Most patient safety improvement occurs incrementally within single institutions. A new method to develop comprehensive statewide risk models that could be exported to large segments of the health care industry is evaluated. Working hypothesis: Sociotechnical probabilistic risk assessment (ST-PRA) can create risk models identifying common medication system and behavioral elements that raise the risk of serious errors and these risk models can be used to design statewide risk reduction programs for nursing and community based care (CBD) long term care facilities. These facilities need robust, well-designed medication systems because they serve a growing and often frail population, administer highly toxic drugs, and must perform to high standards using an unstable and sometimes minimally skilled labor force. Design: Developmental study. Methods: This project uses four tools--process mapping, control system mapping, failure modes and effects analysis (FMEA), and socio-technical probabilistic risk assessment (ST-PRA)--to create two comprehensive probability risk assessment (ST-PRA) models, one for nursing facilities (NFs) and one for CBC (residential care/assisted living) facilities, to identify processes and behaviors that increase the risk of wrong drug, wrong dose, wrong patient medication delivery errors in LTC facilities. The NF risk assessment model is created by focus groups of staff, pharmacists, and physicians from nine randomly selected facilities in a stratified sample of three large, volunteer LTC chains. The CBC process is similar, with nine randomly drawn CBC facilities. Focus groups of CBC residents and their families will be invited to provide input into the CBC model. Appropriate human subjects and privacy protections will be in place. Models are validated in stratified, random samples of nursing and community-based care facilities to determine whether each model is representative of medication delivery systems in the respective types of facilities, using a combination of structured focus groups and direct observation. Recommendations for interventions to address the systems and behavioral risks identified will be made and lessons learned while undertaking this large-scale, multi-facility ST-PRA project will be reported.
