A Pragmatic, Randomized, Controlled Trial Examining the Effectiveness of a Hospital Discharge Follow-up Phone Call Program
Phase: NA
Conditions: Discharge Follow-up Phone Calls
Sponsor: Vanderbilt University Medical Center

A Pragmatic, Randomized, Controlled Trial 
Examining the Efficacy of a Hospital Discharge 
Follow-up Phone Call Program
Principal Investigator: Maame Yaa A. B. Yiadom, MD, MPH
NCT03050918
Protocol Date June 5, 2017

1 
A Pragmatic, Randomized, Controlled Trial  
Examining the Efficacy of a Hospital Discharge 
Follow-up Phone Call Program 
Principal Investigator: Maame Yaa A. B. Yiadom, MD, MPH 
Co-Investigators: Daniel Byrne, MS; Neesha Choma MD, MPH, FACP; Michele 
Hasselblad, RN, MSN, NE-BC; Johnston Morrison, MSN, RN, CPPS; Henry Domenico, 
MS; Sunil Kripalani, MD, MSc; Adam Lewis; Cheryl Gatto, PhD, CAPM; Frank Harrell 
PhD; Tina Hartert MD MSCI; Gordon Bernard, MD 
Funded by: Vanderbilt Institute for Clinical and Translational Research (VICTR) 
Draft or Version Number:  v.0.2 
June 5, 2017 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
Principal Investigator: 
 
     
Maame Yaa Yiadom, MD, MPH   
 
     
Department of Emergency Medicine 
 
Key Study Personnel: 
Daniel Byrne, MS 
 
 
     
Department of Biostatistics 
Neesha Choma MD, MPH, FACP 
            VUMC Quality and Patient Safety 
Michele Hasselblad, RN, MSN, NE-BC  
VUMC Medicine Patient Care Center 
Sarah Marlow, RN 
 
 
 
Phone Call Nurse 
Johnston Morrison, MSN, RN, CPPS 
VUMC Quality, Safety and Risk Prevention 
Henry Domenico, MS  
 
 
Department of Biostatistics 
Sunil Kripalani, MD, MSc 
 
 
Department of Medicine 
Gordon Bernard, MD  
 
 
Division of Pulmonary and Critical Care 
Cheryl Gatto, PhD, CAPM 
 
 
Vanderbilt Institute for Clinical & Translational Research (VICTR) 
Brittney E. Jackson 
 
 
 
Department of Emergency Medicine 
Adam Lewis, MS 
 
 
 
Data Core, VICTR 
Frank Harrell, PhD    
 
 
Department of Biostatistics 
Tina Hartert, MD, MPH 
 
 
Division of Allergy, Pulmonary, and Critical Care Medicine 
Monisha Bhatia  
 
 
 
Medical Student in Training  
Li Wang, MS  
 
 
 
Department of Biostatistics 
 
Abbreviations 
General Medical Services (GMS) 
Intention to Treat (ITT) 
Hospital Consumer Assessment of Healthcare Providers and Systems (HCHAPS) 
Vanderbilt University Medical Center (VUMC) 
Vanderbilt Institute for Clinical and Translational Research (VICTR) 
Center for Clinical Quality and Implementation Sciences Research (CCQIR) 
Post Hospital Discharge Follow-Up Phone Call Data Collection form (Phone Call Starform) 
Research Derivative (RD) 
Department of Quality, Safety and Risk Prevention (QSRP) 
Application Program Interface (API) 
Electronic Health Record (EHR) 
 
Study Summary 
Study Start: February 13, 2017 (1 week run-in period) 
Accrual Start: February 20, 2017 (NCT03050918) 
Primary Outcome: Readmission within 30 days 
 
Primary Analysis: Intention to Treat 
 
Study length/accrual period: ~7 months 
 
Follow up: 45 days 
 
Sample size: 3556 (1778 per arm) 
 
Baseline event rate = 13.5% 
 
Target detectable difference of 3.5% (13.5% controls, 10% intervention) 
 
Power 90% (chi square) 
Secondary Analyses: 
 
Subgroup Analysis of Primary Outcomes (forest plots + interaction analysis) 
 
Survival/Frequency Plot of Readmission events (0-45 days) 
 
Descriptive Demographics of Controls, Reached, Not Reached 
 
Heat Map of readmission rates by zip code 
 
 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
Figure 1 - Study Design Schematic and Enrollment Projection  
 
 
 
 
 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
STUDY TIMELINE: UPDATED 
 
1. Adult Executive Quality Committee 3 month Update - June 21, 2017 
  a. Analysis: Hank Domenico (descriptive, no outcome data) 
 
Table 1 - Patient demographics 
 
Overall VUMC readmission rate 
 
Summary of phone call nurse patient interventions 
  b.  Presenters: Dr. Maya Yiadom, Dr. Gordon Bernard, Michele Hasselblad 
 
2. Blinded Interim Analysis – 50% patient enrollment – ~July 2017 
  a. Content (Li Wang) 
 
2 week analysis window: Alpha 0.005, no stopping/futility rules 
 
Patient demographics (by study arm, Table 1) 
 
VUMC readmission rate by study arm and assessment of significant difference 
 
Pre-specified subgroup analysis for readmission yes/no 
 
Will not include the reachability index at this time. 
 
Will only use death data from VUMC and available Patient Satisfaction data 
 
See Appendix V for details 
 
  b. Safety Review – August 2017 
 
 
 
 
 
Safety Committee Members: Mitch Edgeworth, Dr. Jerry Hickson, Dr. Tina Hartert 
 
Review of Discharge Phone Call RN’s daily reports to her supervisors for safety issues. 
 
