Consistency of safety monitoring using routine national databases: results using a quality of care interpretative model. (29th June 2020) - Labella, Barbara; Giannantoni, Patrizia; De Blasi, Roberta; Caracci, Giovanni; Carinci, Fabrizio
Abstract: Background: In the framework of targeted action for continuous safety monitoring, we aimed to evaluate the consistency of indicators derived from available databases for regular reporting. Methods: We used a quality of care interpretative model to select characteristics from five national databases, aggregated and linked by homogeneous groups of providers. The target population included all subjects admitted to public hospitals for acute care in four regions of Italy between 2011 and 2013. The association between structures, processes and safety-related outcomes was investigated using odds ratios from generalized estimating equations logistic regression. Outcome measures included claims of malpractice and five patient safety indicators calculated from discharge abstracts using standardized algorithms. Results: Over 3 years, claims of malpractice and sepsis increased, whereas deep vein thrombosis and pulmonary embolism decreased. Hospitals with high vs. low volume of discharges were associated with −16% lower rates of claims, but +12% increased risk of sepsis. Compared with research institutes, university clinics had −17% lower rates of claims and −41% cases of dehiscence, with a +32% increased risk of deep vein thrombosis. Local health care authorities recorded −49% deep vein thrombosis, −26% pulmonary embolism, −40% sepsis and +37% risk of claims. Hospitals submitting cases of safe practices and implementing safety recommendations showed significantly higher rates for most outcome measures. Conclusions: Indicators from regular databases can be conveniently used to develop a national safety monitoring system for hospital care. Although deeper analysis is needed, institutions with a higher propensity to implement safe practices and recommendations consistently showed higher rates of adverse events.