A Multicenter RCT of Pharmacist-Directed Transitional Care to Reduce Post-Hospitalization Utilization
Phase: NA
Conditions: Nonadherence, Patient, Polypharmacy, Readmission
Sponsor: Cedars-Sinai Medical Center

A Multicenter RCT of Pharmacist-Directed Transitional Care to 
Reduce Post-Hospitalization Utilization  
Study Protocol 
 
Final Version (version 16) from Aug 25, 2023 
NCT04071951 
 
  

PHARMacist Discharge Care (PHARM-DC)  
 
Protocol Number: 3.0 
National Clinical Trial (NCT) Identified Number: NCT04071951   
Principal Investigator: Dr. Joshua Pevnick  
Funded by: National Institute of Aging 
Version Number: 16.0 
2023.08.25 

  
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Table of Contents 
STATEMENT OF COMPLIANCE ............................................................................................................................. 1 
1 
PROTOCOL SUMMARY ............................................................................................................................... 1 
1.1 
Synopsis ................................................................................................................................................ 1 
1.2 
Specific aims ........................................................................................................................................ 3 
1.3 
Schedule of Activities (SoA) ............................................................................................................... 5 
2 
INTRODUCTION ............................................................................................................................................ 7 
2.1 
Study Rationale .................................................................................................................................... 7 
2.2 
Background........................................................................................................................................... 8 
2.3 
Risk/Benefit Assessment .................................................................................................................. 11 
2.3.1 
Known Potential Risks ................................................................................................... 11 
2.3.2 
Known Potential Benefits .............................................................................................. 12 
3 
OBJECTIVES AND ENDPOINTS .............................................................................................................. 13 
4 
STUDY DESIGN ........................................................................................................................................... 14 
4.1 
Overall Design .................................................................................................................................... 14 
5 
STUDY POPULATION ................................................................................................................................ 15 
5.1 
Inclusion Criteria ................................................................................................................................ 15 
5.2 
Exclusion Criteria ............................................................................................................................... 16 
5.3 
Strategies for Recruitment and Retention ...................................................................................... 16 
6 
STUDY INTERVENTION ............................................................................................................................ 17 
6.1 
Study Intervention(s) Administration ............................................................................................... 17 
6.1.1 
Study Intervention Description ..................................................................................... 17 
6.2 
Measures to Minimize Bias: Randomization and Blinding ........................................................... 18 
6.3 
Study Intervention Compliance ........................................................................................................ 18 
7 
STUDY INTERVENTION DISCONTINUATION AND PARTICIPANT 
DISCONTINUATION/WITHDRAWAL .................................................................................................................... 19 
7.1 
Lost to Follow-Up ............................................................................................................................... 19 
7.2 
Adverse Events and Serious Adverse Events ............................................................................... 19 
7.2.1 
Definition of Adverse Events (AE) ............................................................................... 19 
7.2.2 
Definition of Serious Adverse Events (SAE) .............................................................. 19 
7.2.3 
Classification of an Adverse Event .............................................................................. 19 
7.2.4 
Time Period and Frequency for Event Assessment and Follow-Up ....................... 20 
8 
STATISTICAL CONSIDERATIONS .......................................................................................................... 20 
8.1 
Statistical Hypotheses ....................................................................................................................... 20 
8.2 
Sample Size Determination .............................................................................................................. 20 
8.3 
Populations for Analyses .................................................................................................................. 21 
8.4 
Statistical Analyses............................................................................................................................ 21 
8.4.1 
General Approach .......................................................................................................... 21 
8.4.2 
Analysis of the Secondary Endpoint(s) ....................................................................... 22 
8.4.3 
qualitative Analyses ....................................................................................................... 22 
8.4.4 
Cost-effectiveness analyses ......................................................................................... 23 
8.4.5 
Secondary data analysis: Examine effects of PHARM-DC intervention on 
initiation and deprescribing of benzodiazepine-receptor agonists ............................................................. 24 
8.4.6 
Secondary data analysis: Examine effects of PHARM-DC intervention on fall-
related injuries among older adults with Alzheimer9s disease and related dementias ........................... 25 
8.4.7 
Secondary data analysis: PROPENSITY SCORE ANALYSIS at BRIGHAM AND 
WOmen9s hospital 26 

  
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9 
SUPPORTING DOCUMENTATION AND OPERATIONAL CONSIDERATIONS .............................. 27 
9.1 
Regulatory, Ethical, and Study Oversight Considerations ........................................................... 27 
9.1.1 
Informed Consent Process ........................................................................................... 27 
9.1.2 
Confidentiality and Privacy ........................................................................................... 30 
9.1.3 
Key Roles and Study Governance .............................................................................. 31 
9.1.4 
Safety Oversight ............................................................................................................. 31 
9.1.5 
Data Handling and Record Keeping ............................................................................ 31 
9.1.6 
Publication and Data Sharing Policy ........................................................................... 32 
9.1.7 
Conflict of Interest Policy .............................................................................................. 33 
9.2 
Protocol Amendment History ........................................................................................................... 34 
10 
APPENDIX A ................................................................................................................................................. 37 
11 
REFERENCES ............................................................................................................................................. 38 
 

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1 
STATEMENT OF COMPLIANCE 
 
(1) [The trial will be carried out in accordance with International Conference on 
Harmonisation Good Clinical Practice (ICH GCP) and the following:  
 
• 
United States (US) Code of Federal Regulations (CFR) applicable to clinical studies 
(45 CFR Part 46, 21 CFR Part 50, 21 CFR Part 56, 21 CFR Part 312, and/or 21 CFR 
Part 812)  
 
National Institutes of Health (NIH)-funded investigators and clinical trial site staff who are 
responsible for the conduct, management, or oversight of NIH-funded clinical trials have 
completed Human Subjects Protection and ICH GCP Training. 
 
The protocol, recruitment materials, and all participant materials will be submitted to the 
Institutional Review Board (IRB) for review and approval.  Approval of both the protocol 
and information sheets will be obtained before any participant is enrolled.  Any 
amendment to the protocol will require review and approval by the IRB before the 
changes are implemented to the study.  In addition, all changes to the information sheets 
will be IRB-approved. 
 
1 
 
PROTOCOL SUMMARY 
1.1 SYNOPSIS  
Title: 
PHARMacist Discharge Care (PHARM-DC) 
Study Description: 
To implement evidence-based pharmacist-led strategies for 
preventing ADEs after hospitalization, use implementation science 
methodology to study implementation at two large medical centers, 
and examine the cost-effectiveness of the intervention.  
There are three components to this study: (1) the prospective, 
randomized trial, which includes a pharmacist-led hospital discharge 
care intervention, (2) the qualitative study, which involves focus 
groups and interviews, and (3) a cost-effectiveness study, which 
involves a review of the literature and a time-and-motion study 
component. 
Objectives: 
 
(1) Pharmacist-led Hospital Discharge Care Intervention: To test 
the effect of PHARMacist Discharge Care (PHARM-DC) 
Toolkit on post-discharge utilization among patients most at 
risk for post-discharge adverse drug events (ADEs): recently 
discharged older adults taking >10 chronic prescription 
medications or >3 high-risk medications.  
(2) Qualitative study: To study barriers and facilitators of 
implementing PHARM-DC at two sites, Cedars-Sinai Medical 
Center (CSMC) and Brigham and Women9s Hospital (BWH) 
using a qualitative study.  

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(3) Cost-Effectiveness Study: To analyze the costs of PHARM-
DC, including the incremental cost per readmission averted 
and the net incremental cost from the health system 
perspective using a time-and-motion study and cost-
effectiveness analysis.  
 
Endpoints: 
Pharmacist-led Hospital Discharge Care Intervention: 
Primary Endpoint: 30-day post-discharge utilization, including 
same-hospital utilization data and same-state 30-day hospital 
readmissions and ED visits. 
 
Secondary Endpoints: To assess the Reach of the intervention, we 
will examine differences in effectiveness across sites, and for 
patients of different ages, sex, taking different numbers of 
medications, with different comorbidities/diagnoses, and living in zip 
codes reflecting different median incomes. 
 
Study Population: 
The study population includes individuals being discharged from the 
hospital at high risk for adverse drug events. Inclusion criteria 
includes individuals being discharged from a medical/surgical ward 
and either being 55 years of age or older and having 10 or more 
chronic prescription medications, or using three or more high-risk 
medications before or during hospitalization. 
 
Description of 
Sites/Facilities 
Enrolling 
Participants: 
Two sites will participate in this study: an academic medical center 
(Brigham and Women9s Hospital in Boston, Massachusetts) and a 
university-affiliated community hospital (Cedars-Sinai Medical 
Center in Los Angeles, California 1) that has some community 
physicians. 
 
Description of Study 
Intervention: 
Pharmacist-led Hospital Discharge Care Intervention: 
Eligible pharmacists (those with training in transitions of care) at the 
two sites will receive a list of patients currently admitted to the 
hospital who meet the inclusion/exclusion criteria. Eligible patients 
will meet with a clinical pharmacist for medication reconciliation.  
Clinical pharmacists will conduct an initial medication regimen 
assessment, which will use tools in the PHARM-DC Toolkit to identify 
potentially inappropriate medications. Patients and/or their 
caregivers will undergo a pre-discharge intervention, where clinical 
pharmacists will anticipated discharge medication changes.  
The Toolkit content and 1-2 hours of introductory training add three 
major components: 
1. Pharmacists will use the PHARM-DC Toolkit, which 
summarizes the evidence for post-discharge medication 
management. The Toolkit includes a (1) the Start Actions for 
Assessing Adherence Barriers worksheet, integrated into an 
Epic template, (2) the Beers Medication List, (3) Pre-Discharge 
Worksheet, integrated into an Epic template, (4) Up-to-Date 

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Section on prescribing to older adults, (5) Discharge 
Worksheet, integrated into an Epic template, (6) Post-
Discharge Worksheet, integrated into an Epic template.   
 
2. Pharmacists will assess patient needs and customize 
accordingly. All patients will receive one discharge counseling 
visit and one post-discharge phone call, but pharmacists will 
find that some patients need further phone calls, interventions, 
referrals, or other interactions. 
 
During training, trainers will emphasize to pharmacists 
participating in this study additional, clinically-indicated 
services may be provided to control group patients to ensure 
that it is clear that routine services that are part of the 
PHARM-DC and that the toolkit should not be withheld from 
the control group if they are clinically indicated.   
 
 
Study Duration: 
36 months 
Participant Duration: 
Participation during one hospital admission/discharge 
 
 
1.2 SPECIFIC AIMS 
Our PHARM-DC toolkit improves upon the intervention in our prior trial by incorporating 
evidence-based pharmacist-led strategies for preventing ADEs after hospitalization. To go 
beyond just instructing pharmacists to counsel and call patients, we systematically searched the 
literature for medication management interventions addressing medical conditions most likely to 
lead to readmission among older adults taking >10 chronic prescription medications or >3 high-
risk medications. As such, the toolkit incorporates new evidence involving deprescribing 
interventions to address polypharmacy, as well as from a multidisciplinary technical expert 
panel. 
This study uses a pragmatic trial randomized at the patient level and conducted in two large 
hospitals to achieve the following aims, each of which has been designed using the RE-AIM 
framework: 
Aim 1:  
To test the effect of PHARM-DC on post-discharge utilization among patients 
most at risk for post-discharge ADEs: recently discharged older adults taking >10 medications 
or >3 high-risk medications using a prospective, randomized, pragmatic multi-site study. 
Aim 2:  
To study barriers and facilitators of implementing PHARM-DC using a qualitative 
study. 
Aim 3:  
To analyze the costs of PHARM-DC, including the incremental cost per 
readmission averted and the net incremental cost from the health system perspective using a 
time-and-motion study and a cost-effectiveness analysis. 
 
