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Risk Stratification For Improving Population Health Management Category: Healthcare Administration by - March 9, 2017 | Views: 4282 | Likes: 0 | Comment: 0  

risk stratification

The Importance of Risk Stratification in Population Health Management

Providers manage population health anagement with risk stratification and a delicate balance as value-based care becomes the primary focus of healthcare organizations. It is now important for providers to focus on patients’ individual and distinct health signs and make decisions to take their journey forward to better and quality health.

Before providers deliver care, they should have a prior knowledge of who their patients are, identifying them and finding who needs the care most. In this era of value-based care, risk stratification becomes a necessity: to sort patients into high, moderate and low health risk tiers and delivering appropriate care to address their health needs.

What is Risk Stratification?

Risk stratification is the process of dividing patients into “buckets” based on their vital health signs, their lifestyles, and medical history. Risk stratification is a framework applied for complete population health management, combining several individual risk scores, demographic and socioeconomic characteristics and medical records to create a comprehensive patient profile.

  • Risk stratification is the foundational step for targeting patients at various levels of risks, and further, scheduling follow-ups and keeping them aligned with their care plans. Here’s why risk stratification is important:
  • Predict risks: Risk stratification can help providers to proactively identify patients at risk of unplanned hospital admissions. Almost one-third of all the readmissions that take place in the United States are preventable.
  • Patient-specific care plans: Identifying patient-specific risk factors that may pose a threat in the future can help physicians and health coaches develop care plans tailored to their needs.
  • Understanding population health trends: With a continuous assessment of risk factors and the use of risk scores, providers can understand their patient population and find answers to critical questions.

All in all, it’s the need of the hour to implement risk stratification in any successful population health management model to classify patients into high-risk, low-risk, and rising risk groups and to achieve the Triple Aim: better health outcomes, quality care and lower costs of care.

Overview of Risk Stratification Methods

There are several models available to stratify a population by risk. Here are a few widely used and recognized ones. 

Hierarchical Condition Categories (HCCs): The HCC models were designed by CMS as part of the Medicare Advantage Program. It incorporates 70 conditions, all selected from ICD codes and also brings in expected health expenditures.

Adjusted Clinical Groups (ACG): ACG was developed by John Hopkins University with the ability to stratify risk with a critical review and testing process. It uses both inpatient and outpatient diagnoses and predicts hospital utilizations.

Elder Risk Assessment (ERA): ERA works for the population over 60 years of age and makes use of their demographic data to assign a risk score to each patient.

Chronic Comorbidity Count (CCC): CCC is the total count of selected comorbid conditions spanning over six categories using the public data from the Agency for Healthcare Research and Quality.

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