Addressing Hospital Readmissions: Impact of Weekly Review.

BACKGROUND AND OBJECTIVES: The prevention of hospital readmissions has become an area for improvement for most health care organizations. Systematic reviews have been unable to identify a single intervention or bundle of interventions that reliably reduced risk of readmission in a generalizable manner. The aim of this quality improvement project was to examine the readmission rate to a family medicine residency program inpatient service following the implementation of a once per week session that reviewed patients who were readmitted during the prior week. METHODS: The inpatient admissions and readmission to the family medicine inpatient service associated with a large academic health center were used for analysis. The impact of a regularly scheduled multidisciplinary team meeting that reviewed a list of patients was examined. Readmitted patients who were at high risk for readmission were specifically identified. Descriptive statistics were used to characterize and summarize the integral data obtained. The weekly readmission rate was presented using a control chart. RESULTS: The readmission rate for the patients hospitalized after the intervention was 18.4%, compared to the readmission rate prior to the intervention (23.0%). While not a statistically different rate, a significant signal was noted. Demographic differences were noted in the group of patients considered to be high risk for readmission. CONCLUSIONS: Regular rounds of an inpatient team that focuses on readmissions during the previous week reduced hospital readmissions. The impact of these sessions appears to be multifactorial.

Preoperative assessment of the risk for multiple complications after surgery.

BACKGROUND: The association between preoperative patient characteristics and the number of major postoperative complications after a major operation is not well defined. METHODS: In a retrospective, single-center cohort of 50,314 adult surgical patients, we used readily available preoperative clinical data to model the number of major postoperative complications from none to ≥3. We included acute kidney injury; prolonged stay (>48 hours) in an intensive care unit; need for prolonged (>48 hours) mechanical ventilation; severe sepsis; and cardiovascular, wound, and neurologic complications. Risk probability scores generated from the multinomial logistic models were used to develop an online calculator. We stratified patients based on their risk of having ≥3 postoperative complications. RESULTS: Patients older than 65 years (odds ratio 1.5, 95% confidence interval, 1.4-1.6), males (odds ratio 1.2, 95% confidence interval, 1.2-1.3), patients with a greater Charlson comorbidity index (odds ratio 3.9, 95% confidence interval, 3.6-4.2), patients requiring emergency operation (odds ratio 3.5, 95% confidence interval, 3.3.-3.7), and patients admitted on a weekend (odds ratio 1.4, 95% confidence interval, 1.3-1.5) were more likely to have ≥3 postoperative complications than they were to have none. Patients in the medium- and high-risk categories were 3.7 and 6.3 times more likely to have ≥3 postoperative complications, respectively. High-risk patients were 5.8 and 4.4 times more likely to die within 30 and 90 days of admission, respectively. CONCLUSION: Readily available, preoperative clinical and sociodemographic factors are associated with a greater number of postoperative complications and adverse surgical outcomes. We developed an online calculator that predicts probability of developing each number of complications after a major operation.