Interim Analysis Preparation and Presentation: Dr. Tina Hartert 
 
3. Enrollment End – 100% patient enrollment end: ~Sept 20, 2017 
  a. Readmit f/u end: ~Nov 5, 2017 
  b. Freeze database after Patient Satisfaction data (2mo lag) included: ~Nov 20, 2017 
  c. Re-open database to add death + external hospital readmission data (6-8mo lag): ~May 20, 2018 
  d. Death date source: VUMC EHR 
  e. External hospital readmission data source: Vanderbilt Health Affiliated Network (VHAN)  
 
4. Adult Executive Quality Committee Presentation - Study End Early Findings – Jan 2018 
  a. Final analysis findings, except for death data 
  b. 2 week analysis window: Alpha 0.048 
 
5. Final Analysis - June 2018 
  a. Content (Hank Domenico and Dan Byrne) 
 
2 week analysis window: Alpha 0.048 
 
Patient demographics (by study arm, Table 1) 
 
VUMC readmission rate by study arm and assessment of significant difference 
 
Pre-specified subgroup analysis for readmission yes/no 
 
Identical to the Interim Analysis plan except all patient satisfaction, external hospital readmission, and 
mortality data will be included. 
 
 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
BACKGROUND:  
 
Implementing a post-hospital discharge follow-up phone call program at Vanderbilt University Medical Center 
(VUMC) is expected to support effective patient transitions to out-patient care,1 improve patient satisfaction,2 
and elevate the quality of care delivered. It will, however, add to the existing care delivery workflow and involve 
hiring and training additional staff. Therefore, it is crucial to rigorously quantify the impact of this program 
before the existing program is scaled as a larger enterprise-wide health-system intervention.3 
 
OBJECTIVE 
 
The goal of this project is to quantify the impact of post-hospital discharge follow-up phone calls on hospital 
readmission within 30 days, emergency department (ED) visits, patient satisfaction, and mortality in a general 
medicine inpatient population. We will obtain exploratory information on patient sub-groups at high risk for 
readmission and those experiencing high benefit from the follow-up phone call intervention. In addition, we will 
obtain data on discharge plan implementation assistance needed to support a successful transition from 
inpatient to outpatient care amongst those reached by the intervention phone call. 
 
RATIONALE 
 
In the current medical literature, it is unclear how follow-up calls influence these outcomes in a general medical 
population. Some studies have attempted to address this question, but are limited in that they target very 
specific patient populations,4 are of insufficient quality, or evaluated follow-up calls as part of a larger care 
bundle.5 We will conduct a high quality, real-time clinical care study to determine the efficacy of a follow-up 
phone call program.  
 
STUDY DESIGN 
 
This is a single center, pragmatic, randomized, controlled clinical trial to investigate whether a structured post-
hospital discharge follow-up phone call can improve patients’ transition from in-hospital to outpatient care and 
improve satisfaction with their care. We will also identify the discharge implementation assistance given to 
those in the intervention (Phone Call) group. 
 
Outcome Measures 
Primary Outcome for this study is readmission within 30 days 
Secondary Outcomes include evaluating: The primary outcome of readmission within 30 days within pre-
specified subgroups (age, gender, race, health literacy level, established primary care status, patient 
satisfaction, Medicare readmission penalty diagnosis status, readmission risk score), patient satisfaction 
between the study arms measured as mean Hospital Consumer Assessment of Healthcare Providers and 
Systems (HCAHPS) patient satisfaction scores, all cause VUMC ED visits, the need for assistance with 
discharge plan implementation, and mortality within 30 days. 
 
Inclusion Criteria 
The study will include VUMC patients discharged after an inpatient status hospital stay on the following 
General Medicine services: Riven, Morgan, Geriatrics, and Palliative Care.  
 
Exclusion Criteria 
We will exclude all patients who experience in-hospital death, leave the hospital against medical advice, are 
transferred to any post-acute care facility or are discharged to inpatient hospice. 
 
Study Arms 
VUMC Quality Committee’s Post-Hospital Discharge Program is a quality initiative started in January of 2016 
where a single study nurse calls as many patients after discharge as she can reach.  Using a phone call 
intervention script and form (See Appendix I – Discharge Phone Call Starform) to guide the flow of each call 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
and screening for discharge intervention needs.  After discharge, patients will be randomized to one of 2 study 
arms.  Enrollment projections are included in Figure 1.  
 
Phone Call Group (Intervention Arm): Patients will first be called with a maximum of 3 call attempts by the 
study nurse made up until post-discharge day 7. The semi-structured script imbedded within the Discharge 
Phone Call Starform is used to guide a conversation to obtain information on potential causes of hospital 
readmission that can be identified and addressed to improve each patient’s transition to outpatient care. We 
will collect data on 1) outpatient care support provided to intervention group patients exposed to the phone call 
intervention (coordinating the receipt of durable medical equipment, facilitating a connection with home health, 
referral to PCP, referral to ED, requesting the assistance of case management or social work assistance for 
the patient, medication change initiated by the Phone Call Nurse, requesting pharmacist assistance with 
discharge plan details, requesting other health providers assistance, reminding the patient of planned follow up 
appointments, scheduling expected follow-up appointments, providing self-care education (wound care, diet, 
activity), providing medication dosing and administration education), 2) whether findings from the call generate 
a visit to emergency department or a hospital readmission. (See Appendix I’s Starform Data section) 
 
Usual Care Group (Control Arm): Patients assigned to the Control Group receive standard discharge planning 
and follow-up per the usual care of their medical providers.  
 
