24-hour Oral Morphine Equivalent Based Opioid Prescribing After Surgery
Phase: NA
Conditions: Opioid Use
Sponsor: University of Colorado, Denver

Protocol Template 
Page 1 
CF-146, Effective 7/10/11 
 
w 
COMIRB Protocol 
COLORADO MULTIPLE INSTITUTIONAL REVIEW BOARD 
CAMPUS BOX F-490    TELEPHONE:  303-724-1055   
Fax:  303-724-0990 
 
 
 
Protocol #: 18-2098 
 
Project Title: 24-hour oral morphine equivalent based opioid prescribing after surgery 
 
 
Principal Investigator:  Ana Fernandez-Bustamante, MD 
 
Version Date: 02/12/2021 
 
 
 
 
 
  
 
I. Hypotheses and Specific Aims:   
 
We have previously shown that 83% of patients after Cesarean section and 71% of thoracic 
surgery report taking half or less of opioids prescribed; 53% and 45% respectively report taking 
five or less of the prescribed pills.1 Such overprescribed opioids are stored in unsecured locations 
in the 75% of cases.1,2 These opioids represent a major source of potential morbidity and mortality. 
The rationale that underlies the proposed research is that once we have proven the efficacy of 
patient-centered pain management approaches, we can improve surgical pain therapy on a large 
scale.  
 
Specific Aim: We will utilize the electronic health record to individualize pain therapy in surgical 
patients after hospital discharge using last 24-hour opioid intake as the decision variable for the 
amount of opioid pain pills prescribed. Our preliminary data indicate that current opioid 
prescription practice after surgery follows a “one size fits all” pattern.1 In-hospital opioid use 24 
hours prior to discharge serves as a strong indicator to correctly estimate needs for analgesic 
medications at home.3 We will test our hypothesis that this tool will reduce the amount of opioid 
medications prescribed while maintaining patient post-operative pain control. We will test this tool 
prospectively for 44 post Cesarean section patients anticipated to use about half or less of the 
usually prescribed amount of opioid pain pills randomized equally to prescription tool intervention 
or no intervention (prescription as usual). 
 
This protocol addresses only Specific Aim #3 of the original grant. Specific Aim #1 and #2 are 
addressed under a separate COMIRB protocol #14-1938. 
 
II. Background and Significance:  
 
Prescription opioid overdose has emerged as a leading cause of death in the general 
population.4,5 Opioid-based therapy represents a corner-stone of post-operative pain 
management.6 With increasing emphasis on robust pain therapy, sales of opioid medications have 
increased four-fold in the last decade.7-12 Parallel to this rise, opioid-associated deaths have also 
quadrupled.7 We have shown that long-term opioid use occurs in up to 22% of patients following 
surgery.13 Over-prescribed opioids after surgery can create a reservoir of opioids that become 
available for non-medical use.14,15 Effective strategies to maximize non-opioid pain therapy and 
to limit such a reservoir are lacking. Thus, there is an urgent need to individualize post-operative 
pain therapy and reduce our reliance on opioids.  
 

Protocol Template 
Page 2 
CF-146, Effective 7/10/11 
 
Converting knowledge on actual need for opioid pain medications after surgery into tangible 
benefits can prevent over-prescription of opioids that become available for non-medical use.16 The 
objective of this aim is to prescribe pain medications after surgery in a patient-centered fashion. 
We will use the average amount of opioid medications (in oral morphine equivalents - OME) taken 
in the last 24 hours prior to discharge to inform and design a clinical decision support tool. This 
tool will reduce the amount of opioid medications prescribed while maintaining patient post-
operative pain control. The calculated “last 24 hour OME dose” will be applied to generate a 
recommendation for the prescription of a cumulative opioid dose that will be shared with the 
provider when the post-discharge pain medication is made, e.g. via displaying the last 24-hour 
opioid use in the electronic health record (EHR). The rationale is that testing of such a decision-
making tool will lay the groundwork to translate the findings of this project into more secure and 
efficient opioid prescribing practices to a system-wide level. Upon completion, we expect to have 
developed an effective decision-making tool to help providers estimate required pain medication 
following patient discharge.  
 
