Medicare letters to curb overprescribing of controlled substances had no detectable effect on providers

Health Affairs

Volumn 35, Issue 3, 2016, Pages 471-479

  Sacarny, Adam ^a   Yokum, David ^b,c   Finkelstein, Amy ^d,e,f   Agrawal, Shantanu ^g  

^a Department of Medicine   (United States)

^b White House   (United States)

^c Office of Evaluation Sciences in the General Services Administration   (United States)

^d MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^e J PAL North America   (United States)

^f NATIONAL BUREAU OF ECONOMIC RESEARCH   (United States)

^g CENTERS FOR MEDICARE AND MEDICAID SERVICES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONTROLLED SUBSTANCE;

ARTICLE; BILLING AND CLAIMS; CLINICAL PRACTICE; COST; DRUG ABUSE; GENERAL PRACTITIONER; HEALTH CARE PERSONNEL; HEALTH CARE POLICY; HEALTH CARE QUALITY; HUMAN; INAPPROPRIATE PRESCRIBING; MEDICAL EDUCATION; MEDICAL SPECIALIST; MEDICARE; NURSE PRACTITIONER; PATIENT SAFETY; PEER GROUP; PHYSICIAN ASSISTANT; PRESCRIPTION; PROTOCOL COMPLIANCE; COMPARATIVE STUDY; ECONOMICS; FACTUAL DATABASE; FEMALE; HEALTH CARE COST; MALE; NEEDS ASSESSMENT; OUTCOME ASSESSMENT; PREVENTION AND CONTROL; RETROSPECTIVE STUDY; UNITED STATES; UTILIZATION; WRITING;

CONTROLLED SUBSTANCES; CORRESPONDENCE AS TOPIC; DATABASES, FACTUAL; FEMALE; HEALTH CARE COSTS; HEALTH PERSONNEL; HUMANS; INAPPROPRIATE PRESCRIBING; MALE; MEDICARE PART D; NEEDS ASSESSMENT; OUTCOME ASSESSMENT (HEALTH CARE); RETROSPECTIVE STUDIES; UNITED STATES;

EID: 84960470738     PISSN: 02782715     EISSN: 15445208     Source Type: Journal    
DOI: 10.1377/hlthaff.2015.1025     Document Type: Article

References (33)

