High-density lipoprotein (HDL) as an indicator for alcohol use in a psychiatrically ill population.

AIMS: To examine the cross sectional and longitudinal associations between the Alcohol Use Disorders Identification Test-Concise (AUDIT-C) and differences in high-density lipoprotein (HDL) in a psychiatrically ill population. METHODS: Retrospective observational study using electronic health record data from a large healthcare system, of patients hospitalized for a mental health/substance use disorder (MH/SUD) from 1 July 2016 to 31 May 2023, who had a proximal AUDIT-C and HDL (N = 15 915) and the subset who had a repeat AUDIT-C and HDL 1 year later (N = 2915). Linear regression models examined the association between cross-sectional and longitudinal AUDIT-C scores and HDL, adjusting for demographic and clinical characteristics that affect HDL. RESULTS: Compared with AUDIT-C score = 0, HDL was higher among patients with greater AUDIT-C severity (e.g. moderate AUDIT-C score = 8.70[7.65, 9.75] mg/dl; severe AUDIT-C score = 13.02 [12.13, 13.90] mg/dL[95% confidence interval (CI)] mg/dl). The associations between cross-sectional HDL and AUDIT-C scores were similar with and without adjusting for patient demographic and clinical characteristics. HDL levels increased for patients with mild alcohol use at baseline and moderate or severe alcohol use at follow-up (15.06[2.77, 27.69] and 19.58[2.77, 36.39] mg/dL[95%CI] increase for moderate and severe, respectively). CONCLUSIONS: HDL levels correlate with AUDIT-C scores among patients with MH/SUD. Longitudinally, there were some (but not consistent) increases in HDL associated with increases in AUDIT-C. The increases were within range of typical year-to-year variation in HDL across the population independent of alcohol use, limiting the ability to use HDL as a longitudinal clinical indicator for alcohol use in routine care.

Use of complete medication history to identify and correct transitions-of-care medication errors at psychiatric hospital admission.

Methods for categorizing the scale and severity of medication errors corrected by pharmacy staff during admission medication reconciliation using complete medication history continue to evolve. We established a rating scale that is effective for generating error reports to health system quality leadership. These reports are needed to quantify the value of investment in transitions-of-care pharmacy staff. All medication errors that were reported by pharmacy staff in the admission medication reconciliation process during a period of 6 months were eligible for inclusion. Complete medication history data source was utilized by admitting providers and all pharmacist staff and a novel medication error scoring methodology was developed. This methodology included: medication error category, medication error type, potential medication error severity, and medication non-adherence. We determined that 82 medication errors were detected from 72 patients and assessed that 74 of these errors may have harmed patients if they were not corrected through pharmacist intervention. Most of these errors were dosage discrepancies and omissions. With hospital system budgets continually becoming leaner, it is important to measure the effectiveness and value of staff resources to optimize patient care. Pharmacists performing admission medication reconciliation can detect subtle medication discrepancies that may be overlooked by other clinician types. This methodology can serve as a foundation for error reporting and predicting the severity of adverse drug events.