Delayed treatment in breast cancer patients during the COVID-19 pandemic: a population health information research infrastructure (PHIRI) case study.

BACKGROUND: The indirect impact of the coronavirus disease 2019 pandemic on healthcare services was studied by assessing changes in the trend of the time to first treatment for women 18 or older who were diagnosed and treated for breast cancer between 2017 and 2021. METHODS: An observational retrospective longitudinal study based on aggregated data from four European Union (EU) countries/regions investigating the time it took to receive breast cancer treatment. We compiled outputs from a federated analysis to detect structural breakpoints, confirming the empirical breakpoints by differences between the trends observed and forecasted after March 2020. Finally, we built several segmented regressions to explore the association of contextual factors with the observed changes in treatment delays. RESULTS: We observed empirical structural breakpoints on the monthly median time to surgery trend in Aragon (ranging from 9.20 to 17.38 days), Marche (from 37.17 to 42.04 days) and Wales (from 28.67 to 35.08 days). On the contrary, no empirical structural breakpoints were observed in Belgium (ranging from 21.25 to 23.95 days) after the pandemic's beginning. Furthermore, we confirmed statistically significant differences between the observed trend and the forecasts for Aragon and Wales. Finally, we found the interaction between the region and the pandemic's start (before/after March 2020) significantly associated with the trend of delayed breast cancer treatment at the population level. CONCLUSIONS: Although they were not clinically relevant, only Aragon and Wales showed significant differences with expected delays after March 2020. However, experiences differed between countries/regions, pointing to structural factors other than the pandemic.

Federated causal inference based on real-world observational data sources: application to a SARS-CoV-2 vaccine effectiveness assessment.

INTRODUCTION: Causal inference helps researchers and policy-makers to evaluate public health interventions. When comparing interventions or public health programs by leveraging observational sensitive individual-level data from populations crossing jurisdictional borders, a federated approach (as opposed to a pooling data approach) can be used. Approaching causal inference by re-using routinely collected observational data across different regions in a federated manner, is challenging and guidance is currently lacking. With the aim of filling this gap and allowing a rapid response in the case of a next pandemic, a methodological framework to develop studies attempting causal inference using federated cross-national sensitive observational data, is described and showcased within the European BeYond-COVID project. METHODS: A framework for approaching federated causal inference by re-using routinely collected observational data across different regions, based on principles of legal, organizational, semantic and technical interoperability, is proposed. The framework includes step-by-step guidance, from defining a research question, to establishing a causal model, identifying and specifying data requirements in a common data model, generating synthetic data, and developing an interoperable and reproducible analytical pipeline for distributed deployment. The conceptual and instrumental phase of the framework was demonstrated and an analytical pipeline implementing federated causal inference was prototyped using open-source software in preparation for the assessment of real-world effectiveness of SARS-CoV-2 primary vaccination in preventing infection in populations spanning different countries, integrating a data quality assessment, imputation of missing values, matching of exposed to unexposed individuals based on confounders identified in the causal model and a survival analysis within the matched population. RESULTS: The conceptual and instrumental phase of the proposed methodological framework was successfully demonstrated within the BY-COVID project. Different Findable, Accessible, Interoperable and Reusable (FAIR) research objects were produced, such as a study protocol, a data management plan, a common data model, a synthetic dataset and an interoperable analytical pipeline. CONCLUSIONS: The framework provides a systematic approach to address federated cross-national policy-relevant causal research questions based on sensitive population, health and care data in a privacy-preserving and interoperable way. The methodology and derived research objects can be re-used and contribute to pandemic preparedness.

Evolution of public hospitals expenditure by healthcare area in the Spanish National Health System: the determinants to pay attention to.

BACKGROUND: In Spain, hospital expenditure represents the biggest share of overall public healthcare expenditure, the most important welfare system directly run by the Autonomous Communities (ACs). Since 2001, public healthcare expenditure has increased well above the GDP growth, and public hospital expenditure increased at an even faster rate. This paper aims at assessing the evolution of need-adjusted public hospital expenditure at healthcare area level (HCA) and its association with utilisation and 'price' factors, identifying the relative contribution of ACs, as the main locus of health policy decisions. METHODS: Ecological study on public hospital expenditure incurred in 198 (HCAs) in 16 Spanish ACs, between 2003 and 2015. Aggregated and annual log-log multilevel models, considering ACs as a cluster, were modelled using administrative data. HCA expenditure was analysed according to differences in population need, utilization and price factors. Standardised coefficients were also estimated, as well as the variance partition coefficients. RESULTS: Between 2003 and 2015, over 59 million hospital episodes were produced in Spain for an overall expenditure of €384,200 million. Need-adjusted public hospital expenditure, at HCA level, was mainly associated to medical and surgical hospitalizations (standardized coefficients 0.32 and 0.28, respectively). The ACs explained 42% of the variance not explained by HCA utilization and 'price' factors. CONCLUSIONS: Utilization, rather than 'price' factors, may be explaining the difference in need-adjusted public hospital expenditure at HCA level in Spain. ACs, third-payers in the fully devolved Spanish National Health System, are responsible for a great deal of the variation in hospital expenditure.

