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J Pers Med. 2014 Mar 26;4(2):115-36. doi: 10.3390/jpm4020115.

Formative evaluation of clinician experience with integrating family history-based clinical decision support into clinical practice.

Journal of personalized medicine

Megan Doerr, Emily Edelman, Emily Gabitzsch, Charis Eng, Kathryn Teng

Affiliations

  1. Center for Personalized Healthcare, Medicine Institute, Cleveland Clinic, 9500 Euclid Ave., Cleveland, OH 44195, USA. [email protected].
  2. Genomics Education, the Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609-1500, USA. [email protected].
  3. Center for Personalized Healthcare, Medicine Institute, Cleveland Clinic, 9500 Euclid Ave., Cleveland, OH 44195, USA. [email protected].
  4. Genomic Medicine Institute, Cleveland Clinic, 9500 Euclid Ave., Cleveland, OH 44195, USA. [email protected].
  5. Center for Personalized Healthcare, Medicine Institute, Cleveland Clinic, 9500 Euclid Ave., Cleveland, OH 44195, USA. [email protected].

PMID: 25563219 PMCID: PMC4263968 DOI: 10.3390/jpm4020115

Abstract

Family health history is a leading predictor of disease risk. Nonetheless, it is underutilized to guide care and, therefore, is ripe for health information technology intervention. To fill the family health history practice gap, Cleveland Clinic has developed a family health history collection and clinical decision support tool, MyFamily. This report describes the impact and process of implementing MyFamily into primary care, cancer survivorship and cancer genetics clinics. Ten providers participated in semi-structured interviews that were analyzed to identify opportunities for process improvement. Participants universally noted positive effects on patient care, including increases in quality, personalization of care and patient engagement. The impact on clinical workflow varied by practice setting, with differences observed in the ease of integration and the use of specific report elements. Tension between the length of the report and desired detail was appreciated. Barriers and facilitators to the process of implementation were noted, dominated by the theme of increased integration with the electronic medical record. These results fed real-time improvement cycles to reinforce clinician use. This model will be applied in future institutional efforts to integrate clinical genomic applications into practice and may be useful for other institutions considering the implementation of tools for personalizing medical management.

References

  1. Genet Med. 2010 Jun;12(6):370-5 - PubMed
  2. Genet Med. 2000 May-Jun;2(3):180-5 - PubMed
  3. Genet Med. 2011 Nov;13(11):956-65 - PubMed
  4. J Gen Intern Med. 2004 Mar;19(3):273-80 - PubMed
  5. BMC Med Inform Decis Mak. 2009 Oct 08;9:44 - PubMed
  6. Implement Sci. 2013 Apr 23;8:47 - PubMed
  7. Implement Sci. 2009 Aug 07;4:50 - PubMed
  8. BMC Health Serv Res. 2012 Oct 08;12:349 - PubMed
  9. BMC Fam Pract. 2010 Nov 18;11:90 - PubMed
  10. BMC Med Inform Decis Mak. 2006 Feb 01;6:6 - PubMed
  11. N C Med J. 2013 Jul-Aug;74(4):287-96 - PubMed
  12. Matern Child Health J. 2014 Jul;18(5):1233-45 - PubMed
  13. N Engl J Med. 2004 Nov 25;351(22):2333-6 - PubMed
  14. BMJ. 2005 Apr 2;330(7494):765 - PubMed
  15. Genet Med. 2014 Jan;16(1):60-9 - PubMed
  16. AMIA Annu Symp Proc. 2011;2011:578-87 - PubMed
  17. BMC Med Inform Decis Mak. 2013 Apr 15;13:47 - PubMed
  18. J Am Med Inform Assoc. 2013 Mar-Apr;20(2):388-400 - PubMed
  19. Int J Med Inform. 2001 Dec;64(2-3):143-56 - PubMed

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