HTTP/1.0 200 OK Cache-Control: private, must-revalidate Content-Type: text/html; charset=UTF-8 Date: Sun, 29 Nov 2020 01:36:13 GMT Expires: -1 Pragma: no-cache 内蒙古11选五计划软件
LED行业深度报告:洗尽铅华 光芒更夺目
房企涌入住房租赁 传统开发模式将被颠覆? / 2011 / Article

Research Article | Open Access

Volume 2 |Article ID 628634 | 卖场难觅婴儿家具 市民购买多依靠网络

Farrokh Alemi, Manaf Zargoush, James L. Oakes, Hanan Edrees, "A Simple Method for Causal Analysis of Return on IT Investment", Journal of Healthcare Engineering, vol. 2, Article ID 628634, 12 pages, 2011.

A Simple Method for Causal Analysis of Return on IT Investment

Received01 Aug 2010
Accepted01 Nov 2010


n. 繁荣,兴旺
High and rising US rates may quickly become drivers of EM crises: such conditions may lead to higher borrowing costs in EMs, along with capital outflows and an unwillingness by the financial sector to take risks.
Viewers of online live broadcasting can send virtual gifts, which they purchase, to broadcasters. Gifts range from 0.1 yuan to more than 1,000 yuan. A percentage of the money goes to the platform.
After working for half a year, the average monthly income for 2014 graduates is RMB3,487, a significant increase from RMB3,250 in 2013 and RMB3,048 in 2012.
Gross National Happiness
Perhaps in response, at the start of 2017, China's media regulator quietly began including service fees charged by online ticketing companies when reporting box-office figures.
n. 大巴,教练;(火车)客车车厢,四轮马车,经济舱马纳尔·阿尔-谢里夫(Manal al-Sharif)
"Students are not suited for starting businesses on their own," said Zhang, adding that vocational students are more eager to start businesses than university undergraduates.
British statisticians’ unwillingness to correct known errors in the clothing price component of the RPI redistributes many billions every year from students, recent graduates, taxpayers and rail commuters to index-linked UK government bondholders, wealthy pensioners with RPI-linked pensions and rail companies.


