Enhancing Medication Safety in Children With Polypharmacy Using Parent- Reported Symptom Assessments
Conditions: Neurologic Disorder, Chronic Disease, Pediatric Disorder
Sponsor: University of Colorado, Denver

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COMIRB Protocol 
COLORADO MULTIPLE INSTITUTIONAL REVIEW BOARD 
CAMPUS BOX F-490    TELEPHONE:  303-724-1055  Fax:  303-724-0990 
 
 
 
Protocol #: 
 
 
16-2538 
Project Title: 
Parent-Reported Symptom Assessments in Children Taking 
Multiple Medications  
Principal Investigator:  
James Aaron Feinstein, MD MPH 
Version Date:  
 
January 7, 2019 
 
I. Hypotheses and Specific Aims:  
 
An increasing number of children with complex chronic conditions (CCCs) who have intractable 
illnesses or multi-organ dysfunction are exposed to daily polypharmacy.1-3 Parents of children with 
polypharmacy often administer 5 or more medications each day, sometimes for months1, including 
high-risk medications prescribed by many different specialists in multiple settings of care.4,5 While 
medications can be life-saving, polypharmacy increases the risk of additive adverse effects6, drug-
drug interactions2,3, and can lead to serious adverse drug events (ADEs). Pediatric ADEs result in 
over 4.3 million estimated ambulatory visits annually7, including >150,000 pediatric emergency 
room visits.8 Despite the risks associated with polypharmacy, we do not understand how 
polypharmacy escalates and how polypharmacy should be managed. To enable children to thrive at 
home using medications while minimizing unwanted symptoms, this proposal aims to implement a 
prospective, parent-reported symptom assessment system to guide and monitor pharmaceutical 
care for high-risk children. Strategies to improve recognition of problematic symptoms will have a 
substantial impact on the health of children. Thus, we propose the following specific aims, 
specifically focusing on the high-risk population of children with NI and polypharmacy: 
 
Aim 1: Conduct cross-sectional parent-reported symptom assessments (PRSA): In a clinic 
population of 300 children, we will administer an electronic validated symptom inventory to parents 
to advance our understanding of signal-to-noise and signal detection challenges in this population. 
 
Hypothesis 1a: Patients with higher level of polypharmacy have greater symptom diversity and 
intensity. 
 
Hypothesis 1b: Parent reports will identify more symptoms than concurrent medical record notes. 
 
Aim 2: Conduct a prospective cohort study to quantify the detection of known ADEs using 
PRSA: We will follow 50 children expected to have medication changes (empaneled in Aim 1) and 
assess whether using PRSA prior to and after specific medication changes detects known and 
expected side effects. 
 
Hypothesis 2: Known anti-epileptic side effects will be detected as within-person symptom 
changes following an anti-epileptic medication change of either a new drug start or a substantial 
dosage increase. 
 
II. Background and Significance:  
 
In 2010, more than 263 million outpatient prescriptions were dispensed to pediatric patients in the 
United States.9 According to the Institute of Medicine report “Preventing Medication Errors,” the 
outpatient “environment in particular should be a high priority [for medication safety] given the 
growing reliance on home care for increasingly complex [pediatric] medical conditions.”10 Children 
with complex chronic conditions (CCCs), such as intractable epilepsy or degenerative neurologic 
disease, rely on multiple medications to sustain their lives.11 Children with CCCs, who comprise 

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<5% of the pediatric population but are responsible for 40% of costs associated with 
hospitalizations12 are frequently exposed to daily polypharmacy.1-3,11 Children with polypharmacy 
may take >5 medications simultaneously, and these regimens frequently include complex mixtures 
of high-risk medications including psychotherapeutics, anticonvulsants, cardiovascular agents, and 
opioids.1,2,13,14 We know that the highest-risk children are exposed for many months to high levels of 
polypharmacy.1 These same children have multiple CCCs and technology-dependence, often with 
neurological impairment (NI), that makes self-report of adverse symptoms unreliable.1 The Best 
Pharmaceuticals for Children Act has prioritized the need for further study of outcome measures of 
drug safety and efficacy in children with intellectual and developmental disabilities.15 
 
