Literature DB >> 12714130

A cost-benefit analysis of electronic medical records in primary care.

Samuel J Wang1, Blackford Middleton, Lisa A Prosser, Christiana G Bardon, Cynthia D Spurr, Patricia J Carchidi, Anne F Kittler, Robert C Goldszer, David G Fairchild, Andrew J Sussman, Gilad J Kuperman, David W Bates.   

Abstract

Electronic medical record systems improve the quality of patient care and decrease medical errors, but their financial effects have not been as well documented. The purpose of this study was to estimate the net financial benefit or cost of implementing electronic medical record systems in primary care. We performed a cost-benefit study to analyze the financial effects of electronic medical record systems in ambulatory primary care settings from the perspective of the health care organization. Data were obtained from studies at our institution and from the published literature. The reference strategy for comparisons was the traditional paper-based medical record. The primary outcome measure was the net financial benefit or cost per primary care physician for a 5-year period. The estimated net benefit from using an electronic medical record for a 5-year period was 86,400 US dollars per provider. Benefits accrue primarily from savings in drug expenditures, improved utilization of radiology tests, better capture of charges, and decreased billing errors. In one-way sensitivity analyses, the model was most sensitive to the proportion of patients whose care was capitated; the net benefit varied from a low of 8400 US dollars to a high of 140,100 US dollars . A five-way sensitivity analysis with the most pessimistic and optimistic assumptions showed results ranging from a 2300 US dollars net cost to a 330,900 US dollars net benefit. Implementation of an electronic medical record system in primary care can result in a positive financial return on investment to the health care organization. The magnitude of the return is sensitive to several key factors. Copyright 2003 by Excerpta Medica Inc.

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Year:  2003        PMID: 12714130     DOI: 10.1016/s0002-9343(03)00057-3

Source DB:  PubMed          Journal:  Am J Med        ISSN: 0002-9343            Impact factor:   4.965


  137 in total

1.  Learning relational policies from electronic health record access logs.

Authors:  Bradley Malin; Steve Nyemba; John Paulett
Journal:  J Biomed Inform       Date:  2011-01-26       Impact factor: 6.317

Review 2.  Using electronic health records to help coordinate care.

Authors:  Lynda C Burton; Gerard F Anderson; Irvin W Kues
Journal:  Milbank Q       Date:  2004       Impact factor: 4.911

3.  Study of the cost-benefit analysis of electronic medical record systems in general hospital in China.

Authors:  Kai Li; Shinji Naganawa; Kai Wang; Ping Li; Ken Kato; Xiu Li; Jie Zhang; Kazunobu Yamauchi
Journal:  J Med Syst       Date:  2012-01-03       Impact factor: 4.460

4.  Workflow and electronic health records in small medical practices.

Authors:  Mala Ramaiah; Eswaran Subrahmanian; Ram D Sriram; Bettijoyce B Lide
Journal:  Perspect Health Inf Manag       Date:  2012-04-01

5.  Healthcare information technology and economics.

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

6.  Assessing differences between physicians' realized and anticipated gains from electronic health record adoption.

Authors:  Lori T Peterson; Eric W Ford; John Eberhardt; Timothy R Huerta; Nir Menachemi
Journal:  J Med Syst       Date:  2009-08-08       Impact factor: 4.460

7.  Transaction-neutral implanted data collection interface as EMR driver: a model for emerging distributed medical technologies.

Authors:  Daniel Lorence; Anusha Sivaramakrishnan; Michael Richards
Journal:  J Med Syst       Date:  2009-03-20       Impact factor: 4.460

8.  Benchmarking electronic medical records initiatives in the US: a conceptual model.

Authors:  Carlos Palacio; Jeffrey P Harrison; David Garets
Journal:  J Med Syst       Date:  2010-06       Impact factor: 4.460

9.  Substance abuse treatment programs' data management capacity: an exploratory study.

Authors:  Jennifer P Wisdom; James H Ford; Meg Wise; Deirdre Mackey; Carla A Green
Journal:  J Behav Health Serv Res       Date:  2011-04       Impact factor: 1.505

10.  Prediction of hospitalization due to heart diseases by supervised learning methods.

Authors:  Wuyang Dai; Theodora S Brisimi; William G Adams; Theofanie Mela; Venkatesh Saligrama; Ioannis Ch Paschalidis
Journal:  Int J Med Inform       Date:  2014-10-16       Impact factor: 4.046

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