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Improving the design of California's prescription drug monitoring program.

ABSTRACT: Objective:The US CDC identified prescription drug monitoring programs (PDMPs) as a tool to address the contemporary opioid crisis, but few studies have investigated PDMP usability and effectiveness from the users' perspective. Even fewer have considered how practices differ across medical domains. In this study, we aimed to address these gaps, soliciting perspectives on PDMPs from providers contending with the opioid crisis: physicians working in emergency departments (EDs) and pain management clinics. We aimed to provide practical design recommendations to improve PDMP workflow integration, as well as controlled substance history retrieval, interpretation, and decision support. Methods:We conducted 16 in-depth semi-structured interviews with practicing emergency and pain physicians regarding their procedures, problems, and proposed solutions surrounding their use of CURES, California's PDMP. We investigated design problems in CURES by combining users' feedback with our usability inspection, drawing upon an extensive body of design literature. Then, we generated alternatives using design methods. Results:We found CURES's design did not accommodate the unique information needs of different medical domains. Further, clinicians had trouble accessing CURES and retrieving patients' controlled substance histories, mainly due to usability problems that could be addressed with little technical adjustment. Additionally, CURES rendered patient histories in large, cluttered tables, devoid of overview or context, making interpretation difficult and precarious. Lastly, our interviewees had rarely noticed or used advanced features, such as decision support. Discussion and Conclusion:Usability barriers inhibited adoption and effective use. We provide practical recommendations for improving opioid control by way of improving PDMP design, based on interviewees' suggestions and research-based design principles. Our findings have implications for other disciplines, including surgery and primary care.

SUBMITTER: Hussain MI

PROVIDER: S-EPMC6951861 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Improving the design of California's prescription drug monitoring program.

Hussain Mustafa I MI Nelson Ariana M AM Polston Gregory G Zheng Kai K

JAMIA open 20190128 1

<h4>Objective</h4>The US CDC identified prescription drug monitoring programs (PDMPs) as a tool to address the contemporary opioid crisis, but few studies have investigated PDMP usability and effectiveness from the users' perspective. Even fewer have considered how practices differ across medical domains. In this study, we aimed to address these gaps, soliciting perspectives on PDMPs from providers contending with the opioid crisis: physicians working in emergency departments (EDs) and pain mana ...[more]

PMID: 31984351

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Project description:ObjectiveClinical review of a prescription drug monitoring program (PDMP) is considered a valuable tool for opioid prescribing risk mitigation; however, PDMP use is often low, even in states with mandatory registration and use policies. The objective was to evaluate the impact of an academic detailing (AD) outreach intervention on PDMP use among primary care prescribers.MethodsAD intervention was delivered to primary care based controlled substance prescribers (N = 87) and their associated PDMP delegates (n = 42) by a clinical pharmacist as 1 component of a large-scale, statewide initiative to improve opioid prescribing safety. Prescriber PDMP use behavior was assessed by prescriber self-report and analysis of objective 2016-2018 PDMP data regarding the number of monthly report requests. We compared means between pre- and postintervention using a paired t test and plotted the monthly average reports over time to assess the trend of mean reports over time. Generalized linear mixed model with a negative binomial distribution was used to assess the difference in the trend and magnitude of the combined count of reports for the entire sample and prescriber subsets that were segmented on the basis of the adoption status of PDMP.ResultsThe monthly mean of reports by combined prescribers and delegates significantly increased after the AD intervention (mean 28.1 pre vs. 53.0 post; P < 0.001), with the increase in delegate reports (mean 17.1 pre vs. 60.0 post; P < 0.001) driving the overall increase. Reports were requested 40.4 times more often than in the preintervention period (P < 0.001). Patterns of pre- to postchanges in mean monthly report requests differed by baseline PDMP adoption status.ConclusionThe AD intervention was transformative in facilitating practice change to use delegates to run reports. Visits with both prescribers and delegates, including hands-on PDMP training and registration assistance, can be viewed as beneficial for practice facilitation.

Project description:STUDY OBJECTIVE:We assess whether an automated prescription drug monitoring program intervention in emergency department (ED) settings is associated with reductions in opioid prescribing and quantities. METHODS:We performed a retrospective cohort study of ED visits by Medicaid beneficiaries. We assessed the staggered implementation (pre-post) of automated prescription drug monitoring program queries at 86 EDs in Washington State from January 1, 2013, to September 30, 2015. The outcomes included any opioid prescribed within 1 day of the index ED visit and total dispensed morphine milligram equivalents. The exposure was the automated prescription drug monitoring program query intervention. We assessed program effects stratified by previous high-risk opioid use. We performed multiple sensitivity analyses, including restriction to pain-related visits, restriction to visits with a confirmed prescription drug monitoring program query, and assessment of 6 specific opioid high-risk indicators. RESULTS:The study included 1,187,237 qualifying ED visits (898,162 preintervention; 289,075 postintervention). Compared with the preintervention period, automated prescription drug monitoring program queries were not significantly associated with reductions in the proportion of visits with opioid prescribing (5.8 per 1,000 encounters; 95% confidence interval [CI] -0.11 to 11.8) or the amount of prescribed morphine milligram equivalents (difference 2.66; 95% CI -0.15 to 5.48). There was no evidence of selective reduction in patients with previous high-risk opioid use (1.2 per 1,000 encounters, 95% CI -9.5 to 12.0; morphine milligram equivalents 1.22, 95% CI -3.39 to 5.82). The lack of a selective reduction in high-risk patients was robust to all sensitivity analyses. CONCLUSION:An automated prescription drug monitoring program query intervention was not associated with reductions in ED opioid prescribing or quantities, even in patients with previous high-risk opioid use.

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Improving the design of California's prescription drug monitoring program.

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Improving the design of California's prescription drug monitoring program.

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