Our scientific premise, that the successful use of medications in children is not without risk, is 
rooted in our prior research. Polypharmacy poses significant problems. Our prior work has 
demonstrated that polypharmacy increases the risk of 
additive side effects2,6 and significant potential drug-drug 
interactions (Figure 1),1-3,13 and can lead to serious adverse 
drug events (ADEs),7,8 defined as any adverse effect 
resulting from the use of a drug. Medication use has 
measureable risks: Pediatric medication errors and ADEs 
are frequent and costly,6,16-19 with an increased incidence 
among children with CCCs.8,20 Reports of pediatric ADEs 
submitted to the United States Food and Drug Administration 
have tripled over the past decade. Pediatric ADEs result in 
4.3 million estimated ambulatory visits annually.7 Our work 
has demonstrated that 150,000 ADE-related emergency 
room visits occur each year8 with an increased risk of 
subsequent prolonged hospitalizations.17 Strategies to 
improve safe medication practices, particularly through early 
recognition of problematic symptoms, will have a substantial 
impact on the health of children. 
 
Despite the risks associated with polypharmacy, we do not clearly understand precisely how 
polypharmacy escalates. Furthermore, we lack a system to detect developing problematic 
symptoms in children with medical complexity. The epidemiology of pediatric polypharmacy has 
largely been researched in the inpatient setting,11,21 and the management strategies do not easily 
translate to the ambulatory setting. Practices such as real-time assessment of patient data to 
assess for ADEs are not currently feasible in the ambulatory setting, where children are cared for 
by many providers across multiple settings of care.22 Thus, the use of a variety of uncoordinated 
and unproven management strategies is common.16,23 Part of the problem is that we do not 
thoroughly understand the sequence of events leading to increases in polypharmacy, hampering 
our ability to identify important periods of increased risk during which to intervene. Another part of 
the problem concerns the identification and management of problematic symptoms, which is 
complicated by the limited availability of objective patient data in the ambulatory setting. 
Furthermore, children with NI may experience multiple ongoing symptoms and this background 
symptom noise limits the conduct of clinical trials and of post-marketing surveillance studies to 
detect signals of ADEs. Our overarching hypothesis is that repeated parent-reported symptom 
assessments (PRSA) before and after medication changes will provide clinically pertinent 
information, improve signal detection, and enhance medication safety.24,25 
 
Fortunately, new research opportunities exist to address both issues. First, we can improve our 
understanding of the sequence of events leading to the escalation of polypharmacy, and thereby 
identify possible targets to control polypharmacy. Longitudinal Medicaid data contain the variables 
necessary to study daily medication use in children. Second, we can improve our recognition of 
potential ADEs by utilizing comprehensive symptom assessment techniques initially tested and 
validated in the field of palliative care.24 By prospectively assessing changes in parent-reported 
patient symptoms before and after medication changes, we aim to detect problematic symptoms 
Figure 1: Exposure to 3 serious 
potential drug-drug interactions 
increases by level of polypharmacy 

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earlier, in order to more efficiently alert prescribers of potential problems. If this proposal confirms 
that prospective parent-reported symptoms assessments in children with polypharmacy is feasible 
and improves our ability to identify medication-related issues, then the next step is to disseminate 
this approach and to standardize ambulatory medication monitoring practices.  
 
This proposal is significant because pediatric polypharmacy is associated with major morbidity and 
cost, but our ability to recognize, monitor, and manage problems associated with polypharmacy is 
underdeveloped. Therefore, the best way to elucidate factors involved in the escalation of 
polypharmacy is to use a large comprehensive database containing detailed medication data, and 
the best method to attempt to measure problematic symptoms in children with polypharmacy before 
and after medication changes is through prospective parent-reported symptom assessments. 
 
We believe that there are 3 ways in which the proposed research is innovative both conceptually 
and methodologically. First, we will apply a validated parent-reported symptom assessment tool 
tested in palliative care research in a novel manner to assess the prevalence of symptoms among 
children with polypharmacy. Second, our proposal potentially could demonstrate the utility of 
assessing changes in symptoms to identify ADEs in the ambulatory setting. Third, our proposal 
could provide evidence to support the use of parent-reported symptom assessments more broadly 
to evaluate other therapies and interventions in children with CCCs. 
 
III. Preliminary Studies/Progress Report:   
 
Preliminary Data Relevant to Specific Aim 1: Our study population will be drawn from the Special 
Care Clinic (SCC) for special needs patients at Children’s Hospital of Colorado (CHCO). Of 3,600 
active patients annually (and growing rapidly), 50% of children have ≥5 active total medications, 
and 25% have ≥10 total medications (Table 2). In 2015, there were at least 450 patients prescribed 
an anti-epileptic medication. 
 