 
Figure 1: Flow diagram for PHARM-DC Discharge Intervention 

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Prior to  
Enrollment 
 
 
 
 
 
 
 
 
 
 
Hospital Day 1 
or as soon  
as possible 
 
 
 
 
 
 
 
 
 
 
 
 
Discharge Day 
 
 
 
 
 
 
 
 
 
 
 
 
 
1-3 Days Post- 
Discharge 
 
1. Using a daily Epic report, a coordinator at each site will identify eligible patients and notify 
pharmacists. Trial enrollment will occur for eligible patients admitted every day prior from Monday 
to Friday. 
2. All eligible patients (both arms) will receive the Best Possible Medication History (BPMH) 
(1) On hospital day 1, or as soon as possible: 
Receive an Initial Medication Regimen 
Assessment. Clinical pharmacists assess 
regimen appropriateness, assess barriers to 
medication adherence, start filling out the 
Actions for Assessing Adherence Barriers 
worksheet 
 
(2) On hospital day 1, or as soon as possible: 
Receive a Pre-Discharge Intervention, which, 
depending on the patient condition, might 
include a: trial to discontinue certain 
medications during the hospital; discussion of 
side effects, flags for new medications 
prescribed, education about critical barriers to 
adherence.  
Arm 2 
N 
Arm 1 
N 
Randomize 
Receive usual care 
On day of discharge: Receive an At-Discharge 
Intervention, which may include a brief 
discussion of medication changes, discussion of 
side effects, discussion of red flags for new 
medications. Clinical pharmacists will also 
consult with inpatient clinicians and 
pharmacists to discuss the medication list and 
will ensure that the e-prescribing is done 
appropriately. 
1-3 days after discharge: Receive a Post-
Discharge Intervention, which includes a call 
with a patient to discuss the patient’s regimen, 
discussion of side effects, red flags of new 
medications, a motivational interview, a 
discussion of barriers to adherence. Other tasks 
might include a phone call with the patient’s 
primary care physician. Some patients, 
depending on need, might receive a second 
phone call if needed, a video visit, clinic visit 
with pharmacist, embedded mental health. 

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1.3 SCHEDULE OF ACTIVITIES (SOA) 
(1) Pharmacist-led Hospital Discharge Care Intervention:  
a. Eligible pharmacists at each study site will be selected to participate in the 
intervention based on their training in transitions of care.  
b. Using a daily Epic report generated by EIS, a coordinator at each site will identify 
eligible patients and notify pharmacists. Trial enrollment will occur for eligible 
patients admitted every day prior from Monday to Friday. 
c. Randomization will be performed via the REDCap (Research Electronic Data 
Capture) system. 
d. All eligible patients (both arms) will receive the Best Possible Medication History 
(BPMH) 
e. Patients in the Study arm: 
i. On hospital day 1, or as soon as possible: Receive an Initial Medication 
Regimen Assessment. Clinical pharmacists assess regimen 
appropriateness, assess barriers to medication adherence, start filling out 
the Actions for Assessing Adherence Barriers worksheet 
ii. On hospital day 1, or as soon as possible: Receive a Pre-Discharge 
Intervention, which, depending on the patient condition, might include a: 
trial to discontinue certain medications during the hospital; discussion of 
side effects, flags for new medications prescribed, education about critical 
barriers to adherence. 
iii. On day of discharge: Receive an At-Discharge Intervention, which may 
include a brief discussion of medication changes, discussion of side 
effects, discussion of red flags for new medications. Clinical pharmacists 
will also consult with inpatient clinicians and pharmacists to discuss the 
medication list and will ensure that the e-prescribing is done appropriately. 
iv. 1-3 days after discharge: Receive a Post-Discharge Intervention, which 
includes a call with a patient to discuss the patient9s regimen, discussion 
of side effects, red flags of new medications, a motivational interview, a 
discussion of barriers to adherence. Other tasks might include a phone 
call with the patient9s primary care physician.  
v. After initial phone call: Some patients, depending on need, might receive 
a second phone call if needed, a video visit, clinic visit with pharmacist, 
embedded mental health. 
vi. For any of the above-mentioned activities, patients may be contacted by 
pharmacists over the phone instead of in-person to reduce COVID-19 
exposure to patients, caregivers, and pharmacists. 
f. Patients in the Control arm: 
i. Will receive usual care, which may include pharmacist consultation and/or 
after-discharge phone call(s) if clinically necessary.  
g. Critical covariates, including, age, sex, gender, all recorded diagnoses, number 
of medications, all recorded medication types, zip code, first language, marital 
status, employment, social history (e.g. tobacco use, alcohol use) will be 
extracted from electronic health records (EHR) after the intervention ends at 
each study site. The complete list of data elements to be extracted from the EHR 
for evaluating trial outcomes are provided in Appendix A.  

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(2) Qualitative study to study barriers and facilitators of implementing PHARM-DC: 
 
a. In the first year of the intervention, the investigators (Dr. Pevnick and Dr. 
Kennelty) will visit trial sites to conduct 6 focus groups of 6 to 8 clinicians. These 
focus groups will be grouped by type of clinician (pharmacist, pharmacy tech, 
physician, nurse). We estimate that 48 people per site will participate in the study. 
b. We will use a purposive sampling design by role and department to determine 
eligibility.  
c. Eligible participants will receive an email from study staff inviting them to 
participate in the focus groups. 
i. Documents: 
1. Recruitment email 
2. Information sheet 
d. Focus groups will be 60-90 minutes and will be administered by the PI, the 
qualitative researcher, and study staff. Due to COVID-19, the focus groups may 
take place virtually using video conferring software (e.g. Webex). 
e. We may also conduct phone or video interviews in lieu of focus groups if 
individuals are not available for the focus groups. 
f. In Years 1-3 of the intervention, Drs. Kennelty, Murry and Keller will conduct 40 
pharmacist observations that will last approximately 2 hours each. This may 
include observations with patients/caregivers, however, the research subject of 
these observations will be the pharmacist. No PHI or identifiable information will 
be collected. Researchers will shadow pharmacists for up to 2 hours at a time to 
understand pharmacist activities and workflow. Observation data will include 
handwritten notes on either paper or a secure tablet. Examples of observation 
data include: (1) how pharmacists gather information for medication reconciliation 
(whether they consult SureScripts, call community pharmacists, call the primary 
care physician, (2) how they manage doing the intervention when the hospital 
census is very high, (3) the order in which they do the intervention activities. The 
observations will be collected using paper and pencil. The observations will take 
place in the two sites where the pharmacists conduct their regular activities. The 
pharmacists will be given an updated information sheet (for Study 2) that 
describes these activities. Patients will be told that this is part of an ongoing 
study examining pharmacist activities.  
g. In Year Two, Dr. Keller will conduct 15 in-depth one-on-one phone interviews with 
frontline pharmacists asking about the intervention and about challenges 
pharmacists are having with deprescribing. We estimate that the phone 
interviews will last 60 minutes. 
h. In Year Three, Dr. Kennelty will conduct in-depth one-on-one phone interviews 
with frontline pharmacists and key stakeholders (e.g., pharmacist leaders). 
Interviews will last about 25-90 minutes. We estimate that we will interview 
approximately 50 participants per site. 
i. Documents: 
1. Recruitment email 
2. Information sheet 
i. 
The audiotaped transcripts from both the focus groups and interviews will be 
transcribed a professional transcribing company. The data will be stripped of 
identifiers and will be sent to Dr. Kennelty and her staff. 
j. 
The data will be analyzed using NVivo by Dr. Kennelty and study staff. 
 
 

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(3) Cost-Effectiveness Study to analyze the costs of PHARM-DC: 
 
a. Pharmacists will be approached for oral consent at the beginning of a clinic day 
or clinical shift. Potential participants will be approached, given an information 
sheet, and the nature of the study will be explained.  
i. Documents: 
1. Information sheet 
b. Inclusion Criteria: Pharmacists participating in the PHARM-DC intervention 
actively seeing patients and responsible for generating the majority of 
documentation for the clinical visit  
c. The observers will use the data collection tool to record time spent on PHARM-
DC activities for study patients versus time spent on activities for patients 
receiving usual care. A trained member of the study staff will shadow 
participating pharmacists continuously for 4-8 hours during a clinical shift, using 
an online application (TimeCaT version 3.9, available at 
lopetegui.net/timecat/39/login/) to note the nature of activities the pharmacist 
performs and the beginning and ending times of each activity. The TimeCat 
application requires username and password login, will be installed on a Cedars-
Sinai issued iPad, and will only be accessed on the site9s secure internet 
network. The observations will take place in the two sites where the pharmacists 
conduct their regular activities. Observations may include patients/caregivers. 
The pharmacists will be given an updated information sheet (for Study 3) that 
describes these activities. Patients will be told that this is part of an ongoing 
study examining pharmacist activities.  
d. Patients will be assigned a random unique identifier within the TimeCaT 
application so that no PHI is transmitted over the internet. This will enable the 
observer to record pharmacist activities performed at the patient level (i.e., per 
patient). The observer will record the patient MRN, CSN, and unique identifier in 
a linking file stored separately on Box (https://cedars.app.box.com), along with 
the number of days since discharge for the relevant patient (e.g., post-discharge 
day 4).  
e. To assure that the time-use data is representative, we will sample approximately 
100 patient interactions (20 complete interventions, 20 discharge medication 
reconciliations, 20 post-discharge phone calls, and 40 observations of usual 
care) by study pharmacists at each study site over a one-year period.  
f. To ensure that pharmacists have become efficient in providing the intervention, 
sampling will only occur in years two and three and pharmacists with less than 
two-months experience with the intervention will be excluded.  
g. Covariates of patients, including age, sex, gender, race/ethnicity, all recorded 
diagnoses, number of medications, all recorded medication types, zip code, first 
language, marital status, employment, social history (e.g. tobacco use, alcohol 
use) will be extracted from electronic health records after the study period ends 
at each study site. We will exclude data for patients who have opted out of 
research studies from data extracts.  
 
2 
 
INTRODUCTION 
 
2.1 STUDY RATIONALE  
 

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The sickest patients in the community are recently hospitalized elders. A substantial 
component of their morbidity and mortality is caused by adverse drug events (ADEs). ADEs 
account for 70% of adverse events occurring after discharge, which occur at a rate of 0.30 
ADEs per patient.i-iii The oldest, sickest patients are at highest risk for ADEs: they have the most 
complex and hazardous medication regimens but the fewest social and economic resources 
and the least physiologic reserve.iv Such patients commonly face challenges in understanding, 
obtaining, administering, and monitoring new medications prescribed at discharge. These 
difficulties can lead primarily to avoidable side effects, non-adherence, and suboptimal disease 
management, and secondarily to outpatient and emergency department visits, hospital 
readmission, morbidity, and death.v  
In 2006, one of our investigators published a randomized controlled trial (RCT) showing that 
pharmacist counseling before discharge and a telephone call after discharge decreased the 
prevalence of preventable post-discharge ADEs from 11% to 1% (p=0.01).vi If implemented 
nationally, this simple and scalable intervention could prevent 3.5 million post-discharge ADEs 
annually. Surprisingly, over a decade later, it remains under-resourced and thus underutilized 
even at the institution where the research was conducted.  
Pharmacist leaders around the country report similar implementation difficulties. Many have 
adopted similar pharmacist discharge care interventions on a limited scale and report anecdotal 
success from limited use. However, nearly all pharmacist leaders struggle to obtain operational 
funding to provide this service to all patients likely to benefit. We attribute this struggle in part to 
a weak business case for hospital leaders to invest in it. The business case is weak because 
studies so far have looked at abstract concepts like <preventable post-discharge ADEs= rather 
than healthcare utilization. In annual organizational budgeting, interventions known only to 
prevent suboptimal processes of care are difficult to justify, and thus particularly prone to cuts. 
As such, we seek to measure the effect of this intervention on utilization reduction, which is the 
central innovation of this project.  
 
