Impact of automated alerts on discharge opioid overprescribing after general surgery.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: The objectives of this study were to identify the most performed surgical procedures associated with the highest rates of discharge opioid overprescribing and to implement an electronic health record (EHR) alert to reduce discharge opioid overprescribing. METHODS: This quality improvement, before-and-after study included patients undergoing one of the identified target procedures-laparoscopic cholecystectomy, unilateral open inguinal hernia repair, and laparoscopic appendectomy-at an academic medical center. The alert notified providers when the prescribed opioid quantity exceeded guideline recommendations. The preimplementation cohort included surgical encounters from January 2020 to December 2021. The EHR alert was implemented in May 2022 following provider education via email and in-person presentations. The postimplementation cohort included surgical encounters from May to August 2022. The primary outcome was the proportion of patients with a discharge opioid supply exceeding guideline recommendations (overprescribing). RESULTS: A total of 1,478 patients were included in the preimplementation cohort, and 141 patients were included in the postimplementation cohort. The rate of discharge opioid overprescribing decreased from 48% in the preimplementation cohort to 3% in the postimplementation cohort, with an unadjusted absolute reduction of 45% (95% confidence interval, 41% to 49%; P < 0.001) and an adjusted odds ratio of 0.03 (95% confidence interval, 0.01 to 0.08; P < 0.001). Among patients who received opioids, the mean (SD) opioid supply at discharge decreased from 92 (43) oral morphine milligram equivalents (MME) (before implementation) to 57 (20) MME (after implementation) (P < 0.001). The proportion of patients who received additional opioid prescriptions within 1 to 14 days of hospital discharge did not change (P = 0.76). CONCLUSION: Implementation of an EHR alert along with provider education can reduce discharge opioid overprescribing following general surgery.

Clinic-based interventions to increase preexposure prophylaxis awareness and uptake among United States patients attending an obstetrics and gynecology clinic in Baltimore, Maryland.

BACKGROUND: Cisgender women account for 1 of every 5 new US HIV diagnoses, with most cases (85%) attributed to heterosexual contact. HIV preexposure prophylaxis is an effective prevention strategy; however, preexposure prophylaxis awareness and prescriptions among women are low. OBJECTIVE: This study aimed to increase preexposure prophylaxis counseling and uptake among cisgender women attending obstetrics and gynecology clinics. STUDY DESIGN: The study included 3 obstetrics and gynecology clinics within a single health system in a high HIV prevalence region. There were 3 phases: baseline (the 3-month period before the clinical trial that included provider education and training of a registered nurse about preexposure prophylaxis), clinical trial (the 3-month period during which eligible patients were randomized to an active control or preexposure prophylaxis registered nurse intervention), and maintenance (the 3-month period after the trial ended). Electronic medical record clinical decision support tools were available to both arms during the clinical trial, which included best practice alerts, order sets, progress note templates, and written and video preexposure prophylaxis educational materials for patients. In the intervention arm, a preexposure prophylaxis nurse contacted and counseled patients and was equipped to prescribe preexposure prophylaxis. Moreover, this study evaluated the phases through the "reach, effectiveness, adoption, implementation, and maintenance" framework. The primary outcome of the study was effectiveness (eg, percentage of eligible patients with documented HIV prevention counseling in the electronic medical record or preexposure prophylaxis prescriptions). The secondary outcomes included reach (eg, percentage of best practice alerts that providers acted on or the percentage of eligible patients who spoke with the preexposure prophylaxis registered nurse), adoption (eg, percentage of eligible patients with a best practice alert that triggered or the percentage of eligible patients the preexposure prophylaxis registered nurse attempted to contact), and maintenance (eg, percentage of patients with documented HIV prevention counseling or preexposure prophylaxis prescriptions during the maintenance phase). RESULTS: There were 904 unique patients in all phases with a mean age of 28.8±7.7 years, and 416 patients (46%) were pregnant; moreover, 436 patients were randomized in the clinical trial phase. Concerning reach and adoption, best practice alerts were triggered for 100% of eligible encounters; however, the providers acted on 52% of them. The preexposure prophylaxis nurse attempted to contact every patient and successfully spoke with 81.2% of them in the preexposure prophylaxis registered nurse arm. Concerning effectiveness, there were significantly more patients counseled about preexposure prophylaxis in the preexposure prophylaxis registered nurse group than in the active control group (66.5% vs 12.3%, respectively; P<.001), although preexposure prophylaxis prescriptions were equivalent (P=1.0). Among the subgroup of patients who were counseled about preexposure prophylaxis, 18.5% of patients in the active control arm and 3.4% in the preexposure prophylaxis registered nurse arm were prescribed preexposure prophylaxis (P=.02). Concerning maintenance, clinical decision support tools alone resulted in preexposure prophylaxis counseling of 1.0% of patients during the maintenance phase vs 0.6% of patients during the baseline phase and 11.2% of patients during the clinical trial phase (P<.001). Preexposure prophylaxis prescriptions were not statistically different among the 3 phases (P=.096). CONCLUSION: A preexposure prophylaxis nurse effectively increased HIV prevention discussions but did not lead to more preexposure prophylaxis prescriptions than the preexposure prophylaxis-focused clinical decision support tools used by providers. The decrease in preexposure prophylaxis counseling after the trial phase suggests that persistent interventions are needed to maintain effects.

