Verughese Jacob1, Anilkrishna B Thota1, Sajal K Chattopadhyay1, Gibril J Njie1, Krista K Proia1, David P Hopkins1, Murray N Ross2, Nicolaas P Pronk3, John M Clymer4. 1. Community Guide Branch, Division of Public Health Information Dissemination, Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, USA. 2. Kaiser Institute for Health Policy, Oakland, CA, USA. 3. Health Management Division, HealthPartners Research Foundation, Minneapolis, MN, USA. 4. National Forum for Heart Disease and Stroke Prevention, Washington, DC, USA.
Abstract
OBJECTIVE: This review evaluates costs and benefits associated with acquiring, implementing, and operating clinical decision support systems (CDSSs) to prevent cardiovascular disease (CVD). MATERIALS AND METHODS: Methods developed for the Community Guide were used to review CDSS literature covering the period from January 1976 to October 2015. Twenty-one studies were identified for inclusion. RESULTS: It was difficult to draw a meaningful estimate for the cost of acquiring and operating CDSSs to prevent CVD from the available studies ( n = 12) due to considerable heterogeneity. Several studies ( n = 11) indicated that health care costs were averted by using CDSSs but many were partial assessments that did not consider all components of health care. Four cost-benefit studies reached conflicting conclusions about the net benefit of CDSSs based on incomplete assessments of costs and benefits. Three cost-utility studies indicated inconsistent conclusions regarding cost-effectiveness based on a conservative $50,000 threshold. DISCUSSION: Intervention costs were not negligible, but specific estimates were not derived because of the heterogeneity of implementation and reporting metrics. Expected economic benefits from averted health care cost could not be determined with confidence because many studies did not fully account for all components of health care. CONCLUSION: We were unable to conclude whether CDSSs for CVD prevention is either cost-beneficial or cost-effective. Several evidence gaps are identified, most prominently a lack of information about major drivers of cost and benefit, a lack of standard metrics for the cost of CDSSs, and not allowing for useful life of a CDSS that generally extends beyond one accounting period. Published by Oxford University Press on behalf of the American Medical Informatics Association 2017. This work is written by US Government employees and is in the public domain in the US.
OBJECTIVE: This review evaluates costs and benefits associated with acquiring, implementing, and operating clinical decision support systems (CDSSs) to prevent cardiovascular disease (CVD). MATERIALS AND METHODS: Methods developed for the Community Guide were used to review CDSS literature covering the period from January 1976 to October 2015. Twenty-one studies were identified for inclusion. RESULTS: It was difficult to draw a meaningful estimate for the cost of acquiring and operating CDSSs to prevent CVD from the available studies ( n = 12) due to considerable heterogeneity. Several studies ( n = 11) indicated that health care costs were averted by using CDSSs but many were partial assessments that did not consider all components of health care. Four cost-benefit studies reached conflicting conclusions about the net benefit of CDSSs based on incomplete assessments of costs and benefits. Three cost-utility studies indicated inconsistent conclusions regarding cost-effectiveness based on a conservative $50,000 threshold. DISCUSSION: Intervention costs were not negligible, but specific estimates were not derived because of the heterogeneity of implementation and reporting metrics. Expected economic benefits from averted health care cost could not be determined with confidence because many studies did not fully account for all components of health care. CONCLUSION: We were unable to conclude whether CDSSs for CVD prevention is either cost-beneficial or cost-effective. Several evidence gaps are identified, most prominently a lack of information about major drivers of cost and benefit, a lack of standard metrics for the cost of CDSSs, and not allowing for useful life of a CDSS that generally extends beyond one accounting period. Published by Oxford University Press on behalf of the American Medical Informatics Association 2017. This work is written by US Government employees and is in the public domain in the US.