Preliminary Data Relevant to Specific Aim 2: We conducted a review of the children cared for in the 
Special Care Clinic during 2015 and at least 450 children were prescribed an anti-epileptic 
medication. The majority of these children received at least 5 anti-epileptic prescriptions during the 
year. 
 
IV. Research Methods (We present the requested information in order by each aim). 
 
Overview: To accomplish our aims, we will focus on the population of children with neurological 
impairment (NI) because of their prototypical exposure to polypharmacy. However, the following 
approach will provide generalizable learning and is expected to translate to other high-risk 
populations. We will strictly apply the scientific method to ensure robust and unbiased experimental 
design, methodology, and analyses.  
 
 
 
Part A - Single Survey
During a Clinic Visit
Part B - Set of Internet Surveys at the Time of a New Medication
Survey 
(-7 days by recall)
Start (0 months)
End (12 months)
New 
Medication
Survey #2
(2 days)
Survey #1
(-1 days by recall)
Survey #3
(7 days)
Survey #4
(14 days)
A Complete Set of Surveys

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Identification of Neurologically Impaired (NI) Children: For aims 1 and 2, we will identify 
children with NI using ICD-9-CM and ICD-10-CM diagnostic codes that have been previously 
published and validated.26 Within the diagnostic classification scheme, sub-categories of types of NI 
(e.g. cerebral palsy, epilepsy) are available to facilitate comparisons and analyses between 
different types of NI, as necessary. 
 
Definition of Polypharmacy: No standard 
definition of pediatric polypharmacy exists. 
Conservatively, polypharmacy involves using ³2 
distinct drugs concurrently, although the adult 
definition is typically >5 medications. We are 
interested in the latter, because these are the 
children who are expected to have the greatest 
pharmacovigilance needs. We will use National Drug Codes (NDC) and the Anatomical Therapeutic 
Chemical (ATC) classification system27 to ensure that polypharmacy counts are based on distinct 
medications (i.e., two dosage forms of the same medication are counted as a single medication). 
We will exclude vaccinations and topical medications from our analyses. 
 
Aim 1: Conduct cross-sectional parent-reported symptom assessments (PRSA): In a clinic 
population of 300 children, we will administer an electronic validated symptom inventory to parents 
to advance our understanding of signal-to-noise and signal detection challenges in this population. 
 
Hypothesis 1a: Patients with higher levels of polypharmacy have greater symptom diversity and 
intensity. 
 
Hypothesis 1b: Parent reports will identify more symptoms than concurrent medical record notes. 
 
A. Outcome Measure(s): 
 
Aim 1a 
Outcome Measures: For general symptom burden, the global symptom score (continuous, from 0-
100).  
 
Exposure Variable: Medication count variable (continuous variable). 
 
Additional clinical covariates: We will collect additional clinical information, including biologically 
relevant variables, at the time of the visit (Table 3, below).  
 
Aim 1b 
Outcome Measures: Counts of distinct symptoms.  
 
Exposure Variable: PRSA versus clinic visit notes. 
 
B. Description of Population to be Enrolled: 
We will include all patients with NI and >5 scheduled medications aged 0-17 years-old and their 
parents. Because Aim 1 only requires a 1-day study period, the maximum age limit will be 17 years 
and 364 days. We will include patients with English or Spanish speaking parents (which represents 
96% of potential SCC patients), as the study instrument has been validated for both languages.28 
All eligible subjects and their primary parent caregiver will be screened and enrolled, without bias. 
We anticipate a gender distribution representative of the children cared for in the Special Care 
Clinic, and a 2:1 female-to-male ratio for their parent caregiver. 
 
C. Study Design and Research Methods: 
This will be a cross-sectional analysis of parent-reported symptoms among a cohort of 300 children 
with NI and polypharmacy recruited from the SCC.  
Table 2: Potential Subjects 
 
2012 
2013 
2014 
2015 
# of Meds 
SCC Patients (n=3600/year) 
0-4 
2,736 2,628 
2,376 1,800 
5-9 
540 
576 
756 
900 
³10 
324 
396 
468 
900 

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D. Description, Risks, and Justification of Procedures and Data Collection Tools: 
Study instrument: As the basis for PRSA, we will use the PediQuest Memorial Symptom 
Assessment Scale (PQ-MSAS), which is an adapted pediatric-specific version of the validated adult 
MSAS that assesses 24 physical and psychological symptoms over the past week (the forms are 
provided in the Appendix).24,29,30 The study instrument is designed to be completed by a full-proxy 
parent, and 2 versions tailored for specific age groups are available (0-3, 3-18 years-old). Spanish 
versions are available for both instruments. The study instrument has been previously tested and 
administered in electronic format to children with cancer and their parents. The PQ-MSAS contains 
24 symptom items, each with 4-point scores for domains of frequency, severity, and extent of 
bother.24 Based on these components, a global symptom score and individual symptom scores can 
be calculated (0-100 scale, with 100 being the worst).24 Both Drs. Feudtner24,29,30 and Fairclough31-
34 have extensive experience with the conduct and analysis of MSAS-related research.. 
 
