Three physicians write in NEJM Catalyst about whether healthcare organizations should decide between small, incremental improvements or care redesign. Among their remarks:
“The shift from volume- to value-based payment may constrain revenue, forcing organizations to consider dramatic changes to care delivery. Doing this may require increasing their capacity for innovation relative to incremental improvement. Innovation and improvement are sometimes used interchangeably, but the distinction between them matters.
“Quality improvement methods are usually applied to refine existing care delivery processes. The way forward is relatively clear, and the returns are predictable and quick. Innovation, however, involves creating new products, services, or processes. The way forward is filled with uncertainty. Will the new approach work? When will it show results? Given the choice, most organizations are more comfortable with the predictability of quality improvement, labeling it innovation in some cases, but shunning the risk-taking that characterizes true innovation work.
“But incremental improvement in the absence of some degree of innovation is likely to produce limited gains.
“To thrive in a value-based care environment, organizations will have to be able to do the same things more efficiently and take advantage of the opportunities of digital health, patient empowerment, and integration across sectors to redesign much higher-value care. Organizations will need to decide how much money, time, or political capital they should expend to build structures and cultures that support both the goals of improvement and of innovation.”
Algorithms from machine learning have been beating humans in predicting such illnesses as heart disease and diabetes. Those algorithms will probably become even more accurate as they include personal data from smartphones and wearables, suggests an article from the Harvard Business Review.
Yannis Paschalidis, the director of the Center for Information Systems Engineering at Boston University, wrote in the Harvard Business Review that engineers at BU are working with such local hospitals as Brigham and Women’s Hospital and Boston Medical Center to manage heart disease and diabetes using algorithms that can predict hospitalizations up to a year in advance with 82 percent accuracy.
That’s compared, for example, to a 56 percent predictive accuracy of guidelines used by cardiologists to predict a patient’s risk of cardiovascular disease.
Of course, early identification of risk of serious diseases could save patients, providers and insurers billions of dollars as well a prevent many premature deaths.
Mr. Paschalidis, FierceHealthcare paraphrased, said that “machine learning will only become more accurate as data sets expand with access to personal data from wearables and smartphones. And as value-based payment models take hold, hospitals are likely to build analytics into their care processes.”
He wrote in the article: “If we can now predict future hospitalizations with more than 80% accuracy using medical records alone, imagine what is possible if we can tap into this trove of personal data. Recommender systems could be used to nudge us to adopt healthier eating habits and behaviors. The holy grail of heading off the emergence of conditions by keeping people well could be realized.”
Still, Mr. Paschalidis warned in his article:
“Yes, analytics and data-driven personalized medicine and health monitoring present risks. Do we want our employers and health insurers to know the status of our health and the risks we face? Privacy, security, and reliability of new systems and methods are also critical concerns. But rather than retreating from this new era, we should be working on how to strengthen our methods, institutions, laws, and regulatory framework to avoid those unintended consequences. Algorithms — the foundation of encryption methods, privacy-preserving data processing, and intrusion- and fraud detection systems — could help.”
Kenneth W. Kizer, M.D., is an expert on the expanding potential of community paramedicine. As a former director of the California Emergency Medical Services Authority, he wrote the regulations for paramedicine in the state. More recently, he has become a thought leader in population health — and an advocate for community paramedicine in value-based care.
Hospitals & Health Networks recently interviewed him.
Among his remarks:
“Community paramedicine is an important component of population health management and the new emerging value-based health care economy because it fills gaps in the typical health care delivery infrastructure that are especially relevant to value-based payment.
“The focus of CP programs varies widely — from paramedics providing directly observed treatment for tuberculosis patients at their homes to providing transportation to health care facilities other than emergency departments and many other concepts.”
“The programs that respond to the 9-1-1 superusers hold a lot of promise for better utilizing scarce emergency care resources, including ambulances and hospital emergency departments. We know that in many communities some people call 9-1-1 multiple times per week when what they really need is help with basic primary care or other support services. Many of these persons may be homeless or have mental health needs or other problems that are not always better managed in the ED.”
“Another type of program that I think is going to prove to be very helpful is one that provides follow-up care after a hospital discharge or an ED discharge. These programs serve patients before they can get in to see their usual provider or — probably more often — until they can establish a relationship with a regular health care provider.”
· “Help experts to make better decisions by penetrating the complexity of big data — including structured and unstructured data.”
“The volume of biomedical, clinical, psychosocial, personal and research data available continues to grow at an increasingly overwhelming pace. It is implausible for even the most diligent physicians to keep up with the proliferation of information and, consequently, many providers fail to connect their patients with the best care potentially available to them. If we use cognitive computing systems to give doctors the tools they need to succeed, and empower expertise in every individual caregiver, we can convert information overload into meaningful guidance that allows caregivers to perform at their highest potential.”
Further, “Cognitive computing also can be applied to the challenge of managing the cost of care, by helping organizations to understand where best to apply limited resources. Getting each complex patient just the right care (and avoid unnecessary care) at just the right time requires a careful balance between the a priori knowledge and the interactions of hundreds of factors — a perfect use for cognitive computing. When you have a system that can provide decision support based on intelligent analysis of all of those elements, and can collect and analyze data on which interventions and pathways are most effective, it becomes far easier to meet the demands of tightening margins in the setting of new value-based payment models.”
He notes that there’s “growing skepticism among many respected industry experts who question whether population health, providers at risk and Accountable Care Organizations are really the right answer. They fear these models may all turn out to be a bridge too far. Instead, they argue, we should get the basics of healthcare delivery right first. Then we should use bundled payment–type models as our lead foray into financial incentives that promote improved care coordination and clinical performance delivered by focused, high-performing teams.”.”So, there is a plausible … conclusion that meaningfully incenting providers to deliver care by taking financial risk for a defined population they serve (across the continuum of care) is an impossible dream that will end in failure. Therefore, we should settle back on bundles and other less grandiose improvement initiatives instead.”On the contrary, I still believe that our best hope for sustainable health care may well come from large integrated systems of care competing on the basis of cost and quality for a defined population.”
“Overall, my forecast can be summed up as follows:
“Integrated systems with their own health plans, regional scale, direct contracting and Medicare Advantage contracts is the end game for some large players who are preparing for population health risk.”
“Many hospitals will be caught between two paradigms for the next five years (at-risk vs. fee-for-service), but the direction is toward more risk-bearing on the basis of value through a variety of constantly evolving partnerships and risk-sharing arrangements.
“Bundled payment for procedure-oriented care presents a major step toward promoting value and care coordination that does not require population health (frequency risk).
“And finally: Value-based payment trends are not enthusiastically embraced by providers. So expect public payers to make more payment innovations mandatory, not just voluntary.”
A study in the Health Services Research journal attributed 58 percent of the variation in hospital 30-day readmission rates to the demographics of the county where the hospital was located.
The biggest factors in identifying areas with higher readmission rates: larger percentages of the population eligible for Medicare, higher numbers who had never married and “low employment designation.”
And FierceHealthcare, in its analysis of the research, noted:”One of the most crucial health-system variables that determines the rate of readmissions is the number of general practitioners in the community, primarily because patients in areas with fewer general practitioners have few options but to return to the hospital when they experience complications….”