In biomedical research we often say “if you torture the data long enough, it will confess to anything.” As many in leadership are learning, the complex nature of statistics can be used to obfuscate the truth. The same is true for the burgeoning list of metrics that have spread across health care. Some organizations report on well over a hundred different metrics to track their performance. While these metrics are all intended to reveal important trends in your organization, too many have only a loose correlation with good outcomes.
For the leaders in the hospital C-suite, the question becomes how do you understand your hospital’s true performance? It is our impression that hospitals have exercised appropriate judgment in supply chain decisions and have a strong grasp of issues of appropriate staffing. It is therefore only a small margin that can be achieved by enhanced efficiency and cost reductions in these areas at most hospitals. But the clinical pathway itself still offers large opportunities for improvement. Providing care that results in better patient outcomes will ultimately reduce expenses more than it will reduce revenues. There aren’t a lot of short cuts here. Providers just have to provide more cost-effective care. With that in mind, our research has identified five metrics to use to track your hospital’s performance.
With apologies to Mark Twain, statistical methods can transform “Big Data” into actionable information in healthcare outcomes. MPA Healthcare Solutions has applied sophisticated statistical methods to large databases to identify what the results of care have actually been. We use risk-adjusted measurements to identify specific areas where outcomes of care can and should be improved. Using this approach, we have designed predictive models based on hospital performance nationwide. In the process we have identified five specific risk factors that have a disproportionate impact on patient outcomes. You can track each for your organization:
1) Adverse Outcomes Resulting in Inpatient Deaths,
2) Prolonged Length-Of-Stay (prRLOS) outliers,
3) 90-day post-discharge deaths,
4) Relevant 90-day post-discharge readmissions
5) Preliminary research also suggests that “Risk-adjusted 90-day Emergency Department Visits after Discharge” is a key factor. We are investigating this area further.
We are testing these metrics on the ever-growing number of ambulatory operations as well. Part of our purpose in using these risk factors is not to make any assumptions about why adverse outcomes occurred, but rather to make a no-fault identification of outcomes that were other than what we would prefer to have for patients. This tends to reduce bias and encourage a fair reporting of the data.
At the Becker's 11th Annual IT + Revenue Cycle Conference: The Future of AI & Digital Health, taking place September 14–17 in Chicago, healthcare executives and digital leaders from across the country will come together to explore how AI, interoperability, cybersecurity, and revenue cycle innovation are transforming care delivery, strengthening financial performance, and driving the next era of digital health. Apply for complimentary registration now.
