Within and across country variations in treatment of patients with heart failure and diabetes.

OBJECTIVE: To compare within-country variation of health care utilization and spending of patients with chronic heart failure (CHF) and diabetes across countries. DATA SOURCES: Patient-level linked data sources compiled by the International Collaborative on Costs, Outcomes, and Needs in Care across nine countries: Australia, Canada, England, France, Germany, New Zealand, Spain, Switzerland, and the United States. DATA COLLECTION METHODS: Patients were identified in routine hospital data with a primary diagnosis of CHF and a secondary diagnosis of diabetes in 2015/2016. STUDY DESIGN: We calculated the care consumption of patients after a hospital admission over a year across the care pathway-ranging from primary care to home health nursing care. To compare the distribution of care consumption in each country, we use Gini coefficients, Lorenz curves, and female-male ratios for eight utilization and spending measures. PRINCIPAL FINDINGS: In all countries, rehabilitation and home nursing care were highly concentrated in the top decile of patients, while the number of drug prescriptions were more uniformly distributed. On average, the Gini coefficient for drug consumption is about 0.30 (95% confidence interval (CI): 0.27-0.36), while it is, 0.50 (0.45-0.56) for primary care visits, and more than 0.75 (0.81-0.92) for rehabilitation use and nurse visits at home (0.78; 0.62-0.9). Variations in spending were more pronounced than in utilization. Compared to men, women spend more days at initial hospital admission (+5%, 1.01-1.06), have a higher number of prescriptions (+7%, 1.05-1.09), and substantially more rehabilitation and home care (+20% to 35%, 0.79-1.6, 0.99-1.64), but have fewer visits to specialists (-10%; 0.84-0.97). CONCLUSIONS: Distribution of health care consumption in different settings varies within countries, but there are also some common treatment patterns across all countries. Clinicians and policy makers need to look into these differences in care utilization by sex and care setting to determine whether they are justified or indicate suboptimal care.

An overview of future EU health systems. An insight into governance, primary care, data collection and citizens' participation.

Background: Health systems in the European Union (EU) are being questioned over their effectiveness and sustainability. In pursuing both goals, they have to conciliate coexisting, not always aligned, realities. Methods: This paper originated from a workshop entitled 'Health systems for the future' held at the European Parliament. Experts and decision makers were asked to discuss measures that may increase the effectiveness and sustainability of health systems, namely: (i) increasing citizens' participation; (ii) the importance of primary care in providing integrated services; (iii) improving the governance and (iv) fostering better data collection and information channels to support the decision making process. Results: In the parliamentary debate, was discussed the concept that, in the near future, health systems' effectiveness and sustainability will very much depend on effective access to integrated services where primary care is pivotal, a clearer shift from care-oriented systems to health promotion and prevention, a profound commitment to good governance, particularly to stakeholders participation, and a systematic reuse of data meant to build health data-driven learning systems. Conclusions: Many health issues, such as future health systems in the EU, are potentially transformative and hence an intense political issue. It is policy-making leadership that will mostly determine how well EU health systems are prepared to face future challenges.

The merry-go-round of approval, pricing and reimbursement of drugs against the Hepatitis C virus infection in Spain.

Given that drug innovation has been largely away from breakthroughs, arguing that a new drug recently approved and reaching the market is downright effective, safe and affordable is actually parlous. The soaring costs of an increasing number of new drugs (specially for cancer and rare diseases) threaten to supersede societal absorbing capacity, competing with other health and outside health sector resources. Some health systems are not making headways towards solving the current conundrum of keeping path with the state of the art regulatory mechanisms in delivering cost-effective, equitable and affordable treatments. The way pricing and reimbursement decisions have been made in Spain regarding the recent wave of new drugs against the hepatitis C virus could be one case in point. This paper analyses the path of decision-making and the positioning of the relevant actors in this case, that has set a cumbersome precedent (earmarked fund) for the Spanish National Health Service. It also stresses the need for current decision-making mechanisms on approval, pricing, coverage and reimbursement in Spain to move to a transparent regulatory system, avoiding improvisation and incorporating the highest regulatory standards that other countries have in place.

[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.

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.

Shared component modelling as an alternative to assess geographical variations in medical practice: gender inequalities in hospital admissions for chronic diseases.

BACKGROUND: Small area analysis is the most prevalent methodological approach in the study of unwarranted and systematic variation in medical practice at geographical level. Several of its limitations drive researchers to use disease mapping methods -deemed as a valuable alternative. This work aims at exploring these techniques using - as a case of study- the gender differences in rates of hospitalization in elderly patients with chronic diseases. METHODS: Design and study setting: An empirical study of 538,358 hospitalizations affecting individuals aged over 75, who were admitted due to a chronic condition in 2006, were used to compare Small Area Analysis (SAVA), the Besag-York-Mollie (BYM) modelling and the Shared Component Modelling (SCM). Main endpoint: Gender spatial variation was measured, as follows: SAVA estimated gender-specific utilization ratio; BYM estimated the fraction of variance attributable to spatial correlation in each gender; and, SCM estimated the fraction of variance shared by the two genders, and those specific for each one. RESULTS: Hospitalization rates due to chronic diseases in the elderly were higher in men (median per area 21.4 per 100 inhabitants, interquartile range: 17.6 to 25.0) than in women (median per area 13.7 per 100, interquartile range: 10.8 to 16.6). Whereas Utilization Ratios showed a similar geographical pattern of variation in both genders, BYM found a high fraction of variation attributable to spatial correlation in both men (71%, CI95%: 50 to 94) and women (62%, CI95%: 45 to 77). In turn, SCM showed that the geographical admission pattern was mainly shared, with just 6% (CI95%: 4 to 8) of variation specific to the women component. CONCLUSIONS: Whereas SAVA and BYM focused on the magnitude of variation and on allocating where variability cannot be due to chance, SCM signalled discrepant areas where latent factors would differently affect men and women.