Data Collection 
Every weekday morning, a report will be generated from the Vanderbilt electronic medical record identifying all 
patients discharged from the hospital the previous day. This list will be transmitted securely to the study team.  
The list will then be randomized and uploaded to the study database within Research Electronic Data Capture 
(REDCap).  This will occur using code written in R linked with the application program interface (API) function 
of REDCap.  (See Appendix II – Randomization and REDCap API Database Upload Code). The code will 
upload patients assigned to the 2 study arms into separate database locations. The Intervention Arm Database 
includes a work list queue for the Study Phone Call Nurse.  In addition, she will document interventions 
delivered via a form (Appendix III - Intervention Data Capture Form) for each patient’s phone call encounter 
that will save this data as new variables within the database. 
 
The Study Phone Call Nurse will continue to complete an existing form within the electronic health record, the 
Phone Call Starform (Appendix I) to document care provided via the phone call.  For patients reached, the 
Study Phone Call Nurse will use the semi-structured script provided by the Starform to assess the patient’s 
understanding of their discharge plan, screen for discharge assistance needs, and inquire about new 
symptoms requiring patient referral. 
 
The majority of our study data will be obtained via Vanderbilt University Medical Center’s Research Derivative.  
These variables include: 1) VUMC based primary outcome (hospital readmission to VUMC) data, 2) secondary 
outcome measures (patient satisfaction scores, all cause ED visits within 30 days, identified the need for 
assistance with discharge plan implementation, and 30 day mortality), 3) Hospital readmission risk score 
calculated for each patient before discharge which is included as part of the medical record, and 4) pre-
specified subgroup identifiers (see Figure 1).  
 
The Research Derivative (RD)  is  a  database  of  clinical  and  related  data  derived  from  the Medical 
Center’s clinical systems and restructured for research. Data is repurposed from VU’s  enterprise data  
warehouse,  which  includes  data  from  StarPanel,  Vanderbilt Perioperative Information Management 
System,  ORMIS  (Operating  Room  Management  Information  System),  EPIC,  Medipac,  and  HEO order 
entry records among  others.  The medical  record  number  and  other  person  identifiers  are  preserved 
within the  database. Data  types  include  reimbursement  codes,  clinical  notes  and documentation,  nursing  
records,  medication  data,  laboratory  data,  encounter  and  visit data, among others. Output may include 
structured data points, such as ICD-9 codes or encounter dates, semi-structured  data such as laboratory tests 
and results, or unstructured data such as physician progress reports. The database is maintained by the Office 
of Research Informatics under the direction of Paul Harris, Ph.D. 
 
Not all patients returning to a hospital will be readmitted at Vanderbilt, and the Research Derivative data is 
limited to VUMC care. The inability to capture external health system readmission data is a major limitation of 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
readmission investigations. As a result, we have explored many methods to obtain external readmission data 
and found the use of the Vanderbilt Health Affiliated Network (VHAN) to be most feasible for this pragmatic 
study approach. We plan to overcome this obstacle, albeit in a limited way, by using the infrastructure of the 
Clinical Data Research Network (CDRN) to extract hospital admission and discharge data from VHAN.   
 
Health Literacy Information will be procured from the Center for Clinical and Implementation Sciences 
Research Data Core. 
 
A summary of all study variables is includes as Appendix IV – Study Data Summary. 
 
Figure 2 – Flow of Discharge Phone Call Study Data Collection 
 
 
Securely Reported to Study Team
Randomize and Record 
by Study Arm Assignment
(via R statistical code to study database in REDCap 
using its API function)
Discharged Patient List Generated
(Medical Center Admission & Discharge System)
Control Arm
(REDCap)
Intervention Arm
(REDCap)
Study Nurse Work List
Structured Phone Call 
Intervention
Phone Call Clinical Encounter 
Documented EHR Starform 
Data Extraction 
Starpanel - RD - CCQIR - QSRP - VHAN
(MS Excel or CSV files)
Data Import to Study Database
(REDCap)
Data Analysis
(R)

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
Confidentiality and Source Data 
Only key study personnel at the Data Coordinating Center, Vanderbilt University, will have access to the full 
study dataset which will be maintained in REDCap. 
 
Data Safety and Monitoring 
The interim analysis will be conducted by VICTR biostatistician Li Wang and Data Safety Monitor, Dr. Tina 
Hartert, Assistant Vice Chancellor for Translational Science. The results will be reviewed with the 3 member 
Safety Monitoring Committee including Dr. Hartert, VUMC Adult Enterprise Quality Committee: Mitch 
Edgeworth, CEO of Vanderbilt University Adult Hospital and Clinics; and Jerry Hickson, Chief Quality, Patient 
Safety and Risk Prevention Officer for VUMC. In addition to the study data analysis the Safety Committee will 
review 1) a 10% sample of the Phone Call Nurse’s daily reports to her supervisors which is an element of 
clinical care reporting and 2) a summary of potential safety concerns from the office overseeing this clinical 
program, the Medicine Patient Care Center.  The study team will remain blinded to outcome associated results. 
 
Sample Size Considerations  
Per inpatient hospital admission volume from October 2015 - September 2016, we estimate approximately 
3048 patients will eligible for the study over the 6 month study period. Of those ½ will be randomized to each 
study arm. Based on the experience of a current pilot with calls made by 1 nurse, we anticipate attempting to 
call 1117 patients and reaching 334 patients in the phone call group each month. We will analyze the impact of 
the program on the phone call population with a pre-specified subgroup analysis of those actually reached 
(See Figure 1 – Study Design Schematic and Enrollment Projection). 
 
