Claudia Berlin

Avoidable hospitalizations in Switzerland: a small area analysis on regional variation, density of physicians, hospital supply and rurality

BackgroundAvoidable hospitalizations (AH) are hospital admissions for diseases and conditions that could have been prevented by appropriate ambulatory care. We examine regional variation of AH in Switzerland and the factors that determine AH.MethodsWe used hospital service areas, and data from 2008–2010 hospital discharges in Switzerland to examine regional variation in AH. Age and sex standardized AH were the outcome variable, and year of admission, primary care physician density, medical specialist density, rurality, hospital bed density and type of hospital reimbursement system were explanatory variables in our multilevel poisson regression.ResultsRegional differences in AH were as high as 12-fold. Poisson regression showed significant increase of all AH over time. There was a significantly lower rate of all AH in areas with more primary care physicians. Rates increased in areas with more specialists. Rates of all AH also increased where the proportion of residences in rural communities increased. Regional hospital capacity and type of hospital reimbursement did not have significant associations. Inconsistent patterns of significant determinants were found for disease specific analyses.ConclusionThe identification of regions with high and low AH rates is a starting point for future studies on unwarranted medical procedures, and may help to reduce their incidence. AH have complex multifactorial origins and this study demonstrates that rurality and physician density are relevant determinants. The results are helpful to improve the performance of the outpatient sector with emphasis on local context. Rural and urban differences in health care delivery remain a cause of concern in Switzerland.

Regional Variation of Cost of Care in the Last 12 Months of Life in Switzerland: Small-Area Analysis Using Insurance Claims Data.

Background: Health care spending increases sharply at the end of life. Little is known about variation of cost of end of life care between regions and the drivers of such variation. We studied small-area patterns of cost of care in the last year of life in Switzerland. Methods: We used mandatory health insurance claims data of individuals who died between 2008 and 2010 to derive cost of care. We used multilevel regression models to estimate differences in costs across 564 regions of place of residence, nested within 71 hospital service areas. We examined to what extent variation was explained by characteristics of individuals and regions, including measures of health care supply. Results: The study population consisted of 113,277 individuals. The mean cost of care during last year of life was 32.5k (thousand) Swiss Francs per person (SD=33.2k). Cost differed substantially between regions after adjustment for patient age, sex, and cause of death. Variance was reduced by 52%–95% when we added individual and regional characteristics, with a strong effect of language region. Measures of supply of care did not show associations with costs. Remaining between and within hospital service area variations were most pronounced for older females and least for younger individuals. Conclusions: In Switzerland, small-area analysis revealed variation of cost of care during the last year of life according to linguistic regions and unexplained regional differences for older women. Cultural factors contribute to the delivery and utilization of health care during the last months of life and should be considered by policy makers.

Trends in the use of mammography for early breast cancer detection in Switzerland: Swiss Health Surveys 2007 and 2012

AIMS Breast cancer is the most common cancer in women worldwide. We assessed changes in the use of breast cancer screening 2007-2012 in Switzerland, and associations with socioeconomic and health-related determinants. METHODS We used the nationwide and representative data from the Swiss Health Surveys 2007 and 2012. We analysed the self-reported use of mammography in the last 12 months (proportion of population) among women aged 40-79 years, and opportunistic (without clinical symptoms, initiated by the woman or a physician) and programmatic screening mammography (as part of a systematic screening programme). We performed multivariate logistic regression analyses (presented as adjusted odds ratios, aORs). RESULTS The use of any mammography in the last 12 months declined from 19.1% (95% confidence interval [CI] 17.7-20.5%) in 2007 to 11.7% (95% CI 10.7-12.6%) in 2012. This decline was more pronounced in regions with a long-standing or no cantonal breast cancer screening programme (aOR 0.5, 95% CI 0.4-0.6, and aOR 0.5, 95% CI 0.4-0.6, respectively), but remained relatively stable in regions with a recently introduced programme (aOR 0.9, 95% CI 0.6-1.3, p-value from test for interaction 0.01). Opportunistic screening dropped from 12.0% (95% CI 10.9-13.2%) in 2007 to 6.2% (95% CI 5.5-6.9%; p <0.001) in 2012, whereas the use of programmatic mammography remained stable at 3.1% (95% CI 2.6-3.7%). Use of any mammography was higher in women aged 50-69 years, residing in a region with a systematic screening programme in place, and women having a private hospital stay insurance, but was not associated with education level and non-Swiss citizenship. CONCLUSIONS Overall attendance of breast cancer screening is low in Switzerland and decreased between 2007 and 2012, despite expanding cantonal mammography screening programmes. Many factors may have contributed to this decline, including the ongoing scientific and public debates on the value of breast cancer screening.

