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The goal for any population health program should be to keep members healthy and prevent the onset and advancement of disease. Historically, population health programs have been disjointed because payers, providers, employers and communities execute isolated efforts with no collaboration or communication. Not surprisingly, the impact of siloed programs is usually unremarkable.

The Population Health Objective – A Multidimensional Optimization Problem:TRIANGULATION_GRAPHIC_social

Improving Outcomes is the answer to the challenges that plague the healthcare industry. At its heart, population health management (PHM) is a multidimensional optimization problem with each of the Triple Aim Population Health Objectives being a variable that directly impact a program’s profits.

Financial PerformanceMAX=Improving Outcomes=PMPMMIN+Patient Specific RiskMIN+Quality MeasuresMAX

Improving measurable outcomes like hospital visits, ER visits, and readmissions is the best way to reduce PMPM costs, manage patient specific risk (which includes clinical, socioeconomic, and behavioral risk), and improve quality of care.

Complicated Variables in the PHM Optimization Equation

Improving Outcomes seems like an easy answer on paper. In reality, providers and payers are navigating an evolving healthcare environment. The complexities that stakeholders in any value-based care organization face are multifaceted. The equation shown above is not easy to execute when many of the variables conflict with each other. PHM organizations must use limited resources to invest in programs that will be most effective. Some of complex issues that stakeholders of PHM programs debate everyday are detailed below:

Traditional Fee for Service, Pay-for-Performance, and Full Capitation Contracts

These contracts all sit on a spectrum of differing levels of risk. In addition, each type of risk contract has different quality and cost targets to manage while still maximizing revenue. It would be easy to maximize profit and minimize risk by taking on a variety of contracts, however it is not feasible that a PHM organization offers differing services for patients under each type of contract.   

Quality, Risk, and Cost

For each population cohort, the optimal care delivery plan is different depending on membership, disease and social determinant risk, quality goals, and target per member per month (PMPM) cost. It can often feel like a juggling act trying to balance quality, risk, and cost; however, they each impact the bottom line.

Cost Reduction and Cost Avoidance

Cost reduction involves traditional utilization management while cost avoidance focuses on preventive care management. So how many resources should a population health program allocate to each? It depends on whether that organization values being proactive or prefers to be reactive. An important question to ask is what percent of a PHM program’s revenue is tied to “At-Risk” contracts or Fee-for-Service contracts.

High Touch Care Management and Low Touch Digital Outreach

The type, cost, and efficacy of a patient engagement plan depends on its targeted cohort of patients and the resources a PHM program has at its disposal. Each disease, quality, wellness, and pharmacy compliance program must have an appropriate and logical accompanying patient engagement plan.

Care Management Workload Optimization

Care Managers are a valuable resource for any population health program. Hiring the correct number of Care Managers is vital to keep costs low while maximizing quality of care. How many “High Risk” members are in different disease cohorts – Cardiovascular, COPD/Asthma, Oncology? Where is the quickest and largest ROI? Those are the questions that stakeholders should ask when optimizing Care Management workload.

Retrospective and Predictive/Prescriptive Analytics

When it comes to analytics, the most important thing to consider is that data analytics is only useful if it results in actionable insights. Retrospective reporting and predictive analytics can both be helpful when used appropriately. How much does a PHM organization invest in each of the capabilities and when to invest in them? A general rule of thumb is that the more risk an organization has taken on, the more money it should invest in predictive analytics.

Population Health Programs

Not all population health programs are created equal. So what programs should a population health program invest in for the highest and quickest ROI? It all depends on where that program is in the Population Health Maturity stage and its organizational sense of urgency to reach certain financial goals.

Tracking and Monitoring Performance

Any population health program needs to be regularly assessed and modified. What kinds of tools do stakeholders need to evaluate the outcomes of their program? Storyboards provide prescriptive insights using benchmarking and machine-based artificial intelligence tools while dashboards just display data.  

Considering all these variables, where does a population health program start? Understanding the State-of-Health Analysis (SOHA) of the patient population and where the program falls in the Population Health Maturity model is really the first step. My next two blogs will focus on these two subjects. Later down the line, we will discuss how to manage risk by understanding the above complexities using data analytics. VitreosHealth’s DNA is all about using Data Science to best optimize the Cost-Quality-Risk curves for population health programs. Gleaning actionable insights from your organization’s data is the best way to remain profitable.

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Looking at Population Health from “A Healthcare Resource Optimization” Perspective

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