Regional/National Ele ctronic Health Records Cost-benefit analysis: a systematic review

1. Regional/National Electronic Health RecordsCost-benefit analysis:a systematic review Class 4 aturma4@gmail.com 21st May2012

2. CONCEPTS: Electronic Health Records Introduction  “Media that facilitate transportability of pertinent information concerning patient's illness across varied providers and geographic locations. Some versions include direct linkages to online consumer health information that is relevant to the health conditions and treatments related to a specific patient” PubMed - MeSH, 2010  “Electronically stored and transmitted medical record that contains patientdemographics, medical history, lab tests, X-rays, scans, prescription lists, and any other relevant information” Wulsin, L. and Dougherty, A., 2008 Wulsin, L. and Dougherty, A., Health information technology - Electronic health records: a primer, California State Library, 2008 (http://www.library.ca.gov/crb/08/08-013.pdf) http://www.ncbi.nlm.nih.gov/mesh/68057286

3. CONCEPTS: Cost-Benefit Analysis Introduction “a method of comparing the cost of a program with its expected benefits in dollars (or other currency); the benefit-to-cost ratio is a measure of total return expected per unit of money spent. This analysis generally excludes consideration of factors that are not measured ultimately in economic terms. Cost effectiveness compares alternative ways to achieve a specific set of results.”(PubMed – MeSH, 1976) http://mavit.kabunzo.com/tag/dolar/

4. EHR: Why so delayed? Introduction It is generally agreed that EHRs hold great promise for improving healthcare quality and efficiency But healthcare is decades behind other industries dealing with Information Technology adoption There is an urgent need for hospitals to adopt general EHR systems. However, the efforts of government and other EHR advocates have not sufficiently accelerated the diffusion trajectory. Lori T. Peterson et al., Assessing Differences Between Physicians’ Realized and Anticipated Gains from Electronic Health Record Adoption, 2009

5. Costsandbenefits: economicissues Introduction Costsversusbenefits - Activities - Personnel - Executive management - Human resource and finance - Building - Supplies - Electronic health record - Other operating expenses  Government incentives for use health IT  Pay-for-performance incentives  Eliminating costs of a storing paper records  Downsizing personnel IT – information technology Dukyong Yoona et al., Adoption of electronic health records in Korean tertiary teaching and general hospitals, 2012, International Journal of Medical Informatics 81 (2012) 196–203

6. Barriers to adoption of EHRs (e.g. South Korea) Discussion

7. Facilitators of adoption of EHRs (e.g. South Korea) Discussion Dukyong Yoona et al., Adoption of electronic health records in Korean tertiary teaching and general hospitals, 2012, International Journal of Medical Informatics 81 (2012) 196–203

8. Research Questions What is the return per unit of money spent on regional or national EHR systems?  Is this system financially supported by the government of each country where it was implemented? http://aep.ist.utl.pt/divulgacao/publicacoes/

9. Aim •  To review the published literature regarding the financial costs and benefits of regional or national Electronic Health Records. •  Find out which records characteristics are associated to a bigger investment return. •  Measure the differences relating to the return of investment between all regions. With this, we intend to…

10. Methods Systematic Review A systematic review is a method of identifying, appraising, and synthesising research evidence. The aim is to evaluate and interpret all available research that is relevant to a particular review question. In a systematic review, the scope (for example, the review question and any sub-questions and/or sub-group analyses) is defined in advance, and the methods to be used at each step are specified. The steps include: a comprehensive search to find all relevant studies; the use of criteria to include or exclude studies; and the application of established standards to appraise study quality. Lucie Rychetnik, Penelope Hawe, Elizabeth Waters, Alexandra Barratt, Michael Frommer. A glossary for evidence based public health. J Epidemiol Community Health2004;58:538-545 doi:10.1136/jech.2003.011585. (17/12/2011)

11. How did we create thequeries? Methods Make an inventory of synonyms of the key terms of the research

12. Howdidwecreatethequeries? Methods  Combine the terms in the query using Boolean operators.

13. Howdidwecreatethequeries? Methods  Establish limits on the search Limitthesearch to thetimespan:  1994 to 2012 Limitthesearch to articles in:  English  French Excludedarticleson:  Maths  VeterinarySciences  History  Anthropology Chemistry Physics  Architecture  Geography  Linguistics Religion  Zoology