2.2 BACKGROUND  
Recently hospitalized elders represent the sickest patients in the community. Physiologic 
reserves, known to lessen with age, are often even lower after hospitalization due to illness, 
medication, or surgery.vii Medication regimens are changed during about half of elderly inpatient 
hospital stays.viii Hospital providers usually increase regimen complexity.ix As a result of all this, 
inappropriate under- and over-prescribing usually increase.x Unfortunately, recently hospitalized 
elders are often unable to fully understand such regimen changes, to obtain the new 
medications, to advise pharmacists not to fill older prescriptions that have been discontinued, to 
adhere to new regimens,xi or to appropriately monitor themselves for potential side effects. 
Although seniors9 physiologic reserves may not be remediable, medication regimen 
appropriateness and adherence can be improved, both of which can lessen rates and severity 
of adverse drug events (ADEs). 
Unsurprisingly, the risks noted above can increase the rate and severity of post-discharge ADEs 
(defined as any injury due to medication in the 30 days following discharge) among recently 
hospitalized seniors. In particular, we note: 
• 
Post-discharge ADEs occur in 17-19% of older patients.xii,15  
• 
Post-discharge ADEs cause 23-38% of readmissions in older adult patients.xiii-xv  

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Two studies show that most post-discharge ADEs are either preventable (24-27%) or 
ameliorable (33-38%) (for practicality, these analyses treat the two categories as being mutually 
exclusive).xvi,xvii  
Interventions that Reduce Post-Discharge ADEs: Three Major Types (We will Study Two 
Types) 
For clarity, we separate pharmacist-led post-discharge medication management interventions 
into three major types. From consulting an accepted conceptual framework of medication 
management,xviii,xix we have determined that almost all pharmacist-led interventions reducing 
post-discharge ADEs do so by addressing medication reconciliation (med rec), medication 
adherence, or polypharmacy: 
1. Med Rec: These interventions seek to find out what medications a patient has been 
prescribed and has been taking, and to use this information to make sure patients receive 
correct medications anywhere in the health system.  
We believe that the greatest benefit of med rec may be that it serves as a foundation for 
providers to address the two other issues below. Indeed, recent work by ourselves and others to 
increase implementation and dissemination of med rec is one reason why our proposed RCT is 
so timely – it is only recently that many patients are now receiving the necessary med rec that 
will allow them to benefit from interventions targeted at improving medication adherence and 
reducing inappropriate polypharmacy. 
2. Medication Adherence: These interventions seek to improve patients9 adherence to a 
prescribed medication regimen, which may include identifying barriers (e.g., cost, side effects, 
understanding) and addressing them. 
3. Polypharmacy: This refers to the fact that many patients, especially older patients with 
multimorbidity, are overprescribed medications. It is facilitated by multiple factors, including 
fragmented care and fear of discontinuing old medications. Many pharmacist-led interventions 
to reduce polypharmacy involve 8Medication Review,9 wherein pharmacists critically appraise 
medication regimens and initiate improvements (including addressing under-prescribing, which 
is now known to also be prevalent in this population).xx 
We attribute some of the poor uptake of interventions to reduce ADEs to the fact that different 
interventions come from different disciplines and go by different names. Part of the innovation of 
our study is that we aggregate potentially synergistic interventions that tend to be based in 
separate clinical communities: pharmacy (medication review), medication safety (med rec), and 
geriatrics (polypharmacy).  
Pilot Data from Brigham and Women’s Hospital (BWH) 
Dr. Schnipper9s 2006 trial randomized 178 patients being discharged home to either usual care 
or an intervention with pharmacist counseling at discharge and a follow-up pharmacist 
telephone call 3-5 days later. Interventions focused on clarifying medication regimens; reviewing 
indications, directions, and potential side effects; screening for barriers to adherence and early 
side effects; and providing patient counseling or physician feedback. This initial study was 
powered on reducing the rate of preventable post-discharge ADEs. 
Comparing trial outcomes 30 days after discharge, preventable ADEs were detected in 11% of 
patients in the control group but only in 1% of patients in the intervention group (p = .01). 

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Despite this success in reducing preventable ADEs, and despite being cited in over 500 
publications, this intervention remains underfunded to achieve these outcomes even at Brigham 
and Women’s Hospital (BWH), where the study was conducted. No differences were found in an 
unpowered comparison between groups in total health care utilization. However 
there was a statistically significant decrease in preventable medication-related utilization: only 1 
preventable medication-related ED visit or readmission occurred in the intervention group, as 
opposed to 7 in the control arm (p = 0.03). This suggests the trial was underpowered to detect 
the effect on utilization. 
B.2.2 Pharmacist Intervention to Decrease Medication Errors in Heart Disease Patients (PILL-
CVD)xxi 
This 2-site RCT, for which Dr. Schnipper served as site-PI at BWH, randomized 851 cardiac 
patients to either usual care or pharmacist-assisted med rec. The pharmacist assistance 
included inpatient pharmacist counseling, low-literacy adherence aids, and individualized 
telephone follow-up after discharge. There was no significant change in the primary outcome, 
the per-patient number of clinically important medication errors (unadjusted incidence rate ratio, 
0.92 [95% CI, 0.77-1.10]).  
We attribute much of this failure to the use of non-clinician study coordinators rather than 
pharmacists for phone calls. Especially for the patients targeted by our RCT (taking >10 
medications or >3 high-risk medications, age >55), we anticipate complex medication regimens 
that will require at least two 8touches9 by a pharmacist to ensure proper post-discharge 
medication management. Despite missing its primary outcome, the PILL-CVD intervention 
reduced early unplanned health-care utilization among patients with inadequate health literacy 
(aHR 0.41, 95% CI 0.17-1.00).xxii Given the results of PILL-CVD, we have taken four major 
steps to ensure that the best possible version of PHARM-DC is tested on the most appropriate 
patients in our RCT: 
1. Having pharmacists make the post-discharge phone calls and lead other post-discharge 
activities 
2. Providing pharmacists with an updated evidence-based Toolkit of medication management 
interventions  
3. Focusing the intervention on high-risk patients: age >55, taking >3 high-risk medications or 
>10 overallxxiii,xxiv 
4. Not requiring a cardiac diagnosis (done in PILL-CVD to align with the goals of a funder) 
 
Pilot Data from Cedars-Sinai Medical Center (CSMC) 
B.3.1 A Three-Arm Pragmatic Randomized Controlled Trial of Adding Admission Medication 
History Interviews by Pharmacists or Pharmacist-Supervised Pharmacy Technicians to Usual 
Carexxv 
Dr. Pevnick recently completed an RCT that studied med rec in the emergency department. The 
trial is an example of using pharmacy personnel for medication management. It was successful, 
reducing admission medication order errors by >80% (3.2 errors per patient in the usual care 
arm vs only 0.6 per patient in each intervention arm, p<0.0001). The RCT easily enrolled more 
than 300 patients with a mean age of 72 and a mean of 15 medications over 23 enrollment 
days, a rate of over 13 daily. This shows that the CSMC team has the operational capacity to 
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patient population at CSMC but also the aging US population and its increasing 
polypharmacy.xxvi 
B.3.2 An Unpowered Nested RCT Suggested Post-Discharge Pharmacist Phone Calls Reduced 
Readmissions 
Analyzing a nested trial within this RCT looked at the effect of post-discharge pharmacist phone 
calls to improve medication management among patients with suboptimal medication 
adherence or literacy.xxvii Although this unpowered analysis did not yield significant findings, and 
although there was substantial dropout due to patients not answering phone calls at 30 days, 
the point estimate for readmissions was 10% lower (absolute drop of 10%) at 30 days in the 
group receiving phone calls. This shows that CSMC pharmacists have the operational capacity 
to make post-discharge phone calls, and suggests that the intervention might reduce 
readmissions, even when pharmacists were not provided with a toolkit of updated evidence-
based content. 
B.3.3 PHARM-DC Toolkit Development: Results to Date and Work to be Completed in 2017 for 
ASHP 
To identify, aggregate, and synthesize existing evidence regarding the content that pharmacists 
should provide during the PHARM-DC intervention, we obtained grant-funding from the 
American Society for Health-System Pharmacists in 2016 to use a literature review and 
technical expert panel to develop the <PHARM-DC Toolkit.= We used an overview of systematic 
reviews approachxxviii (searching MEDLINE, Cochrane and DARE) to identify 74, 14, and 28 
existing systematic reviews in the areas of medication adherence, polypharmacy, and post-
discharge med rec, respectively. In cases where we found at least one high quality systematic 
review (AMSTAR >8)xxix with reasonable evidence that an intervention could successfully 
improve even intermediate processes demonstrating improved post-discharge medication 
management, we have traced the literature findings back to the original paper or best summary 
of the intervention for inclusion in the PHARM-DC toolkit.  
 
2.3 RISK/BENEFIT ASSESSMENT   
 
2.3.1 KNOWN POTENTIAL RISKS  
 
Hospital Discharge Study 
 
This is a low-risk intervention. Since the intervention is already being conducted at the two sites 
by clinical pharmacists when there is administrative capacity to do so, we do not anticipate any 
additional risks involved with the hospital discharge intervention.  
 
There is a small risk of breach of confidentiality with regards to the electronic health records 
data collected by the researchers at the end of the study; however, all data will be kept on 
password-protected, encrypted study site computers. Only investigators and study staff who are 
IRB-approved will have access to the study data. Since we are examining data at the end of the 
intervention, the data analysis is similar to a retrospective secondary data analysis. 
 
To reduce the risk of COVID-19 exposure, some or all of the intervention activities (medication 
reconciliation, patient/caregiver education and counseling) will be conducted over the phone. 
 

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Focus Groups and Interviews 
 
Individuals who participate in the focus groups and/or interviews may experience mild 
discomfort about certain questions. However, they will be reminded at the beginning of the focus 
group that they are not required to answer any questions they find cause discomfort and that 
they may stop the focus group/interview at any time.  
 
There is also a small risk of breach of confidentiality. Interviewees/participants of focus 
groups/interviews will be given number identifiers, which will be kept separate from their 
identifiers/demographic information. Only the study staff will have access to the identifiers. This 
sub-study will not include any patient observation or use of PHI. 
 
Observations will not affect any clinical decisions or clinical care. The pharmacist will be notified 
that observations will take place and that no identifiable information will be recorded about the 
interactions. Patients who may have interactions with the pharmacists will not be notified of the 
observations for research, since information will not be collected about them. Individuals who 
participate in the observations may experience mild discomfort when being observed. However, 
they will be reminded at the beginning of the observation that they are not required to participate 
in the observations and can stop the observation at any time. There is also a small risk of 
breach of confidentiality. Participants in the observations will be given number identifiers, which 
will be kept separate from their identifiers/demographic information. Only the study staff will 
have access to the identifiers. 
 
Time and Motion Study/Cost-Effectiveness Analysis 
 
There is a small risk of breach of confidentiality. Patients will be assigned a unique identifier 
within the TimeCaT application so that no PHI is transmitted over the internet. Only study staff 
will have access to the identifier and linking file, which will be stored separately on Box and will 
only be accessed on a password protected, encrypted study site computer. When not in use, 
iPads will be stored in a locked cabinet behind a locked office door in the Department of 
Medicine9s administrative office at each site.  
 
Observations will not affect any clinical decisions or clinical care. The pharmacist will be notified 
that observations will take place. Patients who may have interactions with the pharmacists will 
be told that this is part of an ongoing study examining pharmacist activities. Individuals who 
participate in the observations may experience mild discomfort when being observed. However, 
they will be reminded at the beginning of the observation that they are not required to participate 
in the observations and can stop the observation at any time.  
 
There is also a small risk of breach of confidentiality with regards to the electronic health 
records data collected by the researchers at the end of the study; however, all data will be kept 
on password-protected, encrypted study site computers. Only investigators and study staff who 
are IRB-approved will have access to the study data. Since we are examining data after the end 
of the study period at both sites, the data analysis is similar to a retrospective secondary data 
analysis. We will exclude data for patients who have opted out of research studies from data 
extracts. 
 
