BACKGROUND: This study demonstrates that digital maturity contributes to strengthened quality and safety performance outcomes in US hospitals. Advanced digital maturity is associated with more digitally enabled work environments with automated flow of data across information systems to enable clinicians and leaders to track quality and safety outcomes. This research illustrates that an advanced digitally enabled workforce is associated with strong safety leadership and culture and better patient health and safety outcomes.
OBJECTIVE: This study aimed to examine the relationship between digital maturity and quality and safety outcomes in US hospitals.
METHODS: The data sources were hospital safety letter grades as well as quality and safety scores on a continuous scale published by The Leapfrog Group. We used the digital maturity level (measured using the Electronic Medical Record Assessment Model [EMRAM]) of 1026 US hospitals. This was a cross-sectional, observational study. Logistic, linear, and Tweedie regression analyses were used to explore the relationships among The Leapfrog Group\'s Hospital Safety Grades, individual Leapfrog safety scores, and digital maturity levels classified as advanced or fully developed digital maturity (EMRAM levels 6 and 7) or underdeveloped maturity (EMRAM level 0). Digital maturity was a predictor while controlling for hospital characteristics including teaching status, urban or rural location, hospital size measured by number of beds, whether the hospital was a referral center, and type of hospital ownership as confounding variables. Hospitals were divided into the following 2 groups to compare safety and quality outcomes: hospitals that were digitally advanced and hospitals with underdeveloped digital maturity. Data from The Leapfrog Group\'s Hospital Safety Grades report published in spring 2019 were matched to the hospitals with completed EMRAM assessments in 2019. Hospital characteristics such as number of hospital beds were obtained from the CMS database.
RESULTS: The results revealed that the odds of achieving a higher Leapfrog Group Hospital Safety Grade was statistically significantly higher, by 3.25 times, for hospitals with advanced digital maturity (EMRAM maturity of 6 or 7; odds ratio 3.25, 95% CI 2.33-4.55).
CONCLUSIONS: Hospitals with advanced digital maturity had statistically significantly reduced infection rates, reduced adverse events, and improved surgical safety outcomes. The study findings suggest a significant difference in quality and safety outcomes among hospitals with advanced digital maturity compared with hospitals with underdeveloped digital maturity.

BACKGROUND: Bariatric surgery aims for optimal patient outcomes, often evaluated through the percentage total weight loss (%TWL). Quality registries employ funnel plots for outcome comparisons between hospitals. However, funnel plots are traditionally used for dichotomous outcomes, requiring %TWL to be dichotomized, potentially limiting feedback quality. This study evaluates whether a funnel plot around the median %TWL has better discriminatory performance than binary funnel plots for achieving at least 20% and 25% TWL.
METHODS: All hospitals performing bariatric surgery were included from the Dutch Audit for Treatment of Obesity. A funnel plot around the median was constructed using 5-year %TWL data. Hospitals positioned above the 95% control limit were colored green and those below red. The same hospitals were plotted in the binary funnel plots for 20% and 25% TWL and colored according to their performance in the funnel plot around the median. We explored the hospital\'s procedural mix in relation to %TWL performance as possible explanatory factors.
RESULTS: The median-based funnel plot identified four underperforming and four outperforming hospitals, while only one underperforming and no outperforming hospitals were found with the binary funnel plot for 20% TWL. The 25% TWL binary funnel plot identified two underperforming and three outperforming hospitals. The proportion of sleeve gastrectomies performed per hospital may explain part of these results as it was negatively associated with median %TWL (β =  - 0.09, 95% confidence interval [- 0.13 to - 0.04]).
CONCLUSIONS: The funnel plot around the median discriminated better between hospitals with significantly worse and better performance than funnel plots for dichotomized %TWL outcomes.

Over the past 25 years, the gap between the increase in health insurance costs and workers\' wages has significantly expanded. This trend has led to significant concerns about healthcare affordability, with surveys revealing conflicting opinions regarding whether hospitals or health insurance companies bear the blame for escalating costs. To better understand these dynamics, we examined consumer price indices for health insurance, hospital services, and professional services from 2006 to 2023 using Bureau of Labor Statistics data. Our analysis shows that the hospital price index rose steadily between 2006 and 2023, faster than insurance premiums or professional services. To examine whether differences in underlying costs are driving higher hospital price increases, we evaluated the profit margins of hospitals and health insurance companies using the National Academy for State Health Policy\'\'s Hospital Cost Tool and National Association of Insurance Commissioners Industry Reports. Our findings reveal that hospitals (for-profit and nonprofit) have consistently maintained higher profit margins than insurance companies. As health insurance costs continue to weigh heavily on working Americans, our analysis suggests that high hospital prices drive insurance premiums.

