Medication fill duration in pediatric hypertension: adherence, blood pressure control, and disparities.

BACKGROUND: Medication nonadherence is a barrier to hypertension control. The Centers for Disease Control and Prevention recommends prescribing 90-day fills for maintenance medications yet antihypertensives are often dispensed as 30-day fills. Our objectives were to examine how often patients receive 30-day supplies of medication despite prescriptions for longer duration and to examine the effect of medication fill duration on adherence and hypertension control. METHODS: We conducted a retrospective cohort study of pediatric patients with hypertension over a 3-year period. For each patient, days prescribed per fill were compared to days dispensed per fill using pharmacy reports and insurance claim data. Proportion of Days Covered (PDC) was calculated to estimate adherence. Hypertension control was determined by provider assessment of control and blood pressure measurement at the final visit. RESULTS: Final cohort included 449 patients. A total of 70% had at least one prescription for ≥ 90 days but only 37% had at least one dispense for ≥ 90 days. There was no difference in the likelihood of being prescribed a 90-day fill by insurance type (public vs. private); however, patients with public insurance were less likely to be dispensed a 90-day fill (OR = 0.068, p < 0.001). Patients who received 90-day fills had better adherence (median PDC 77.5% vs. 58.1%, p < 0.001) and were more likely to have hypertension control based on provider assessment. CONCLUSIONS: Longer fill duration is associated with improved adherence and hypertension control. Patients with public insurance are markedly less likely to be dispensed 90-day fills, a modifiable barrier to improving adherence.

Automated Screening to Enhance Proactive Consultation-Liaison Psychiatry Services in Acute Medicine Units: Evaluation of Service Outcomes.

Objective: Proactive consultation-liaison (C-L) psychiatry aims to meet the mental health needs of medical-surgical populations-many of which go unmet by the conventional C-L model-through systematic screening and integrated care. We implemented an automated screening list to enhance case identification of an existing proactive C-L service and evaluated service metrics along with clinician- and patient-reported outcomes.Methods: Service outcomes were evaluated using historical and contemporary comparison data. Adjusted difference-in-difference analyses were used to determine change in consult characteristics, mean length of stay (LOS), and scores on Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS). Practitioners and nurses were surveyed regarding service satisfaction, perceived safety, and burnout.Results: During the intervention, the consult rate was 3-fold higher than at baseline. Change in time to consultation was equivocal. Overall mean LOS was not reduced, but observed LOS was 1.2 days shorter than expected among non-COVID patients receiving psychiatric consultation (P = not significant). Mean patient-rated hospital satisfaction on HCAHPS was 1 point higher on intervention units during the intervention. Surveys revealed broad satisfaction with this model among practitioners and improved perception of safety among nurses.Conclusions: Proactive C-L psychiatry enhanced by automated screening was associated with improved service utilization and evidence suggestive of LOS reduction among those most likely to receive direct benefit from this model of care. Further, both patient and clinician ratings were improved during the intervention. Proactive C-L psychiatry provides benefits to patients, clinicians, and health systems and may be poised to achieve the Triple Aim in health care.Prim Care Companion CNS Disord 2024;26(2):23m03647. Author affiliations are listed at the end of this article.

Addressing Alert Fatigue by Replacing a Burdensome Interruptive Alert with Passive Clinical Decision Support.

BACKGROUND: Recognizing that alert fatigue poses risks to patient safety and clinician wellness, there is a growing emphasis on evaluation and governance of electronic health record clinical decision support (CDS). This is particularly critical for interruptive alerts to ensure that they achieve desired clinical outcomes while minimizing the burden on clinicians. This study describes an improvement effort to address a problematic interruptive alert intended to notify clinicians about patients needing coronavirus disease 2019 (COVID) precautions and how we collaborated with operational leaders to develop an alternative passive CDS system in acute care areas. OBJECTIVES: Our dual aim was to reduce the alert burden by redesigning the CDS to adhere to best practices for decision support while also improving the percent of admitted patients with symptoms of possible COVID who had appropriate and timely infection precautions orders. METHODS: Iterative changes to CDS design included adjustment to alert triggers and acknowledgment reasons and development of a noninterruptive rule-based order panel for acute care areas. Data on alert burden and appropriate precautions orders on symptomatic admitted patients were followed over time on run and attribute (p) and individuals-moving range control charts. RESULTS: At baseline, the COVID alert fired on average 8,206 times per week with an alert per encounter rate of 0.36. After our interventions, the alerts per week decreased to 1,449 and alerts per encounter to 0.07 equating to an 80% reduction for both metrics. Concurrently, the percentage of symptomatic admitted patients with COVID precautions ordered increased from 23 to 61% with a reduction in the mean time between COVID test and precautions orders from 19.7 to -1.3 minutes. CONCLUSION: CDS governance, partnering with operational stakeholders, and iterative design led to successful replacement of a frequently firing interruptive alert with less burdensome passive CDS that improved timely ordering of COVID precautions.