Study Procedure: COMIRB will approve all recruitment materials and activities. Children and their 
primary parental caregivers will be recruited from the Special Care Clinic at the Children’s Hospital 
Colorado. For the studies, an investigator or research coordinator will review the SCC appointments 
daily. For all patients identified as potential subjects, we will review the medical record to ensure 
that the patient is eligible. Prior to study enrollment, the study team will obtain and document 
informed consent from the parent caregiver, as well as assent from the child depending on the level 
of NI. For eligible patients, data will be recorded prospectively through administration of the PRSA 
system. Children enrolled in the prospective cohort study will also have clinical information 
extracted from their EPIC electronic medical record at Children’s Hospital Colorado. For patients 
deemed ineligible at the time of first screening, we will record only patient age and the reason for 
ineligibility. 
 
Dr. Feinstein or a trained research assistant will obtain paper-based informed consent prior to the 
start of the clinic appointment. Before the visit, the parent or parent will then complete the electronic 
tablet-based study instrument. To minimize the burden of completing this symptom assessment, we 
will use an electronic delivery system employing Research Electronic Data Capture (REDCap), a 
secure, HIPAA-compliant web-based application designed for data collection for research studies, 
which is supported free of charge to University researchers. PQ-MSAS information will be 
transmitted directly to REDCap servers from the electronic capture device for subsequent scoring 
and analysis. Parents will receive a $25 reloadable debit card upon completion of the study 
instrument. Relevant clinical data (Table 3) will be electronically exported into REDCap from the 
electronic medical record (EMR) by the Research Informatics Team at Children’s Hospital 
Colorado. A member of the study team blinded to the results of the PRSA will review each subject’s 
electronic medical record (EMR) 48 hours after completion of the visit (to ensure complete chart 
data is reviewed) and extract symptoms from the progress note and/or coded visit diagnoses. 
 
Potential Risks and Justification: This is an observational study with minimal psychological, social, 
and/or legal risks to the subjects. The study design will not alter the natural course of medical care 
provided to the subject. The main potential risks are related to data privacy. Privacy concerns will 
be managed through appropriate data collection and storage. Confidentiality will be protected by 
limiting access to the research data and by maintaining coded databases. Each child and their 
primary parental caregiver will be assigned the same unique study number. PRSA data will be 
transmitted directly to REDCap servers from the electronic capture device for subsequent scoring 
and analysis, so that no private information is stored locally. Clinical EMR data will be exported by 
the Children’s Hospital Colorado Research Informatics group directly into a RedCap™ database 
compliant with regulatory requirements, again so that no intermediary repositories of data are 
created.  PRSA and clinical data will be linked by the study number. Paper-based consent forms 
and a key that links study numbers to patient medical record numbers will be kept in the primary 
investigator’s locked office within a badge-accessed research office suite (ACCORDS) within a 
badge-accessed research building with 24-hour on-site security. Medical record numbers will be 
required for the clinical EMR data extractions. Once data extraction has been completed, the key 

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will be destroyed in a confidential manner. All analyses will be completed on Dr. Feinstein’s whole 
disk-encrypted personal computer stored in a locked office within the badge-accessed ACCORDS 
research office suite. Additional detailed information about institutional safeguards for data safety 
are included in the Facilities & Other Resources attachment. 
 
Data Safety and Monitoring: The proposed studies do not meet the definition of clinical trials 
defined by Public Law as a drug or device trial, and a Data Safety and Monitoring Board will not be 
required. However, the PI will be responsible for ongoing oversight, review, and reporting of any 
unforeseen events related to the study. The consent form and study instruments will reinforce that 
the study information collected is not a communication with the participant’s provider. In the unlikely 
event that worsening symptoms are observed out-of-proportion to what is expected, the PI will 
review the case within 24 hours and potentially contact the patient’s provider. 
 
E. Potential Scientific Problems and Alternative Approaches:  
Given the cross-sectional design of this study, we fully acknowledge that we will not be able to 
investigate causality between medications and symptoms; that is the goal of Aim 3. 
 
