Health care has benefitted tremendously in the past decade from the explosion of data of all kinds. From more accurately identifying and tracking trends in care delivery, to developing the ability to predict the likely onset of disease, to documenting the real-world effects of social determinants of health, data has contributed to significant industry advances.
But as one leader of an academic medical institution phrased it recently, “It’s hard to know where you’re going when you’re constantly looking at what happened behind you.”
To rectify this, health care systems large and small are becoming more adept at using real-time data to make care decisions, ranging from tracking, and trending the acuity of a patient in the hospital setting to management of chronic and non-chronic patients through their physician’s office. Likewise, most health insurers have built robust data analytics capabilities and are increasingly working with health care professionals to use that data for the benefit of their patients and members.
Historically, clinicians and administrative teams at both entities have relied on online portals or faxing documents to share clinical information and determine medical necessity. When those decisions aren’t clear, additional time is spent on manual processes to gather and share more data. Typically, peer-to-peer discussions are also scheduled to review the information. The result is an inefficient and subjective process that consumes our clinical resources and introduces waste, friction, error, and delay.
A 2018 report by the Office of the Inspector General found that Medicare Advantage plans overturned 75% of their own denials over a three-year period when providers and beneficiaries appealed those decisions. If health insurers typically approve upwards of 90% of all services which require an authorization, as noted in this same report, why is there so much administrative time spent on these reviews and authorizations? This question has never been more pressing than in today’s staff-stretched and resource-constrained environment.
Part of the reason is because the health care system does not fully utilize real-time patient data, nor does it apply objective analysis to make medical necessity determinations. With the advent of predictive analytics, machine learning and artificial intelligence, we are now prepared for real collaboration across health insurers and health systems. The net result is a more efficient health care system for all stakeholders.
There are early examples of the benefits when providers and health insurers leverage shared platforms for clinical information exchange and predictive analytics to make these decisions faster and more objectively, eliminating a significant amount of administrative waste. This approach doesn’t benefit the provider over the payer or vice versa; it places a premium on getting it right quickly and with as little friction as possible.
One example, in a recent Chilmark Research case study of a health insurer found that the average time for approvals on a shared platform was reduced by 76% when compared with traditional EMR workflows (at 37 minutes). In addition, this study found that 66% of the time, this level of collaboration and application of data produced a determination of patient status with a single touch of that case by utilization management teams.
When health system and health plan teams are able to work collaboratively using real-time data coupled with the application of highly accurate data science, they work more efficiently, spending less time on cases where they will ultimately agree. This allows limited staff resources to focus on cases which require their clinical expertise.
With nearly $4 trillion spent on health care in the U.S. annually, one quarter of which is on non-clinical administrative functions, the way health care operates is long overdue for modernization. With operating expense increases and ongoing staffing challenges, hospitals’ and health insurers’ motivations are increasingly aligned. A new path forward is necessary for the continued viability of our health care system. Payers and providers will benefit from shared views of forward-thinking data to support joint efficiencies, build trust and accelerate collaboration for a smoother and more sustainable health care system.