns with study performance 

54 
 
13.3 
Pieces Functionality 
We will assure the functionality of our decision support systems software by verifying with each 
site a sample of patients identified with CKD, Diabetes and Hypertension at the beginning of the 
implementation period and quarterly thereafter. 
13.4 
Monitoring Data Quality 
The quality of data received from all sites will be reviewed and verified at beginning of the 
implementation phase and monthly thereafter to ensure problems are identified and corrected in 
a timely manner 
13.5 
Routine Progress Reports 
We will prepare a monthly progress for each site to include the following: 
1. Screening, Recruitment, enrollment and retention  
2. Protocol compliance 
3. Data quality reports - describe missing, erroneous, and inconsistent data to ensure 
protocol is followed and deviations are tracked 
4. Site monitoring  results 
 
 
 
 
 
 
14. 
Ethics/Protection of Human Subjects 
14.1 
Ethical Standards 
This study will follow the highest level of ethical standards. All study staff will be required to train 
and certify in human subject protection 
14.2 
Institutional Review Board 
The final study protocol will be submitted to UTSW, THR and VA North Texas IRBs for review 
and approval. Patient recruitment will not occur until the study has been approved by the 
various IRB. UTSW IRB will serve as the review body for Parkland and ProHealth of 
Connecticut HCS. Protocol amendments and changes will be submitted to all IRBs and 
approval must be received prior to implementation. 
14.3 
Informed Consent Process 
This pragmatic clinical trial will offer an opt-out option for any eligible patients in either control or 
intervention groups. There will be no formal informed consent obtained from each individual 
patient. The rationale for waiver of informed consent has been carefully reviewed and presented 
to the IRBs overseeing the study as well as to the federal agencies overseeing the study. The 
research involves minimal risk to subjects. Both groups including control (standard care group) 
and intervention will have access to recommended best therapies for treatment of CKD, 
diabetes and hypertension. In both groups the primary care provider will have the final say on 
what interventions are implemented for the care of CKD, diabetes and hypertension for their 
individual patients. The waiver of informed consent will not adversely affect the rights and 
welfare of participating subjects. This pragmatic trial cannot be performed at all participating 

55 
 
healthcare systems and practice sites without the waiver. As there will be several thousand 
patients enrolled it would not be logistically possible for coordinators to address the geographic 
and time limitations to obtain consent from such a large number of participants as to make the 
trial possible. The risks to patient privacy and data security will be carefully addressed with 
multiple safeguards as detailed in Section 15 Data Management and Responsibilities. Study 
subjects will be notified of findings at completion of the study. 
As previously mentioned, patients who are in clinics randomized to either control group or 
intervention group will have an option to opt-out of the study and use of any of their health 
information. The goal is to give all potential patients the opportunity to know that the study will 
be carried in their healthcare system and to have the opportunity to decide if they want to 
participate and if they will allow for their data to be used in the study. Participants will be made 
aware of the study through various forms including posters and handouts and other media in 
clinics describing that the study aims to improve care of patients with CKD, diabetes and 
hypertension by assisting primary care providers to implement the best practices for their care. 
There will be reference to a phone number and a link to the collaboratory website specific to 
ICD-PIECES so that patients can obtain as much detail as they need to make an informed 
decision. If a patient does use the opt-out mechanism, the research team will document and 
track the instances for those patients to remain outside of the study interventions or use of any 
of their specific data.   
14.4 
Exclusion of Women, Minorities, and Children (Special Populations) 
This study will be conducted in all adults 18-85 years attending the outpatient clinics of the 
participating Health Care Systems 
14.5 
Subject Confidentiality 
All patient data will be maintained in a secure location. Study data to be obtained will be part of 
standard information available in the EHR. Access to study data in the EHR, PIECES and study 
databases for data collection and analysis at UTSW and PHHS will be limited to study 
personnel and password protected. 
14.6 
Study Discontinuation 
Study participation can be discontinued at any time by patients or their PCPs. 
14.7 
Future Use of Study Specimens 
There will be no study specimens collected for this study. Data will be collected and stored 
securely. De-identified data will be available for future use as per NIH policies.  
 
 
 
 
 
 
 
 

56 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
15. 
Data Handling and Record Keeping 
Informatics Section 
15.1 Data Collection 
Data capture will be aggregated on a central cloud based (Software-as-a Service) SaaS 
platform hosting the Pieces TM software. Flat file transfer via SFTP will occur and HL7 based 
data integration will occur with a site specific selection of the best method to transmit data 
centrally. In the instance that external approval of data transfer cannot occur, a process of 
locally matching patient selection criteria on software server with a local firewall will be 
implemented with a process to allow deidentified data to the SaaS server will be implemented. 
Access to the central server will be restricted using Secure VPN tunnel with two factor 
authorization. The Secure Cloud Hosting Environment will be FISMA (Federal Information 
Security Management Act of 2002) compliant. 
Hospitalization and Death Outcome Data: 
Data requests by the National Association for Public Health Statistics and Information Systems 
(NAPHSIS) Death index information from the CDC will be obtained after completion of IRB 
submission for approval and then performed at the termination of the study a single time to 
obtain death outcomes after enrollment and follow up of planned time period for augmentation 
of EHR stored death date and death status of inpatient discharge to ascertain mortality 
outcomes. 
Master Patient Index matching to a shared Dallas Fort Worth Hospital Council data set will 
occur for the THR and PHHS site using the REMPI match system to obtain inpatient 
hospitalization events throughout the Dallas-Fort Worth area. Patient outcomes within the 
outside of the Veterans Affairs System will occur with an additional research effort to assess the 

57 
 
feasibility of patient patching between the Veterans Affairs patient index and the DFWHC data 
to provide additional hospitalization events for veterans outside the VHANTX system. 
15.2  Data Management and Reports 
Encrypted computers stored in physical secured premise. Patient cohort selection criteria will be 
preserved in PheKB platform and publically available after the completion of the grant 
(https://phekb.org/). Snapshots of the data elements constituting candidate identification and 
confirmation will be stored for all patients meeting the candidate definition. 
Formats RDBMS using MySQL or Sql Server environment configured to support the data model 
with access controls overseen by a PCCI Security officer. Deidentified final registry data sets 
with Safe harbor HIPAA data elements removed will be provided to the final statistics team 
performing predictive modeling for Aim 3 and final analysis of the planned analysis. 
Data aggregation by assigned data analyst from the PCCI under terms of executed Business 
Associates Agreements between the parties to the grant. Analytic file extracts from the RDBMS 
will be exported as .csv or tab delimited txt files for additional analysis. Quality Assurance 
reports will evaluate the distribution and frequency of mapped data elements and validation of 
the final mapping of the Pieces TM data model will be confirmed with the site coordinators. 
Periodic reporting on the number of candidate patients per site will be reviewed at least 
quarterly to monitor for target patient identification consistent with expected patient volumes 
from power calculations and available on request to the Data Safety Monitoring Board. 
Server Data will be backed up on mirrored virtual machines within a partitioned cloud server 
environment with disaster recovery. RDMBS scripts, stored procedures and Pieces TM platform 
executables related will be versioned control using Subversion as will data exports to the 
analytic teams. 
DATA VALIDATION: 
Annual review of value sets update form the VSAC and HEDIS will be performed to test for the 
impact of newly released medications or laboratory mappings. Unexpected drop offs in patient 
identification will also prompt analyst review of site data. Data model and queries will be stored 
in version control software. Data mappings for the patient selection criteria will undergo dual 
analyst review with an investigator and site specific revisions will undergo review with the local 
site investigator. Medication mappings will be explicitly reviewed for name based mappings to 
target list and route of administration. For example, if an NDC medication code for a blood 
pressure medication from the current release of RxNorm maps to an inappropriate medication 
(say an estrogen), inappropriate medications will be removed from final cohort selection. 
Laboratory values for LOINC mapped  labs will be reviewed for name matching, specimen 
source and that diagnostic results are in expected ranges by mean, median, maximum, and  
minimum tables and histograms.  Non-numeric text values will be reviewed to generate 
interpretative keys for all sites with periodic review for text values not mapping to the interpretive 
key table. For example, if out of range labs reporting changes for HgbA1c from ‘>12.1’ to 
‘>12.3’, new text values not seen during the validation phase will be flagged for analyst review. 
ICD10 conversation dates will be tracked for all institutions and ICD10 crosswalks for  inclusion. 
Data transfers to federated data store in Pieces system 