14. Collecting articles Methods  Insert queries in three different Databases DATABASES 2199 851 1312 TOTAL: 4362

15. Query – PUBMED Methods (("Electronic Health Record*" OR "Electronic Medical Record*" OR "Electronic Patient Record*" OR "Computer* Patient Record*" OR "Computer* Health record*" OR "Computer* Medical Record*" OR "Digital Health Record*" OR "Digital medical record*" OR "Digital patient record*") AND ("Cost-benefit" OR cost OR costs))

16. Query – ISI WEB OF KNOWLEDGE Methods Topic=((("Electronic Health Record*" OR "Electronic Medical Record*" OR "Electronic Patient Record*" OR "Computer* Patient Record*" OR "Computer* Health record*" OR "Computer* Medical Record*" OR "Digital Health Record*" OR "Digital medical record*" OR "Digital patient record*") AND ("Cost-benefit" OR cost OR costs))) Refined by: [excluding] Subject Areas=( VETERINARY SCIENCES OR HISTORY OR ANTHROPOLOGY OR CHEMISTRY OR PHYSICS OR ARCHITECTURE OR GEOGRAPHY OR LINGUISTICS OR RELIGION OR ZOOLOGY ) AND Languages=( ENGLISH OR UNSPECIFIED OR FRENCH ) Timespan=1994-2012.

17. Query – SCOPUS Methods (("Electronic Health Record*" OR "Electronic Medical Record*" OR "Electronic Patient Record*" OR "Computer* Patient Record*" OR"Computer* Health record*" OR "Computer* Medical Record*" OR "Digital Health Record*" OR "Digital medical record*" OR "Digital patient record*") AND ("Cost-benefit" OR cost OR costs))) AND (EXCLUDE(SUBJAREA, "CENG") OR EXCLUDE(SUBJAREA, "MATH") OR EXCLUDE(SUBJAREA, "PHYS") OREXCLUDE(SUBJAREA, "AGRI") OR EXCLUDE(SUBJAREA, "MATE") OR EXCLUDE(SUBJAREA, "ENVI") OR EXCLUDE(SUBJAREA, "ARTS") OREXCLUDE(SUBJAREA, "VETE") OR EXCLUDE(SUBJAREA, "CHEM")) AND (LIMIT-TO(LANGUAGE, "English") OR LIMIT-TO(LANGUAGE, "French")) AND (LIMIT-TO(PUBYEAR, 2012) OR LIMIT-TO(PUBYEAR, 2011) OR LIMIT-TO(PUBYEAR, 2010) OR LIMIT-TO(PUBYEAR, 2009) OR LIMIT-TO(PUBYEAR, 2008) OR LIMIT-TO(PUBYEAR, 2007) OR LIMIT-TO(PUBYEAR, 2006) OR LIMIT-TO(PUBYEAR, 2005) OR LIMIT-TO(PUBYEAR, 2004) OR LIMIT-TO(PUBYEAR, 2003) OR LIMIT-TO(PUBYEAR, 2002) OR LIMIT-TO(PUBYEAR, 2001) OR LIMIT-TO(PUBYEAR, 2000) OR LIMIT-TO(PUBYEAR, 1999) OR LIMIT-TO(PUBYEAR, 1998) OR LIMIT-TO(PUBYEAR, 1997) OR LIMIT-TO(PUBYEAR, 1996) OR LIMIT-TO(PUBYEAR, 1995) OR LIMIT-TO(PUBYEAR, 1994))

18. Collecting the Final Articles – Step by step Methods  Exclude the repeated articles  Exclude the non-real articles (ex: letters, conversations, news)  First exclusion by abstract with two revisors

19. Collecting the Final Articles – Step by step Methods  Exclude the articles from previous years than 2008  Get the full-texts available – search on 7 different databases (PubMed, Google Scholar, B-On, Scopus, Isi Web of Knowledge, AtoZ, EBSCO)  Contact the authors to ask for the articles of interest that were not available  Second exclusion reading the full-article, according to the same parameters as the first one Extract data from the articles

20. Selection of the Articles - STEPS Methods  Repeated: 1425  Notarticles: 316

21. Selection of the Articles - STEPS Methods

22. Selection of the Articles - STEPS Methods

23. Variables Methods • Country wherethesystemisimplemented • Date ofarticlepublication • Institutions involved • What type of medical data is integrated • User groups • Financing agents • Cost Savings • Costs of initial investment • Profit

24. Countries where the systems were implemented Results • USA • South Korea • Japan • Norway • UnitedKingdom • India

25. Date of article publication Results • 2008-2012 • Hospitals • Physician groups • Clinics • Nursing homes • Municipal health station • Community health centers • RHIOs Institutions involved

