Perspective: Health information technology and patient safety: Evidence from panel data

Health Affairs

Volumn 28, Issue 2, 2009, Pages 357-360

  Parente, Stephen T ^a   McCullough, Jeffrey S ^b  

^a UNIVERSITY OF MINNESOTA MEDICAL SCHOOL   (United States)

^b UNIVERSITY OF MINNESOTA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTERIZED PHYSICIAN ORDER ENTRY; ELECTRONIC MEDICAL RECORD; HEALTH CARE DELIVERY; HEALTH CARE POLICY; INVESTMENT; MEDICAL INFORMATICS; MEDICARE; PATIENT SAFETY; SHORT SURVEY; ARTICLE; EVIDENCE BASED MEDICINE; HUMAN; REGRESSION ANALYSIS; SAFETY;

ELECTRONIC HEALTH RECORDS; EVIDENCE-BASED MEDICINE; HUMANS; MEDICAL INFORMATICS; REGRESSION ANALYSIS; SAFETY MANAGEMENT;

EID: 66149179022     PISSN: 02782715     EISSN: 15445208     Source Type: Journal    
DOI: 10.1377/hlthaff.28.2.357     Document Type: Short Survey

References (20)

1. Institute of Medicine, Crossing the Quality Chasm: A New Health System for the Twenty-first Century (Washington: National Academies Press, 2001).
2. R. Hillestad et al., "Can Electronic Medical Record Systems Transform Health Care? Potential Health Benefits, Savings, and Costs," Health Affairs 24, no. 5 (2005): 1103-1117. (Pubitemid 41577096)
3. B. Chaudhry et al., "Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care," Annals of Internal Medicine 144, no. 10 (2006): 742-752;
4. A.X. Garg et al., "Effects of Computerized Clinical Decision Support Systems on Practitioner Performance and Patient Outcomes: A Systematic Review," Journal of the American Medical Association 293, no. 10 (2005): 1223-1238;
5. R. Kaushal, K.G. Shojania, and D.W. Bates, "Effects of Computerized Physician Order Entry and Clinical Decision Support Systems on Medication Safety: A Systematic Review," Archives of Internal Medicine 163, no. 12 (2003): 1409-1416;
6. and G.J. Kuperman and R.F. Gibson, "Computerized Physician Order Entry: Benefits, Costs, and Issues," Annals of Internal Medicine 139, no. 1 (2003): 31-39. (Pubitemid 38124617)
7. J.S. Ash, M. Berg, and E. Coiera, "Some Unintended Consequences of Information Technology in Health Care: The Nature of Patient Care Information System-Related Errors," Journal of the American Medical Informatics Association 11, no. 2 (2004): 104-112;
8. R.G. Berger and J.P. Kichak, "Computerized Physician Order Entry: Helpful or Harmful?" Journal of the American Medical Informatics Association 11, no. 2 (2004): 100-103;
9. and R. Koppel et al., "Role of Computerized Physician Order Entry Systems in Facilitating Medication Errors," Journal of the American Medical Association 293, no. 10 (2005): 1197-1203. (Pubitemid 40327905)
10. J.S. Ash et al., "The Extent and Importance of Unintended Consequences Related to Computerized Provider Order Entry," Journal of the American Medical Informatics Association 14, no. 4 (2007): 415-423;
11. and J.R. Nebeker et al., "High Rates of Adverse Drug Events in a Highly Computerized Hospital," Archives of Internal Medicine 165, no. 10 (2005): 1111-1116. (Pubitemid 40720734)
12. Note that a few studies examined multihospital settings. For example, Devaraj and Kohli investigated the effect of health IT on thirty-day postoperative mortality using patient-specific information, using data from an eight-hospital system over thirty-six months. S. Devaraj and R. Kohli, "Information Technology Payoff in the HealthCare Industry: A Longitudinal Study," Journal of Management Information Systems 16, no. 4 (2000): 41-67.
13. Lee and Wan examined relationships among clinical integration, efficiency, and patient outcomes for a sample of 358 hospitals. K. Lee and T.T. Wan, "Effects of Hospitals' Structural Clinical Integration on Efficiency and Patient Outcome," Health Services Management Research 15, no. 4 (2002): 234-244. Neither study found explicit relationships between health IT and patient outcomes.
14. Our empirical approach is described in an online Appendix, at http://content.healthaffairs.org/cgi/content/full/28/2/357/DC1.
15. As a practical matter, we can only generate precise measures of health IT value for applications that diffused rapidly during our study period. Although applications like computerized physician order entry (CPOE) are interesting, they are rare, and they diffused slowly during the period; thus, we cannot measure their value.
16. K. Fonkych and R. Taylor, The State and Pattern of Health Information Technology Adoption (Santa Monica, Calif.: RAND, 2005). Clinical decision support in the Health Information Management Systems Society (HIMSS) data refers to ex post clinical data analysis capabilities rather than real-time decision-support features associated with CPOE applications.
17. Application definitions are based on the 2001 HIMSS data documentation published by S.I. Dorenfest, "The Third Dorenfest Complete Integrated Healthcare Delivery System+ (IHDS+) Database: User Guide and Data Dictionary" (Chicago: Sheldon I. Dorenfest Associates, January 2001).
18. Marginal effects are shown in the online Appendix, as in Note 7.
19. L.T. Kohn, J.M. Corrigan, and M.S. Donaldson, eds., To Err Is Human: Building a Safer Health System (Washington: National Academies Press, 1999).
20. For a more detailed discussion of relevant technology diffusion and econometric identification issues, see S.C. Athey and S. Stern, "The Impact of Information Technology on Emergency Health Care Outcomes," RAND Journal of Economics 33, no. 3 (2002): 399-432.