Monday, February 13, 2012

Healthcare Outcomes and Business Analytics

In 2001, the Institute of Medicine (IOM), an arm of the US National Academy of Sciences, released a report detailing the many failings of health care provision in the US, and laying out a plan to fix health care. The plan was to become more proactive and less reactive in engaging patients and families to manage their healthcare, improving the overall health of the population, improving the safety and reliability of the healthcare system, coordinating patient care amongst multiple agencies, delivering palliative services, eliminating abuse, maximizing access, and improving the healthcare system's information infrastructure.

In fact, the focus on healthcare IT at the IOM goes back even further. In 1991, they published "The Computer-Based Patient Record: An Essential Technology for Healthcare"(revised 1997), a report heralding computerized patient records as the best hope for higher quality of care.

In the Fall 2010 issue of the Journal of Healthcare Information Management (a publication of the Healthcare Information and Management Systems Society ‑ membership required), Judy Murphy writes about the progress that has been made in healthcare since the IOM's push for better healthcare IT began over twenty years ago:
Robert Wachter, author of two books on patient safety and editor of the federal government's two leading safety Web sites, gives efforts an overall grade of B-, a slight improvement from his grade of C+ when he performed a similar analysis five years ago. Wachter says that overall, the past decade has seen progress in hospitals' responses to accreditation requirements, regulation and error reporting, but health IT has lagged behind, with research in the area slowly advancing and remaining underfunded.
As Judy Murphy notes, progress has been at best mediocre:
Unfortunately, the attractive claims linking health IT and quality outcomes rest on scant empirical data. Several studies and system reviews published in 2009 and 2010 have demonstrated some evidence for cost and quality benefits of computerization at a few institutions, but with little evidence of broader application.
And it seems that the long-term strategic objectives of this initiative have been obscured by the shorter-term tactical objectives:
The modest quality advantages associated with computerization are difficult to interpret, and are clouded by the fact that the quality indicators used today often reflect care process metrics rather than patient care outcomes. In other words, we are measuring how many patients receive smoking cessation counseling or prescriptions for beta blockers; we are not measuring how many patients quit smoking or what their reinfarction rates are.
The bright spot in all of this is the use of clinical decision support tools: also seems clear that implementing and adopting health IT is not enough. The evidence points out that, unless you specifically use systems with clinical decision support tools and paired with practice changes, you are unlikely to improve quality and patient safety and unlikely to achieve overall reductions in health costs.
Before computerization of healthcare records, we said that healthcare was data-rich, but information-poor. Post computerization, it seems healthcare IT is information-rich, but analysis-poor. In other words, we have the information we need to make a difference, but haven't yet applied the appropriate analytics tools and mindset to the larger strategic objectives.

Clearly, budget is a large part of the problem, but in the age of doing-more-with-less, asking for a larger budget is probably a non-starter. So business analytics managers in healthcare need to look at ways to liberate resources from repetitive administrative tasks so they can spend more time adding value to outcomes via better decision support capabilities. You can't focus effectively on the larger issues if you spend all your time resolving the smaller ones.

1 comment:

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