III. Preliminary Studies/Progress Report:   
 
Preliminary Studies. In a cohort of 652 
patients who had undergone surgery at 
UCH Metro clinicians chose the same 
cumulative opioid dose (300 oral morphine 
equivalents) in more than 75% of patients 
for the discharge opioid prescription 
(Figure 1). These data indicate that opioids 
following 
inpatient 
surgery 
are 
not 
prescribed in an individualized fashion, but 
rather that most patients receive a very 
similar regimen for post-discharge pain 
management. Using the same EHR (Epic) 
database that generated the data above, 
we are able to generate information on types and doses of pain medications that are administered 
to patients, who are still in the hospital in real time (Dr. Lin, Chief Medical Information Officer and 
Dr. Jean Kutner, CMO at UCHealth strongly support this project). We have previously shown that 
83% of patients after Cesarean section and 71% of thoracic surgery patients report taking half or 
less of opioids prescribed; 53% and 45% respectively report taking five or less of the prescribed 
pills.1 Hence, a “one size fits all” approach to pain management after discharge is common in 
clinical practice and leads to frequent over-prescription of opioids. Based on our own preliminary 
data and recommendation published by others, opioids taken 24 hours prior to discharge inform 
the amount of opioids that are likely to be used at home and hence the following prescriptions 
amounts have been suggested for patients taking equal or less than 22.5 MME in the 24 hours 
prior to discharge:  
- 
no opioids for home use for patients having taken no opioids in the last 24 hours prior to 
discharge 
- 
75 morphine milligram equivalent (MME), e.g. 10 oxycodone 5mg tablets, for home use 
for patients having taken equal or less than 22.5 MME, e.g. 1-3 oxycodone 5mg tablets in 
the last 24 hours prior to discharge.17  
 
IV. Research Methods 
 
A.  Outcome Measure(s):   
 
Figure 4: Cumulative opioid dose in oral morphine equivalents 
(OME) prescribed to 652 patients upon hospital discharge 
after surgery. Clinicians chose the same cumulative opioid 
dose (300 OME) in more than 75% of patients. 

Protocol Template 
Page 3 
CF-146, Effective 7/10/11 
 
Study measurements will include 24 hour prior to discharge opioid and other medication 
intake, prescribed post-discharge opioid doses in morphine milligram equivalents from 
the EHR, self-reported analgesic medication requirements (post-discharge intake of 
opioid medications, left-over opioids, intake of other pain medications, such as 
acetaminophen and non-steroidal anti-inflammatory drugs – NSAIDs), NIH PROMIS18 
outcomes for Pain Intensity and Pain Interference, side effects, reasons for not taking 
opioids, as well as basic demographic information. We will also collect information about 
need for additional opioid prescriptions, and reported medication disposal for left-over 
opioids, length of hospitalization, repeat vs. first C-section and other relevant 
perioperative variables. For this study, we will be using REDCap for data collection after 
Cesarean section to administer four weekly surveys following the day of discharge.  
 
We will seek follow-up with providers about the usefulness and acceptability of the EHR-
based intervention. Providers will be surveyed with a REDCap survey using a modified 
version of the GUIDES checklist, which provides a tool to improve the successful use of 
guideline-based computerized clinical decision support.21 
 
 
B. Description of Population to be Enrolled:   
 
Survey population:  
Inflating enrollment by approximately 25% to account for drop out and result in 44 patient 
completers, we will consent 60 adult patients receiving a Cesarean section procedure.  
After completing an observational study in three surgical groups (thoracic surgery, 
gastrointestinal surgery, C-section), we chose to evaluate this intervention first in C-
Section patients based on their unique characteristics: low procedural variability, low 
incidences of chronic opioid use, and low level of comorbidities. Also, the issue of having 
potentially unsecured opioids in a household with young children is of special relevance 
for opioid safety research in the Cesarean section cohort.19 
 
Inclusion Criteria: 1) Women ages at least 18 years of age having undergone Cesarean 
section surgery at the University of Colorado Hospital are eligible. 2) Willingness to 
complete weekly surveys for 4 weeks after discharge. 3) Anticipated to need half or less 
of the usually prescribed amount of opioids based on the amount of opioids taken in the 
last 24 hours prior to the opioid medication being written for discharge (only patients who 
took 22.5 MME or less opioids in the last 24 hours prior to the day of discharge will be 
eligible for this study). Inclusion and exclusion criteria (including the amount of opioids 
taken in the last 24 hours prior to discharge) will be evaluated in the morning in patients 
scheduled to be discharged later that day.  
 