58 
 
Data files will be transferred from participating sites via secure FTP at least once weekly to a 
central database using a standard data model. Local copies of the same data model will be 
allowed where necessary for data security approvals of participating institutions with entirely 
local versions of the data model within the VA Internet Firewall planned for initiation of trial 
activity to expedite information security and privacy concerns. Identical query logic will be used 
to identify patients on local copies of the Pieces data model. Federated Data Systems using the 
Pieces system to store research data and perform uniform selection logic. Minimal data 
transformation steps necessary to standardized date/time formatting and import of data with 
minimal transformations.  
As a condition of the data use agreements signed with ProHealth Physicians, individual 
elements of the Safe Harbor elements of PHI are encrypted before transmission until they are 
needed for final data sets linkages for outcome standardization to maximize patient privacy and 
minimize data loss risk. As a result the data base of candidate and confirmed patients will be 
mirrored on the ProHealth Corporate Data ware house to allow subsequent on premises 
identification and generation of worklists.  
Data transfers from Pieces system to participating sites 
Standardized worklists that represent patients will be transmitted to the clinical sites. Patients 
with a candidate status and upcoming appointments in the subsequent week will be reported to 
the practice facilitator for additional follow up confirmatory testing to be arranged.  An additional 
report on confirmed patients with planned visits in the coming week will also be transmitted to 
the sites. Additional reports on candidate or confirmed patients presenting in the prior week, not 
reported on the prior report due to new interval data or scheduling changes since the time of the 
prior report will also be transmitted. Where these data transfers can trigger additional provider 
notification or worklist integration with the local EHR will be permitted as a site specific IT 
decisions 
Intellectual Property related to the Pieces TM platform is owned by the PCCI. Data definitions 
and workflows of the cohort selection will be public maintained and associated predictive 
models for specific aim three will be public released. 
Disseminations Methods 
Data Sharing Plan and Public Access 
We are obliged to share our data within the analytic team of the ICD-Pieces TM trial. The authors 
will retain the rights to the deidentifed final data until the trial is completed. Interested parties will 
be 
able 
to 
download 
information 
about 
the 
predictive 
model 
from 
the 
PCCI 
website.pccipieces.org. 
Short term data storage of transfer files will occurred via encrypted drives between password 
protected encrypted computers. 
Roles and Responsibilities 
PCCI data analyst 

59 
 
Software: 
Statistical analysis planned perform in R Version, Stata MP version 
MySQL Server 5.6 
Pieces TM Platform Version 2.0 
Deidentification Algorithm 
DeID (Nematullah et al) 
 
 
 
 
 
 
 
16. 
Study Administration 
16.1 
Study Leadership and Governance 
16.1.1 Steering Committee 
The Steering Committee will include members of the executive committee, representatives from 
NIH, representatives from the advisory groups/ cores and the PI from each of the collaborating 
health care systems. The steering committee will provide direct oversight of ICD-Pieces and set 
policies and procedures for the study. The steering committee will be the first resource both for 
planning and implementing strategies and also for receiving information from the study sites. 
The steering committee will review all study outcomes. During the implementation phase, the 
steering committee will hold monthly telephone conferences and a face-to-face meeting in 
Dallas, TX at the beginning of the implementation period and yearly thereafter till the end of the 
study. PIs at each HCS are Dr. George Oliver at PHHS, Dr. Ferdinand Velasco at THR, Dr. Tom 
Meehan in ProHealth Physicians, and Dr. Susan Hedayati and Dr. Tyler Miller at VA North 
Texas Healthcare Systems. 
16.1.2 Executive Committee 
The Executive Committee will be responsible for all major decisions affecting the study and will 
provide direction, ongoing review and guide allocation of resources. Members of the Executive 
Committee will meet face to face or via conference call every 2 weeks or more often if there is 
need to address new issues before scheduled meetings. The Executive Committee members 
will be Dr. Vazquez, Dr. Toto and Dr. Oliver Dr. Vazquez, PI is Professor of Medicine at UT 
Southwestern, Nephrology Chief at Parkland Health and Hospital System and Clinical Director 
of the Nephrology Division at UT Southwestern. Dr. Robert Toto is Co-Principal Investigator and 
Professor of Medicine at UT Southwestern, Associate Dean for Translational Science, Director 
of the Center for Translational Medicine/Clinical Translational Award (CTSA) at UT 
Southwestern and Director of the Clinical and Translational Core of the George M. O’Brien 
Kidney Center at UT Southwestern. Dr. Oliver is Vice-President of Clinical Informatics at the 

60 
 
Parkland Center for Clinical Innovation. Dr. Andrew Narva, Program Director of the National 
Kidney Disease Education Program at NIDDK and Dr. Barbara Wells, Senior Health Services 
Researcher at NHLBI, provide study oversight and ongoing input on study planning and 
operations. 
16.1.3 Conflict of Interest Policy 
The UT Southwestern Office of Research Compliance conflict of interest policy is in compliance 
with the PHS regulation (42 C.F.R. Part 50, Subpart F). 
16.2  Subcommittees 
16.2.1 Technical Workgroup 
The technical workgroup is led by Dr. George “Holt’ Oliver, VP of Clinical Informatics at PCCI is 
responsible for the technical design of the study, including mapping and deployment of the 
Pieces software to the study sites. Dr. Oliver is working with the IT staff from all study sites on 
this effort. Dr. Brett Moran, Professor of Medicine at UTSW and Chief of Health Information 
Management at PHHS serves as expert on use of EHR for the study. 
 
16.2.2 Biostatistics and Research Design Core 
Dr. Chul Ahn, Professor of Clinical Sciences and Director Biostatistics and Research Design 
Core, directs the Biostatistics and Research Design Core. Dr. Song Zhang, Associate Professor 
of Clinical Sciences, also works directly with ICD-Pieces. Dr. Ahn has over 380 peer-reviewed 
publications including new strategies for cluster randomization and has led design and analysis 
of multicenter clinical trials and studies on health services. Dr. Ahn and Dr. Zhang will be 
providing expertise with trial design, data collection/management and study analysis. 
16.2.3  Diabetes Advisory Workgroup 
Dr. Perry Bickel, Associate Professor of Medicine and Chief, Division of Endocrinology at UT 
Southwestern, leads the Diabetes Advisory Group to provide expert input for diabetes 
management strategies. Dr. Bickel and his group have initiated efforts to use electronic health 
technology to improve inpatient and outpatient diabetes management at Parkland 
16.2.4 Evaluation Workgroup 
The steering committee will provide oversight on primary care practices and assessments of 
patient and provider satisfaction. 
 
