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Purpose: The increasing use of advanced medical technologies to detect adverse events, for instance, artificial intelligence‐assisted technologies, has shown promise in improving various aspects within health care but may also come with substantial expenses. Therefore, understanding the potential economic benefits can guide decision‐making processes regarding implementation. We aimed to estimate the potential cost savings associated with reducing length of stay and avoiding readmissions within the framework of an artificial intelligence‐assisted vital signs monitoring system. Methods: We used data from Danish national registries and coarsened exact matching to estimate the difference in length of stay and probability of readmission among adult in‐hospital patients exposed to and not exposed to serious adverse events. We used these estimates to calculate the maximum potential savings that could be achieved by early detection of adverse events to reduce length of stay and avoid readmissions. Results: Patients exposed to serious adverse events during admission had 2.4 (95% CI: 2.4–2.5) additional hospital bed days and had 14% (95% CI 11%–17%) higher odds of readmissions compared with patients not exposed to such events. A base case scenario yielded maximum potential savings if one patient avoided a serious adverse event of EUR 2040 due to reduced length of stay and EUR 43 due to avoidance of readmissions caused by serious adverse events. Conclusion: Reductions in serious adverse events are associated with decreased healthcare costs due to reduced length of stay and avoided readmissions. Artificial intelligence‐assisted vital signs monitoring systems are one potential approach to reduce serious adverse events, however, the ability of this technology to reduce adverse events remains unclear. Comprehensive prospective analyses of such systems including the intervention and implementation costs are necessary to understand their full economic impact. [ABSTRACT FROM AUTHOR]

Over the last decade, the strain on the English National Health Service (NHS) has increased. This has been especially felt by acute hospital trusts where the volume of admissions has steadily increased. Patient outcomes, including inpatient mortality, vary between trusts. The extent to which these differences are explained by systems-based factors, and whether they are avoidable, is unclear. Few studies have investigated these relationships. A systems-based methodology recognises the complexity of influences on healthcare outcomes. Rather than clinical interventions alone, the resources supporting a patient's treatment journey have near-equal importance. This paper first identifies suitable metrics of resource and demand within healthcare delivery from routinely collected, publicly available, hospital-level data. Then it proceeds to use univariate and multivariable linear regression to associate such systems-based factors with standardised mortality. Three sequential cross-sectional analyses were performed, spanning the last decade. The results of the univariate regression analyses show clear relationships between five out of the six selected predictor variables and standardised mortality. When these five predicators are included within a multivariable regression analysis, they reliably explain approximately 36% of the variation in standardised mortality between hospital trusts. Three factors are consistently statistically significant: the number of doctors per hospital bed, bed occupancy, and the percentage of patients who are placed in a bed within four hours after a decision to admit them. Of these, the number of doctors per bed had the strongest effect. Linear regression assumption testing and a robustness analysis indicate the observations have internal validity. However, our empirical strategy cannot determine causality and our findings should not be interpreted as established causal relationships. This study provides hypothesis-generating evidence of significant relationships between systems-based factors of healthcare delivery and standardised mortality. These have relevance to clinicians and policymakers alike. While identifying causal relationships between the predictors is left to the future, it establishes an important paradigm for further research. [ABSTRACT FROM AUTHOR]

