A Performance Management System in Healthcare for All Seasons?

Health systems face challenges which are inherent to care demand and supply evolution (i.e., demographic change, new technologies) or are the results of unexpected occurrence originating outside the health system, such as economic shocks or epidemic outbreaks. Both challenges often require a paradigm shift in governance and organization, financing and resource allocation, accountability frameworks, as well as public health system responses. Based on key reviews and seminal papers of performance management, public health, sustainability and resilience, the article presents three emerging challenges for performance management systems in healthcare: i) the inclusion of the population approach; ii) the measurement and consideration of the multi-facets concepts of value; iii) the importance of resilience and sustainability. Performance management systems need to evolve to cope with this changing scenario. The article sheds light on uncovered areas by performance management, and it proposes a research agenda for scholars of both performance management and health service research

Changing relative and absolute socioeconomic health inequalities in Ontario, Canada:A population-based cohort study of adult premature mortality, 1992 to 2017

BackgroundThis study aimed to characterize trends in absolute and relative socioeconomic inequalities in adult premature mortality between 1992 and 2017, in the context of declining population-wide mortality rates. We conducted a population-based cohort study of all adult premature deaths in Ontario, Canada using provincial vital statistics data linked to census-based, area-level deprivation indices for socioeconomic status.MethodsThe cohort included all individuals eligible for Ontario's single-payer health insurance system at any time between January 1, 1992 and December 31, 2017 with a recorded Ontario place of residence and valid socioeconomic status information (N = 820,370). Deaths between ages 18 and 74 were used to calculate adult premature mortality rates per 1000, stratified by provincial quintile of material deprivation. Relative inequalities were measured using Relative Index of Inequality (RII) measures. Absolute inequalities were estimated using Slope Index of Inequality (SII) measures. All outcome measures were calculated as sex-specific, annual measures for each year from 1992 to 2017.ResultsPremature mortality rates declined in all socioeconomic groups between 1992 and 2017. Relative inequalities in premature mortality increased over the same period. Absolute inequalities were mostly stable between 1992 and 2007, but increased dramatically between 2008 and 2017, with larger increases to absolute inequalities seen in females than in males.ConclusionsAs in other developed countries, long-term downward trends in all-cause premature mortality in Ontario, Canada have shifted to a plateau pattern in recent years, especially in lower- socioeconomic status subpopulations. Determinants of this may differ by setting. Regular monitoring of mortality by socioeconomic status is the only way that this phenomenon can be detected sensitively and early, for public health attention and possible corrective action

Overcrowded housing during adolescence and future risk of premature mortality: a 28-year follow-up of 556,191 adolescents from Switzerland

BACKGROUND: Few large-scale studies have examined the health impacts of overcrowded housing in European countries. The aim of this study was to assess whether household crowding during adolescence increases the risk of all-cause and cause-specific mortality in Switzerland. METHODS: Study participants were 556,191 adolescents aged 10-19 years at the 1990 census from the Swiss National Cohort. Household crowding at baseline was measured as the ratio between the number of persons living in the household and the number of available rooms, categorized as none (ratio ≤ 1), moderate (1 1.5). Participants were linked to administrative mortality records through 2018 and followed for premature mortality from all causes, cardiometabolic disease and self-harm or substance use. Cumulative risk differences between ages 10 and 45 were standardized by parental occupation, residential area, permit status and household type. FINDINGS: Of the sample, 19% lived in moderately and 5% lived in severely crowded households. During an average follow-up of 23 years, 9766 participants died. Cumulative risk of death from all causes was 2359 (95% compatibility intervals: 2296-2415) per 100,000 persons when living in non-crowded households. Living in moderately crowded households led to 99 additional deaths (-63 to 256) per 100,000 persons and living in severely crowded households 258 additional deaths (-37 to 607) per 100,000 persons. The effect of crowding on mortality from cardiometabolic diseases, self-harm or substance use was negligible. INTERPRETATION: Excess risk of premature mortality in adolescents living in overcrowded households appears to be small or negligible in Switzerland. FUNDING: University of Fribourg Scholarship Programme for foreign post-doctoral researchers

“AI’s gonna have an impact on everything in society, so it has to have an impact on public health”: a fundamental qualitative descriptive study of the implications of artificial intelligence for public health

Background: Our objective was to determine the impacts of artificial intelligence (AI) on public health practice. Methods: We used a fundamental qualitative descriptive study design, enrolling 15 experts in public health and AI from June 2018 until July 2019 who worked in North America and Asia. We conducted in-depth semi-structured interviews, iteratively coded the resulting transcripts, and analyzed the results thematically. Results: We developed 137 codes, from which nine themes emerged. The themes included opportunities such as leveraging big data and improving interventions; barriers to adoption such as confusion regarding AI’s applicability, limited capacity, and poor data quality; and risks such as propagation of bias, exacerbation of inequity, hype, and poor regulation. Conclusions: Experts are cautiously optimistic about AI’s impacts on public health practice, particularly for improving disease surveillance. However, they perceived substantial barriers, such as a lack of available expertise, and risks, including inadequate regulation. Therefore, investment and research into AI for public health practice would likely be beneficial. However, increased access to high-quality data, research and education regarding the limitations of AI, and development of rigorous regulation are necessary to realize these benefits