The impact of automatic physician review of prescription drug monitoring program data on opioid prescribing in a Maryland statewide hospital system.

BACKGROUND AND AIMS: Prescription drug monitoring programs (PDMPs) were implemented to decrease dangerous opioid prescribing but have had variable results. This report details how automatic PDMP review changed opioid prescribing across a statewide medical system. DESIGN: An observational study. SETTING: Fourteen hospital networks in the United States. CASES: Healthcare encountered from July 1, 2016 to June 30, 2019. INTERVENTION: Starting from July 1, 2018, the patient's PDMP data would be displayed automatically to providers in the unified electronic medical record (EMR) whenever the provider began to write for an opioid prescription. MEASUREMENTS: Outcomes were prescriptions per encounter (PPE) and the morphine milligram equivalents (MME) per prescription. Outcomes were stratified by practice location, medication prescribed, and diagnosis. All data, including whether the prompt was triggered for a given encounter and whether a prescription was given, were extracted from the EMR. An interrupted timeseries analysis was used to determine how PPE and MME changed in response to the implementation of automatic PDMP review. FINDINGS: Of the 624,488 encounters examined, 18.37 percent (n = 114,710) were in emergency departments, 56.79 percent were admissions (n = 354,634), and 24.84 percent (n = 155,144) were outpatient visits. Opioid prescriptions were started and then canceled 24 percent of the time after the PDMP was shown. There was a decline in MME (ßOverall + Policy Trends = -3.17, p = <0.0001), which was driven by inpatient (ßOverall + Policy Trends = -2.10, p < 0.0001) and outpatient providers (ßOverall + Policy Trends = -3.24, p < 0.01). A decline in MME was seen in all medication categories (-1.72 < ßOverall + Policy Trends < -5.87, p < 0.01). There were no changes in these trends after excluding encounters for severe and acute pain. CONCLUSIONS: Automated PDMP review is associated with fewer prescriptions and smaller doses without decreasing appropriate use.

Utility of the History and Physical Examination in the Detection of Acute Coronary Syndromes in Emergency Department Patients.

Chest pain accounts for approximately 6% of all emergency department (ED) visits and is the most common reason for emergency hospital admission. One of the most serious diagnoses emergency physicians must consider is acute coronary syndrome (ACS). This is both common and serious, as ischemic heart disease remains the single biggest cause of death in the western world. The history and physical examination are cornerstones of our diagnostic approach in this patient group. Their importance is emphasized in guidelines, but there is little evidence to support their supposed association. The purpose of this article was to summarize the findings of recent investigations regarding the ability of various components of the history and physical examination to identify which patients presenting to the ED with chest pain require further investigation for possible ACS. Previous studies have consistently identified a number of factors that increase the probability of ACS. These include radiation of the pain, aggravation of the pain by exertion, vomiting, and diaphoresis. Traditional cardiac risk factors identified by the Framingham Heart Study are of limited diagnostic utility in the ED. Clinician gestalt has very low predictive ability, even in patients with a non-diagnostic electrocardiogram (ECG), and gestalt does not seem to be enhanced appreciably by clinical experience. The history and physical alone are unable to reduce a patient's risk of ACS to a generally acceptable level (<1%). Ultimately, our review of the evidence clearly demonstrates that "atypical" symptoms cannot rule out ACS, while "typical" symptoms cannot rule it in. Therefore, if a patient has symptoms that are compatible with ACS and an alternative cause cannot be identified, clinicians must strongly consider the need for further investigation with ECG and troponin measurement.