1. Department of Health and Human Services, Office of Inspector General. Retail pharmacies with questionable Part D billing. Washington (DC): HHS; 2012 May. (Technical Report No. OEI-02-09-00600).
2. Department of Health and Human Services, Office of Inspector General. Prescribers with questionable patterns in Medicare Part D. Washington (DC): HHS; 2013 Jun. (Technical Report No. OEI-02-09-00603).
3. Olfson M, King M, Schoenbaum M. Benzodiazepine use in the United States. JAMA Psychiatry. 2015; 72(2):136-42.
4. Government Accountability Office. Antipsychotic drug use: HHS has initiatives to reduce use among older adults in nursing homes, but should expand efforts to other settings. Washington (DC): GAO; 2015 Jan. (Technical Report No. GAO-15-211).
5. Centers for Disease Control and Prevention. Vital signs: overdoses of prescription opioid pain relievers-United States, 1999-2008. MMWR Morb MortalWkly Rep. 2011;60(43):1487-92.
6. Frenk SM, Porter KS, Paulozzi LJ. Prescription opioid analgesic use among adults: United States, 1999-2012. NCHS Data Brief. 2015;(189):1-8.
7. Hampton LM, Daubresse M, Chang HY, Alexander GC, Budnitz DS. Emergency department visits by adults for psychiatric medication adverse events. JAMA Psychiatry. 2014; 71(9):1006-14.
8. Kiefe CI, Allison JJ, Williams OD, Person SD, Weaver MT, Weissman NW. Improving quality improvement using achievable benchmarks for physician feedback: a randomized controlled trial. JAMA. 2001; 285(22):2871-9.
9. Hallsworth M, List J, Metcalfe R, Vlaev I. The behavioralist as tax collector: using natural field experiments to enhance tax compliance. Cambridge (MA): National Bureau of Economic Research; 2014 Mar. (NBER Working Paper No. 20007).
10. Kleven HJ, Knudsen MB, Kreiner CT, Pedersen S, Saez E. Unwilling or unable to cheat? Evidence from a tax audit experiment in Denmark. Econometrica. 2011; 79(3):651-92.
11. To access the Appendix, click on the Appendix link in the box to the right of the article online.
12. Here is an example of the potential for biased materials to influence prescribing behavior away from best practices. Van Zee A. The promotion and marketing of OxyContin: commercial triumph, public health tragedy. Am J Public Health. 2009; 99(2):221-7.
13. Centers for Disease Control and Prevention. Wide-ranging Online Data for Epidemiologic Research (WONDER), multiple cause of death, 2000-2014 [Internet]. Atlanta (GA): CDC; 2015 [cited 2016 Feb 8]. Available from: http://www.cdc.gov/nchs/data/health_policy/AADR_ drug_poisoning_involving_OA_ Heroin_US_2000-2014.pdf
14. Suzuki S. Potentially inappropriate opioid use in Medicare Part D [Internet]. Washington (DC): Medicare Payment Advisory Commission; 2014 Oct 9 [cited 2016 Feb 1]. Available from: http://www .medpac.gov/documents/october-2014-meeting-presentationpotentially-inappropriate-opioiduse-in-medicare-part-d-.pdf
15. Centers for Medicare and Medicaid Services. The role of a prescription drug monitoring program in reducing prescription drug diversion, misuse, and abuse [Internet]. Baltimore (MD): CMS; 2014 Jun [cited 2016 Feb 1]. Available from: http://www.cms.gov/Medicare-Medicaid-Coordination/Fraud-Prevention/Medicaid-Integrity-Education/Downloads/prescriptiondrugmonitoring-factsheet.pdf
16. Centers for Medicare and Medicaid Services. CMS strategy to combat Medicare Part D prescription drug fraud and abuse [Internet]. Baltimore (MD): CMS; 2014 Jan 6 [cited 2016 Feb 1]. Available from: https://www.cms.gov/Newsroom/Media ReleaseDatabase/Fact-sheets/2014-Fact-sheets-items/2014-01-06-2.html
17. Fehn AK, Colagiovanni J. Comparative billing reports: what providers should know. RAC Monitor [serial on the Internet]. 2011 Aug 3 [cited 2016 Feb 1]. Available from: http://www.racmonitor.com/news/3-feature-aritcles/625-comparativebilling-reports-what-providersshould-know.html
18. Levitt SD, List JA. What do laboratory experiments measuring social preferences reveal about the real world? J Econ Perspect. 2007;21(2):153-74.
19. Allcott H, Rogers T. The short-run and long-run effects of behavioral interventions: experimental evidence from energy conservation. Am Econ Rev. 2014; 104(10):3003-37.
20. Castro L, Scartascini C. Tax compliance and enforcement in the Pampas: evidence from a field experiment. Washington (DC): Inter-American Development Bank. 2013 Dec. (IDB Working Paper Series No. IDB-WP-472).
21. Fellner G, Sausgruber R, Traxler C. Testing enforcement strategies in the field: threat, moral appeal, and social information. J Eur Econ Assoc. 2013; 11(3):634-60.
22. Pomeranz D. No taxation without information: deterrence and selfenforcement in the value added tax. Cambridge (MA): National Bureau of Economic Research. 2013 Jul. (NBER Working Paper No. 19199).
23. Carrillo P, Pomeranz D, Singhal M. Dodging the taxman: firm misreporting and limits to tax enforcement. Cambridge (MA): National Bureau of Economic Research. 2014 Oct. (NBER Working Paper No. 20624).
24. This review article presents Catarina I. Kiefe and colleagues's study (Note 8) as an example of the value of benchmarking and other forms of feedback in continuing medical education. Mazmanian PE, Davis DA. Continuing medical education and the physician as a learner: guide to the evidence. JAMA. 2002;288(9):1057-60.
25. Arditi C, Rège-Walther M, Wyatt JC, Durieux P, Burnand B. Computergenerated reminders delivered on paper to health care professionals; effects on professional practice and health care outcomes. Cochrane Database Syst Rev. 2012; 12. DOI:10.1002/14651858.CD001175.pub3
26. Soumerai SB, McLaughlin TJ, Avorn J. Improving drug prescribing in primary care: a critical analysis of the experimental literature. Milbank Q. 1989; 67(2):268-317.
27. There is a long history of attempting to use audits and feedback to raise quality of care; for an early systematic review and discussion of the literature, see Note 26. This article presents a more recent systematic review. Ivers N, Jamtvedt G, Flottorp S, Young JM, Odgaard-Jensen J, French SD, et al. Audit and feedback: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2012;6:CD00D259.
28. McDonald CJ, Hui SL, Tierney WM. Effects of computer reminders for influenza vaccination on morbidity during influenza epidemics. MD Comput. 1992; 9(5):304-12.
29. McDonald CJ, Hui SL, Smith DM, Tierney WM, Cohen SJ, Weinberger M, et al. Reminders to physicians from an introspective computer medical record. A two-year randomized trial. Ann Intern Med. 1984; 100(1):130-8.
30. Hirano K, Imbens GW, Rubin DB, Zhou XH. Assessing the effect of an influenza vaccine in an encouragement design. Biostatistics. 2000; 1(1):69-88.
31. The prescribers were not notified that they were taking part in the study because such a message would need to indicate that the prescriber was an outlier, disclosing the information that we intended to test. The intervention was reviewed extensively by the Centers for Medicare and Medicaid Services to ensure that it was appropriate for the population.
32. The analysis plan is available at the study's page on the Amercian Economic Association Randomized Controlled Trials Registry (ID: AEARCTR-0000525). Finkelstein A, Sacarny A, Yokum D. The effect of informative letters on the prescription and receipt of Schedule II controlled substances [Internet]. Nashville (TN): American Economic Association Randomized Controlled Trials Registry; 2015 Jan 20 [cited 2016 Feb 1]. Available from: https://www.socialscienceregistry.org/trials/525
33. We also ran subanalyses by prescriber specialty and geographic region, both of which failed to detect effects.We expanded the outcome window of Exhibit 3 to 180 days, which also did not uncover effects. Of all the analyses we ran, the only statistically significant result was the thirty-day time window prescribing for low outliers, which showed an increase at the 10 percent level.