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Referral determinants in Swiss primary care with a special focus on managed care.

ABSTRACT: Studies have shown large variation of referral probabilities in different countries, and many influencing factors have been described. This variation is most likely explained by different healthcare systems, particularly to which extent primary care physicians (PCPs) act as gatekeepers. In Switzerland no mandatory gatekeeping system exists, however insurance companies offer voluntary managed care plans with reduced insurance premiums. We aimed at investigating the role of managed care plans as a potential referral determinant in a non-gatekeeping healthcare system. We conducted a cross-sectional study with 90 PCPs collecting data on consultations and referrals in 2012/2013. During each consultation up to six reasons for encounters (RFE) were documented. For each RFE PCPs indicated whether a referral was initiated. Determinants for referrals were analyzed by hierarchical logistic regression, taking the potential cluster effect of the PCP into account. To further investigate the independent association of the managed care plan with the referral probability, a hierarchical multivariate logistic regression model was applied, taking into account all available data potentially affecting the referring decision. PCPs collected data on 24'774 patients with 42'890 RFE, of which 2427 led to a referral. 37.5% of patients were insured in managed health care plans. Univariate analysis showed significant higher referral rates of patients with managed care plans (10.7% vs. 8.5%). The difference in referral probability remained significant after controlling for other confounders in the hierarchical multivariate regression model (OR 1.355). Patients in managed care plans were more likely to be referred than patients without such a model. These data contradict the argument that patients in managed care plans have limited healthcare access, but underline the central role of PCPs as coordinator of care.

SUBMITTER: Tandjung R

PROVIDER: S-EPMC5675398 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Referral determinants in Swiss primary care with a special focus on managed care.

Tandjung Ryan R Morell Seraina S Hanhart Andreas A Haefeli Andreas A Valeri Fabio F Rosemann Thomas T Senn Oliver O

PloS one 20171107 11

Studies have shown large variation of referral probabilities in different countries, and many influencing factors have been described. This variation is most likely explained by different healthcare systems, particularly to which extent primary care physicians (PCPs) act as gatekeepers. In Switzerland no mandatory gatekeeping system exists, however insurance companies offer voluntary managed care plans with reduced insurance premiums. We aimed at investigating the role of managed care plans as a ...[more]

PMID: 29112975

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Project description:ImportanceManaged care payment formulas commonly allocate more money for medically complex populations, but ignore most social determinants of health (SDH).ObjectiveTo add SDH variables to a diagnosis-based payment formula that allocates funds to managed care plans and accountable care organizations.Design, setting, and participantsUsing data from MassHealth, the Massachusetts Medicaid and Children's Health Insurance Program, we estimated regression models predicting Medicaid spending using a diagnosis-based and SDH-expanded model, and compared the accuracy of their cost predictions overall and for vulnerable populations. MassHealth members enrolled for at least 6 months in 2013 in fee-for-service (FFS) programs (n = 357 660) or managed care organizations (MCOs) (n = 524 607).ExposuresWe built cost prediction models from a fee-for-service program. Predictors in the diagnosis-based model are age, sex, and diagnoses from claims. The SDH model adds predictors describing housing instability, behavioral health issues, disability, and neighborhood-level stressors.Main outcomes and measuresOverall model explanatory power and overpayments and underpayments for subgroups of interest for all Medicaid-reimbursable expenditures excepting long-term support services (mean annual cost = $5590 per member).ResultsWe studied 357 660 people who were FFS participants and 524 607 enrolled in MCOs with a combined 806 889 person-years of experience. The FFS program experience included more men (49.6% vs 43.6%), older patients (mean age of 26.1 years vs 21.6 years), and sicker patients (mean morbidity score of 1.16 vs 0.89) than MCOs. Overall, the SDH model performed well, but only slightly better than the diagnosis-based model, explaining most of the spending variation in the managed care population (validated R2 = 62.4) and reducing underpayments for several vulnerable populations. For example, raw costs for the quintile of people living in the most stressed neighborhoods were 9.6% ($537 per member per year) higher than average. Since greater medical morbidity accounts for much of this difference, the diagnosis-based model underpredicts costs for the most stressed quintile by about 2.1% ($130 per member per year). The expanded model eliminates the neighborhood-based underpayment, as well as underpayments of 72% for clients of the Department of Mental Health (observed costs of about $30 000 per year) and of 7% for those with serious mental illness (observed costs of about $16 000 per year).Conclusions and relevanceSince October 2016, MassHealth has used an expanded model to allocate payments from a prespecified total budget to managed care organizations according to their enrollees' social and medical risk. Extra payments for socially vulnerable individuals could fund activities, such as housing assistance, that could improve health equity.

