Dataset Information

Can Additional Homeopathic Treatment Save Costs? A Retrospective Cost-Analysis Based on 44500 Insured Persons.

ABSTRACT:

Objectives

The aim of this study was to compare the health care costs for patients using additional homeopathic treatment (homeopathy group) with the costs for those receiving usual care (control group).

Methods

Cost data provided by a large German statutory health insurance company were retrospectively analysed from the societal perspective (primary outcome) and from the statutory health insurance perspective. Patients in both groups were matched using a propensity score matching procedure based on socio-demographic variables as well as costs, number of hospital stays and sick leave days in the previous 12 months. Total cumulative costs over 18 months were compared between the groups with an analysis of covariance (adjusted for baseline costs) across diagnoses and for six specific diagnoses (depression, migraine, allergic rhinitis, asthma, atopic dermatitis, and headache).

Results

Data from 44,550 patients (67.3% females) were available for analysis. From the societal perspective, total costs after 18 months were higher in the homeopathy group (adj. mean: EUR 7,207.72 [95% CI 7,001.14-7,414.29]) than in the control group (EUR 5,857.56 [5,650.98-6,064.13]; p<0.0001) with the largest differences between groups for productivity loss (homeopathy EUR 3,698.00 [3,586.48-3,809.53] vs. control EUR 3,092.84 [2,981.31-3,204.37]) and outpatient care costs (homeopathy EUR 1,088.25 [1,073.90-1,102.59] vs. control EUR 867.87 [853.52-882.21]). Group differences decreased over time. For all diagnoses, costs were higher in the homeopathy group than in the control group, although this difference was not always statistically significant.

Conclusion

Compared with usual care, additional homeopathic treatment was associated with significantly higher costs. These analyses did not confirm previously observed cost savings resulting from the use of homeopathy in the health care system.

SUBMITTER: Ostermann JK

PROVIDER: S-EPMC4521756 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Can Additional Homeopathic Treatment Save Costs? A Retrospective Cost-Analysis Based on 44500 Insured Persons.

Ostermann Julia K JK Reinhold Thomas T Witt Claudia M CM

PloS one 20150731 7

<h4>Objectives</h4>The aim of this study was to compare the health care costs for patients using additional homeopathic treatment (homeopathy group) with the costs for those receiving usual care (control group).<h4>Methods</h4>Cost data provided by a large German statutory health insurance company were retrospectively analysed from the societal perspective (primary outcome) and from the statutory health insurance perspective. Patients in both groups were matched using a propensity score matching ...[more]

PMID: 26230412

Similar Datasets

Project description:BackgroundA number of German statutory health insurance companies are offering integrated care contracts for homeopathy (ICCHs) that cover the reimbursement of homeopathic treatment. The effectiveness and cost-effectiveness of these contracts are highly debated.MethodsTo evaluate the effectiveness and cost-effectiveness of treatment after an additional enrollment in an ICCH, a comparative, prospective, observational study was conducted in which participants in the ICCH (HOM group) were compared with matched (on diagnosis, sex and age) insured individuals (CON group) who received usual care alone. Those insured with either migraine or headache, allergic rhinitis, asthma, atopic dermatitis and depression were included. Primary effectiveness outcomes were the baseline adjusted scores of diagnosis-specific questionnaires (e.g. RQLQ, AQLQ, DLQI, BDI-II) after 6 months. Primary cost-effectiveness endpoints were the baseline adjusted total costs from an insurer perspective in relation to the achieved quality-adjusted life years (QALYs). Costs were derived from health claims data and QALYs were calculated based on SF-12 data.ResultsData from 2524 participants (1543 HOM group) were analyzed. The primary effectiveness outcomes after six months were statistically significant in favor of the HOM group for migraine or headache (Δ = difference between groups, days with headache: - 0.9, p = 0.042), asthma (Δ-AQLQ(S): + 0.4, p = 0.014), atopic dermatitis (Δ-DLQI: - 5.6, p ≤ 0.001) and depression (Δ-BDI-II: - 5.6, p ≤ 0.001). BDI-II differences reached the minimal clinically important difference. For all diagnoses, the adjusted mean total costs over 12 months were higher in the HOM group from an insurer perspective, with migraine or headache, atopic dermatitis and depression suggesting cost-effectiveness in terms of additional costs per QALY gained.ConclusionAfter an additional enrollment in the ICCH, the treatment of participants with depression showed minimally clinically relevant improvements. From an insurer perspective, treatment with an ICCH enrollment resulted in higher costs over all diagnoses but seemed to be cost-effective for migraine or headache, atopic dermatitis and depression according to international used threshold values. Based on the study design and further limitations, our findings should be considered cautiously and no conclusions regarding the effectiveness of specific treatment components can be made. Further research is needed to overcome limitations of this study and to confirm our findings.Trial registrationclinicaltrials.gov , NCT01854580. Registered 15 March 2013 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT01854580.

