ABSTRACT
BACKGROUND: Hospitals have sought to increase pre-noon discharges to improve capacity, although evidence is mixed on the impact of these initiatives. Past interventions have not quantified the daily gap between morning bed supply and demand. The authors quantified this gap and applied the pre-noon data to target a pre-noon discharge initiative. METHODS: The study was conducted at a large hospital and included adult and pediatric medical/surgical wards. The researchers calculated the difference between the average cumulative bed requests and transfers in for each hour of the day in 2018, the year prior to the intervention. In 2019 an intervention on six adult general medical and two surgical wards was implemented. Eight intervention and 14 nonintervention wards were compared to determine the change in average cumulative pre-noon discharges. The change in average hospital length of stay (LOS) and 30-day readmissions was also calculated. RESULTS: The average daily cumulative gap by noon between bed supply and demand across all general care wards was 32.1 beds (per ward average, 1.3 beds). On intervention wards, mean pre-noon discharges increased from 4.7 to 6.7 (p < 0.0000) compared with the nonintervention wards 14.0 vs. 14.6 (pâ¯=â¯0.19877). On intervention wards, average LOS decreased from 6.9 to 6.4 days (p < 0.001) and readmission rates were 14.3% vs 13.9% (pâ¯=â¯0.3490). CONCLUSION: The gap between daily hospital bed supply and demand can be quantified and applied to create pre-noon discharge targets. In an intervention using these targets, researchers observed an increase in morning discharges, a decrease in LOS, and no significant change in readmissions.
Subject(s)
Patient Discharge , Patient Readmission , Adult , Humans , Child , Length of Stay , Equipment and Supplies, Hospital , HospitalsABSTRACT
PURPOSE: Obtaining an accurate medication history is a vital component of medication reconciliation upon admission to the hospital. Despite the importance of this task, medication histories are often inaccurate and/or incomplete. We evaluated the association of a pharmacy-driven medication history initiative on clinical outcomes of patients admitted to the general medicine service of an academic medical center. METHODS: Comparing patients who received a pharmacy-driven medication history to those who did not, a retrospective stabilized inverse probability treatment weighting propensity score analysis was used to estimate the average treatment effect of the intervention on general medical patients. Fifty-two patient baseline characteristics including demographic, operational, and clinical variables were controlled in the propensity score model. Hospital length of stay, 7-day and 30-day unplanned readmissions, and in-hospital mortality were evaluated. RESULTS: Among 11,576 eligible general medical patients, 2,234 (19.30%) received a pharmacy-driven medication history and 9,342 (80.70%) patients did not. The estimated average treatment effect of receiving a pharmacy-driven medication history was a shorter length of stay (mean, 5.88 days vs 6.53 days; P = 0.0002) and a lower in-hospital mortality rate (2.34% vs 3.72%, P = 0.001), after adjustment for differences in patient baseline characteristics. No significant difference was found for 7-day or 30-day all-cause readmission rates. CONCLUSION: Pharmacy-driven medication histories reduced length of stay and in-hospital mortality in patients admitted to the general medical service at an academic medical center but did not change 7-day and 30-day all-cause readmission rates. Further research via a large, multisite randomized controlled trial is needed to confirm our findings.
