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Journal of General Internal Medicine

, Volume 25, Issue 5, pp 408–414 | Cite as

Patient-Provider Concordance in the Prioritization of Health Conditions Among Hypertensive Diabetes Patients

  • Donna M. ZulmanEmail author
  • Eve A. Kerr
  • Timothy P. Hofer
  • Michele Heisler
  • Brian J. Zikmund-Fisher
Original Article

Abstract

BACKGROUND

Many patients with diabetes have multiple other chronic conditions, but little is known about whether these patients and their primary care providers agree on the relative importance that they assign these comorbidities.

OBJECTIVE

To understand patterns of patient-provider concordance in the prioritization of health conditions in patients with multimorbidity.

DESIGN

Prospective cohort study of 92 primary care providers and 1,169 of their diabetic patients with elevated clinic triage blood pressure (≥140/90) at nine Midwest VA facilities.

MEASUREMENTS

We constructed a patient-provider concordance score based on responses to surveys in which patients were asked to rank their most important health concerns and their providers were asked to rank the most important conditions likely to affect that patient’s health outcomes. We then calculated the change in predicted probability of concordance when the patient reported having poor health status, pain or depression, or competing demands (issues that were more pressing than his health), controlling for both patient and provider characteristics.

RESULTS

For 714 pairs (72%), providers ranked the patient's most important concern in their list of three conditions. Both patients and providers ranked diabetes and hypertension most frequently; however, providers were more likely to rank hypertension as most important (38% vs. 18%). Patients were more likely than providers to prioritize symptomatic conditions such as pain, depression, and breathing problems. The predicted probability of patient-provider concordance decreased when a patient reported having poor health status (55% vs. 64%, p < 0.01) or non-health competing demands (46% vs. 62%, p < 0.01).

CONCLUSIONS

Patients and their primary care providers often agreed on the most important health conditions affecting patients with multimorbidity, but this concordance was lower for patients with poor health status or non-health competing demands. Interventions that increase provider awareness about symptomatic concerns and competing demands may improve chronic disease management in these vulnerable patients.

KEY WORDS

concordance chronic disease multimorbidity diabetes competing demands 

Notes

Acknowledgements

The authors thank Rob Holleman for assisting with data management, Mandi Klamerus for project management, and Shirley Chen for helping with manuscript preparation.

Financial Disclosures

None reported.

Funding/Support

This work was supported by the Robert Wood Johnson Clinical Scholars Program and an associated VA Advanced Fellowship, as well as research grants from the US Department of Veterans Affairs Health Services Research and Development Service (IIR02-225) and the Michigan Diabetes Research and Training Center Grant (P60DK-20572). Dr. Zikmund-Fisher is supported by a career development award from the American Cancer Society (MRSG-06-130-01-CPPB).

Role of the Sponsor

The funding sources had no role in the design and conduct of the study, in the collection, analysis, and interpretation of the data, or in the preparation, review, or approval of the manuscript.

Conflict of Interest

None disclosed.

