Avoidable hospital readmissions may be reflective of poor quality of inpatient healthcare and may be used as a metric to guide reimbursement rates to hospitals. Most existing risk prediction models rely on administrative databases and have poor predictive ability. Physician chart reviews are necessary to identify both the cause and preventability of a readmission.
We performed a retrospective chart review of 135 patients with an unplanned readmission to Bellevue Hospital within 7 days of discharge from the medicine service during a six month period. Each chart was reviewed independently by two experienced attending physicians. Using an algorithm developed via a pilot study, each readmission was classified into one of five categories: (1) not medically necessary (medical necessity), (2) following a discharge against medical advice (AMA), (3) related to a deficiency in the discharge process, (4) related to poor patient adherence (patient behavior) to the discharge plan, or (5) related to a condition that was difficult to predict. The latter three categories were further subcategorized to allow for more detailed analysis. Discrepancies in classification were resolved by consensus of the four authors. Baseline demographic information was obtained for the same time frame for patients who were not readmitted within 7 days.
During the study period there were 265 patients who were readmitted within seven days of discharge and 3,411 patients who were not. The gender ratio was not significantly different between groups (65% male in the readmitted group versus 62% male in the not readmitted group, P = 0.47). Age was significantly lower in the readmitted group (mean = 52.9 years) as compared to the not readmitted group (56.3; P = 0.001). Median length of stay (LOS) for the initial hospitalization was longer in the readmitted group (5 days vs 3 days; P = 0.0002). For the 135 readmitted cases, there was good agreement between reviewers (84%; k 0.776). The most common category of readmission was “unpredictable” (37.8%), followed by patient behavior (22.2%), discharge process (21.5%), medical necessity (9.6%), and AMA (8.9%).
Our novel algorithm efficiently and reproducibly classified 7day readmissions into discreet categories. Compared to all other patients, those who were readmitted within 7 days were more likely to be younger and have a longer initial LOS. We found 62% of readmissions were attributable to physician or patient behaviors, or system failures. This categorization algorithm can be used to guide creation of risk prediction models and allows for detailed analysis of individual groups that will assist development of individualized interventions to reduce rates of avoidable readmissions.
Table 1Characteristics of Patients Readmitted Within 7 Days
Table 2Characteristics of Patients Readmitted Within 7 Days by Category
To cite this abstract:Burke D, Bails D, Janjigian M, Link N. Factors Contributing to 7Day Readmissions in an Urban Teaching Hospital. Abstract published at Hospital Medicine 2012, April 1-4, San Diego, Calif. Abstract 97594. Journal of Hospital Medicine. 2012; 7 (suppl 2). https://www.shmabstracts.com/abstract/factors-contributing-to-7day-readmissions-in-an-urban-teaching-hospital/. Accessed May 26, 2019.