Shikhar Agarwal1, James M Pitcavage2, Karan Sud3, Badal Thakkar4. 1. Department of Cardiology, Section of Interventional Cardiology, Geisinger Medical Center, Danville, Pennsylvania. Electronic address: dr.shikhar.agarwal@gmail.com. 2. Institute for Advanced Application, Geisinger Health System, Danville, Pennsylvania. 3. Department of Internal Medicine, Mount Sinai St. Luke's Hospital, New York, New York. 4. Department of Internal Medicine, Rutgers New Jersey Medical School, Newark, New Jersey.
Abstract
BACKGROUND: Readmissions constitute a major health care burden among critical limb ischemia (CLI) patients. OBJECTIVES: This study aimed to determine the incidence of readmission and factors affecting readmission in CLI patients. METHODS: All adult hospitalizations with a diagnosis code for CLI were included from State Inpatient Databases from Florida (2009 to 2013), New York (2010 to 2013), and California (2009 to 2011). Data were merged with the directory available from the American Hospital Association to obtain detailed information on hospital-related characteristics. Geographic and routing analysis was performed to evaluate the effect of travel time to the hospital on readmission rate. RESULTS: Overall, 695,782 admissions from 212,241 patients were analyzed. Of these, 284,189 were admissions with a principal diagnosis of CLI (primary CLI admissions). All-cause readmission rates at 30 days and 6 months were 27.1% and 56.6%, respectively. The majority of these were unplanned readmissions. Unplanned readmission rates at 30 days and 6 months were 23.6% and 47.7%, respectively. The major predictors of 6-month unplanned readmissions included age, female sex, black/Hispanic race, prior amputation, Charlson comorbidity index, and need for home health care or rehabilitation facility upon discharge. Patients covered by private insurance were least likely to have a readmission compared with Medicaid/no insurance and Medicare populations. Travel time to the hospital was inversely associated with 6-month unplanned readmission rates. There was a significant interaction between travel time and major amputation as well as travel time and revascularization strategy; however, the inverse association between travel time and unplanned readmission rate was evident in all subgroups. Furthermore, length of stay during index hospitalization was directly associated with the likelihood of 6-month unplanned readmission (odds ratio for log-transformed length of stay: 2.39 [99% confidence interval: 2.31 to 2.47]). CONCLUSIONS: Readmission among patients with CLI is high, the majority of them being unplanned readmissions. Several demographic, clinical, and socioeconomic factors play important roles in predicting readmissions.
BACKGROUND: Readmissions constitute a major health care burden among critical limb ischemia (CLI) patients. OBJECTIVES: This study aimed to determine the incidence of readmission and factors affecting readmission in CLI patients. METHODS: All adult hospitalizations with a diagnosis code for CLI were included from State Inpatient Databases from Florida (2009 to 2013), New York (2010 to 2013), and California (2009 to 2011). Data were merged with the directory available from the American Hospital Association to obtain detailed information on hospital-related characteristics. Geographic and routing analysis was performed to evaluate the effect of travel time to the hospital on readmission rate. RESULTS: Overall, 695,782 admissions from 212,241 patients were analyzed. Of these, 284,189 were admissions with a principal diagnosis of CLI (primary CLI admissions). All-cause readmission rates at 30 days and 6 months were 27.1% and 56.6%, respectively. The majority of these were unplanned readmissions. Unplanned readmission rates at 30 days and 6 months were 23.6% and 47.7%, respectively. The major predictors of 6-month unplanned readmissions included age, female sex, black/Hispanic race, prior amputation, Charlson comorbidity index, and need for home health care or rehabilitation facility upon discharge. Patients covered by private insurance were least likely to have a readmission compared with Medicaid/no insurance and Medicare populations. Travel time to the hospital was inversely associated with 6-month unplanned readmission rates. There was a significant interaction between travel time and major amputation as well as travel time and revascularization strategy; however, the inverse association between travel time and unplanned readmission rate was evident in all subgroups. Furthermore, length of stay during index hospitalization was directly associated with the likelihood of 6-month unplanned readmission (odds ratio for log-transformed length of stay: 2.39 [99% confidence interval: 2.31 to 2.47]). CONCLUSIONS: Readmission among patients with CLI is high, the majority of them being unplanned readmissions. Several demographic, clinical, and socioeconomic factors play important roles in predicting readmissions.
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