F. Data Analysis Plan: 
To analyze Aim 1, we will generate descriptive statistics of individual symptoms present among 
eligible patients. We will stratify findings by level of polypharmacy, such that we can report, for 
example, “Among children with NI taking ³10 medications, in the past week 70% experienced 
constipation, 50% somnolence, and 20% pain.” We will further stratify by the most common 
medication classes. 
 
To test hypothesis 1a, that increasing levels of polypharmacy will be associated with a greater 
symptom burden, we will employ multiple linear regression techniques. We will model the number 
of medications as a continuous predictor variable with the symptom composite score as the 
continuous outcome variable. We will perform transformations of the outcome variable as 
necessary depending on its distribution. We will adjust for age, number of acute diagnoses, and 
number of CCCs. 
 
Power and Sample Size Calculation: To detect a minimum 4-point difference in global symptom 
scores (which has previously been reported as a clinically relevant difference24) between those 
children taking 5 medications and those children taking 10 medications, with a power of 80% and a 
significance of 0.05, we would require 168 subjects (112 in the 5 medication group and 56 in the 10 
medication group). 
 
To test hypothesis 1b, we will test differences in means of PRSA and clinic visit counts of 
symptoms using a two-sided paired t-test. 
 
Power and Sample Size Calculation: With a sample size of 300, significance of 0.05, standard 
deviation of 5, and correlation of 0.5, we will have 90% power to detect a minimum 1-point 
difference in mean counts. 
 
G: Summarize Knowledge to be Gained: 
Almost no drug trial or post-marketing surveillance data exist to guide medication safety in this 
complex population. Two major problems impede the identification of ADEs in children with NI and 
polypharmacy: 1) No system exists to assess multiple symptoms among children who cannot self-
report and 2) we lack prevalence information about the background symptoms commonly 
experienced in this population against which to look for problematic signals. Systematic parent-
based symptom inventories have been used to measure symptom burden in complex patient 
populations, such as children with terminal cancers.24,29,30 Like children with NI, these complex 
oncology patients often experience a multitude of symptoms24 with limited ability to report them. 
Thus, validated parent-based assessments have been developed to measure symptom burden at 

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the end of life, in order to tailor symptom management. Such tools have been successfully 
administered to children with cancer as frequently as monthly even during their terminal decline.24 
 
Deliverable: We will provide estimates of the most prevalent symptoms among children with NI and 
polypharmacy, stratified by both level of polypharmacy and certain drug classes. These data will 
help providers understand the symptoms typically encountered by their patients, in order to 
optimize their prescribing and monitoring decisions. This will also allow us to target classes of 
medications potentially associated with commonly experienced symptoms, which when prescribed, 
may benefit from proactive, increased monitoring. 
 
Aim 2: Conduct a prospective cohort study to quantify the detection of known ADEs using 
PRSA: We will follow 50 children expected to have medication changes (empaneled in Aim 2) and 
assess whether using PRSA prior to and after specific medication changes detects known side 
effects. 
 
Hypothesis 2: Known anti-epileptic side effects will be detected as within-person symptom 
changes following an anti-epileptic medication change of either a new drug start or a substantial 
dosage increase. 
 
A. Outcome Measure(s): 
 
Exposure Variable of Interest: New start prescription of an antiepileptic medication (or subsequent 
dose increase). 
 
Primary Longitudinal Outcome of Interest:  Reported symptom levels during peri-exposure 
monitoring. Symptoms will be assessed using the age-appropriate PQ-MSAS proxy form as 
described above in Aim 2. A priori, we will focus on the known ADE of somnolence6, and expand 
the analysis to other common and significant symptoms as identified in Aim 2. 
 
Covariates: We will collect additional clinical information, including biologically relevant variables 
(Table 3). 
 
B. Description of Population to be Enrolled: 
We will include all patients with NI and >5 scheduled medications aged 0-17 years-old and their 
parents. Because Aim 2 requires a 12-month study period, the maximum age limit at study 
enrollment will be 17 years and 0 days. We will include patients with English or Spanish speaking 
parents (which represents 96% of potential SCC patients), as the study instrument has been 
validated for both languages.28 All eligible subjects and their primary parent caregiver will be 
screened and enrolled, without bias. We anticipate a gender distribution representative of the 
children cared for in the Special Care Clinic, and a 2:1 female-to-male ratio for their parent 
caregiver. 
 