Leveraging clinical decision support tools to improve guideline-directed medical therapy in patients with atherosclerotic cardiovascular disease at hospital discharge.

BACKGROUND: Guidelines recommend moderate to high-intensity statins and antithrombotic agents in patients with atherosclerotic cardiovascular disease (ASCVD). However, guideline-directed medical therapy (GDMT) remains suboptimal. METHODS: In this quality initiative, best practice alerts (BPA) in the electronic health record (EHR) were utilized to alert providers to prescribe to GDMT upon hospital discharge in ASCVD patients. Rates of GDMT were compared for 5 months pre- and post-BPA implementation. Multivariable regression was used to identify predictors of GDMT. RESULTS: In 5985 pre- and 5568 post-BPA patients, the average age was 69.1 ± 12.8 years and 58.5% were male. There was a 4.0% increase in statin use from 67.3% to 71.3% and a 3.1% increase in antithrombotic use from 75.3% to 78.4% in the post-BPA cohort. CONCLUSIONS: This simple EHR-based initiative was associated with a modest increase in ASCVD patients being discharged on GDMT. Leveraging clinical decision support tools provides an opportunity to influence provider behavior and improve care for ASCVD patients, and warrants further investigation.

Implementing Pharmacogenomics Testing: Single Center Experience at Arkansas Children's Hospital.

Pharmacogenomics (PGx) is a growing field within precision medicine. Testing can help predict adverse events and sub-therapeutic response risks of certain medications. To date, the US FDA lists over 280 drugs which provide biomarker-based dosing guidance for adults and children. At Arkansas Children's Hospital (ACH), a clinical PGx laboratory-based test was developed and implemented to provide guidance on 66 pediatric medications for genotype-guided dosing. This PGx test consists of 174 single nucleotide polymorphisms (SNPs) targeting 23 clinically actionable PGx genes or gene variants. Individual genotypes are processed to provide per-gene discrete results in star-allele and phenotype format. These results are then integrated into EPIC- EHR. Genomic indicators built into EPIC-EHR provide the source for clinical decision support (CDS) for clinicians, providing genotype-guided dosing.

Advances and required improvements in methods to diagnosing Clostridioides difficile infections in the healthcare setting.

INTRODUCTION: Clostrididioides difficile is associated with adverse clinical outcomes and increased morbidity, mortality, length of hospital stay, and health-care costs.Areas Covered: We searched relevant papers in PubMed for the last 10 years. In major papers, we scanned the bibliographies to ensure that important articles were included. This review addresses the evolving epidemiology of Clostridioides difficile infection (CDI) and discusses novel methods/approaches for improving the diagnosis of this important disease. EXPERT OPINION: No single diagnostic test to date has demonstrated optimum sensitivity and specificity for detection of CDI. Many institutions have developed multi-step algorithms consistent with guidelines established by various professional societies. Some institutions have successfully tried to improve the pretest probability of molecular assays by implementing appropriate sample rejection criteria and establishing best practice alerts at the time of electronic order entry. Others have established PCR cycle threshold cutoffs to attempt to differentiate symptomatic patients from asymptomatic carriers or to make predictions about severity of disease with variable success. As research advances our understanding of C. difficile pathogenesis and pathophysiology, more information on CDI specific biomarkers is emerging. Finally, assessments of the microbiome and metabolome may expand the diagnostic armamentarium with advances in mass spectrometry and sequencing technologies.

To act or not to act: responses to electronic health record prompts by family medicine clinicians.

Objective: A major focus of health care today is a strong emphasis on improving the health and quality of care for entire patient populations. One common approach utilizes electronic clinical alerts to prompt clinicians when certain interventions are due for individual patients being seen. However, these alerts have not been consistently effective, particularly for less visible (though important) conditions such as hearing loss (HL) screening. Materials and Methods: We conducted hour-long cognitive task analysis interviews to explore how family medicine clinicians view, perceive, and use electronic clinical alerts, and to utilize this information to design a more effective alert using HL identification and referral as a model diagnosis. Results: Four key direct barriers were identified that impeded alert use: poor standardization and formatting, time pressures in primary care, clinic workflow variations, and mental models of the condition being prompted (in this case, HL). One indirect barrier was identified: electronic health record and institution/government regulations. We identified that clinicians' mental model of the condition being prompted was probably the major barrier, though this was often expressed as time pressure. We discuss solutions to each of the 5 identified barriers, such as addressing physicians' mental models, by focusing on physicians' expertise rather than knowledge to improve their comfort when caring for patients with the conditions being prompted. Conclusions: To unleash the potential of electronic clinical alerts, electronic health record and health care institutions need to address some key barriers. We outline these barriers and propose solutions.