Clinical factors, including All Patient Refined Diagnosis Related Group severity, as predictors of early rehospitalization after COPD exacerbation

BACKGROUND Patients hospitalized for chronic obstructive pulmonary disease (COPD) exacerbations carry a high risk for early rehospitalization. We wished to identify the basic clinical factors associated with a high risk of rehospitalization, and to see how well the standardized All Patient Refined Diagnosis Related Group (APR-DRG) severity of illness (SOI) subclassification predicted rehospitalization if combined with other simple clinical measures. METHODS We identified adult patients aged ≥40 years discharged from a major hospital in the Southwestern USA with a COPD discharge diagnosis during the study index period (1 October 2009 to 30 September 2010). Patients readmitted within 30 days ("early rehospitalization") and 90 days ("any rehospitalization") were each compared with those not rehospitalized. Clinical parameters (including demographics, comorbidities) and recent healthcare utilization were examined for their association with rehospitalization. Factors independently associated with rehospitalization were then combined with the index admission APR-DRG SOI assessment using conditional linear regression to find the best models in terms of the highest C-statistic. RESULTS Among 306 patients hospitalized for COPD, 62 (20.3%) had a rehospitalization within 90 days and 28 (9.2%), an early readmission. An APR-DRG SOI subclassification ≥3 was a modest independent predictor of early or any readmission, with adjusted odds ratios ranging from 2.09 to 3.33. Models that combined the APR-DRG SOI subclassification with clinical factors present before the index hospitalization had strong C-statistics of ≥0.80. Good models without the APR-DRG SOI subclassification but including a history of recent hospitalizations before the index hospitalization were also identified. CONCLUSIONS An APR-DRG SOI subclassification of ≥3 for the index COPD admission is associated with an increased risk of early rehospitalizations, and can be combined with a few historical clinical factors to create strong predictive models for rehospitalization. This study demonstrates that hospitals can use commonly collected clinical information to help identify COPD patients at a high risk of failure after discharge.