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A Comparison of Methods for Capturing Patient Preferences for Delivery of Mental Health Services to Low-Income Hispanics Engaged in Primary Care

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Abstract

Background

Consideration of patient preferences regarding delivery of mental health services within primary care may greatly improve access and quality of care for the many who could benefit from those services.

Objectives

This project evaluated the feasibility and usefulness of adding a consumer-products design method to qualitative methods implemented within a community-based participatory research (CBPR) framework.

Research Design

Discrete-choice conjoint experiment (DCE) added to systematic focus group data collection and analysis.

Subjects

Focus group data were collected from 64 patients of a Federally-Qualified Health Center (FQHC) serving a predominantly low-income Hispanic population. A total of 604 patients in the waiting rooms of the FQHC responded to the DCE.

Measures

The DCE contained 15 choice tasks that each asked respondents to choose between three mental health services options described by the levels of two (of eight) attributes based on themes that emerged from focus group data.

Results

The addition of the DCE was found to be feasible and useful in providing distinct information on relative patient preferences compared with the focus group analyses alone. According to market simulations, the package of mental health services guided by the results of the DCE was preferred by patients.

Conclusions

Unique patterns of patient preferences were uncovered by the DCE and these findings were useful in identifying pragmatic solutions to better address the mental health service needs of this population. However, for this resource-intensive method to be adopted more broadly, the scale of the primary care setting and/or scope of the issue addressed have to be relatively large.

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References

  1. Croghan TW, Brown JD. Integrating mental health treatment into the patient-centered medical home. Rockville (MD): Mathematical Policy Research; 2009.

    Google Scholar 

  2. Kessler R, Stafford D. Primary care is the de facto mental health system. New York: Springer; 2008.

    Book  Google Scholar 

  3. Caldwell A, Couture A, Nowotny H. Closing the mental health gap: eliminating disparities in treatment for Latinos. Kansas City: Mattie Rhodes Center; 2008.

    Google Scholar 

  4. Arcury TA, Quandt SA. Delivery of health services to migrant and seasonal farmworkers. Annu Rev Public Health. 2007;28:345–63.

    Article  PubMed  Google Scholar 

  5. Surgeon General. Mental health: culture, race, ethnicity. A supplement to mental health: a report of the Surgeon General. Washington, DC: US Department of Health and Human Services; 2001.

  6. Miranda J, Cooper LA. Disparities in care for depression among primary care patients. J Gen Intern Med. 2004;19(2):120–6.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Wang PS, Lane M, Olfson M, Pincus HA, Wells KB, Kessler RC. Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62(6):629–40.

    Article  PubMed  Google Scholar 

  8. González HM, Vega WA, Williams DR, Tarraf W, West BT, Neighbors HW. Depression care in the United States: too little for too few. Arch Gen Psychiatry. 2010;67(1):37–46.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Grant R. A bridge between public health and primary care. Am J Public Health. 2012;102(Suppl 3):S304.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Institute of Medicine. Crossing the quality chasm: a new health system for the twenty-first century. Washington, DC: National Academies Press; 2001.

    Google Scholar 

  11. Agency for Healthcare Research and Quality. Chapter 5. Patient centeredness: national healthcare disparities report, 2010. Rockville : Agency for Healthcare Research and Quality; 2014.

  12. Berry LL, Beckham D, Dettman A, Mead R. Toward a strategy of patient-centered access to primary care. Mayo Clin Proc. 2014;89(10):1406–15.

    Article  PubMed  Google Scholar 

  13. Sorel E, Everett A. Psychiatry and primary care integration: challenges and opportunities. Int Rev Psychiatry. 2011;23(1):28–30.

    Article  PubMed  Google Scholar 

  14. Lin P, Campbell DG, Chaney EF, Liu C-F, Heagerty P, Felker BL, et al. The influence of patient preference on depression treatment in primary care. Ann Behav Med. 2005;30(2):164–73.

    Article  PubMed  Google Scholar 

  15. Cunningham CE, Deal K, Rimas H, Campbell H, Russell A, Henderson J, et al. Using conjoint analysis to model the preferences of different patient segments for attributes of patient-centered care. Patient. 2008;1(4):317–30.

    Article  PubMed  Google Scholar 

  16. Fraenkel L, Gulanski B, Wittink D. Patient treatment preferences for osteoporosis. Arthritis Care Res. 2006;55(5):729–35.

