Implementing the European Core Health Indicators (ECHI) in the Netherlands: an overview of data availability.

BACKGROUND: The European Commission, together with the European Union (EU) Member States, developed a core set of indicators for monitoring public health in the EU, the European Core Health Indicators (ECHI) shortlist. From 2009 to 2012 developmental work on the ECHI indicators continued within the framework of the Joint Action for European Community Health Indicators and Monitoring (ECHIM). In this article, we give the current state of affairs on the availability of data for the ECHI indicators in the Netherlands and show what progress has been made over the past 5 years. The information provided serves as an illustration of the challenges encountered in a European country when working on harmonising national data collections with international data delivery requirements. METHODS: To assess data availability, we consulted Dutch data experts and relevant websites and reports on health monitoring activities. We compared the available Dutch data with the definitions, preferred data sources and relevant dimensions as requested by ECHI. RESULTS: The Netherlands can provide data for 66 of the 75 ECHI indicators for which availability could be assessed: for all of the 48 ECHI indicators that can be extracted from international databases and for 18 of the 27 indicators not available from international databases. Breakdowns by socio-economic status and region are not possible for 23 (35%) of the total of 66 indicators for which data are available and for 21 (32%) of these 66 indicators the definition is not exactly the same as requested by ECHIM. Since 2009, better estimates have become available for low birth weight, practising physicians and practising nurses. Moreover, several European initiatives to improve harmonised data collection are expected to have a positive effect on data availability for the Netherlands. Such initiatives should become sustainable in order to provide possibilities for monitoring trends. The scattered data ownership in the Netherlands complicates the coordination work for international data deliveries. CONCLUSION: Data availability in the Netherlands is good. Since 2009, several Dutch and European developments in harmonising data collection have contributed or will significantly contribute to improvements in the data situation for the ECHI indicators in the Netherlands.

[Standardised in-hospital mortality decreasing over time]. / Gestandaardiseerde ziekenhuissterfte daalt in de tijd.

OBJECTIVE: To study the changes in standardised in-hospital mortality in the period 2005 to 2010. DESIGN: Retrospective, descriptive study. METHOD: Data from the National Medical Registration (LMR) for the period 2005 to 2010 were used to calculate a time-series of the standardised in-hospital mortality rate. Predicted mortality was calculated for 50 principle diagnosis groups using logistic regression models with 8 explanatory variables. This was used, in combination with actual in-hospital mortality, to calculate the Time-Series Standardised Hospital Mortality Ratio (TSHMR). RESULTS: The TSHMR decreased significantly each year in the period 2005 to 2010. The greatest decrease was from 2009 to 2010, which was partly due to a registration effect. Total age- and sex-standardised mortality in the population also decreased in the period 2005 to 2010, mortality out of hospital decreasing less than in-hospital mortality. Standardised hospital mortality decreased significantly in all adult age categories (≥ 25 years of age). The TSHMR fell most sharply in the diagnosis groups 'gastrointestinal haemorrhage' and 'deficiencies and other anaemias'. The diagnosis groups 'heart valve disorders' and 'aspiration pneumonia due to food or vomitus' showed the smallest decrease in TSHMR, and this decrease was not significant. CONCLUSION: The decrease in standardised in-hospital mortality shows that the risk of dying in hospital has decreased substantially in the past few years. The size of the decrease in TSHMR differed per diagnosis group. There can be many reasons for this decrease in in-hospital mortality, including improved quality of care; however, it may also be due to, for instance, changes in hospital admission and discharge policies.

Hospital stroke volume and case-fatality revisited.

BACKGROUND: A few studies have found an inverse association between hospital patient volume and case-fatality among stroke patients. However, the different stroke categorizations used in these studies might have influenced the findings. Furthermore, the relevance of the association observed remains questionable given that the relatively small magnitude may not support volume-based referral policies. We re-examined this association in a large nationwide study, paying attention to the influence of volume categorizations. METHODS: Applying multilevel logistic regression, we re-examined the relationship between hospital stroke volume and 7-day case-fatality using admissions data obtained from Statistics Netherlands on 73,077 stroke patients for the years 2000 to 2004. Different cut-offs were used to categorize hospitals in volume groups. We also examined the implications of a volume based referral strategy. RESULTS: Stroke patients in high-volume hospitals had decreased risk of dying within 7 days of admission even when different hospital categorizations are applied. For instance, the odds ratio was 0.45(95% CI 0.20-0.99) in high-volume(>200 case-volume) versus low-volume(<50 case-volume) hospitals, but 0.89(95% CI 0.79-1.00) in high-volume(>250 case-volume) versus low-volume (< or =250 case-volume) hospitals. Ignoring travel time and workload implications an optimistic volume-based referral policy would save 183 patients when all patients are referred to the >200 case-volume hospital. A nontransfer policy aimed at reducing mortality by 10% in all those hospitals would save 1260 patients. CONCLUSION: Stroke patients in low-volume versus high-volume hospitals have higher odds of dying. This finding may not lend itself to a substantial volume-based referral strategy.

Mortality after elective abdominal aortic aneurysm repair.