Death at no cost? Persons with no health insurance claims in the last year of life in Switzerland

BackgroundLack of health insurance claims (HIC) in the last year of life might indicate suboptimal end-of-life care, but reasons for no HIC are not fully understood because information on causes of death is often missing. We investigated association of no HIC with characteristics of individuals and their place of residence.MethodsWe analysed HIC of persons who died between 2008 and 2010, which were obtained from six providers of mandatory Swiss health insurance. We probabilistically linked these persons to death certificates to get cause of death information and analysed data using sex-stratified, multivariable logistic regression. Supplementary analyses looked at selected subgroups of persons according to the primary cause of death.ResultsThe study population included 113,277 persons (46% males). Among these persons, 1199 (proportion 0.022, 95% CI: 0.021–0.024) males and 803 (0.013, 95% CI: 0.012–0.014) females had no HIC during the last year of life. We found sociodemographic and health differentials in the lack of HIC at the last year of life among these 2002 persons. The likelihood of having no HIC decreased steeply with older age. Those who died of cancer were more likely to have HIC (adjusted odds ratio for males 0.17, 95% CI: 0.13–0.22; females 0.19, 95% CI: 0.12–0.28) whereas those dying of mental and behavioural disorders (AOR males 1.83, 95% CI:1.42–2.37; females 1.65, 95% CI: 1.27–2.14), and males dying of suicide (AOR 2.15, 95% CI: 1.72–2.69) and accidents (AOR 2.41, 95% CI: 1.96–2.97) were more likely to have none. Single, widowed, and divorced persons also were more likely to have no HIC (AORs in range of 1.29–1.80). There was little or no association between the lack of HIC and characteristics of region of residence. Patterns of no HIC differed across main causes of death. Associations with age and civil status differed in particular for persons who died of cancer, suicide, accidents and assaults, and mental and behavioural disorders.ConclusionsParticular groups might be more likely to not seek care or not report health insurance costs to insurers. Researchers should be aware of this aspect of health insurance data and account for persons who lack HIC.

A comparison of regret-based and utility-based discrete choice modelling – an empirical illustration with hospital bed choice

ABSTRACT There is some concern that the unobserved preference heterogeneity in random utility maximization theory-based discrete choice experiment modelling is an important source of error variability. The randomness in utility is often interpreted as interpersonal preference heterogeneity but it can also be intrapersonal random variation in preferences. We compare utility maximization and regret minimization-based choice models’ sensitivity to individual heterogeneity, examine differences between two consecrated models and validate with empirical illustrations. We use frequency of category (public, semi-private, and private) of bed chosen from Swiss cross-sectional datasets (2007–2012) to compare two approaches – utility maximization and regret minimization by applying multinomial logit (MNL) models in regard to the variances in utility (regret) function, goodness-of-fit and predicted marginal effects (pseudo-elasticity) of additional payment. We find parameters with the same sign and estimates with almost same order of magnitude in both the approaches. The statistical significance of attribute effects is consistent in all variants of utility -based MNL models while effects of different attributes are significant only in heteroskedastic extreme value (HEV) variant of regret-based MNL models. This empirical illustration suggests that HEV variant of regret-based models perform better in capturing attribute effects in choice behaviour.

