Importance of healthcare utilization and multimorbidity level in choosing a primary care provider
in Sweden
Engelsk titel: Importance of healthcare utilization and multimorbidity level in choosing a primary care provider
in Sweden
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Författare:
Ranstad, Karin
;
Midlöv, Patrik
;
Halling, Anders
Email: karin.ranstad@ltblekinge.se
Språk: Eng
Antal referenser: 27
Dokumenttyp:
Artikel
UI-nummer: 15069383
Sammanfattning
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.