 
 
 
 
 
 

61 
 
 
 
 
 
 
 
 
 
 
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69 
 
Appendix I: CHRONIC KIDNEY DISEASE (CKD) HYPERTENSION MANAGEMENT 
PROTOCOL 
This protocol will be initiated as directed by CHRONIC KIDNEY DISEASE (CKD) CHRONIC 
DISEASE MANAGEMENT PROTOCOL.  
Protocol will be reviewed every year. 
RN will perform protocol with assistance from PA or NP at same clinical site. 
PA or NP may suggest deviations from protocol as deemed clinically appropriate. 
Orders (except medication orders) will be placed by RN in electronic medical record using 
"per protocol" order mode with physician, PA or NP as authorizing provider. Medication 
orders may be routed to provider as suggested per protocol, but medication and dose will 
ultimately be selected and ordered by provider. After medication orders are finalized by 
provider, RN will notify patient of final decision. 
Goals/Background 
1. Chronic Kidney Disease (CKD) is defined as (for the purposes of this protocol): 
a. Glomerular Filtration Rate (GFR) < 60 mL/min 
b. Or presence of proteinuria, defined as any one of the following: 
i. Random Urine Protein/Creatinine Ratio > 200 mg/g 
ii. Random Urine Microalbumin/Creatinine Ratio > 30 mg/g 
iii. 24 hour Urine Protein > 150mg 
iv. Urine dipstick protein (adjusted for specific gravity) 
2. Blood pressure (BP) goals 
a. For patients with CKD  goal blood pressure is Systolic (SBP) < 140 mmHg AND 
 
Diastolic (DBP) < 90 mmHg 
3. ACEi/ARB 
a. 
All patients with chronic kidney disease (with or without proteinuria) 
should be treated with an angiotensin converting enzyme inhibitor (ACEi) or 
angiotensin receptor blocker (ARB). 
b. Recommended ACEi: lisinopril 
i. Starting dose 5mg once daily if GFR > 10 mL/min or 2.5mg if GFR <1= 
10mL/min 
ii. Maximum dose 40mg once daily 
iii. Class-specific considerations. Be aware of these potential adverse 
effects when conduction follow-up of initiation or titration of this 
medication (details on the follow-up process are below). 
1. 
Elevated potassium (hyperkalemia) 
2. 
Reduction in kidney function (increase in creatinine or decrease 
 
in GFR) 
3. 
Dry cough 

70 
 
4. 
Facial swelling (angioedema) 
c. Recommended ARB: losartan 
i. Starting dose 25mg once daily 
ii. Maximum dose 100mg once daily 
iii. Class-specific considerations. Be aware of these potential adverse 
effects when conduction follow-up of initiation or titration of this 
medication (details on the follow-up process are below). 
1. Hyperkalemia 
2. Reduction in kidney function (increase in creatinine or 
decrease in glomerular filtration rate) 
3. Very rarely causes dry cough 
4. Facial swelling (angioederria) 
RN BP ASSESSMENT 
1. RN BP Assessment Visit 
a. Pre-Visit Planning: perform 1-2 weeks prior to appointment. 
i. Call patient 
1. Request patient bring all pill bottles to appointment. 
2. If patient has home blood pressure device, ask patient to bring 
home device and written home blood pressure log (after 
checking blood pressure twice daily for 1 week) to 
appointment. 
ii. GFR Assessment 
1. Review prior labs in "Results Review". 
2. Review last potassium, creatinine and glomerular filtration rate 
(GFR) in last 6 months. 
3. If all present within 6 months, no further action needed for 
GFR assessment. 
4. If no creatinine and GFR in last 6 months, order "CREATININE 
with-GFR. 
5. If no potassium in last 6 months, "POTASSIUM LEVEL". 
6. Compare most recent GFR with second most recent GFR. If most 
recent GFR is > 20% lower, discuss with provider. 
7. If GFR < 60 but >/= 30, update problem list to include "CKD 
Stage 3" 
8. If GFR < 30 but >15, update problem list to include "CKD Stage 
4". 
9. If GFR < 15, update problem list to include "CKD Stage 5" 
iii. Proteinuria Assessment 
1. Review prior urine protein testing in "Results Review" for following 
results in last 1 year: 
a. Microalbumin/Creatinine Ratio, Urine, Random 
b. Protein, Urine and Creatinine, Urine (both are required as 
ratio must be calculated manually by dividing urine 

71 
 
protein by urine creatinine). 
c. Protein, 24 hour, Urine 
d. Urine dipstick protein (adjusted for specific gravity) 
2. If labs are present in last year, no further action is needed for 
Proteinuria Assessment. 
3. If none are available, order MICROALBUMIN/CREATININE 
RATIO 
 
NOTE: 
"Unable to calculate" for Microalbumin/Creatinine Ratio implies zero 
 
protein present in urine. 
 
b. Assessment of BP goal 
Goal blood pressure is SBP < 140 mmHg AND DBP < 90 mmHg. 
c. Provide education annually on non-pharmacologic management of 
hypertension. 
i. Low Sodium Diet 
1. Discuss with patient importance of low sodium diet included no 
added salt as well as checking labels for processed foods. 
2. Provide patient with Exit Care SmartText in Patient Instructions: 
DIET-2 GRAM LOW SODIUM (choose appropriate language). 
3. Refer to nutrition at same clinical site for further counseling as 
needed. 
ii. Avoidance of daily use of non-steroidal anti-inflammatory drugs 
(NSAIDs). 
1. Discuss with patient that NSAIDs (included ibuprofen and 
naproxen) can increase blood pressure as well as cause further 
kidney damage. 
2. Discuss with provider as needed to identify alternatives to daily 
NSAIDs. 
iii. Moderation of alcohol (less than 2 servings per day). 
1. Discuss with patient that daily alcohol consumption can raise 
blood pressure. 
2. If needed, provide patient with Exit Care SmartText in Patient 
Instructions: ALCOHOL AND DRUG ABUSE (choose appropriate 
language). 
3. Refer for substance abuse counseling as needed. 
iv. Importance of exercise > 3 days per week. 
1. Discuss with patient that regular exercise can lower blood 
pressure. 
2. Provide patient with Exit Care SmartText in Patient Instructions: 
PKAMB OPC EXERCISE TO LOSE WEIGHT 
v. Abstinence from nicotine products. 
1. Discuss with patient that all nicotine products can raise blood 
pressure. 
2. If active smoker, perform 'Ready to Quit' assessment in social 
history section Epic and refer to Smoking Cessation Clinic if 

72 
 
patient is ready to quit. 
3. Provide patient with Exit Care SmartText in Patient Instructions: 
SMOKING CESSATION (choose appropriate language). 
vi. Maintenance of optimal weight is body mass index (BMI) 20.0 to 
25.0. 
1. Discuss with patient that maintenance of normal BMI can improve 
blood pressure. 
2. If BMI > 25.0 
(a) Provide patient with both of following Exit Care SmartText 
in Patient Instructions: DIET—CALORIE COUNTING 
(choose appropriate language) and DIET— LOW-FAT, 
LOW-SATURATEDFAT, 
LOW-CHOLESTEROL 
DIETS 
(choose appropriate language) 
3. Refer to nutrition at same clinical site as needed for dietary 
counseling. 
vii. Avoidance of daily use of over-the-counter decongestants 
(pseudoephedrine or phenylephrine). 
1. Discuss with patient that prolonged use of decongestants can 
raise blood pressure. 
2. Discuss with provider as needed for alternatives to decongestants 
for control of symptoms. 
viii. RN Blood Pressure Assessment: Ask patient about missed doses of 
BP medications in last 24 hours. If any missed doses, reschedule 
BP measurement 1-2 weeks after improved adherence. Ask patient 
about use of nicotine products. Wait 30 minutes after last use 
before measuring blood pressure. Measure and record blood 
pressure according to JNC 8 standards: After patient has sat quietly 
for 5 minutes in chair, measure with arm supported at heart level 
and with legs uncrossed and feet on the floor. Obtain at least two 
measurements and record the average of the two —sum of systolic 
values divided by 2 and sum of diastolic values divided by 2. (See 
Page number 4 (which is page 20 of 52 including introductory 
section) of the following link for full details: 
http://www.nhibi.nih.goviguidelines/hynertension/exnress.bdf). 
1. "RN BP measurement" below refers to average calculated as 
above per JNC 8 guidelines. 
2. If patient does not have written home blood pressure log and RN 
BP measurement is > 140 mmHg systolic or > 90 mmHg 
diastolic, 
initiate 
CKDHYPERTENSION 
PROTOCOL 
and 
perform at this visit. 
3. If patient does not have written home blood pressure log, and 
RN BP measurement systolic < 140 mmHg AND diastolic < 90 
mmHg, no further action is necessary. 
4. Home Blood Pressure Device Validation 
a 
If patient provides written home blood pressure log, review 
documentation in overview section of CKD diagnosis in 
problem list for date of last blood pressure device 
validation. 