Background Pay-for-performance (P4P) programmes to incentivise health providers to improve quality of care have been widely implemented globally. Despite intuitive appeal, evidence on the effectiveness of P4P is mixed, potentially due to differences in how schemes are designed. We exploited municipality variation in the design features of Brazil's National Programme for Improving Primary Care Access and Quality (PMAQ) to examine whether performance bonuses given to family health team workers were associated with changes in the quality of care and whether the size of bonus mattered. Methods and findings For this quasi-experimental study, we used a difference-in-differences approach combined with matching. We compared changes over time in the quality of care delivered by family health teams between (bonus) municipalities that chose to use some or all of the PMAQ money to provide performance-related bonuses to team workers with (nonbonus) municipalities that invested the funds using traditional input-based budgets. The primary outcome was the PMAQ score, a quality of care index on a scale of 0 to 100, based on several hundred indicators (ranging from 598 to 660) of health care delivery. We did one-to-one matching of bonus municipalities to nonbonus municipalities based on baseline demographic and economic characteristics. On the matched sample, we used ordinary least squares regression to estimate the association of any bonus and size of bonus with the prepost change over time (between November 2011 and October 2015) in the PMAQ score. We performed subgroup analyses with respect to the local area income of the family health team. The matched analytical sample comprised 2,346 municipalities (1,173 nonbonus municipalities; 1,173 bonus municipalities), containing 10,275 family health teams that participated in PMAQ from the outset. Bonus municipalities were associated with a 4.6 (95% CI: 2.7 to 6.4; p < 0.001) percentage point increase in the PMAQ score compared with nonbonus municipalities. The association with quality of care increased with the size of bonus: the largest bonus group saw an improvement of 8.2 percentage points (95% CI: 6.2 to 10.2; p < 0.001) compared with the control. The subgroup analysis showed that the observed improvement in performance was most pronounced in the poorest two-fifths of localities. The limitations of the study include the potential for bias from unmeasured time-varying confounding and the fact that the PMAQ score has not been validated as a measure of quality of care. Conclusions Performance bonuses to family health team workers compared with traditional input-based budgets were associated with an improvement in the quality of care., Author(s): Nasser Fardousi 1, Everton Nunes da Silva 2, Roxanne Kovacs 1, Josephine Borghi 1, Jorge O. M. Barreto 3, Søren Rud Kristensen 4, Juliana Sampaio 5, Helena Eri Shimizu [...]

Background: The burden of patient safety incidents (PSIs) is often characterized by their impact on mortality, morbidity, and treatment costs. Few studies have attempted to estimate the impact of PSIs on patients' health-related quality of life (HRQoL) and the studies that have made such estimates primarily focus on a narrow set of incidents. The aim of this paper is to estimate the impact of PSIs on HRQoL of patients undergoing elective hip and knee surgery in England. Patients and methods: A unique linked longitudinal data set consisting of patient-reported outcome measures for patients with hip and knee replacements linked to Hospital Episode Statistics (HES) collected between 2013/14 and 2016/17 was examined. Patients with any of nine US Agency for Healthcare Research and Quality (AHRQ) PSI indicators were identified. HRQoL was measured using the general EuroQol five dimensions questionnaire (EQ-5D) before and after surgery. Exploiting the longitudinal structure of the data, exact matching was combined with difference in differences to estimate the impact of experiencing a PSI on HRQoL and its individual dimensions, comparing HRQoL improvements after surgery in similar patients with and without a PSI in a retrospective cohort study. This design compares the change in HRQoL before and after surgery in patients who experience a PSI to those who do not. Results: The sample comprised 190 697 and 204 649 observations for patients undergoing hip replacement and knee replacement respectively. For six out of nine PSIs, patients who experienced a PSI reported improvements in HRQoL that were 14-23% lower than those who did not experience a PSI during surgery. Those who experienced a PSI were also more likely to report worse health states after surgery than those without a PSI on all five dimensions of HRQoL. Conclusion: PSIs are associated with a substantial negative impact on patients' HRQoL. [ABSTRACT FROM AUTHOR]

Objectives: To examine the effectiveness of two integrated care models ('vanguards') in Salford and South Somerset in England, United Kingdom, in relation to patient experience, health outcomes and costs of care (the 'triple aim'). Methods: We used difference-in-differences analysis combined with propensity score weighting to compare the two care model sites with control ('usual care') areas in the rest of England. We estimated combined and separate annual effects in the three years following introduction of the new care model, using the national General Practice Patient Survey (GPPS) to measure patient experience (inter-organisational support with chronic condition management) and generic health status (EQ-5D); and hospital episode statistics (HES) data to measure total costs of secondary care. As secondary outcomes we measured proxies for improved prevention: cost per user of secondary care (severity); avoidable emergency admissions; and primary care utilisation. Results: Both intervention sites showed an increase in total costs of secondary care (approximately £74 per registered patient per year in Salford, £45 in South Somerset) and cost per user of secondary care (£130–138 per person per year). There were no statistically significant effects on health status or patient experience of care. There was a more apparent short-term negative effect on measured outcomes in South Somerset, in terms of increased costs and avoidable emergency admissions, but these reduced over time. Conclusion: New care models such as those implemented within the Vanguard programme in England might lead to unintended secondary care cost increases in the short to medium term. Cost increases appeared to be driven by average patient severity increases in hospital. Prevention-focused population health management models of integrated care, like previous more targeted models, do not immediately improve the health system's triple aim. [ABSTRACT FROM AUTHOR]