Data analytics are an opportunity to better understand and determine specifics about how conditions like knee and hip OA drive productivity and other measures. Unfortunately, choosing a strategy to assess or measure osteoarthritis in a population can be complex and challenging. Different stakeholders value different things. As a result, there is a lack of uniformity and a variety of different metrics used. Clinicians focus on disease progression and severity, patients value pain reduction and related quality of life improvements, and employers often look at impact on productivity measures and employee satisfaction. (EPIC p. 23)
To complicate things further, many people with osteoarthritis have multiple chronic conditions including heart disease, diabetes, obesity and depression. Untangling osteoarthritis from other chronic conditions can be difficult and is another challenge facing employers trying to determine the prevalence and cost impact of OA.