73 
 
i. 
If validation in < 1 year, proceed to "Home 
Blood Pressure Log Review". 
ii. 
If no validation in > 1 year and patient did not 
bring home blood pressure device, then 
schedule follow-up appointment in 1-2 weeks 
with RN. Ask patient to provide new written 
blood pressure log and bring home blood 
pressure device to appointment for comparison 
with RN measurement. 
iii. 
If no validation in > 1 year and patient brings 
home blood pressure device, obtain 
measurement from home blood pressure 
device. 
1. 
Ask patient to demonstrate proper use of 
device and provide education as needed 
according to JNC 8 guidelines above. 
2. 
If difference > 10 mmHg (systolic or 
diastolic) between home device and RN 
measurement, disregard home blood 
pressure log and notify patient that device is 
not sufficiently accurate. a. Under CKD 
diagnosis in Problem List, record in Overview 
section: "Home BP Device Validation 
[DATE]: home device not consistent with RN 
measurement." 
3. 
If difference < 10 mmHg (systolic or 
diastolic), under CKD diagnosis in Problem 
List, record in Overview section: "Home BP 
Device Validation [DATE]: home device 
validated as consistent with RN 
measurement" and proceed to "Home 
Blood Pressure Log Review". 
5. Home Blood Pressure Log Review 
a 
If BP cuff is validated as above and home BP log is used 
in clinical decision-making, log should be scanned into 
Epic. 
b 
Calculate average of seven most recent systolic and 
diastolic values (i.e. sum of seven most recent systolic 
values divided by 7; and sum of seven most recent 
diastolic values divided by 7). 
c 
If average systolic > 140 mmHg or average diastolic > 90 
mmHg, initiate CKD HYPERTENSION PROTOCOL and 
perform at this visit. 
d 
If average systolic < 140 mmHg AND average diastolic < 
90 mmHg, no further action is necessary. 
e 
Consider extenuating circumstances such as acute pain 
and acute psychological distress. Discuss with provider if 
you feel such extenuating circumstances are contributing 
to blood pressure elevation. Consider rescheduling RN BP 
Assessment Visit in 2-4 weeks to reassess. 

74 
 
f 
Assess for adverse effects every visit including class-
specific considerations above as well as side effects 
common to many blood pressure medications which 
include (but are not limited to) lightheadedness and 
fainting. 
(i) 
If any new adverse effects, discuss with 
provider. 
(ii) If no new adverse effects, proceed to BP 
Medication Adherence Assessment. 
g 
BP Medication Adherence Assessment 
(i) 
Ask patient about each BP medication and 
ask, "How many days per week do you forget 
your [insert BP medication]?" 
(ii) If one day or less, consider adherent by self-
report. 
(iii) Review BP medication bottles if available. 
(iv) If medications are filled at Parkland 
pharmacy, review refill history in Cerner for 
last 6 months. Consider adherent if obtains 
within 6 days for a 30 day prescription or 
within 18 days for a 90 day prescription. 
(v) If not adherent by self-report or refill history, 
discuss with patient importance of adherence. 
(a.) Reschedule RN BP Assessment Visit in 2 
weeks after improved adherence. 
(b.) If patient was deemed non-adherent on two 
consecutive visits, refer to clinical 
pharmacist for medication review and 
assistance with barriers to adherence (cost, 
complexity, etc). 
(vi) If considered adherent by self-report and refill 
history, proceed to "Medication Adjustment". 
6. Medication Adjustment 
a 
If patient is already on ACEi or ARB but not at maximum 
tolerated dose (see above), increase dose to achieve SBP 
and DBP goal (as per ACEi/ARB PROTOCOL below) 
b 
If patient is on maximum tolerated dose of ACEi or ARB, 
proceed to NON ACEi/ARB PROTOCOL. 
c 
If patient is not on ACEi or ARB, confirm allergies with 
patient. 
d 
If no prior allergy or adverse reaction to ACEi or ARB, 
proceed to ACEi/ARB PROTOCOL. 
e 
If prior allergy to ACEi is cough, proceed to ACEi/ARB 
PROTOCOL. 
f 
If prior allergy or adverse reaction to ACEi or ARB other 
than cough, consult with provider safety of starting ACEi or 
ARB. 
g 
If after discussion with provider, ACEi and ARB are both 
considered contraindicated, update allergies as needed 

75 
 
and proceed to NON-ACEi/ARB PROTOCOL. 
ACEI/ARB PROTOCOL 
1. Consider this protocol active until completed. 
2. Review "Results Review" for past potassium and creatinine (abbreviated as "Cr" 
and "K" respectively hereafter). If both are available, no further action is needed. If 
one or both is not available in last 3 months, order both CREATININE LEVEL and 
POTASSIUM LEVEL as appropriate (referred to as "Cr/K Check" hereafter). 
a. Lab Results Interpretation 
i. 
Is K > 4.9? 
1. Yes 
a 
Discuss with provider before starting or increasing ACEi or ARB. 
2. No 
a 
If not on ACEi/ARB, and no prior allergy to ACEi or ARB, route 
pended order to provider for lisinopril 5mg once daily and proceed 
to "Follow-Up" below. 
b 
If not on ACEi or ARB and prior cough due to ACEi but no other 
ACEi or ARB allergy, route pended order to provider for losartan 
25mg once daily and proceed to "Follow-Up" below. 
c 
If already on ACEi or ARB, but not at maximum tolerated dose, 
increase dose and proceed to "Follow-Up" below. 
d 
If already on ACEi/ARB at maximum tolerated dose, consider this 
protocol 
COMPLETED 
and 
proceed 
to 
NON-ACEI/ARB 
PROTOCOL. 
e 
Follow-Up 
f 
Schedule RN BP Assessment Visit and Cr/K Check 1-3 weeks 
following initiation or dose increase. Request patient to have labs 
drawn prior to appointment. 
b. K Interpretation 
i. Is K > 5.4? 
1. Yes. Discuss with provider stopping ACEI/ARB 
2. No 
ii. 1. Is K > 4.9? 
3. Yes 
a 
Continue ACEi/ARB at current dose. 
b 
Provide patient with low potassium diet handout 
c 
Order repeat POTASSIUM LEVEL in 1 week. 
d 
If K is not < 5.0 on repeat evaluation, discuss with provider. 
e 
If K is </= 4.9, proceed to Cr Interpretation. 
4. No - proceed to Cr Interpretation. 

76 
 
c. Serum Creatinine (Cr) Interpretation 
ii. Is Cr >20% higher than value prior to initiation or last increase of ACEi/ARB? 
1. Yes. Discuss with provider decreasing dose by 50% (or stopping if at 
starting dose). Discuss follow up plan for Cr with provider as well. 
2. No 
(i) Is creatinine within 30% of baseline since initiation? 
(a) No. Discuss with provider decreasing dose by 50% (or stopping if 
at starting dose). Discuss follow up plan for Cr with provider as 
well. 
(b) Yes. Proceed to RN BP Assessment. 
3. RN BP Assessment 
a. Perform RN BP Assessment as detailed above. 
b. Is BP at goal based on definitions above? 
i. Yes. Continue regimen and schedule RN BP Assessment Visit in 3 
months and follow-up with PCP within 6 months. 
1. If BP continues to be at goal in 3 months, this protocol is COMPLETE and 
can return hypertension management to PCP. 
ii. No 
2. Is ACEi/ARB at maximum tolerated dose? 
(i) Yes. 
This 
protocol 
is 
COMPLETE. 
Initiate 
NON-ACEi/ARB 
PROTOCOL. 
(ii) No 
route pended order to provider for double prior dose of 
current ACE and return to "Follow-Up" above. 
 