This study proposes a multi-level model of institutional innovation in the healthcare sector-in other words, field-level institutional change pressures that start as network-level institutional innovation by hospitals and government for their organizational performance, with an emphasis on the effect of organizational-level construct-knowledge creation capabilities. A case study using in-depth interviews and a historical inquiry approach has been used to qualitatively analyze our cases during the development of Taiwan\'s National Health Insurance (NHI). Our results propose a multi-level explanation of institutional innovation by showing how field-level institutional change pressures can stimulate the government\'s institutional innovation at the network level. Moreover, knowledge creation capabilities may positively influence the government hospitals\' ongoing institutional change pressures induced institutional innovation activity for their performance at the organizational level in an institutional setting. This study contributes to health organization management researchers and administrators by developing explanations of institutional innovation and creating a much-needed multi-level insight into hospital behavior in the highly institutionalized healthcare sector.

Although there have been studies that compared outcomes of patients with acute myocardial infarction (AMI) across countries, little focus has been placed on institutional variance of outcomes. The aim of the present study was to compare institutional variance in mortality following percutaneous coronary intervention (PCI) for AMI and factors explaining this variance across different health systems.
Data on inpatients who underwent PCI for AMI in 2016 were obtained from the National Health Insurance Data Sharing Service in Korea, the Diagnosis Procedure Combination (DPC) Study Group Database in Japan, and the National Health Insurance Research Database (NHIRD) in Taiwan. Multilevel analyses with inpatient mortality as the outcome and the hierarchical structure of patients nested within hospitals were conducted, adjusting for common patient-level and hospital-level variables. We compared the intraclass correlation coefficient (ICC) and the proportion of variance explained by hospital-level characteristics across the three health systems.
There were 17 351 patients from 160 Korean hospitals, 29 804 patients from 660 Japanese hospitals, and 10 863 patients from 104 Taiwanese hospitals included in the analysis. Inpatient mortality rates were 6.3%, 7.3%, and 6.0% in Korea, Japan, and Taiwan, respectively. After adjusting for patient and hospital characteristics, Taiwan had the lowest variation in mortality (ICC, 1.8%), followed by Korea (2.2%) and then Japan (4.5%). The measured hospital characteristics explained 38%, 19%, and 9% of the institutional variance in Korea, Taiwan, and Japan, respectively.
Korea, Japan, and Taiwan had similarly uniform outcomes across hospitals for patients undergoing PCI for AMI. However, Japan had a relatively large institutional variance in mortality and a lower proportion of variation explainable by hospital characteristics, compared with Korea and Taiwan.

UNASSIGNED: During the pandemic of COVID-19, the function and performance of hospitals have been affected by various economic-financial and management aspects. The aim of the current study was to assess the process of therapeutic care delivery and also the economic-financial functions of the selected hospitals before and after COVID-19.
UNASSIGNED: This research is a descriptive-analytical study and a cross-sectional-comparative study in terms of time, and it was conducted in several selected teaching hospitals of Iran University of Medical Sciences. A purposeful and convenient sampling method was used. The data has been collected using the standard research tool (standard checklist of the Ministry of Health) in the two areas of financial-economic and healthcare performance (such as Data of financial and economic indicators such as direct and indirect costs, liquidity ratio and profitability index as well as key performance indicators of hospitals such as bed occupancy ratio (BOR; %), average length of stay (ALOS), bed turnover rate (BTR), bed turnover distance rate (BTIR) and hospital mortality rate (HMR), physician-to-bed ratio and nurse-to-bed ratio) of hospitals in two times before and after the outbreak of COVID-19 (time period 2018 to 2021). The data was collected from 2018 to 2021. Pearson/Spearman regression was used for the evaluation of the relationship between variables using SPSS 22.
UNASSIGNED: This research showed the admission of COVID-19 patients caused a change in the indicators we evaluated. ALOS (-6.6%), BTIR (-40.7%), and discharge against medical advice (-7.0%) decreased from 2018 to 2021. BOR; % (+5.0%), occupy bed days (+6.6%), BTR (+27.5%, HMR (+50%), number of inpatients (+18.8%), number of discharges (+13.1%), number of surgeries (+27.4%), nurse-per-bed ratio (+35.9%), doctor-per-bed ratio (+31.0%) increased in the same period of time. The profitability index was correlated to all of the performance indicators except for the net death rate. Higher length of stay and turnover interval had a negative effect on the profitability index while higher bed turnover rate, bed occupancy ratio, bed day, number of inpatient admission, and number of surgery had a positive effect on the profitability index.
UNASSIGNED: It has been shown from the beginning of the COVID-19 pandemic, the performance indicators of the studied hospitals were negatively affected. As a consequence of the COVID-19 epidemic, many hospitals were not able to deal with the negative financial and medical outcomes of this crisis due to a significant decrease in income and a double increase in expenses.

The coronavirus infection COVID-19 killed millions of people around the world in 2019-2022. Hospitals were in the forefront in the battle against the pandemic. This paper proposes a novel approach to assess the effectiveness of hospitals in saving lives. We empirically estimate the production function of COVID-19 deaths among hospital inpatients, applying Heckman\'s two-stage approach to correct for the bias caused by a large number of zero-valued observations. We subsequently assess performance of hospitals based on regression residuals, incorporating contextual variables to convex quantile regression. Data of 187 hospitals in England over a 35-week period from April to December 2020 is divided in two sub-periods to compare the structural differences between the first and second waves of the pandemic. The results indicate significant performance improvement during the first wave, however, learning by doing was offset by the new mutated virus straits during the second wave. While the elderly patients were at significantly higher risk during the first wave, their expected mortality rate did not significantly differ from that of the general population during the second wave. Our most important empirical finding concerns large and systematic performance differences between individual hospitals: larger units proved more effective in saving lives, and hospitals in London had a lower mortality rate than the national average.

