A Community Health Center Buyback Program to Reduce the Supply of Opioids to Secondary Users
Last registered on March 23, 2019

Pre-Trial

Trial Information
General Information
Title
A Community Health Center Buyback Program to Reduce the Supply of Opioids to Secondary Users
RCT ID
AEARCTR-0004041
Initial registration date
March 21, 2019
Last updated
March 23, 2019 8:18 PM EDT
Location(s)

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Primary Investigator
Affiliation
Northeastern University
Other Primary Investigator(s)
PI Affiliation
Northeastern University
PI Affiliation
Northeastern University
Additional Trial Information
Status
In development
Start date
2019-05-06
End date
2020-12-31
Secondary IDs
Abstract
Secure disposal of unused medications is one strategy to reduce the availability of opioids for diversion or abuse to secondary users after they have been dispensed. Are patients more likely to return unused opioids when informed and incentivized about a medication disposal program compared to passively observing a disposal kiosk in their pharmacy? We hypothesize that informing patients at the point of dispensing the medication, sending reminders via text message, and providing a financial incentive can significantly boost return rates. Our proposed pilot intervention will take place at five in-house community health center pharmacies in Massachusetts yielding a potential sample size of 2,400 acute opioid prescriptions over 12 months that will be randomized across treatment and control groups. We will measure the percent of patients returning opioids as well as the amount and type of medication returned across both groups. We will also compare the amount returned to the amount prescribed by type of medication to better understand whether the program has an impact on usage and refills. Finally, we will explore the degree of heterogeneity in outcomes across different groups according to patient characteristics that predict opioid addiction such as age, gender, and diagnosis.
External Link(s)
Registration Citation
Citation
Alam, Md Noor E, Alicia Modestino and Gary Young. 2019. "A Community Health Center Buyback Program to Reduce the Supply of Opioids to Secondary Users." AEA RCT Registry. March 23. https://www.socialscienceregistry.org/trials/4041/history/43978
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
We seek to provide proof of concept for an opioid buy-back program that could reduce the flow of opioids from patients to secondary users and the black market. To study the effectiveness of the intervention, we will randomly assign patients to receive information about the buyback program when the prescription is filled including details on the financial incentive and reminder text messages. We will assess the direct impacts of the program based on the number of patients that take up the buyback and the total quantity of opioid medications that are returned. We will also explore how the effect varies across different groups of patients (e.g. age range, gender, English proficiency, underlying reason for prescription) as well as whether there are any program spillovers to patients that not served by the community health center.

Implementing Partner: A community health care center in Massachusetts with five in-house pharmacy locations in the same city will implement the program. Serving a culturally diverse population, the community health center is responsive to emerging community needs and has developed programs and services designed to improve access to care as well as improve the quality of life for patients.

Target Population: The intervention will target patients prescribed an opioid for an acute diagnosis such as surgery, injury, or acute pain at all five of the community health center’s in-house pharmacy sites. Acute users will be identified as having an opioid prescription for a supply of 14 days or less.

Treatment Arms: There will be two main treatment arms that will be implemented across different pharmacy locations. At the main location, patients will be randomly assigned to receiving either no information or information on how to return unused medication plus the financial incentive. At the other four locations, patients will be randomly assigned to receiving either no information or information on how to return unused medication (e.g., no financial incentive). One of the larger sites in the second treatment arm, will also receive a text notification at the end of the month to remind them about the disposal program when their prescription is likely to be completed.

Randomization: To minimize contamination, patients will be randomized into the treatment and control groups within sites but across calendar days. The randomization will occur ex-ante and each week the staff will be provided with a schedule to indicate which days are designated for patient assignment to the intervention group and instructed to apply the intervention on only those days that week. Note that patients receiving an opioid prescription at locations other than the main site will only be informed on weekdays since those locations are not open on the weekends.

IRB Approval: The research team has obtained IRB approval from Northeastern University. All data provided by the pharmacy will be de-identified with all personally identifiable information (PII) such as first and last name, date of birth, and Rx number and date removed before the data is transmitted to the research team.
Intervention Start Date
2019-05-06
Intervention End Date
2020-05-05
Primary Outcomes
Primary Outcomes (end points)
Our primary outcome of interest is whether individuals with an opioid prescription for acute who receive the intervention use are more likely to return unused medication to the pharmacy compared to those who do not receive the intervention. This is measured relative to the passive observation of the disposal kiosk (control), which is the baseline outcome for prior medication disposal programs. We will also explore heterogeneity of outcomes across different groups according to patient characteristics that predict opioid addiction such as age, gender, and diagnosis (e.g., injury versus surgery). We will also test which program features (e.g., text reminders, financial incentive) help to increase the increase take-up rate by comparing impacts across treatment arms. Finally, we will measure the amount of spillover to other patients and community residents who do not directly receive the intervention.
Primary Outcomes (explanation)