References

  1. 1.
    Partnership For Solutions. Diabetes: The impact of multiple chronic conditions. http://www.partnershipforsolutions.org/DMS/files/Diabetes_Common_Comorbidities_Fact_Sheet.doc. Accessed August 15, 2009.
  2. 2.
    Struijs JN, Baan CA, Schellevis FG, Westert GP, van den Bos GA. Comorbidity in patients with diabetes mellitus: impact on medical health care utilization. BMC Health Serv Res. 2006;6:84.CrossRefPubMedGoogle Scholar
  3. 3.
    Wolff JL, Starfield B, Anderson G. Prevalence, expenditures, and complications of multiple chronic conditions in the elderly. Arch Intern Med. 2002;162(20):2269–2276.CrossRefPubMedGoogle Scholar
  4. 4.
    Schoenthaler A, Chaplin WF, Allegrante JP, et al. Provider communication effects medication adherence in hypertensive African Americans. Patient Educ Couns. 2009;75(2):185–191.CrossRefPubMedGoogle Scholar
  5. 5.
    Kerr EA, Heisler M, Krein SL, et al. Beyond comorbidity counts: how do comorbidity type and severity influence diabetes patients’ treatment priorities and self-management? J Gen Intern Med. 2007;22(12):1635–1640.CrossRefPubMedGoogle Scholar
  6. 6.
    Krein SL, Hofer TP, Holleman R, Piette JD, Klamerus ML, Kerr EA. More than a pain in the neck: how discussing chronic pain affects hypertension medication intensification. J Gen Intern Med. 2009;24(8):911–916.CrossRefPubMedGoogle Scholar
  7. 7.
    Krein SL, Heisler M, Piette JD, Makki F, Kerr EA. The effect of chronic pain on diabetes patients’ self-management. Diabetes Care. 2005;28(1):65–70.CrossRefPubMedGoogle Scholar
  8. 8.
    Ciechanowski PS, Katon WJ, Russo JE. Depression and diabetes: impact of depressive symptoms on adherence, function, and costs. Arch Intern Med. 2000;160(21):3278–3285.CrossRefPubMedGoogle Scholar
  9. 9.
    Egede LE, Zheng D, Simpson K. Comorbid depression is associated with increased health care use and expenditures in individuals with diabetes. Diabetes Care. 2002;25(3):464–470.CrossRefPubMedGoogle Scholar
  10. 10.
    Abbo ED, Zhang Q, Zelder M, Huang ES. The increasing number of clinical items addressed during the time of adult primary care visits. J Gen Intern Med. 2008;23(12):2058–2065.CrossRefPubMedGoogle Scholar
  11. 11.
    Fung CH, Setodji CM, Kung FY, et al. The relationship between multimorbidity and patients’ ratings of communication. J Gen Intern Med. 2008;23(6):788–793.CrossRefPubMedGoogle Scholar
  12. 12.
    Ostbye T, Yarnall KS, Krause KM, Pollak KI, Gradison M, Michener JL. Is there time for management of patients with chronic diseases in primary care? Ann Fam Med. 2005;3(3):209–214.CrossRefPubMedGoogle Scholar
  13. 13.
    Piette JD, Kerr EA. The impact of comorbid chronic conditions on diabetes care. Diabetes Care. 2006;29(3):725–731.CrossRefPubMedGoogle Scholar
  14. 14.
    Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW. Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: implications for pay for performance. JAMA. 2005;294(6):716–724.CrossRefPubMedGoogle Scholar
  15. 15.
    Kaplan SH, Greenfield S, Ware JE Jr. Assessing the effects of physician-patient interactions on the outcomes of chronic disease. Med Care. 1989;27(3 Suppl):S110–127.CrossRefPubMedGoogle Scholar
  16. 16.
    Stewart M, Brown JB, Donner A, et al. The impact of patient-centered care on outcomes. J Fam Pract. 2000;49(9):796–804.PubMedGoogle Scholar
  17. 17.
    Stewart MA. Effective physician-patient communication and health outcomes: a review. Can Med Assoc J. 1995;152(9):1423–1433.Google Scholar
  18. 18.
    Street RLJ, Makoul G, Arora NK, Epstein RM. How does communication heal? Pathways linking clinician-patient communication to health outcomes. Patient Educ Couns. 2009;74(3):295–301.CrossRefPubMedGoogle Scholar
  19. 19.
    Bass MJ, Buck C, Turner L, Dickie G, Pratt G, Robinson HC. The physician’s actions and the outcome of illness in family practice. J Fam Pract. 1986;23(1):43–47.PubMedGoogle Scholar
  20. 20.
    Chesney AP, Brown KA, Poe CW, Gary HE Jr. Physician-patient agreement on symptoms as a predictor of retention in outpatient care. Hosp Community Psychiatry. 1983;34(8):737–739.PubMedGoogle Scholar
  21. 21.
    Starfield B, Steinwachs D, Morris I, Bause G, Siebert S, Westin C. Patient-doctor agreement about problems needing follow-up visit. JAMA. 1979;242(4):344–346.CrossRefPubMedGoogle Scholar
  22. 22.