BACKGROUND: The effect of hospital participation in the Japan Nosocomial Infection Surveillance (JANIS) programme on surgical site infection (SSI) prevention is unknown.
OBJECTIVE: To determine if participation in the JANIS programme improved hospital performance in SSI prevention.
METHODS: This retrospective before-after study analysed Japanese acute care hospitals that joined the SSI component of the JANIS programme in 2013 or 2014. The study participants comprised patients who had undergone surgeries targeted for SSI surveillance at JANIS hospitals between 2012 and 2017. Exposure was defined as the receipt of an annual feedback report 1 year after participation in the JANIS programme. The changes in standardized infection ratio (SIR) from 1 year before to 3 years after exposure were calculated for 12 operative procedures: appendectomy, liver resection, cardiac surgery, cholecystectomy, colon surgery, caesarean section, spinal fusion, open reduction of long bone fracture, distal gastrectomy, total gastrectomy, rectal surgery, and small bowel surgery. Logistic regression models were used to analyse the association of each post-exposure year with the occurrence of SSI.
RESULTS: In total, 157,343 surgeries at 319 hospitals were analysed. SIR values declined after participation in the JANIS programme for procedures such as liver resection and cardiac surgery. Participation in the JANIS programme was significantly associated with reduced SIR for several procedures, especially after 3 years. The odds ratios in the third post-exposure year (reference: pre-exposure year) were 0.86 [95% confidence interval (CI) 0.79-0.84] for colon surgery, 0.72 (95% CI 0.56-0.92) for distal gastrectomy, and 0.77 (95% CI 0.59-0.99) for total gastrectomy.
CONCLUSIONS: Participation in the JANIS programme was associated with improved SSI prevention performance in several procedures in Japanese hospitals after 3 years.

Patient satisfaction is a crucial indicator for assessing quality of care in healthcare settings. However, patient satisfaction benchmark for cancer hospitals in China is not established.
To examine patient satisfaction levels in tertiary cancer hospitals in China, and inter-hospital variations after case-mix adjustment.
A nationwide cross-sectional hospital performance survey conducted from January to March 2021.
At 30 tertiary cancer hospitals in China.
A total of 4,847 adult inpatients consecutively recruited at 30 tertiary cancer hospitals were included.
Patient characteristics included demographic characteristics (sex, age, education, and annual family income), clinical characteristics (cancer type, cancer stage, self-reported health status, and length of stay), and actual respondents of questionnaire.
Patient satisfaction was measured using 23 items covering five aspects, administrative process, hospital environment, medical care, symptom management, and overall satisfaction. Responses to each item were recorded using a 5-point Likert scale. Patient satisfaction level for each aspect was described at individual and hospital levels. Using multilevel logistic regression, patient characteristics associated with patient satisfaction were examined as case-mix adjusters and inter-hospital variation were determined.
The satisfaction rates for symptom management, administrative process, hospital environment, overall satisfaction, and medical care aspects were 74.56, 81.70, 84.18, 84.26, and 90.86% with a cut-off value of 4, respectively. Significant predictors of patient satisfaction included sex, age, cancer type, cancer stage, self-reported health status, and actual respondent (representative or patient) (all P < 0.05). The ranking of the hospitals\' performance in satisfaction was altered after the case-mix adjustment was made. But even after the adjustment, significant variation in satisfaction among hospitals remained.
This study pointed to symptom management as a special area, to which a keen attention should be paid by policymakers and hospital administrators. Significant variation in satisfaction among hospitals remained, implying that future studies should examine major factors affecting the variation. In review, target interventions are needed in low-performing hospitals.

BACKGROUND: Very limited empirical research has been done on operational flexibility management in the healthcare industry, especially in hospital settings. This study aimed to propose a model of the effects of operational flexibility on hospital performance through management capability and employee engagement as mediating variables.
METHODS: The proposed model is validated through an empirical study among 480 clinical and administrative staff from five hospitals in Jordan. Structural equation modeling and confirmatory factor analysis were the main techniques used to validate the model and examine the hypotheses.
RESULTS: Operational flexibility was demonstrated to have a positively significant impact on hospital performance, management capability, and employee engagement. Employee engagement was demonstrated to positively impact hospital performance. Management capability had a significant result on hospital performance without having a clear impact. In addition, management capability and employee engagement played a major role as partial mediating effects between operational flexibility and hospital performance, and there is a role for employee engagement as a partial mediating effect between management capability and hospital performance.
CONCLUSIONS: Significant progress has been achieved in hospital management, especially in terms of operational flexibility, management capability, and staff engagement.