Exclusion Criteria:  1) Patients under the age of 18 years, 2) Patients returning to 
institutional settings (e.g. prison, jail, mental health facility), 3) Pregnant women (patients 
will be approached after their C-section), 4) Decisionally challenged patients, 5) Blind or 
illiterate patients.  
 
Based on our prior research factors such as emergency status, prior opioid use, repeat 
vs primary C-section, and associated procedures were not associated with post-
discharge opioid use once we adjusted for last-24 hour inpatient opioid use. Hence, 
these patients will not be excluded.  
 
 

Protocol Template 
Page 4 
CF-146, Effective 7/10/11 
 
We will perform a randomized clinical trial (RCT) of an EHR-based recommendation to 
prescribe opioids at discharge according to the recorded last 24-hour inpatient use 
according to current recommendations and evaluate its effect on the amount of opioids 
prescribed as well as pain control after discharge.  
 
The medical provider of each patient enrolled (up to n=60) will also be surveyed using 
an online REDCap survey. Inclusion criteria: 1) Medical provider of a patient enrolled in 
the study, 2) Willingness to use the Prescription Tool and complete an online survey. No 
exclusion criteria.  
 
Total number of participants counting both patients and providers will be114; up to 60 
patients and 54 providers enrolled in the study. 
 
C. Study Design and Research Methods   
Using the UCH Epic/Clarity database, we will continuously identify all patients who 
underwent Cesarean section surgery at University Hospital. Patients will be approached 
regarding interest in the study prior to hospital discharge. A trained PRA, Perinatal 
CTRC staff or other trained provider will explain the study to prospective participants 
using standard language. Participants will be told that they are being asked to be in this 
research study because they recently had surgery at the University of Colorado Hospital.  
 
If the patient is interested in participation the study PRA, Perinatal CTRC staff or trained 
provider will review the consent/HIPAA form with the patient and answer any questions 
the patient may have. Study staff will also provide them with a hard copy of the 
consent/HIPAA form.  
 
- OR – 
  
During the SARS-CoV-2 (COVID-19) pandemic or as required by UCHealth, we will 
minimize in-person contact with patients and complete study visits remotely whenever 
possible. Perinatal CTRC staff will obtain informed consent from patients using the 
procedures detailed below. 
Consent-HIPAA authorization will be obtained remotely via phone or HIPAA-compliant 
videoconference application (Zoom) following COMIRB guidance (CG-85, Version April 
9, 2020).  
 
A trained provider with appropriate PPE, who is already providing standard care to the 
patient, will give the patient a hard copy of the consent/HIPAA form so they have an 
approved copy of the consent form “in hand” at the time of the informed consent 
discussion.  
 
 
Perinatal CTRC staff will call the patient to initiate the informed consent discussion.  
 
The discussion will begin with identification of who is participating on the call; 
Perinatal CTRC staff will confirm the potential subject has a hard copy of the 
consent-HIPAA form before beginning the discussion. 
 
Perinatal CTRC staff will review the consent/HIPAA form with the patient and answer 
any questions. 

Protocol Template 
Page 5 
CF-146, Effective 7/10/11 
 
 
The patient will sign the consent-HIPAA form and give it to the trained provider already 
providing standard care. The provider will give the signed form to Perinatal CTRC staff 
who will also sign the form noting that consent was obtained by phone. A copy of the 
signed consent-HIPAA form will be given to the patient.  
  
We will seek a waiver of written consent for surveying providers who are given the 
dosing suggestion via the EHR-based Prescription Tool. At their convenience, these 
providers will complete an online postcard consent and survey via REDCap.   
 
