The healthcare industry is constantly evolving and changing. Today, there is a lot of change in the way organizations care for their populations and the care delivery models. New care models incentivize keeping populations healthy through better preventative care, proactive chronic disease care, cost avoidance and optimal utilization management. Additionally, new payment models incorporate financial risk taking and pay-for-performance incentive management.
Looking at Risk Contracts on a Continuum
Provider-led PHM programs don’t just form overnight. Organizations must actively make the transition from traditional siloed fee-for-service (FFS) programs to a patient-centric, payer-agnostic model, value-based payment models. In this journey, organizations will go through four phases of maturity (read more about that here). Where you currently are on the Population Health Maturity Cycle and where you want to be will determine how much risk your organization should take on and how you will get paid from the different value-based contracts you sign. In that way, payment models and your organization’s exposure to risk are also on a continuum.
These types of contracts utilize the most traditional and conservative payment model and one that most healthcare organizations excel at. Here, services are unbundled and paid for separately, and physicians concern themselves with the quantity of care more than the quality of care. This model unknowingly incentivizes physicians to perform as many treatments as possible; fee-for-service contracts often damage the trust of the patient-physician relationship. Fee-for-service contracts result in higher healthcare costs, less efficient and integrated care, and a less satisfied patient population.
This contract has a payment model that offers financial incentives to physicians, hospitals, medical groups, and other healthcare providers for meeting metrics related to quality measures, healthcare outcomes and patient satisfaction. Pay-for-performance programs can depend on a variety of different metrics and these metrics may often seem conflicting. For example:
- Process Metrics: patients should be undergoing appropriate tests to close gaps-in-care on a regular basis as defined by best practices for certain chronic conditions
- Outcome Metrics: lab and test results should be within the target range with the expectation that it will avoid adverse events
- Cost or Utilization Metrics: resources should be managed effectively as measured by readmission rates, generic prescribing rate, formulary compliance, and getting treatment at the most appropriate settings (Urgent care vs. Emergency Care vs. Primary Care Clinics)
- Patient Satisfaction Metrics: patients should be satisfied with the overall experience with respect to access, communication and well-being.
A pay-for-performance contract results in attractive financial incentives for physicians that manage to reduce cost and improve outcomes at the same time. Thus, physicians are increasingly motivated to comply with evidence based practices and keep their populations healthier.
Under a full-capitation payment model, a payer gives a set payment per patient for specified medical services to a provider organization. Therefore, the provider takes on all the risk for the covered patient. These payments are in the form of a monthly per-patient-fee and are risk adjusted for each population. Providers reap the rewards of providing care at a cost below the capitated rate, but also bear the risk if the cost of care exceeds the capitated amounts. There are two capitation models:
- Global Capitation: an arrangement where a healthcare organization receives a single fixed payment for the entirety of healthcare services a patient could receive (including primary care, hospitalizations, specialist care, and ancillary care)
- Partial Capitation: an arrangement where the single monthly fee paid to a healthcare organization only covers a defined set of services. Services that aren’t covered are paid for with a fee-for-service model
Managing Care Delivery in a Multiple Contract Environment
Where an organization is in the Population Health Maturity Cycle determines what kinds of risk contracts that group should undertake and what percent of revenue is exposed to FFS, pay-for-performance, and capitated contracts. The challenge at the current transitionary stage for physicians and healthcare administrators is how to manage the transition in an environment where there are multiple payment models co-existing. Does your treatment protocol change with each patient based on what health plan they belong to? The answer to managing this transition is a PHM organization that is program-driven with a closed-loop continuum of care where utilization management, patient engagement, and care management all work together.
Analytics-Driven Program Development
This image shows how program development is central to effective PHM; programs change on an annual basis as an organization moves up the risk continuum. There are never enough resources to invest in every program. This is where analytics comes in. Choosing the right programs and the right patient cohorts to target in each of those programs is the only way to utilize your resources wisely.
By understanding your business goals, and using historical data and proven disease models, Vitreos can help design the right programs for your population regardless of which type of contract they fall under. In addition, our models can help target the riskiest patients for these programs. Predictive analytics along with optimization algorithms can prioritize the members that can have an impact on multiple programs in your portfolio. Effective, impactful care programs can help drive your organization through the Population Health Maturity Cycle.
Aligning Cost and Quality Goals
We keep hearing about ACOs, health plans and health systems meeting quality measures but missing the cost target. Or meeting cost targets but missing quality measures like STAR, HEDIS, and GPRO goals. Are cost goals and quality goals in conflict? Not really. The problem is that most healthcare systems do not use advanced analytics to design and drive their programs. For example, if you want to increase your diabetic quality measure, you can identify all the members with diabetes who are not regularly testing for A1C and target them with a member outreach program and bring them into the clinic to close that gap.
Compare that to a program that uses a predictive algorithm that looks at all the diabetic patients and analyzes what other chronic conditions they have, their historical behavior patterns towards compliance, and access and socioeconomic issues. An advanced predictive algorithm can generate a prioritized list of members to target monthly. When these members show up on-site, healthcare professionals can address the other gaps-in-care necessary in addition to A1C.
This is what Vitreos does and the reason why most of our customers beat their competition when it comes to maximizing outcomes in an evolving healthcare landscape.