Unintended Consequences of Centralization? Increased Care Fragmentation and Subsequent Mortality after Complex Cancer Surgery

Association of hospital centrality in inter-hospital patient-sharing networks with patient mortality and length of stay

OBJECTIVE

The interdependence of hospitals is underappreciated in patient outcomes studies. We used a network science approach to foreground this interdependence. Specifically, within two large state-based interhospital networks, we examined the relationship of a hospital's network position with in-hospital mortality and length of stay.

METHODS

We constructed interhospital network graphs using data from the Healthcare Cost and Utilization Project and the American Hospital Association Annual Survey for Florida (2014) and California (2011). The exposure of interest was hospital centrality, defined as weighted degree (sum of all ties to a given hospital from other hospitals). The outcomes were in-hospital mortality and length of stay with sub-analyses for four acute medical conditions: pneumonia, heart failure, ischemic stroke, myocardial infarction. We compared outcomes for each quartile of hospital centrality relative to the most central quartile (Q4), independent of patient- and hospital-level characteristics, in this retrospective cross-sectional study.

RESULTS

The inpatient cohorts had 1,246,169 patients in Florida and 1,415,728 in California. Compared to Florida's central hospitals which had an overall mortality 1.60%, peripheral hospitals had higher in-hospital mortality (1.97%, adjusted OR (95%CI): Q1 1.61 (1.37, 1.89), p<0.001). Hospitals in the middle quartiles had lower in-hospital mortality compared to central hospitals (%, adjusted OR (95% CI): Q2 1.39%, 0.79 (0.70, 0.89), p<0.001; Q3 1.33%, 0.78 (0.70, 0.87), p<0.001). Peripheral hospitals had longer lengths of stay (adjusted incidence rate ratio (95% CI): Q1 2.47 (2.44, 2.50), p<0.001). These findings were replicated in California, and in patients with heart failure and pneumonia in Florida. These results show a u-shaped distribution of outcomes based on hospital network centrality quartile.

CONCLUSIONS

The position of hospitals within an inter-hospital network is associated with patient outcomes. Specifically, hospitals located in the peripheral or central positions may be most vulnerable to diminished quality outcomes due to the network. Results should be replicated with deeper clinical data.

Fragmentation of Care in Pancreatic Cancer: Effects on Receipt of Care and Survival

BACKGROUND

The impact of fragmentation of care (FC), i.e., receipt of care at > 1 institution, on treatment of pancreatic cancer is unknown. The purpose of this study was to determine factors associated with FC in curative-intent treatment of pancreatic cancer (PDAC) patients and evaluate how FC affects survival outcomes.

METHODS

Using the National Cancer Database (NCDB), data on stage I-III PDAC patients diagnosed 2006-2016 were extracted. Multiple logistic regression analyses were performed to identify factors predictive of FC and survival.

RESULTS

Of the 20,013 patients identified, 24.1% had FC. Factors predictive of FC were stage-III tumors (odds ratio [OR] 1.36; p = 0.014), higher median-income [third quartile (OR 1.38; p = 0.006) and highest-quartile (OR 1.50; p = 0.003)], care at high-volume facility (OR 1.47; p < 0.001), and receipt of multi-modal therapy (OR 1.69; p < 0.001). In contrast, age > 80 years (OR 0.82; p = 0.018), Black (OR 0.85; p = 0.013) or Asian race (OR 0.76; p = 0.033), Charlson comorbidity-index 2 (OR 0.85; p = 0.033), treatment at non-academic facility (OR 0.87; p = 0.041), and non-private insurance were negatively predictive of FC. FC independently predicted decreased 30-day [OR 0.57; p < 0.001] and 90-day mortality [OR 0.61; p < 0.001] and improved overall survival [hazard ratio 0.91; p < 0.001].

DISCUSSION

Sociodemographic factors are significantly associated with FC in curative-intent treatment of PDAC patients. FC was found to predict improved 30-day, 90-day, and overall survival outcomes.