Dataset Information

Impact of a State Opioid Prescribing Limit and Electronic Medical Record Alert on Opioid Prescriptions: a Difference-in-Differences Analysis.

ABSTRACT:

Background

Prescribing limits are one policy strategy to reduce short-term opioid prescribing, but there is limited evidence of their impact.

Objective

Evaluate implementation of a state prescribing limit law and health system electronic medical record (EMR) alert on characteristics of new opioid prescriptions, refill rates, and clinical encounters.

Design

Difference-in-differences study comparing new opioid prescriptions from ambulatory practices in New Jersey (NJ) to controls in Pennsylvania (PA) from 1 year prior to the implementation of a NJ state prescribing limit (May 2016-May 2017) to 10 months after (May 2017-March 2018).

Participants

Adults with new opioid prescriptions in an academic health system with practices in PA and NJ.

Interventions

State 5-day opioid prescribing limit plus health system and health system EMR alert.

Main measures

Changes in morphine milligram equivalents (MME) and tablet quantity per prescription, refills, and encounters, adjusted for patient and prescriber characteristics.

Key results

There were a total of 678 new prescriptions in NJ and 4638 in PA. Prior to the intervention, median MME/prescription was 225 mg in NJ and 150 mg in PA, and median quantity was 30 tablets in both. After implementation, median MME/prescription was 150 mg in both states, and median quantity was 20 in NJ and 30 in PA. In the adjusted model, there was a greater decrease in mean MME and tablet quantity in NJ relative to PA after implementation of the policy plus alert (-?82.99 MME/prescription, 95% CI -?148.15 to -?17.84 and -?10.41 tabs/prescription, 95% CI -?19.70 to -?1.13). There were no significant differences in rates of refills or encounters at 30 days based on exposure to the interventions.

Conclusions

Implementation of a prescribing limit and EMR alert was associated with an approximately 22% greater decrease in opioid dose per new prescription in NJ compared with controls in PA. The combination of prescribing limits and alerts may be an effective strategy to influence prescriber behavior.

SUBMITTER: Lowenstein M

PROVIDER: S-EPMC7080923 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Publications

Impact of a State Opioid Prescribing Limit and Electronic Medical Record Alert on Opioid Prescriptions: a Difference-in-Differences Analysis.

Lowenstein Margaret M Hossain Erik E Yang Wei W Grande David D Perrone Jeanmarie J Neuman Mark D MD Ashburn Michael M Delgado M Kit MK

Journal of general internal medicine 20191010 3

<h4>Background</h4>Prescribing limits are one policy strategy to reduce short-term opioid prescribing, but there is limited evidence of their impact.<h4>Objective</h4>Evaluate implementation of a state prescribing limit law and health system electronic medical record (EMR) alert on characteristics of new opioid prescriptions, refill rates, and clinical encounters.<h4>Design</h4>Difference-in-differences study comparing new opioid prescriptions from ambulatory practices in New Jersey (NJ) to cont ...[more]