NON ACEi/ARB PROTOCOL 
1. Discuss with provider selection of next anti-hypertensive protocol. 
2. Discuss following medication suggestions with provider. These are only suggestions 
to guide management, but final selection is at provider's discretion. 
a. If patient has history of myocardial infarction or heart failure, recommend BETA-
BLOCKER PROTOCOL. 
i. 
Recommend carvedilol given dual properties of heart rate reduction (beta 
blockade) and vasodilation (alpha blockade) and, therefore, typically greater 
impact on blood pressure. 
ii. Recommended starting dose: carvedilol 6.25mg twice daily. 
iii. Maximum dose: carvedilol 25mg twice daily. 
iv. Class-specific considerations 
1. Low heart rate (bradycardia) 
2. Lower extremity swelling, erectile dysfunction, fatigue. 
3. Exacerbation of asthma or chronic obstructive lung disease symptoms 
(shortness of breath or wheezing). 
b. If patient is on maximum tolerated beta-blocker or has no history of myocardial infarction 
or heart failure, recommend DIURETIC PROTOCOL. 
i. 
For patients with GFR > 30 mL/min, recommend chlorthalidone. 
1. Starting dose 12.5mg once daily. 
2. Maximum dose 25mg once daily. However, dose adjustment is 
dependent on provider assessment of volume status. All follow-up 

77 
 
evaluations should be discussed with provider. 
ii. For patients with GFR < 30, recommend furosemide. 
1. Starting dose 20mg twice daily. 
a. Maximum dose dependent on provider assessment of volume status. All 
follow-up evaluations should be discussed with provider. 
iii. Class-specific considerations 
1. Must counsel patients that diuretics will increase urinary frequency 
2. May worsen prostate symptoms in men. 
c. If patient is already on maximum tolerated diuretic and no history of myocardial infarction 
or heart failure, recommend CALCIUM CHANNEL BLOCKER PROTOCOL. 
i. 
For patients with proteinuria, recommend non-dihyrdopyridine calcium 
channel blocker (CCB) verapamil SR as it may help reduce proteinuria. 
1. Recommended starting dose verapamil SR 120mg once daily. 
2. Maximum dose verapamil SR 360mg once daily. 
ii. For patients without proteinuria, dihydropyridine CCB amlodipine may be 
used. 
1. Recommended starting dose amlodipine 5mg once daily. 
2. Maximum dose amlodipine 10mg once daily. 
iii. Class-specific considerations 
1. Amlodipine may cause increased heart rate (reflex tachycardia). 
2. Verapamil may cause bradycardia and constipation. 
Both may cause lower extremity swelling. 
d. If patient is already on maximum tolerated doses of beta-blocker, 
diuretic and calcium channel blocker, recommend HYDRALAZINE 
PROTOCOL. i. Hydralazine 
i. 
Recommended starting dose 10mg three times daily. 
ii. Maximum dose 100mg three times daily. 
iii. Class-specific considerations 
1. May cause reflex tachycardia. 
e. If patient is already on maximum tolerated doses of beta-blocker, diuretic and 
calcium channel blocker and hydralazine, discuss with provider the following: 
i. 
Referral to Hypertension Clinic. 
ii. Referral to clinical pharmacist for full medication review and 
assessment of adherence. 
iii. Return management of hypertension to PCP for work-up of secondary 
hypertension and selection of fifth anti-hypertensive agent. 
BETA-BLOCKER PROTOCOL 
1. Discuss following medication suggestions with provider. These are only suggestions 
to guide management, but final selection is at provider's discretion. 
2. Perform RN BP Assessment as detailed above. 
3. Is BP at goal? 
a. Yes.  Continue regimen and schedule RN BP Assessment Visit in 3 months and 
follow-up with PCP within 6 months. 
i. 
If BP continues to be at goal in 3 months, can return hypertension 
management to PCP. 

78 
 
b. No 4 is HR > 60? 
i. 
Yes.  Route pended order to provider for carvedilol 6.25mg twice daily (or 
alternative beta-blocker as directed by provider) and schedule for "Follow-
Up" as detailed below in 2-4 weeks. 
ii. No.  Discuss with provider safety of starting beta-blocker or alternatively 
selection of diuretic, calcium channel blocker or hydralazine protocols. 
4. Follow-Up 
a. Perform RN BP Assessment as detailed above in 2-4 weeks. 
b. Is BP at goal? 
i. 
Yes.  Continue regimen and schedule RN BP Assessment Visit in 3 
months and follow-up with PCP within 6 months. 
1. If BP continues to be at goal in 3 months, can return hypertension 
management to PCP. 
ii. No.  Is HR > 60? 
1. Yes.  Is beta-blocker at maximum dose? 
a. No. Route pended order to provider for double prior dose of beta-
blocker and schedule for "Follow-Up" as detailed above in 2-4 
weeks. 
b. Yes.  Return to NON-ACEi/ARB PROTOCOL for selection of next 
medication. 
2. No.  Discuss with provider safety of continuing beta-blocker or selection 
of diuretic, calcium channel blocker or hydralazine protocols. 
DIURETIC PROTOCOL 
1. Discuss following medication suggestions with provider. These are only suggestions 
to guide management, but final selection is at provider's discretion. 
2. Perform RN BP Assessment as detailed above. 
3. Is BP at goal? 
a. Yes.  Continue regimen and schedule RN BP Assessment Visit in 3 months 
and follow-up with PCP within 6 months. 
i. 
If BP continues to be at goal in 3 months, can return hypertension 
management to PCP. 
b. No.  Proceed with diuretic selection 
4. Diuretic selection 
a. If no K or GFR in last three months then order POTASSIUM LEVEL and 
CREATININE WITH eGFR in EHR. 
i. Is K > 3.5? 
1. No.  Discuss with provider safety of initiation or titration of diuretic 
or need for potassium supplementation and schedule for "Follow-
Up" as detailed below in 2-4 weeks after provider has provided 
recommendation. 
2. Yes.  Is patient already taking diuretic? 
a. Yes.  Discuss with provider next choice (consider 
recommendations below based on GFR) and schedule for "Follow-
Up" as detailed below in 2-4 weeks. 

79 
 
b. No.  Is GFR > 30? 
(i) Yes.  Recommend thiazide diuretic such as chlorthalidone 12.5mg 
or other diuretic selected by provider and schedule for "Follow-Up" 
as detailed below in 2-4 weeks. 
(ii) No.  Recommend furosemide 20mg twice daily or other diuretic 
selected by provider and schedule for "Follow-Up" as detailed 
below in 2-4 weeks. 
5. Follow-Up 
a. Schedule RN BP Assessment Visit in 2-4 weeks 
b. Order POTASSIUM LEVEL and CREATININE WITH E-GFR and request 
patient have labs drawn at least 1 business day prior to visit. 
c. Perform RN BP Assessment as detailed above in 2-4 weeks. 
d. Is K > 3.4? 
i. No.  Discuss with provider change in therapy or potassium 
supplementation. Discuss follow up plan for K with provider as well. 
ii. Yes 
1. 
Is GFR > 10% lower than last value? 
a 
Yes.  Discuss with provider decrease in diuretic dose or stopping 
diuretic. Discuss follow up plan for Cr with provider as well. 
b 
No.  Is BP at goal? 
(i) If BP is still not at goal at maximum tolerated dose of diuretic, 
return to NON-ACEi/ARB PROTOCOL. 
(ii) If BP is still not at goal and not taking chlorthalidone 25mg or 
maximum tolerated dose of diuretic, then discuss with provider if 
dose of diuretic should be increased. 
(iii) If provider recommends to increase dose, schedule for "Follow-
Up" as detailed above in 2-4 weeks. 
(iv) If provider recommends to not increase dose, return to NON-
ACEi/ARB PROTOCOL. 
CALCIUM CHANNEL BLOCKER PROTOCOL 
1. Discuss following medication suggestions with provider. These are only suggestions 
to guide management, but final selection is at provider's discretion. 
2. Perform RN BP Assessment as detailed above. 
3. Is BP at goal? 
a. Yes.  Continue regimen and schedule RN BP Assessment Visit in 3 months and 
follow-up with PCP within 6 months. 
i. If BP continues to be at goal in 3 months, can return hypertension 
management to PCP. 
b. No.  Is patient already taking calcium channel blocker (CCB)? 
i. Yes - Is CCB at maximum dose? 
1 
Yes.  Return to NON-ACEI/ARB PROTOCOL. 
2 
No.  Route pended order to provider for double dose of current CCB and 
schedule for "Follow-Up" as detailed below in 2-4 weeks. 
a 
No.  Does patient have proteinuria as defined above? 
b 
Yes.  Route pended order for verapamil SR 120mg once daily and 

