Health Care Monitoring by Hypergeometric Control Charts for Fractions Non-Conforming

Process monitoring in health care organisations is one of the core tasks of an efficient medical risk management system for detecting, assessing, mitigating, and preventing risks. Statistical control charts as adequate tools for process monitoring are well-suited to observe, measure, and improve health care outcomes as well as to minimize the occurrence of adverse events. In this presentation we focus on various improvements of control charts for „fraction non-conforming“ and their application to health care monitoring, since (hospital) quality indicators are often binary at the patient level, presented as proportions, risk-adjusted or standardised rates. In particular, we introduce a new class of statistical control charts based on the (negative) Hypergeometric distribution that comprises improvements of Binomial p-charts (with approximative or exact control limits), Geometric g-charts, and negative Binomial cumulative count of conforming charts. The proposed class of Hypergeometric control charts meets numerous requirements of efficient health care monitoring and is especially useful when monitoring high-yield processes.