2.3.2 KNOWN POTENTIAL BENEFITS  
 
Individuals may receive consultations with pharmacists that help them understand their 
medications and/or chronic conditions more thoroughly. 

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3 
OBJECTIVES AND ENDPOINTS 
 
Primary Outcome 
We chose an endpoint of 30-day post-discharge utilization as our primary outcome because the 
RE-AIM model points to the importance of institutional-level effectiveness and cost. We chose to 
power this trial on an absolute utilization reduction of 2.5% (% of patients with readmissions or 
ED visits within 30 days of hospital discharge) from a baseline of 27.5%. 
We define this utilization in two different ways, based on what data is available. For the first 
analysis, we will use same-hospital utilization data. Both site PIs can electronically access 
inpatient admission, observation stay, and ED visit data for their health system. These three 
utilization types will represent the basis for the first RCT analysis (manuscript #2 above). 
 
We recognize the limitations of same-hospital utilization data.xxx As such, the RCT is powered 
on a primary endpoint of same-state 30-day hospital readmissions and ED visits (manuscript #6 
above).  
 
This utilization will be tracked with data from the Massachusetts All Payer Claims Data (APCD) 
database and California's Office of Statewide Health Planning and Development.xxxi  Because 
we expect little utilization in other states (discharge to another state is an exclusion criterion) 
and because we do not anticipate any differential effect on such utilization, we will not track it. 
Statewide data sources do not track observation stays, so they will be excluded from statewide 
analyses. However, we will conduct a sensitivity analysis projecting changes in same-hospital 
observation stays to the statewide analysis.  
The current version of this protocol does not include information for these analyses using other 
data sources; we will include this information in subsequent versions through protocol/IRB 
amendments.  
 
Secondary Outcomes 
 
We will examine the endpoints in the following subgroups: 
 
Patients: 
1) Patient socioeconomic status (estimated via median income of home census tract);  
2) Patient medication adherence and literacy (as assessed by study pharmacists, in addition to using limited 
English proficiency as a proxy for low medication literacy);  
3) Study site;  
4) Ten or more medications;  
5) Three or more high risk medications;  
6) Patient history of congestive heart failure; 
7) By receipt of different intervention components; 
8) Patient age groups; 
9) Before and after historical changes to the intervention and control arms; 
10) Primary outcome restriction to medication-related post-discharge utilization; 
11) Primary outcome restriction to 7-day post-discharge utilization.  
12) 30-day mortality 
13) Effect of the intervention on each type of utilization considered separately (ED visits alone, observations 
stays alone, readmissions alone) 

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4 
STUDY DESIGN  
 
4.1 OVERALL DESIGN 
 
 
Hospital Discharge Study 
This is a prospective, randomized, controlled, pragmatic trial of a pharmacist-led intervention 
aimed at reducing readmissions. The study will focus on discharge utilization among patients 
most at risk for post-discharge ADEs: recently discharged older adults taking >10 medications 
or >3 high-risk medications.  
 
Focus Groups and Interviews 
 
This is a qualitative study employing interviews, observations, and focus groups aimed at 
understanding implementation barriers and facilitators. Drs. Pevnick and Kennelty and study 
staff will conduct 3-day site visits to hold focus groups regarding intervention expectations, how 
the intervention is being implemented, barriers/facilitators to adoption and implementation, and 
adaptations made during delivery. 
 
Towards the end of the trial, Dr. Kennelty and study staff will use phone interviews to determine 
any changes to the implementation of PHARM-DC that occurred during the RCT, as well as to 
understand whether and how institutions will address the maintenance of PHARM-DC after the 
study ends. 
 
We will use qualitative methods to the reach of the intervention (overview in Table 6 above), and 
to investigate several hypotheses developed using RE-AIM as a guide. 
We hypothesize that staff adoption will be facilitated by:  
(1) units and sites with better safety culture and teamwork and  
(2) unit-based (vs central) pharmacists, whereas barriers to staff adoption will include:  
(1) difficulties associated with coordinating a time for discharge counseling (patients are 
frequently anxious to leave as soon as discharge orders are placed, but the discharge 
medication regimen is not usually available before this time), and  
(2) that even when problems are identified, lack of resources may still be an issue (e.g., 
medications with expensive copayments). We hypothesize that implementation 
consistency will be higher and that adaptations will be lower when pharmacists are not 
overwhelmed by other responsibilities, and on medical (vs surgical) units. 
Surveys to Assess Organizational Context: We will assess safety culture with the AHRQ Patient 
Safety Survey. Individuals who participate in the focus groups/interviews will be asked to 
complete the survey prior to participating in the study.   
 
The observations will take place at the two study sites (CSMC and BWH). They may include 
observations of patients/caregiver interactions. Researchers will not collect any PHI. 
Observations will include the collection of information such as: 

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• 
Amount of time spent by pharmacists on each individual task 
• 
Challenges pharmacists have when attempting to contact caregivers, nurses, pharmacist 
technicians, primary care physicians, and attending physicians 
• 
Number of sources that pharmacists use (SureScripts, retail pharmacies, asking 
caregivers) to put together medication reconciliation information 
• 
Challenges pharmacists have when trying to contact patients (e.g. patient doesn9t 
answer the phone) 
• 
How pharmacists divide up work when there are a lot of patients in the study (e.g. how 
they each have a floor to cover and how they cover for each other when one is busy or is 
out). 
 
Time and Motion Study 
 
This is a time-and-motion study aimed at understanding how much time during the day 
pharmacists spend on activities related to the hospital discharge (and post-discharge) 
interventions. During the trial, we will use time-and-motion methodology to understand how 
much pharmacist time is needed for PHARM-DC. Coupled with data on post-discharge 
utilization, this will enable us to conduct economic analyses. 
 
Researchers will collect pharmacist demographics, including:  
1. Name 
2. Study site 
3. Years of experience as a pharmacist 
4. Years of experience in TOC 
5. Years of Experience in Hospital-Based Pharmacy 
6. Years of Residency Training 
7. Month and year that you started working at the study site 
8. Month and year that you started delivering the PHARM-DC intervention 
9. Type of Residency Training 
10. List of Board Certifications and Credentials 
 
5 
STUDY POPULATION 
 
5.1 INCLUSION CRITERIA 
 
 
Inclusion criteria include: 
 
• 
Being discharged from a medical ward, AND 
• 
> 55 years old AND 
• 
≥ 10 chronic prescription medications  
 
OR  
• 
> 3 high-risk medications (anticoagulants, antiplatelets, insulin, oral hypoglycemics, and) 
before or during hospitalization 
 
 

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5.2 EXCLUSION CRITERIA 
 
Exclusion criteria include the following: 
• 
Expected discharge to another state, acute care facility, psychiatric facility, or locked facility 
(including locked skilled nursing facility, jail, or prison) OR 
• 
Expected leaving hospital against medical advice (AMA) or actual AMA OR 
• 
Homeless OR  
• 
On hospice OR  
• 
Already enrolled into study during prior discharge in previous year OR  
• 
Expected to receive pharmacist-led post-discharge medication management regardless of 
the trial OR 
• 
Patients admitted by admitting or attending Primary Medical Doctors who have a specialty 
that is not Internal Medicine or Family Medicine OR 
• 
Expected post-discharge setting not conducive to the studied medication management 
intervention OR 
• 
Patients admitted with a suspected or confirmed diagnosis of COVID-19. 
 
 
5.3 STRATEGIES FOR RECRUITMENT AND RETENTION 
 
Hospital Discharge Study 
 
Eligible pharmacists will be selected by the pharmacy managers at each site. Eligibility includes 
training in transitions of care and/or post-discharge care. 
 
A daily Epic report will be generated at each site to identify eligible patients. A research 
assistant will conduct a brief chart review to confirm eligibility before randomizing the patient 
using REDCap. For quality assurance, operational reports will be obtained from the emergency 
department and cross-checked with the EIS report to ensure all patients who may be eligible for 
the study are accurately identified. The study coordinator will stop randomizing patients if the 
number of patients concurrently receiving the intervention on any given weekday exceeds the 
workload capacity of pharmacists at each site. Study coordinators will communicate with 
pharmacists to regularly re-assess the maximum threshold of concurrent patients in the 
intervention arm. This strategy aims to reduce the potential for pharmacist burnout and to 
optimize intervention quality.  
 
Once the patient has been randomized to the intervention or control arm, the clinical pharmacist 
will approach the patients in the intervention arm.  
 
 
Focus Group/Interviews Study 
We will use a purposive sampling design by role and department to determine eligibility. Eligible 
participants will receive an email from study staff inviting them to participate in the focus groups, 
and/or interviews. To enhance recruitment, we will offer a $125 honorarium to nurses and a 
$250 honorarium to physicians for their participation in a 60-90 minute focus group or interview.   
Time and Motion Study 
 

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Pharmacists will be approached for oral consent at the beginning of a clinic day or clinical shift. 
Potential participants will be approached, given an information sheet, and the nature of the 
study will be explained. Inclusion Criteria: Pharmacists participating in the PHARM-DC 
intervention actively seeing patients and responsible for generating the majority of 
documentation for the clinical visit.  
 
6 
STUDY INTERVENTION 
 
6.1 STUDY INTERVENTION(S) ADMINISTRATION 
 
6.1.1 STUDY INTERVENTION DESCRIPTION 
 
PHARM-DC Intervention Overview 
Pharmacists at both study sites have experience in providing discharge counseling and in 
making post-discharge phone calls. This experience will ensure that PHARM-DC is being tested 
in its best light. The Toolkit content and 1-2 hours of introductory training add three major 
components: 
1. Rather than incorporating content based solely upon their prior training and experience, 
pharmacists will use the PHARM-DC Toolkit, which summarizes the evidence for post-
discharge medication management.  
 
2. Pharmacists will assess patient needs and customize accordingly. All patients will receive 
one discharge counseling visit and one post-discharge phone call, but pharmacists will find 
that some patients need further phone calls, interventions, referrals, or other interactions. 
 
3. Although pharmacists have long been successful in leading med rec interventions, most 
work focused on what medications patients had been prescribed and are taking. This is a 
necessary step, but we believe most benefit occurs from the subsequent step of figuring 
out what medications patients should be taking.  
 
PHARM-DC toolkit:  
 
1) Pharmacist review of discharge med rec and medication appropriateness (e.g., reduction 
in polypharmacy); 
 
2) In-hospital room visit to screen for previous barriers to safe medication use, initiate 
management of these barriers, and communicate with post-discharge providers 
regarding likely actions that will need to be taken;   
 
3) Post-discharge phone call by a pharmacist 1-3 days after discharge to screen for 
patient/caregiver lack of understanding of their medication regimen, medication non-
adherence, early side-effects, lack of knowledge of what ADEs to watch for and what to 
do if they occur, other barriers to safe medication use, and management of these 
problems;   
 

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4) Based on this risk assessment, pharmacists will tailor the interventions to each patient. 
The personalized intervention may include:  
 
a. Patient education, counseling, and coaching regarding the importance of 
taking medication as prescribed and contacting a designated caregiver or 
provider if there are problems;  
b. Taking further steps to improve medication appropriateness;   
c. Post-discharge assistance with obtaining medications, including drug 
assistance programs (for reduced pricing) and linkage with community or social 
service organizations;  
d. Pharmacist communication with key inpatient and outpatient providers 
(e.g., PCPs; skilled nursing facilities; inpatient rehabilitation hospitals, including 
the California Rehabilitation Institute) to ensure that they understand changes to 
their patient9s discharge medication regimen, including why those changes were 
made and recommended actions to take. This includes requesting Medication 
Administration Records (MAR) from downstream providers to facilitate this type 
of communication; 
e. Communication with each patient’s pharmacy to ensure the pharmacy has an 
updated medication list, with focus on newly discontinued medications, and to 
encourage patient education as needed when patients fill their prescriptions;  
f. Use of illustrated pill cards, pillboxes (traditional and electronic), and other 
tools to help patients with low literacy better understand and adhere to their 
medication regimens;   
g. Health information technology such as patient portals and texting chatbots 
to facilitate communication between patients, pharmacists, and other providers 
after discharge;   
h. Home pharmacist visits for high-risk patients to educate them and to identify 
and manage challenges to safe medication use.   
 