Using Discrete Form Data in the Electronic Medical Record to Predict the Likelihood of Psychiatric Consultation.

BACKGROUND: Manually screening for mental health needs in acute medical-surgical settings is thorough but time-intensive. Automated approaches to screening can enhance efficiency and reliability, but the predictive accuracy of automated screening remains largely unknown. OBJECTIVE: The aims of this project are to develop an automated screening list using discrete form data in the electronic medical record that identify medical inpatients with psychiatric needs and to evaluate its ability to predict the likelihood of psychiatric consultation. METHODS: An automated screening list was incorporated into an existing manual screening process for 1 year. Screening items were applied to the year's implementation data to determine whether they predicted consultation likelihood. Consultation likelihood was designated high, medium, or low. This prediction model was applied hospital-wide to characterize mental health needs. RESULTS: The screening items were derived from nursing screens, orders, and medication and diagnosis groupers. We excluded safety or suicide sitters from the model because all patients with sitters received psychiatric consultation. Area under the receiver operating characteristic curve for the regression model was 84%. The two most predictive items in the model were "3 or more psychiatric diagnoses" (odds ratio 15.7) and "prior suicide attempt" (odds ratio 4.7). The low likelihood category had a negative predictive value of 97.2%; the high likelihood category had a positive predictive value of 46.7%. CONCLUSIONS: Electronic medical record discrete data elements predict the likelihood of psychiatric consultation. Automated approaches to screening deserve further investigation.

Shaping the Future of Older Adult Care: ChatGPT, Advanced AI, and the Transformation of Clinical Practice.

As the older adult population in the United States grows, new approaches to managing and streamlining clinical work are needed to accommodate their increased demand for health care. Deep learning and generative artificial intelligence (AI) have the potential to transform how care is delivered and how clinicians practice in geriatrics. In this editorial, we explore the opportunities and limitations of these technologies.

A review of thrombotic microangiopathies in multiple myeloma.

Patients with multiple myeloma (MM) are susceptible to developing thrombotic microangiopathies (TMAs), an etiologically diverse group of syndromes which include atypical hemolytic uremic syndrome (aHUS) and thrombotic thrombocytopenic purpura (TTP). The TMAs are characterized by thrombocytopenia and microangiopathic hemolytic anemia (MAHA), and are associated with a high mortality risk and irreversible end-organ damage when treatment is delayed. In MM patients, TMAs may be triggered by specific chemotherapies, bone marrow transplantation (BMT), and progression of underlying disease. Because many characteristics of TMAs overlap with sequelae of MM and its treatments, diagnosis requires a high index of suspicion. Furthermore, our understanding of optimal treatments for these entities is rapidly evolving and clinical practice guidelines do not yet exist. Historically, consideration of a diagnosis of TMA has prompted initiation of therapeutic plasma exchange. In this review, we present an overview of the MM-related TMAs, an approach to workup and diagnosis, and argue for initial empiric MM-related TMA treatment with eculizumab rather than plasma exchange.

Acyldepsipeptide HDAC inhibitor production induced in Burkholderia thailandensis.

Natural product gene clusters are often tightly regulated, resulting in gene cluster silencing in laboratory fermentation studies. The systematic overexpression of transcription factors (TFs) associated with biosynthetic gene clusters found in the genome of Burkholderia thailandensis E264 identified a set of TFs that, when overexpressed, alter the secondary metabolome of this bacterium. The isolation and characterization of burkholdacs A and B, two new acyldepsitripeptide histone deacetylase inhibitors produced by B. thailandensis overexpressing the TF bhcM, is reported.