Project description:BackgroundFew studies have estimated the real-world economic burden such as all-cause and follicular lymphoma (FL)-related costs and health care resource utilization (HCRU) in patients with FL.ObjectivesThis study evaluated outcomes in patients who were newly initiated with FL indicated regimens by line of therapy with real-world data.MethodsA retrospective study was conducted among patients with FL from MarketScan® databases between January 1, 2010 and December 31, 2013. Patients were selected if they were ≥18 years old when initiated on a FL indicated therapy, had at least 1 FL-related diagnosis, ≥1 FL commonly prescribed systemic anti-cancer therapy after diagnosis, and did not use any FL indicated regimen in the 24 months prior to the first agent. These patients were followed up at least 48 months and the outcomes, including the distribution of regimens by line of therapy, the treatment duration by line of therapy, all-cause and FL-related costs, and HCRU by line of therapy were evaluated.ResultsThis study identified 598 patients who initiated FL indicated treatment. The average follow-up time was approximately 5.7 years. Of these patients, 50.2% (n=300) were female, with a mean age of 60.7 years (SD=13.1 years) when initiating their treatment with FL indicated regimens. Overall, 598 (100%) patients received first-line therapy, 180 (43.6%) received second-line therapy, 51 received third-line therapy, 21 received fourth-line therapy, and 10 received fifth-line therapy. Duration of treatment by each line of therapy was 370 days, 392 days, 162 days, 148 days, and 88 days, respectively. The most common first-line regimens received by patients were rituximab (n=201, 33.6%), R-CHOP (combination of rituximab, cyclophosphamide, doxorubicin hydrochloride [hydroxydaunomycin]; n=143, 24.0%), BR (combination of bendamustine and rituximab; n=143, 24.0%), and R-CVP (combination of rituximab, cyclophosphamide, vincristine, and prednisone; n=71, 11.9%). The most common second-line treatment regimens were (N=180): rituximab (n=78, 43.3%) and BR (n=41, 22.8%). Annualized all-cause health care costs per patient ranged from US$97 141 (SD: US$144 730) for first-line to US$424 758 (SD: US$715 028) for fifth-line therapy.ConclusionsThe primary regimens used across treatment lines conform to those recommended by the National Comprehensive Cancer Network clinical practice guidelines. The economic burden for patients with FL is high and grows with subsequent lines of therapy.

Project description:ObjectiveThe economic burden of commercially insured patients in the United States with treatment-resistant depression and patients with non-treatment-resistant major depressive disorder was compared using data from the Optum Clinformatics™ claims database.MethodsPatients 18-63 years on antidepressant treatment between 1/1/13 and 9/30/13, who had no treatment claims for depression 6 months before the index date (first antidepressant dispensing), and who had a major depressive disorder or depression diagnosis within 30 days of the index date, were included. Treatment-resistant depression was defined as receiving 3 antidepressant regimens during 1 major depressive disorder episode. Patients with treatment-resistant depression were matched with patients with non-treatment-resistant major depressive disorder at a 1:4 ratio using propensity score matching. The study consisted of 1-year baseline (pre-index) and 2-year follow-up (post index) periods. Cost outcomes were compared using a generalized linear model.Results2,370 treatment-resistant depression and 9,289 non-treatment-resistant major depressive disorder patients were included. In year 1 of the follow-up period, compared with non-treatment-resistant major depressive disorder, patients with treatment-resistant depression had: more emergency department visits (odds ratio = 1.39, 95% confidence interval = 1.24-1.56); more inpatient hospitalizations (odds ratio = 1.73, 95% confidence interval = 1.46-2.05); longer hospital stays (mean difference vs non-treatment-resistant major depressive disorder = 2.86, 95% confidence interval = 0.86-4.86 days); and more total healthcare costs (mean difference vs non-treatment-resistant major depressive disorder = US$3,846, 95% confidence interval = $2,855-$4,928). These patterns remained consistent in year 2 of the follow-up period.ConclusionTreatment-resistant depression was associated with higher healthcare resource utilization and costs versus non-treatment-resistant major depressive disorder in this commercially insured cohort of patients in the United States.

Project description:OBJECTIVES:To measure 18-month healthcare cost difference attributable to hearing loss (HL) in older adults. DESIGN:Matched cohort. SETTING:Retrospective analysis of administrative healthcare bills of insured older Americans. PARTICIPANTS:Older U.S. adults with health insurance in 3 cohorts matched based on HL diagnosis using propensity score methods (N=904,750). MEASUREMENTS:Comparison groups were defined as those with and without HL diagnosis using International Classification of Diseases, Ninth Revision, diagnosis codes from billing records. Outcomes measured include 18-month total healthcare payments and healthcare payments broken down according to payment type (inpatient, outpatient, prescription, hearing services). Three comparison cohorts were examined for these outcomes: individuals covered by Medicare plus supplemental private insurance (Cohort 1, n=782,216), those covered only under Medicare (Cohort 2, n=105,296), and those within the Medicare sample that were dually eligible for Medicare and Medicaid coverage (Subcohort 3, n=17,238). The quality of the propensity score match was examined using standardized differences in means or proportions between all matched covariates, and cost outcomes were analyzed using multiple generalized linear regression models. RESULTS:Fully adjusted models showed significantly higher 18-month healthcare payments for individuals with a diagnosis of HL without indication of use of hearing services than in those without a HL diagnosis in the 3 samples (payment differences: $3,587 Cohort 1, $3,779 Cohort 2, $4,657 Subcohort 3; all p<.001). Payment differences were also found between individuals with HL and indications of hearing services and those without HL. CONCLUSION:We observed more than 20% higher total healthcare payments over 18 months for a group of insured individuals with HL regardless of insurance type or hearing services use, indicating that negative health-related effects of HL may increase healthcare use unrelated to HL. Thus, clinical care to ameliorate HL may improve overall health.

Dataset Information

Can Additional Homeopathic Treatment Save Costs? A Retrospective Cost-Analysis Based on 44500 Insured Persons.

Objectives

Methods

Results

Conclusion

Publications

Can Additional Homeopathic Treatment Save Costs? A Retrospective Cost-Analysis Based on 44500 Insured Persons.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets