Advanced post-acute analytics and value-based care
Now that we’ve covered predictive post-acute analytics in practice, we move on to the topic of tackling the challenges of the Triple-Aim.
This series of blogs on predictive analytics and value-based care is inspired by a recent panel session – Predictive Analytics to Power Up SNF Performance – and aims to encourage excitement for and adoption of advanced analytics in the post-acute space. Thank you to my colleagues and fellow panelists Bob Latz (Trinity Rehab Services), Majd Alwan (LeadingAge), and Jane Moffett (Net Health) for contributing to this conversation.
SNF Provider Perspective
Providers are using post-acute analytics to guide their decision-making and succeed in value-based care arrangements with payers today. Referral sources are looking at provider data and you want to be ready to tell your story behind it. Rehospitalization is a big point of collaboration amongst provider partners and an area where predictive measures can identify opportunities to intervene as early as possible. As a SNF Provider, showing the impact of improved outcomes on the tenets of the Triple Aim sends a positive message to their payer partners.
"The value of [predictive analytics] is...improved care across the entire system." - Bob Latz, PT, DPT, CHCIO, CIO at @trinityrehabsvc #ForcuraCONNECT #ForcuraWebinar
— Forcura (@Forcura) January 19, 2022
Healthcare Continuum Perspective
Predictive analytics help meet the challenges of the Triple Aim and value-based care because you need to demonstrably advance the needle on all three fronts: improve quality of care of your residents, reduce the cost of care for the residents or population, and at the same time increase the satisfaction of your residents and their families. With the CMS focus on paying for performance, the post-acute space in general has been somewhat at a disadvantage.
The regulators are using analytics to benchmark us, and providers are using these benchmarks to create their networks, so if you are not looking at these metrics for performance, you will be at a disadvantage. Insights from analytics are key to making the right decisions, particularly future facing ones. Benchmarking against your peers is essential.
"If we're not aware of our performance and not taking steps to reduce hospitalizations & improve the way we care for certain populations...we're going to be at a disadvantage." - Majd Alwan, Ph.D., @LeadingAge #ForcuraCONNECT #ForcuraWebinar
— Forcura (@Forcura) January 19, 2022
Analytics Provider Perspective
Providers can use post-acute analytics as a competitive differentiator in value-based care by tracking and sharing KPIs that matter most to referral partners and payers.
A recommended KPI starter set includes:
- hospital readmission rate,
- risk adjusted length of stay,
- risk adjusted return to community rate,
- and post-acute care volume.
Risk adjustment is so important because that allows a facility to compare themselves over time to their own performance and their peers.
You never want to be in a meeting compared to other providers and that’s your first time seeing the data. And where you’re performing well, you want to tell that story; and where you’re not performing well, analytics should help you discover why and devise a plan. Take that into your Quality Assurance and Performance Improvement (QAPI) program.
"[Predictive analytics] at the patient level and the staff level have reduced hospitalization...and made a difference in peoples' lives." - Janine Savage, RN, CHC, VP of Product Management, Analytics & Business Intelligence, @NetHealthFits #ForcuraCONNECT #ForcuraWebinar
— Forcura (@Forcura) January 19, 2022
Next level of KPIs would include key clinical quality measures that lead to and inform those utilization outcomes like falls, pressure ulcers, antipsychotic medication use and other things that concern payers.
Predictive Analytics and Triple Aim – In Summary
Access to predictive analytics in the post-acute space benefits both SNF providers and payers who are all under the same pressure to meet the triple challenge of increasing healthcare quality, reducing healthcare cost and improving the patient experience. Risk identification and early intervention through predictive analytics are key elements in tackling these challenges.
Next Topic in Predictive Analytics Series…
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