Readmissions to hospital – Interpretive notes

Updated as of January 22, 2016

• This indicator has been risk adjusted for age, sex and co-morbidities. Risk adjustment takes into account the differences among patient populations to allow for fairer comparisons between your patients and other populations. Risk adjusted data are easier and more meaningful to compare between teams. However, unadjusted data may provide an estimate that better reflects what is actually happening in your team and thus might help guide local improvement efforts.
• The readmission rate for a primary care organization is based on the experience of patients on the roster of that organization AND patients who are considered to be “virtually” rostered according to MOHLTC methodology. Virtual rostering assigns patients to the primary care physician that provided the highest dollar amount of services within a defined set of primary care services. Primary care organizations may not be aware that patients have been “virtually” rostered to them and thus might think the data related to these patients are erroneously attributed to their team (i.e. “they are not ‘our’ patients”). Hence, your team’s sense of how many readmissions should be attributed to the team may be different than the rate shown in D2D.
• The data refer to hospitalization and readmissions that happened 1.5 years ago (on average) because they are based on hospital data submitted to CIHI 2-6 months after discharge (on average), after which they must be compiled and validated prior to release for reporting purposes.
• The current definition may under-estimate actual readmission rates for patients who have preventable readmissions because the denominator includes ALL patients who were hospitalized for any reason.
  • Readmissions may appear to be lower for teams with a higher proportion of child-bearing women because childbirth is one of the most common reasons for hospitalization and thus will increase the denominator, artificially decreasing the overall rate of readmissions.
  • The same is true for teams with high proportions of young, healthy patients needing elective surgeries, which are not nearly as common as birth as a reason for hospitalization, but still would reduce the overall readmissions rate because readmissions in such situations are rare.
• Many primary care providers do not get timely information about recent hospitalizations of their patients. Teams who do not know if their patients have recently been in hospital may therefore have higher readmission rates than teams with timely access to data, who are better able to engage with patients and other providers to prevent readmissions.
• There are many challenges in preventing readmissions, not all of which are solely under the control of primary care providers such as premature discharge from hospital and the natural progression of chronic conditions. Consider the possible impact of these factors on your team’s readmission rates.