This is the age of advanced analytics in healthcare: population management, predictive analytics, personalized medicine, and clinical decision support. Laboratory analytics are a dominant — in fact, disruptive — solution well-suited for many health systems.
Health system C-suite challenges
It’s no secret that health system executives are challenged with reducing costs. But the health system C-suite is equally concerned with the other aspects of care delivery: integrating care delivery, coordinating care delivery, and maximizing quality.
Organizations like Cleveland Clinic and Mayo are facing 15% cuts in operating expenditure (OPEX), which is quite substantial. This means that the usual ways of cutting OPEX — reducing staffing, supply cost management, etc. — just don’t work anymore. Executives have moved on to structural aspects of reducing costs, like moving from inpatient to outpatient, looking at post-acute care, moving patients out of nursing homes, and working at top of license.
Integrating care delivery
Care delivery needs to be integrated everywhere and anywhere across settings. There’s a lot of merging going on; hospitals are buying physician groups so they can be set up for population health.
Coordinating care delivery
Due to bundled care, different specialties are coordinating across service lines now, and RNs and mid-level case managers are all working together to coordinate care.
There are hundreds of measures that need to be met, and unpaid events, like readmissions, that have to be managed in order to receive proper reimbursement. Today’s healthcare world is consumer-driven; it’s estimated that consumers actually pay more than employers in total out-of-pocket costs. There’s more transparency, so consumers have more choice. Approximately a third of the metrics that are used by Medicare and other payers to link and determine providers’ pay come from patient satisfaction scores.
Enter the age of advanced analytics
This is a lot of change. Add to all of this the fact that clinicians are struggling with decision-making. The Institute of Medicine issued a report a few years ago called “Best Care at Lower Cost,” which states, “The pace at which new knowledge is produced outstrips the ability of any individual clinician to…manage information that could inform clinical practice.”
“The pace at which new knowledge is produced outstrips the ability of any individual clinician to…manage information that could inform clinical practice.”
That’s because the complexity of things like molecular testing, genomics, the number of new tests that are coming out, and the sheer amount of patient information is staggering. The number of patients these doctors have to see, the number of doctors that exist, the IT, the number of alerts that happen — all of this is overwhelming. On top of that, there is the need to be managing to more targets, more quality metrics, as well as forecasting costs and risks. This is a setup for a lot of errors to occur.
That’s why this is the age of advanced analytics. Doctors need help with clinical decision support. Health systems need help with predictive decision-making. There’s a whole toolbox needed for population management. And we’re entering the era of personalized medicine, where you have to be intelligent about how you’re applying molecular and genetic testing to optimize therapeutic decision-making.
Health systems and doctors, individually, are basically being paid and measured for metrics that are used for consumers to choose them and payers to decide what ratings to give them, based on how they perform relative to each other. So, these analytics are becoming really critical to their performance. In fact, health systems refer to these analytics together as the “central nervous system” — really the “brain” of what they need to perform in modern medicine and modern healthcare.
For more of Dr. Herriman’s insights into the new era of analytical tools, download “Advanced Laboratory Analytics — A Disruptive Solution for Health Systems“.