6.2 MEASURES TO MINIMIZE BIAS: RANDOMIZATION AND BLINDING 
 
Randomization will be performed via the REDCap (Research Electronic Data Capture) system. 
REDCap is a secure, web-based application supporting data capture for research studies, 
providing:  
 
1) an intuitive interface for validated data entry;  
2) audit trails for tracking data manipulation and export procedures;  
3) automated export procedures for seamless data downloads to common statistical packages; 
and;  
4) procedures for importing data from external sources.  
 
REDCap will incorporate allocation tables generated in R. Study participants will be randomized 
1:1 to the two arms of the study and stratified by site.  Arm assignment will not be actively 
masked, but most clinical personnel and patients will remain unaware of the trial, just as they 
are unaware of the details of most post-discharge medication management practices currently. 
 
6.3 STUDY INTERVENTION COMPLIANCE 
 
We will use EHR documentation to assess study intervention compliance. This will include 
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7 
STUDY INTERVENTION DISCONTINUATION AND PARTICIPANT 
DISCONTINUATION/WITHDRAWAL 
 
7.1 LOST TO FOLLOW-UP 
 
Hospital Discharge Study 
 
Patients who leave the state or country after their hospital discharge or who do not answer 
phone calls post-discharge will be considered lost to follow-up and this will be recorded in the 
CONSORT diagram.  
 
7.2 ADVERSE EVENTS AND SERIOUS ADVERSE EVENTS 
 
7.2.1 DEFINITION OF ADVERSE EVENTS (AE) 
 
Adverse event means any untoward medical occurrence associated with the use of an 
intervention in humans, whether or not considered intervention-related (21 CFR 312.32 (a)). 
 
7.2.2 DEFINITION OF SERIOUS ADVERSE EVENTS (SAE)  
 
An adverse event (AE) or suspected adverse reaction is considered "serious" if, in the view of 
either the investigator or sponsor, it results in any of the following outcomes: death, a life-
threatening adverse event, inpatient hospitalization or prolongation of existing hospitalization, a 
persistent or significant incapacity or substantial disruption of the ability to conduct normal life 
functions, or a congenital anomaly/birth defect. Important medical events that may not result in 
death, be life-threatening, or require hospitalization may be considered serious when, based 
upon appropriate medical judgment, they may jeopardize the participant and may require 
medical or surgical intervention to prevent one of the outcomes listed in this definition. 
Examples of such medical events include allergic bronchospasm requiring intensive treatment in 
an emergency room or at home, blood dyscrasias or convulsions that do not result in inpatient 
hospitalization, or the development of drug dependency or drug abuse. 
 
7.2.3 CLASSIFICATION OF AN ADVERSE EVENT 
 
7.2.3.1 RELATIONSHIP TO STUDY INTERVENTION 
 
We do not anticipate any adverse events related directly to the study intervention. Therefore, 
AEs will be classified as:  
 
Not Related – There is not a reasonable possibility that the administration of the study 
intervention caused the event, there is no temporal relationship between the study intervention 
and event onset, or an alternate etiology has been established. 

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Each site PI, Dr. Josh Pevnick (CSMC) and Dr. Jeffrey Schnipper (BWH) will be responsible for 
determining whether an adverse event (AE) is expected or unexpected.  An AE will be 
considered unexpected if the nature, severity, or frequency of the event is not consistent with 
the risk information previously described for the study intervention. AEs will be reported to the 
DSMB for evaluation. 
7.2.4 TIME PERIOD AND FREQUENCY FOR EVENT ASSESSMENT AND 
FOLLOW-UP 
 
The occurrence of an adverse event (AE) or serious adverse event (SAE) may come to the 
attention of study personnel during study visits and interviews of a study participant presenting 
for medical care, or upon review by a study monitor. Study staff will immediately notify the 
principal investigator (Dr. Josh Pevnick) upon becoming aware of deaths occurring in study 
participants. The PI will report deaths to the NIA PO within 48 hours by email and submitting the 
appropriate case report form (CRF). 
 
Deaths and same-hospital readmissions (inpatient, observation, or emergency department 
visits) occurring within 90-days of hospital discharge will be collected retrospectively from the 
patient9s medical record every six months through the study. All AEs/SAEs will be reported in a 
semi-annual summary safety report to the Data Safety Monitoring Board (see Section 9.1.4). 
 
All AEs including local and systemic reactions not meeting the criteria for SAEs will be captured 
on the appropriate CRF. Information to be collected includes event description, time of onset, 
clinician9s assessment of severity, relationship to study product (assessed only by those with the 
training and authority to make a diagnosis), and time of resolution/stabilization of the event. All 
AEs occurring while on study must be documented appropriately regardless of relationship. All 
AEs will be followed to adequate resolution. 
 
Any medical condition that is present at the time that the participant is screened will be 
considered as baseline and not reported as an AE. However, if the study participant9s condition 
deteriorates at any time during the study, it will be recorded as an AE.  
 
Changes in the severity of an AE will be documented to allow an assessment of the duration of 
the event at each level of severity to be performed. AEs characterized as intermittent require 
documentation of onset and duration of each episode. 
 
 
8 
STATISTICAL CONSIDERATIONS  
 
8.1 STATISTICAL HYPOTHESES 
 
Hypothesis 1: PHARM-DC will reduce post-discharge utilization reduction of 2.5% (% of patients 
with readmissions or ED visits within 30 days of hospital discharge) from a baseline of 27.5%. 
 
 
8.2 SAMPLE SIZE DETERMINATION 
 

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We will use a two-sided likelihood ratio test to compare the proportion of patients with utilization 
within 30 days of discharge between the intervention and usual care groups. Assuming 80% 
power and a type I error rate of 0.05, a two-sided Z test between two proportions with 4,888 
subjects per group would detect a difference of at least 2.49% from a baseline of 27.5%. Thus, 
our primary statistical analysis will be a two-sided Z test. We will also compare the baseline 
characteristics of those subjects across both arms to ensure there are no major differences. All 
enrolled patients will be analyzed. 
Table 5 shows that varying the baseline utilization proportion does not substantially alter the 
minimum detectable difference. We also performed a sensitivity analysis assuming that 7.5% of 
patients in the intervention arm were unreachable or refused a phone call. Even at this rate, 
which is our best estimate from our pilot data, we would have 80% power to detect a difference 
of 2.54%. Finally, these rates were robust to contamination rates of 2% among patients in the 
usual care arm. We believe this low rate is a reasonable estimate for contamination, because 
patients thought to have a clear need for these services will be excluded from the RCT, and 
because we believe that non-pharmacist clinicians will remain so busy that they will not begin to 
provide such services to other patients. 
 
 
 
 
 
 
 
For the qualitative study, the study will enroll up to 48 people in the focus groups, 15 people in 
the Year 2 interviews, and 50 people in the interviews per site. 
 
8.3 POPULATIONS FOR ANALYSES 
 
We will conduct the following analyses: 
 
• 
Intention-to-Treat (ITT) Analysis Dataset (i.e., all randomized participants) 
• 
Modified Intention-to-Treat Analysis Dataset (e.g., participants who had the in-hospital 
intervention but did not respond to post-discharge phone calls) 
• 
Per-Protocol Analysis Dataset: defines a subset of the participants in the full analysis 
(ITT) set who complied with the protocol sufficiently to ensure that these data would be 
likely to represent the effects of study intervention according to the underlying scientific 
model (e.g. participants who had both the in-hospital intervention and the post-discharge 
phone call). 
 
8.4 STATISTICAL ANALYSES 
 
8.4.1 GENERAL APPROACH 
 
• 
We will use chi-square tests, Analysis of Variance (ANOVAs), logistic regression, and 
means/medians for descriptive statistics.  
• 
We will use a 0.05 cutoff for p-values and 95% confidence intervals for statistical 
significance.  
Table 5. How Baseline Utilization Affects Minimum Detectable Difference 
Percentage of Patients with Utilization within 30 Days of Hospital Discharge 
Usual Care 
Intervention 
Minimum detectable difference 
30.0% 
27.44% 
2.56% 
27.5% 
25.01% 
2.49% 
25.0% 
22.59% 
2.41% 

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• 
Our primary statistical analysis will be a two-sided Z test. We will also compare the 
baseline characteristics of those subjects across both arms to ensure there are no major 
differences. All enrolled patients will be analyzed.  
• 
We will check for normality and log-transform variables if necessary for skewed 
distributions.  
• 
We will calculate all-cause unplanned post-discharge utilization within a 30-day period 
from the date of discharge from an index admission. Post-discharge utilization will 
include emergency department visits, observation stays, and inpatient readmissions. 
Planned readmissions will be excluded using the Centers for Medicare and Medicaid9s 
Planned Readmissions Algorithm. The algorithm assesses a dichotomous yes or no 
outcome of whether each admitted patient has any unplanned readmission within 30 
days. In accordance with the CMS algorithm, if a patient has more than one unplanned 
admission within 30 days of discharge from the index admission, only the first is 
considered a readmission. If the first readmission after discharge is planned, any 
subsequent unplanned readmission is not considered in the outcome for that index 
admission because the unplanned readmission could be related to care provided during 
the intervening planned readmission rather than during the index admission. 
 
8.4.2 ANALYSIS OF THE SECONDARY ENDPOINT(S) 
 
To assess the Reach of the intervention, we will examine differences in effectiveness 
across sites, and for patients of different ages, sex, medication literacy, taking different 
numbers of medications, and living in zip codes reflecting different median incomes. We 
hypothesize that the intervention will work best to prevent readmissions, will work 
equally at both sites, will work better for older patients, those with higher medication 
literacy, those taking more medications, and those from poorer zip codes. We will also 
explore effectiveness of the intervention before and after historical changes to the 
intervention and control groups, as well as when the primary outcome is restricted to 
include only medication-related post-discharge utilization or 7-day post-discharge 
utilization. However, we recognize that these underpowered analyses may be most 
useful for shaping future hypotheses. To ensure that no results are misinterpreted, we 
will report that any negative results may be due to inadequate power. 
The descriptive phase of analysis will include an assessment of the distributions and 
correlations of the aforementioned variables of interest. We will use logistic regression 
to examine these factors. We will also examine the potential interaction of covariates. 
We will explore collinearity using the condition index and with careful assessment of the 
correlation matrix. 
8.4.3 QUALITATIVE ANALYSES 
For the qualitative analysis of interviews and focus groups, we will combine a content-analysis 
approach with qualitative inquiry allowing us to discover and quantify key stakeholders9 
experiences and perceptions. We will use an iterative process to identify <a priori= themes based 
on the domains in the RE-AIM framework and to create <in vivo= themes as they emerge during 
coding (e.g., specific barriers to PHARM-DC implementation).xxxii Two coders will code each 
interview independently and then discuss variations until consensus is reached. After coding all 
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data under more general themes.110 We will use NVivo software which will allow for quantifying 
the number of key stakeholders who addressed these themes and their density (i.e., number of 
overall mentions). Theme density is a valid proxy for importance. In the final step of the 
qualitative analysis, we will prepare NVivo code reports (participant N and density) of salient 
themes and coding matrices related to significant interview findings. We will perform follow-up 
interviews as needed to supplement or clarify themes. We will also prepare descriptive statistics 
of all interview and focus group participants.  
We will take several measures to ensure rigorous analysis. All transcripts will be independently 
analyzed by Dr. Kennelty and two other researchers who will meet weekly during the qualitative 
analysis process to discuss each transcript and resolve disagreements through negotiated 
consensus.xxxiii Analysts will also maintain an audit trail throughout this process to document the 
fit between the raw data and the conclusions drawn. NVivo software will be used to code 
patterns among sites and individuals, and to code variations within and between key 
stakeholders. We will later triangulate survey results with interviews, focus groups, and on-site 
observations to better understand the impact of context on the experiences of key stakeholders.  
Finally, after conducting initial qualitative and quantitative analyses, we will use a mixed 
methods approach to further explore relationships between contextual factors, interventions, 
and outcomes.xxxiv Qualitative and mixed methods may be especially important if there are any 
differences between the two sites RCT outcomes and to develop hypotheses regarding possible 
reasons for our findings. 
 
