Assessing the Predictive and Analytics Capability of Electronic Clinical Data for High-Cost Patients

Hotspotting may prevent high healthcare costs surrounding a minority of patients when void of issues such as availability, completeness, and accessibility of information in electronic health records (EHRs). We performed a descriptive study using Barnes-Jewish Hospital patients to assess the availability and accessibility of information that can predict negative outcomes. Manual electronic chart review produced descriptive statistics for a sample of 100 High Resource and 100 Control patient records. The majority of cases were not predictive. Predictive information and their sources were inconsistent. Certain types of patients were more predictive than others, albeit a small percentage of the total. Among the largest and most predictive groups was the most difficult to classify, "Other." These findings were expected and consistent with previous studies but contrast with approaches for attempting prediction such as hotspotting. Further studies may provide solutions to the problems and limitations identified in this study.