It saves lives, It promises to reduce costs, but it’s hard to define, and even harder to implement. In the big picture, population health management is broadly defined as a systematic effort to do three things in the health care system; enhancing health through disease prevention and management, Improving care quality and reducing waste and variation, and eliminate silos.
Population health mostly focuses on making it worthwhile for insured patients, many studies find it useful for managing another risk—caring for underserved, uninsured and underinsured community members. The concept of population health is not exclusively relevant to large systems or registries it is applicable in small healthcare organizations as well, as evidence, the Science of using the data for population health management as a method for improving care for patients at a high level are reported to work in small settings and can be categorized as follows: identify target population, Apply analytics, determine gaps and segments, target interventions and Measure and monitor all of which are methods to identify clinical gaps and apply practices holistically that produce the desired outcome.
A closer look to the health system and tools, we learn that we are not equipped for population health management because most of the infrastructure— financial systems, Electronic health records (EHR)s, and billing—are set up first and foremost to drive revenue not the quality of care or clinical outcomes. But, Market Conditions are showing a growing trend where healthcare organizations are ready to move from fee for service to pay for performance embracing change, payers support or partner in risk-contracting, view provider-sponsored plans less of a threat and patients are willing to accept narrow networks, care coordination, and preventive medicine and lifestyle coaching. Key opportunities organization can drive are revenue vs. cost trends—Opportunity for lowering costs and improving quality by “rationalizing” service delivery.
Doing population health management right entails essentially overhauling the delivery system and starting over with network building. Organizations must assemble the building blocks of clinical targets, prioritization tools, and data warehouses that convene and enable nimble access to the disparate clinical d and financial systems that largely function as silos now.
Moving into population health management without a comprehensive network and data strategy limits an organization’s ability to orchestrate utilization in a way that moves the cost needle in the right direction and quality of care. Building a data warehouse and ensuring data governance is the key to population health management.
Population health management is a journey, not a project and no guarantees are made for success. Healthcare organizations.
are exposed to additional risks: population-based accountable care arrangements reward innovators who can cut costs and improve outcomes. The rewards mostly flow from revenues previously budgeted for hospital services often funding services that directly reduce in patient volume. Successfully negotiating the transition to value-based care requires full assessment and management of local markets conditions.
The success of healthcare care organizations ultimately depends on the extent to which it intelligently deploys technology solutions for data analytics, care team workflows, and patient engagement to improve population health while reducing costs. To do it right organization should assess if: their systems have the ability to coordinate services across the care spectrum? Are there quality improvement and quality reporting systems in place? Are clinical services operating at optimal efficiency? Are physicians on board with specific types of risk-contracting? And do you have in place or can you buy or contract for all services required for a particular type of risk-contracting?
Key forces that impact adoption in healthcare organizations are; enrollment in Medicare is climbing exponentially as the U.S. population ages, the big data revolution is exploding with increasing IT infrastructure and data analytic requirements along the continuum of care, chronic, preventable disease is reaching epidemic proportions and the increasing regulatory requirements coming from the Affordable Care Act.
A focus on population health management is a necessary ingredient for success under value-based payment models. As part of that effort, it is essential to embrace technology that can help healthcare organizations improve population health, enhance the patient experience, and reduce costs. Here are some of the practices organization reported to be effective: use predictive analytics for risk stratification, combine predictive modeling with algorithms for financial risk management, use population registries to identify care gaps, use automated messaging for patient outreach, engage patients with automated alerts and educational campaigns, automate care management tasks, build programs and organize clinicians into care teams, and use analytics to measure performance of organizations and providers.
An important part of the puzzle is depending on population health management vendors, they need to adopt as well, it is expected that they will develop different models for service delivery that can be decoupled from traditional health benefits. The customer model likely will shift away from employer-sponsored programs toward the individual consumer market, health plans, provider networks, or ACOs. With the shift in customer focus, population health management vendors will need to become better at individual consumer engagement and integration with health care delivery system stakeholders. They will also need to refine their metrics to enhance the focus on individual and business performance outcomes.
In closing, as hospitals and payers pay more attention to how to keep their populations of interest healthier and at a lower level of risk per dollar spent, a crucial component will be appropriate risk adjustment of outcomes and payments. The quality of these adjustments is ultimately limited by which data are entered into the record and how they are entered. Moving forward, risk-adjusted utilization will increasingly influence how well providers can negotiate favorable contracts with payers that are increasingly seeking out more value.