BackgroundRisk factors for hip fracture are well studied because of the negative impact on patients and the community, with mortality in the first year being almost 30% in the elderly. Age, gender and fall risk-increasing drugs, identified by the National Board of Health and Welfare in Sweden, are well known risk factors for hip fracture, but how multimorbidity level affects the risk of hip fracture during use of fall risk-increasing drugs is to our knowledge not as well studied. This study explored the relationship between use of fall risk-increasing drugs in combination with multimorbidity level and risk of hip fracture in an elderly population.MethodsData were from Östergötland County, Sweden, and comprised the total population in the county aged 75 years and older during 2006. The odds ratio (OR) for hip fracture during use of fall risk-increasing drugs was calculated by multivariate logistic regression, adjusted for age, gender and individual multimorbidity level. Multimorbidity level was estimated with the Johns Hopkins ACG Case-Mix System and grouped into six Resource Utilization Bands (RUBs 0–5).Results2.07% of the study population (N = 38,407) had a hip fracture during 2007. Patients using opioids (OR 1.56, 95% CI 1.34-1.82), dopaminergic agents (OR 1.78, 95% CI 1.24-2.55), anxiolytics (OR 1.31, 95% CI 1.11-1.54), antidepressants (OR 1.66, 95% CI 1.42-1.95) or hypnotics/sedatives (OR 1.31, 95% CI 1.13-1.52) had increased ORs for hip fracture after adjustment for age, gender and multimorbidity level. Vasodilators used in cardiac diseases, antihypertensive agents, diuretics, beta-blocking agents, calcium channel blockers and renin-angiotensin system inhibitors were not associated with an increased OR for hip fracture after adjustment for age, gender and multimorbidity level.ConclusionsUse of fall risk-increasing drugs such as opioids, dopaminergic agents, anxiolytics, antidepressants and hypnotics/sedatives increases the risk of hip fracture after adjustment for age, gender and multimorbidity level. Fall risk-increasing drugs, high age, female gender and multimorbidity level, can be used to identify high-risk patients who could benefit from a medication review to reduce the risk of hip fracture.

Objective. To study the associations between active choice of primary care provider and healthcare utilization, multimorbidity, age, and sex, comparing data from primary care and all healthcare in a Swedish population. Design. Descriptive cross-sectional study using descriptive analyses including t-test, correlations, and logistic regression modelling in four separate models. Setting and subjects. The population (151 731) and all healthcare in Blekinge in 2007. Main outcome measure. Actively or passively listed in primary care, registered on 31 December 2007. Results. Number of consultations (OR 1.31, 95% CI 1.30–1.32), multimorbidity level (OR 1.69, 95% CI 1.67–1.70), age (OR 1.03, 95% CI 1.03–1.03), and sex (OR for men 0.67, 95% CI 0.65–0.68) were all associated with registered active listing in primary care. Active listing was more strongly associated with number of consultations and multimorbidity level using primary care data (OR 2.11, 95% CI 2.08–2.15 and OR 2.14, 95% CI 2.11–2.17, respectively) than using data from all healthcare. Number of consultations and multimorbidity level were correlated and had similar associations with active listing in primary care. Modelling number of consultations, multimorbidity level, age, and sex gave four separate models with about 70% explanatory power for active listing in primary care. Combining number of consultations and multimorbidity did not improve the models. Conclusions. Number of consultations and multimorbidity level were associated with active listing in primary care. These factors were also associated with each other differently in primary care than in all healthcare. More complex models including non-health-related individual characteristics and healthcare-related factors are needed to increase explanatory power.

BackgroundHealthcare systems are complex networks where relationships affect outcomes. The importance of primary care increases while health care acknowledges multimorbidity, the impact of combinations of different diseases in one person. Active listing and consultations in primary care could be used as proxies of the relationships between patients and primary care. Our objective was to study hospitalisation as an outcome of primary care, exploring the associations with active listing, number of consultations in primary care and two groups of practices, while taking socioeconomic status and morbidity burden into account.MethodsA cross-sectional study using zero-inflated negative binomial regression to estimate odds of any hospital admission and mean number of days hospitalised for the population over 15 years (N = 123,168) in the Swedish county of Blekinge during 2007. Explanatory factors were listed as active or passive in primary care, number of consultations in primary care and primary care practices grouped according to ownership. The models were adjusted for sex, age, disposable income, education level and multimorbidity level.ResultsMean days hospitalised was 0.94 (95%CI 0.90–0.99) for actively listed and 1.32 (95%CI 1.24–1.40) for passively listed. For patients with 0–1 consultation in primary care mean days hospitalised was 1.21 (95%CI 1.13–1.29) compared to 0.77 (95%CI 0.66–0.87) days for patients with 6–7 consultations. Mean days hospitalised was 1.22 (95%CI 1.16–1.28) for listed in private primary care and 0.98 (95%CI 0.94–1.01) for listed in public primary care, with odds for hospital admission 0.51 (95%CI 0.39–0.63) for public primary care compared to private primary care.ConclusionsActive listing and more consultations in primary care are both associated with reduced mean days hospitalised, when adjusting for socioeconomic status and multimorbidity level.Different odds of any hospitalisation give a difference in mean days hospitalised associated with type of primary care practice.To promote well performing primary care to maintain good relationships with patients could reduce mean days hospitalised.