26. Type of data integrated Results • Insurance coverage and benefits • Payment remittance advice • Electronic radiology reports • Computerized physician order entry for medications • Electronic physician notes • Data about the patient’s consults • Demographic information • Nursing assessments • Medication lists • Discharge summaries • Laboratory, radiology reports and other diagnostic testing

27. User groups Results • Health care providers • Payers • Pharmacists • Chiropractors • Doctors • Physicians • Patients • Nurses • All hospital services

28. Financing Agents Results • Government • CNO • Massachusetts eHealth Collaborative and New York City Primary Care Information Project • Other EHR advocates

29. Initial Investment Results

30. Cost Savings Results

31. Conclusions • In terms of cost savings, we studied them per year. • The investment from government or other entities was, in mean, 24 billion dollars, being the highest value from the USA, 77.8 billion dollars and the lowest 36500, also from USA (Massachusetts and New York). • Our data related to cost savings came from 13 articles that referred values varying from 81 billion dollars to 42000 dollars. • In mean, 22 billion dollars were saved per year with EHR. • With two exceptions (Korea and UK), all of this was related to USA medical institutions.

32. Conclusions • From this point of view, EHR appear as advantageous. However, when compared to the mean of investment, which is 24 billion, we observe that this is not that linear. • In terms of profit, the target articles almost didn’t contain this type of information. Just some of them stated that the profit was 11billion, 20-30 billion, 1-2 million or 154,900 per year.

33. Conclusions • One of the main limitations to our project was the lack of relevant information in the final articles selected • The access to the full-text of many articles was denied and when asking the authors to provide us their articles, the majority did not answer us • The variables related to monetary values, such as initial cost investment, cost savings and profit, did not gathered information in every article

34. Conclusion From our systematic review, because the major barriers to adoption of EHRs are financial, we suggest that hospitals in better financial position with regard to liquidity, profitability and human resources efficiency will be more likely to adopt EHRs.

35. References Abraham, S. (2010). Technological trends in health care: electronic health record. Thehealthcare manager, 29: 318-23 Adler-Milstein, J. et al. (2011). A Survey of Health Information Exchange Organizations in the United States: Implications for Meaningful Use. Annals of internal medicine, 154: 666-W241. Al Hajeri, A. (2011). Electronic Health Records in Primary Care: Are We Ready? Bahrain Medical Bulletin, 33 Bahensky, J. et al. (2008). Health care information technology in rural America: electronic medical record adoption status in meeting the national agenda. The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association, 24: 101-5 Bailit, M. and Koller, C. (2009). Using insurance standards and policy levers to build a high performance health system. Issue brief (Commonwealth Fund), 70: 1-12 Balfour D. et al. (2009). Health information technology--results from a roundtable discussion. Journal of managed care pharmacy: JMCP, 15: 10-7 Behkami, N. et al. (2010). A Business case for HIT Adoption: effects of “meaningful use” EHR financial incentives on clinic revenue. Studies in health technology and informatics, 160(Pt 1): 779-783. Bernd, DL. and Fine, PS. (2011). Electronic medical records: a path forward. Frontiers of health services management, 28: 3-13. Black, A. et al. (2011). The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS medicine, 8 Cherry, B. et al. (2011). Experiences with electronic health records: early adopters in long- term care facilities. Health care management review, 36: 265-74 Dixon, B. et al. (2010). A Framework for evaluating the costs, effort, and value of nationwide health information exchange. Journal of the American medical informatics association, 17: 295-301. Federowicz, M. et al. (2010). A tutorial on activity-based costing of electronic health records. Quality Management in Health Care, 19: 86-89. Furukawa, M. et al. (2010). Electronic medical records and cost efficiency in hospital medical-surgical units. Inquiry: a journal of medical care organization, provision and financing, 47: 110-23 Furukawa, M. et al. (2010). Electronic medical records, nurse staffing, and nurse-sensitive patient outcomes: evidence from California hospitals, 1998-2007. Health services research, 45: 941-62 Gans, D. (2010). Going electronic pays off. New MGMA report links EHRs with higher medical revenue. MGMA connexion / Medical group Management Association, 10: 21-2 Ginn, G. et al. (2011). Hospital financial position and the adoption of electronic health records. Journal of healthcare management / American College of Healthcare Executives, 56: 337-50 Haugen, DK. (2009). A blueprint for 21st century health care: requirements for standard, electronic administrative data. Minnesota medicine, 92: 42-43. Heimly, V. et al. (2010). Diffusion and use of Electronic Health Record Systems in Norway. Studies in Health Technology and Informatics, 160: 381-385 Himmelstein, D. et al. (2010). Hospital computing and the costs and quality of care: a national study. The American journal of medicine, 123: 40-6 Hollar, D. (2009). Progress along developmental tracks for electronic health records implementation in the United States. Health research policy and systems / BioMed Central, 7 Hussain, A. (2011). Meaningful use of information technology: a local perspective. Annals of internal medicine, 154: 690-2 Jha, A. et al. (2010). A progress report on electronic health records in U.S. hospitals. Health affairs, 29: 1951-1957. Jones, S. et al. Electronic health record adoption and quality improvement in US hospitals. The American journal of managed care, 16: SP64-71 Joseph, M. (2010). Meaningful streamlining. Hybrid practice management/EMR system boosts quality, reduces costs. Modern healthcare, 40: C8 Kumar, S. and Aldrich, K. (2010). Overcoming barriers to electronic medical record (EMR) implementation in the US healthcare system: A comparative study. Health informatics journal,16: 306-18