Comparing variation across European countries: building geographical areas to provide sounder estimates.

BACKGROUND: In geographical studies, population distribution is a key issue. An unequal distribution across units of analysis might entail extra-variation and produce misleading conclusions on healthcare performance variations. This article aims at assessing the impact of building more homogeneous units of analysis in the estimation of systematic variation in three countries. METHODS: Hospital discharges for six conditions (congestive heart failure, short-term complications of diabetes, hip fracture, knee replacement, prostatectomy in prostate cancer and percutaneous coronary intervention) produced in Denmark, England and Portugal in 2008 and 2009 were allocated to both original geographical units and new ad hoc areas. New areas were built using Ward's minimum variance methods. The impact of the new areas on variability was assessed using Kernel distribution curves and different statistic of variation such as Extremal Quotient, Interquartile Interval ratio, Systematic Component of Variation and Empirical Bayes statistic. RESULTS: Ward's method reduced the number of areas, allowing a more homogeneous population distribution, yet 20% of the areas in Portugal exhibited less than 100 000 inhabitants vs. 7% in Denmark and 5% in England. Point estimates for Extremal Quotient and Interquartile Interval Ratio were lower in the three countries, particularly in less prevalent conditions. In turn, the Systematic Component of Variation and Empirical Bayes statistic were slightly lower in more prevalent conditions. CONCLUSIONS: Building new geographical areas produced a reduction of the variation in hospitalization rates in several prevalent conditions mitigating random noise, particularly in the smallest areas and allowing a sounder interpretation of the variation across countries.

Potentially avoidable hospitalizations in five European countries in 2009 and time trends from 2002 to 2009 based on administrative data.

INTRODUCTION: Potentially avoidable hospitalizations in chronic conditions are used to evaluate health-care performance. However, evidence comparing different countries at small geographical areas is still scarce. The aim of the present study is to describe and discuss differences in rates and time-trends across health-care areas from five European countries. METHODS: Observational, ecological study, on virtually all discharges produced in five European countries between 2002 and 2009. Potentially avoidable hospitalizations were operationally defined as a joint indicator composed of six chronic conditions. Episodes flagged as potentially avoidable were allocated to 913 geographical health-care areas. Age-sex standardized rates and standardized hospitalization ratios, as well as several statistics of variation, were estimated. RESULTS: Four hundred sixty-two thousand seven hundred and ninety-two episodes were flagged as potentially avoidable. Variation in rates across countries was notable, from 93.7 cases per 10,000 inhabitants in Denmark to 34.8 cases per 10,000 inhabitants in Portugal. Within-country variation was also noteworthy, from 3.12 times among extreme areas in Spain to a 1.46-fold difference in Denmark. The highest systematic variation was found in Denmark (empirical Bayes 0.45) and the lowest in England (empirical Bayes 0.08). Rates and systematic variation remained fairly stable over time, with Denmark and England experiencing a statistically significant decrease (20% and 10%, respectively). Income and educational level, hospital utilization propensity, and region of residence were found to be associated with avoidable admissions. CONCLUSION: The dramatic variation across countries, beyond age and sex differences, and its consistency over time, implies systemic, although differential, behaviour of the five health-care systems with regard to chronic care.

Potential of geographical variation analysis for realigning providers to value-based care. ECHO case study on lower-value indications of C-section in five European countries.