After consent, demographics and the best contact information will be collected (remotely 
by phone during the COVID-19 pandemic or as required by UCHealth) from those 
enrolled patients who indicate they are interested in completing the surveys after their 
hospital discharge.  
 
We expect 44 patients to complete all four weekly surveys and we define the intent-to-
treat sample as patients who complete one or more surveys (providing at least one 
observation to be used in analyses).  To conservatively allow for increased variability 
due to attrition, 60 patients will be randomized equally electronically to intervention 
(prescription tool) or no intervention (prescription as usual). We will use an electronic 
randomization scheme created so that the principal investigator and statistician can 
remain blind to assignment.   
 
At the time of writing the prescription for a patient the provider will be informed that a 
patient may be considered for a lower post-discharge opioid dose (No opioids for 
patients who did not take any opioids in the last 24 hours, and 10 oxycodone 5mg 
tablets, for patients having taken less than 22.5 MME, e.g. 1-3 oxycodone 5mg tablets in 
the last 24 hours). No dosing recommendations for patients having taken more than 22.5 
MME will be made as these patients are not eligible for this study. Final dosing decisions 
and drug choices will remain at the discretion of the treating provider and decisions will 
be tracked.  
 
For this pilot study, the provider information (best practice alert – BPA) will be 
operationalized via a written recommendation on paper handed to the provider by study 
staff in a sealed envelope or emailed with a read receipt that the provider will be asked 
to open and read. Alternatively, the BPA may be presented electronically using a screen. 
Providers will be asked to acknowledge that they read the BPA by closing the window or 
opening the envelope or email.  
 
For the intervention group:  
For patients receiving no opioids in the last 24 hours prior to an oxycodone or 
oxycodone/acetaminophen discharge prescription being written:  
 
BPA: “In the last 24 hours, your patient received NO opioids. Consider not 
prescribing any opioids for pain management after discharge.” 
 
For patients receiving >0 MME up to <22.5 MME in the last 24 hours prior to an 
oxycodone or oxycodone/acetaminophen discharge prescription being written (example 
BPA is for 15 MME – 2 oxycodone 5mg tablets):  
 

Protocol Template 
Page 6 
CF-146, Effective 7/10/11 
 
BPA: “In the last 24 hours, your patient received opioid medication equivalent to 2 
oxycodone 5 mg tablets by mouth. Consider writing for a total of 10 oxycodone 5 
mg tablets for pain management after discharge.” 
 
Note, oxycodone-containing medications are the opioid prescribed in >96% of cases 
after Cesarean section at our hospital. We will make equivalent recommendations if 
hydrocodone is used. Based on our data, no other opioid medications have been 
prescribed for use after discharge following Cesarean section.  
 
For the control group: 
BPA: “Consider prescribing the usual medications for pain management after 
discharge.” 
 
One week after hospital discharge interested patients will be contacted and asked to 
complete the first of four surveys. Participants will receive a $10 gift card, or equivalent 
money order if requested, for each of four weekly surveys, for a total of $40. All enrolled 
patients will complete the weekly post-discharge surveys within REDCap or by hard 
copy or phone if they do not have internet access.  
 
Providers will not be paid to use the Prescription Tool or complete the short, one-time 
online survey.  
 
D.   
Description, Risks, Justification of Procedures and Data Collection Tools: 
 
Discomforts and other possible risks include: 
Common Risks: 
• 
Tiredness or boredom when completing study assessments.  
 
Uncommon Risks: 
• 
Tension or nervousness may occur from completing the study assessments. 
Participants can talk with the researchers about such problems, and can 
terminate the study if they wish. 
  
• 
Problems with pain management.  
Only patients who are predicted to require approximately half or less than the 
usually prescribed opioid dose (i.e., those taking equal or less than 22.5 MME in 
the 24 hours prior to discharge) will be eligible. Patients will be randomized to have 
their provider receive a suggestion for a reduction of opioid dose versus standard 
of care. Providers may still choose to prescribe a higher dose as clinically 
indicated. The prescription tool will only make a suggestion. We will track the 
recommendation made as well as the actual dose prescribed.  
 