C. Study Design and Research Methods: 
This will be a 12-month prospective cohort study of 50 children with NI and polypharmacy, aged 2-
17 years-old who receive primary care in the SCC. To increase the likelihood of exposure to a new 
anti-epileptic, we will identify children with evidence of poor seizure control who are most likely to 
receive new anti-epileptic prescriptions, including an encounter in the past month for seizure control 
or current use of multiple anti-epileptics. 
 
D. Description, Risks, and Justification of Procedures and Data Collection Tools: 
Study Procedure: COMIRB will approve all recruitment materials and activities. Children and their 
primary parental caregivers will be recruited from the Special Care Clinic at the Children’s Hospital 
Colorado. For the studies, an investigator or research coordinator will review the SCC appointments 
daily. For all patients identified as potential subjects, we will review the medical record to ensure 
that the patient is eligible. Prior to study enrollment, the study team will obtain and document 

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informed consent from the parent caregiver, as well as assent from the child depending on the level 
of NI. For eligible patients, data will be recorded prospectively through administration of the PRSA 
system. Children enrolled in the prospective cohort study will also have clinical information 
extracted from their EPIC electronic medical record at Children’s Hospital Colorado. For patients 
deemed ineligible at the time of first screening, we will record only patient age and the reason for 
ineligibility. 
 
Dr. Feinstein or a professional research assistant 
will obtain paper-based informed consent upon 
identification of a potential subject. After 
enrollment, we will identify exposure events by 
generating daily EHR-based medication reports on 
enrolled subjects that will flag new AED 
prescriptions. When an event occurs, we will email 
the parent within 24 hours with a link to a REDCap 
survey containing the age-appropriate PQ-MSAS 
proxy form. If the parent has hasn’t yet 
administered the new prescription, we will ask 
about current symptoms; if they have, we will ask 
about the 24 hours prior to starting the medication. 
The parent will receive the survey at additional 
times (Figure 3) chosen to capture potential 
immediate, acute, and longer term symptoms. To 
minimize recall bias, all surveys will ask parents to 
report symptoms in the past 24 hours. We will also 
generate monthly EHR-based reports of subjects’ 
medication lists; office, ED, and hospital visits; 
and, any acute diagnoses. All data will be stored in 
a HIPAA-compliant REDCap database. Parents 
will also be compensated with a $25 reloadable debit card for up to 2 instances of peri-event 
monitoring and a $50 reloadable debit card upon study completion (the total possible 
reimbursement is $100). 
 
Potential Risks and Justification: This is an observational study with minimal psychological, social, 
and/or legal risks to the subjects. The study design will not alter the natural course of medical care 
provided to the subject. The main potential risks are related to data privacy. Privacy concerns will 
be managed through appropriate data collection and storage. Confidentiality will be protected by 
limiting access to the research data and by maintaining coded databases. Each child and their 
primary parental caregiver will be assigned the same unique study number. PRSA data will be 
transmitted directly to REDCap servers from the electronic capture device for subsequent scoring 
and analysis, so that no private information is stored locally. Clinical EMR data will be exported by 
the Children’s Hospital Colorado Research Informatics group directly into a RedCap™ database 
compliant with regulatory requirements, again so that no intermediary repositories of data are 
created.  PRSA and clinical data will be linked by the study number. Paper-based consent forms 
and a key that links study numbers to patient medical record numbers will be kept in the primary 
investigator’s locked office within a badge-accessed research office suite (ACCORDS) within a 
badge-accessed research building with 24-hour on-site security. Medical record numbers will be 
required for the clinical EMR data extractions. Once data extraction has been completed, the key 
will be destroyed in a confidential manner. All analyses will be completed on Dr. Feinstein’s whole 
disk-encrypted personal computer stored in a locked office within the badge-accessed ACCORDS 
research office suite. Additional detailed information about institutional safeguards for data safety 
are included in the Facilities & Other Resources attachment. 
 
Data Safety and Monitoring: The proposed studies do not meet the definition of clinical trials 
defined by Public Law as a drug or device trial, and a Data Safety and Monitoring Board will not be 
    1       2       3       4       5       6 mo
New Rx
-1   0  2       7     14   days
Somnolence
New Rx
A. New Rx Peri-Event Monitoring
Increase Rx
40
20
60 60
A
B
Somnolence
New Rx
B. Titrated Rx Peri-Event Monitoring
60
30
60 50
Study Period
-1   0  2       7     14   days
Figure 3: Design of Data Collection 

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required. However, the PI will be responsible for ongoing oversight, review, and reporting of any 
unforeseen events related to the study. The consent form and study instruments will reinforce that 
the study information collected is not a communication with the participant’s provider; the RedCap-
based internet PRSAs will reinforce that if a participant feels that their child is having a problem, the 
participant will need to call their child’s provider immediately. In the unlikely event that worsening 
symptoms are observed out-of-proportion to what is expected, the PI will review the case within 24 
hours and potentially contact the patient’s provider. 
 
