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      Geographic variation in the costs of medical care for people living with HIV in British Columbia, Canada

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          Abstract

          Background

          Regional variation in medical care costs can indicate heterogeneity in clinical practice, inequities in access, or inefficiencies in service delivery. We aimed to estimate regional variation in medical costs for people living with HIV (PLHIV), adjusting for demographics and case-mix.

          Methods

          We conducted a retrospective cohort study using linked health administrative databases of PLHIV, from 2010 to 2014, in British Columbia (BC), Canada. Quarterly health care costs (2018 CAD) were derived from inpatient, outpatient, prescription drugs, antiretroviral therapy (ART), and HIV diagnostics. We used a two-part model with a logit link for the probability of incurring costs, and a log link and gamma distribution for observations with positive costs. We also estimated quarterly utilization rates for hospitalization-, physician billing- and prescription drug-days. Primary variables were indicators of individuals’ Health Service Delivery Area (HSDA). We adjusted cost and utilization estimates for demographic characteristics, HIV-disease progression, and comorbidities.

          Results

          Our cohort included 9577 PLHIV (median age 45.5 years, 80% male). Adjusted total quarterly costs for all 16 HSDAs were within 20% of the provincial mean, 8/16 for hospitalization costs, 16/16 for physician billing costs and 10/16 for prescription drug costs. Northern Interior and Northeast HSDAs had 38 and 44% lower quarterly non-ART prescription drug costs, and 2 and 5% higher quarterly inpatient costs, respectively.

          Conclusions

          We observed limited variation in medical care costs and utilization among PLHIV in BC. However, lower levels of outpatient care and higher levels of inpatient care indicate possible barriers to accessing care among PLHIV in the most rural regions of the province.

          Electronic supplementary material

          The online version of this article (10.1186/s12913-019-4391-8) contains supplementary material, which is available to authorized users.

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          Most cited references33

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          Medication adherence: its importance in cardiovascular outcomes.

          Medication adherence usually refers to whether patients take their medications as prescribed (eg, twice daily), as well as whether they continue to take a prescribed medication. Medication nonadherence is a growing concern to clinicians, healthcare systems, and other stakeholders (eg, payers) because of mounting evidence that it is prevalent and associated with adverse outcomes and higher costs of care. To date, measurement of patient medication adherence and use of interventions to improve adherence are rare in routine clinical practice. The goals of the present report are to address (1) different methods of measuring adherence, (2) the prevalence of medication nonadherence, (3) the association between nonadherence and outcomes, (4) the reasons for nonadherence, and finally, (5) interventions to improve medication adherence.
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            Impact of medication adherence on hospitalization risk and healthcare cost.

            The objective of this study was to evaluate the impact of medication adherence on healthcare utilization and cost for 4 chronic conditions that are major drivers of drug spending: diabetes, hypertension, hypercholesterolemia, and congestive heart failure. The authors conducted a retrospective cohort observation of patients who were continuously enrolled in medical and prescription benefit plans from June 1997 through May 1999. Patients were identified for disease-specific analysis based on claims for outpatient, emergency room, or inpatient services during the first 12 months of the study. Using an integrated analysis of administrative claims data, medical and drug utilization were measured during the 12-month period after patient identification. Medication adherence was defined by days' supply of maintenance medications for each condition. The study consisted of a population-based sample of 137,277 patients under age 65. Disease-related and all-cause medical costs, drug costs, and hospitalization risk were measured. Using regression analysis, these measures were modeled at varying levels of medication adherence. For diabetes and hypercholesterolemia, a high level of medication adherence was associated with lower disease-related medical costs. For these conditions, higher medication costs were more than offset by medical cost reductions, producing a net reduction in overall healthcare costs. For diabetes, hypercholesterolemia, and hypertension, cost offsets were observed for all-cause medical costs at high levels of medication adherence. For all 4 conditions, hospitalization rates were significantly lower for patients with high medication adherence. For some chronic conditions, increased drug utilization can provide a net economic return when it is driven by improved adherence with guidelines-based therapy.
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              Generalized modeling approaches to risk adjustment of skewed outcomes data.

              There are two broad classes of models used to address the econometric problems caused by skewness in data commonly encountered in health care applications: (1) transformation to deal with skewness (e.g., ordinary least square (OLS) on ln(y)); and (2) alternative weighting approaches based on exponential conditional models (ECM) and generalized linear model (GLM) approaches. In this paper, we encompass these two classes of models using the three parameter generalized Gamma (GGM) distribution, which includes several of the standard alternatives as special cases-OLS with a normal error, OLS for the log-normal, the standard Gamma and exponential with a log link, and the Weibull. Using simulation methods, we find the tests of identifying distributions to be robust. The GGM also provides a potentially more robust alternative estimator to the standard alternatives. An example using inpatient expenditures is also analyzed.
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                Author and article information

                Contributors
                604-806-8649 , bnosyk@cfenet.ubc.ca
                Journal
                BMC Health Serv Res
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central (London )
                1472-6963
                3 September 2019
                3 September 2019
                2019
                : 19
                : 626
                Affiliations
                [1 ]ISNI 0000 0000 8589 2327, GRID grid.416553.0, BC Centre for Excellence in HIV/AIDS, St. Paul’s Hospital, ; 613-1081 Burrard St, Vancouver, BC V6Z 1Y6 Canada
                [2 ]ISNI 0000 0004 1936 8649, GRID grid.14709.3b, Faculty of Medicine, Department of Epidemiology, Biostatistics and Occupational Health, , McGill University, ; 1020 Pine Avenue West, Montreal, QC H3A 1A2 Canada
                [3 ]ISNI 0000 0001 2288 9830, GRID grid.17091.3e, Division of AIDS, Department of Medicine, , University of British Columbia, ; 667-1081 Burrard Street, Vancouver, BC V6Z 1Y6 Canada
                [4 ]ISNI 0000 0004 1936 7494, GRID grid.61971.38, Faculty of Health Sciences, , Simon Fraser University, ; Blusson Hall, Room 11300, 8888 University Drive, Burnaby, BC V5A 1S6 Canada
                Article
                4391
                10.1186/s12913-019-4391-8
                6724338
                31481056
                cae7427f-cc58-426c-b248-8f4be237d1fa
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 13 February 2019
                : 1 August 2019
                Funding
                Funded by: British Columbia Ministry of Health (CA)
                Award ID: Seek and Treat for Optimal Prevention of HIV & AIDS
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;
                Award ID: 201610PJT
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Health & Social care
                medical costs,hiv,hiv costs,regional costs,medical utilization
                Health & Social care
                medical costs, hiv, hiv costs, regional costs, medical utilization

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