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Published in: Journal of General Internal Medicine 6/2008

01-06-2008 | Original Article

The Relationship Between Multimorbidity and Patients’ Ratings of Communication

Authors: Constance H. Fung, MD, MSHS, Claude M. Setodji, PhD, Fuan-Yue Kung, MS, Joan Keesey, BA, Steven M. Asch, MD, MPH, John Adams, PhD, Elizabeth A. McGlynn, PhD

Published in: Journal of General Internal Medicine | Issue 6/2008

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Abstract

BACKGROUND

The growing interest in pay-for-performance and other quality improvement programs has generated concerns about potential performance measurement penalties for providers who care for more complex patients, such as patients with more chronic conditions. Few data are available on how multimorbidity affects common performance metrics.

OBJECTIVE

To examine the relationship between multimorbidity and patients’ ratings of communication, a common performance metric.

DESIGN

Cross-sectional study

SETTING

Nationally representative sample of U.S. residents

PARTICIPANTS

A total of 15,709 noninstitutionalized adults living in the United States participated in a telephone interview.

MEASUREMENTS

We used 2 different measures of multimorbidity: 1) “individual conditions” approach disregards similarities/concordance among chronic conditions and 2) “condition-groups” approach considers similarities/concordance among conditions. We used a composite measure of patients’ ratings of patient–physician communication.

RESULTS

A higher number of individual conditions is associated with lower ratings of communication, although the magnitude of the relationship is small (adjusted average communication scores: 0 conditions, 12.20; 1–2 conditions, 12.06; 3+ conditions, 11.90; scale range 5 = worst, 15 = best). This relationship remains statistically significant when concordant relationships among conditions are considered (0 condition groups 12.19; 1–2 condition groups 12.03; 3+ condition groups 11.94).

