Physician Responses to Enhanced Prescription Drug Monitoring Program Profiles

Development of the ADFICE_IT clinical decision support system to assist deprescribing of fall-risk increasing drugs: A user-centered design approach

INTRODUCTION

Deprescribing fall-risk increasing drugs (FRIDs) is promising for reducing the risk of falling in older adults. Applying appropriate deprescribing in practice can be difficult due to the outcome uncertainties associated with stopping FRIDs. The ADFICE_IT intervention addresses this complexity with a clinical decision support system (CDSS) that facilitates optimum deprescribing of FRIDs by using a fall-risk prediction model, aggregation of deprescribing guidelines, and joint medication management.

METHODS

The development process of the CDSS is described in this paper. Development followed a user-centered design approach in which users and experts were involved throughout each phase. In phase I, a prototype of the CDSS was developed which involved a literature and systematic review, European survey (n = 581), and semi-structured interviews with clinicians (n = 19), as well as the aggregation and testing of deprescribing guidelines and the development of the fall-risk prediction model. In phase II, the feasibility of the CDSS was tested by means of two usability testing rounds with users (n = 11).

RESULTS

The final CDSS consists of five web pages. A connection between the Electronic Health Record allows for the retrieval of patient data into the CDSS. Key design requirements for the CDSS include easy-to-use features for fast-paced clinical environments, actionable deprescribing recommendations, information transparency, and visualization of the patient's fall-risk estimation. Key elements for the software include a modular architecture, open source, and good security.

CONCLUSION

The ADFICE_IT CDSS supports physicians in deprescribing FRIDs optimally to prevent falls in older patients. Due to continuous user and expert involvement, each new feedback round led to an improved version of the system. Currently, a cluster-randomized controlled trial with process evaluation at hospitals in the Netherlands is being conducted to test the effect of the CDSS on falls. The trial is registered with ClinicalTrials.gov (date; 7-7-2022, identifier: NCT05449470).

Barriers and facilitators related to healthcare practitioner use of real time prescription monitoring tools in Australia

Introduction

Real time prescription monitoring tools have been implemented in Australia to address the growing concerns of drug misuse, drug-related mortality and morbidity. The objective of this pilot study is to investigate the barriers and facilitators related to healthcare practitioner use of real time prescription monitoring tools.

Methods

An online survey was distributed to Australian prescribers and pharmacists who use a real time prescription monitoring tool. Data analysis included descriptive statistics, chi-square tests and multivariate logistic regression analyses.

Results

A total of 102 questionnaires were analyzed. Practitioners mainly agreed that the tool was easy to use (n = 64; 66.7%) and access (n = 56; 57.7%), and the data was easy to interpret (n = 77; 79.4%). Over half agreed that they wanted training to guide clinical actions (n = 52; 55.9%) and clinical guidelines or guidance on what to do with the RTPM findings (n = 51; 54.8%). Prescribers were more likely to report difficulties with workplace access to a computer or the internet (n = 7; 21.2%) compared with pharmacists (n = 6; 9.2%; p = 0.037). Practitioners working in community settings (n = 59; 57.9%; p = 0.022) and those with 1-10 years practice experience (n = 45; 44.2%; p = 0.036) were more likely to want training to guide clinical actions in response to RTPM information.

Conclusion

This is the first known study to investigate the barriers and facilitators related to practitioner use of RTPM tools in Australia. The results from this study can inform further research to gain an understanding of healthcare practitioners use of RTPM tools, and how to minimize barriers and optimize use for the essential delivery of quality healthcare.

Opioid-related policy changes: Experiences and perspectives from people who use opioids to manage non-cancer chronic pain

INTRODUCTION

People who use prescription opioids to manage non-cancer chronic pain are particularly vulnerable to opioid-related policy change. This study aims to better understand what prescription opioids provide this population, what concerns they have in the context of new and changing opioid policies, such as the recently implemented prescription drug monitoring program in Victoria, Australia, their experiences of prescription opioid use, chronic pain and what they would like their healthcare to look like.

METHODS

Semi-structured interviews were conducted with 30 people who use opioids to manage chronic non-cancer pain.

RESULTS

Prescription opioids played an important role in supporting quality of life and mental health. However, experiences of stigma and lack of empathy from healthcare providers were common. Participants sought accurate information about their medications and expressed a desire for shared decision-making in healthcare.

DISCUSSION AND CONCLUSION

Prescription opioids can play an important role in pain management as well as social and psychological functioning for people living with non-cancer chronic pain. Opioid-related policy changes to medication availability need to consider the potential impacts that reducing, limiting or discontinuing opioids may have on this population. Including the voices of people who use prescription opioids to manage non-cancer chronic pain in respectful, compassionate and meaningful ways.

Provider perspectives and experiences following the integration of the prescription drug monitoring program into the electronic health record

Prescription drug monitoring programs (PDMPs) are a public health tool for prescribers and pharmacists to monitor controlled substance use at the patient level. The objectives of this study were to (1) assess attitudes about the PDMP and perceived changes in experience and decision-making following integration into the electronic health record (EHR), and (2) identify barriers to optimal PDMP use and user recommendations for improvement. This descriptive study used an electronic survey to obtain feedback from prescribers and pharmacists at a single academic medical center. Descriptive statistics were calculated, and textual data were analyzed. Of 1480 PDMP users 208 responded (14.1%). Responses demonstrated the integration of the PDMP into the EHR simplified log-in and access to PDMP information resulting in more frequent access and perceived improvement of care quality. Barriers included technical issues accessing the PDMP within the EHR and the lack of integration of other state PDMPs. Overall, the benefit of integrating the PDMP into the EHR was positive but largely limited to streamlining log-in and patient selection. Recommendations for improvement include addressing technological issues and education on PDMP interpretation and integrating new features that may modify prescribing, referral, and co-prescribing behaviors.