36. References Kumar, S. and Bauer, K. (2011). The business case for implementing electronic health records in primary care settings in the United States. Journal of Revenue and Pricing Management, 10: 119-131 Li, K. et al. (2012). Study of the Cost-Benefit Analysis of Electronic Medical Record Systems in General Hospital in China. Journal of medical systems, 1-9 Menachemi, N. and Collum, T. (2011). Benefits and drawbacks of electronic health record systems. Risk management and healthcare policy, 4: 47-55. Milstein, A, Darling. (2010). Better U.S. Health Care at Lower Cost. Issues in science and technology, 31-40. Mohapatra, S. (2009). Better healthcare at reduced cost through electronic integration of patient care data. International journal of electronic healthcare, 5: 87-98 Mostashari, F. et al. (2009). A tale of two large community electronic health record extension projects. Health Affairs, 28: 345-356. Murer, C. (2010). Meaningful use rules proposed electronic health record incentives under HITECH act. Rehab management, 23: 32-3 Palacio, C. et al. (2010). Benchmarking electronic medical records initiatives in the US: A conceptual model. Journal of Medical Systems, 34: 273-279. Payne, T. et al. (2011). National-scale clinical information exchange in the United Kingdom: lessons for the United States. Journal of the American Medical Informatics Association: JAMIA, 18: 91-8 Peterson, L. et al. (2011). Assessing differences between physicians' realized and anticipated gains from electronic health record adoption. Journal of Medical Systems, 35: 151-161. Pitcher, E. (2010). CNO Role in the Implementation of an Electronic Health Record. Nurse Leader, 8: 32-35. Police, R. et al. (2011). Adoption and use of health information technology in physician practice organisations: systematic review. Informatics in Primary Care, 18: 245–258. Richardson, C. et al. (2010). Lessons from credit bureaus for improving the market for electronic medical records. Journal of Consumer Affairs, 44: 546-556 Song, P. et al. (2011). Exploring the business case for ambulatory electronic health record system adoption. Journal of healthcare management / American College of Healthcare Executives, 56: 169-82. Stanberry, K. (2011). US and global efforts to expand the use of electronic health records. Records Management Journal, 21: 214-224 Swab, J. and Ciotti, V. (2010). What to consider when purchasing an EHR system. Healthcare financial management : journal of the Healthcare Financial Management Association, 64: 38-41 Thompson, D. and Fleming, N. (2008). Finding the ROI in EMRs. Healthcare financial management : journal of the Healthcare Financial Management Association, 62: 76-81 Thompson, D. et al. (2010). Reducing clinical costs with an EHR. Healthcare financial management : journal of the Healthcare Financial Management Association, 64: 106-8 Whittaker, L. et al. (2010). Effect of Implementing a Computerized System for Bone Mineral Density Storage and Report Preparation on Result Turnaround Time and Savings in Cost , Time, and Space . Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists, 16:30-5. Yasunaga, H. et al.(2008). Computerizing medical records in Japan. International journal of medical informatics, 77: 708-13 Yoon, D. et al. (2012). Adoption of electronic health records in Korean tertiary teaching and general hospitals. International Journal of Medical Informatics, 81: 196-203. Zhivan, N. and Diana M. (2012). U.S. hospital efficiency and adoption of health information technology. Health care management science, 15: 37-47 Zlabek, J. et al. (2011). Early cost and safety benefits of an inpatient electronic health record. Journal of the American Medical Informatics Association, 18: 169-172