Study Length and Timeline 
The informatics run-in period will begin February 7th, 2017 to test the Study Data Flow and integrity of the 
randomization process.  Official study enrollment will begin February 20th, 2017. Patients will be randomized 
the morning after hospital discharge.  Those receiving a call will be contacted within 7 days of hospital 
discharge. We will obtain interim impact estimates of the discharge phone call intervention at 50% enrollment 
for 80% power (See the Study Timeline, on page 2), and conduct the definitive analysis at 100% enrollment. 
In addition, the analyses will account for a 30 day re-admission observation window.  Fifteen additional days 
will be added to the follow-up period to assure re-admissions are not minimally deferred to just after the 30 
days period. Run-in period patient cases will be used to test the study data extraction and database upload 
process prior to the planned study analyses.  This will permit us to troubleshoot unforeseen data collection 
challenges. Given the sample size considerations noted above, we estimate a study length of 7 months with 
enrollment completion in September of 2017, primary outcome follow-up ending in November of 2017, and 
data collection completed in (due to data lags for patient satisfaction, external hospital readmission, and 
mortality data) May of 2018. 
 
ANALYSIS PLAN 
 
General Approach 
The study analysis will have 3 phases.  The primary analysis will examine our primary outcome, hospital 
readmission within 30 days, via an intention-to-treat analysis where comparisons will be made between the 2 
study arms.  We will then examine secondary outcomes of all cause ED visits to Vanderbilt or VHAN ED and 
mortality. Given VUMC’s interest in understanding characteristics of patients not reached via telephone, we will 
explore differences among those called and reached, called and not reached, and the control arm.   In these 3 
phases we will examine outcome differences by treatment assignment, age, gender, race, highest educational 
attainment, health literacy, established primary care status, patient satisfaction level, Medicare readmission 
penalty diagnosis status, and readmission risk score calculated at discharge as part of routine care at VUMC. 
Lastly, we will use descriptive statistics to quantify the need for patient assistance with discharge plan 
implementation (appointment scheduling or reminders, questions about new medications, durable medical 
equipment acquisition, referral for new symptoms, etc.) among patients in the intervention arm who are called 
and reached.   
 
Statistical Analysis 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
In our univariate analysis, differences among these patient characteristic groups will be assessed using the 
continuity corrected chi-square test or Mann-Whitney test for continuous outcomes and the Kruskal-Wallis test 
for categorical outcomes.  In our multivariate analysis, we will examine the relationship between treatment 
assignment and our secondary endpoints using logistic regression. The study is not powered for a time-to-
event analysis; however, we will explore time-to-readmission using the Cox proportional hazard model to 
understand the timing of when readmissions occur. In order to provide VUMC Leadership with preliminary 
efficacy data, we will perform an interim analysis at 50% enrollment (~3.5 months) followed by the final 
analysis at study completion months (~7 months). See Appendix V for details. We have pre-specified an α-
level of significance of 0.05 with penalties for a mid-study interim analysis per the O’Brian-Fleming alpha 
spending function allowing for an α-significance level of 0.005 for the interim analysis and 0.048 for the final 
analysis. 
 
Power Calculation 
The study design is targeted to achieve 80% power before October of 2017. Given our 0.048 alpha level for 
our final analysis, and controls anticipated to have a 13.52% readmission rate based on estimates,  this 
requires approximately 320 patients enrolled per month (n = 2234). We assessed the feasibility of this target 
after observing there were approximately 508 eligible patients per month based on medical center data 
collected from 10/1/2015 - 9/30/2016. We noted approximately 11% of these patient would need to be 
excluded after 
randomization due 
to mis-categorized 
hospital discharge 
status affecting 
study eligibility 
reducing potential 
monthly 
enrollment to 452 
(n = 3164, or 1582 
patients per arm). 
In Table 1, we 
illustrate conservative and ambitious enrollment scenarios with estimates for 80% and 90% power.  
Considering we have 1 Phone Call Study Nurse and will miss enrollment days for paid time off or sick days, we 
opted for a more conservative power target and detectable differences of 80% and 3.9% respectively.  This 
carries an associated enrollment of 1117 patent per arm (n = 2234, or 11 patients per day). 
 
POTENTIAL RISKS AND BENEFITS 
We anticipate minimal risk to patient as none will receive less than what was the VUMC standard discharge 
practice (no structured follow-up call) prior to the initiation of the phone call program in 2016.  In addition, there 
are no invasive tests or sensitive questions.  The phone call nurse currently is able to attempt calls for 75% of 
all discharged inpatient general medicine patients.  She successfully reaches 30% after an average of 2.1 call 
attempts. With study call efforts focused on the intervention arm we anticipate she will attempt a call for all 
patients assigned to the Phone Call Group, and complete up to 3 call attempts.  This may improve the 
intervention delivery rate. Patients that may have received a call before the study will not be exposed to 
potential benefits from the follow-up phone call.  This, however, is anticipated to balance with the patients in 
the intervention arm that would otherwise have not been exposed to a call.  Despite mixed results on the 
effectiveness of a discharge phone call program reported in the literature, we expect to observe a benefit from 
exposure to the phone call intervention,6 particularly in those found to require discharge plan implementation 
assistance.5 Other risks are related to potential breaches in confidentiality in the handling of patient protected 
health information (PHI).  To avoid this, all PHI will be transferred among key study personnel and stored using 
REDCap.  To avoid breaches in confidentiality induced by the Study Phone Call Nurse potentially sharing PHI 
with a friend, family member or stranger answering the patient’s phone, she requests identifying information 
before initiating a discussion of the patient discharge care plan.  Health proxies, caretakers or family members 
Table 1 - Power and Sample Size Scenarios
Control Group Readmission Rate† 
13.52%
13.52%
13.52%
13.52%
Intervention Group Readmission Rate
9.60%
9.10%
10.20%
9.70%
Power
80%
90%
80%
90%
Detectable Difference
3.9%
4.4%
3.3%
3.8%
Projected Study Sample Size
1117
1117
1582
1582
*2 group X^2 test of equal proportions (equal n's), 2-sided text, final analysis α = 0.048
† Historical VUMC readmission rates
Ambitious
Conservative