8.4.4 COST-EFFECTIVENESS ANALYSES 
 
Costs are a critical consideration for health system leaders deciding to adopt an intervention, as 
noted by the RE-AIM model. Because the leadership at different hospitals may consider 
different factors when deciding whether to fund the PHARM-DC intervention, we will report the 
cost of implementing the PHARM-DC intervention in two ways: (1) the program costs per 
utilization event (readmission, observation stay, or ED visit) averted and (2) the incremental net 
cost from the health system perspective.  
Program Cost: The primary program cost will be the ongoing labor of the pharmacists who 
implement it. Startup costs will be minimal because hospital pharmacists can be trained to use 
the PHARM-DC Toolkit in only 1-2 hours, and no purchases of equipment or supplies are 
needed.  
 
We will ascertain pharmacist labor costs through a micro-costing approach employing accepted 
time and motion methodology used in our previous work.xxxv-xxxix Our published data collection 
tool, which was developed for admission medication histories, categorizes time spent on 
discussions with patients, family members, and caregivers, utilizing secondary resources 
(obtaining prior prescription and fill information), and utilizing the electronic health record to 
obtain, document, and communicate information.xl We will add categories pertinent to post-
discharge medication management (e.g., calling retail pharmacies to communicate that a 
medication has been stopped) and pilot the tool until all relevant activities have been 
categorized. 
Trained observers with a clinical background (e.g., research nurses, medical students) will 
document time use by study pharmacists on a minute-by-minute basis in real time. The 
observers will use the time-use data collection tool to record time spent on PHARM-DC 
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also record the number of days since discharge for the relevant patient (e.g., post-discharge day 
4). Because pharmacists will also complete non-intervention tasks each day, observers will 
follow pharmacists for up to an entire workday.  
To assure that the time-use data is representative, we will sample approximately 100 patient 
interactions (20 complete interventions, 20 discharge medication reconciliations, 20 post-
discharge phone calls, and 40 observations of usual care) by study pharmacists at each study 
site over a one-year period. To ensure that pharmacists have become efficient in providing the 
intervention, sampling will only occur in years two and three and pharmacists with less than two-
months experience with the intervention will be excluded.  
 
Time spent on PHARM-DC activities for study subjects by the number of days since 
discharge. For example, we will identify all study subjects for which study pharmacists spent 
time on post-discharge day 1, etc. This will enable us to calculate the mean amount of 
pharmacist time necessary to provide the PHARM-DC intervention on each post-discharge day, 
and then the mean total time across all days. After estimating the mean total time per patient, 
we will apply National Bureau of Labor Statistics wage and benefit data to calculate the 
intervention9s program cost per patient2.  
  Next, we will calculate the mean program cost necessary to avert each measured utilization 
event (e.g., readmission) by multiplying the number needed to treat to prevent the utilization 
event by the cost of applying the intervention to one patient. For some hospital decision makers, 
we expect this data, in combination with hospital-specific costs, to be useful in deciding whether 
(and to what extent) to implement PHARM-DC. One example of hospital-specific costs would be 
anticipated HRRP costs (CMS readmissions penalties). 
Costs of Post-Discharge Utilization: We will ascertain the total cost of all readmissions, 
observation stays, and ED visits with 30 days of discharge for all trial patients. At least 80% of 
patients are likely to return to the study hospitals; in this case, we will obtain charge data for the 
return visits and apply hospital-specific cost-to-charge ratios provided by hospital administrators. 
For return visits to outside hospitals, we will obtain charges for inpatient hospitalizations and ED 
visits using statewide data sets and calculate costs by applying cost-to-charge ratios for hospital 
services published by the Centers for Medicare and Medicaid Services.  
Net Costs: Next, we will calculate net cost for each patient from the health system perspective 
by subtracting the cost of any post-discharge utilization from any program costs (program costs 
are zero in the control group). Because we will apply a 30-day time horizon, discounting will not 
be used. We will calculate and test differences in mean values. Finally, we will calculate the 
difference between the intervention and control group to estimate incremental net costs per 
patient from the health system perspective. 
8.4.5 SECONDARY DATA ANALYSIS: EXAMINE EFFECTS OF PHARM-DC 
INTERVENTION ON INITIATION AND DEPRESCRIBING OF 
BENZODIAZEPINE-RECEPTOR AGONISTS 
 
The following secondary analyses of trial data are planned to examine effects of the PHARM-
DC intervention on (1) the initiation of new outpatient prescriptions of benzodiazepine-receptor 
agonists (BZRs) and (2) the deprescribing of BZRs among patients taking BZRs prior to 
hospitalization: 
 
1. Among patients without a BZR prescription on admission, we will examine the difference in 
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between the intervention group and the control group. We will use logistic regression using a 
generalized estimating equations approach and estimate adjusted predicted probabilities.3 We 
hypothesize that among patients without a BZR prior to hospitalization, the risk-adjusted 
probability of having a new discharge BZR prescription will be substantially lower (e.g. 35% 
lower) among patients who are enrolled in the PHARM-DC intervention compared to the control 
group. 
 
2. Among patients taking BZRs prior to hospitalization, we will use logistic regression to 
estimate the adjusted predicted probability of dose intensification among patients in the 
PHARM-DC intervention and the control group.3 We hypothesize that among patients with BZRs 
prior to hospitalization, the risk-adjusted probability of experiencing a dose increase will be 
substantially lower (e.g. 35% lower) among patients who are enrolled in the PHARM-DC 
intervention compared to controls. 
 
Outcome measures: We will create two measures: (1) a dichotomous variable for a new 
discharge prescription of BZRs among patients not taking BZRs prior to admission, and (2) a 
dichotomous variable for an increased dose prescription among patients taking BZRs prior to 
admission.  
 
8.4.6 SECONDARY DATA ANALYSIS: EXAMINE EFFECTS OF PHARM-DC 
INTERVENTION ON FALL-RELATED INJURIES AMONG OLDER ADULTS 
WITH ALZHEIMER9S DISEASE AND RELATED DEMENTIAS 
 
The following secondary analyses of trial data are planned to examine effects of the PHARM-
DC intervention on post-hospitalization fall-related injuries among all trial participants and 
among the subgroup of older adults with Alzheimer9s disease and related dementias (ADRD):   
 
1. We will investigate whether the intervention reduces the severity of fall-related injuries by 
using a two-sided Z test to compare the proportions of severe injuries (e.g., hip fractures) and 
acute care utilization (hospitalization and ED visits) between the intervention and control groups. 
We hypothesize that the PHARM-DC intervention reduces the severity of fall-related injuries by 
mitigating medication-related risk factors. 
 
2. We will use a two-sided Z test to compare the proportion of those who have post-
hospitalization healthcare utilization for fall-related injuries within 30 days among all trial 
participants and among individuals with ADRD. We hypothesize that the PHARM-DC 
intervention reduces fall-related injuries among individuals with ADRD. We also hypothesize 
that the benefit of the intervention is larger among individuals with ADRD compared to 
individuals without ADRD by addressing both general and ADRD-specific medication-related 
risk factors for falls. 
 
3. We will examine the effect of the intervention among individuals with dementia with Lewy 
bodies (ICD-10-CM code: G31.83) and individuals with an ADRD diagnosis code associated 
with the ICD-10-CM code for Parkinson9s disease (G20), because previous literature suggests 
that they have a much higher incidence of fall-related injuries, as compared to individuals with 
Alzheimer9s disease.4  
 
4. We will describe the difference in the nature of falls among individuals with and without ADRD 
using external causes of morbidity codes (e.g., falls from bed vs. falls while walking).  
 

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Variables: We will check for balanced demographics and comorbidities across arms in all 
analyses. In cases with imbalance, we will consider post-hoc adjustment, including by 
considering sex as a biological variable. Individuals with ADRD will be identified by the ICD-10-
CM codes based on hospital claims, adapting the algorithm from the Chronic Conditions Data 
Warehouse.5  
 
Outcome measures: We define post-hospitalization fall-related injuries as healthcare utilization 
(hospitalization, ED visits, urgent care visits, or office visits) due to fall-related injuries within 30 
days of discharge of the index admission. We will link Medicare claims data to trial data to track 
this outcome at the individual patient level. In order to link Medicare claims data to trial data, 
linking variables for trial participants will be requested through the Honest Enterprise Research 
Broker (HERB) Committee at Cedars-Sinai and will include: (1) social security numbers (SSNs), 
(2) Medicare Beneficiary Identifiers (MBIs), and (3) Medicare Health Insurance Claim Numbers 
(HICNs). We anticipate data may be missing on linking variables for some participants (e.g., 
patients without an SSN number), and therefore, will request patient age, SSNs, MBIs, and 
HICNs to ensure data for all participants can be linked to claims data. The same linking 
variables in (1)-(3) will be requested from the Brigham and Women9s Hospital site and uploaded 
to a password-protected Box folder hosted on the Cedars-Sinai network (for further details, see 
section 9.1.5.1 DATA COLLECTION AND MANAGEMENT RESPONSIBILITIES). Linking 
variables for participants at both study sites will be mailed on a flash drive to the Centers for 
Medicare & Medicaid Services (CMS) based on their submission requirements for requesting 
claims data. Medicare claims data will subsequently be sent from CMS to the study team at 
Cedars-Sinai on a flash drive through postal mail.  
 
Sensitivity analysis: It is possible that we under-detect individuals with ADRD diagnoses if the 
ADRD diagnoses are not coded diligently on hospital claims. To mitigate this issue, we will 
conduct a sensitivity analysis by using electronic health record (EHR) data prior to the index 
admission, so that we can include those who were diagnosed with ADRD in the outpatient 
setting. Because this can only be done for patients who receive outpatient care from doctors 
using our EHR, it would introduce bias if used as part of the overall analysis. However, it can be 
done among this group to test the sensitivity of detecting ADRD via claims. 
 
8.4.7 SECONDARY DATA ANALYSIS: PROPENSITY SCORE ANALYSIS AT 
BRIGHAM AND WOMEN9S HOSPITAL  
 
Admission medication reconcilitation is theorized to be one of the key components of the 
PHARM-DC intervention that may contribute to reduced 30-day post-discharge utilization. At the 
Brigham and Women9s Hospital (BWH) site, many more patients were eligible for enrollment in 
the PHARM-DC clinical trial than were actually enrolled due to limited pharmacist staff 
bandwidth. For this reason, patients who were eligible, yet were not enrolled, did not receive 
admission medication reconcilitation (also known as a <Best Possible Medication History= 
[BPMH] in the literature).  
 
As a secondary analysis of trial data, we propose to compare patients who were eligible for trial 
enrollment and enrolled to patients who were eligible and not enrolled at BWH. We will perform 
a propensity score analysis to predict enrollment into the PHARM-DC clinical trial at the 
individual patient-level. Resulting propensity scores will then be used to identify matches 
between patients at BWH who were eligible and enrolled vs. eligible and not enrolled during the 
study period for comparison. The outcome of interest is 30-day post-discharge utilization (same 
hospital).  
 

