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      Cost Effectiveness of Internet Interventions: Review and Recommendations

      research-article
      , Ph.D. 1 , 2 , , , Ph.D., MHA 3 , , M.A. 4 , , MPH, RD 2
      Annals of Behavioral Medicine
      Springer-Verlag
      Internet interventions, Public health impact, Economic evaluations

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          Abstract

          Background

          Internet interventions have a large potential for public health impact, and their efficacy has been established over the past 10–15 years. Cost effectiveness of Internet interventions is one of the most frequently cited reasons for developing such treatments.

          Purpose

          This paper provides a review of economic evaluations of Internet interventions with specific recommendations for future economic analyses of Internet interventions.

          Methods

          A review of PubMed from 1995 through 2008 was conducted.

          Results

          We identified eight studies that reported specific economic indicators associated with an Internet intervention, though many were lacking comprehensive analyses. Issues related to analysis perspective, included costs, type of analysis performed, and appropriate outcomes for Internet interventions are explored.

          Conclusions

          The lack of cost data published to date is likely a reflection of the early stage of research for many papers published during the review period. As the field now moves to effectiveness studies, it is important for cost-effectiveness data to be collected.

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          Most cited references16

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          The Effectiveness of Web-Based vs. Non-Web-Based Interventions: A Meta-Analysis of Behavioral Change Outcomes

          Background A primary focus of self-care interventions for chronic illness is the encouragement of an individual's behavior change necessitating knowledge sharing, education, and understanding of the condition. The use of the Internet to deliver Web-based interventions to patients is increasing rapidly. In a 7-year period (1996 to 2003), there was a 12-fold increase in MEDLINE citations for “Web-based therapies.” The use and effectiveness of Web-based interventions to encourage an individual's change in behavior compared to non-Web-based interventions have not been substantially reviewed. Objective This meta-analysis was undertaken to provide further information on patient/client knowledge and behavioral change outcomes after Web-based interventions as compared to outcomes seen after implementation of non-Web-based interventions. Methods The MEDLINE, CINAHL, Cochrane Library, EMBASE, ERIC, and PSYCHInfo databases were searched for relevant citations between the years 1996 and 2003. Identified articles were retrieved, reviewed, and assessed according to established criteria for quality and inclusion/exclusion in the study. Twenty-two articles were deemed appropriate for the study and selected for analysis. Effect sizes were calculated to ascertain a standardized difference between the intervention (Web-based) and control (non-Web-based) groups by applying the appropriate meta-analytic technique. Homogeneity analysis, forest plot review, and sensitivity analyses were performed to ascertain the comparability of the studies. Results Aggregation of participant data revealed a total of 11,754 participants (5,841 women and 5,729 men). The average age of participants was 41.5 years. In those studies reporting attrition rates, the average drop out rate was 21% for both the intervention and control groups. For the five Web-based studies that reported usage statistics, time spent/session/person ranged from 4.5 to 45 minutes. Session logons/person/week ranged from 2.6 logons/person over 32 weeks to 1008 logons/person over 36 weeks. The intervention designs included one-time Web-participant health outcome studies compared to non-Web participant health outcomes, self-paced interventions, and longitudinal, repeated measure intervention studies. Longitudinal studies ranged from 3 weeks to 78 weeks in duration. The effect sizes for the studied outcomes ranged from -.01 to .75. Broad variability in the focus of the studied outcomes precluded the calculation of an overall effect size for the compared outcome variables in the Web-based compared to the non-Web-based interventions. Homogeneity statistic estimation also revealed widely differing study parameters (Qw16 = 49.993, P ≤ .001). There was no significant difference between study length and effect size. Sixteen of the 17 studied effect outcomes revealed improved knowledge and/or improved behavioral outcomes for participants using the Web-based interventions. Five studies provided group information to compare the validity of Web-based vs. non-Web-based instruments using one-time cross-sectional studies. These studies revealed effect sizes ranging from -.25 to +.29. Homogeneity statistic estimation again revealed widely differing study parameters (Qw4 = 18.238, P ≤ .001). Conclusions The effect size comparisons in the use of Web-based interventions compared to non-Web-based interventions showed an improvement in outcomes for individuals using Web-based interventions to achieve the specified knowledge and/or behavior change for the studied outcome variables. These outcomes included increased exercise time, increased knowledge of nutritional status, increased knowledge of asthma treatment, increased participation in healthcare, slower health decline, improved body shape perception, and 18-month weight loss maintenance.
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            Recommendations of the Panel on Cost-effectiveness in Health and Medicine.