We will follow up with all patients at half of their usual follow-up period (usually 2 
weeks) via a REDCap survey, phone, email, or in clinic to assess how they are 
doing and if they are likely to run out of opioid medications despite still requiring 
them for acute surgical pain. For patients, who are running low on opioid pain 
medications, we will arrange for additional pain medications to be prescribed as 
deemed appropriate by their providers using the electronic prescription route if 
needed. We will monitor the study progress closely and reassess our study design 

Protocol Template 
Page 7 
CF-146, Effective 7/10/11 
 
if more than 5 intervention group patients require prescriptions prior to scheduled 
clinic follow-up.  
 
All patients are routinely given a phone number where they can reach a surgical 
provider 24 hours a day, seven days a week, in case pain therapy is inadequate.  
 
The study team will monitor need for secondary prescriptions from providers to 
ensure that no significant under-prescription of opioid medications after surgery 
occurs.  
 
These recommendations are in accordance with current quality improvement 
efforts by the system-wide Pharmacy and Therapeutics (P&T) Opioid 
Subcommittee charged with addressing UCHealth actions to meet the new Joint 
Commission Pain Assessment and Management guidelines. This committee is 
co-chaired by the Co-I of this study (Karsten Bartels) and Dr. Clark Lyda, 
Pharm.D. The PI is also an active member of the system-wide UCHealth Opioid 
and Pain Management Steering Committee that is chaired by Dr. Jean Kutner. 
This committee also supports this application. Lastly, the PI holds an active 
funded 5-year NIH K23 grant “Improving Opioid Prescription Safety After 
Surgery” that provides material and personal support, statistical support, and 
regulatory support for this application.  
 
Rare But Serious Risks: 
• 
Breaches of confidentiality.  
 
 
 
Confidentiality is maintained throughout the study’s entirety and protected health 
information will not be disclosed outside the University of Colorado. The study 
therefore does not involve any more than minimal risk to patients, namely loss of 
confidentiality. While there is no direct benefit to subjects, knowledge gained 
from our study will help to tailor prescription of analgesic medications after 
surgery to patients’ actual needs.  
 
Strict safeguards for data protection will be followed including storage on 
protected servers, password protection and monitored access to authorized 
users. Please see the Data and Safety Monitoring Plan section for additional 
details. Patients are provided with the PI’s office phone number, COMIRB’s 
phone number, and the PI’s email address and phone number should they have 
any questions. Patients may withdraw from the study at any time.    
 
 
Data and Safety Monitoring Plan:  
 
Each participant will be assigned a corresponding study ID number. ID numbers will be 
assigned in the order of patient enrollment. A master list connecting the enrollment 
number with the patient’s medical history number will be maintained only for the duration 
of the data collection. Only PI-approved study personnel who have current COMIRB-
required human subject protection training will have password-protected and monitored 
access to the data. Following the interpretation of the data, the master list will be 
destroyed and no patient identifying information will be maintained.   
 

Protocol Template 
Page 8 
CF-146, Effective 7/10/11 
 
Demographic data, information on prescribed and non-prescribed medications, and 
clinical outcome values relevant for pain management will be obtained from the Epic 
database and stored in a secure fashion using REDCap.  
 
E.   Potential Scientific Problems:   
Concomitant provider education may itself lead to a change in pain management 
practices. To address this, a future larger pragmatic clinical trial could include cluster 
randomization based on study site. Few prognostic models actually are in clinical use, 
often because they have not been externally validated and because of the data collection 
burden. Our local Clinical Decision Support Program has confirmed the feasibility of our 
proposal to integrate a future decision-making tool into the electronic medical record and 
order entry system.  
 
F.   Data Analysis Plan:   
 
The intent-to-treat (ITT) sample is defined as those who complete at least one survey. In 
our prior observational study, 100% of the C-section patients satisfied this criterion. If there 
is a subsample that does not complete at least one survey, we will compare that group to 
the ITT group on relevant demographic and clinical characteristics. Outcomes not 
requiring any response to the survey will be compared for all patients enrolled, regardless 
if they completed at least one survey. 
 
