A History of Prescription Drug Monitoring Programs in the United States: Political Appeal and Public Health Efficacy

A Jay  Holmgren; Alyssa  Botelho; Allan M Brandt

Article | American Journal of Public Health | August 2020

A History of Prescription Drug Monitoring Programs in the United States: Political Appeal and Public Health Efficacy

by A Jay Holmgren, Alyssa Botelho and Allan M Brandt

Abstract

Prescription drug monitoring programs (PDMPs) have become a widely embraced policy to address the US opioid crisis. Despite mixed scientific evidence on their effectiveness at improving health and reducing overdose deaths, 49 states and Washington, DC have adopted PDMPs, and they have received strong bipartisan legislative support. This article explores the history of PDMPs, tracking their evolution from paper-based administrative databases in the early 1900s to modern-day electronic systems that intervene at the point of care. We focus on two questions: how did PDMPs become so widely adopted in the United States, and how did they gain popularity as an intervention in the contemporary opioid crisis? Through this historical approach, we evaluate what PDMPs reflect about national drug policy and broader cultural understandings of substance use disorder in the United States today.

Keywords: Health Disorders; Technology; Programs; Technology Adoption; History; Government and Politics; Policy; United States;

Format: Print

Citation:

Holmgren, A Jay, Alyssa Botelho, and Allan M Brandt. "A History of Prescription Drug Monitoring Programs in the United States: Political Appeal and Public Health Efficacy." American Journal of Public Health 110, no. 8 (August 2020).

Prescription drug monitoring programs (PDMPs) have become a widely embraced policy solution to the opioid epidemic in the US. PDMPs offer prescribers a comprehensive view of patients’ controlled substance prescription history and can be used to monitor and reduce inappropriate opioid prescribing. However, poor usability and lack of integration with electronic health records (EHRs) have limited their effectiveness. Furthermore, without PDMP integration in EHRs, prescribers are forced to manage multiple disconnected software systems that interrupt clinical workflow, which may exacerbate technology-driven physician burnout and result in prescribers neglecting to check the PDMP before writing opioid prescriptions. Efforts to integrate PDMPs with EHRs may be associated with reduced prescriber burden and improved PDMP effectiveness; however, the extent to which this adoption has occurred remains unknown on a national scale in the US. Extant literature has focused on usability of PDMP systems rather than adoption and integration. PDMP integration rates are particularly important among hospitals, which are major sources of ambulatory care and thus potential opioid prescribing. Furthermore, hospitals in areas with high opioid prescribing rates may gain the most from PDMP integration efforts because physicians are more likely to provide treatment to patients with current or past opioid prescriptions in these regions. In this study, we assessed the level of EHR and PDMP integration in hospitals, comparing hospitals located in US counties with vs without high opioid prescribing rates.

Mobile health applications (“apps”) have rapidly proliferated, yet their ability to improve outcomes for patients remains unclear. A validated tool that addresses apps’ potentially important dimensions has not been available to patients and clinicians. The objective of this study was to develop and preliminarily assess a usable, valid, and open-source rating tool to objectively measure the risks and benefits of health apps. We accomplished this by using a Delphi process, where we constructed an app rating tool called THESIS that could promote informed app selection. We used a systematic process to select chronic disease apps with ≥4 stars and <4-stars and then rated them with THESIS to examine the tool’s interrater reliability and internal consistency. We rated 211 apps, finding they performed fair overall (3.02 out of 5 [95% CI, 2.96–3.09]), but especially poorly for privacy/security (2.21 out of 5 [95% CI, 2.11–2.32]), interoperability (1.75 [95% CI, 1.59–1.91]), and availability in multiple languages (1.43 out of 5 [95% CI, 1.30–1.56]). Ratings using THESIS had fair interrater reliability (κ = 0.3–0.6) and excellent scale reliability (ɑ = 0.85). Correlation with traditional star ratings was low (r = 0.24), suggesting THESIS captures issues beyond general user acceptance. Preliminary testing of THESIS suggests apps that serve patients with chronic disease could perform much better, particularly in privacy/security and interoperability. THESIS warrants further testing and may guide software and policymakers to further improve app performance, so apps can more consistently improve patient outcomes.

Article | JAMA Network Open

National Trends in the Safety Performance of Electronic Health Record Systems From 2009 to 2018

David Classen, A Jay Holmgren, Zoe Co, Lisa Newmark, Diane Seger, Melissa Danforth and David Bates

Importance Despite the broad adoption of electronic health record (EHR) systems across the continuum of care, safety problems persist. Objective To measure the safety performance of operational EHRs in hospitals across the country during a 10-year period. Design, Setting, and Participants This case series included all US adult hospitals nationwide that used the National Quality Forum Health IT Safety Measure EHR computerized physician order entry safety test administered by the Leapfrog Group between 2009 and 2018. Data were analyzed from July 1, 2018 to December 1, 2019. Exposure The Health IT Safety Measure test, which uses simulated medication orders that have either injured or killed patients previously to evaluate how well hospital EHRs could identify medication errors with potential for patient harm. Main Outcomes and Measures Descriptive statistics for performance on the assessment test over time were calculated at the overall test score level, type of decision support category level, and EHR vendor level. Results Among 8657 hospital-years observed during the study, mean (SD) scores on the overall test increased from 53.9% (18.3%) in 2009 to 65.6% (15.4%) in 2018. Mean (SD) hospital score for the categories representing basic clinical decision support increased from 69.8% (20.8%) in 2009 to 85.6% (14.9%) in 2018. For the categories representing advanced clinical decision support, the mean (SD) score increased from 29.6% (22.4%) in 2009 to 46.1% (21.6%) in 2018. There was considerable variation in test performance by EHR. Conclusions and Relevance These findings suggest that despite broad adoption and optimization of EHR systems in hospitals, wide variation in the safety performance of operational EHR systems remains across a large sample of hospitals and EHR vendors. Hospitals using some EHR vendors had significantly higher test scores. Overall, substantial safety risk persists in current hospital EHR systems.

Keywords: electronic health record systems; United States;

Citation:

Classen, David, A Jay Holmgren, Zoe Co, Lisa Newmark, Diane Seger, Melissa Danforth, and David Bates. "National Trends in the Safety Performance of Electronic Health Record Systems From 2009 to 2018." JAMA Network Open 3, no. 5 (May 2020). View Details

Cite View Details Read Now

Faculty & Research

A History of Prescription Drug Monitoring Programs in the United States: Political Appeal and Public Health Efficacy

Abstract

Citation:

About the Author

More from the Author