BACKGROUND: Although C-section is a highly effective procedure, literature abounds with evidence of overuse and particularly misuse, in lower-value indications such as low-risk deliveries. This study aims to quantify utilization of C-section in low-risk cases, mapping out areas showing excess-usage in each country and to estimate excess-expenditure as a proxy of the opportunity cost borne by healthcare systems. METHODS: Observational, ecologic study on deliveries in 913 sub-national administrative areas of five European countries (Denmark, England, Portugal, Slovenia and Spain) from 2002 to 2009. The study includes a cross-section analysis with 2009 data and a time-trend analysis for the whole period. Main endpoints: age-standardized utilization rates of C-section in low-risk pregnancies and deliveries per 100 deliveries. Secondary endpoints: Estimated excess-cases per geographical unit of analysis in two scenarios of minimized utilization. RESULTS: C-section is widely used in all examined countries (ranging from 19% of Slovenian deliveries to 33% of deliveries in Portugal). With the exception of Portugal, there are no systematic variations in intensity of use across areas in the same country. Cross-country comparison of lower-value C-section leaves Denmark with 10% and Portugal with 2%, the highest and lowest. Such behaviour was stable over the period of analysis. Within each country, the scattered geographical patterns of use intensity speak for local drivers playing a major role within the national trend. CONCLUSION: The analysis conducted suggests plenty of room for enhancing value in obstetric care and equity in women's access to such within the countries studied. The analysis of geographical variations in lower-value care can constitute a powerful screening tool.

Should policy-makers and managers trust PSI? An empirical validation study of five patient safety indicators in a national health service.

BACKGROUND: Patient Safety Indicators (PSI) are being modestly used in Spain, somewhat due to concerns on their empirical properties. This paper provides evidence by answering three questions: a) Are PSI differences across hospitals systematic -rather than random?; b) Do PSI measure differences among hospital-providers -as opposed to differences among patients?; and, c) Are measurements able to detect hospitals with a higher than "expected" number of cases? METHODS: An empirical validation study on administrative data was carried out. All 2005 and 2006 publicly-funded hospital discharges were used to retrieve eligible cases of five PSI: Death in low-mortality DRGs (MLM); decubitus ulcer (DU); postoperative pulmonary embolism or deep-vein thrombosis (PE-DVT); catheter-related infections (CRI), and postoperative sepsis (PS). Empirical Bayes statistic (EB) was used to estimate whether the variation was systematic; logistic-multilevel modelling determined what proportion of the variation was explained by the hospital; and, shrunken residuals, as provided by multilevel modelling, were plotted to flag hospitals performing worse than expected. RESULTS: Variation across hospitals was observed to be systematic in all indicators, with EB values ranging from 0.19 (CI95%:0.12 to 0.28) in PE-DVT to 0.34 (CI95%:0.25 to 0.45) in DU. A significant proportion of the variance was explained by the hospital, once patient case-mix was adjusted: from a 6% in MLM (CI95%:3% to 11%) to a 24% (CI95%:20% to 30%) in CRI. All PSI were able to flag hospitals with rates over the expected, although this capacity decreased when the largest hospitals were analysed. CONCLUSION: Five PSI showed reasonable empirical properties to screen healthcare performance in Spanish hospitals, particularly in the largest ones.

Timing of surgery for hip fracture and in-hospital mortality: a retrospective population-based cohort study in the Spanish National Health System.

BACKGROUND: While the benefits or otherwise of early hip fracture repair is a long-running controversy with studies showing contradictory results, this practice is being adopted as a quality indicator in several health care organizations. The aim of this study is to analyze the association between early hip fracture repair and in-hospital mortality in elderly people attending public hospitals in the Spanish National Health System and, additionally, to explore factors associated with the decision to perform early hip fracture repair. METHODS: A cohort of 56,500 patients of 60-years-old and over, hospitalized for hip fracture during the period 2002 to 2005 in all the public hospitals in 8 Spanish regions, were followed up using administrative databases to identify the time to surgical repair and in-hospital mortality. We used a multivariate logistic regression model to analyze the relationship between the timing of surgery (< 2 days from admission) and in-hospital mortality, controlling for several confounding factors. RESULTS: Early surgery was performed on 25% of the patients. In the unadjusted analysis early surgery showed an absolute difference in risk of mortality of 0.57 (from 4.42% to 3.85%). However, patients undergoing delayed surgery were older and had higher comorbidity and severity of illness. Timeliness for surgery was not found to be related to in-hospital mortality once confounding factors such as age, sex, chronic comorbidities as well as the severity of illness were controlled for in the multivariate analysis. CONCLUSIONS: Older age, male gender, higher chronic comorbidity and higher severity measured by the Risk Mortality Index were associated with higher mortality, but the time to surgery was not.

Revisiting systematic geographical variations in tonsils surgery in children in the Spanish National Health System: spatiotemporal ecological study on hospital administrative data.