The prescription tool and prescription as usual (PAU) groups will be compared on baseline 
demographic and clinical characteristics using Mann-Whitney tests, independent t-tests 
and chi-square tests as appropriate for continuous and categorical data; when necessary 
(i.e. when variables have distributions violating assumptions), nonparametric procedures 
will be substituted. We expect randomization to ensure group equivalence; should 
variables be different they will be evaluated as covariates in the analyses described below 
as appropriate.   
 
Our primary analyses will compare the prescription tool group with the PAU group on oral 
morphine equivalent dose left over (not used) from the total amount of prescribed opioids. 
Based on our preliminary data, we will assume the control group to receive an opioid 
prescription for 20 oxycodone 5mg tablets (150MME), leading to a mean MME of 101.8 
(SD 60.5) left over. Conservatively estimating a 50% adoption rate of the decision support 
tool by prescribing clinicians, we would expect a mean MME of 55 (SD 37.6) left over 
opioids in the intervention group. Assuming statistical comparisons will be made using 
Mann-Whitney test a sample size of n=22 per group (44 total using 1:1 allocation) will yield 
90% power with an assumed one-tailed alpha of 0.05 (G-Power, version 3.1.9.2).20  
 
For the primary weekly opioid use variable and for secondary longitudinal variables of 
interest (i.e. weekly scores for pain interference and pain intensity), trajectories will first be 
visually compared between the two groups. Mixed models will then be used to analyze 
each outcome that will include fixed group, time, and group by time interaction effects and 
random patient effects. Covariates will only be included if they differ by group at baseline 
and are related to the outcome of interest. The test of the group by time interaction will 
indicate if each outcome differs over time by groups. Overall means for each outcome will 
be estimated and compared between groups as will week 1 and week 4 means of each 
outcome will be separately compared between groups. These analyses on the ITT sample 
will then be repeated on the subset of patients who complete all 4 surveys and any 
differences between results will be reported. 

Protocol Template 
Page 9 
CF-146, Effective 7/10/11 
 
 
Important secondary summary variables that will be compared between groups using chi-
square, t-test, nonparametric, and covariate-adjusted (i.e. ANCOVA) methods as 
appropriate are: need for additional opioid prescriptions (yes, no), and amount of opioid 
and non opioid analgesic drugs taken (total mg). Reported medication disposal by group 
will additionally be described. 
 
G.  Summarize Knowledge to be Gained:   
We expect to have designed and demonstrated the feasibility of implementation of a 
decision-making support tool to better estimate individual patient needs for pain therapy 
after surgery. The instrument will be parsimonious in nature, as it will rely on information 
that is readily available in the patient’s medical record and it will not require any special 
action by the clinician to obtain a dosage recommendation. Creating such a tool will be 
critical to translate the findings of this line of research into safer opioid prescribing 
practices for our patients. Given that the tool can be integrated into a nationally used 
electronic medical record and order entry system (Epic), usage and further testing of its 
performance will be possible in many diverse environments. Eventually, public health will 
be promoted through improving non-opioid analgesia and by decreasing prescriptions of 
unneeded opioid pain medications. This will lead to a subsequent decreased availability 
of opioid medications for non-medical use. Further, the data obtained from this aim will be 
used for a subsequent grant application.  
 