    Article  Google Scholar 

  17. Marshall D, Bridges JF, Hauber B, Cameron R, Donnalley L, Fyie K, et al. Conjoint analysis applications in health: how are studies being designed and reported? Patient. 2010;3(4):249–56.

    Article  PubMed  Google Scholar 

  18. Osman L, McKenzie L, Cairns J, Friend J, Godden D, Legge J, et al. Patient weighting of importance of asthma symptoms. Thorax. 2001;56(2):138–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Ryan M, Farrar S. Using conjoint analysis to elicit preferences for health care. BMJ. 2000;320(7248):1530.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Dwight-Johnson M, Lagomasino IT, Aisenberg E, Hay J. Using conjoint analysis to assess depression treatment preferences among low-income Latinos. Psychiatric Serv. 2004;55(8):934–6.

    Article  Google Scholar 

  21. Dwight-Johnson M, Lagomasino IT, Hay J, Zhang L, Tang LQ, Green JM, et al. Effectiveness of collaborative care in addressing depression treatment preferences among low-income Latinos. Psychiatric Serv. 2010;61(11):1112–8.

    Article  Google Scholar 

  22. Okumura Y, Sakamoto S. Depression treatment preferences among Japanese undergraduates: using conjoint analysis. Int J Soc Psychiatry. 2012;58(2):195–203.

    Article  PubMed  Google Scholar 

  23. Wittink MN, Cary M, TenHave T, Baron J, Gallo JJ. Towards patient-centered care for depression. Patient. 2010;3(3):145–57.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Wittink MN, Morales KH, Cary M, Gallo JJ, Bartels SJ. Towards personalizing treatment for depression. Patient. 2013;6(1):35–43.

    Article  PubMed  Google Scholar 

  25. Bell RA, Paterniti DA, Azari R, Duberstein PR, Epstein RM, Rochlen AB, et al. Encouraging patients with depressive symptoms to seek care: a mixed methods approach to message development. Patient Educ Couns. 2010;78(2):198–205.

    Article  PubMed  Google Scholar 

  26. Zimmermann TM, Clouth J, Elosge M, Heurich M, Schneider E, Wilhelm S, et al. Patient preferences for outcomes of depression treatment in Germany: a choice-based conjoint analysis study. J Affect Disord. 2013;148(2):210–9.

    Article  PubMed  Google Scholar 

  27. Orme BK. Getting started with conjoint analysis: strategies for product design and pricing research. 2nd ed. Madison: Research Publishers; 2010.

    Google Scholar 

  28. Ryan M, Scott D, Reeves C, Bate A, Van Teijlingen E, Russell E, et al. Eliciting public preferences for healthcare: a systematic review of techniques. Health Technol Assess. 2001;5:1–186.

    Article  CAS  PubMed  Google Scholar 

  29. Phillips KA, Johnson FR, Maddala T. Measuring what people value: a comparison of “attitude” and “preference” surveys. Health Serv Res. 2002;37(6):1659–79.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Payne J, Bettman J, Johnson E. The adaptive decision maker. Cambridge: Cambridge University Press; 1993.

    Book  Google Scholar 

  31. Hsee CK, Loewenstein GF, Blount S, Bazerman MH. Preference reversals between joint and separate evaluations of options: a review and theoretical analysis. Psychol Bull. 1999;125(5):576.

    Article  Google Scholar 

  32. Bridges J, Onukwugha E, Johnson F, Hauber A. Patient preference methods: a patient centered evaluation paradigm. ISPOR Connect. 2007;13(6):4–7.

    Google Scholar 

  33. Bridges J. Stated preference methods in health care evaluation: an emerging methodological paradigm in health economics. Appl Health Econ Health Policy. 2003;2(4):213–24.

    PubMed  Google Scholar 

  34. Israel BA, Schulz AJ, Parker EA, Becker AB. Review of community-based research: assessing partnership approaches to improve public health. Annu Rev Public Health. 1998;19(1):173–202.

    Article  CAS  PubMed  Google Scholar 

  35. Ingram M, Murrietta L, de Zapien JG, Herman PM, Carvajal SC. Community health workers as focus group facilitators: A participatory action research method to improve behavioral health services for farmworkers in a primary care setting. Action Res. 2015;13(1):48–64.