OBJECTIVE: To provide new evidence on how tonsils surgery in children has geographically varied over time in the context of the Spanish National Health System. DESIGN: Observational ecological spatiotemporal study on geographical variations in medical practice, using linked administrative datasets, including virtually all surgeries performed from 2003 to 2015. SETTING: The Spanish National Health System, a quasi-federal structure with 17 autonomous communities (ACs), and 203 healthcare areas (HCAs). PARTICIPANTS: Patients aged 19 and younger residing in the HCAs and ACs. INTERVENTIONS: Tonsillectomy with adenoidectomy (T&A); and tonsillectomies alone (T). MAIN ENDPOINTS: (1) Evolution of T&A and T rates; (2) spatiotemporal variation in the risk of receiving T&A or T surgery at regional level (ACs) and HCAs; and (3) the fraction of the variation (FV) attributed to each of the components of variation-ACs, HCAs, year and interaction ACs year. RESULTS: T&A age-sex standardised rates increased over the period of analysis from 15.2 to 20.9 (5.7 points per 10 000 inhabitants). T alone remained relatively lower than T&A rates, evolving from 3.6 in 2003 to 3.9 in 2015 (0.3 points per 10 000 inhabitants). Most of the risk variation was captured at the HCAs level in both procedures (FV: 55.3% in T&A and 72.5% in T). The ACs level explained 27.6% of the FV in the risk in T&A versus 8% in T. The interaction ACs year was similar in both procedures (FV: 15.5% in T&A and 17.5% in T). The average trend hardly explained 1.46% and 1.83% of the variation, respectively. CONCLUSION: Our study showed wide persistent variations with a steady increase in rates and risk of T&A and a stagnation of T alone, where most of the variation risk was explained at HCA level.

Population-based organized screening by faecal immunochemical testing and colorectal cancer mortality: a natural experiment.

BACKGROUND: Population-based organized screening programmes for colorectal cancer (CRC) are underway worldwide, with many based on the faecal immunochemical test (FIT). No clinical trials assessing FIT compared with no screening are planned, and few studies have assessed the population impact of such programmes. METHODS: Before 2010, 11 out of 50 Spanish provinces initiated population-based organized screening programmes with FIT for an average-risk population aged 50-69 years. We used a quasi-experimental design across Spanish provinces between 1999 and 2016 to evaluate their impact on population age-standardized mortality and incidence rates due to CRC. Difference-in-differences and synthetic control analyses were performed to test for validation of statistical assumptions and to assess the dynamics of screening-associated changes in outcomes over time. RESULTS: No differences in outcome trends between exposed (n = 11) and control (n = 36) provinces were observed for up to 7 years preceding the implementation of screening. Relative to controls, exposed provinces experienced a mean increase in age-standardized incidence of 10.08% [95% confidence interval (CI) (5.09, 15.07)] 2 years after implementation, followed by a reduction in age-standardized mortality rates due to CRC of 8.82% [95% CI (3.77, 13.86)] after 7 years. Results were similar for both women and men. No associated changes were observed in adjacent age bands not targeted by screening, nor for 10 other major causes of death in the exposed provinces. CONCLUSIONS: FIT-based organized screening in Spain was associated with reductions in population colorectal cancer mortality. Further research is warranted in order to assess the replicability and external validity of our findings, and on gender-specific use of FIT in organized screening.

Applying spatio-temporal models to assess variations across health care areas and regions: Lessons from the decentralized Spanish National Health System.

OBJECTIVE: To illustrate the ability of hierarchical Bayesian spatio-temporal models in capturing different geo-temporal structures in order to explain hospital risk variations using three different conditions: Percutaneous Coronary Intervention (PCI), Colectomy in Colorectal Cancer (CCC) and Chronic Obstructive Pulmonary Disease (COPD). RESEARCH DESIGN: This is an observational population-based spatio-temporal study, from 2002 to 2013, with a two-level geographical structure, Autonomous Communities (AC) and Health Care Areas (HA). SETTING: The Spanish National Health System, a quasi-federal structure with 17 regional governments (AC) with full responsibility in planning and financing, and 203 HA providing hospital and primary care to a defined population. METHODS: A poisson-log normal mixed model in the Bayesian framework was fitted using the INLA efficient estimation procedure. MEASURES: The spatio-temporal hospitalization relative risks, the evolution of their variation, and the relative contribution (fraction of variation) of each of the model components (AC, HA, year and interaction AC-year). RESULTS: Following PCI-CCC-CODP order, the three conditions show differences in the initial hospitalization rates (from 4 to 21 per 10,000 person-years) and in their trends (upward, inverted V shape, downward). Most of the risk variation is captured by phenomena occurring at the HA level (fraction variance: 51.6, 54.7 and 56.9%). At AC level, the risk of PCI hospitalization follow a heterogeneous ascending dynamic (interaction AC-year: 17.7%), whereas in COPD the AC role is more homogenous and important (37%). CONCLUSIONS: In a system where the decisions loci are differentiated, the spatio-temporal modeling allows to assess the dynamic relative role of different levels of decision and their influence on health outcomes.

