Assessing the impact of a restrictive opioid prescribing law in West Virginia

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Abstract

Background

The Opioid Reduction Act (SB 273) took effect in West Virginia in June 2018. This legislation limited ongoing chronic opioid prescriptions to 30 days’ supply, and first-time opioid prescriptions to 7 days’ supply for surgeons and 3 days’ for emergency rooms and dentists. The purpose of this study was to determine the effect of this legislation on reducing opioid prescriptions in West Virginia, with the goal of informing future similar policy efforts.

Methods

Data were requested from the state Prescription Drug Monitoring Program (PDMP) including overall number of opioid prescriptions, number of first-time opioid prescriptions, average daily morphine milligram equivalents (MME) and prescription duration (expressed as “days’ supply”) given to adults during the 64 week time periods before and after legislation enactment. Statistical analysis was done utilizing an autoregressive integrated moving average (ARIMA) interrupted time series analysis to assess impact of both legislation announcement and enactment while controlling secular trends and considering autocorrelation trends. Benzodiazepine prescriptions were utilized as a control.

Results

Our analysis demonstrates a significant decrease in overall state opioid prescribing as well as a small change in average daily MME associated with the date of the legislation’s enactment when considering serial correlation in the time series and accounting for pre-intervention trends. There was no such association found with benzodiazepine prescriptions.

Conclusion

Results of the current study suggest that SB 273 was associated with an average 22.1% decrease of overall opioid prescriptions and a small change in average daily MME relative to the date of legislative implementation in West Virginia. There was, however, no association of the legislation on first-time opioid prescriptions or days’ supply of opioid medication, and all variables were trending downward prior to implementation of SB 273. The control demonstrated no relationship to the law.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13011-021-00349-y.

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Interrupted time series regression for the evaluation of public health interventions: a tutorial

James Lopez Bernal, Steven Cummins, Antonio Gasparrini (2016)

Abstract Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at a clearly defined point in time. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical therapy to national public health legislation. Whereas the design shares many properties of regression-based approaches in other epidemiological studies, there are a range of unique features of time series data that require additional methodological considerations. In this tutorial we use a worked example to demonstrate a robust approach to ITS analysis using segmented regression. We begin by describing the design and considering when ITS is an appropriate design choice. We then discuss the essential, yet often omitted, step of proposing the impact model a priori. Subsequently, we demonstrate the approach to statistical analysis including the main segmented regression model. Finally we describe the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders, and we also outline some of the more complex design adaptations that can be used to strengthen the basic ITS design.

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Use of interrupted time series analysis in evaluating health care quality improvements.

Robert B Penfold, Fang Zhang (2015)

Interrupted time series (ITS) analysis is arguably the strongest quasi-experimental research design. ITS is particularly useful when a randomized trial is infeasible or unethical. The approach usually involves constructing a time series of population-level rates for a particular quality improvement focus (eg, rates of attention-deficit/hyperactivity disorder [ADHD] medication initiation) and testing statistically for a change in the outcome rate in the time periods before and time periods after implementation of a policy/program designed to change the outcome. In parallel, investigators often analyze rates of negative outcomes that might be (unintentionally) affected by the policy/program. We discuss why ITS is a useful tool for quality improvement. Strengths of ITS include the ability to control for secular trends in the data (unlike a 2-period before-and-after t test), ability to evaluate outcomes using population-level data, clear graphical presentation of results, ease of conducting stratified analyses, and ability to evaluate both intended and unintended consequences of interventions. Limitations of ITS include the need for a minimum of 8 time periods before and 8 after an intervention to evaluate changes statistically, difficulty in analyzing the independent impact of separate components of a program that are implemented close together in time, and existence of a suitable control population. Investigators must also be careful not to make individual-level inferences when population-level rates are used to evaluate interventions (though ITS can be used with individual-level data). A brief description of ITS is provided, including a fully implemented (but hypothetical) study of the impact of a program to reduce ADHD medication initiation in children younger than 5 years old and insured by Medicaid in Washington State. An example of the database needed to conduct an ITS is provided, as well as SAS code to implement a difference-in-differences model using preschool-age children in California as a comparison group. Copyright © 2013 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

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Prescription Opioid Analgesics Commonly Unused After Surgery

Mark Bicket, Jane Long, Peter Pronovost … (2017)

Prescription opioid analgesics play an important role in the treatment of postoperative pain; however, unused opioids may be diverted for nonmedical use and contribute to opioid-related injuries and deaths.

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Author and article information

Contributors

Cara L. Sedney:

ORCID: http://orcid.org/0000-0003-1290-7083

csedney@hsc.wvu.edu

Journal

Journal ID (nlm-ta): Subst Abuse Treat Prev Policy

Journal ID (iso-abbrev): Subst Abuse Treat Prev Policy

Title: Substance Abuse Treatment, Prevention, and Policy

Publisher: BioMed Central (London )

ISSN (Electronic): 1747-597X

Publication date (Electronic): 1 February 2021

Publication date PMC-release: 1 February 2021

Publication date Collection: 2021

Volume: 16

Electronic Location Identifier: 14

Affiliations

[1 ]GRID grid.268154.c, ISNI 0000 0001 2156 6140, School of Medicine, , West Virginia University, ; Morgantown, WV 26505 USA

[2 ]GRID grid.268154.c, ISNI 0000 0001 2156 6140, West Virginia Clinical and Translational Science Institute, ; Morgantown, WV USA

[3 ]GRID grid.268154.c, ISNI 0000 0001 2156 6140, Department of Behavioral Medicine & Psychiatry, , West Virginia University, ; Morgantown, WV USA

[4 ]GRID grid.268154.c, ISNI 0000 0001 2156 6140, Department of Epidemiology, , West Virginia University, ; Morgantown, WV USA

[5 ]West Virginia Board of Pharmacy, Charleston, WV USA

Author information

Cara L. Sedney http://orcid.org/0000-0003-1290-7083

Article

Publisher ID: 349

DOI: 10.1186/s13011-021-00349-y

PMC ID: 7852151

PubMed ID: 33526045

SO-VID: 8e3f538d-da47-4bcd-9dc1-81d0c7362a57

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date accepted : 19 January 2021

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000026, National Institute on Drug Abuse;

Award ID: 1R21DA049861-01

Award Recipient : Cara L. Sedney

Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;

Award ID: 5U54GM104942-04

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ScienceOpen disciplines: Health & Social care

Keywords: opioids,law,prescription opioids,opiates,interrupted time series

Data availability:

ScienceOpen disciplines: Health & Social care

Keywords: opioids, law, prescription opioids, opiates, interrupted time series

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Assessing the impact of a restrictive opioid prescribing law in West Virginia

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Most cited references 34

Interrupted time series regression for the evaluation of public health interventions: a tutorial

Use of interrupted time series analysis in evaluating health care quality improvements.

Prescription Opioid Analgesics Commonly Unused After Surgery

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