    Starfield B, Wray C, Hess K, Gross R, Birk PS, D'Lugoff BC. The influence of patient-practitioner agreement on outcome of care. Am J Public Health. 1981;71(2):127–131.CrossRefPubMedGoogle Scholar
  23. 23.
    Krupat E, Bell RA, Kravitz RL, Thom D, Azari R. When physicians and patients think alike: patient-centered beliefs and their impact on satisfaction and trust. J Fam Pract. 2001;50(12):1057–1062.PubMedGoogle Scholar
  24. 24.
    Roter D. The enduring and evolving nature of the patient-physician relationship. Patient Educ Couns. 2000;39(1):5–15.CrossRefPubMedGoogle Scholar
  25. 25.
    Street RL Jr, Gordon HS, Ward MM, Krupat E, Kravitz RL. Patient participation in medical consultations: why some patients are more involved than others. Med Care. 2005;43(10):960–969.CrossRefPubMedGoogle Scholar
  26. 26.
    Bell RA, Kravitz RL, Thom D, Krupat E, Azari R. Unmet expectations for care and the patient-physician relationship. J Gen Intern Med. 2002;17(11):817–824.CrossRefPubMedGoogle Scholar
  27. 27.
    Zebiene E, Svab I, Sapoka V, et al. Agreement in patient-physician communication in primary care: a study from Central and Eastern Europe. Patient Educ Couns. 2008;73(2):246–250.CrossRefPubMedGoogle Scholar
  28. 28.
    Boland BJ, Scheitel SM, Wollan PC, Silverstein MD. Patient-physician agreement on reasons for ambulatory general medical examinations. Mayo Clin Proc. 1998;73(2):109–117.CrossRefPubMedGoogle Scholar
  29. 29.
    Greer J, Halgin R. Predictors of physician-patient agreement on symptom etiology in primary care. Psychosom Med. 2006;68(2):277–282.CrossRefPubMedGoogle Scholar
  30. 30.
    Heisler M, Vijan S, Anderson RM, Ubel PA, Bernstein SJ, Hofer TP. When do patients and their physicians agree on diabetes treatment goals and strategies, and what difference does it make? J Gen Intern Med. 2003;18(11):893–902.CrossRefPubMedGoogle Scholar
  31. 31.
    Scheuer E, Steurer J, Buddeberg C. Predictors of differences in symptom perception of older patients and their doctors. Fam Pract. 2002;19(4):357–361.CrossRefPubMedGoogle Scholar
  32. 32.
    Sewitch MJ, Abrahamowicz M, Dobkin PL, Tamblyn R. Measuring differences between patients’ and physicians’ health perceptions: the patient-physician discordance scale. J Behav Med. 2003;26(3):245–264.CrossRefPubMedGoogle Scholar
  33. 33.
    Stewart MA, McWhinney IR, Buck CW. The doctor/patient relationship and its effect upon outcome. J R Coll Gen Pract. 1979;29(199):77–81.PubMedGoogle Scholar
  34. 34.
    Kerr EA, Zikmund-Fisher BJ, Klamerus ML, Subramanian U, Hogan MM, Hofer TP. The role of clinical uncertainty in treatment decisions for diabetic patients with uncontrolled blood pressure. Ann Intern Med. 2008;148(10):717–727.PubMedGoogle Scholar
  35. 35.
    DeSalvo KB, Bloser N, Reynolds K, He J, Muntner P. Mortality prediction with a single general self-rated health question: a meta-analysis. J Gen Intern Med. 2005;20:267–275.CrossRefGoogle Scholar
  36. 36.
    DeSalvo KB, Fisher WP, Tran K, Bloser N, Merrill W, Peabody J. Assessing measurement properties of two single-item general health measures. Qual Life Res. 2006;15(2):191–201.CrossRefPubMedGoogle Scholar
  37. 37.
    Eriksson I, Unden AL, Elofsson S. Self-rated health. Comparisons between three different measures. Results from a population study. Int J Epidemiol. 2001;30(2):326–333.CrossRefPubMedGoogle Scholar
  38. 38.
    Mossey JM, Shapiro E. Self-rated health: a predictor of mortality among the elderly. Am J Public Health. 1982;72(8):800–808.CrossRefPubMedGoogle Scholar
  39. 39.
    Corson K, Gerrity MS, Dobscha SK. Screening for depression and suicidality in a VA primary care setting: two items are better than one item. Am J Manag Care. 2004;10(11 Pt 2):839–845.PubMedGoogle Scholar
  40. 40.
    Bair MJ, Robinson RL, Katon W, Kroenke K. Depression and pain comorbidity: a literature review. Arch Intern Med. 2003;163(20):2433–2445.CrossRefPubMedGoogle Scholar
  41. 41.
    Safran DG, Kosinski M, Tarlov AR, et al. The Primary Care Assessment Survey: tests of data quality and measurement performance. Med Care. 1998;36(5):728–739.CrossRefPubMedGoogle Scholar
  42. 42.
    Yu W, Ravelo A, Wagner TH, et al. Prevalence and costs of chronic conditions in the VA health care system. Med Care Res Rev. 2003;60(3 Suppl):146S–167S.CrossRefPubMedGoogle Scholar
  43. 43.
    Long JS, Freese J. Regression Models for Categorical Outcomes Using Stata. 2nd ed. College Station: Stata Press; 2005.Google Scholar
