Access to clinically-detailed patient information: a fundamental element for improving the efficiency and quality of healthcare.

Although we also value service and ethical aspects of healthcare provision, the main reason we tolerate spending $2 trillion annually on healthcare (almost $7000 per person)1 is with the hope that the care we receive will improve the quality and length of our lives. Given the overwhelming evidence that much of healthcare spending is wasteful and that quality problems are pervasive, it is more than sensible to demand greater accountability from providers, and what better way than to directly assess the outcomes in which we are most interested, such as risk-adjusted mortality. As early as the 1910s, E. A. Codman called for just such accountability.2 Although his ideas were largely ignored for many years, since the 1980s there have been repeated attempts to implement risk-adjusted outcomes as accountability measures, with improving the completeness and affordability of case-mix adjustment widely being seen as the key to success. In this issue of Medical Care, Escobar et al3 report on how integrating automated data across medical information systems can produce a risk-adjustment tool for hospital mortality that is inexpensive and highly predictive. This work builds on that by Render et al4 and provides a case-mix tool that has substantial implications for quality monitoring and improvement, and is likely to also be a valuable research tool. However, performance measurement leaders would be wise to heed the authors' warning3 sample size limitations usually limit the accuracy of risk-adjusted mortality rates as an accountability measure even if perfect case-mix was obtainable,5"6 something that is easily overlooked unless statistical methods that adjust for measurement error are used.7'8 In addition, even an impressive prediction tool, like that developed by the authors, has been shown in past research to be unable to reliably account for high levels of patient selection (ie, that often seen at referral centers or in transfer patients). 9 However, risk-adjusted outcome rates have proved to be extremely valuable in cooperative quality improvement (QI) programs in which members are required to disclose and discuss their outcomes and are encouraged to learn from others in the program. Such programs have been very successful where implemented101 ! ; however, the dissemination of such programs has often been limited by the resources, time, and costs of obtaining the clinical data needed for legitimate case-mix adjustment. The work by investigators like Escobar et al, Render et al, and others, however, has implications well beyond risk-adjusted mortality rates. This research is just one of many examples of how effective administrative initiatives to improve the efficiency and quality of health care usually require access to clinically-detailed medical information. Kerr and colleagues have demonstrated how linking multiple automated data sources in an integrated healthcare system can greatly improve the accuracy of and clinical insights into processes and appropriateness of care, such as the appropriateness of intensification of blood pressure and lipid therapies.12 Further work has demonstrated how more comprehensive, clinically-detailed chart-based quality measurement tools can be used to effec-