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How the presentation of patient information and decision-support advisories influences opioid prescribing behavior: A simulation study.

ABSTRACT: OBJECTIVE:The United States faces an opioid crisis. Integrating prescription drug monitoring programs into electronic health records offers promise to improve opioid prescribing practices. This study aimed to evaluate 2 different user interface designs for prescription drug monitoring program and electronic health record integration. MATERIALS AND METHODS:Twenty-four resident physicians participated in a randomized controlled experiment using 4 simulated patient cases. In the conventional condition, prescription opioid histories were presented in tabular format, and computerized clinical decision support (CDS) was provided via interruptive modal dialogs (ie, pop-ups). The alternative condition featured a graphical opioid history, a cue to visit that history, and noninterruptive CDS. Two attending pain specialists judged prescription appropriateness. RESULTS:Participants in the alternative condition wrote more appropriate prescriptions. When asked after the experiment, most participants stated that they preferred the alternative design to the conventional design. CONCLUSIONS:How patient information and CDS are presented appears to have a significant influence on opioid prescribing behavior.

SUBMITTER: Hussain MI

PROVIDER: S-EPMC7075535 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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How the presentation of patient information and decision-support advisories influences opioid prescribing behavior: A simulation study.

Hussain Mustafa I MI Nelson Ariana M AM Yeung Brent G BG Sukumar Lauren L Zheng Kai K

Journal of the American Medical Informatics Association : JAMIA 20200401 4

<h4>Objective</h4>The United States faces an opioid crisis. Integrating prescription drug monitoring programs into electronic health records offers promise to improve opioid prescribing practices. This study aimed to evaluate 2 different user interface designs for prescription drug monitoring program and electronic health record integration.<h4>Materials and methods</h4>Twenty-four resident physicians participated in a randomized controlled experiment using 4 simulated patient cases. In the conv ...[more]

PMID: 32016407

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Project description:BackgroundMoving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test-driven development and automated regression testing promotes reliability. Test-driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a "safety net" for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and "living" design documentation. Rapid-cycle development or "agile" methods are being successfully applied to CDS development. The agile practice of automated test-driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as "executable requirements."ObjectiveWe aimed to establish feasibility of acceptance test-driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse).MethodsAcceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory's expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with tests becoming part of the production regression test suite.ResultsWe used test-driven development to construct a new CDS tool advising Emergency Department nurses to perform a swallowing assessment prior to administering oral medication to a patient with suspected stroke. Test tables specified desired behavior for (1) applicable clinical settings, (2) triggering action, (3) rule logic, (4) user interface, and (5) system actions in response to user input. Automated test suite results for the "executable requirements" are shown prior to building the CDS alert, during build, and after successful build.ConclusionsAutomated acceptance test-driven development and continuous regression testing of CDS configuration in a commercial EHR proves feasible with open source software. Automated test-driven development offers one potential contribution to achieving high-reliability EHR configuration. Vetting acceptance tests with clinicians elicits their input on crucial configuration details early during initial CDS design and iteratively during rapid-cycle optimization.

Project description:OBJECTIVE:To evaluate the effects of shared decision making using a simple decision aid for opioid prescribing after hysterectomy. METHODS:We conducted a prospective quality initiative study including all patients undergoing hysterectomy for benign, nonobstetric indications between March 1, 2018, and July 31, 2018, at our academic institution. Using a visual decision aid, patients received uniform education regarding postoperative pain management. They were then educated on the department's guidelines regarding the maximum number of tablets recommended per prescription and the mean number of opioid tablets used by a similar cohort of patients in a previously published study at our institution. Patients were then asked to choose their desired number of tablets to receive on discharge. Structured telephone interviews were conducted 14 days after surgery. The primary outcome was total opioids prescribed before compared with after implementation of the decision aid. Secondary outcomes included opioid consumption, patient satisfaction, and refill requests after intervention implementation. RESULTS:Of 170 eligible patients, 159 (93.5%) used the decision aid (one patient who used the decision aid was subsequently excluded from the analysis owing to significant perioperative complications), including 110 (69.6%) laparoscopic, 40 (25.3%) vaginal, and eight (5.3%) abdominal hysterectomies. Telephone surveys were completed for 89.2% (n=141) of participants. Student's t-test showed that patients who participated in the decision aid (post-decision aid cohort) were discharged with significantly fewer oral morphine equivalents than patients who underwent hysterectomy before implementation of the decision aid (pre-decision aid cohort) (92±35 vs 160±81, P<.01), with no significant change in the number of requested refills (9.5% [n=15] vs 5.7% [n=14], P=.15). In the post-decision aid cohort, 76.6% of patients (n=121) chose fewer tablets than the guideline-allotted maximum. Approximately 76% of patients (n=102) reported having leftover tablets. CONCLUSION:This quality improvement initiative illustrates that a simple decision aid can result in a significant decrease in opioid prescribing without compromising patient satisfaction or postoperative pain management.

Project description:PROBLEM/CONDITION:In 2017, a total of 70,237 persons in the United States died from a drug overdose, and 67.8% of these deaths involved an opioid. Historically, the opioid overdose epidemic in the United States has been closely associated with a parallel increase in opioid prescribing and with widespread misuse of these medications. National and state policy makers have introduced multiple measures to attempt to assess and control the opioid overdose epidemic since 2010, including improvements in surveillance systems. PERIOD COVERED:2010-2016 DESCRIPTION OF SYSTEM: The Prescription Behavior Surveillance System (PBSS) was created in 2011. Its goal was to track rates of prescribing of controlled substances and possible misuse of such drugs using data from selected state prescription drug monitoring programs (PDMP). PBSS data measure prescribing behaviors for prescription opioids using multiple measures calculated from PDMP data including 1) opioid prescribing, 2) average daily opioid dosage, 3) proportion of patients with daily opioid dosages ?90 morphine milligram equivalents, 4) overlapping opioid prescriptions, 5) overlapping opioid and benzodiazepine prescriptions, and 6) multiple-provider episodes. For this analysis, PBSS data were available for 2010-2016 from 11 states representing approximately 38.0% of the U.S. POPULATION:Average quarterly percent changes (AQPC) in the rates of opioid prescribing and possible opioid misuse measures were calculated for each state. RESULTS AND INTERPRETATION:Opioid prescribing rates declined in all 11 states during 2010-2016 (range: 14.9% to 33.0%). Daily dosage declined least (AQPC: -0.4%) in Idaho and Maine, and most (AQPC: -1.6%) in Florida. The percentage of patients with high daily dosage had AQPCs ranging from -0.4% in Idaho to -2.3% in Louisiana. Multiple-provider episode rates declined by at least 62% in the seven states with available data. Variations in trends across the 11 states might reflect differences in state policies and possible differential effects of similar policies. PUBLIC HEALTH ACTIONS:Use of PDMP data from individual states enables a more detailed examination of trends in opioid prescribing behaviors and indicators of possible misuse than is feasible with national commercially available prescription data. Comparison of opioid prescribing trends among states can be used to monitor the temporal association of national or state policy interventions and might help public health policymakers recognize changes in the use or possible misuse of controlled prescription drugs over time and allow for prompt intervention through amended or new opioid-related policies.

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How the presentation of patient information and decision-support advisories influences opioid prescribing behavior: A simulation study.

Publications

How the presentation of patient information and decision-support advisories influences opioid prescribing behavior: A simulation study.

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