Factors associated with hospitalisations in chronic conditions deemed avoidable: ecological study in the Spanish healthcare system.

OBJECTIVES: Potentially avoidable hospitalisations have been used as a proxy for primary care quality. We aimed to analyse the ecological association between contextual and systemic factors featured in the Spanish healthcare system and the variation in potentially avoidable hospitalisations for a number of chronic conditions. METHODS: A cross-section ecological study based on the linkage of administrative data sources from virtually all healthcare areas (n=202) and autonomous communities (n=16) composing the Spanish National Health System was performed. Potentially avoidable hospitalisations in chronic conditions were defined using the Spanish validation of the Agency for Health Research and Quality (AHRQ) preventable quality indicators. Using 2012 data, the ecological association between potentially avoidable hospitalisations and factors featuring healthcare areas and autonomous communities was tested using multilevel negative binomial regression. RESULTS: In 2012, 151 468 admissions were flagged as potentially avoidable in Spain. After adjusting for differences in age, sex and burden of disease, the only variable associated with the outcome was hospitalisation intensity for any cause in previous years (incidence risk ratio 1.19 (95% CI 1.13 to 1.26)). The autonomous community of residence explained a negligible part of the residual unexplained variation (variance 0.01 (SE 0.008)). Primary care supply and activity did not show any association. CONCLUSIONS: The findings suggest that the variation in potentially avoidable hospitalisations in chronic conditions at the healthcare area level is a reflection of how intensively hospitals are used in a healthcare area for any cause, rather than of primary care characteristics. Whether other non-studied features at the healthcare area level or primary care level could explain the observed variation remains uncertain.

[Trend in potentially avoidable hospitalisations for chronic conditions in Spain]. / Evolución de las hospitalizaciones potencialmente evitables por condiciones crónicas en España.

OBJECTIVE: To analyse the trend in potentially avoidable hospitalisations (PAH) in frail patients or those with chronic conditions in Spain during the period 2002-2013. METHODS: An observational, ecological study was conducted to analyse the trend in age-sex standardised rates of PAH affecting six clinical conditions, and their variation, in the 203 health care areas composing the publicly-funded health system in Spain. RESULTS: During the period 2002-2013, overall PAH standardised rates decreased by 35%, but systematic variation remained moderately high, around 13% above that expected by chance. Angina admissions showed the largest reduction, followed by those for asthma and chronic obstructive pulmonary disease. In contrast, the prevalence of admissions for dehydration doubled. CONCLUSIONS: Despite the decrease in PAH rates, systematic variation among areas remains, indicating differences in chronic care management that lead to distinct healthcare outcomes.

[Variability and opportunity costs among the surgical alternatives for breast cancer]. / Variabilidad y coste de oportunidad de las alternativas quirúrgicas en cáncer de mama.

OBJECTIVE: To analyze medical practice variation in breast cancer surgery (either inpatient-based or day-case surgery), by comparing conservative surgery (CS) plus radiotherapy vs. non-conservative surgery (NCS). We also analyzed the opportunity costs associated with CS and NCS. METHODS: We performed an observational study of age- and sex-standardized rates of CS and NCS, performed in 199 Spanish healthcare areas in 2008-2009. Costs were calculated by using two techniques: indirectly, by using All-Patients Diagnosis Related Groups (AP-DRG) based on hospital admissions, and directly by using full costing from the Spanish Network of Hospital Costs (SNHC) data. RESULTS: Standardized surgery rates for CS and NCS were 6.84 and 4.35 per 10,000 women, with variation across areas ranging from 2.95 to 3.11 per 10,000 inhabitants. In 2009, 9% of CS was performed as day-case surgery, although a third of the health care areas did not perform this type of surgery. Taking the SNHC as a reference, the cost of CS was estimated at 7,078 € and that of NCS was 6,161 €. Using AP-DRG, costs amounted to 9,036 € and 8,526 €, respectively. However, CS had lower opportunity costs than NCS when day-case surgery was performed frequently-more than 46% of cases (following SNHC estimates) or 23% of cases (following AP-DRG estimates). CONCLUSIONS: Day-case CS for breast cancer was found to be the best option in terms of opportunity-costs beyond a specific threshold, when both CS and NCS are elective.