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Data will be retrieved retrospectively from the electronic health record at BWH as previously 
described in this IRB protocol. Specifically, variables in the propensity model will include: 
 
1. Time of day of hospital admission 
2. Day of week of hospital admission 
3. Day of week of hospital discharge 
4. Admit type 
5. Admit service 
6. Discharge service 
7. Hospital length of stay 
8. Discharge location 
9. Admissions medications list 
10. High-risk medications list at admission 
11. Calendar quarter 
12. Insurance type 
13. Admission source 
14. Interaction effect between length of stay and day of week of admission 
 
9 
SUPPORTING DOCUMENTATION AND OPERATIONAL CONSIDERATIONS 
 
9.1 REGULATORY, ETHICAL, AND STUDY OVERSIGHT CONSIDERATIONS 
 
 
9.1.1 INFORMED CONSENT PROCESS 
 
Hospital Discharge Study 
Justification for Randomization of the PHARM-DC Intervention with a Waiver of Informed 
Consent 
As noted above, both sites already conduct the majority of components of the PHARM-DC 
intervention on some patients. Because it is currently used, but allocation is determined by 
operational convenience (e.g., pharmacists try to provide this service to everyone they think 
would benefit, but only reach some patients), there is justification for an RCT with a waiver of 
informed consent.  
Because the RCT will only change how the intervention is allocated (from operational 
convenience to randomization), it will not require informed consent. This approach was used by 
Dr. Pevnick in his recent RCT. 
We are asking for a waiver of informed consent for the following reasons: 
1. 
Feasibility: Our primary aim in this study is to examine utilization. Our study design is 
powered to detect a clinically meaningful difference between the two study groups 
(intervention and control), but to detect this difference, we require a very large 
sample size. We are looking to recruit several thousand patients in the study period. 
Given the high workload of the clinical pharmacists participating in this study, it would 
not be feasible for us to conduct this study without a waiver of consent [See Weijer 
C, Grimshaw JM, Taljaard M, Binik A, Boruch R, Brehaut JC, et al. Ethical issues 
posed by cluster randomized trials in health research. Trials. 2011;12:100] 

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2. 
Minimal Risk: The risks to the patients are minimal. After the medication history is 
taken for patients, the patients are randomized into either the treatment or control 
group. However, if a clinician believes that the patient would benefit from the 
pharmacist consult and/or post-discharge phone call, the patient will meet with the 
pharmacist regardless of whether they are in the study. Thus, any patient who needs 
the pharmacist services will receive the appropriate care. The pharmacist 
participating in the intervention will provide a consult to the physician about 
medications that should be changed, but the physician will have the final say about 
any medication changes. This is equivalent to the physician consulting an online 
resource or receiving a computerized alert about medication recommendations 
(clinical decision support). Participating in the study will not adversely affect the 
rights or welfare of the participants since patients who request a meeting with a 
clinical pharmacist or situations where the attending physician believes the patient 
should meet with the clinical pharmacist will have every right to do so.  
3. 
Reducing Risk: Since this study is a very low risk intervention, we believe that adding 
a signed consent form would actually introduce more risk because it would now 
introduce a document that could identify the participants. We are planning on 
analyzing the study data at the completion of the intervention and the data will be 
extracted and only accessed by select study staff. Incorporating documents with PHI 
may increase the risk for patients of loss of confidentiality.  
4. 
Decrease of Data Validity and Quality: Patients who are randomized to the control 
group may be more likely not to participate in the study (a phenomenon known as 
<resentful demoralization=) so there may be systematic bias introduced if patients are 
asked to consent, which could decrease the validity of study results [see Rebers S, 
Aaronson NK, Van Leeuwen FE, Schmidt MK. Exceptions to the rule of informed 
consent for research with an intervention. BMC medical ethics. 2016 Dec;17(1):9.].  
The risk to subjects is no more than minimal risk to privacy. We have put several measures in 
place to protect the privacy of subjects and confidentiality of the data: 
[1] Personally identifying information will only be available to study personnel. 
[2] All identifiable (and de-identified) data will be in electronic format. These data will be stored 
and used entirely within CSMC computer systems on the CSMC network, where appropriate 
technical safeguards (including authentication, security and virus protection) are in place. Since 
the data originates on this network, the increase in risk is minimal. 
[3] All identifiers will be destroyed at the end of the study (the research data itself will be kept for 
seven years after completion of the research). 
During training, trainers will emphasize to pharmacists participating in this study additional, 
clinically-indicated services may be provided to control group patients to ensure that it is clear 
that routine services that are part of the PHARM-DC and that the toolkit should not be withheld 
from the control group if they are clinically indicated. This will ensure that patients in the control 
group will receive appropriate services if needed.   
Focus Groups and Interviews 
 
For the focus groups, we will provide an information sheet outlining the purpose, risks, and 
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Information sheets will be Institutional Review Board (IRB)-approved, and the participant will be 
asked to read and review the document. The investigator will explain the research study to the 
participant and answer any questions that may arise. A verbal explanation will be provided in 
terms suited to the participant9s comprehension of the purposes, procedures, and potential risks 
of the study and of their rights as research participants.  Participants will have the opportunity to 
carefully review the written information sheet and ask questions prior to participating in the focus 
group. Participants will be informed that participation is voluntary and that they may withdraw 
from the study at any time, without prejudice.  
 
Focus groups and interviews present no more than minimal risk. Signed consent will not be 
obtained for focus group/interview participants. The focus groups/interviews will be conducted in 
areas which the staff frequently occupy as part of their daily tasks and the questions will require 
no more disclosure of information than would be routinely occur in their conventional work 
environment. Attendance and participation in the focus group will be considered consent to 
participate. It is also possible that interviews and/or focus groups will take place via video 
conferencing software (e.g. Webex) or over the phone. 
 
The qualitative information will not include any sensitive or incriminating information. Our study 
team will not collect more data than is necessary to answer the research question. However, 
questions could elicit negative comments about their health system. Focus group sessions and 
interviews will be recorded via audiotape and transcribed by research team members or a 
professional transcribing service. The audiotapes will be stored in locked file cabinets within 
locked offices, and electronic transcriptions will also be housed on firewall protected servers, will 
not include subject names, and may only be accessed by select members of the research team. 
Names will be stripped from the transcribed interviews and focus group responses will reported 
only in aggregate. Names will be removed from the documentation material use for data 
analyses. 
 
The observations will take place at the two study sites (CSMC and BWH). They may include 
observations of patients/caregiver interactions. Researchers will not collect any PHI or 
identifiable information while observing these interactions. The qualitative information obtained 
during observations will not include any sensitive or incriminating information, or any information 
that could impact a subject9s employability. All observation data will be recorded with no 
identifiable information. Subjects will be provided with the information sheet which includes 
information on the observation component of the study and will be verbally notified that 
observations will occur prior to observations commencing. 
 
Focus group and interview participants will not sign a consent form. Keeping signed consent 
forms will only increase the chance of a breach of confidentiality. Further, no identifying 
information, including any PHI elements, will be asked during the focus group. If a subject 
mentions any PHI elements during the focus group, it will not be transcribed and will be deleted 
from the audio-recording. 
 
Time and Motion Study 
 
Eligible participants (pharmacists working on the intervention) will be approached at the 
beginning of the day and will be given an information sheet. The information sheet will include 
information about the participant observation. The investigator will explain the research study to 
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in terms suited to the participant9s comprehension of the purposes, procedures, and potential 
risks of the study and of their rights as research participants.   
 
 
9.1.2 CONFIDENTIALITY AND PRIVACY  
 
Participant confidentiality and privacy is strictly held in trust by the participating investigators, 
their staff, and the sponsor(s) and their interventions. Therefore, the study protocol, 
documentation, data, and all other information generated will be held in strict confidence. No 
information concerning the study or the data will be released to any unauthorized third party 
without prior written approval of the sponsor.  
 
All research activities will be conducted in as private a setting as possible. 
 
The study monitor, other authorized representatives of the sponsor, representatives of the 
Institutional Review Board (IRB), regulatory agencies or pharmaceutical company supplying 
study product may inspect all documents and records required to be maintained by the 
investigator, including but not limited to, medical records (office, clinic, or hospital) and 
pharmacy records for the participants in this study. The clinical study site will permit access to 
such records. 
 
The study participant9s contact information will be securely stored at each clinical site for internal 
use during the study. At the end of the study, all records will continue to be kept in a secure 
location for as long a period as dictated by the reviewing IRB, Institutional policies, or sponsor 
requirements. 
 
Study participant research data, which is for purposes of statistical analysis and scientific 
reporting, will be transmitted to and stored at CSMC. This will not include the participant9s 
contact or identifying information. Rather, individual participants and their research data will be 
identified by a unique study identification number. The study data entry and study management 
systems used by clinical sites and by CSMC research staff will be secured and password 
protected. At the end of the study, all study databases will be de-identified and archived at the 
CSMC. 
 
Qualitative Study 
 
The qualitative data will be stripped of identifiers and will be analyzed by researchers at the 
University of Iowa.  The qualitative information will not include any sensitive or incriminating 
information. Our study team will not collect more data than is necessary to answer the research 
question. However, questions could elicit negative comments about their health system. Focus 
group sessions and interviews will be recorded via audiotape and transcribed by research team 
members or a professional transcribing service. The audiotapes will be stored in locked file 
cabinets within locked offices, and electronic transcriptions will also be housed on firewall 
protected servers, will not include subject names, and may only be accessed by select 
members of the research team. Names will be stripped from the transcribed interviews and 
focus group responses will reported only in aggregate. Names will be removed from the 
documentation material use for data analyses. 
 
We have added relevant text to the information sheets to note that investigators may conduct 
observations with pharmacists. Participants will be informed that participation is voluntary and 
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will not include any sensitive or incriminating information. Our study team will not collect more 
data than is necessary to answer the research question. However, questions could elicit 
negative comments about their health system. Observations will be given codes and they will be 
stored separately with a linking list. No patient-level data will be recorded. 
 
Time-and-Motion Study 
 
Patients will be assigned a unique identifier within the online data collection tool so that no PHI 
is transmitted over the internet. Only IRB-approved study staff will have access to the linking file 
which will be stored separately from patient-level data on Box. Data will only be accessed on a 
password protected, encrypted study site computer.  
 
Pharmacists will be provided a study information sheet prior to observations taking place, and 
patients who may have interactions with the pharmacists will be told that this is part of an 
ongoing study examining pharmacist activities. Participants will be reminded at the beginning of 
the observation that they are not required to participate in the observations and can stop the 
observation at any time.  
 
 
9.1.3 KEY ROLES AND STUDY GOVERNANCE 
Provide the name and contact information of the Principal Investigator and the Medical Monitor. 
Principal Investigator 
Joshua Pevnick, MD, MS 
CSMC  
8700 Beverly Blvd, West 
Hollywood, CA 90048 
310-423-6976 
Joshau.pevnick@cshs.org 
 
9.1.4 SAFETY OVERSIGHT 
 
Safety oversight will be under the direction of a Data and Safety Monitoring Board (DSMB) 
composed of individuals with the appropriate expertise. Members of the DSMB are independent 
from the study conduct and free of conflict of interest, or measures should be in place to 
minimize perceived conflict of interest.  The DSMB will meet at least semiannually to review 
adverse events. The DMSB will operate under the rules of an approved charter that will be 
written and reviewed at the organizational meeting of the DSMB. At this time, each data element 
that the DSMB needs to assess will be clearly defined. The DSMB will provide its input to NIA. 
 
9.1.5 DATA HANDLING AND RECORD KEEPING  
 
Each participating site will maintain appropriate medical and research records for this trial, in 
compliance with ICH GCP and regulatory and institutional requirements for the protection of 
confidentiality of participants.  As part of participating in a NIH-sponsored or NIH-affiliated study, 
each site will permit authorized representatives of the NIH, sponsor, and regulatory agencies to 
examine (and when permitted by applicable law, to copy) clinical records for the purposes of 
quality assurance reviews, audits, and evaluation of the study safety, progress, and data 
validity. Describe in this section who will have access to records.   