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
may be spoken to with the explicit verbal permission of the patient. This is the current standard of medical care 
for follow-up phone call health service and not specifically implemented for the purpose of this study. 
 
SIGNIFICANCE AND IMPACT  
 
The results of the primary endpoint analysis of this study will inform an evidence-based VUMC decision on 
whether to invest in a hospital discharge follow-up phone call program for medical patients across the 
enterprise. If launched, our secondary outcome analyses results will inform the design of the program to 
maximize patient benefit. We intend to publish our result in the medical literature to contribute to knowledge on 
the efficacy of post-hospital discharge follow-up phone calls as a means of delaying hospital readmissions, 
improving patient’s transition from inpatient to outpatient care, and improving patient satisfaction. 
 
REFERENCES 
 
1. 
Harrison PL, Hara PA, Pope JE, Young MC, Rula EY. The impact of postdischarge telephonic follow-up 
on hospital readmissions. Popul Health Manag. 2011 Feb;14(1):27-32. PMID: 21090991 PMCID: 
PMC3128446 
 
2. 
Dudas V, Bookwalter T, Kerr KM, Pantilat SZ. The impact of follow-up telephone calls to patients after 
hospitalization. Am J Med. 2001 Dec 21;111(9B):26S–30S. PMID: 117903651.  
Weisman DS, Bashir 
L, Mehta A, Bhatia L, Levine SM, Mete M, Padmore JS. A medical resident post-discharge phone call 
study. Hosp Pract (1995). 2012 Apr;40(2):138–146. PMID: 22615088 
 
3. 
Wong, F. K. Y. et al. Economic evaluation of the differential benefits of home visits with telephone calls 
and telephone calls only in transitional discharge support. Age Ageing 44, 143–147 (2015).Ashton CM, 
Del Junco DJ, Souchek J, Wray NP, Mansyur CL. The association between the quality of inpatient care 
and early readmission: a meta-analysis of the evidence. Medical care. 1997 Oct 1:1044-59. 
 
4. 
Wong, F. K. Y., Chow, S. K. Y., Chan, T. M. F. & Tam, S. K. F. Comparison of effects between home 
visits with telephone calls and telephone calls only for transitional discharge support: a randomised 
controlled trial. Age Ageing 43, 91–97 (2014). 
 
5. 
Kripalani S, Theobald CN, Anctil B, Vasilevskis EE. Reducing Hospital Readmission: Current Strategies 
and Future Directions. Annual review of medicine. 2014;65:471-485. doi:10.1146/annurev-med-022613-
090415. 
 
6. 
O’Connor, C.M., and Fiuzat, M. (2010). Is Rehospitalization After Heart Failure Admission a Marker of 
Poor Quality? Time for Re-Evaluation. Journal of the AmericanCollege of Cardiology, 56(5), 369-371 
 
7. 
Wong FKY, Chow SKY, Chan TMF, Tam SKF. Comparison of effects between home visits with telephone 
calls and telephone calls only for transitional discharge support: a randomised controlled trial. Age 
Ageing. 2014 Jan;43(1):91–97. PMCID: PMC3861338 
 
8. 
Soong C, Kurabi B, Wells D, Caines L, Morgan MW, Ramsden R, Bell CM. Do post discharge phone calls 
improve care transitions? A cluster-randomized trial. PLoS ONE. 2014;9(11):e112230. PMCID: 
PMC4227814 
 
9. 
Wong FKY, So C, Chau J, Law AKP, Tam SKF, McGhee S. Economic evaluation of the differential 
benefits of home visits with telephone calls and telephone calls only in transitional discharge support. 
Age Ageing. 2015 Jan;44(1):143–147. PMCID: PMC4255617 
 
10. Melton LD, Foreman C, Scott E, McGinnis M, Cousins M. Prioritized post-discharge telephonic outreach 
reduces hospital readmissions for select high-risk patients. Am J Manag Care. 2012 Dec;18(12):838–
844. PMID: 23286612 
 
11. Balaban RB, Weissman JS, Samuel PA, Woolhandler S. Redefining and redesigning hospital discharge 
to enhance patient care: a randomized controlled study. J Gen Intern Med. 2008 Aug;23(8):1228–1233. 
PMCID: PMC2517968 
 
12. Goldman LE, Sarkar U, Kessell E, Guzman D, Schneidermann M, Pierluissi E, Walter B, Vittinghoff E, 
Critchfield J, Kushel M. Support from hospital to home for elders: a randomized trial. Ann Intern Med. 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
2014 Oct 7;161(7):472–481. PMID: 25285540 
 
13. Mistiaen P, Poot E. Telephone follow-up, initiated by a hospital-based health professional, for 
postdischarge problems in patients discharged from hospital to home. Cochrane Database Syst Rev. 
2006 Oct 18;(4):CD004510. PMID: 17054207 
 
