Commentary on Pardo (2017) and Moyo <i>et al.</i> (2017): Much still unknown about prescription drug monitoring programs

Davis, Corey S.

doi:10.1111/add.13936

Cited by 9 publications

(12 citation statements)

References 18 publications

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“…While PDMPs are a valuable tool, they are not a panacea. Even with their successful application to support safe prescribing and reduce diversion, more comprehensive and dynamic approaches are needed to curtail opioid morbidity and mortality . Strategies that address the rapidly escalating role of illicit opioids, and develop consensus regarding the indications for opioid medications, and their proper use to manage acute and chronic pain types are essential .…”

Section: Discussionmentioning

confidence: 99%

“…How PDMPs are structured and operated (e.g., functionality, funding, oversight and evaluation, data sharing, and prescriber and dispenser requirements) varies among states and across time. Such heterogeneity may modify PDMP effectiveness but has often been overlooked in prior studies …”

Section: Introductionmentioning

confidence: 99%

“…Such heterogeneity may modify PDMP effectiveness but has often been overlooked in prior studies. 5,6 Only recently has research started to examine the role of program characteristics and differences in evaluations of PDMP effectiveness. [6][7][8][9][10][11][12][13][14][15] States with specific characteristics, including PDMPs that monitored four or more drug schedules or required more frequent data reporting, have been associated with greater reductions in nonfatal and fatal prescription opioid overdoses compared with states whose PDMPs lacked such features.…”

Section: Introductionmentioning

confidence: 99%

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Prescription drug monitoring programs: Assessing the association between “best practices” and opioid use in Medicare

Moyo

Simoni

Griffin

et al. 2019

Health Services Research

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Objective To estimate the impact of implementing prescription drug monitoring program (PDMP) best practices on prescription opioid use. Data Sources 2007–2012 Medicare claims for noncancer pain patients, and PDMP attributes from the Prescription Drug Abuse Policy System. Study Design We derived PDMP composite scores using the number of best practices adopted by states (range: 0‐14), classifying states as either no PDMP, low strength (0 < score < median), or high strength (score ≥ median). Using generalized linear models, we quantified the association between the PDMP score category and opioid use measures—overall and stratified by disability/age. Sensitivity analyses assessed the general Medicare sample regardless of pain diagnoses, individual PDMP characteristics, and compared GEE model findings to models with state fixed effects. Principal Findings Compared to non‐PDMP states, strong PDMP states had lower opioid cumulative doses (−296 mg; 95% CI: −512, −132), days supplied (−7.84; 95% CI: −10.6, −5.04), prescription fill rates (0.97; 95% CI: 0.95, 0.98), and mean daily doses (−2.31 mg; 95% CI: −3.14, −1.48) but greater prevalence of high opioid doses in disabled adults, whereas there was little or no change in older adults. Findings in states with weak PDMPs were substantively similar to those of strong PDMPs. Results from sensitivity analyses were mostly consistent with main findings except there was a null relationship with mean daily doses and high doses in models with state fixed effects. Conclusions Comprehensive or minimal adoption of PDMP best practices was associated with mostly comparable effects on Medicare beneficiaries’ opioid use; however, these effects were concentrated among nonelderly disabled adults.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Prescription drug monitoring programs: Assessing the association between “best practices” and opioid use in Medicare

Moyo

Simoni

Griffin

et al. 2019

Health Services Research

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“…Commentary on Pardo (2017) and Moyo et al (2017): Much still unknown about prescription drug monitoring programs…”

Section: Erratummentioning

confidence: 99%

“…

ErratumCommentary on Pardo (2017) and Moyo et al (2017): Much still unknown about prescription drug monitoring programs

Corey S. DavisIn the commentary by Davis [1], page 1798, printed as part of ADD 112:10, the first sentence in the second paragraph contains an error and should have read:We must also acknowledge that, even if PDMPs are targeted and utilized more effectively, scarce public re-sources may be deployed more effectively and cost-effectively elsewhere.The online version has now been corrected.We apologize for this error.

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confidence: 99%

Erratum

2017

Addiction

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ErratumCommentary on Pardo (2017) and Moyo et al. (2017): Much still unknown about prescription drug monitoring programs Corey S. DavisIn the commentary by Davis [1], page 1798, printed as part of ADD 112:10, the first sentence in the second paragraph contains an error and should have read:We must also acknowledge that, even if PDMPs are targeted and utilized more effectively, scarce public re-sources may be deployed more effectively and cost-effectively elsewhere.The online version has now been corrected.We apologize for this error.

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The importance of data source in prescription drug monitoring program research

Horwitz¹,

Davis

McClelland

et al. 2020

Health Services Research

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Objective To develop a legal research protocol for identifying various measures of prescription drug monitoring program (PDMP) start dates, apply the protocol to create a useable PDMP database, and test whether the different legal databases that are meant to contain the same information produce divergent results when used in an illustrative empirical exercise. Data sources Original research from state statutes, regulations, policy statements, and interviews; alternative PDMP data from the National Alliance for Model State Drug Laws and Prescription Drug Abuse Policy System; claims from a 40 percent random sample of Medicare beneficiaries, 2006‐2014. Study design Collaborative research effort among a group of lawyers to develop protocol. Legal research to produce an original database of dates state PDMP laws: (a) were enacted, (b) became operational, and (c) required query before prescribing controlled substances. Descriptive analyses characterize differences in dates of enactment, operation, and must query requirements. Regression analyses estimating, for each beneficiary annually any opioid prescription received in a calendar year, among other measures. Estimates conducted on under age 65 and full Medicare population. Data collection/extraction methods PDMP legal databases were linked to annual Medicare claims. Principal findings An original database differs from commonly used, publicly available data. Outcomes tested depend on the measure of PDMP date used and differ by data source. Must‐query laws show the largest effects among all the laws tested. Conclusions Data choices likely have had large consequences for study results and may explain contradictory outcomes in prior research. Researchers must understand and report protocol for dates used in PDMP research to ensure that results are internally consistent and verifiable.

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Commentary on Pardo (2017) and Moyo et al. (2017): Much still unknown about prescription drug monitoring programs

Cited by 9 publications

References 18 publications

Prescription drug monitoring programs: Assessing the association between “best practices” and opioid use in Medicare

Prescription drug monitoring programs: Assessing the association between “best practices” and opioid use in Medicare

Erratum

The importance of data source in prescription drug monitoring program research

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