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Implementation Science
Published in: Implementation Science 1/2018

Open Access 01-12-2018 | Study protocol

Protocol: mixed-methods study to evaluate implementation, enforcement, and outcomes of U.S. state laws intended to curb high-risk opioid prescribing

Authors: Emma E. McGinty, Elizabeth A. Stuart, G. Caleb Alexander, Colleen L. Barry, Mark C. Bicket, Lainie Rutkow

Published in: Implementation Science | Issue 1/2018

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Abstract

Background

The U.S. opioid epidemic has been driven by the high volume of opioids prescribed by healthcare providers. U.S. states have recently enacted four types of laws designed to curb high-risk prescribing practices, such as high-dose and long-term opioid prescribing, associated with opioid-related mortality: (1) mandatory Prescription Drug Monitoring Program (PDMP) enrollment laws, which require prescribers to enroll in their state’s PDMP, an electronic database of patients’ controlled substance prescriptions, (2) mandatory PDMP query laws, which require prescribers to query the PDMP prior to prescribing an opioid, (3) opioid prescribing cap laws, which limit the dose and/or duration of opioid prescriptions, and (4) pill mill laws, which strictly regulate pain clinics to prevent nonmedical opioid prescribing. Some pain experts have expressed concern that these laws could negatively affect pain management among patients with chronic non-cancer pain. This paper describes the protocol for a mixed-methods study analyzing the independent effects of these four types of laws on opioid prescribing patterns and chronic non-cancer pain treatment, accounting for variation in implementation and enforcement of laws across states.

Methods

Many states have enacted multiple opioid prescribing laws at or around the same time. To overcome this issue, our study focuses on 18 treatment states that each enacted a single law of interest, and no other potentially confounding laws, over a 4-year period (2 years pre-/post-law). Qualitative interviews with key leaders in each of the 18 treatment states will characterize the timing, scope, and strength of each state law’s implementation and enforcement. This information will inform the design and interpretation of synthetic control models analyzing the effects of each of the two types of laws on two sets of outcomes: measures of (1) high-risk opioid prescribing and (2) non-opioid treatments for chronic non-cancer pain.

Discussion

Study of mandatory PDMP enrollment, mandatory PDMP query, opioid prescribing cap, and pill mill laws is timely given a dynamic policy environment in which numerous states pass, revise, implement, and enforce varied laws to address opioid prescribing each year. Findings will inform enactment, implementation, and enforcement of these laws in additional states.
Footnotes
1
States with mandatory PDMP enrollment laws as of January 1, 2017: Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Idaho, Illinois, Maine, Maryland, Massachusetts, Minnesota, Mississippi, Nevada, New Hampshire, New Mexico, Texas, Utah
 
2
States with mandatory PDMP query laws as of January 1, 2017: Arizona, Connecticut, Indiana, Kentucky, Louisiana, Maine, Massachusetts, New Hampshire, New Jersey, New Mexico, New York, Ohio, Oklahoma, Pennsylvania, Rhode Island, Tennessee, Vermont, Virginia, West Virginia, Wisconsin
 
3
States with opioid prescribing cap laws as of January 1, 2017: Connecticut, Maine, Massachusetts, New Hampshire, New York, Rhode Island, Vermont
 
4
States with pill mill laws as of January 1, 2017: Alabama, Florida, Georgia, Kentucky, Louisiana, Mississippi, Ohio, Tennessee, Texas, West Virginia, Wisconsin
 