14. Chan B, Goldman LE, Sarkar U, Schneidermann M, Kessell E, Guzman D, Critchfield J, Kushel M. The 
Effect of a Care Transition Intervention on the Patient Experience of Older Multi-Lingual Adults in the 
Safety Net: Results of a Randomized Controlled Trial. J Gen Intern Med. 2015 Dec;30(12):1788–1794. 
PMCID: PMC4636586 
 
15. Dudas V, Bookwalter T, Kerr KM, Pantilat SZ. The impact of follow-up telephone calls to patients after 
hospitalization. Dis Mon. 2002 Apr;48(4):239–248. PMID: 12021756 
 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
APPENDIX I - Follow Up Phone Call Data Collection Form (Phone Call Starform) 
 
Provider (indexing): 
(*** This will change the provider displayed in the all documents listing of StarPanel. ***) 
*Standard 
Document Name: 
Comment for Indexing (optional): 
 
VANDERBILT UNIVERSITY MEDICAL CENTER 
POST DISCHARGE TELEPHONE CALL 
 
Date of Discharge: 
 
 
Patient Home Phone: 
 
 
CALL INFO: 
Call Attempt Date and Time: 
 
 
Contact Attempts:  
 
Caller:  
 
Pre-Call Prep 
Time:  
 
Call Duration: 
 
Pt Location: 
 
Call Successful  
Call Unsuccessful
Call Unnecessary
Phone Call Occurred with: 
 
 
 
 
 
 
INTRODUCTION: 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
 
Hello, 
, this is 
from Vanderbilt. I am calling to follow-up with you 
after your recent visit to our hospital. I'd like to ask you a few questions to make sure everything is 
going ok. This could take 10 to 15 minutes - Is this a good time to talk? 
 
If Yes proceed; 
 
If No - can you give me a time that would be better and I will call you back? 
I see you were in the Hospital for [x]. How are you feeling? 
Comments:  
 
DISCHARGE INSTRUCTIONS 
 
Click HERE for Discharge Instructions 
 
 
I want to make sure the discharge instructions we gave you were clear and understandable... 
Can you please tell me in your own words how you are caring for yourself at home? 
 
What questions do you have about your discharge instructions?  
o If none... Great - if something were to come up, what would you do to get your 
questions answered? 
 
Are you having any unusual symptoms or problems? (Specific to problem *base this on the 
discharge summary* - i.e. dressing, PAIN, bruising or swelling, N/V; e.g., Do your favorite 
pair of shoes still fit?) 
Patient can teach back self-care 
Yes 
No 
Partial 
Provider contacted for pain/symptoms/complications 
Yes 
No 
Comments: 
 
 
FOLLOW-UP APPOINTMENT  

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
 
When is your follow-up appointment? 
Follow-up appointment change made based on this call 
Yes 
No 
Able to teach back follow-up appointment related to hospitalization 
Yes 
No 
Comments: 
 
MEDICATIONS: 
 
*Are new prescriptions identified on the discharge summary?  
 
Yes – 
o I see you have [number] new medicines from your hospital visit.  How are you 
tolerating taking your [medication]? (follow protocol if you find patient has not 
filled prescriptions) 
o Would you talk through your daily plan for taking all your medicines 
o What questions do you have about your medicines 
 
No –  
o I see we didn’t prescribe any new medicines when you left the hospital. Is that still 
correct?  
o Yes: Great – do you take any other medicines on a regular basis?    
 
Would you talk through your daily plan for taking your medicines?   
 
Do you have any questions about your medicines?   
o No: Ok, what medicines did you get? How are you tolerating taking your new 
medicines?  
 
Would you talk through your daily plan for taking your new medicines and 
any others you take on a regular basis?              
 
What questions do you have about your medicines? 
Able to teach back medications 
Yes 
No 
Partial 
Has obtained medications 
prescribed at discharge 
Yes 
No 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
Partial 
Medication education or 
clarification was needed 
Yes 
No 
Medication change made by 
caller/provider based on phone 
call 
Yes 
No 
Comments: 
 
Meds Editor: (Click to expand/collapse)  

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
 
 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
CLOSING:  
 
Thank you for talking with me. We are always trying to get better at giving excellent care. 
Is there one thing that comes to mind for you that we can improve on? 
 
You will be getting a survey in the mail asking about your experience during your hospital 
stay. We would appreciate you taking the time to give us your feedback. It is very important 
to us and should only take you about five minutes.  
 
Do you need anything from us right now?  
o Ok we wish you all the best in your recovery.  If you need anything, please contact 
us at [phone number] 
Comments: 
 
 
 
 
      
 
 
 
  Form:  post_discharge_telephone_call (Post Discharge Telephone Call) 
  Version:  2.4 
  Last modified:  $Date: 2015/12/21 18:22:48 $ 
   
 
 
 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
Appendix II - R Code Template for Daily Patient Cohort Randomization and  
Upload to the REDCap Study Database 
 
#Load Necessary Libraries 
library(RCurl) 
library(readr) 
 
#Set your file path to the folder where BOR report is stored 
setwd("D:/Data/Documents/Temp Work computer/FU Phone Call/Randomization") 
 
#Will upload BOR csv corresponding to today's date 
filename <- paste("discharge_report_",format(Sys.Date(), "%m-%d-%Y"),".csv", sep = "") 
filename <- paste("discharge_report_", Sys.Date(),".csv", sep = "") 
data <- read.csv(file = filename) 
 
#Sets a seed based on today's date for reproducibility 
set.seed(floor(as.numeric(Sys.Date())^1.5)) 
 
