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Mental Illness, Functional Impairment, and Patient Preferences for Collaborative Care in an Uninsured, Primary Care Population
STUDY DESIGN: We compared a survey of consecutive primary care adults in April and May 1999 with a 1997-98 survey of 3000 general population primary care patients. Both studies used the Primary Care Evaluation of Mental Disorders Patient Health Questionnaire and the 20-question Medical Outcomes Study Short Form.
POPULATION: The patients were from a private nonprofit primary care clinic in Grand Junction, Colorado, that served only low-income uninsured people. We approached a total of 589 consecutive patients and enrolled 500 of them.
MAIN OUTCOME MEASURE: The main outcomes were the prevalence of psychiatric illnesses and the relationship with functional impairment. We compared our findings with a more generalizable primary care population.
RESULTS: This low-income uninsured population had a higher prevalence of 1 or more psychiatric disorders (51% vs 28%): mood disorders (33% vs 16%), anxiety disorders (36% vs 11%), probable alcohol abuse (17% vs 7%), and eating disorders (10% vs 7%). Having psychiatric disorders was associated with lower functional status and more disability days compared with not having mental illness. Patients indicated a preference for mental health providers and medical providers to communicate about their care.
CONCLUSIONS: This low-income uninsured primary care population has an extremely high prevalence of mental disorders with impaired function. It may be important in low-income primary care settings to include collaborative care designs to effectively treat common mental disorders, improve functional status, and enhance patient self-care.
Poverty is bad for a person’s health,1 diminishing physical, cognitive, and psychological2 well-being.3 Attempts to understand why persons with low socioeconomic status have poor health point to psychosocial and behavioral variables,4 such as smoking, bad dietary habits, exposure to trauma and violence, sedentary lifestyles, hopelessness, hostility, and depression.5 Mental illnesses6 (particularly depression7) cause more disability8 and diminished functional status than most physical illnesses.9 It is no surprise, therefore, that people with untreated mental illness use a disproportionate amount of health care resources.10 Thus, the more than 11 million11 people living in poverty who are uninsured are a particularly vulnerable sector of our society.12
In primary care settings the prevalence of mental illness13,14 and its relationship to functional status9 and health care use10 is well studied. However, we know little about these issues in indigent primary care populations. Miranda and colleagues15 studied 205 women at an urban, public sector, gynecology clinic and found that 48% had at least 1 psychiatric disorder. Olfson and coworkers16 studied an urban, older, low-income, mostly Hispanic, general medical population and found a high prevalence of depression, anxiety, substance use, and suicidal ideation associated with decreased function. A recent study by Woolf and colleagues17 found the functional status of inner city, indigent, primary care patients to be lower than the general population and lower than a national sample of patients with common chronic illnesses. We found no studies examining the prevalence of mental disorders and their relationship with functional status and health care use in low-income uninsured patients in primary care settings.
Family physicians18 and the Surgeon General19 have advocated for the integration of mental health into medical settings to improve care and reduce the stigmatization of mental illness. Models of collaboration20,21 between mental health and medical providers have been shown to be effective22-25 and cost-effective.26,27 Attending to patient preferences about therapeutic modality enhances the effectiveness of mental disorder treatments.28 However, we found no studies examining indigent patient preferences regarding the separation versus integration of medical and mental health services.
We predicted that an underprivileged, uninsured sample of primary care patients would have higher levels of mental illness and more impaired function than has been reported in general primary care samples. We also suspected that heath care utilization would be higher for indigent patients with more psychiatric symptoms compared with indigent primary care patients without psychiatric distress. Because policy,19 provider,18 and research23,25 recommendations endorse collaborative care designs, we wanted to initiate exploration of patient preferences for these service structures, since attending to patient wishes might enhance the effectiveness of future interventions.
Methods
Setting
We conducted our study at the Marillac Clinic in Grand Junction, Colorado. Marillac is a privately funded, nonprofit, primary care clinic serving Mesa County, Colorado (3313 square miles), with a population of 113,000 in 1999. Marillac serves only people without any form of health insurance (no Medicare or Medicaid) and with household incomes less than 150% of federal poverty guidelines. In 1998,14.5% of the Mesa County population lived below the poverty level, 16.6% lacked health insurance, 4.5% were unemployed, 90% were white, and 8% were Hispanic.29 The Human Subjects Review committee of St. Mary’s Hospital, Grand Junction, Colorado, approved our study.
