Prescription Drug Monitoring Programs: A Policy with Limited Impact on the Opioid Painkiller Epidemic Courtney R. Yarbrough Ph.D. Candidate University of Georgia Department of Public Administration and Policy Supported by a grant from the Robert Wood Johnson Foundation’s Public Health Law Research program (#72227)
Research Question • What is the e fg ect of prescription drug monitoring programs (PDMP) on prescribing for opioid and nonopioid analgesics through the Medicare Part D program? • Di fg erence-in-di fg erences estimation • Physician-level prescribing, 2010-2013 • Looking at days supply of prescriptions for opioids and nonopioid pain relievers, oxycodone, hydrocodone, and DEA Schedules II-IV
Rates of prescription painkiller sales, deaths and substance abuse treatment admissions (1999-2010) Source: Centers for Disease Control and Prevention MOTIVATION: THE OPIOID EPIDEMIC
The Opioid Epidemic • In 2012, U.S. patients filled 259 million prescriptions for opioid painkillers, enough to medicate every American adult for a month. • The U.S. consumes 80% of opioid painkillers in the world (99% of hydrocodone). • 1.9 million Americans have an opioid painkiller substance abuse disorder. More than 4 million use the drugs non-medically. • In 2014, there were almost 19,000 deaths related to opioid painkiller overdose.
Source: New York Times, Jan. 16, 2016
POLICY RESPONSE: PRESCRIPTION DRUG MONITORING PROGRAMS
Prescription Drug Monitoring Programs • Forty-nine states have now enacted PDMPs as a primary response to prescription painkiller abuse. • Online databases collect dispensing data from pharmacies about prescriptions filled for controlled substances. • Physicians can consult the PDMP to see if a patient has multiple, overlapping prescriptions. • PDMPs help uncover doctor shopping behavior by providing physicians with a tool to verify a patient’s drug-seeking behavior.
Prescription Drug Monitoring Programs • They vary state-to-state in operational details. • Unsolicited reports • Reporting frequency • Registration requirements • Statutes explicitly not requiring access • Mandatory access
PDMP Literature • Few studies have systematically studied the e fg ects of PDMPs. • The literature presents conflicting results on PDMP e fg ectiveness. • Most focus on ecological measures of outcomes such as opioid-related deaths or treatment admissions at the state-level. • Few contend with endogeneity of policy adoption.
Contribution • Observes individual-level responses to PDMPs by the policies’ intended targets—physicians • Examines possible switching between opioid and nonopioid pain treatments • Measures e fg ects on the most commonly abused opioids—oxycodone and hydrocodone • Uses di fg erence-in-di fg erences estimator to help control endogeneity of policy adoption
Prescription Drug Monitoring Programs • For this study, I consider a state to have a PDMP in time t if: 1. Dispensers are required to report. 2. Physicians have access. 3. The database is available online. • I use a proportional value of PDMP if the program was implemented in time t . • I also measure if a state has a statute explicitly not requiring physician PDMP access.
Online PDMP Implementation Pre-2010: 29 States
Online PDMP Implementation Pre-2010: 29 States 2010: MA (Dec.)
Online PDMP Implementation Pre-2010: 29 States 2010: MA (Dec.) 2011: FL, KS*, OR*
Online PDMP Implementation Pre-2010: 29 States 2012: AK*, DE, MT, NJ*, RI, SD*, TX, WA 2010: MA (Dec.) 2011: FL, KS*, OR*
Online PDMP Implementation Pre-2010: 29 States 2012: AK*, DE, MT, NJ*, RI, SD*, TX, WA 2010: MA (Dec.) 2013: AR, GA*, WI*, WY* 2011: FL, KS*, OR*
Online PDMP Implementation Pre-2010: 29 States 2012: AK*, DE, MT, NJ*, RI, SD*, TX, WA 2010: MA (Dec.) 2013: AR, GA*, WI*, WY* 2011: FL, KS*, OR* Control: MD, MO, NE, NH, PA
Data – Dependent Variables • ProPublica Prescriber Checkup database (2010-2012) and Centers for Medicare and Medicaid Services (2013) • Number of prescriptions filled through Medicare Part D at the drug-provider-year level • All providers included with at least 50 Part D fills per year • Drugs suppressed if < 10 • Aggregated according to drug categories (from Medicare Formulary Reference File) to form 7 DVs
Data – Dependent Variables • Logged days supply of a physicians prescribing that is for: 1. Opioid painkillers 2. Nonopioid painkillers 3. Hydrocodone 4. Oxycodone 5. Schedule II Opioids (including oxycodone) 6. Schedule III Opioids (including hydrocodone) 7. Schedule IV Opioids (e.g., tramadol)
Data – Independent Variables • State-Level • PDMP (proportional [0,1]) • “No Required Access” Statute (proportional [0,1]) • County-Level • Part D Enrollment • Per Capita Medicare Costs • Percent of Population White, Black, Hispanic, Asian, and Other • Median Income • HHI of Physician Prescribing • Provider-Level • Provider Sex • Medical Specialty Dummies • State Fixed E fg ects • Year Fixed E fg ects
Empirical Model • OLS models with state and year fixed e fg ects • n = 789,569 at the physician-year level • Excluding the 29 states with PDMPs prior to 2011 and including state and year fixed e fg ects transforms the models into the algebraic equivalents of di fg erence-in-di fg erences models with the coe ffj cient for PDMP st becoming the DID interaction term.