#Samples a random 1/2 of rows to be included in the intervention group. Will randomly round up or down if an 
odd number of rows. 
sample_rows <- sample(1:nrow(data), sample(c(floor(nrow(data)/2), ceiling(nrow(data)/2)), 1), replace = F) 
random_group <- rep("B", nrow(data)) 
random_group[sample_rows] <- "A" 
data <- data.frame(data, random_group) 
 
#Saves intervention and control patients to separate datasets 
data_intervention <- data[data$random_group == 'A',] 
data_control <- data[data$random_group == "B",] 
 
#Change directory to store intervention patients in Intervention Folder 
setwd("D:/Data/Documents/Temp Work computer/FU Phone Call/Randomization/Intervention") 
 
#Saves intervention patients with date stamp 
write.csv(data_intervention, file = paste("data_intervention", Sys.Date(),".csv", sep = ""), row.names = F) 
 
#Creates data object containing the intervention patients that can be uploaded to REDCap 
Data.INT <- read_file(paste("data_intervention", Sys.Date(),".csv", sep = "")) 
 
#Uploads data to redcap, paste API token for project 2 below 
result_intervention <- postForm( 
  uri='https://redcap.vanderbilt.edu/api/', 
  token='0F5278ECF8493BDA2A5FB71EBE828110', 
  content='record', 
  format='csv', 
  type='flat', 
  overwriteBehavior='normal', 
  data=Data.INT, 
  returnContent='count', 
  returnFormat='json' 
) 
 
print(result_intervention) 
 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
#Change directory to store Control patients in Control Folder 
setwd("D:/Data/Documents/Temp Work computer/FU Phone Call/Randomization/Control") 
 
#Saves control patients with date stamp 
write.csv(data_control, file = paste("data_control", Sys.Date(),".csv", sep = ""), row.names = F) 
 
#Creates data object containing the Control patients that can be uploaded to REDCap 
Data.Control <- read_file(paste("data_control", Sys.Date(),".csv", sep = "")) 
 
#Uploads data to redcap, paste API token for project 1 below 
result_control <- postForm( 
  uri='https://redcap.vanderbilt.edu/api/', 
  token='6EA859FA6C7F35B11CAAAA744ADAAC48', 
  content='record', 
  format='csv', 
  type='flat', 
  overwriteBehavior='normal', 
  data=Data.Control, 
  returnContent='count', 
  returnFormat='json' 
) 
 
print(result_control) 
 
 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
Appendix III – Intervention Data Capture Form 
 
Discharge Follow Up Phone Call 
 Editing existing Encounter Number 12345678901 
Encounter Number 
12345678901 
To rename the record, see the record action drop-down 
at top of the Record Home Page. 
Current Date and time 
 
    NowM-D-Y H:M 
Discharge Team 
 
 
Discharge Team Group 
 
 
MRN 
 
 
Name 
 
 
BHLS 
 
 
Education 
 
 
Admit Date/Time 
 
    NowM-D-Y H:M 
Discharge Date and time 
 
    NowM-D-Y H:M 
Hours Since Discharge (auto-calculated, ineligible for call after 168 hours) 
 
  View equation 
Tele 
 
 
PCP Name 
 
 
PCP ID 
 
 
Patients Preferred Language 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
 
Date of First Contact 
 
    TodayM-D-Y 
Call Attempts 
 
 
Date of Last Contact 
 
    TodayM-D-Y 
Status 
 
 
Interventions Delivered (check all that apply) 
 
 
Durable Medical Equipment 
Facilitated Home Health Connection 
Referral to PCP (pt instructed to call) 
Referral to ED (pt instructed to go) 
Case Management/Social Work 
assistance requested 
Medication Change by Call RN 
Pharmacist assistance requested 
Provider assistance requested 
Planned Follow Up Appt Reminder 
Planned Follow Up Appt Scheduled 
Self-care teaching (wound care, diet, 
activity) 
Medication education provided 
Other 
Notes 
 
 
 
Expand  
Form Status 
Complete? 
 
 
 

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
Appendix IV- Study Variable Summary 
 
 
 
 
 