Project description:BACKGROUND: Questions about the existence of supplier-induced demand emerge repeatedly in discussions about governing Swiss health care. This study therefore aimed to evaluate the interrelationship between structural factors of supply and the volume of services that are provided by primary care physicians in Switzerland. METHODS: The study was designed as a cross-sectional investigation, based on the complete claims data from all Swiss health care insurers for the year 2004, which covered information from 6087 primary care physicians and 4.7 million patients. Utilization-based health service areas were constructed and used as spatial units to analyze effects of density of supply. Hierarchical linear models were applied to analyze the data. RESULTS: The data showed that, within a service area, a higher density of primary care physicians was associated with higher mortality rates and specialist density but not with treatment intensity in primary care. Higher specialist density was weakly associated with higher mortality rates and with higher treatment intensity density of primary care physicians. Annual physician-level data indicate a disproportionate increase of supplied services irrespective of the size of the number of patients treated during the same year and, even in high volume practices, no rationing but a paradoxical inducement of consultations occurred. The results provide empirical evidence that higher densities of primary care physicians, specialists and the availability of out-patient hospital clinics in a given area are associated with higher volume of supplied services per patient in primary care practices. Analyses stratified by language regions showed differences that emphasize the effect of the cantonal based (fragmented) governance of Swiss health care. CONCLUSION: The study shows high volumes in Swiss primary care and provides evidence that the volume of supply is not driven by medical needs alone. Effects related to the competition for patients between primary care physicians, specialists and out-patient hospital clinics and an association with the system of reimbursing services on a fee-for-service basis can not be excluded.

Project description:INTRODUCTION:Intensive behavioral counseling is effective in preventing type 2 diabetes, and insurance coverage for such interventions is increasing. Although primary care provider referrals are not required for entry to the Centers for Disease Control and Prevention (CDC)-recognized National Diabetes Prevention Program lifestyle change program, referral rates remain suboptimal. This study aims to assess the association between primary care provider behaviors regarding prediabetes screening, testing, and referral and awareness of the CDC-recognized lifestyle change program and the Prevent Diabetes STAT: Screen, Test, and Act Today™ toolkit. Awareness of the lifestyle change program and the STAT toolkit, use of electronic health records, and the ratio of lifestyle change program classes to primary care physicians were hypothesized to be positively associated with primary care provider prediabetes screening, testing, and referral behaviors. METHODS:Responses from primary care providers (n=1,256) who completed the 2016 DocStyles cross-sectional web-based survey were analyzed in 2017 to measure self-reported prediabetes screening, testing, and referral behaviors. Multivariate logistic regression was used to estimate the effects of primary care provider awareness and practice characteristics on these behaviors, controlling for provider characteristics. RESULTS:Overall, 38% of primary care providers were aware of the CDC-recognized lifestyle change program, and 19% were aware of the STAT toolkit; 27% screened patients for prediabetes using a risk test; 97% ordered recommended blood tests; and 23% made referrals. Awareness of the lifestyle change program and the STAT toolkit was positively associated with screening and referring patients. Primary care providers who used electronic health records were more likely to screen, test, and refer. Referring was more likely in areas with more lifestyle change program classes. CONCLUSIONS:This study highlights the importance of increasing primary care provider awareness of and referrals to the CDC-recognized lifestyle change program.

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Referral determinants in Swiss primary care with a special focus on managed care.

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Referral determinants in Swiss primary care with a special focus on managed care.

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