E. Potential Scientific Problems: 
There is a risk of reporting fatigue that may result in missing or incomplete data. However, prior 
studies utilizing this instrument in a different capacity demonstrated that the majority of respondents 
completed the inventory on at least a monthly basis.30 We will encourage reporting through the use 
of electronic reminders.35 Should reporting fatigue occur, this will help us to elucidate the optimal 
frequency of reporting, and to complete our analyses, we will employ robust methods to handle 
missing longitudinal data. Additionally, there exists a small likelihood that children may receive 
specialty or emergency care outside the Children’s Hospital Colorado network, which may limit our 
ability to detect new medication starts. We have attempted to mitigate this by enrolling those who 
receive primary care in SCC. 
 
F. Data Analysis Plan:  
To test hypothesis 2, we will analyze the ability to detect changes in somnolence following the 
exposure of interest. To summarize the data, we will graphically depict individual trajectories over 
time, group trajectories over time, and report group means of key variables over time. During peri-
event monitoring, to test if exposure to a new (or subsequently increased) AED was associated with 
changes in somnolence, we will employ repeated measures mixed models to estimate the effects of 
a new-start AED on the level of somnolence over time. This type of analysis will enable us to study 
intra-individual changes in symptoms, while also providing flexibility in case missing data is present. 
We will model as fixed effects the time from start of AED and the starting level of polypharmacy; 
and, random effects to account for correlation among observations from the same patient. We will 
test using higher-order terms to model changes over time as necessary. 
 
Implementation Analysis: We will report measures of implementation including the ability of 
participants to carry out the intervention activities, positive/negative effects on the target population, 
cohort retention, and the amount and type of resources needed to implement the intervention.  
 
Power and Sample Size Calculation: The main objective is to determine whether we can detect 
changes in expected adverse symptoms (e.g. somnolence) within subjects using the study 
instrument. The prevalence and severity of symptoms is unknown among children exposed to 
polypharmacy. We based our conservative power calculation on studies using PQ-MSAS in 
children with cancer (the composite symptom score was 12.7 on a scale of 0-100, with a standard 
deviation of 8.6).30 We expect that in a population of NI children, the somnolence symptom score 
will be much higher and more variable with medication changes than the composite score we used 
for this power calculation.6 Because of the powerful within-subjects design, using a sample size of 
50 subjects, a power of 80%, an alpha of 0.05, a conservative within-subject correlation between 
symptom measurements of 0.5, and accounting for 10% missing data, we will have the power to 
detect a clinically meaningful average 4-point change in a 100-point symptom score, such as 
somnolence.24  
 
G.  Summarize Knowledge to be Gained:   
Amidst a complicated background of symptom noise, we will capitalize on parent-reported 
outcomes to improve the quantity and quality of data to detect significant symptom changes that 
could signal ADEs. Healthcare systems primarily rely on passive surveillance of ADEs, i.e. an 
adverse event is identified when a patient worsens enough to present for evaluation of a 
medication-related problem. The use of patient reported outcomes, particularly in patients with 
oncologic processes, has been shown to provide significantly more toxicity and symptom data than 

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clinician-based assessments36,37, facilitate improved communication between patients and 
providers, and to improve clinical outcomes.38 In both pediatric and adult cancer populations, 
electronic completion of symptom inventories is feasible and acceptable to patients.24,39  
 
Deliverable: Aim 2 will assess the ability of a PRSA system to detect changes in symptoms 
consistent with known ADEs, which will be ready for definitive evaluation of its impact on improving 
patient safety and for implementation in additional high-risk populations. 
 