            To develop consensus-based recommendations for the conduct of cost-effectiveness analysis (CEA). This article, the second in a 3-part series, describes the basis for recommendations constituting the reference case analysis, the set of practices developed to guide CEAs that inform societal resource allocation decisions, and the content of these recommendations. The Panel on Cost-Effectiveness in Health and Medicine, a nonfederal panel with expertise in CEA, clinical medicine, ethics, and health outcomes measurement, was convened by the US Public Health Service (PHS). The panel reviewed the theoretical foundations of CEA, current practices, and alternative methods used in analyses. Recommendations were developed on the basis of theory where possible, but tempered by ethical and pragmatic considerations, as well as the needs of users. The panel developed recommendations through 2 1/2 years of discussions. Comments on preliminary drafts prepared by panel working groups were solicited from federal government methodologists, health agency officials, and academic methodologists. The panel's methodological recommendations address (1) components belonging in the numerator and denominator of a cost-effectiveness (C/E) ratio; (2) measuring resource use in the numerator of a C/E ratio; (3) valuing health consequences in the denominator of a C/E ratio; (4) estimating effectiveness of interventions; (5) incorporating time preference and discounting; and (6) handling uncertainty. Recommendations are subject to the ¿rule of reason,¿ balancing the burden engendered by a practice with its importance to a study. If researchers follow a standard set of methods in CEA, the quality and comparability of studies, and their ultimate utility, can be much improved.
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              Assessing cost-effectiveness in healthcare: history of the $50,000 per QALY threshold.

              Cost-effectiveness analyses, particularly in the USA, commonly use a figure of $50,000 per life-year or quality-adjusted life-year gained as a threshold for assessing the cost-effectiveness of an intervention. The history of this practice is ill defined, although it has been linked to the end-stage renal disease kidney dialysis cost-effectiveness literature from the 1980s. The use of $50,000 as a benchmark for assessing the cost-effectiveness of an intervention first emerged in 1992 and became widely used after 1996. The appeal of the $50,000 figure appears to lie in the convenience of a round number rather than in the value of renal dialysis. Rather than arbitrary thresholds, estimates of willingness to pay and the opportunity cost of healthcare resources are needed.
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                Author and article information

                Contributors
                +1-919-9667546 , dtate@unc.edu
                Journal
                Ann Behav Med
                Annals of Behavioral Medicine
                Springer-Verlag (New York )
                0883-6612
                1532-4796
                17 October 2009
                August 2009
                : 38
                : 1
                : 40-45
                Affiliations
                [1 ]Department of Health Behavior and Health Education, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7440 USA
                [2 ]Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7461 USA
                [3 ]Health Services and Systems Research Program, Duke-NUS Graduate Medical School, Singapore, Singapore 169857
                [4 ]Division of Health, Social, and Economics Research, RTI International, Research Triangle Park, NC 27709-2194 USA
                Article
                9131
                10.1007/s12160-009-9131-6
                2772952
                19834778
                dec223cf-51b3-4a23-a0a1-2d6ecead3445
                © The Author(s) 2009
                History
                Categories
                Original Article
                Custom metadata
                © The Society of Behavioral Medicine 2009

                Neurology
                economic evaluations,public health impact,internet interventions
                Neurology
                economic evaluations, public health impact, internet interventions

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