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9.1.5.1 DATA COLLECTION AND MANAGEMENT RESPONSIBILITIES  
  
Clinical data (including adverse events (AEs), concomitant medications, and expected adverse 
reactions data) and clinical laboratory data will be entered into RED-Cap, a 21 CFR Part 11-
compliant data capture system provided by CSMC. The data system includes password 
protection and internal quality checks, such as automatic range checks, to identify data that 
appear inconsistent, incomplete, or inaccurate. Clinical data will be entered directly from the 
source documents. 
 
To evaluate trial outcomes, data from the Brigham and Women9s Hospital site will be 
transmitted to the coordinating study team at Cedars-Sinai. Data transmission, storage, and 
management will adhere to the following procedures for data security and privacy:  
 
• 
Secure storage: Data will be housed in a password-protected, HIPAA-compliant secure 
storage system, Box, within the Cedars-Sinai network with access restricted to approved 
members of the research team.  
• 
Limited Access: Private identifiable information, will be accessible only to IRB approved 
study team members with current IRB training. 
• 
Unique ID Numbers: Each patient will be assigned a unique ID number.  
• 
Removal of Identifiers: Direct identifiers (like name or MRN) will be removed from the 
research records and destroyed as soon as scientifically possible and maintained only as 
long as necessary to abstract, analyze and verify data.  
• 
Storage of Physical Records: This study will not include the storage of physical records. 
 
 
9.1.5.2 STUDY RECORDS RETENTION  
 
Study documents should be retained for a minimum of 2 years after the last approval of a 
marketing application in an International Conference on Harminosation (ICH) region and until 
there are no pending or contemplated marketing applications in an ICH region or until at least 2 
years have elapsed since the formal discontinuation of clinical development of the study 
intervention. These documents should be retained for a longer period, however, if required by 
local regulations. No records will be destroyed without the written consent of the sponsor, if 
applicable.  
 
9.1.6 PUBLICATION AND DATA SHARING POLICY 
 
This study will be conducted in accordance with the following publication and data sharing 
policies and regulations: 
 
National Institutes of Health (NIH) Public Access Policy, which ensures that the public has 
access to the published results of NIH funded research. It requires scientists to submit final 
peer-reviewed journal manuscripts that arise from NIH funds to the digital archive PubMed 
Central upon acceptance for publication. 
 
This study will comply with the NIH Data Sharing Policy and Policy on the Dissemination of NIH-
Funded Clinical Trial Information and the Clinical Trials Registration and Results Information 
Submission rule. As such, this trial will be registered at ClinicalTrials.gov, and results 
information from this trial will be submitted to ClinicalTrials.gov. In addition, every attempt will be 

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made to publish results in peer-reviewed journals.  Data from this study may be requested from 
other researchers 2 years after the completion of the primary endpoint by contacting Josh 
Pevnick, the study PI. 
 
9.1.7 CONFLICT OF INTEREST POLICY 
 
The independence of this study from any actual or perceived influence, such as by the 
pharmaceutical industry, is critical.  Therefore, any actual conflict of interest of persons who 
have a role in the design, conduct, analysis, publication, or any aspect of this trial will be 
disclosed and managed. Furthermore, persons who have a perceived conflict of interest will be 
required to have such conflicts managed in a way that is appropriate to their participation in the 
design and conduct of this trial.  The study leadership in conjunction with the <specify NIH 
Institute or Center (IC)> has established policies and procedures for all study group members to 
disclose all conflicts of interest and will establish a mechanism for the management of all 
reported dualities of interest. 
 
 

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9.2 PROTOCOL AMENDMENT HISTORY 
 
 
Version 
Date 
Description of Change  
Brief Rationale 
4.0 
10/22/2020 Changed inclusion criteria of age 
from <>65 years old= to <>55 
years old=. 
After 43 weeks of 
randomization, the minimum 
patient enrollment age was 
reduced from 65 years to 55 
years to enhance study 
enrollment due to 
unexpected COVID-19 
impacts on participant 
enrollment. 
5.0 
12/15/2020 1. Added exclusion criteria for 
patients with suspected or 
confirmed diagnosis of COVID-
19. 
 
2. Added description of 
pharmacist communication with 
key inpatient providers as part of 
the intervention. 
1. Patients admitted with a 
suspected or confirmed 
diagnosis of COVID-19 
constitute a significantly 
different patient population 
than that which is current 
under study in the PHARM-
DC trial. 
 
2. This description was 
added to more clearly 
describe activities being 
delivered as part of the 
intervention by pharmacists 
at both study sites. 
6.0 
2/16/2021 
Added sections: 
 
8.4.5. Examine effects of 
PHARM-DC intervention on 
initiation and deprescribing of 
benzodiazepine-receptor agonists 
 
8.4.6 Examine effects of PHARM-
DC intervention on fall-related 
injuries among older adults with 
Alzheimer9s disease and related 
dementias 
These sections were added 
to describe pre-planned 
secondary data analyses. 
7.0 
4/20/2021 
Updating the definition of adverse 
events/severe adverse events in 
Section 7.2.4 
To clarify the time period and 
frequency for event 
assessment and follow-up 
8.0 
6/25/2021 
Updates to time-and-motion study 
procedures  
To clarify data collection, 
data management, and data 
analyses for the time-and-
motion study 
9.0 
2/16/2022 
1. Clarified handling of elective 
readmissions in calculating the 
To clarify study procedures, 
additional secondary 

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primary outcome of 30-day post-
discharge utilization 
 
2. Clarified procedures for study 
coordinators to stop randomizing 
additional patients if pharmacist 
workload capacity is exceeded 
 
3. Updated 1 reference that was 
recently published 
 
4. Added secondary subgroup 
analyses, including outcome 
comparisons by:  
(a) patient age group, 
(b) limited English proficiency as 
a proxy for low medication 
literacy,  
(c) before and after historical 
changes to the intervention and 
control arm, 
(d) restriction to medication-
related post-discharge utilization, 
and 
(e) restriction to 7-day post-
discharge utilization.   
subgroup analyses, and 
update references. 
10.0 
3/17/2022 
1. Notification of request for a 
"one-time operational report" 
without switching our data source. 
For quality assurance, one-time 
operational report(s) will be 
obtained from the Emergency 
Department and cross-checked 
with the EIS report to ensure all 
patients who may be eligible for 
the study are being accurately 
identified. We believe our existing 
EIS reporting/code may contain 
errors and need to obtain the 
operational report in order to 
ensure validity of our subject 
recruitment. 
 
2. Specified demographic 
variables to be collected from 
participating pharmacists. 
Subjects (pharmacists) were 
already previously informed of 
demographic data collection. 
Information will be collected via 
the pharmacist demographic data 
1. Operational report needed 
form the ED to verify EIS 
daily reports are sufficiently 
capturing all potential, 
eligible patients for PHARM-
DC enrollment.  
 
2. Confirmation and approval 
of specific pharmacist 
demographic variables 
requested for time and 
motion manuscript. 
 
3. IRB analyst instructed this 
clerical change when 
requesting information for the 
operational report 
clarification. 

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collection form (attached) 
forwarded to their department 
manager. 
 
3. Clarified that the daily 
admissions reports used for 
subject enrollment are and have 
been generated by EIS. 
11.0 
6/2/2022 
1. Added patient identifiers to be 
obtained for Dr. Gotanda9s 
secondary analysis of trial data  
 
2. Added secondary outcomes: 
30-day mortality and effect of the 
intervention on each type of 
utilization considered separately 
(ED visits alone, observations 
stays alone, readmissions alone) 
 
3. Moved description (list) of 
pharmacist demographics from 
secondary outcomes to Study 
Design section.  
To link Medicare claims data 
to trial data 
 
Specification of additional 
secondary outcomes to be 
assessed for main trial. 
 
 
 
 
 
Moved to correct location as 
these were not secondary 
outcomes. 
12.0 
9/9/2022 
Clarified recruitment strategies for 
focus groups and interviews 
under Section 5.3   
Clarified that an honorarium 
will be offered to nurses and 
physicians as a strategy to 
enhance recruitment of these 
professionals for focus 
groups and/or interviews. 
 
13.0 
11/9/2022 
Clarified data collection and 
management procedures for Dr. 
Gotanda9s secondary analysis 
under sections 8.4.6 and 9.1.5.1. 
Clarified procedures for 
maintaining privacy and 
security of patient identifiers 
transmitted from the Brigham 
and Women9s Hospital site to 
the coordinating study team 
at Cedars-Sinai. 
14.0 
11/17/2022 Increased focus group 
honorariums by 25% for 
physicians (from $200 to $$250) 
and for nurses (from $100 to 
$125).  
Requesting increase to focus 
group honorariums by 25% 
to account for gift cards 
being taxed as taxable 
income for the focus group 
participants who are 
employees of the study site. 
15.0 
12/29/2022 Added Appendix A 
 
 
 
To clarify data elements to 
be extracted from the 
electronic health records at 
study sites for the purpose of 
evaluating trial outcomes 

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16.0 
8/25/2023 
Added Section 8.4.7 (secondary 
analysis) 
To clarify secondary analysis 
for propensity score 
matching at BWH 
 
10 APPENDIX A 
List of data elements to be requested from electronic health records at study sites 
Unless otherwise specified, the following data elements are requested at the time of admission for the 
index hospital admission (CSN’s will be provided): 
1. Index hospital admission date 
2. Index hospital discharge date 
3. Index admission encounter type: emergency department, inpatient, or observation visit 
4. Body mass index (BMI) 
5. Charlson Comorbidity Index (CCI) and/or Elixhauser Comorbidity Index 
a. Age-adjusted CCI 
6. Count of the number of hospital admissions in 3 years preceding index admission 
7. Count of medications prior to admission 
8. Count of medications at discharge 
9. Date of birth 
10. Date of death 
11. Discharge location 
12. Education level 
13. Estimated glomerular filtration rate (mL/min) 
14. Ethnicity 
15. ICD-9 and ICD-10 diagnosis codes (from physician billing, hospital billing, and problem list) at 
admission 
16. ICD-9 and ICD-10 diagnosis codes (from physician billing, hospital billing, and problem list) at 
discharge 
17. Date of diagnosis (associated with diagnosis codes, see #15 and #16) 
18. Insurance type (e.g., Medicare, Medicaid, dual eligible, private, uninsured) 
19. Interpreter needed (yes/no)? 
20. Length of stay 
21. Marital status 
22. Medication Adherence and Literacy Scale (MedAL) score at hospital discharge 
23. Medication names prior to admission 
a. Medication sigs, medication meta-data (class, subclass, dose dispensed etc.), if available 
24. Medication names at discharge 
25. Medication category (i.e., anticoagulant, antiplatelet, antihypoglycemics) 
26. Patient's home address 
a. National Deprivation Index 
27. Primary language 
28. Race 

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29. Sex/gender 
30. Social history (including smoking status, alcohol use status, and employment status), if available  
31. Zip code 
The following data elements are requested for all encounters within 30 days after hospital discharge of 
the index admission: 
32. CSN’s for all encounters within 30 days after hospital discharge 
33. Encounter dates 
34. Encounter type (e.g., emergency department, inpatient, or observation visit) 
35. Location of encounter (e.g., hospital, emergency department, office) 
36. Was the encounter preceded by an emergency department visit (yes/no)? 
37. For encounters, all available ICD-9 and ICD-10 diagnosis codes at admission 
38. For encounters, all available ICD-9 and ICD-10 diagnosis codes at discharge 
39. For encounters, all available procedure codes (ICD, CPT, Healthcare Common Procedure Coding 
System [HCPCS] codes) during encounter 
40. For encounters, all available external cause of injury codes (<E-codes=) at admission 
41. For encounters, all available external cause of injury codes (<E-codes=) at discharge 
42. For encounters, date of diagnosis, procedure, and external cause of injury (see codes for #37-#41) 
43. Source of encounter data for #37-41 (e.g., institutional claims, professional claims), if available 
 
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