Literature
1.
Rudd RA, Seth P, David F, Scholl L. Increases in drug and opioid-involved overdose deaths—United States, 2010–2015. MMWR Morb Mortal Wkly Rep. 2016;65
2.
3.
4.
Alexander GC, Kruszewski SP, Webster DW. Rethinking opioid prescribing to protect patient safety and public health. JAMA. 2012;308(18):1865–6.CrossRefPubMed
5.
Volkow ND, AT ML. Opioid abuse in chronic pain—misconceptions and mitigation strategies. N Engl J Med. 2016;374(13):1253–63.CrossRefPubMed
6.
Rutkow L, Davis CS. Opportunities to improve decision-making about opioid prescribing. J Gen Intern Med. 2016;
7.
King NB, Fraser V, Boikos C, Richardson R, Harper S. Determinants of increased opioid-related mortality in the United States and Canada, 1990-2013: a systematic review. Am J Public Health. 2014;104(8):e32–42.CrossRefPubMedPubMedCentral
8.
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):241–8.CrossRefPubMed
9.
Centers for Disease Control and Prevention. Vital signs: overdoses of prescription opioid pain relievers—United States, 1999–2008. MMWR Morb Mortal Wkly Rep. 2011;60(43):1487–92.
10.
Saha TD, Kerridge BT, Goldstein RB, et al. Nonmedical prescription opioid use and DSM-5 nonmedical prescription opioid use disorder in the United States. J Clin Psychiatry. 2016;77(6):772–80.CrossRefPubMedPubMedCentral
11.
Jones CM. Heroin use and heroin use risk behaviors among nonmedical users of prescription opioid pain relievers—United States, 2002-2004 and 2008-2010. Drug Alcohol Depend. 2013;132(1–2):95–100.CrossRefPubMed
12.
13.
14.
Twillman RK, Kirch R, Gilson A. Efforts to control prescription drug abuse: why clinicians should be concerned and take action as essential advocates for rational policy. CA Cancer J Clin. 2014;64(6):369–76.CrossRefPubMed
15.
Dowell D, Haegerich TM, Chou R. CDC guideline for prescribing Opioids for chronic pain - United States, 2016. MMWR Recomm Rep. 2016;65(1):1–49.CrossRefPubMed
16.
Dowell D, Zhang K, Noonan RK, Hockenberry JM. Mandatory provider review and pain clinic laws reduce the amounts of opioids prescribed and overdose death rates. Health Aff. 2016;35(10):1876–83.CrossRef
17.
Rutkow L, Turner L, Lucas E, Hwang C, Alexander GC. Most primary care physicians are aware of prescription drug monitoring programs, but many find the data difficult to access. Health Aff. 2015;34(3):484–92.CrossRef
18.
Chang HY, Lyapustina T, Rutkow L, et al. Impact of prescription drug monitoring programs and pill mill laws on high-risk opioid prescribers: a comparative interrupted time series analysis. Drug Alcohol Depend. 2016;165:1–8.CrossRefPubMedPubMedCentral
19.
Lyapustina T, Rutkow L, Chang HY, et al. Effect of a “pill mill” law on opioid prescribing and utilization: the case of Texas. Drug Alcohol Depend. 2016;159:190–7.CrossRefPubMed
20.
Bao Y, Pan Y, Taylor A, et al. Prescription drug monitoring programs are associated with sustained reductions in opioid prescribing by physicians. Health Aff. 2016;35(6):1045–51.CrossRef
21.
22.
Rutkow L, Smith, K.C., Debinski, B., Vernick, J.S., Alexander, G.C. Legal variation in efforts to address prescription drug abuse: a qualitative analysis. American Public Health Association Annual Meeting; 2016; Denver, CO.
23.
Rutkow L, Smith, K.C., Debinski, B., Vernick, J.S., Alexander, G.C. Interorganizational relationships within public health systems to address prescription drug abuse: a qualitative analysis. AcademyHealth Annual Research Meeting, Public Health Systems Research Interest Group; 2016; Boston, MA.
24.
