“It’s like comparing champagne with cognac. No — with coca-cola.” Maria Callas
One of the most important lessons learned during the 1990s is that appropriate risk-adjustment must be context specific.
Dr Iezzoni indicates that devising appropriate risk-adjustment strategies requires answers to four major questions:
Risk of what outcome?
Over what time frame?
For what population?
For what purpose?
The authors of this third edition about the risk-adjustment of healthcare data frequently return to these questions in their discussions of conceptual, methodological, and applications issues.
Among the topics addressed in the book are: specific patient-level characteristics used in risk-adjustment models (e.g. demographic, clinical, functional); windows of observation for risk adjustment (e.g. hospitalization, episode, fixed time period); data sources for developing, validating, and applying risk-adjustment models (e.g. administrative data, medical records, surveys); statistical and conceptual issues related to model development and validation; methodological issues related to application of risk models, including comparison of outcomes across providers; and risk-adjustment issues specific to four populations: pediatric patients, mental health patients, long-term care patients, and people with disabilities.
Although the topics addressed can be quite technical, the authors steer clear of the use of clinical and statistical jargon, and they make the text readable and understandable for people from a variety of backgrounds.
I also applaud the inclusion of historical references to Florence Nightingale and Ernest Codman (to mention just a couple). They remind the reader that over time ideas have been posited and rejected, only to come back around again to a more receptive (wiser?) audience.