CONCLUSIONS

In our nationally representative sample, patients with more chronic conditions gave their doctors modestly lower patient–doctor communication scores than their healthier counterparts. Accounting for concordance among conditions does not widen the difference in communication scores. Concerns about performance measurement penalty related to patient complexity cannot be entirely addressed by adjusting for multimorbidity. Future studies should focus on other aspects of clinical complexity (e.g., severity, specific combinations of conditions).
Literature
2.
go back to reference Safran DG, Kosinski M, Tarlov AR, et al. The Primary Care Assessment Survey: tests of data quality and measurement performance. Med Care. 1998;36:728.PubMedCrossRef Safran DG, Kosinski M, Tarlov AR, et al. The Primary Care Assessment Survey: tests of data quality and measurement performance. Med Care. 1998;36:728.PubMedCrossRef
3.
go back to reference Safran DG, Karp M, Coltin K, et al. Measuring patients’ experiences with individual primary care physicians. Results of a statewide demonstration project. J Gen Intern Med. 2006;21:13–21.PubMedCrossRef Safran DG, Karp M, Coltin K, et al. Measuring patients’ experiences with individual primary care physicians. Results of a statewide demonstration project. J Gen Intern Med. 2006;21:13–21.PubMedCrossRef
4.
go back to reference Fung CH, Elliott MN, Hays RD, et al. Patients’ preferences for technical versus interpersonal quality when selecting a primary care physician. Health Serv Res. 2005;40:957.PubMedCrossRef Fung CH, Elliott MN, Hays RD, et al. Patients’ preferences for technical versus interpersonal quality when selecting a primary care physician. Health Serv Res. 2005;40:957.PubMedCrossRef
5.
go back to reference Laine C, Davidoff F, Lewis CE, et al. Important elements of outpatient care: a comparison of patients’ and physicians’ opinions. Ann Intern Med. 1996;125:640–5.PubMed Laine C, Davidoff F, Lewis CE, et al. Important elements of outpatient care: a comparison of patients’ and physicians’ opinions. Ann Intern Med. 1996;125:640–5.PubMed
10.
go back to reference Werner RM, Greenfield S, Fung C, Turner BJ. Measuring quality of care in patients with multiple clinical conditions: summary of a conference conducted by the Society of General Internal Medicine. J Gen Intern Med. 2007;22:1206–11.PubMedCrossRef Werner RM, Greenfield S, Fung C, Turner BJ. Measuring quality of care in patients with multiple clinical conditions: summary of a conference conducted by the Society of General Internal Medicine. J Gen Intern Med. 2007;22:1206–11.PubMedCrossRef
11.
go back to reference Yancik R, Ershler W, Satariano W, Hazzard W, Cohen HJ, Ferrucci L. Report of the national institute on aging task force on comorbidity. J Gerontol Ser A Biol Sci Med Sci. 2007;62:275–80. Yancik R, Ershler W, Satariano W, Hazzard W, Cohen HJ, Ferrucci L. Report of the national institute on aging task force on comorbidity. J Gerontol Ser A Biol Sci Med Sci. 2007;62:275–80.
12.
go back to reference Fortin M, Bravo G, Hudon C, Vanasse A, Lapointe L. Prevalence of multimorbidity among adults seen in family practice. Ann Fam Med. 2005;3:223–8.PubMedCrossRef Fortin M, Bravo G, Hudon C, Vanasse A, Lapointe L. Prevalence of multimorbidity among adults seen in family practice. Ann Fam Med. 2005;3:223–8.PubMedCrossRef
13.
go back to reference Wolff JL, Starfield B, Anderson G. Prevalence, expenditures, and complications of multiple chronic conditions in the elderly. Arch Intern Med. 2002;162:2269–76.PubMedCrossRef Wolff JL, Starfield B, Anderson G. Prevalence, expenditures, and complications of multiple chronic conditions in the elderly. Arch Intern Med. 2002;162:2269–76.PubMedCrossRef
14.
go back to reference Parchman ML, Noel PH, Lee S. Primary care attributes, health care system hassles, and chronic illness. Med Care. 2005;43:1123–9.PubMedCrossRef Parchman ML, Noel PH, Lee S. Primary care attributes, health care system hassles, and chronic illness. Med Care. 2005;43:1123–9.PubMedCrossRef
15.
go back to reference Tai-Seale M, McGuire TG, Zhang W. Time allocation in primary care office visits. Health Serv Res. 2007;42:1871–94.PubMedCrossRef Tai-Seale M, McGuire TG, Zhang W. Time allocation in primary care office visits. Health Serv Res. 2007;42:1871–94.PubMedCrossRef
16.
go back to reference Community Tracking Study Household Survey, 2000–2001:[United States] [Computer file]. Inter-university Consortium for Political and Social Research. Ann Arbor: Center for Studying Health System Change; 2003. Community Tracking Study Household Survey, 2000–2001:[United States] [Computer file]. Inter-university Consortium for Political and Social Research. Ann Arbor: Center for Studying Health System Change; 2003.
17.