  1. S. Xu, “Advancing return on investment analysis for electronic health record investment. Impacts of payment mechanisms and public returns,” J Healthc Inf Manag, vol. 21, no. 4, pp. 32–9, 2007 Fall. View at: Google Scholar
  2. S. J. Simon and S. J. Simon, “An examination of the financial feasibility of Electronic Medical Records (EMRs): a case study of tangible and intangible benefits,” Int J Electron Healthc, vol. 2, no. 2, pp. 185–200, 2006. View at: Google Scholar
  3. D. L. Grieger, S. H. Cohen, and D. A. Krusch, “A pilot study to document the return on investment for implementing an ambulatory electronic health record at an academic medical center,” J Am Coll Surg, vol. 205, no. 1, pp. 89–96, 2007 Jul. View at: Google Scholar
  4. R. Kaushal, A. K. Jha, C. Franz et al., “Brigham and Women's Hospital CPOE Working Group. Return on investment for a computerized physician order entry system,” J Am Med Inform Assoc, vol. 13, no. 3, pp. 261–6, 2006 May-Jun. View at: Google Scholar
  5. K. F. Schmitt and D. A. Wofford, “Financial analysis projects clear returns from electronic medical records,” Healthc Financ Manage, vol. 56, no. 1, pp. 52–7, 2002 Jan. View at: Google Scholar
  6. R. Amarasingham, L. Plantinga, M. Diener-West, D. J. Gaskin, and N. R. Powe, “Clinical information technologies and inpatient outcomes: a multiple hospital study,” Arch Intern Med, vol. 169, no. 2, pp. 108–14, 2009 Jan 26. View at: Google Scholar
  7. R. H. Miller, C. West, T. M. Brown, I. Sim, and C. Ganchoff, “The value of electronic health records in solo or small group practices,” Health Aff (Millwood), vol. 24, no. 5, pp. 1127–37, 2005 Sep-Oct. View at: Google Scholar
  8. R. Fernandopulle and N. Patel, “How the electronic health record did not measure up to the demands of our medical home practice,” Health Aff (Millwood), vol. 29, no. 4, pp. 622–8, 2010 Apr. View at: Google Scholar
  9. J. Sidorov, “It Ain't Necessarily So: The Electronic Health Record And The Unlikely Prospect Of Reducing Health Care Costs,” Health Aff (Millwood), vol. 25, no. 4, pp. 1079–85, 2006 Jul-Aug. View at: Google Scholar
  10. P. G. Shekelle, S. C. Morton, and E. B. Keeler, “Costs and benefits of health information technology,” Evid Rep Technol Assess, no. 132, pp. 1–71, 2006 Apr. View at: Google Scholar
  11. L. M. Hitt and E. Brynjolfsson, “Productivity, Business Profitability, and Consumer Surplus: Three Different Measures of Information Technology Value,” MIS Quarterly, vol. 20, no. 2, pp. 121–142, 1996. View at: Google Scholar
  12. R. Borzekowski, “Measuring the cost impact of hospital information systems: 1987-1994,” J Health Econ, vol. 28, no. 5, pp. 938–49, 2009 Sep, Epub 2009 Jun 13. View at: Google Scholar
  13. Sachdeva, Ramesh C. MD, PhD, MBA, “Measuring the impact of new technology: An outcomes-based approach,” Critical Care Medicine, vol. 29, no. 8, Supplement, pp. N190–N195, August 2001. View at: Google Scholar
  14. S. J. Wang, B. Middleton, L. A. Prosser et al., “A cost-benefit analysis of electronic medical records in primary care,” Am J Med, vol. 114, no. 5, pp. 397–403, 2003 Apr 1. View at: Google Scholar
  15. S. T. Parente and J. S. McCullough, “Health information technology and patient safety: evidence from panel data,” Health Aff (Millwood), vol. 28, no. 2, pp. 357–60, 2009 Mar-Apr. View at: Google Scholar
  16. J. S. McCullough, M. Casey, I. Moscovice, and S. Prasad, “The effect of health information technology on quality in U. S. hospitals,” Health Aff (Millwood), vol. 29, no. 4, pp. 647–54, 2010 Apr. View at: Google Scholar
  17. C. L. Goldzweig, A. Towfigh, M. Maglione, and P. G. Shekelle, “Costs and benefits of health information technology: new trends from the literature,” Health Aff (Millwood), vol. 28, no. 2, pp. w282–93, 2009 Mar-Apr, Epub 2009 Jan 27. View at: Google Scholar
  18. D. U. Himmelstein, A. Wright, and S. Woolhandler, “Hospital computing and the costs and quality of care: a national study,” Am J Med, vol. 123, no. 1, pp. 40–6, 2010 Jan, Epub 2009 Nov 24. View at: Google Scholar
  19. M. Joffe and J. Mindell, “Complex causal process diagrams for analyzing the health impacts of policy interventions,” Am J Public Health, vol. 96, no. 3, pp. 473–9, 2006 Mar. View at: Google Scholar
  20. R. J. Little and D. B. Rubin, “Causal effects in clinical and epidemiological studies via potential outcomes: concepts and analytical approaches,” Annu Rev Public Health, vol. 21, pp. 121–45, 2000. View at: Google Scholar
  21. A. Bernard and S. Tichkiewitch, Methods and Tools for Effective Knowledge Life-Cycle-Management, Springer, 2008.
  22. N. Menachemi, J. Burkhardt, R. Shewchuk, D. Burke, and R. G. Brooks, “Hospital information technology and positive financial performance: a different approach to finding an ROI,” Healthc Manag, vol. 51, no. 1, pp. 40–58, 2006 Jan-Feb. View at: Google Scholar
  23. J. Pearl, Causality: Models Reasoning and Inference, Cambridge University Press, 2000.
  24. M. G. Kendall and A. Stuart, The Advanced Theory of Statistics, Volume 2, 3rd edition, 1973, ISBN 0-85264-215-6.
  25. Baba, Kunihiro, Reitei Shibata, and Masaaki Sibuya, “Partial correlation and conditional correlation as measures of conditional independence,” Australian and New Zealand Journal of Statistics, vol. 46, no. 4, pp. 657–664, 2004. View at: Google Scholar
  26. C. M. Byrne, L. M. Mercincavage, E. C. Pan, A. G. Vincent, D. S. Johnston, and B. Middleton, “The value from investments in health information technology at the U. S. Department of Veterans Affairs,” Health Aff (Millwood), vol. 29, no. 4, pp. 629–38, 2010 Apr. View at: Google Scholar
  27. Unspecified authors, “The Veterans Health Administration: quality, value, accountability and information as transforming strategies for patient centered care,” The American Journal of Managed Care, November, 2004a. View at: Google Scholar
  28. Unspecified authors, “Comparison of quality of care for patients in the Veterans Health Administration and patients in a national sample,” Annals of Internal Medicine, December, 2004b. View at: Google Scholar
  29. M. M. Glymour and S. Greenland, “Causal diagrams,” in Modern epidemiology, K. J. Rothman, S. Greenland, and T. L. Lash, Eds., Wolters Kluwer/Lippincott Williams & Wilkins, Philadelphia, 2008. View at: Google Scholar
  30. P. P. Howards, E. F. Schisterman, and P. J. Heagerty, “Potential confounding by exposure history and prior outcomes – an example from perinatal epidemiology,” Epidemiology, vol. 18, no. 5, pp. 544–51, 2007. View at: Google Scholar

Copyright © 2011 Hindawi Publishing Corporation. This is an open access article distributed under the 木林森并购超时代光源 扩张欧洲超商通路版图, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

More related articles

 PDF Download Citation Citation
 Order printed copiesOrder

Related articles

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.