Entities:
Keywords:
Decision support systems; clinical; economics; economics; medical
Authors: Thomas H Payne; David W Bates; Eta S Berner; Elmer V Bernstam; H Dominic Covvey; Mark E Frisse; Thomas Graf; Robert A Greenes; Edward P Hoffer; Gil Kuperman; Harold P Lehmann; Louise Liang; Blackford Middleton; Gilbert S Omenn; Judy Ozbolt Journal: J Am Med Inform Assoc Date: 2012-07-10 Impact factor: 4.497
Authors: Naomi S Bardach; Jason J Wang; Samantha F De Leon; Sarah C Shih; W John Boscardin; L Elizabeth Goldman; R Adams Dudley Journal: JAMA Date: 2013-09-11 Impact factor: 56.272
Authors: Gibril J Njie; Krista K Proia; Anilkrishna B Thota; Ramona K C Finnie; David P Hopkins; Starr M Banks; David B Callahan; Nicolaas P Pronk; Kimberly J Rask; Daniel T Lackland; Thomas E Kottke Journal: Am J Prev Med Date: 2015-11 Impact factor: 5.043
Authors: Michael Apkon; Jennifer A Mattera; Zhenqiu Lin; Jeph Herrin; Elizabeth H Bradley; Michael Carbone; Eric S Holmboe; Cary P Gross; Jared G Selter; Amy S Rich; Harlan M Krumholz Journal: Arch Intern Med Date: 2005-11-14
Authors: Bonnie B Blanchfield; Richard W Grant; Greg A Estey; Henry C Chueh; G Scott Gazelle; James B Meigs Journal: Int J Technol Assess Health Care Date: 2006 Impact factor: 2.188
Authors: Davis Bu; Eric Pan; Janice Walker; Julia Adler-Milstein; David Kendrick; Julie M Hook; Caitlin M Cusack; David W Bates; Blackford Middleton Journal: Diabetes Care Date: 2007-02-23 Impact factor: 19.112
Authors: R Herring; D L Russell-Jones; C Pengilley; H Hopkins; B Tuthill; J Wright; S V Hordern; S Davidson Journal: Diabet Med Date: 2013-01 Impact factor: 4.359
Authors: Michael D Murray; Lisa E Harris; J Marc Overhage; Xiao-Hua Zhou; George J Eckert; Faye E Smith; Nancy Nienaber Buchanan; Fredric D Wolinsky; Clement J McDonald; William M Tierney Journal: Pharmacotherapy Date: 2004-03 Impact factor: 4.705
Authors: Steven P Dehmer; Alan R Sinaiko; Nicole K Trower; Stephen E Asche; Heidi L Ekstrom; James D Nordin; Patrick J O'Connor; Elyse O Kharbanda Journal: Acad Pediatr Date: 2020-01-28 Impact factor: 3.107
Authors: JoAnn M Sperl-Hillen; Jeffrey P Anderson; Karen L Margolis; Rebecca C Rossom; Kristen M Kopski; Beth M Averbeck; Jeanine A Rosner; Heidi L Ekstrom; Steven P Dehmer; Patrick J O'Connor Journal: JMIR Form Res Date: 2022-10-06
Authors: Daniel Chavez-Yenter; Melody S Goodman; Yuyu Chen; Xiangying Chu; Richard L Bradshaw; Rachelle Lorenz Chambers; Priscilla A Chan; Brianne M Daly; Michael Flynn; Amanda Gammon; Rachel Hess; Cecelia Kessler; Wendy K Kohlmann; Devin M Mann; Rachel Monahan; Sara Peel; Kensaku Kawamoto; Guilherme Del Fiol; Meenakshi Sigireddi; Saundra S Buys; Ophira Ginsburg; Kimberly A Kaphingst Journal: JAMA Netw Open Date: 2022-10-03
Authors: Sajal K Chattopadhyay; Verughese Jacob; Shawna L Mercer; David P Hopkins; Randy W Elder; Christopher D Jones Journal: Am J Prev Med Date: 2017-12 Impact factor: 5.043
Authors: Edwin A Lomotan; Ginny Meadows; Maria Michaels; Jeremy J Michel; Kristen Miller Journal: Appl Clin Inform Date: 2020-02-12 Impact factor: 2.342