H. References: 
 
1. 
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outpatient pediatric polypharmacy in Colorado fee-for-service Medicaid patients. 
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Feinstein J, Dai D, Zhong W, Freedman J, Feudtner C. Potential Drug-Drug Interactions in 
Infant, Child, and Adolescent Patients in Children's Hospitals. Pediatrics. 2015;135(1):e99-
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3. 
Dai D, Feinstein JA, Morrison W, Zuppa AF, Feudtner C. Epidemiology of Polypharmacy 
and Potential Drug-Drug Interactions Among Pediatric Patients in ICUs of U.S. Children's 
Hospitals. Pediatric critical care medicine : a journal of the Society of Critical Care 
Medicine and the World Federation of Pediatric Intensive and Critical Care Societies. 2016. 
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Antonelli R, Stille, C., and Freeman, L. Enhancing Collaboration Between Primary and 
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7. 
Bourgeois FT, Shannon MW, Valim C, Mandl KD. Adverse drug events in the outpatient 
setting: an 11-year national analysis. Pharmacoepidemiology and drug safety. 
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8. 
Feinstein JA, Feudtner C, Kempe A. Adverse drug event-related emergency department 
visits associated with complex chronic conditions. Pediatrics. 2014;133(6):e1575-1585. 
9. 
Chai G, Governale L, McMahon AW, Trinidad JP, Staffa J, Murphy D. Trends of outpatient 
prescription drug utilization in US children, 2002-2010. Pediatrics. 2012;130(1):23-31. 
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Medication Errors. Preventing medication errors. Washington, DC: National Academies 
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Feudtner C, Dai D, Hexem KR, Luan X, Metjian TA. Prevalence of polypharmacy exposure 
among hospitalized children in the United States. Arch Pediatr Adolesc Med. 
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12. 
Simon TD, Berry J, Feudtner C, et al. Children with complex chronic conditions in inpatient 
hospital settings in the United States. Pediatrics. 2010;126(4):647-655. 
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Blackmer AB, Feinstein JA. Management of Sleep Disorders in Children With 
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errors: a systematic review. Pediatrics. 2014;134(2):338-360. 
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Zed PJ, Black KJ, Fitzpatrick EA, et al. Medication-related emergency department visits in 
pediatrics: a prospective observational study. Pediatrics. 2015;135(3):435-443. 

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18. 
Ferranti J, Horvath MM, Cozart H, Whitehurst J, Eckstrand J. Reevaluating the safety 
profile of pediatrics: a comparison of computerized adverse drug event surveillance and 
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Bourgeois FT, Mandl KD, Valim C, Shannon MW. Pediatric adverse drug events in the 
outpatient setting: an 11-year national analysis. Pediatrics. 2009;124(4):e744-750. 
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Walsh KE, Roblin DW, Weingart SN, et al. Medication errors in the home: a multisite study 
of children with cancer. Pediatrics. 2013;131(5):e1405-1414. 
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Sharek PJ, McClead RE, Jr., Taketomo C, et al. An intervention to decrease narcotic-
related adverse drug events in children's hospitals. Pediatrics. 2008;122(4):e861-866. 
22. 
Walsh KE, Kaushal R, Chessare JB. How to avoid paediatric medication errors: a user's 
guide to the literature. Arch Dis Child. 2005;90(7):698-702. 
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Zhong W, Feinstein JA, Patel NS, Dai D, Feudtner C. Tall Man lettering and potential 
prescription errors: a time series analysis of 42 children's hospitals in the USA over 9 
years. BMJ Qual Saf. 2016;25(4):233-240. 
24. 
Wolfe J, Orellana L, Ullrich C, et al. Symptoms and Distress in Children With Advanced 
Cancer: Prospective Patient-Reported Outcomes From the PediQUEST Study. Journal of 
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Methodology WCCfDS. Guidelines for ATC classification and DDD assignment 2016. 19 
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Dussel V, Orellana L, Soto N, et al. Feasibility of Conducting a Palliative Care Randomized 
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30. 
Wolfe J, Orellana L, Cook EF, et al. Improving the care of children with advanced cancer 
by using an electronic patient-reported feedback intervention: results from the PediQUEST 
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in patients with heart failure. J Card Fail. 2007;13(8):643-648. 
32. 
Kessler ER, Moss A, Eckhardt SG, et al. Distress among caregivers of phase I trial 
participants: a cross-sectional study. Support Care Cancer. 2014;22(12):3331-3340. 
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assessment at the end of life: the role of proxy response. J Pain Symptom Manage. 
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34. 
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35. 
Basch E, Iasonos A, Barz A, et al. Long-term toxicity monitoring via electronic patient-
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36. 
Bruner DW. Should patient-reported outcomes be mandatory for toxicity reporting in cancer 
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adverse event reporting in oncology. Journal of clinical oncology : official journal of the 
American Society of Clinical Oncology. 2007;25(32):5121-5127. 

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38. 
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