Int J Qual Health Care-2001-Rubin-469-74

In addition existing risk adjustment models often

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: databases at present, that may not be part of medical records, and that may be expensive to collect. In addition, existing risk adjustment models often perform poorly when applied to new data sets, limiting application of a common risk adjustment model to all providers [19,20]. The development of new risk adjustment models is analytically complex, requiring expert statistical analytical resources and a large sample of patients available for the development process. Using process measures applied to an accurately defined population avoids some of the time and expense that risk adjustment entails. Process-based measures of health care quality Table 1 Advantages and disadvantages: comparison of process and outcome measures Process measures Outcome measures ......................................................................................................................................................................................................................................... Resources Need for updating and maintenance of measures Need for development of risk adjustment models and collection of risk data Time needed for measurement Size of population needed for measurement Need for additional follow-up tracking of patients for later data collection Use of routinely collected data Need for advanced statistical consultation for development of measures and analysis of data Require updating and maintenance of guidelines, review criteria, instruments and software according to advances in treatment Most measures do not require the use of extensive risk adjustment models; however, require good definition of eligible patients Takes less time to accumulate, smaller sample needed, less observation time needed for processes occurring during provider contact Can use a smaller sample size as all included patients experience the process and once eligible patients are defined, only descriptive statistics are needed Data collection can be done when clinical process is occurring Has the potential to be abstracted from data already recorded for clinical and administrative use, and ultimately to be completely integrated into such data collection Not needed in general Known risk factors and models may require some updating, generally less often than updates to process measures are needed Risk adjustment is difficult; need different models for each outcome Due to need for risk adjustment a larger sample is needed; also many outcomes of interest are long-te...
View Full Document

Ask a homework question - tutors are online