80 
 
proceed to "Follow-Up" below. 
c 
No.  Route pended order for amlodipine 5mg once daily and schedule for 
"Follow-Up" as detailed below in 2-4 weeks. 
4. Follow-Up 
a. Perform RN BP Assessment as detailed above in 2-4 weeks. 
b. Is HR >/= 100? 
i. Yes - discuss with provider 
ii. No. Is BP at goal? 
1 
Yes.  Continue regimen and schedule RN BP Assessment Visit in 3 
months and follow-up with PCP within 6 months. 
a 
If BP continues to be at goal in 3 months, can return hypertension 
management to PCP. 
2 
No.  Is CCB at maximum dose? 
a. No.  Route pended order to provider for double dose of current 
CCB and return to follow-up above. 
b. Yes.  Return to NON-ACE i/ARB PROTOCOL. 
HYDRALAZINE PROTOCOL 
1. Discuss following medication suggestions with provider. These are only suggestions 
to guide management, but final selection is at provider's discretion. 
2. Perform RN BP Assessment as detailed above. 
3. Is BP at goal? 
a. Yes.  Continue regimen and schedule RN BP Assessment Visit in 3 months 
and follow-up with PCP within 6 months. 
i. 
If BP continues to be at goal in 3 months, can return hypertension 
management to PCP. 
b. No.  Route pended order to provider for hydralazine 10rng PO TID. If 
patient is already taking hydralazine 10mg PO TID, route pended order to 
provider for dose to 25mg PO TID. If patient is already taking 25mg or 
more TID, route pended order to provider for double current dose of 
hydralazine if not at maximum dose. Schedule for "Follow-Up" as detailed 
below in 2-4 weeks. 
4. Follow-Up 
a. Perform RN BP Assessment as detailed above in 2-4 weeks. 
b. is HR >1= 100? 
i. 
Yes.  Discuss with provider 
ii. No.  Is BP at goal? 
1. Yes.  Continue regimen and schedule RN BP Assessment Visit in 3 
months and follow-up with PCP within 6 months. 
c. If BP continues to be at goal in 3 months, can return hypertension management to 
PCP. 
d.  No.  Is hydralazine at maximum dose? 
i. 
No.  Route pended order to provider for double current dose of 
hydralazine and return to follow-up above. 
ii. Yes.  Return to NON-ACEi/ARB PROTOCOL. 

81 
 
References 
 
 
James PA et al.  2014 Evidence-based Guideline for the Management of High Blood Pressure 
in Adults. Report from the Panel Members Appointed to the Eighth Joint National Committee 
(JNC 8). JAMA 2014, 311(5):507-520 
 
Kidney Disease:  Improving Global Outcomes (KDIGO) CKD Work Group.  KDIGO 2012 Clinical 
Practice Guideline for the Evaluation and Management of Chronic Kidney Disease.  Kidney 
International 2013, Supp 3:1-150 
 
Kidney Disease: Improving Global Outcomes (KDIGO) Blood Pressure Work Group.  KDIGO  
Clinical Practice Guideline for the Management of Blood Pressure in Chronic Kidney Disease.  
Kidney International 2012, Supp 2:337-414 
 
K/DOQI Clinical Practice Guidelines for Chronic Kidney Disease: Evaluation, Classification and 
Stratification.  Am J Kidney Dis 2002, 39: S266. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

82 
 
Appendix II: DIABETES MANAGEMENT PROTOCOL 
Goals:  
The goal of this protocol is to assist primary care providers in delivering diabetes care to 
patients with CKD, type 2 diabetes, and hypertension. This protocol focuses on safely achieving 
targets for blood glucose control that are tailored to each individual based on the factors listed 
below and in the context of an overall care plan that promotes reduction of cardiovascular risk 
factors. 
• 
Duration of diabetes 
• 
Remaining life expectancy 
• 
Presence and severity of microvascular complications, such as 
o Retinopathy 
o Albuminuria 
o Neuropathy 
• 
Presence and severity of major active co-morbidities, such as 
o Coronary artery disease 
o Chronic obstructive pulmonary disease 
o Chronic kidney disease 
o Chronic liver disease 
o Recent stroke 
o Life-threatening malignancy 
• 
Risk for severe hypoglycemia 
• 
Financial resources 
• 
Patient factors that affect adherence, such as motivation, family support, and 
insight 
 
The short-term benefits of improving poor glucose control include the resolution of symptoms 
(polyuria, polydipsia, polyphagia, unintended weight loss) and the avoidance of volume 
depletion due to excessive glycosuria, which is especially dangerous in the elderly and those at 
risk for acute kidney injury, and of excessive catabolism resulting in weight loss and ketosis. 
Long-term benefits include reduced risk of the development or progression of the microvascular 
complications of diabetes, including retinopathy, nephropathy, and neuropathy. 
The risks of tighter glucose control include the requirement of increased glucose self-monitoring 
(cost and inconvenience) and of hypoglycemia. Iatrogenic hypoglycemia is a major patient 
safety issue, especially in those who have blunted or absent hypoglycemia awareness and 
those with coronary artery disease. 
Thus, for each patient, goals for glucose control must be individualized based on the degree of 
achievable benefit and the degree of acceptable risk. The figure below from the American 
Diabetes Association Position Statement on Glycemic Targets visually summarizes this risk-
benefit consideration.  
 
 

83 
 
Protocol Figure 1 
 
 
Protocol Figure 1. From Inzucchi SE et al. Diabetologia (2015) 58:434 
 
The decision about what glucose control target to aim for in a given patient at a given time must 
take into account multiple factors that cannot be fully protocolized. In striving to reduce the long-
term risks of microvascular complications, it is important to remember that hypoglycemia, if 
severe and prolonged, may result in seizure, coma and death in the short-term. Even mild 
hypoglycemia in someone driving a motor vehicle, for example, may result in significant harm to 
the patient and to others. The elderly are particularly at risk for falls resulting from 
hypoglycemia. 
 
 

84 
 
Monitoring Glucose Control: the Hemoglobin A1C (A1C) 
Methods for monitoring glucose control include self-monitoring with glucose meters, continuous 
glucose monitors, and the hemoglobin A1C. For type 2 diabetes in non-insulin treated patients, 
the most pragmatic basis for making changes in therapy is the A1C, because it integrates 
glucose control over 2-3 months. Some caveats are necessary to recognize. First, A1C 
measurements may be falsely reduced in cases of shortened RBC lifespan, blood transfusions 
and hemolysis. Second, renal dysfunction and/or dialysis may complicate the relationship 
between A1C and glucose levels, so it is important to examine the patient’s blood glucose 
logbook to assess glucose control by an independent method. In general, the A1C should be 
measured twice yearly in patients who are at goal and every 3 months in those who are 
adjusting their therapeutic regimen. 
Hypoglycemia and the Rule of 15 
At each visit, patients should be asked if they are experiencing symptomatic or asymptomatic 
hypoglycemia. Each patient should demonstrate knowledge of the symptoms of hypoglycemia 
and how to treat hypoglycemia. 15-20 grams of pure glucose is the preferred method of 
treatment for hypoglycemia (BG <70 mg/dl). The patient should repeat treatment with 15-20 
grams of glucose every 15 minutes until their self-monitored blood sugar is above 70 mg/dl 
(Rule of 15). After the blood sugar reaches over 70 mg/dl, the patient should eat a meal within 
one hour or eat a snack to prevent recurrence of hypoglycemia. 
Setting Glucose Control Targets Based on the A1C 
Guidelines have been proposed for appropriate A1C targets based on the considerations 
described above. 
The Kidney Disease Outcomes Quality Initiative (KDOQI) published in 2012 guidelines for the 
management of hyperglycemia and general diabetes care in CKD. 
• 
KDOQI Guideline 2.1 recommends “a target HbA1c of ~7.0% to prevent or delay 
progression of the microvascular complications of diabetes, including DKD” (diabetic 
kidney disease). 
 