Secondary Outcomes
Secondary Outcomes (end points)
Secondary outcomes that we will measure include the type and estimated quantity of medication returned across the treatment and control groups based on the visual verification conducted by the pharmacists. The type of medication returned can reveal which opioids are more likely to be returned. The amount of medication returned can reveal the degree to which the program may have diverted consumption of opioids from either a primary or secondary user. We will compare the amount returned to the amount prescribed by type of medication in several ways. First, based on the visual verification and estimation conducted by the pharmacists we will compare the types and amount of medication returned by the treatment and control groups. Second, in cases where it is possible to match the Rx or patient name of those returning medication to those who were prescribed medication, we will directly compare the amount returned to the amount prescribed. Third, by comparing the total amount disposed of (e.g., pounds) based on reports from the disposal vendor to the total amount prescribed as recorded by the pharmacy, we will assess the aggregate amount returned versus prescribed across different treatment arms.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We seek to provide proof of concept for an opioid buy-back program that could reduce the flow of opioids from patients to secondary users and the black market. To study the effectiveness of the intervention, we will randomly assign patients to receive information about the buyback program when the prescription is filled including details on the financial incentive and reminder text messages. We will assess the direct impacts of the program based on the number of patients that take up the buyback and the total quantity of opioid medications that are returned. We will also explore how the effect varies across different groups of patients (e.g. age range, gender, English proficiency, underlying reason for prescription) as well as whether there are any program spillovers to patients that not served by the community health center.

Implementing Partner: A community health care center in Massachusetts with five in-house pharmacy locations in the same city will implement the program. Serving a culturally diverse population, the community health center is responsive to emerging community needs and has developed programs and services designed to improve access to care as well as improve the quality of life for patients.

Target Population: The intervention will target patients prescribed an opioid for an acute diagnosis such as surgery, injury, or acute pain at all five of the community health center’s in-house pharmacy sites. Acute users will be identified as having an opioid prescription for a supply of 14 days or less.

Treatment Arms: There will be two main treatment arms that will be implemented across different pharmacy locations. At the main location, patients will be randomly assigned to receiving either no information or information on how to return unused medication plus the financial incentive. At the other four locations, patients will be randomly assigned to receiving either no information or information on how to return unused medication (e.g., no financial incentive). One of the larger sites in the second treatment arm, will also receive a text notification at the end of the month to remind them about the disposal program when their prescription is likely to be completed.

Randomization: To minimize contamination, patients will be randomized into the treatment and control groups within sites but across calendar days. The randomization will occur ex-ante and each week the staff will be provided with a schedule to indicate which days are designated for patient assignment to the intervention group and instructed to apply the intervention on only those days that week. Note that patients receiving an opioid prescription at locations other than the main site will only be informed on weekdays since those locations are not open on the weekends.

IRB Approval: The research team has obtained IRB approval from Northeastern University. All data provided by the pharmacy will be de-identified with all personally identifiable information (PII) such as first and last name, date of birth, and Rx number and date removed before the data is transmitted to the research team.
Experimental Design Details
Not available
Randomization Method
Randomization: To minimize contamination, patients will be randomized into the treatment and control groups within sites but across calendar days. The randomization will occur ex-ante and each week the staff will be provided with a schedule to indicate which days are designated for patient assignment to the intervention group and instructed to apply the intervention on only those days that week. Note that patients receiving an opioid prescription at locations other than the main site will only be informed on weekdays since those locations are not open on the weekends.
Randomization Unit
Randomization will be at the individual level within clusters.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
5 pharmacy locations
Sample size: planned number of observations
Based on a sample of prescriptions over a three-month period, the community health center projects that they fill about 2,400 opioid prescriptions for acute users over a 12-month period across their five locations. The largest location, fills half of this amount with the remaining half divided between their next largest location, and the other three locations.
Sample size (or number of clusters) by treatment arms
We make several assumptions to arrive at an estimated take-up rate for each of the treatment and control groups. First, even with recent restrictions on prescribing opioids for acute users, most experts agree that patients still end up with excess medication. As such, we assume that all acute users will have at least some minimal amount (e.g., one pill) that could be returned. Second, we assume the potential take-up rate will be similar to that found in a 2014 survey of beliefs and behaviors regarding unused and expired medication among community pharmacy patients. The survey found that 15 percent had utilized a take-back disposal location in their community, although 77 percent of patients were willing to return unused medication when asked about it (Kozak et al. 2015). As such, we use a range of take-up rates across each group: 10-15 percent for the control group, 30-40 percent for the information-only treatment group, and 50-75 percent for the incentivized treatment group. Finally, we assume spillovers to individuals outside the pharmacy would be minimal with one patient per week per location.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
A back-of-the-envelope power calculation using the projected sample size and anticipated program impacts based on estimates from the literature indicates that the study is sufficiently powered. Assuming a power threshold of 80 percent, we show the MDE needed given our projected sample sizes across the two arms. Given a control mean of 15 percent, an MDE of 6.5 percentage points would be required to demonstrate a significant program impact at the 5 percent level for the largest site which has 1,200 patients. For the smaller sites with only 600 patients, the MDE is 9.0 percentage points. Given that prior surveys indicate upwards of 77 percent of individuals would be willing to return medication even without a financial incentive, achieving a treatment mean of 21.5 to 24.0 percent seems likely. In addition, we estimate the total sample size required to achieve a policy relevant MDE that corresponds to doubling the percent of individuals returning medication relative to the control group. The required sample size ranges from 236 to 394, about one-half to two-thirds the sample size projected at our smallest site. We believe effect sizes of this magnitude would be of interest to state policymakers deciding whether to expand the program.
Supporting Documents and Materials

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IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Northeastern University Institutional Review Board
IRB Approval Date
2018-01-28
IRB Approval Number
19-04-05
Analysis Plan

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