Incorporating patient-reported outcome measures into the electronic health record for research: application using the Patient Health Questionnaire (PHQ-9)

Quality of Life Research

Volumn 24, Issue 2, 2015, Pages 295-303

  Griffith, Sandra D ^a   Thompson, Nicolas R ^a   Rathore, Jaivir S ^a,b   Jehi, Lara E ^a   Tesar, George E ^a   Katzan, Irene L ^a  

^a LERNER RESEARCH INSTITUTE   (United States)

^b UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

Author keywords

Classification; Depressive disorder; Electronic health records; ICD 9 CM; Patient outcome assessment

Indexed keywords

AGED; DEPRESSIVE DISORDER; ELECTRONIC MEDICAL RECORD; FEMALE; HUMAN; INTERNATIONAL CLASSIFICATION OF DISEASES; MALE; MIDDLE AGED; OUTCOME ASSESSMENT; QUESTIONNAIRE; RECEIVER OPERATING CHARACTERISTIC; RETROSPECTIVE STUDY; SENSITIVITY AND SPECIFICITY; UNITED STATES;

AGED; DEPRESSIVE DISORDER; ELECTRONIC HEALTH RECORDS; FEMALE; HUMANS; INTERNATIONAL CLASSIFICATION OF DISEASES; MALE; MIDDLE AGED; PATIENT OUTCOME ASSESSMENT; QUESTIONNAIRES; RETROSPECTIVE STUDIES; ROC CURVE; SENSITIVITY AND SPECIFICITY; UNITED STATES;

EID: 84931096306     PISSN: 09629343     EISSN: 15732649     Source Type: Journal    
DOI: 10.1007/s11136-014-0764-y     Document Type: Article

References (32)