  44. 44.
    Rogers WH. Regression standard errors in clustered samples. Stata Tech Bull. 1993;13:19–23.Google Scholar
  45. 45.
    Oehlert GW. A note on the delta method. Am Stat. 1992;46:27–29.CrossRefGoogle Scholar
  46. 46.
    Carlin JB, Galati JC, Royston P. A new framework for managing and analyzing multiply imputed data in Stata. Stata J. 2008;8:49–67.Google Scholar
  47. 47.
    Parchman ML, Pugh JA, Romero RL, Bowers KW. Competing demands or clinical inertia: the case of elevated glycosylated hemoglobin. Ann Fam Med. 2007;5(3):196–201.CrossRefPubMedGoogle Scholar
  48. 48.
    Berlowitz DR, Ash AS, Hickey EC, Glickman M, Friedman R, Kader B. Hypertension management in patients with diabetes: the need for more aggressive therapy. Diabetes Care. 2003;26(2):355–359.CrossRefPubMedGoogle Scholar
  49. 49.
    Hansson L, Zanchetti A, Carruthers SG, et al. Effects of intensive blood-pressure lowering and low-dose aspirin in patients with hypertension: principal results of the Hypertension Optimal Treatment (HOT) randomised trial. HOT Study Group. Lancet. 1998;351(9118):1755–1762.CrossRefPubMedGoogle Scholar
  50. 50.
    Snow V, Weiss KB, Mottur-Pilson C. The evidence base for tight blood pressure control in the management of type 2 diabetes mellitus. Ann Intern Med. 2003;138(7):587–592.PubMedGoogle Scholar
  51. 51.
    Subramanian U, Hofer TP, Klamerus ML, Zikmund-Fisher BJ, Heisler M, Kerr EA. Knowledge of blood pressure targets among patients with diabetes. Prim Care Diabetes. 2007;1(4):195–198.CrossRefPubMedGoogle Scholar
  52. 52.
    Wong N, Wang SS, Lamoureux E, et al. Blood pressure control and awareness among patients with diabetes and hypertension attending a tertiary ophthalmic clinic. Diabet Med. 2009;26(1):34–39.CrossRefPubMedGoogle Scholar
  53. 53.
    Katon WJ, Rutter C, Simon G, et al. The association of comorbid depression with mortality in patients with type 2 diabetes. Diabetes Care. 2005;28(11):2668–2672.CrossRefPubMedGoogle Scholar
  54. 54.
    Lustman PJ, Anderson RJ, Freedland KE, de Groot M, Carney RM, Clouse RE. Depression and poor glycemic control: a meta-analytic review of the literature. Diabetes Care. 2000;23(7):934–942.CrossRefPubMedGoogle Scholar
  55. 55.
    Staiger TO, Jarvik JG, Deyo RA, Martin B, Braddock CH 3rd. BRIEF REPORT: patient-physician agreement as a predictor of outcomes in patients with back pain. J Gen Intern Med. 2005;20(10):935–937.CrossRefPubMedGoogle Scholar
  56. 56.
    Schoenberg NE, Leach C, Edwards W. “It’s a toss up between my hearing, my heart, and my hip”: prioritizing and accomodating multiple morbidities by vulnerable older adults. J Health Care Poor Underserved. 2009;20(1):134–151.CrossRefPubMedGoogle Scholar
  57. 57.
    Glasgow RE, Nutting PA, King DK, et al. Randomized effectiveness trial of a computer-assisted intervention to improve diabetes care. Diabetes Care. 2005;28(1):33–39.CrossRefPubMedGoogle Scholar
  58. 58.
    Greenfield S, Kaplan S, Ware JE Jr. Expanding patient involvement in care. Effects on patient outcomes. Ann Intern Med. 1985;102(4):520–528.PubMedGoogle Scholar
  59. 59.
    Liaw ST, Young D, Farish S. Improving patient-doctor concordance: an intervention study in general practice. Fam Pract. 1996;13(5):427–431.CrossRefPubMedGoogle Scholar
  60. 60.
    Schillinger D, Handley M, Wang F, Hammer H. Effects of self-management support on structure, process, and outcomes among vulnerable patients with diabetes: a three-arm practical clinical trial. Diabetes Care. 2009;32(4):559–566.CrossRefPubMedGoogle Scholar
  61. 61.
    Williams GC, Lynch M, Glasgow RE. Computer-assisted intervention improves patient-centered diabetes care by increasing autonomy support. Health Psychol. 2007;26(6):728–734.CrossRefPubMedGoogle Scholar

Copyright information

© Society of General Internal Medicine 2010

Authors and Affiliations

  • Donna M. Zulman
    • 1
    • 2
    • 3
    Email author
  • Eve A. Kerr
    • 1
    • 2
  • Timothy P. Hofer
    • 1
    • 2
  • Michele Heisler
    • 1
    • 2
    • 3
  • Brian J. Zikmund-Fisher
    • 1
    • 2
  1. 1.Department of Veterans AffairsHealth Services Research and Development Center of ExcellenceAnn ArborUSA
  2. 2.Department of Internal MedicineUniversity of Michigan Medical SchoolAnn ArborUSA
  3. 3.The Robert Wood Johnson Clinical Scholars ProgramUniversity of MichiganAnn ArborUSA

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