Rutkow L, Chang HY, Daubresse M, Webster DW, Stuart EA, Alexander GC. Effect of Florida’s prescription drug monitoring program and pill mill laws on opioid prescribing and use. JAMA Intern Med. 2015;175(10):1642–9.CrossRefPubMed
25.
Kennedy-Hendricks A, Richey M, McGinty EE, Stuart EA, Barry CL, Webster DW. Opioid overdose deaths and Florida’s crackdown on pill mills. Am J Public Health. 2016;106(2):291–7.CrossRefPubMedPubMedCentral
26.
Chaparro LE, Furlan AD, Deshpande A, Mailis-Gagnon A, Atlas S, Turk DC. Opioids compared with placebo or other treatments for chronic low back pain: an update of the Cochrane review. Spine. 2014;39(7):556–63.CrossRefPubMed
27.
Dowell D, Haegerich TM, Chou R. CDC guideline for prescribing opioids for chronic pain—United States, 2016. JAMA. 2016;315(15):1624–45.CrossRefPubMed
28.
Loder E, Weizenbaum E, Frishberg B, Silberstein S. Choosing wisely in headache medicine: the American Headache Society’s list of five things physicians and patients should question. Headache. 2013;53(10):1651–9.CrossRefPubMed
29.
30.
Qaseem A, Wilt TJ, McLean RM, Forciea MA. Noninvasive treatments for acute, subacute, and chronic low back pain: a clinical practice guideline from the American College of Physicians. Ann Intern Med. 2017;166(7):514–30.CrossRefPubMed
31.
Fitzcharles MA, Ste-Marie PA, Goldenberg DL, et al. 2012 Canadian guidelines for the diagnosis and management of fibromyalgia syndrome: executive summary. Pain Res Manag. 2013;18(3):119–26.CrossRefPubMedPubMedCentral
32.
Abadie A, Diamond A, Hainmueller J. Comparative politics and the synthetic control method. Am J Polit Sci. 2015;59(2):495–510.CrossRef
33.
Wagenaar AC, Burris, S. Public Health Law Research: Theory and Methods. Jossey-Bass; 2013.
34.
Booth A, Hannes K, Harden A, Noyes J, Harris J. COREQ (consolidated criteria for reporting qualitative studies) . 2014.
35.
36.
Miles MB, Huberman AM. Qualitative data analysis: an expanded sourcebook. 2nd ed. Thousand Oaks, CA: Sage Publications; 1994.
37.
Richards L, Morse J. Read me first for a user’s guide to qualitative methods. 2nd ed. Thousand Oaks, CA: Sage; 2007.
38.
Abadie A, Diamond A, Hainmueller J. Synthetic control methods for comparative case studies: estimating the effect of California’s tobacco control program. J Am Stat Assoc. 2010;105(490):493–505.CrossRef
39.
Rudolph KE, Stuart EA, Vernick JS, Webster DW. Association between Connecticut’s permit-to-purchase handgun law and homicides. Am J Public Health. 2015;105(8):e49–54.CrossRefPubMedPubMedCentral
40.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B. 1995;57(1):289–300.
41.
Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Chapter 20. Meta-regression. Introduction to meta-analysis; 2009. p. 187–204.CrossRef
42.
Chen D-G (Din), Peace KE. Meta-regression. Applied meta-analysis with R. 2013:177–212.
43.
Thompson SG, Higgins J. How should meta-regression analyses be undertaken and interpreted? Stat Med. 2002;21(11):1559–73.CrossRefPubMed
44.
45.
Khandelwal N, Duncan I, Rubinstein E, Ahmed T, Pegus C. Community pharmacy and mail order cost and utilization for 90-day maintenance medication prescriptions. J Manag Care Pharm. 2012;18(3):247–55.PubMed
Metadata
Title
Protocol: mixed-methods study to evaluate implementation, enforcement, and outcomes of U.S. state laws intended to curb high-risk opioid prescribing
Authors
Emma E. McGinty
Elizabeth A. Stuart
G. Caleb Alexander
Colleen L. Barry
Mark C. Bicket
Lainie Rutkow
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Implementation Science / Issue 1/2018
Electronic ISSN: 1748-5908
DOI
https://doi.org/10.1186/s13012-018-0719-8

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