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      Association of Default Electronic Medical Record Settings With Health Care Professional Patterns of Opioid Prescribing in Emergency Departments : A Randomized Quality Improvement Study

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          Abstract

          This quality improvement study assesses whether and to what extent changes in the default settings in the electronic medical record (EMR) are associated with the quantity of opioids prescribed for patients discharged from emergency departments (EDs). Is changing the electronic medical record default settings for opioid prescriptions associated with the quantity of opioids prescribed for patients discharged from emergency departments? In this randomized quality improvement study of 4320 opioid prescriptions, lower default settings were associated with fewer opioids prescribed and a lower proportion of prescriptions that exceeded the opioid prescribing recommendation of the Centers for Disease Control and Prevention. These findings suggest that default electronic medical record settings may influence prescribing behavior and should be modified to decrease the quantity of opioids prescribed. Prescription 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. To 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). This 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. Default 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. The primary outcome was the number of tablets of opioid-containing medications prescribed under each default setting. A 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. These 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. ClinicalTrials.gov identifier: NCT04155229

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          Characteristics of opioid prescriptions in 2009.

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            Intertwined Epidemics: National Demographic Trends in Hospitalizations for Heroin- and Opioid-Related Overdoses, 1993–2009

            The historical patterns of opiate use show that sources and methods of access greatly influence who is at risk. Today, there is evidence that an enormous increase in the availability of prescription opiates is fuelling a rise in addiction nationally, drawing in new initiates to these drugs and changing the geography of opiate overdoses. Recent efforts at supply-based reductions in prescription opiates may reduce harm, but addicted individuals may switch to other opiates such as heroin. In this analysis, we test the hypothesis that changes in the rates of Prescription Opiate Overdoses (POD) are correlated with changes in the rate of heroin overdoses (HOD). ICD9 codes from the Nationwide Inpatient Sample and population data from the Census were used to estimate overall and demographic specific rates of POD and HOD hospital admissions between 1993 and 2009. Regression models were used to test for linear trends and lagged negative binomial regression models were used to model the interrelationship between POD and HOD hospital admissions. Findings show that whites, women, and middle-aged individuals had the largest increase in POD and HOD rates over the study period and that HOD rates have increased in since 2007. The lagged models show that increases in a hospitals POD predict an increase in the subsequent years HOD admissions by a factor of 1.26 (p<0.001) and that each increase in HOD admissions increase the subsequent years POD by a factor of 1.57 (p<0.001). Our hypothesis of fungibility between prescription opiates and heroin was supported by these analyses. These findings suggest that focusing on supply-based interventions may simply lead to a shift in use to heroin rather minimizing the reduction in harm. The alternative approach of using drug abuse prevention resources on treatment and demand-side reduction is likely to be more productive at reducing opiate abuse related harm.
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              Intensity of Chronic Pain--The Wrong Metric?

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                Author and article information

                Journal
                JAMA Internal Medicine
                JAMA Intern Med
                American Medical Association (AMA)
                2168-6106
                January 21 2020
                Affiliations
                [1 ]Department of Emergency Medicine, University of California, San Francisco
                [2 ]Department of Emergency Medicine, Highland Hospital–Alameda Health System, Oakland, California
                [3 ]Tuba City Regional Health Care Corporation, Tuba City, Arizona
                Article
                10.1001/jamainternmed.2019.6544
                6990860
                31961377
                7c625bde-66c4-4001-bf36-3972e462de73
                © 2020
                History

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