    Article  Google Scholar 

  36. Ingram M, Schachter KA, Guernsey de Zapien J, Herman PM, Carvajal SC. Using participatory methods to enhance patient-centred mental health care in a federally qualified community health center serving a Mexican American farmworker community. Health Expect. doi:10.1111/hex.12284 (Epub 10 Oct 2014).

  37. Bergold J, Thomas S. Participatory research methods: a methodological approach in motion. FORUM: Qual Soc Res. 2012;13(1):30.

  38. Cheraghi-Sohi S, Bower P, Mead N, McDonald R, Whalley D, Roland M. What are the key attributes of primary care for patients? Building a conceptual ‘map’of patient preferences. Health Expect. 2006;9(3):275–84.

    Article  PubMed  Google Scholar 

  39. Bridges JF, Hauber AB, Marshall D, Lloyd A, Prosser LA, Regier DA, et al. Conjoint analysis applications in health—a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. Value Health. 2011;14(4):403–13.

    Article  PubMed  Google Scholar 

  40. Lancsar E, Louviere J. Conducting discrete choice experiments to inform healthcare decision making. Pharmacoeconomics. 2008;26(8):661–77.

    Article  PubMed  Google Scholar 

  41. Lenk PJ, DeSarbo WS, Green PE, Young MR. Hierarchical Bayes conjoint analysis: recovery of partworth heterogeneity from reduced experimental designs. Mark Sci. 1996;15(2):173–91.

    Article  Google Scholar 

  42. Sawtooth Software I. The CBC/HB system for hierarchical Bayes estimation version 5.0 technical paper. Sequim: Sawtooth Software, Inc.; 2009.

  43. Halme M, Kallio M. Estimation methods for choice-based conjoint analysis of consumer preferences. Eur J Oper Res. 2011;214(1):160–7.

    Article  Google Scholar 

  44. Orme BK. SSI Web V6.6 software for web interviewing and conjoint analysis. Sequim: Sawtooth Software, Inc.; 2009.

  45. Orme B, Huber J. Improving the value of conjoint simulations. Mark Res. 2000;12(4):12–20.

    Google Scholar 

  46. Huber J, Orme BK, Miller R. Dealing with product similarity in conjoint simulations. In: Gustafsson A, Herrmann A, Huber F, editors. Conjoint measurement: methods and applications. 4th ed. New York: Springer; 2007. p. 347–62.

    Chapter  Google Scholar 

  47. Herman PM, Ingram M, Rimas H, Carvajal S, Cunningham CE. Patient preferences of a low-income Hispanic population for mental health services in primary care. Adm Policy Ment Health (Epub 26 Sep 2015).

  48. Carvajal SC, Rosales C, Rubio-Goldsmith R, Sabo S, Ingram M, McClelland DJ, et al. The border community and immigration stress scale: a preliminary examination of a community responsive measure in two southwest samples. J Immigr Minor Health. 2013;15(2):427–36.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Wilkinson S. Focus groups in health research exploring the meanings of health and illness. J Health Psychol. 1998;3(3):329–48.

    Article  CAS  PubMed  Google Scholar 

  50. Caruso EM, Rahnev DA, Banaji MR. Using conjoint analysis to detect discrimination: revealing covert preferences from overt choices. Soc Cogn. 2009;27(1):128–37.

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to acknowledge the partnership of the Sunset Community Health Center in carrying out this research, and the Sunset Community Health Workers who participated in research activities.

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Corresponding author

Correspondence to Patricia M. Herman.

Ethics declarations

This work was supported through a Patient-Centered Outcomes Research Institute (PCORI) Pilot Project Program award (1IP2PI000275-01). The participation of Dr. Cunningham and Ms. Rimas was supported by the Jack Laidlaw Chair in Patient-Centered Health Care. Lucy Murrieta is an employee of the FQHC that was the subject of this research. With the exception of Ms. Murrieta’s employment status, all authors declare that they have no conflicts of interest, financial or otherwise, with respect to this research. Our study received exempt approval from the University of Arizona Institutional Review Board. Informed consent was obtained from all individual participants included in this study.

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

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Herman, P.M., Ingram, M., Cunningham, C.E. et al. A Comparison of Methods for Capturing Patient Preferences for Delivery of Mental Health Services to Low-Income Hispanics Engaged in Primary Care. Patient 9, 293–301 (2016). https://doi.org/10.1007/s40271-015-0155-7

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