go back to reference McGlynn EA, Asch SM, Adams J, et al. The quality of health care delivered to adults in the United States. N Engl J Med. 2003;348:2635.PubMedCrossRef McGlynn EA, Asch SM, Adams J, et al. The quality of health care delivered to adults in the United States. N Engl J Med. 2003;348:2635.PubMedCrossRef
18.
go back to reference Chang JT, Hays RD, Shekelle PG, et al. Patients’ global ratings of their health care are not associated with the technical quality of their care. Ann Intern Med. 2006;144:665–72.PubMed Chang JT, Hays RD, Shekelle PG, et al. Patients’ global ratings of their health care are not associated with the technical quality of their care. Ann Intern Med. 2006;144:665–72.PubMed
19.
go back to reference Hargraves JL, Hays RD, Cleary PD. Psychometric properties of the Consumer Assessment of Health Plans Study (CAHPS) 2.0 adult core survey. Health Serv Res. 2003;38:1509–27.PubMedCrossRef Hargraves JL, Hays RD, Cleary PD. Psychometric properties of the Consumer Assessment of Health Plans Study (CAHPS) 2.0 adult core survey. Health Serv Res. 2003;38:1509–27.PubMedCrossRef
22.
go back to reference Fiellin DA, Reid MC, O’Connor PG. Outpatient management of patients with alcohol problems. Ann Intern Med. 2000;133:815–27.PubMed Fiellin DA, Reid MC, O’Connor PG. Outpatient management of patients with alcohol problems. Ann Intern Med. 2000;133:815–27.PubMed
24.
go back to reference Katz JN, Chang LC, Sangha O, Fossel AH, Bates DW. Can comorbidity be measured by questionnaire rather than medical record review? Med Care. 1996;34:73–84.PubMedCrossRef Katz JN, Chang LC, Sangha O, Fossel AH, Bates DW. Can comorbidity be measured by questionnaire rather than medical record review? Med Care. 1996;34:73–84.PubMedCrossRef
25.
go back to reference Piette JD, Kerr EA. The impact of comorbid chronic conditions on diabetes care. Diabetes Care. 2006;29:725–31.PubMedCrossRef Piette JD, Kerr EA. The impact of comorbid chronic conditions on diabetes care. Diabetes Care. 2006;29:725–31.PubMedCrossRef
26.
go back to reference Schellevis FG, van der Velden J, van de Lisdonk E, van Eijk JT, van Weel C. Comorbidity of chronic diseases in general practice. J Clin Epidemiol. 1993;46:469–73.PubMedCrossRef Schellevis FG, van der Velden J, van de Lisdonk E, van Eijk JT, van Weel C. Comorbidity of chronic diseases in general practice. J Clin Epidemiol. 1993;46:469–73.PubMedCrossRef
27.
go back to reference Van den Akker M, Buntinx F, Roos S, Knottnerus JA. Problems in determining occurrence rates of multimorbidity. J Clin Epidemiol. 2001;54:675–9.PubMedCrossRef Van den Akker M, Buntinx F, Roos S, Knottnerus JA. Problems in determining occurrence rates of multimorbidity. J Clin Epidemiol. 2001;54:675–9.PubMedCrossRef
28.
go back to reference Landon BE, Zaslavsky AM, Bernard SL, Cioffi MJ, Cleary PD. Comparison of performance of traditional Medicare vs Medicare managed care. JAMA. 2004;291:1744–52.PubMedCrossRef Landon BE, Zaslavsky AM, Bernard SL, Cioffi MJ, Cleary PD. Comparison of performance of traditional Medicare vs Medicare managed care. JAMA. 2004;291:1744–52.PubMedCrossRef
29.
go back to reference Hargraves JL, Wilson IB, Zaslavsky A, et al. Adjusting for patient characteristics when analyzing reports from patients about hospital care. Med Care. 2001;39:635–41.PubMedCrossRef Hargraves JL, Wilson IB, Zaslavsky A, et al. Adjusting for patient characteristics when analyzing reports from patients about hospital care. Med Care. 2001;39:635–41.PubMedCrossRef
30.
go back to reference Morales LS, Elliott MN, Weech-Maldonado R, Spritzer KL, Hays RD. Differences in CAHPS adult survey reports and ratings by race and ethnicity: an analysis of the National CAHPS benchmarking data 1.0. Health Serv Res. 2001;36:595–617.PubMed Morales LS, Elliott MN, Weech-Maldonado R, Spritzer KL, Hays RD. Differences in CAHPS adult survey reports and ratings by race and ethnicity: an analysis of the National CAHPS benchmarking data 1.0. Health Serv Res. 2001;36:595–617.PubMed
31.
go back to reference Graubard B, Korn E. Predictive margins with survey data. Biometrics. 55:652–9. Graubard B, Korn E. Predictive margins with survey data. Biometrics. 55:652–9.
32.
go back to reference Werner RM, Asch DA. Clinical concerns about clinical performance measurement. Ann Fam Med. 2007;5:159–63.PubMedCrossRef Werner RM, Asch DA. Clinical concerns about clinical performance measurement. Ann Fam Med. 2007;5:159–63.PubMedCrossRef
33.
go back to reference Donabedian A. Explorations in Quality Assessment and Monitoring: The Definition of Quality and Approaches to Its Assessment. Ann Arbor, MI: Health Administration Press; 1980. Donabedian A. Explorations in Quality Assessment and Monitoring: The Definition of Quality and Approaches to Its Assessment. Ann Arbor, MI: Health Administration Press; 1980.
34.