1. Blumenthal, D., & Tavenner, M. (2010). The “meaningful use” regulation for electronic health records. The New England Journal of Medicine,363(6), 501–504. doi:10.1056/NEJMp1006114.
2. Kohane, I. S. (2011). Using electronic health records to drive discovery in disease genomics. Nature Reviews Genetics,12(6), 417–428. doi:10.1038/nrg2999.
3. Hripcsak, G., & Albers, D. J. (2013). Next-generation phenotyping of electronic health records. Journal of the American Medical Informatics Association,20, 117–121. doi:10.1136/amiajnl-2012-001145.
4. O’Malley, K. J., Cook, K. F., Price, M. D., Wildes, K. R., Hurdle, J. F., & Ashton, C. M. (2005). Measuring diagnoses: ICD code accuracy. Health Services Research,40(5 Pt 2), 1620–1639. doi:10.1111/j.1475-6773.2005.00444.x.
5. Shivade, C., Raghavan, P., Fosler-Lussier, E., Embi, P. J., Elhadad, N., Johnson, S. B., et al. (2013). A review of approaches to identifying patient phenotype cohorts using electronic health records. Journal of the American Medical Informatics Association,21(2), 221–230. doi:10.1136/amiajnl-2013-001935.
6. Kandula, S., Zeng-Treitler, Q., Chen, L., Salomon, W. L., & Bray, B. E. (2011). A bootstrapping algorithm to improve cohort identification using structured data. Journal of Biomedical Informatics,44(Suppl 1), S63–S68. doi:10.1016/j.jbi.2011.10.013.
7. Jakobsen, K. D., Hansen, T., Dam, H., Larsen, E. B., Gether, U., & Werge, T. (2008). Reliability of clinical ICD-10 diagnoses among electroconvulsive therapy patients with chronic affective disorders. European Journal of Psychiatry,22(3), 161–172. doi:10.4321/S0213-61632008000300005.
8. Kho, A. N., Pacheco, J., Peissig, P. L., Rasmussen, L., Newton, K. M., Weston, N., et al. (2011). Electronic medical records for genetic research: Results of the eMERGE consortium. Science Translational Medicine,3(79re1), 1–7. doi:10.1126/scitranslmed.3001807.
9. Newton, K. M., Peissig, P. L., Kho, A. N., Bielinski, S. J., Berg, R. L., Choudhary, V., et al. (2013). Validation of electronic medical record-based phenotyping algorithms: Results and lessons learned from the eMERGE network. Journal of the American Medical Informatics Association,20, e147–e154. doi:10.1136/amiajnl-2012-000896.
10. Williams, C., Templin, T., & Mosely-Williams, A. (2004). Usability of a computer-assisted interview system for the unaided self-entry of patient data in an urban rheumatology clinic. Journal of the American Medical Informatics Association,11(4), 249–260. doi:10.1197/jamia.M1527.
11. McGowan, J. J. (2008). The pervasiveness of telemedicine: Adoption with or without a research base. Journal of General Internal Medicine,23(4), 505–507. doi:10.1007/s11606-008-0534-z.
12. Rose, M., & Bezjak, A. (2009). Logistics of collecting patient-reported outcomes (PROs) in clinical practice: An overview and practical examples. Quality of Life Research,18(1), 125–136. doi:10.1007/s11136-008-9436-0.
13. Katzan, I., Speck, M., Dopler, C., Urchek, J., Bielawski, K., Dunphy, C., et al. (2011). The Knowledge Program: An innovative, comprehensive electronic data capture system and warehouse. AMIA Annual Symposium Proceedings,2011, 683–692.
14. Broderick, J. E., DeWitt, M. M., Rothrock, N., Crane, P. K., & Forrest, C. B. (2013). Advances in patient reported outcomes: The NIH PROMIS measures. eGEMS (Generating Evidence & Methods to Improve Patient Outcomes),1(1), 12. doi:10.13063/2327-9214.1015.
15. Snyder, C., Blackford, A., Wolff, A., Carducci, M., Herman, J., & Wu, A. (2013). Feasibility and value of PatientViewpoint: A web system for patient-reported outcomes assessment in clinical practice. Psycho-Oncology,22, 895–901. doi:10.1002/pon.3087.
16. Snyder, C. F., Jensen, R., Courtin, S., & Wu, A. (2009). PatientViewport: A website for patient-reported outcomes assessment. Quality of Life Research,18(7), 793–800. doi:10.1007/s11136-009-9497-8.
17. Porter, M. (2010). What is value in health care? New England Journal of Medicine,363, 2477–2481. doi:10.1056/NEJMp1011024.
18. Wu, A. W., Snyder, C., Clancy, C. M., & Steinwachs, D. M. (2010). Adding the patient perspective to comparative effectiveness research. Health Affairs,29(10), 1863–1871. doi:10.1377/hlthaff.2010.0660.
19. Wu, A. W., Kharrazi, H., Boulware, L. E., & Snyder, C. F. (2013). Measure once, cut twice—Adding patient-reported outcome measures to the electronic health record for comparative effectiveness research. Journal of Clinical Epidemiology,66, S12–S20. doi:10.1016/j.jclinepi.2013.04.005.
20. Perlis, R. H., Iosifescu, D. V., Castro, V. M., Murphy, S. N., Gainer, V. S., Minnier, J., et al. (2012). Using electronic medical records to enable large-scale studies in psychiatry: Treatment resistant depression as a model. Psychological Medicine,42(1), 41–50. doi:10.1017/S0033291711000997.
21. Valuck, R. J., Anderson, H. O., Libby, A. M., Brandt, E., Bryan, C., Allen, R. R., et al. (2012). Enhancing electronic health record measurement of depression severity and suicide ideation: A distributed ambulatory research in therapeutics network (DARTNet) study. The Journal of the American Board of Family Medicine,25(5), 582–593. doi:10.3122/jabfm.2012.05.110053.
22. Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine,16, 606–613.
23. Sheehan, D., Lecrubier, Y., Sheehan, K., Amorim, P., Janava, J., Wieller, E., et al. (1998). The mini international neuropsychiatric interview (MINI): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. Journal of Clinical Psychiatry,59(Suppl 20), 22–33.
24. Rathore, J. S., Jehi, L. E., Fan, Y., Patel, S. I., Foldvary-Schaefer, N., Ramirez, M. J., et al. (2014). Validation of the Patient Health Questionnaire-9 (PHQ-9) for depression screening in adults with epilepsy. Epilepsy & Behavior, 37, 215–220. doi:10.1016/j.yebeh.2014.06.030.
25. Missouri Census Data Center. (2012). Missouri Census Data Center Data Archive. http://mcdc.missouri.edu/.
26. Agency for Healthcare Research and Quality. (2012). Priority populations (continued). National Healthcare Disparities Report, 2011. Rockville, MD. Accessed March 2013, from http://www.ahrq.gov/research/findings/nhqrdr/nhdr11/chap10a.html.
27. Youden, W. (1950). Index for rating diagnostic tests. Cancer,3(1), 32–35. doi:10.1002/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3.
28. R Core Team. (2013). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.
29. Robin, X., Turck, N., Hainard, A., Tiberti, N., Lisacek, F., Sanchez, J.-C., et al. (2011). pROC: An open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics,12(1), 77. doi:10.1186/1471-2105-12-77.
30. Wittkampf, K. A., Naeije, L., Schene, A. H., Huyser, J., & van Weert, H. C. (2007). Diagnostic accuracy of the mood module of the Patient Health Questionnaire: A systematic review. General Hospital Psychiatry,29(5), 388–395. doi:10.1016/j.genhosppsych.2007.06.004.
31. Gilliam, F. G., Barry, J. J., Hermann, B. P., Meador, K. J., Vahle, V., & Kanner, A. M. (2006). Rapid detection of major depression in epilepsy: A multicentre study. Lancet Neurology,5(5), 399–405. doi:10.1016/S1474-4422(06)70415-X.
32. Zhou, X., McClish, D., & Obuchowski, N. (2009). Statistical methods in diagnostic medicine. Hoboken, NJ: Wiley-Interscience.