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      High‐Cost Users of Prescription Drugs: A Population‐Based Analysis from British Columbia, Canada

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          Abstract

          Objective

          To examine variation in pharmaceutical spending and patient characteristics across prescription drug user groups.

          Data Sources

          British Columbia's population‐based linked administrative health and sociodemographic databases ( N = 3,460,763).

          Study Design

          We classified individuals into empirically derived prescription drug user groups based on pharmaceutical spending patterns outside hospitals from 2007 to 2011. We examined variation in patient characteristics, mortality, and health services usage and applied hierarchical clustering to determine patterns of concurrent drug use identifying high‐cost patients.

          Principal Findings

          Approximately 1 in 20 British Columbians had persistently high prescription costs for 5 consecutive years, accounting for 42 percent of 2011 province‐wide pharmaceutical spending. Less than 1 percent of the population experienced discrete episodes of high prescription costs; an additional 2.8 percent transitioned to or from high‐cost episodes of unknown duration. Persistent high‐cost users were more likely to concurrently use multiple chronic medications; episodic and transitory users spent more on specialized medicines, including outpatient cancer drugs. Cluster analyses revealed heterogeneity in concurrent medicine use within high‐cost groups.

          Conclusions

          Whether low, moderate, or high, costs of prescription drugs for most individuals are persistent over time. Policies controlling high‐cost use should focus on reducing polypharmacy and encouraging price competition in drug classes used by ordinary and high‐cost users alike.

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          Most cited references23

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          Gender differences in the utilization of health care services.

          Studies have shown that women use more health care services than men. We used important independent variables, such as patient sociodemographics and health status, to investigate gender differences in the use and costs of these services. New adult patients (N = 509) were randomly assigned to primary care physicians at a university medical center. Their use of health care services and associated charges were monitored for 1 year of care. Self-reported health status was measured using the Medical Outcomes Study Short Form-36 (SF-36). We controlled for health status, sociodemographic information, and primary care physician specialty in the statistical analyses. Women had significantly lower self-reported health status and lower mean education and income than men. Women had a significantly higher mean number of visits to their primary care clinic and diagnostic services than men. Mean charges for primary care, specialty care, emergency treatment, diagnostic services, and annual total charges were all significantly higher for women than men; however, there were no differences for mean hospitalizations or hospital charges. After controlling for health status, sociodemographics, and clinic assignment, women still had higher medical charges for all categories of charges except hospitalizations. Women have higher medical care service utilization and higher associated charges than men. Although the appropriateness of these differences was not determined, these findings have implications for health care.
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            Development and application of a population-oriented measure of ambulatory care case-mix.

            This article describes a new case-mix methodology applicable primarily to the ambulatory care sector. The Ambulatory Care Group (ACG) system provides a conceptually simple, statistically valid, and clinically relevant measure useful in predicting the utilization of ambulatory health services within a particular population group. ACGs are based on a person's demographic characteristics and their pattern of disease over an extended period of time, such as a year. Specifically, the ACG system is driven by a person's age, sex, and ICD-9-CM diagnoses assigned during patient-provider encounters; it does not require any special data beyond those collected routinely by insurance claims systems or encounter forms. The categorization scheme does not depend on the presence of specific diagnoses that may change over time; rather it is based on broad clusters of diagnoses and conditions. The presence or absence of each disease cluster, along with age and sex, are used to classify a person into one of 51 ACG categories. The ACG system has been developed and tested using computerized encounter and claims data from more than 160,000 continuous enrollees at four large HMOs and a state's Medicaid program. The ACG system can explain more than 50% of the variance in ambulatory resource use if used retrospectively and more than 20% if applied prospectively. This compares with 6% when age and sex alone are used. In addition to describing ACG development and validation, this article also explores some potential applications of the system for provider payment, quality assurance, utilization review, and health services research, particularly as it relates to capitated settings.
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              Deprescribing: Achieving Better Health Outcomes for Older People through Reducing Medications

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                Author and article information

                Contributors
                steve.morgan@ubc.ca
                Journal
                Health Serv Res
                Health Serv Res
                10.1111/(ISSN)1475-6773
                HESR
                Health Services Research
                John Wiley and Sons Inc. (Hoboken )
                0017-9124
                1475-6773
                18 April 2016
                April 2017
                : 52
                : 2 ( doiID: 10.1111/hesr.2017.52.issue-2 )
                : 697-719
                Affiliations
                [ 1 ]University of British Columbia (UBC) School of Population and Public Health Vancouver BCCanada
                Author notes
                [*] [* ]Address correspondence to Steven G. Morgan, Ph.D., University of British Columbia (UBC) School of Population and Public Health, 2206 East Mall, Vancouver, BC, Canada V6T 1Z9; e‐mail: steve.morgan@ 123456ubc.ca .
                Article
                HESR12492
                10.1111/1475-6773.12492
                5346502
                27087391
                876ce255-0c92-45e6-9503-b4c25e892cd8
                © 2016 The Authors. Health Services Research published by Wiley Periodicals, Inc. on behalf of Health Research and Educational Trust

                This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                Page count
                Figures: 1, Tables: 3, Pages: 23, Words: 8770
                Funding
                Funded by: Canadian Institutes of Health Research
                Award ID: CIHR DCO150GP
                Funded by: CIHR Banting Postdoctoral Fellowship
                Categories
                Research Article
                Costs and Expenditures
                Custom metadata
                2.0
                hesr12492
                April 2017
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.0.9 mode:remove_FC converted:20.04.2017

                Health & Social care
                prescription drug costs,high‐cost users,population‐based analysis
                Health & Social care
                prescription drug costs, high‐cost users, population‐based analysis

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