METHODS: Eligible studies were included if they used any models to assess the impact of COVID-19 disruptions on any health services. Articles published from January 2020 to December 2022 were identified from PubMed, Embase and CINAHL, using detailed searches with key concepts including COVID-19, modelling and healthcare disruptions. Two reviewers independently extracted the data in four domains. A descriptive analysis of the included studies was performed under the format of a narrative report.
RESULTS: This scoping review has identified a total of 52 modelling studies that employed several models (n=116) to assess the potential impact of disruptions to essential health services. The majority of the models were simulation models (n=86; 74.1%). Studies covered a wide range of health conditions from infectious diseases to non-communicable diseases. COVID-19 has been reported to disrupt supply of health services, demand for health services and social change affecting factors that influence health. The most common outcomes reported in the studies were clinical outcomes such as mortality and morbidity. Twenty-five studies modelled various mitigation strategies; maintaining critical services by ensuring resources and access to services are found to be a priority for reducing the overall impact.
CONCLUSION: A number of models were used to assess the potential impact of disruptions to essential health services on various outcomes. There is a need for collaboration among stakeholders to enhance the usefulness of any modelling. Future studies should consider disparity issues for more comprehensive findings that could ultimately facilitate policy decision-making to maximise benefits to all.
METHODS: All patients with traumatic brain injury (mild, moderate, and severe) who were admitted to Queen Elizabeth Hospital from November 1, 2017, to January 31, 2019, were prospectively analyzed through a data collection sheet. The discriminatory power of the models was assessed as area under the receiver operating characteristic curve and calibration was assessed using the Hosmer-Lemeshow (H-L) goodness-of-fit test and Cox calibration regression analysis.
RESULTS: We analyzed 281 patients with significant TBI treated in a single neurosurgical center in Malaysia over a 2-year period. The overall observed 14-day mortality was 9.6%, a 6-month unfavorable outcome of 23.5%, and a 6-month mortality of 13.2%. Overall, both the CRASH and IMPACT models showed good discrimination with AUCs ranging from 0.88 to 0.94 and both models calibrating satisfactorily H-L GoF P>0.05 and calibration slopes >1.0 although IMPACT seemed to be slightly more superior compared to the CRASH model.
CONCLUSIONS: The CRASH and IMPACT prognostic models displayed satisfactory overall performance in our cohort of TBI patients, but further investigations on factors contributing to TBI outcomes and continuous updating on both models remain crucial.