go back to reference Min LC, Wenger NS, Fung C, et al. Multimorbidity is associated with better quality of care among vulnerable elders. Med Care. 2007;45:480–8.PubMedCrossRef Min LC, Wenger NS, Fung C, et al. Multimorbidity is associated with better quality of care among vulnerable elders. Med Care. 2007;45:480–8.PubMedCrossRef
35.
go back to reference Higashi T, Wenger NS, Adams J, et al. Patients with more medical conditions receive better quality care: analysis of quality data from three large surveys. New Engl J Med. 2007;356:2496–504.PubMedCrossRef Higashi T, Wenger NS, Adams J, et al. Patients with more medical conditions receive better quality care: analysis of quality data from three large surveys. New Engl J Med. 2007;356:2496–504.PubMedCrossRef
36.
go back to reference Noel PH, Chris Frueh B, Larme AC, et al. Collaborative care needs and preferences of primary care patients with multimorbidity. Health Expect. 2005;8:54–63.PubMedCrossRef Noel PH, Chris Frueh B, Larme AC, et al. Collaborative care needs and preferences of primary care patients with multimorbidity. Health Expect. 2005;8:54–63.PubMedCrossRef
37.
go back to reference Nutting PA, Baier M, Werner JJ, Cutter G, Conry C, Stewart L. Competing demands in the office visit: what influences mammography recommendations? J Am Board Fam Pract. 2001;14:352.PubMed Nutting PA, Baier M, Werner JJ, Cutter G, Conry C, Stewart L. Competing demands in the office visit: what influences mammography recommendations? J Am Board Fam Pract. 2001;14:352.PubMed
38.
go back to reference Nutting PA, Rost K, Smith J, Werner JJ, Elliot C. Competing demands from physical problems: effect on initiating and completing depression care over 6 months. Arch Fam Med. 2000;9:1059.PubMedCrossRef Nutting PA, Rost K, Smith J, Werner JJ, Elliot C. Competing demands from physical problems: effect on initiating and completing depression care over 6 months. Arch Fam Med. 2000;9:1059.PubMedCrossRef
39.
go back to reference Street RL Jr. Communication in medical encounters: an ecological perspective. In: Thompson TL, Dorsey AM, Miller KI, Parrott R, eds. Handbook of Health Communication. Mahwah, NJ: Lawrence Erlbaum Associates; 2003. Street RL Jr. Communication in medical encounters: an ecological perspective. In: Thompson TL, Dorsey AM, Miller KI, Parrott R, eds. Handbook of Health Communication. Mahwah, NJ: Lawrence Erlbaum Associates; 2003.
40.
go back to reference Zyzanski SJ, Stange KC, Langa D, Flocke SA. Trade-offs in high-volume primary care practice. J Fam Pract. 1998;46:397–402.PubMed Zyzanski SJ, Stange KC, Langa D, Flocke SA. Trade-offs in high-volume primary care practice. J Fam Pract. 1998;46:397–402.PubMed
41.
go back to reference Damiano P, Elliott M, Tyler MC, Hays RD. Differential use of the CAHPS 0–10 global rating scale by Medicaid and commercial populations. Health Services and Outcomes Research Methodology. 2004;5:193–205.CrossRef Damiano P, Elliott M, Tyler MC, Hays RD. Differential use of the CAHPS 0–10 global rating scale by Medicaid and commercial populations. Health Services and Outcomes Research Methodology. 2004;5:193–205.CrossRef
42.
go back to reference Safran DG, Taira DA, Rogers WH, Kosinski M, Ware JE, Tarlov AR. Linking primary care performance to outcomes of care. J Fam Pract. 1998;47:213.PubMed Safran DG, Taira DA, Rogers WH, Kosinski M, Ware JE, Tarlov AR. Linking primary care performance to outcomes of care. J Fam Pract. 1998;47:213.PubMed
43.
go back to reference Burack JH, Impellizzeri P, Homel P, Cunningham JN Jr. Public reporting of surgical mortality: a survey of New York State cardiothoracic surgeons. Ann Thorac Surg. 1999;68:1195–1200. discussion 201–2.PubMedCrossRef Burack JH, Impellizzeri P, Homel P, Cunningham JN Jr. Public reporting of surgical mortality: a survey of New York State cardiothoracic surgeons. Ann Thorac Surg. 1999;68:1195–1200. discussion 201–2.PubMedCrossRef
44.
go back to reference Hannan EL, Kilburn H Jr., Racz M, Shields E, Chassin MR. Improving the outcomes of coronary artery bypass surgery in New York State. JAMA. 1994;271:761–6.PubMedCrossRef Hannan EL, Kilburn H Jr., Racz M, Shields E, Chassin MR. Improving the outcomes of coronary artery bypass surgery in New York State. JAMA. 1994;271:761–6.PubMedCrossRef
45.
go back to reference 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;43:960–9.PubMedCrossRef 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;43:960–9.PubMedCrossRef
Metadata
Title
The Relationship Between Multimorbidity and Patients’ Ratings of Communication
Authors
Constance H. Fung, MD, MSHS
Claude M. Setodji, PhD
Fuan-Yue Kung, MS
Joan Keesey, BA
Steven M. Asch, MD, MPH
John Adams, PhD
Elizabeth A. McGlynn, PhD
Publication date
01-06-2008
Publisher
Springer-Verlag
Published in
Journal of General Internal Medicine / Issue 6/2008
Print ISSN: 0884-8734
Electronic ISSN: 1525-1497
DOI
https://doi.org/10.1007/s11606-008-0602-4

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