Back

Association of Shared Care Networks with Heart Failure Excessive Hospital Readmissions

Pinheiro, D.; Hartman, R.; Mai, J.; Romero, E.; Soroya, S.; Bastos-Filho, C.; Lima, R.; Gibson, M.; Ebong, I.; Bidwell, J. T.; Nuno, M.; Cadeiras, M.

2021-04-07 health systems and quality improvement
10.1101/2021.04.07.21255061 medRxiv
Show abstract

STRUCTURED ABSTRACTO_ST_ABSObjectivesC_ST_ABSThis study aimed to evaluate the impact of shared care networks on heart failure readmission rates. BackgroundHigher-than-expected heart failure (HF) readmissions affect half of US hospitals every year. The Hospital Reduction Readmission Program (HRRP) has reduced risk-adjusted readmissions, but it has also produced unintended consequences. Shared care models have been advocated for HF care, but the association of shared care networks with HF readmissions has never been investigated. MethodsWe curated publicly available data on hospital discharges and HF excessive readmission ratios (ERRs) from hospitals in California between 2012 and 2017. Shared Care Areas (SCAs) were delineated as data-driven units of care coordination emerging from discharge networks. The localization index (LI), the proportion of patients who reside in the same SCA in which they are admitted, were calculated by year. Generalized estimating equations (GEE) were used to evaluate the association between the LI and the ERR of hospitals controlling for race/ethnicity and socioeconomics factors. ResultsA total of 300 hospitals in California in a 6-yr period were included. The HF excessive readmission ratio (ERR) was negatively associated with the localization index (beta: -0.0474; 95% CI: -0.082 to -0.013). The percentage of Black residents within the SCAs was the only statistically significant covariate (beta: 0.4128; 95% CI: 0.302 to 0.524). ConclusionsHigher-than-expected HF readmissions were associated with shared care networks. Control mechanisms such as the HRRP may need to characterize and reward shared care to guide hospitals towards a more organized HF care system.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.