Concepts of Risk Stratification in Measurement and Delivery of Quality

Abstract

The importance of quality is gaining increased attention from all stakeholders in healthcare due to high regional variability and association between poor quality care and increased healthcare costs. Quality of care is assessed by patient-reported outcome measures; however, if not available, quality is then commonly calculated by dividing value by cost. Value varies with respect to perspective, and cost can be complex to compute. Costs may comprise direct cost, indirect cost, or both depending on the perspective. To ensure high quality of care, the concept of risk stratification is imperative. This involves identification of parameters likely to influence outcome negatively including patient’s age, diagnosis etc., which may be predictive of poor postoperative quality of life. For stratification, risk models, expert panels, and databases can be utilized. In the literature, various categories of risk for many parameters have been developed. For example, preoperative specific spine diagnoses have been found to be predictive of postoperative quality of life. To apply this concept, one must define a specific endpoint, build risk models based on data or in collaboration with experts, and establish risk groups with risk calculators based on preoperative profiles. When judiciously applied, it seems that risk stratification has the potential to inform patients and healthcare providers with tools to set expectations, predict likelihood of outcome, and ensure good quality of care in the new era of accountable care.