Mapping the research addressing prescription drug monitoring programs: A scoping review

ISSUES

Prescription drug monitoring programs are a harm minimisation intervention and clinical decision support tool that address the public health concern surrounding prescription drug misuse. Given the large number of studies published to date and the ongoing implementation of these programs, it is important to map the literature and identify areas for further research to improve practice.

APPROACH

A scoping review was undertaken to identify the research on prescription drug monitoring programs published between January 2015 and April 2021.

KEY FINDINGS

A total of 153 citations were included in this scoping review. The majority of the studies originated from the USA and were quantitative. Results on program effectiveness are mixed and mainly examine their association with opioid-related outcomes. Unintended consequences are revealed in the literature and this review also highlights barriers to program use.

IMPLICATIONS

Overall, findings are mixed despite the large number of studies published to date. Mapping the literature identifies priority areas for further research that can advise policymakers and clinicians on practice improvement.

CONCLUSION

Results on prescription drug monitoring program effectiveness are mixed and mainly examine their association with opioid-related outcomes. This review highlights barriers to prescription drug monitoring program effectiveness related to program use and system integration. Further research is needed in these areas to improve prescription drug monitoring program use and patient outcomes.

Phenotyping as disciplinary practice: data infrastructure and the interprofessional conflict over drug use in California

The narrative of the digital phenotype as a transformative vector in healthcare is nearly identical to the concept of "data drivenness" in other fields such as law enforcement. We examine the role of a prescription drug monitoring program (PDMP) in California-a computerized law enforcement surveillance program enabled by a landmark Supreme Court case that upheld "broad police powers"-in the interprofessional conflict between physicians and law enforcement over the jurisdiction of drug use. We bring together interview passages, clinical artifacts, and academic and gray literature to investigate the power relations between police, physicians, and patients to show that prescribing data appear to the physician as evidence of problematic patient behavior by the patients, and to law enforcement as evidence of physician misconduct. In turn, physicians have adopted a disciplinary approach to patients, using quasi-legalistic documents to litigate patient behavior. We conclude that police powers have been used to pave data infrastructure through a contested jurisdiction, and law enforcement have used that infrastructure to enroll physicians into the work of disciplining patients.

Advances in prescription drug monitoring program research: a literature synthesis (June 2018 to December 2019)

PURPOSE OF REVIEW

Nearly every U.S. state operates a prescription drug monitoring program (PDMP) to monitor dispensing of controlled substances. These programs are often considered key policy levers in the ongoing polydrug epidemic. Recent years have seen rapid growth of peer-reviewed literature examining PDMP consultation and the impacts of these programs on diverse patient populations and health outcomes. This literature synthesis presents a review of studies published from June 2018 to December 2019 and provides relevant updates from the perspective of three researchers in this field.

RECENT FINDINGS

The analyzed studies were primarily distributed across three overarching research focus areas: outcome evaluations (n = 29 studies), user surveys (n = 23), and surveillance (n = 22). Identified themes included growing awareness of the unintended consequences of PDMPs on access to opioids, effects on benzodiazepines and stimulant prescribing, challenges with workflow integration across multiple specialties, and new opportunities for applied data science.

SUMMARY

There is a critical gap in existing PDMP literature assessing how these programs have impacted psychiatrists, their prescribing behaviors, and their patients. Although PDMPs have improved population-level monitoring of controlled substances from medical sources, their role in responding to a drug epidemic shifting to illicitly manufactured drugs is under scrutiny.

Advanced visualizations to interpret prescription drug monitoring program information

OBJECTIVES

Prescription drug monitoring programs (PDMPs) are state-based databases that contain information about controlled substance prescriptions dispensed by pharmacies. Many states now mandate PDMP use by prescribers, despite unclear effectiveness. We hypothesize that it is possible to improve the interpretability, and hence effectiveness, of PDMPs by enhancing them.

METHODS

This was a real-time simulation of an enhanced PDMP. Fifty practicing physicians (25 primary care, 25 emergency medicine) were randomized to see three cases with a standard profile or an enhanced profile that included graphical representation of prescriptions and identified risky prescribing patterns. After a two-month washout period, participants were placed in the opposite group.

RESULTS

Physicians presented with the enhanced profile were more likely to correctly identify patients with multiple providers (97.0% vs. 85.8%, p = 0.002), overlapping opioid and benzodiazepine prescriptions (94.7% vs. 87.5%, p = 0.03), overlapping opioid prescriptions (89.5% vs. 70.8%, p < 0.01), high daily dosages of opioids (99.2% vs. 25.0%, p = 0.02), and traveling to distant pharmacies (79.7% vs. 2.5%, p < 0.01). There was no difference in interpretation time for the three cases (standard profile 657.3 s vs. enhanced profile 686.3 s, p = 0.31).

CONCLUSIONS

A simulated PDMP with graphical displays and interpretation of findings was, for this cohort of emergency physicians and primary care physicians, associated with an increased ability to determine high-risk features on PDMP profiles.