• 
KDOQI Guideline 2.2 recommends “not treating to an HbA1c target of <7.0% in patients 
at risk of hypoglycemia.” 
 
• 
KDOQI Guideline 2.3 suggests “that target HbA1c be extended above 7.0% in 
individuals with co-morbidities or limited life expectancy and risk of hypoglycemia.” 
 
The VA Clinical Practice Guidelines for the Management of Diabetes Mellitus suggest glucose 
control target ranges based on major comorbidities, life expectancy, and the presence/severity 
of microvascular complications. See Protocol Table 1. 
 

85 
 
Protocol Table 1 
 
Protocol Table 1: From VA/DoD Clinical Practice Guideline, Management of Diabetes Mellitus, 
2010, p. 49. 
 
As eGFR declines below 60 ml/min/1.73 m2, the risk of hypoglycemia increases. Thus, it is 
important to reassess glucose control targets in the setting of declining renal function. The 
American Diabetes Association Consensus Conference on Diabetic Kidney Disease (2014) has 
recommended the A1C goal of <8% when GFR <60 ml/min/1.73 m2 due to the increased risk 
of hypoglycemia. 
Any target chosen for a given patient must be revised upward in the face of frequent or 
dangerous hypoglycemia, as well as the development of hypoglycemia unawareness. On the 
other hand, a more aggressive goal of <6.5%, if achieved without significant hypoglycemia, may 
be appropriate in “early-onset diabetes in younger patients” (Tuttle et al., 2014). 
 

86 
 
General Guidelines for Antidiabetic Medications 
• 
Metformin, which reduces liver glucose production, is usually the first line treatment for 
type 2 diabetes in those for whom it is not contraindicated and who tolerate it 
o Advantages include low risk of hypoglycemia, no weight gain, and low cost 
o Long history as safe and effective 
o May reduce risk for cardiovascular events (UKPDS) 
• 
If glycemic goals have not been reached after 3 months of therapy, adding additional 
oral antidiabetes medications should be guided by patient-centered considerations.  
o Refer to Protocol Figure 2 for a schematic guide to dual and triple therapy 
o In patients with type 2 diabetes who have little remaining beta cell function, 
insulin therapy is usually required. Refer to Protocol Figure 3 for a schematic 
approach to initiating insulin therapy in patients with type 2 diabetes. 
o In patients already on oral antidiabetes medications up to three oral agents, a 
basal insulin (glargine, detemir, or NPH) is usually added as a single daily 
injection. If prandial bolus insulin is later added, then sulfonylureas, DPP-4 
inhibitors, and GLP-1 receptor agonists are usually discontinued. Combination of 
basal-bolus insulin with metformin, pioglitazone, or SGLT2 inhibitors may reduce 
the insulin requirement and improve control over insulin only. 
• 
In general, one can expect a 1% decrease in the A1C after starting an oral antidiabetes 
medication and an additional 1% decrease after adding a second oral agent. 
• 
If given as part of dual or triple therapy with insulin, any antidiabetes medication can be 
associated with hypoglycemia. 
 
Specific Guidelines for Oral Antidiabetes Medications 
• 
The medications listed below are the most commonly prescribed in the U.S. Other 
approved drugs are used less frequently due to lower efficacy or side effects. 
• 
Recommended dose adjustments in CKD for the non-insulin diabetes medications have 
been published. The table below is taken from Tuttle KR et al. Diabetic Kidney Disease: 
A Report From an ADA Consensus Conference. Diabetes Care 2014,37:2864-2883. 
 
 
 
 
 
 
 
 
 
 

87 
 
Metformin 
• 
Increases risk for lactic acidosis in those with significant renal dysfunction (do not use if 
eGFR < 30 mL/min/1.73 m2, in those at risk for AKI, and in those with fluctuating renal 
function) 
• 
Use of Metformin in CKD: 
o FDA label reads, “do not use if SCr ≥1.5 mg/dl in men, ≥1.4 mg/dl in women,” but 
this restriction has been questioned due to the low incidence of metformin-
induced lactic acidosis 
o Proposed recommendations from Lipska et al. Use of Metformin in the Setting of 
Mild-to-Moderate Renal Insufficiency. Diabetes Care. 2011, 34:1431-1437: 
 
▪ 
eGFR ≥60 
 
No renal contraindications; monitor annually 
▪ 
eGFR <60 and ≥45 
May continue use; monitor every 3-6 months 
▪ 
eGFR <45 and ≥30 
Use caution and at lower dose (e.g. 50% maximal) 
Monitor every 3 months 
Do not start new patients on metformin 
▪ 
eGFR <30 
 
Stop metformin 
 
• 
May cause GI side effects, including diarrhea and cramping, but these are minimized if 
started at low doses, taken with food, and titrated up slowly 
 
o Start at 500 mg once to twice daily with meals 
o Wait 1-2 weeks before increasing dose 
o If GI side effects occur, reduce dose to the dose last tolerated 
o Maximal dose is 2550 mg/day in divided doses or 2000 mg of the extended 
release (ER) formulation 
• 
Prolonged use is associated with vitamin B12 deficiency 
 
Sulfonylureas (glyburide, glipizide, glimepiride) 
• 
Promote insulin secretion independent of ambient glucose level 
o Risk of hypoglycemia 
o Use with caution in the elderly and in CKD 
o Avoid use in stage 3 or greater CKD 
o Glipizide is preferred in CKD 
• 
Efficacy is good initially but requires addition of second agent sooner than other drugs 
• 
Risk for weight gain 
• 
Must not skip or delay meals 
• 
Low cost 
 
 
 
 

88 
 
Rapid-acting Secretagogues (repaglinide, nateglinide) 
• 
This class, the metaglinides, are more rapid-acting than sulfonylureas and are taken 
before each meal 
• 
May cause less hypoglycemia than sulfonylureas in patients who skip or delay meals 
• 
Expensive 
 
Pioglitazone  
• 
Promotes insulin sensitivity in muscle and reduces hepatic glucose production 
• 
Disadvantages include weight gain (both water and fat), edema and heart failure, and 
increased risk of bone fracture 
• 
Contraindicated in NYHA Class III and IV heart failure 
• 
Advantages include low risk of hypoglycemia and good durability of efficacy 
• 
Generic formulation now available; low cost 
• 
No adjustment for eGFR 
 
DPP-4 Inhibitors (sitagliptin, saxagliptin, linagliptin, alogliptin) 
• 
Increase glucose-dependent insulin secretion and decrease glucagon secretion 
• 
Low risk of hypoglycemia; no weight gain 
• 
Expensive 
• 
Possible risk of acute pancreatitis 
• 
Possible increased risk of heart failure admissions 
 
SGLT2 Inhibitors (canagliflozin, dapagliflozin, empagliflozin) 
• 
Inhibit reabsorption of glucose in the kidney, thereby promoting glucosuria 
• 
Advantages include low risk of hypoglycemia, weight loss, and blood pressure lowering 
• 
Do not rely on intact beta cell function, so SGLT2 inhibitors are effective at all stages in 
the natural history of type 2 diabetes 
• 
Do rely on renal function; as renal function falls, SGLT2 inhibitors are less effective 
• 
When starting, consider reducing doses of diuretics or other antihypertensives to avoid 
hypotension 
• 
Must use with caution or not at all in patients with eGFR <60;  
• 
Renal dosing: 
o For canagliflozin and dapagliflozin see Table below 
o Empagliflozin: do not use for eGFR <45 
 
 
 
 
 

89 
 
GLP-1 Receptor Agonists (exenetide, liraglutide, albiglutide) 
• 
Stimulate glucose-dependent insulin secretion, decrease glucagon secretion, delay 
gastric emptying, and diminish appetite 
• 
Advantages include low risk of hypoglycemia and weight loss 
• 
Disadvantages include requiring injection and cost 
• 
Some experience nausea/vomiting, especially soon after starting treatment 
• 
Rodents have developed thyroid C-cell tumors in these drugs, but the risk for humans is 
not known   
• 
Contraindicated in patients with personal or family history of medullary carcinoma of the 
thyroid or multiple endocrine neoplasia syndrome type 2 
• 
Some reports of exenetide drug-induced renal injury 
 

90 
 
Protocol Table 2
 
 
Protocol Table 2. Tuttle KR et al. Diabetic Kidney Disease: A Report From an ADA Consensus 
Conference. Diabetes Care 2014,37:2864-2883. 
 