OBJECTIVE: Purpose of this study is to provide detailed age- and gender-specific mortality risks of patients hospitalized for elective AAA repair. SUMMARY BACKGROUND DATA: Whether to perform elective abdominal aortic aneurysm (AAA) surgery is balancing the risks of natural history against the risks of surgical intervention. Literature is lacking mortality risks after elective AAA repair with stratification by both age and gender. METHODS: Mortality risks for 28 days, 1 year, and 5 years were derived from a nationwide cohort of patients hospitalized for elective AAA repair in 1997 or 2000. This cohort was formed through linkage of the Hospital Discharge Register with the Dutch Population Register. The relations between demographics, medical history and mortality were studied by Cox regression. RESULTS: A total of 3457 patients were identified; 86% males, mean age 72 +/- 8.0 years. Mortality risks after elective AAA repair increased with age: 28-day mortality ranged from 3.3% to 27.1% in men and 3.8% to 54.3% in women, 5-year mortality from 12.9% to 78.1% in men and 24.3% to 91.3% in women. Higher age, congestive heart failure, cerebrovascular disease and diabetes mellitus were independent risk factors for 5-years mortality. CONCLUSIONS: Mortality risks after elective AAA repair are strongly age-related. Age, gender, and comorbidities should be taken into account when deciding on surgery. A general threshold of 55 mm for surgery might not be justified for all patients.

Mortality in Dutch hospitals: trends in time, place and cause of death after admission for myocardial infarction and stroke. An observational study.

BACKGROUND: Patterns in time, place and cause of death can have an important impact on calculated hospital mortality rates. Objective is to quantify these patterns following myocardial infarction and stroke admissions in Dutch hospitals during the period 1996-2003, and to compare trends in the commonly used 30-day in-hospital mortality rates with other types of mortality rates which use more extensive follow-up in time and place of death. METHODS: Discharge data for all Dutch admissions for index conditions (1996-2003) were linked to the death certification registry. Then, mortality rates within the first 30, 90 and 365 days following admissions were analyzed for deaths occurring within and outside hospitals. RESULTS: Most deaths within a year after admission occurred within 30 days (60-70%). No significant trends in this distribution of deaths over time were observed. Significant trends in the distribution over place of death were observed for both conditions. For myocardial infarction, the proportion of deaths after transfer to another hospital has doubled from 1996-2003. For stroke a significant rise of the proportion of deaths outside hospital was found. For MI the proportion of deaths attributed to a circulatory disease has significantly fallen overtime. Seven types of hospital mortality indicators, different in scope and observation period, all show a drop of hospital mortality for both MI and stroke over the period 1996-2003. For stroke the observed absolute reduction in death rate increases for the first year after admission, for MI the observed drop in 365-day overall mortality almost equals the observed drop in 30-day in hospital mortality over 1996-2003. CONCLUSION: Changes in the timing, place and causes of death following admissions for myocardial infarction and stroke have important implications for the definitions of in-hospital and post-admission mortality rates as measures of hospital performance. Although necessary for understanding mortality patterns over time, including within mortality rates deaths which occur outside hospitals and after longer periods following index admissions remain debatable and may not reflect actual hospital performance but probably mirrors transfer, efficiency, and other health care policies.

Acute myocardial infarction incidence and hospital mortality: routinely collected national data versus linkage of national registers.

BACKGROUND AND OBJECTIVE: To compare levels of and trends in incidence and hospital mortality of first acute myocardial infarction (AMI) based on routinely collected hospital morbidity data and on linked registers. Cases taken from routine hospital data are a mix of patients with recurrent and first events, and double counting occurs when cases are admitted for an event several times during 1 year. By linkage of registers, recurrent events and double counts can be excluded. STUDY DESIGN AND SETTING: In 1995 and 2000, 28,733 and 25,864 admissions for AMI were registered in the Dutch national hospital discharge register. Linkage with the population register yielded 21,565 patients with a first AMI in 1995 and 20,414 in 2000. RESULTS: In 1995 and 2000, the incidence based on the hospital register was higher than based on the linked registers in men (22% and 23% higher) and women (18% and 20% higher). In both years, hospital mortality based on the hospital register and on linked registers was similar. The decline in incidence between 1995 and 2000 was comparable whether based on standard hospital register data or linked data (18% and 20% in men, 15% and 17% in women). Similarly, the decline in hospital mortality was comparable using either approach (11% and 9% in both men and women). CONCLUSION: Although the incidence based on routine hospital data overestimates the actual incidence of first AMI based on linked registers, hospital mortality and trends in incidence and hospital mortality are not changed by excluding recurrent events and double counts. Since trends in incidence and hospital mortality of AMI are often based on national routinely collected data, it is reassuring that our results indicate that findings from such studies are indeed valid and not biased because of recurrent events and double counts.

Short- and long-term prognosis after acute myocardial infarction in men versus women.

The prevailing view is that women have a higher early mortality after acute myocardial infarction (AMI) than men, but several studies have shown no differences. Further, long-term differences have not been addressed widely. The present study examined gender differences in short- and long-term prognoses after AMI in The Netherlands. A nationwide cohort of 21,565 patients with a first hospitalized AMI in 1995 was identified through linkage of the National Hospital Discharge Register and the population register. Crude short- and long-term mortalities were significantly higher in women than in men (28-day hazard ratio [HR] 1.70, 95% confidence interval [CI] 1.58 to 1.82; 5-year HR 1.52, 95% CI 1.46 to 1.59). After adjustment for age, the risk difference was attenuated at 28 days and even reversed at 5 years in favor of women (28-day HR 1.11, 95% CI 1.03 to 1.20; 5-year HR 0.94, 95% CI 0.90 to 0.99). When differences in other covariates were also taken into account, the risk differences remained virtually the same. To account for differences in reperfusion procedures, we repeated the analyses in 1,176 patients who underwent acute reperfusion therapy (angioplasty/thrombolysis). Comparable, but not statistically significant, gender differences were observed (28-day HR 1.06, 95% CI 0.65 to 1.74; 5-year HR 0.82, 95% CI 0.62 to 1.08). In conclusion, our findings in an unselected cohort covering a complete nation indicate that the worse short- and long-term prognoses after an AMI in women compared with men may largely be explained by differences in age, whereas differences in co-morbidity, origin, infarct location, and reperfusion therapy seem to contribute little.