This week we’re delighted to share an article written by Mitch Morris, MD, US and Global Health Care Sector leader, Deloitte Consulting LLP. In his ‘My Take’, Mitch explores population health management and the potential to move to a more predictive model:
Wear particle analysis...ultrasonic noise detection...infrared thermography...all of these have one thing in common. They are technologies commonly used in NASA's predictive maintenance systems that keep equipment and their components working. With the onslaught of new technologies and predictive analytics, NASA can now predict ahead of time when a diesel generator, condenser, transformer, or pump may break down. And, more importantly, it knows this far enough in advance to replace components at just the right time – before they are unusable – preventing both waste and catastrophes (or just an inconvenient breakdown).1
While NASA and many other industries that depend on advanced manufacturing have progressed to this level of predictive maintenance, many others have not evolved beyond the break-fix system. Case in point: Health care.
In health care today, we often wait until something is broken and then we attempt to repair it. We stent the coronary artery after years of hypertension and high cholesterol. We start insulin after decades of obesity and poor diets. This has largely been a result of the way we pay for health care. A patient who is overweight may go years without receiving wellness and medical care – until he or she begins to show signs of difficulty controlling blood sugar. It is often only at that point, when they may already have developed a chronic condition that will require monitoring and medication for the remainder of their lives, that the system gets involved.
As shown below, today, health care largely operates a corrective maintenance system, fixing problems as they arise and charging for services when they are performed. Some of the more advanced health care systems have begun to move toward preventive maintenance systems, regularly performing checks and diagnostic tests such as blood pressure screenings and pap smears to catch things before they become a larger issue. But, few are operating a predictive maintenance system, where the system is designed to help monitor the patient's health on an ongoing basis to predict when an intervention should be performed.
However, as I explain in the 2016 Health Care Provider Outlook, we are seeing slow movement and progress forward. Promising movements such as accountable care organizations, bundled payments, and other reimbursement models are starting to address some of the underlying structural issues that have plagued the system for so long. As a result, we're seeing progress toward preventing emergency department visits and prolonged hospital stays. And, more importantly, care is moving away from hospitals and into more accessible, less costly settings – into homes, schools, and even work.
To fully accomplish the shift to a predictive maintenance system, technology adoption will play an important role. Mobile phones, telehealth, and portals are just a few examples of technologies that can help providers monitor patients' conditions and prevent major health care problems. Digital technologies will shape the health care landscape through tools that encourage and empower consumers to take better care of themselves, and thus reduce reliance on the costliest and most acute health care resources. Other enabling technologies will be needed to take information from remote devices, electronic health records, consumers, and clinicians to coordinate messaging and tasks across the health ecosystem.
Technology is just one component, however. Care coordination and consumer engagement strategies will be important to help ensure that the technologies are used properly and routinely. Physicians and care providers may also need to change the way they practice, shifting to employ evidence-based medicine and best practices to design the system to achieve optimal outcomes. And finally, analytics that assess outcomes, both clinical and financial, may help health care systems fully understand impact and continually improve the system.
If we are going to be successful at effectively managing population health, the public and private sectors may need to align financial incentives and move away from the "break-fix" model of care and into a new era of predictive maintenance and optimization.
Footnotes
1 US Department of Energy, O&M Best Practices Guide, Release 3.0, Chapter 6: Predictive Maintenance Technologies," 2013
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