The Impact of a PDMP-EHR Data Integration Combined With Clinical Decision Support on Opioid and Benzodiazepine Prescribing Across Clinicians in a Metropolitan Area

Abstract

IntroductionDespite inconclusive evidence that prescription drug monitoring programs (PDMP) reduce opioid-related mortality, guidelines recommend PDMP review with opioid prescribing. Some reported barriers to use include time-consuming processes to obtain data and workflow disruptions.MethodsWe provided access to a PMDP-electronic health record (EHR) integrated program to 123 clinicians in one healthcare system. Remaining clinicians within the healthcare system and metropolitan area did not receive PDMP-EHR integration program access. We identified changes in opioid prescribing by linking prescription data available in the state PMDP database to individual clinicians. The primary outcome was change in receipt of high dose opioid prescriptions (>90 mg morphine equivalents) by Colorado residents before and after program integration. Secondary outcomes included changes in long-acting opioid receipt and overlapping opioid and benzodiazepine prescription days. Next, we surveyed clinicians to assess their perspectives on PDMP data acquisition before and after PDMP-EHR integration program access.ResultsHigh-dose opioid receipt decreased significantly across all 3 clinician groups [PDMP-EHR integration program access (27.6%, to 6.9%, P < 0.001); no program access in the same healthcare system (4.8% to 2.9%, P < 0.001), and no program access across the metropolitan area (13.5% to 6.1%, P < 0.001)]. Clinicians reported improved access to PDMP data using the PDMP-EHR integrated program compared to the state PDMP website (98.6%).ConclusionsFurther study of PDMP-EHR integration programs on patient and clinician outcomes may illuminate the role of this technology in public health and in clinical practice.

Barriers to Increasing Prescription Drug Monitoring Program Use

“…As EHR systems such as Cerner, EPIC, and Allscripts integrate PDMP for their customers, it is important to encourage the end-user (eg, prescribers and pharmacists) to become involved with the optimization and subsequent adoption so their needs and expectations are heard. This will enhance successful outcomes, as studies show successful integration significantly increases access to these data, improves satisfaction in use, and potentially guides safe and effective decision-making in opioid prescribing 20,28,29 …”

“…Improving treatment decisions and prescribing practices were identified as goals for accessing the PDMP. 20,21 Prior literature demonstrated HCPs and pharmacists felt this resource was extremely helpful in identifying "doctor shopping" and misuse of opioids and identifying those at risk for opioid overdose. 4,22 There were also multiple shortcomings and barriers to optimal use.…”

“…Prescribers and pharmacists used the PDMP for information about opioid doses and information on patients not known to them and to communicate and make decisions about the potential need for treatment. Improving treatment decisions and prescribing practices were identified as goals for accessing the PDMP 20,21 . Prior literature demonstrated HCPs and pharmacists felt this resource was extremely helpful in identifying “doctor shopping” and misuse of opioids and identifying those at risk for opioid overdose 4,22 …”

“…This will enhance successful outcomes, as studies show successful integration significantly increases access to these data, improves satisfaction in use, and potentially guides safe and effective decision-making in opioid prescribing. 20,28,29 There appeared to be an overall lack of training on the PDMP system received by the disciplines that prescribe and dispense. 10,22,23,30 More training may facilitate an increase in use.…”

Do clinical decision support systems for prescribing improve patient safety? a systematic literature review

“…A total of eight articles reported the weaknesses in the implementation of CDSS. The eight weaknesses are: i) incomplete information about drug side effects, prescribing recommendations for specific patient profiles, and adaptation to local epidemiology [2]; ii) the increase in prescribing time using CDSS is overestimated by end users [19]; iii) different prescribers' perceptions of the relevance of alerts [24]; iv) great variation in response to inpatient and outpatient alerts, as well as multiple alerts fatigue [27]; v) time consuming to get data and workflow interruption [44]; vi) the "alert fatigue" caused by a large number of irrelevant alerts reduces the effectiveness of CDSS [49]; vii) has no impact on compliance with appropriate usage guidelines [50]; and viii) the effect on clinical impact remains unclear [53].…”