H. References: 
 
1. 
Bartels K, Mayes LM, Dingmann C, et al. Opioid Use and Storage Patterns by Patients after 
Hospital Discharge following Surgery. PLoS One. 2016;11(1):e0147972. 
2. 
Bateman BT, Cole NM, Maeda A, et al. Patterns of Opioid Prescription and Use After Cesarean 
Delivery. Obstet Gynecol. 2017;130(1):29-35. 
3. 
Chen EY, Marcantonio A, Tornetta P, 3rd. Correlation Between 24-Hour Predischarge Opioid Use 
and Amount of Opioids Prescribed at Hospital Discharge. JAMA Surg. 2018;153(2):e174859. 
4. 
Centers for Disease Control and Prevention. Prescription Drug Overdose: Understanding the 
Epidemic. http://www.cdc.gov/drugoverdose/data/index.html Accessed on 10/28/2017. 
5. 
Centers for Disease Control and Prevention. Leading Causes of Death.  
http://www.cdc.gov/injury/wisqars/leading_causes_death.html Accessed on 09/27/2017. 
6. 
Acute Pain Management: Operative or Medical Procedures and Trauma. Agency for Healthcare 
Research and Quality (AHCPR). 1992; http://archive.ahrq.gov/clinic/medtep/acute.htm. Accessed 
12/11/2017. 
7. 
Prevention CfDCa. Vital signs: overdoses of prescription opioid pain relievers - United States, 
1999-2008. . MMWR Morb Mortal Wkly Rep. 2011;60(43):1487-1492. 
8. 
Volkow ND, Frieden TR, Hyde PS, Cha SS. Medication-assisted therapies--tackling the opioid-
overdose epidemic. N Engl J Med. 2014;370(22):2063-2066. 
9. 
Olsen Y, Daumit GL, Ford DE. Opioid prescriptions by U.S. primary care physicians from 1992 to 
2001. J Pain. 2006;7(4):225-235. 
10. 
Calcaterra S, Glanz J, Binswanger IA. National trends in pharmaceutical opioid related overdose 
deaths compared to other substance related overdose deaths: 1999-2009. Drug Alcohol Depend. 
2013;131(3):263-270. 
11. 
Binswanger IA, Blatchford PJ, Mueller SR, Stern MF. Mortality after prison release: opioid 
overdose and other causes of death, risk factors, and time trends from 1999 to 2009. Ann Intern 
Med. 2013;159(9):592-600. 
12. 
Dart RC, Surratt HL, Cicero TJ, et al. Trends in Opioid Analgesic Abuse and Mortality in the 
United States. N Engl J Med. 2015;372(3):241-248. 

Protocol Template 
Page 10 
CF-146, Effective 7/10/11 
 
13. 
Bartels K, Fernandez-Bustamante A, McWilliams S, Hopfer CH, Mikulich-Gilbertson SK. Long-
Term Opioid Use After Inpatient Surgery – A Retrospective Cohort Study. Drug Alcohol Depend. 
2018:In press. 
14. 
Rodgers J, Cunningham K, Fitzgerald K, Finnerty E. Opioid consumption following outpatient 
upper extremity surgery. J Hand Surg Am. 2012;37(4):645-650. 
15. 
Harris K, Curtis J, Larsen B, et al. Opioid pain medication use after dermatologic surgery: a 
prospective observational study of 212 dermatologic surgery patients. JAMA Dermatol. 
2013;149(3):317-321. 
16. 
Bartels K, Binswanger IA, Hopfer CJ. Sources of Prescription Opioids for Nonmedical Use. J 
Addict Med. 2016;10(2):132. 
17. 
Hill MV, Stucke RS, Billmeier SE, Kelly JL, Barth RJ, Jr. Guideline for Discharge Opioid 
Prescriptions after Inpatient General Surgical Procedures. J Am Coll Surg. 2018;226(6):996-
1003. 
18. 
National Institutes of Health, PROMIS tools for pain intensity and pain interference. 
http://www.healthmeasures.net/explore-measurement-systems/promis Last accessed on 
03/02/2018. 
19. 
Lavonas EJ, Banner W, Bradt P, et al. Root causes, clinical effects, and outcomes of 
unintentional exposures to buprenorphine by young children. J Pediatr. 2013;163(5):1377-1383 
e1371-1373. 
20. 
Faul F, Erdfelder E, Buchner A, Lang AG. Statistical power analyses using G*Power 3.1: tests for 
correlation and regression analyses. Behav Res Methods. 2009;41(4):1149-1160. 
21.  
Van de Velde S, et al., Implement Sci. 2018 Jun 25;13(1):86. doi: 10.1186/s13012-018-0772-
3. The GUIDES checklist: development of a tool to improve tfhe successful use of guideline-
based computerised clinical decision support.