PMID: 31602561

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Project description:ImportanceReliance on prescription opioids for postprocedural analgesia has contributed to the opioid epidemic. With the implementation of electronic medical record (EMR) systems, there has been increasing use of computerized order entry systems for medication prescriptions, which is now more common than handwritten prescriptions. The EMR can autopopulate a default number of pills prescribed, and 1 potential method to alter prescriber behavior is to change the default number presented via the EMR system.ObjectiveTo investigate the association of lowering the default number of pills presented when prescribing opioids in an EMR system with the amount of opioid prescribed after procedures.Design, setting, and participantsA prepost intervention study was conducted to compare postprocedural prescribing patterns during the 3 months before the default change (February 18 to May 17, 2017) with the 3 months after the default change (May 18 to August 18, 2017). The setting was a multihospital health care system that uses Epic EMR (Hyperspace 2015 IU2; Epic Systems Corporation). Participants were all patients in the study period undergoing 1 of the 10 most common operations and discharged by postoperative day 1.InterventionThe default number of opioid pills autopopulated in the EMR when prescribing discharge analgesia was lowered from 30 to 12.Main outcomes and measuresLinear regression estimating the change in the median number of opioid pills and the total dose of opioid prescribed was performed. Opioid doses were converted into morphine milligram equivalents (MME) for comparison. The frequency of patients requiring analgesic prescription refills was also evaluated.ResultsThere were 1447 procedures (mean [SD] age, 54.4 [17.3] years; 66.9% female) before the default change and 1463 procedures (mean [SD] age, 54.5 [16.4] years; 67.0% female) after the default change. After the default change, the median number of opioid pills prescribed decreased from 30 (interquartile range, 15-30) to 20 (interquartile range, 12-30) per prescription (P < .001). The percentage of prescriptions written for 30 pills decreased from 39.7% (554 of 1397) before the default change to 12.9% (183 of 1420) after the default change (P < .001), and the percentage of prescriptions written for 12 pills increased from 2.1% (29 of 1397) before the default change to 24.6% (349 of 1420) after the default change (P < .001). Regression analysis demonstrated a decrease of 5.22 (95% CI, -6.12 to -4.32) opioid pills per prescription after the default change, for a total decrease of 34.41 (95% CI, -41.36 to -27.47) MME per prescription. There was no statistical difference in opioid refill rates (3.0% [4 of 135] before the default change vs 1.5% [2 of 135] after the default change, P = .41).Conclusions and relevanceLowering the default number of opioid pills prescribed in an EMR system is a simple, effective, cheap, and potentially scalable intervention to change prescriber behavior and decrease the amount of opioid medication prescribed after procedures.

Project description:BackgroundMultiple policy initiatives encourage more cautious prescribing of opioids in light of their risks. Electronic health record (EHR) redesign can influence prescriber choices, but some redesigns add to workload.ObjectiveTo estimate the effect of an EHR prescribing redesign on both opioid prescribing choices and keystrokes.DesignQuality improvement quasi-experiment, analyzed as interrupted time series.ParticipantsAdult patients of an academic multispecialty practice and a federally qualified health center (FQHC) who received new prescriptions for short-acting opioids, and their providers.InterventionIn the redesign, new prescriptions of short-acting opioids defaulted to the CDC-recommended minimum for opioid-naïve patients, with no alerts or hard stops, such that 9 keystrokes were required for a guideline-concordant prescription and 24 for a non-concordant prescription.Main measuresProportion of guideline-concordant prescriptions, defined as new prescriptions with a 3-day supply or less, calculated per 2-week period. Number of mouse clicks and keystrokes needed to place prescriptions.Key resultsAcross the 2 sites, 22,113 patients received a new short-acting opioid prescription from 821 providers. Before the intervention, both settings showed secular trends toward smaller-quantity prescriptions. At the academic practice, the intervention was associated with an immediate increase in guideline-concordant prescriptions from an average of 12% to 31% of all prescriptions. At the FQHC, about 44% of prescriptions were concordant at the time of the intervention, which was not associated with an additional significant increase. However, total keystrokes needed to place the concordant prescriptions decreased 62.7% from 3552 in the 6 months before the intervention to 1323 in the 6 months afterwards.ConclusionsAutocompleting prescription forms with guideline-recommended values was associated with a large increase in guideline concordance in an organization where baseline concordance was low, but not in an organization where it was already high. The redesign markedly reduced the number of keystrokes needed to place orders, with important implications for EHR-related stress.Trial registrationwww.ClinicalTrials.gov protocol 1710018646.

