Medical Decision Support Systems: General Considerations

  • Prakash M. Nadkarni
Part of the Health Informatics book series (HI)


Mere capture of data is useful in an EMR, but being able to support clinical and administrative decision-making through means other than the presentation of stored data makes the overall system much more useful.


Personal Health Record Computerize Physician Order Entry Medication Reconciliation Implementation Team Computerize Physician Order Entry System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Committee on Quality of Health Care in America IoM. To Err Is Human: Building a Safer Health System. Washington, DC: National Academy Press; 1999.Google Scholar
  2.  2.
    Witten IH, Frank E, Hall MA. Data Mining: Practical Machine Learning Tools and Techniques. San Francisco: Morgan Kaufmann; 2011.Google Scholar
  3.  3.
    University of Waikato. Weka: data mining software in Java [cited 10/1/10]. Available from: 2010.
  4.  4.
    Ash JS et al. Organizational and cultural change considerations. In: Greenes RA, ed. Clinical Decision Support: The Road Ahead. New York: Elsevier/Academic; 2007.Google Scholar
  5.  5.
    Kuperman GJ, Gandhi TK, Bates DW. Effective drug-allergy checking: methodological and operational issues. J Biomed Inform. 2003;36(1–2):70-79.PubMedCrossRefGoogle Scholar
  6.  6.
    Kuperman GJ, Bobb A, Payne TH, et al. Medication-related clinical decision support in ­computerized provider order entry systems: a review. J Am Med Inform Assoc. 2007;14(1):­29-40.PubMedCrossRefGoogle Scholar
  7.  7.
    Bobb A, Gleason K, Husch M, Feinglass J, Yarnold PR, Noskin GA. The epidemiology of prescribing errors: the potential impact of computerized prescriber order entry. Arch Intern Med. 2004;164(7):785-792.PubMedCrossRefGoogle Scholar
  8.  8.
    Anderson HJ. Medication reconciliation: is there a better way? Health Data Management Magazine, January 1, 2010.Google Scholar
  9.  9.
    Pichichero ME. Cephalosporins can be prescribed safely for penicillin-allergic patients. J Fam Pract. 2006;55(2):106-112.PubMedGoogle Scholar
  10. 10.
    Weingart SN, Toth M, Sands DZ, Aronson MD, Davis RB, Phillips RS. Physicians’ decisions to override computerized drug alerts in primary care. Arch Intern Med. 2003;163(21):2625-2631.PubMedCrossRefGoogle Scholar
  11. 11.
    Howell D. Medication reconciliation, CPOE and patient safety: one physician’s viewpoint [cited 10/2/10]. Available from:, 2008.
  12. 12.
    Connelly C. Cedars-Sinai doctors cling to pen and paper. Washington Post, March 21, 2005.Google Scholar
  13. 13.
    Phansalkar S, Edworthy J, Hellier E, et al. A review of human factors principles for the design and implementation of medication safety alerts in clinical information systems. J Am Med Inform Assoc. 2010;17(5):493-501.PubMedCrossRefGoogle Scholar
  14. 14.
    Miller RA, Waitman LR, Chen S, Rosenbloom ST. The anatomy of decision support during inpatient care provider order entry (CPOE): empirical observations from a decade of CPOE experience at Vanderbilt. J Biomed Inform. 2005;38(6):469-485.PubMedCrossRefGoogle Scholar
  15. 15.
    Conniff R. What’s behind a smile. Smithsonian Magazine; 2007:51–52.Google Scholar
  16. 16.
    Horvitz E, Breese J, Heckerman D, Hovel D, Rommelse K. The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users. In: Cooper GF, Serafín M, eds. Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, San Francisco, CA, 24–26 July 1998, University of Wisconsin Business School, Madison; 1998.Google Scholar
  17. 17.
    Sinofsky S. Project management at Microsoft [cited 11/3/10]; Available from:, 2005.

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Prakash M. Nadkarni
    • 1
  1. 1.School of MedicineYale UniversityNew HavenUSA

Personalised recommendations