 
 
 

91 
 
Protocol Figure 2 
 
Protocol Figure 2. From Inzucchi SE et al. Diabetologia (2015) 58:436  
 
 

92 
 
Protocol Figure 3 
 
Protocol Figure 3. From Inzucchi SE et al. Diabetologia (2015) 58:438 
 
 

93 
 
Another commonly used formula to design a starting multi-injection insulin regimen is to 
estimate the total daily dose of insulin as follows: 
Total Daily Dose (TDD)= 0.5 units X body weight in kilograms 
The estimated TDD for a 70 kg person would be 35 units. 
Prescribe 50% of the Total Daily Dose as basal insulin and 50% as prandial insulin divided 
between three meals.  
In the example of the same 70 kg person, prescribe 18 u basal insulin once daily and 6 u rapid-
acting insulin three times daily before each meal. 
For the elderly, those at risk for hypoglycemia, or significant CKD, consider a lower multiplier, 
e.g 0.2-0.4 units X body weight in kilograms to determine the TDD. 

94 
 
Recommendations for Lipid Management in Patients with Diabetes and CKD 
A new KDIGO Clinical Practice Guideline for Lipid Management in CKD greatly simplifies the 
approach. Regardless of LDL, statins are recommended for all adult patients with both diabetes 
mellitus and non-dialysis-dependent CKD, unless there is a contraindication or statin-
intolerance. Initial assessment of fasting lipid profile is recommended, but routine reassessment 
of fasting lipids on statin treatment is not currently recommended. Specific KDIGO 
recommendations are as follows: 
Statin or statin/ezetimibe treatment is recommended for: 
• 
Adults ≥50 years with eGFR <60 ml/min/1.73 m2 but not treated with chronic dialysis or 
kidney transplant 
• 
 
Statin treatment is recommended for: 
• 
Adults ≥50 years with eGFR ≥60 ml/min/1.73 m2  
 
Statin treatment is recommended for: 
• 
Adults aged 18-49 years with CKD but not treated with chronic dialysis or kidney 
transplantation with one or more fo the following: 
 
o Known coronary artery disease (MI or coronary revascularization) 
o Diabetes Mellitus 
o Prior ischemic stroke 
o Estimated 10-year incidence of coronary death or non-fatal MI >10%. 
 
Drug treatment of hypertriglyceridemia in adults with CKD is not recommended but rather 
therapeutic lifestyle changes are advised. Therapeutic lifestyle changes include diet changes, 
weight reduction, increased exercise, reduction in alcohol consumption, and improvement in 
glucose control if indicated. In the case of severe hypertriglyceridemia (triglycerides >1000 
mg/dl), drug treatment with fibrates may be considered for patients with CK, but at doses 
adjusted for kidney function. 
KDIGO Guidelines recommend doses for statin use in CKD that are based on regimens and 
doses “shown to be beneficial in randomized trials done specifically in this population” (adults 
with eGFR <60 ml/min/1.73 m2 or on renal replacement therapy). 
See Protocol Table 3 for recommended doses of statins in mg/day for adults with CKD. 
 
 
 

95 
 
Protocol Table 3 
  
Protocol Table 3. From Kidney International Supplements (2013) 3(3), p. 274 
 

96 
 
Checklist for Patient Visits 
o Ask about symptomatic and asymptomatic hypoglycemia 
o Review how to recognize and self-manage hypoglycemia (Rule of 15) 
 
o Action point: If the patient is having hypoglycemia unawareness, frequent 
hypoglycemia, or severe hypoglycemia, liberalize glycemic targets for at least 
several weeks in order to allow recovery from hypoglycemia unawareness or 
prevent its onset. 
o Glucagon kits are recommended for those at risk for severe hypoglycemia. 
 
o Is the patient pregnant? Might the patient be pregnant? 
o For overweight or obese patients, encourage weight loss/maintenance through 
sustainable lifestyle interventions. As little as 5-10% reduction in body weight may result 
in significant improvement in glucose control. 
o Consider referral for medical nutrition therapy 
o Review with the patient exercise recommendations for adults with diabetes who can 
safely exercise:  
o At least 150 minutes/week of moderate intensity aerobic physical activity (50-
70% of maximal heart rate) over 3 days per week 
o Resistance training two days per week 
o Advise smoking cessation and stopping use of all tobacco products; refer for counseling 
if indicated 
o Confirm or administer annual influenza vaccine 
o Confirm or administer pneumococcal vaccine 
o Confirm yearly dilated retinal exam 
o Confirm yearly diabetic neuropathy screen (vibration and 10-gram microfilament tests) 
o Examine feet and instruct in foot self-exam by patients 
o Consider actions to reduce the patient’s cardiovascular risk profile 
o Consider statin therapy for all adults 18 or older with diabetes and CKD unless 
the patient is statin-intolerant or statins are contraindicated (e.g. pregnancy) 
o Follow protocols for management of hypertension to achieve  ≤140/90 
o Consider whether the patient would benefit from daily aspirin (75-162 mg/day) 
▪ 
10-year cardiovascular risk of >10% (includes most men >50 years and 
women >60 years who have at least one additional risk factor (family 
history of CVD, hypertension, smoking, dyslipidemia, albuminuria) 
o Review interval medical history and instances of hypoglycemia. Adjust A1C treatment 
target as appropriate 
o Consider screening for depression, especially if patient adherence is complicating 
glucose control 
o Review A1C and self-monitored glucose logbook and adjust antidiabetes medications to 
treat-to-target.  
 
 
 
 

97 
 
References 
American Diabetes Association Standards of Medical Care in Diabetes—2015. Diabetes Care. 
2015;38(Suppl. 1):S1-S93 
American Diabetes Association. Glycemic targets. Sec. 6. In Standards of Medical Care in 
Diabetes—2015. Diabetes Care 2015;38(Suppl.1): S33-S40 
Inzucchi SE et al. Management of hyperglycaemia in type 2 diabetes, 2015: a patient-centred 
approach. Update to the Position Statement of the American Diabetes Association and the 
European Association for the Study of Diabetes. Diabetologia (2015). Published online 13 
January 2015.  
KIDIGO Clinical Practice Guideline for Lipid Management in Chronic Kidney Disease. Kidney 
International Supplements (2013) 3(3), p. 259-30  
Lipska et al. Use of Metformin in the Setting of Mild-to-Moderate Renal Insufficiency. Diabetes 
Care. 2011, 34:1431-1437 
National Kidney Foundation. KDOQI Clinical Practice Guideline for Diabetes and CKD: 2012 
update. Am J Kidney Dis. 2012;60(5):850-886. 
Tuttle KR et al. Diabetic Kidney Disease: A Report From an ADA Consensus Conference. 
Diabetes Care. 2014;37:2864-2883 
VA/DoD Clinical Practice Guideline, Management of Diabetes Mellitus, 2010 
Wanner C et al. KDIGO Clinical Practice Guideline for Lipid management in CKD: summary of 
the recommendation statements and clinical approach to the patient. Kidney International 
(2014) 85;1303-1309