July 27, 2021
In the first part of our Healing Healthcare series, we discussed the history of modern managed care and healthcare delivery. As these models of coverage have evolved, so have the structures for payment. Historically, most patients avoided thinking about the billing and payment process, instead deferring this oversight to their insurer. However, high deductible plans, balance billing, and skyrocketing out-of-pocket costs related to pharmaceuticals have increasingly made the patient a customer like in any other industry. This new climate has made each patient a more discerning consumer for healthcare, expecting the best value from his or her care.
Fee for Service: The traditional model of reimbursement in modern healthcare relies on a “fee for service” (FFS) model of billing. In the simplest terms, the doctor or hospital charges for each service provided during a patient’s care. Some of these charges may be based on the amount of time spent with the patient, while others are flat charges regardless of time spent. One of the biggest concerns/issues/complaints about the FFS model is that the more services that a provider recommends, the more revenue generated by the provider. There is a built-in financial incentive for a provider to recommend extra services, even if they do not consciously consider this during treatment. As we discussed in Part II, managed care insurance plans have stepped in as gatekeepers, requiring authorization and medical review for the approval of many more costly procedures. However, even with insurers employing utilization management systems to reduce billing, there is very little financial benefit for a provider to deliver fewer services or pursue more efficient care under the FFS model.
In this current model of reimbursement, health systems must continue to increase their volume of services provided. This doesn’t just mean increased services for each patient, but it also requires the system to grow its patient volume and continually look to expand its market size. Progressive health systems have looked to advance this growth by increasing their breadth of services; extending beyond acute hospital care to include primary care, specialty care, surgery centers and other services. These systems must continually optimize their strategic and patient acquisition practices in order to remain profitable with this volume-based definition of operational success.
Value-based care: Over the past 20 years, there has been growing support for a value-based care model of reimbursement as an alternative to FFS. Value-based care can be summarized as basing payment on the quality of services provided, rather than the quantity. Michael Porter (2010) defines “value” as outcomes divided by costs and proposes that this “value” should always be viewed from the perspective of the patient/consumer. This means that value can be added to care by improving outcomes, reducing costs (which includes time, money, resources, etc.), or more likely a combination of both. Although it can be challenging, optimal value-based care results in what is often called the “triple aim”: better care for individuals, better health for populations, and lower cost of care.
There are numerous models of value-based care, but a common feature is a shift in payment where charges are not solely based on the number of services rendered, instead of incorporating some measure of quality. This may involve a pre-determined or “bundled” rate for a procedure and recovery, bonus reimbursement for care meeting exemplary outcomes, or the promotion of care that is outcome-based rather than a la carte in its charges. Other value-based care models build a healthcare system where the risk shifts to the provider, and they are reimbursed for keeping patients healthy and reducing treatment needs. These models often include large care teams that provide service at different levels, reducing the need for regular physician services. There remain several challenges in achieving widespread value-based care implementation, but a healthcare payment future that focuses on the aforementioned “triple aim” seems to align well with goals for patients and providers alike.
Health systems that are shifting their operations towards a more value-based reimbursement system must act thoughtfully not only in their daily operations but also in their strategic planning. These systems must continue to rely on data analytics in their strategic planning and marketing and still remain increasingly aware of the outcomes and costs associated with the care provided. They are well served by utilizing clinical data analytics to monitor patient care and are at the forefront of the increased utilization of Artificial Intelligence aided decision making for diagnoses and treatment.
Transparency: An additional by-product of both the concepts of “patient as a consumer” and value-based care is increasing price transparency. Patients are becoming more informed consumers by questioning the anticipated costs and benefits of a recommended care plan, charges associated, and comparing the quality and satisfaction of services delivered by a potential provider. Regarding quality of care, patients no longer solely rely on recommendations from friends and family. Consumers can use simple tools to compare quality through numerous independent websites, non-profits that rate hospitals on safety, and the Center for Medicare and Medicaid Services (CMS) star rating for quality.
This increased desire for patient knowledge has pushed the healthcare industry to not only demonstrate the quality of their outcomes but also provide comprehensive quotes for care. Since 2020, hospitals have been required to publish the costs associated with many of the most common billable codes; however, figuring out actual costs is not quite as easy as adding up your grocery receipt. The flat rates that are charged have significant discounts added based on agreed upon rates with each insurer, and these vary from payer to payer. Additionally, there are massive swings in patient responsibility based upon a patient’s deductible. And so, while pricing transparency is improving, there is still a long way to go.
As discussed, value can be simplified in its definition as outcomes per cost; but it is incredibly difficult to define the terms “outcomes” or “cost” in healthcare. At present, “outcomes” are commonly reduced to whether a patient is readmitted after a procedure/admission or based upon an extremely focused clinical outcome measure. These measures leave much of a patient’s story untold. Data over a longitudinal period is necessary to track how a patient is functioning, what medications they require, and their overall quality of life. Such a data set would not only require extended time but would also require integration of multiple data sources. The importance of increasing inter-operability between electronic health records (making sure different health systems’ records communicate with each other) has been gaining increased attention of late and appropriately employing these massive data sets will be a key component in monitoring a patient’s long-term outcomes.
Proper consideration of “cost” is equally difficult, requiring inclusion of long-term and comprehensive inputs. Costs extend beyond the charges applied by the provider, but also need to consider the patient’s lost wages and non-monetary matters like time, discomfort, and other stressors associated with a plan of care. While there may never be a model that can truly account for all of the variables that influence the value equation; as data’s reach, inter-operability, and coordination improve, it will become more realistic to consider this more integrated approach. Health systems that can best observe the total costs of care will not only have improved success as defined by financial performance but also can utilize this benefit in their communication with potential patients/consumers.
With ncreased recognition of the patient as a consumer, these health systems can also better coordinate their outreach efforts to potential future patients. The breadth of consumer data that is available allows forward-thinking health systems to identify key audiences that meet clinical criteria for a systems’ services. These systems can gain a tremendous understanding of these audiences, all without any concern for HIPAA-protected information. Other systems can take this concept even further and employ advanced modeling practices to identify the base audiences that are most likely to engage with the health system based upon numerous sentiment, demographic, and consumer data sets.
Data analytics can also be incredibly helpful in blending the worlds of public health with hospital-based care and reimbursement. This is especially true in value-based care models, where there are financial incentives for the clinical network to keep patients healthy. Predictive modeling is an essential inclusion in this approach; seeking to properly identify audiences that are both most in need and most likely to be responsive to preventative messaging and care. By utilizing data to drive this audience identification, health systems can be more effective and efficient in community outreach efforts, benefiting both patient care and financial performance.
As reimbursement models continue along the slow, but important, road from FFS to value-based care, health systems will be presented with an almost infinite number of possible methods to employ data in their practice. While much of the current attention is placed on the potential of big data and AI to improve care performance and efficiency, it is also essential the health systems continue to consider how analytics can help to drive strategic planning, marketing, and other operational decision-making processes. The systems that best employ data analytics across this full spectrum of their services will be best suited for success, no matter what reimbursement models are in place.
In the next section of the Healing Healthcare series, we will discuss how 2020 and the COVID-19 pandemic impacted the future of healthcare reimbursement, operations, and delivery. What impacts are likely to be temporary and what has altered the direction of healthcare delivery in the US moving forward? And of course...how will data and analytics play a role?
Porter, M.E. (2010). What is value in health care? New England Journal of Medicine, 363(26), 2477-2481.
Ready to learn more? Contact Causeway Solutions to get started!