Pre-trend Analysis
Results PDMP PDMP Statute Outcome t-score t-score Coefficient Coefficient Opioids 0.0072 (-0.78) 0.038*** (-3.27) Nonopioids 0.025*** (-2.61) 0.0065 (-0.53) Oxycodone -0.063*** (-5.77) 0.061*** (-4.52) Hydrocodone -0.0021 (-0.23) 0.0078 (-0.66) Schedule II -0.039*** (-3.53) 0.040*** (-2.93) Schedule III -0.0045 (-0.50) 0.012 (-1.04) Schedule IV 0.023** (-2.42) 0.017 (-1.45)
Results PDMP Statute PDMP
Conclusion: A Limited E fg ect for PDMPs • PDMPs do not appear to decrease physician prescribing of opioid painkillers overall. • They have a small but targeted e fg ect with respect to the high-profile drug oxycodone. • Back-of-the-envelope calculation shows a decrease of ~104 days supply per doctor. • Statutes explicitly not requiring physician use of a PDMP have the e fg ect of reversing these reductions.
Conclusion: A Limited E fg ect for PDMPs • Hydrocodone prescribing seems to remain unchanged, despite also being heavily abused. • Small substitution e fg ects from Schedule 2 to Schedule 4 drugs and nonopioids analgesics might prevent some adverse e fg ects of opioid use. • PDMPs have in recent years shown only limited success in reducing opioid prescribing, suggesting that they need to be strengthened and/or additional policy tools are required.
Next Steps • Exploit other variation in PDMP characteristics to understand what works. • Measure the e fg ect of PDMPs for the prescribing outliers. • Examine changes in states that have begun to require physician consultation of the PDMP for every prescription written. • Analyze the relationship between PDMPs and individual pain management.
Limitations • Studies using claims data outside Medicare may arrive at di fg erent results. • DID models control for unobservable time- invariant sources of endogeneity; however, time-variation sources may persist. • Other policy changes related to opioid abuse prevention are not included (e.g., Pill Mill legislation). • If many patients are crossing state lines to non- PDMP states, the models may overestimate size of the e fg ect.
Thank you COURTNEY R. YARBROUGH UNIVERSITY OF GEORGIA cryarb@uga.edu
Medicare Part D Data • Beneficiaries include age-eligible (65+ YO) and disability-eligible (from SSDI) individuals. • 1/3 of all beneficiaries had ≥ 1 opioid prescription. • 25% of observations in data were from claims by disability-eligible patients. 44% of disabled beneficiaries had ≥ 1 opioid prescription; 23% were chronic users. 1/3 have a musculoskeletal diagnosis (e.g., back pain). • MedPAC found evidence for 170,000 cases of doctor shopping in 2008 claims. • Inpatient hospital stays increased 10.6% annually among Medicare patients 1993-2012.
Source: Social Security Administration Credit: Lam Thuy Vo/NPR
Opioids: A Gateway Drug • Heroin poisoning deaths have tripled since 2010 (10,574 in 2014). • Both opioid painkillers and heroin are opiates and operate through similar channels on the brain, producing comparable euphoria. • 80% of new heroin users are previous abusers of opioid painkillers. • Users report transitioning to heroin because the drug is much less expensive and more accessible than prescription opioids. • Suspicions that opioid-abuse policies have driven to rise in heroin use appear to unsubstantiated (Compton, Jones & Baldwin, 2016).
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