Selection of Subjects
During April and early May 1999, all consecutive patients aged 18 years and older with clinic medical appointments were invited to participate in our study. One of 4 medical office assistants explained the study to each patient. The participants could allow or not allow study findings to be shared with their care providers after the clinic visit. Trained readers were available for those patients unable to read the survey. This service was used on 3 occasions. Participants received a $5 coupon to a local grocery store. Of the 589 patients approached, 68 refused and 21 were missed, for an enrollment of 500 patients (85%), representing 19% of the patients seen at the clinic in 1999. Of those refusing participation, 18 were not interested, 17 were too sick, 23 were too busy, and 10 cited other reasons. There were no significant differences in age or sex between the study participants and those who refused. The mean age for those who refused was 40 years (standard deviation [SD]=11.2) versus 38 years (SD=12.1) for study participants, (t(588)=1.88). Of those who refused 59% were women; 68% of the study participants were women (c2=2.42; df=1).
Data Collection
Patients. The patients completed a questionnaire before being seen by their health care providers. For patients who agreed, providers were alerted when survey results indicated the presence of 1 or more mental disorders.
Study Instrument. The study instruments included the recently validated Primary Care Evaluation of Mental Disorders (PRIME-MD) Patient Health Questionnaire (PHQ)30; the 20-item Medical Outcomes Study Short Form (SF-20), a validated31 tool to assess functional status; and other questions described below. The PRIME-MD PHQ is a self-report version of the original PRIME-MD32 that allows researchers to assess the presence of 7 psychiatric disorders. Like the original PRIME-MD, the PHQ assessed threshold disorders (major depression, panic disorder, other anxiety disorder, bulimia) and subthreshold disorders (minor depression, binge-eating disorder, probable alcohol abuse, somatoform disorder). Because providers were blind to patient response, diagnosis of somatoform disorder was not included. Some patients were classified as symptom screen positive because they indicated distress but failed to meet criteria for a subthreshold or a threshold diagnosis. Patients who screened positive reported depressed mood or low interest on more than half the days, a panic attack in the previous 4 weeks, feeling nervous more than half the days, often feeling “you cannot control what or how much you eat,” or being “bothered a lot” by more than 6 of the 13 PHQ physical symptoms. The SF-20 measures functional status in 6 dimensions. We defined the term “disability days” as the number of days in the past 3 months patients were kept from usual activities because of not feeling well. Health care use was defined by the number of separate times during the past 3 months that patients went to a medical physician in an office, clinic, or emergency room because of not feeling well, not counting the present visit.
Other questions added to the questionnaire included a 20-item list of current physical illnesses (medical comorbidity)24 and demographic questions. A question to assess patient preferences for service design asked: “In the future, if you desire mental health care, please check your top 2 preferred designs:” (A) your medical provider and mental health provider work in the same setting and communicate with one another about your care; (B) communication between providers with service at separate settings; (C) providers do not communicate with service at the same setting; and (D) providers do not communicate, and service is provided at separate settings (alternatives B, C, and D are abbreviated).
Statistical Analyses
We examined descriptive data for the sample. To test the hypothesis that poor, uninsured primary care patients will have higher rates of mental illness compared with a general primary care sample, we compared prevalence data for psychiatric disorders in the study sample against a representative primary care PHQ sample of 3000 patients. Since the PHQ study is from a different population with different sociodemographic and medical characteristics and different sampling techniques, we could not directly compare its data with statistical tests to discern differences in the populations. To determine if there were more problems with functional status and disability days and higher health care use for patients with more psychiatric symptoms, we classified patients into 3 groups based on psychiatric diagnoses: symptom screen negative, screen positive/subthreshold, and threshold groups. Originally the screen-positive and subthreshold groups were analyzed separately. However, because of nearly identical means they were combined for subsequent analyses. Analyses of covariance were used to examine differences in functioning and disability days. The covariates we used were personal income and number of physical health problems. We performed a chi-square analysis to determine if the psychiatric patient groups differed in the proportion with 3 or more physician visits in the past 3 months.
Results
Prevalence of Psychiatric Diagnoses
Table 1 shows the study sample demographics. Table 2 presents a comparison of the prevalence of current disorders in the Marillac study with those in the PHQ 3000 study. The percentage of Marillac patients with at least 1 current psychiatric diagnosis is almost twice the prevalence of the PHQ study (51% vs 28%). Marillac patients had between 2 and 3 times as many of each of the current threshold diagnoses. The rates of each current subthreshold disorder are mildly higher than the PHQ study except for probable alcohol abuse, which is more than twice as high.
Functional Status, Disability Days, and Health Care Use
Figure 1 displays the adjusted means for the 6 scales of the SF-20 and shows that patients with one or more current threshold psychiatric disorders have significantly (P <.001) lower functional status on all SF-20 scales compared with the other 2 groups, which did not differ except for mental health. The percentage of patients in each of the 3 psychiatric symptom groups were: symptom screen negative, 31%; symptom screen positive/subthreshold diagnosis, 34%; and threshold diagnosis, 35%.