Project description:ImportancePrescription opioids play a significant role in the ongoing opioid crisis. Guidelines and physician education have had mixed success in curbing opioid prescriptions, highlighting the need for other tools that can change prescriber behavior, including nudges based in behavioral economics.ObjectiveTo determine whether and to what extent changes in the default settings in the electronic medical record (EMR) are associated with opioid prescriptions for patients discharged from emergency departments (EDs).Design, setting, and participantsThis quality improvement study randomly altered, during a series of five 4-week blocks, the prepopulated dispense quantities of discharge prescriptions for commonly prescribed opioids at 2 large, urban EDs. These changes were made without announcement, and prescribers were not informed of the study itself. Participants included all health care professionals (physicians, nurse practitioners, and physician assistants) working clinically in either of the 2 EDs. Data were collected from November 28, 2016, through July 9, 2017, and analyzed from July 16, 2017, through May 14, 2018.InterventionsDefault quantities for opioids were changed from status quo quantities of 12 and 20 tablets to null, 5, 10, and 15 tablets according to a block randomization scheme. Regardless of the default quantity, each health care professional decided for whom to prescribe opioids and could modify the quantity prescribed without restriction.Main outcomes and measuresThe primary outcome was the number of tablets of opioid-containing medications prescribed under each default setting.ResultsA total of 104 health care professionals wrote 4320 prescriptions for opioids during the study period. Using linear regression, an increase of 0.19 tablets prescribed (95% CI, 0.15-0.22) was found for each tablet increase in default quantity. When evaluating each of the 15 pairwise comparisons of default quantities (eg, 5 vs 15 tablets), a lower default was associated with a lower number of pills prescribed in more than half (8 of the 15) of the pairwise comparisons; there was a higher quantity in 1 and no difference in 6 comparisons.Conclusions and relevanceThese findings suggest that default settings in the EMR may influence the quantity of opioids prescribed by health care professionals. This low-cost, easily implementable, EMR-based intervention could have far-reaching implications for opioid prescribing and could be used as a tool to help combat the opioid epidemic.Trial registrationClinicalTrials.gov identifier: NCT04155229.

Project description:ImportanceThe majority of US states have passed mandates requiring the use of electronic prescribing of controlled substances (EPCS) as a tool to reduce rates of opioid prescribing. It is not known whether increasing use of EPCS will have the intended effect.ObjectiveTo assess the association between use of EPCS and trends in opioid prescribing.Design, setting, and participantsIn this retrospective, longitudinal cohort study of all patients and prescribers in the 50 US states and the District of Columbia from 2010 to 2018, changes in state-level use of EPCS and concurrent changes in opioid prescribing in each state are described. Then the association between changes in the use of EPCS and opioid prescribing are estimated using state and year fixed-effects models that include covariates for policy change and state demographic change. Data Analysis was performed on May 5, 2020.Main outcomes and measuresThe proportion of controlled substances in each state prescribed using EPCS based on opioid prescriptions per 100 persons and morphine milligram equivalents (MME) of opioids.ResultsIn 2018, the population-weighted percent of opioids prescribed using EPCS was 27%, up from 0% as of 2013. National rates of opioid prescriptions decreased from 78 prescriptions per 100 persons in 2013 to 53 in 2018. Over the same period, there was a decrease from 64 071 MME per 100 persons in 2013 to 40 906 MME per 100 persons in 2018, representing 36% of the 2013 level. By 2018, EPCS increased to 69.4% in states with mandates for its use and 23.6% in states without mandates. In multivariable models, a 10 percentage-point increase in the use of EPCS was associated with an additional 2 prescriptions per 100 persons (95% CI, 1.3-2.8) and a 0.8% (95% CI, 0.06%-1.5%) increase in MME per 100 persons.Conclusions and relevanceThese data suggest that an increased use of EPCS was not associated with decreased opioid prescribing or a decrease in the amount prescribed and may have been associated with a small increase in opioid prescribing. Opioid prescribing is associated with a variety of social and public health factors, and thus, despite the appeal, EPCS adoption alone may be insufficient to reduce opioid prescribing. Policy makers should consider levers to ensure that EPCS is integrated with outside data and that information is actively used to inform prescribing decisions.

Dataset Information

Impact of a State Opioid Prescribing Limit and Electronic Medical Record Alert on Opioid Prescriptions: a Difference-in-Differences Analysis.

Background

Objective

Design

Participants

Interventions

Main measures

Key results

Conclusions

Publications

Impact of a State Opioid Prescribing Limit and Electronic Medical Record Alert on Opioid Prescriptions: a Difference-in-Differences Analysis.

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