Phone Call Study Patient Variates
BASELINE PATIENT DATA
INDEX HOSPITALIZATION DATA
CALL INTERVENTION DATA
First name
Intervention Arm
1st Contact
Last name
Encounter Number
Time of first call
Zipcode
Date of admission
Date of first call
Medical record number
Time of admission
Final Contact
Established Primary Care Yes
Admission day of the week
Time of Final Contact
No 
Admission Diagnosis #1
Date of Final Contact
Admission Diagnosis #2
Call attempts
Health Literacy
BHLS
Admission Diagnosis #X
1
Education level
Highest bed level
2
Floor
3
Race
Black
ICU
Not eligible
White
Discharge Service
AMA
Latino
Riven
Facility Placement
Non-white Hispanic
Morgan
Deceased
Multiple Races
Geriatrics
Already seen in clinic
Unknown
Palliative Care
CRC patient
Discharge Diagnosis #1 (ICD-10)
Patient currently admitted/readmitted
Primary Language
English
Discharge Diagnosis #2 (ICD-10)
Call status
Spanish
Discharge Diagnosis #3 (ICD-10)
Success
Arabic
Discharge Diagnosis #4 (ICD-10)
Unsuccessful - Wrong Number
Other
Discharge Diagnosis #X (ICD-10)
Unsuccessful - Refused
Discharge Date
Unsuccessful - Patient Call Back Requested
Number of Hospitalizations in Prior Year
Discharge Time
Unsuccessful - Patient Not Available
Discharge Location/Disposition
Unsuccessful - No Answer
Complicating Baseline Comorbidities (Natural Language Processing)
Unsuccessful - Patient Never Admitted
Congestive heart failure
Unsuccessful - Left a Message
COPD
Number of medications upon discharge
Unsuccessful - Patient in Hospital
VUMC Cornelius Readmission Risk Score
Unnecessary (already seen in clinic)
Diabetes
Patient satisfaction (Press Ganey Score, 1-5)
Can teach back self care
Outpatient hospice
Yes
Substance abuse
READMISSION HOSPITALIZATION DATA
No
Depression
Date of admission
Partial
Time of admission
Pt aware of follow up appointment
Admission Diagnosis #1
Yes
Admission Diagnosis #2
No
Admission Diagnosis #X
Able to teach-back follow up appointment
Highest bed level
Yes
Floor
No
ICU
Partial
Discharge Diagnosis #1 (ICD-10)
New Meds Upon Discharge
Discharge Diagnosis #2 (ICD-10)
Yes
Discharge Diagnosis #3 (ICD-10)
No
Discharge Diagnosis #4 (ICD-10)
Able to teach-back current medications dosing
Discharge Diagnosis #X (ICD-10)
Yes
No
Discharge Date
Partial
Discharge Time
Has obtained medications prescribed at discharge
Discharge Location
Yes
Patient satisfaction (Press Ganey Score, 1-5)
No
Discharge Implementation Assistance Required
Extra-Institutional Data
Provider contacted for pain/symptom/complication
Survival Data (at 30 days)
Durable Medical Equipment 
Facilitated Home Health Connection
Referral to PCP (pt instructed to call)
 (minimum data = yes/no)
Referral to ED (pt instructed to go)
Case Management/Social Work Assistance Requested
Medication Dose Change by Call RN
Pharmacist assistance requested
Provider assistance requested
Planned Follow Up Appt Reminder
Planned Follow Up Appt Scheduled
Medication education provided
Total Intervention Time (call prep, phone time, care coordination)
Readmission penalty dx  - AMI, HF, PNA, COPD, 
CABG, Total hip/knee repair, and stroke
Readmission penalty dx  cohort- AMI, HF, PNA, 
COPD, CABG, Total hip/knee repair, and stroke
Readmission penalty dx  - AMI, HF, PNA, COPD, 
CABG, Total hip/knee repair, and stroke
Non-VUMC TN Readmission (at 30 days post VUMC 
admit)

A Pragmatic, Randomized, Controlled Trial Examining the  
Efficacy of a Hospital Discharge Follow-up Phone Call Program 
 
 
Appendix V – Interim Analysis Plan 
INTERIM ANALYSIS PLAN 
 
1. Consort Diagram (Consort Diagram – Figure 1) 
a. Pts Enrolled  
b. Pts Randomized  
c. Post-Randomization exclusions by arm total count and rate (including reasons with counts) 
  
2. Adverse Events Summary 
a. All Pts: Results of a debriefing with the Medicine Patient Care Center for incidents that  
i. Raised concerns that the phone calls may introduce harm or create and issue 
(i.e. – MVC s/p picking up call from the Phone call RN, d/c plan confusion introduced by phone 
call RN involvement, etc) 
b. Intervention Pts: Unmet need upon initial discharge (Summarized in Table 3, see below) 
      
3. Co-Variate Distribution (Table 1)  
a. Patient: Age, sex, zip code, established primary care, BHLS, education level, race, primary language, 
VUMC admits in prior 6 mo, VUMC ED visits in prior  6 mo, PMHx (7 readmit penalty diagnoses, DM, 
outpatient hospice, substance abuse, depression)  
b. Index Admission: Admit diagnosis, # meds upon discharge,  Cornelius score, Any ICU time, meds-to-beds 
program exposure, %weekend discharges, % discharges after 4pm, Hospital LOS 
  
4. Outcome Analysis (ITT analysis for stat significant differences) 
a. VUMC Readmission Rate  
i. Rates (Table 2 – 2x2 Table) 
ii. Descriptives for proportion readmit penalty diagnosis 
b. Time to VUMC readmission 
i. Kaplan-Meier Curve (Figure 2) 
c. VUMC ED Revisit Rate 
d. Patient Satisfaction (Press Ganey) 
  
5. Intervention Delivery 
a. Intervention Delivery Rate: Successful Calls 
b. Unsuccessful Calls and Reason (wrong number, refused, call back requetsed, no answer, never 
admitted, left a message, in hospital) 
c. #Call Attempts to success: proportion 1, 2, 3, mean, median 
d. Time-to-Successful Call (adjusted for first call?) 
e. Total Intervention Time: mean/SD, median/IQR 
f. 
Discharge Implementation Assistance Provide: (Table 3 - Frequencies, %) 
- 
Any (Count, % of Total) 
- 
Provider contact for a new symptom/complication 
- 
Durable medical equipment 
- 
Facilitate home health connection 
- 
Referral to PCP (pt to call) 
- 
Referral to ED (pt told to go) 
- 
Case mgmt./Social work assistance requested 
- 
Med dose change by Call RN 
- 
Pharmacist assistance requested 
- 
Planned F/U appt reminder 
- 
Planne F/U appt scheduled 
- 
Med Education provided 
  
6. VUMC Admission Trend (Figure 3 – Admission Rates from Feb 20 – Sept 20 2017) 
    
7. Stopping Rules (none) 
   
8. Checking Readmission Rate Assumption 
a. adjusted sample size calculation (if needed)