Screen-negative patients reported a mean (SD) of 4.3 (8.5) disability days; screen-positive/subthreshold patients reported 5.6 (12.2) days; and threshold diagnosis patients reported 18.9 (25.6) days. Controlling for physical comorbidity and personal income, patients with threshold psychiatric diagnoses had significantly more disability days than either of the 2 other groups, which did not differ from one another (F[2453]=30.20; P <.001). The 3 groups differed in number of physician visits in the previous 3 months. Controlling for physical comorbidity and personal income, percentages of patients within each diagnostic group with 3 or more physician visits were: screen negative, 15.7%; screen positive/subthreshold, 21.7%; and threshold, 34.5%. Patients in the threshold group were more likely to report 3 or more visits than patients in the other 2 groups (c2=16.27; df=2; P <.001). Differences between the screen-positive/subthreshold and the threshold group were also significant (c2=6.77; P <.009), but differences between screen-negative and screen-positive/subthreshold groups did not reach significance (c2=1.87; P <.17).
Patient Preferences for Medical and Mental Health Service Designs
Table 3 shows patient preferences. After choosing a first option patients were asked to make a second choice, which meant changing the location of service to maintain interprovider communication or eliminating communication to maintain service at a preferred location. Of the 284 patients who marked 2 votes, 246 (87%) chose the 2 options for providers to communicate with one another. The proportion of votes for the 2 communication options within each of the symptom groups was: threshold, 91%, subthreshold/screen positive, 86%, and screen negative, 90%.
Discussion
Using an instrument recently validated across 3000 primary care patients (the PRIME-MD PHQ) we found the proportion of the patients in this clinic with current major mental illnesses to be roughly twice the number in the general population (35% vs 15%). Overall, a larger proportion of patients in the Marillac population report some current psychiatric distress compared with the sample from Spitzer and coworkers30 (51% vs 28%). Because the PHQ does not diagnose dysthymia, non-alcohol–related substance abuse, or other chronic mental illnesses such as bipolar disorder, these findings represent a conservative view of the prevalence of mental illness and addictive disorders in this sample. Also, because primary care providers did not evaluate whether physical symptoms were secondary to a medical illness, somatoform disorders were not diagnosed.
Consistent with other studies9,33 patients with threshold disorders report significantly lower functional status compared with patients with subthreshold diagnoses or who are screen positive for psychiatric distress or without any psychiatric symptoms. However, these other studies have found a gradient of functional status inversely proportional to the degree of psychiatric impairment that was absent in the Marillac sample. The mean scores for Marillac symptom screen-negative patients are 7 to 15 points lower than the PHQ 3000 symptom screen-negative patients across all 6 SF-20 scales. These findings are consistent with findings reported by Woolf and colleagues17 who found mean scores on all the functional status indices for low-income patients to be significantly lower than their overall population means. It is unclear whether these findings are because of more severe mental disorders, a higher prevalence of physical disorders, or other characteristics of low-income populations.
Consistent with other studies,10,30 patients at Marillac with higher levels of psychiatric symptoms report increasing numbers of disability days and physician visits. Comparing disability days in PHQ 3000 patients in the threshold diagnosis (17), subthreshold (6.6), and screen-positive (4.8) groups shows similar numbers to our sample. However, the number of disability days for the Marillac patients without any psychiatric symptoms is almost twice as high as that in the PHQ 3000 sample (2.4) and consistent with the lower levels of functional status in the Marillac screen-negative group.
Although the prevalence of virtually all biomedical, psychosocial, and psychiatric illnesses is greater in the underprivileged, special attention needs to be paid to addressing cognitive, psychosocial, and psychiatric issues. The high prevalence of mental disorders may lead to chronic disability,34 perpetuating poverty. Mental illness complicates the management of chronic medical illness and increases risks for illness and death.35 Diminished sense of control of life compromises self-care36,37 and well-being.38
The majority (90%) of Marillac patients preferred their medical providers and mental health providers to communicate with one another about their health care. These patient preferences combined with research supporting the use of collaborative designs represented a compelling argument for system redesign. The findings of this study helped secure 4 years of funding from the Robert Wood Johnson 2000 Local Initiative Funding Partners Program to match funding from local contributors lead by the Colorado Trust. These funds will pay for on-site counselors, case managers, psychiatric and substance abuse assessments, group treatments, and ongoing training to create stronger linkages with a variety of community agencies (The Mesa County Coalition on Health). Marillac has adopted Collaborative Family Health Care,39 a model emphasizing teamwork between biomedical, nursing, and psychosocial providers, and that views the patient40,41 and family42-44 as crucial in treatment design and implementation. System adjustments emphasized the management of chronic illness45 with a focus on the psychosocial needs of this population.46 More details of these changes are described elsewhere.47
Limitations
The major limitation of our study may be lack of generalizability to other indigent primary care populations. More studies are needed that examine the prevalence of mental illnesses and relationships with functional status and disability in poor, urban populations with and without health insurance. Most subjects in our study are white and speak English. The prevalence and nature of mental disorders among urban diverse primary care patients may differ from the profiles we have described. In our study the method used to assess medical comorbidity relied on patient report. Patients may have under-reported or over-reported physical illness. Some symptoms reported on the PHQ could be caused by medical illnesses, and many may be medically unexplained.48 In the PHQ study, mental health professionals interviewed patients to validate survey findings. We assume that responses from this low-income population are valid, but future studies may want to further validate the PHQ in indigent samples. Our data probably underestimate overall prevalence of mental disorders in Marillac patients, because the number of disorders detected by the PHQ is limited. The Marillac population was younger (18-64 years) than the PHQ-3000 sample (19-99 years). An older population may have a different prevalence of mental disorders, levels of functional status, and service use. The relationships among these variables may also be different.