No significant gender difference in hospitalizations for acute coronary syndrome in Switzerland over the time period of 2001 to 2010

BACKGROUND Morbidity and mortality from cardiovascular diseases have decreased since the 1970s in most Western societies. However, it is unclear if this positive trend can also be found in younger women suffering from acute coronary syndrome (ACS). METHODS This is a prospective single center registry study including 11.015 women and men hospitalized for a first ACS between the years 2001 and 2010. We analyzed ACS rates according to sex and age group using Poisson regression in order to assess temporal trends. RESULTS Overall ACS hospitalization rates per 100.000 inhabitants increased by 31% between 2001 and 2010 (Rate Ratio (RR) of 1.31, 95% CI 1.20-1.43; p<0.001) with a similar increase in men (RR 1.29, p<0.00001) and women (RR 1.35, p<0.0001). Analyses of age-specific ACS rates showed a significant increase in ACS hospitalization rates only for the age groups 70-79years (p=0.003) and 80+ years (p<0.00001). None of the age matched subgroups showed a sex related significant difference in trend for ACS hospitalization rates. Temporal trends for recorded risk factors showed a significant increase in smoking (p=0.03), and a trend to increased obesity prevalence (p=0.06) in females in the age group 60-69years. CONCLUSIONS In contrast to other studies, we found no evidence for a particular increase in the number of younger women referred for a first ACS during the years 2001 and 2010. Potential negative effects of smoking and obesity on ACS incidence may be delayed to women older than 70years.

Revascularization Treatment of Emergency Patients with Acute ST-Segment Elevation Myocardial Infarction in Switzerland: Results from a Nationwide, Cross-Sectional Study in Switzerland for 2010-2011

Background Cardiovascular diseases are the leading cause of death worldwide and in Switzerland. When applied, treatment guidelines for patients with acute ST-segment elevation myocardial infarction (STEMI) improve the clinical outcome and should eliminate treatment differences by sex and age for patients whose clinical situations are identical. In Switzerland, the rate at which STEMI patients receive revascularization may vary by patient and hospital characteristics. Aims To examine all hospitalizations in Switzerland from 2010–2011 to determine if patient or hospital characteristics affected the rate of revascularization (receiving either a percutaneous coronary intervention or a coronary artery bypass grafting) in acute STEMI patients. Data and Methods We used national data sets on hospital stays, and on hospital infrastructure and operating characteristics, for the years 2010 and 2011, to identify all emergency patients admitted with the main diagnosis of acute STEMI. We then calculated the proportion of patients who were treated with revascularization. We used multivariable multilevel Poisson regression to determine if receipt of revascularization varied by patient and hospital characteristics. Results Of the 9,696 cases we identified, 71.6% received revascularization. Patients were less likely to receive revascularization if they were female, and 80 years or older. In the multivariable multilevel Poisson regression analysis, there was a trend for small-volume hospitals performing fewer revascularizations but this was not statistically significant while being female (Relative Proportion = 0.91, 95% CI: 0.86 to 0.97) and being older than 80 years was still associated with less frequent revascularization. Conclusion Female and older patients were less likely to receive revascularization. Further research needs to clarify whether this reflects differential application of treatment guidelines or limitations in this kind of routine data.

Do acute myocardial infarction and stroke mortality vary by distance to hospitals in Switzerland? Results from the Swiss National Cohort Study

Objective Switzerland has mountains and valleys complicating the access to a hospital and critical care in case of emergencies. Treatment success for acute myocardial infarction (AMI) or stroke depends on timely treatment. We examined the relationship between distance to different hospital types and mortality from AMI or stroke in the Swiss National Cohort (SNC) Study. Design and setting The SNC is a longitudinal mortality study of the census 2000 population of Switzerland. For 4.5 million Swiss residents not living in a nursing home and older than 30 years in the year 2000, we calculated driving time and straight-line distance from their home to the nearest acute, acute with emergency room, central and university hospital (in total 173 hospitals). On the basis of quintiles, we used multivariable Cox proportional hazard models to estimate HRs of AMI and stroke mortality for driving time distance groups compared to the closest distance group. Results Over 8 years, 19 301 AMI and 21 931 stroke deaths occurred. Mean driving time to the nearest acute hospital was 6.5 min (29.7 min to a university hospital). For AMI mortality, driving time to a university hospital showed the strongest association among the four types of hospitals with a hazard ratio (HR) of 1.19 (95% CI 1.10 to 1.30) and 1.10 (95% CI 1.01 to 1.20) for men and women aged 65+ years when comparing the highest quintile with the lowest quintile of driving time. For stroke mortality, the association with university hospital driving time was less pronounced than for AMI mortality and did not show a clear incremental pattern with increasing driving time. There was no association with driving time to the nearest hospital. Conclusions The increasing AMI mortality with increasing driving time to the nearest university hospital but not to any nearest hospital reflects a complex interplay of many factors along the care pathway.