Have I mentioned that CMS’ hospital readmission penalty program is really based on poor data and ideology? Getting some basic data on readmissions might help with reform of that program. The latest data dump is at the Public Library of Science and involves a large study of readmission characteristics. (PLOS Article) The authors looked at adult readmissions from 2013 in 21 states in a readmissions database. They primarily were interested in type of insurance and patient characteristics. The researchers had access to data on age, insurance status, and clinical variables like primary diagnoses, primary reason for hospitalization and procedures performed during hospitalization. The primary outcome was 30-day all cause readmission. Medicare patients accounted for 56% of all readmissions, private insurance for 18.3%, Medicaid for 15% and self-pay for 4.8%. Given the relative size of coverage sources, Medicare obviously has a disproportionate number of readmissions, with a 17.5% unadjusted rate, followed by Medicaid at 15%, self-pay at 14% and private insurance, although it covers the most people, at only 9.6%. Older people also, as expected, had much higher readmission rates.
The most common diagnoses associated with a subsequent readmission are septicemia, heart failure, cellulite, and dysrhythmias. For adults in the 18-64 age brackets, conditions like complications of pregnancy or mental illness accounted for many hospitalizations. An estimated $51 billion was spent on readmissions in 2013, $29.6 billion was paid by Medicare. So it is understandable why people are concerned. But given the age and/or disease history of most of the people, it is not surprising that they were readmitted and I am not sure what could reasonably done by a hospital to prevent the readmission. Should we keep people from being readmitted for mental illness or substance abuse? Dual eligibles have particularly high rates of readmission, which the authors suggest is likely due to socioeconomic and general life approach issues. What are hospitals supposed to do about those? There are certainly avoidable readmissions, but blanket calculations of supposed acceptable rates of readmission don’t capture their complexity. I keep suggesting that a better alternative is to examine each readmission and determine whether it was appropriate.