Conclusions
We found an indigent uninsured primary care adult population to have an extremely high prevalence of current mental disorders. Also, in addition to the expected decrease in functional status for those with severe mental disorders, the functional status of the entire clinic population was quite low. A sizable portion of the literature suggests that much of this diminished health-related quality of life might be the expression of an impoverished existence. Beyond financial poverty and limited education, the chronically poor person suffers from a higher prevalence of mental illness and a limited sense of being able to control the future. Patient preferences support provider and policy recommendations for the integration of mental health and primary care services. These health care designs may increase our potential to improve the health of those with the greatest need.49
Acknowledgments
Between August 1998 and July 1999 Mr Mauksch was on leave from the University of Washington Department of Family Medicine as a consultant in collaborative care to the Marillac Clinic. Funding for his position came from the Brownson Memorial Fund, the Victim/Witness Assistance and Law Enforcement Fund—21st Judicial District of Colorado, the Sisters of Charity, and St. Mary’s Hospital.
We wish to thank the Marillac Clinic medical assistants, administrative staff, community volunteers, and clinicians who contributed to this study in many essential ways. Because no additional financial support was used to fund this study, the role of the entire clinic community was critical for its successful completion.
The authors thank Jurgen Unützer, MD, for help in selecting an instrument to measure medical comorbidity.
Related Resources:
- The Collaborative Family HealthCare Coalition www.cfhcc.org
- The Institute for Healthcare Improvement-Information on “Improving Care for People with Chronic Conditions,” a national congress with a focus on asthma and depression www.ihi.org
- Anxiety Disorders Association of America www.adaa.org
- National Depressive and Manic Depressive Association www.ndmda.org
1. Feinstein JS. The relationship between socioeconomic status and health: a review of the literature. Milbank Q 1993;71:279-322.
2. Bruce ML, Takeuchi DT, Leaf PJ. Poverty and psychiatric status: longitudinal evidence from the New Haven Epidemiologic Catchment Area study. Arch Gen Psychiatry 1991;48:470-74.
3. Lynch JW, Kaplan GA, Shema SJ. Cumulative impact of sustained economic hardship on physical, cognitive, psychological, and social functioning. N Engl J Med 1997;337:1889-95.
4. Stronks K, van de Mheen HD, Mackenbach JP. A higher prevalence of health problems in low income groups: does it reflect relative deprivation? J Epidemiol Community Health. 1998;52:548-57.
5. Lynch JW, Kaplan GA, Salonen JT. Why do poor people behave poorly? Variation in adult health behaviours and psychosocial characteristics by stages of the socioeconomic lifecourse. Soc Sci Med 1997;44:809-19.
6. Norquist G, Hyman SE. Advances in understanding and treating mental illness: implications for policy. Health Aff 1999;18:32-47.
7. Hays RD, Wells KB, Sherbourne CD, Rogers W, Spritzer K. Functioning and well-being outcomes of patients with depression compared with chronic general medical illnesses. Arch Gen Psychiatry 1995;52:11-19.
8. Ormel J, VonKorff M, Ustun TB, Pini S, Korten A, Oldehinkel T. Common mental disorders and disability across cultures: results from the WHO Collaborative Study on Psychological Problems in General Health Care. JAMA 1994;272:1741-48.
9. Spitzer RL, Kroenke K, Linzer M, et al. Health-related quality of life in primary care patients with mental disorders: results from the PRIME-MD 1000 Study. JAMA 1995;274:1511-17.
10. Katon W, Von Korff M, Lin E, et al. Distressed high utilizers of medical care: DSM-III-R diagnoses and treatment needs. Gen Hosp Psychiatry 1990;12:355-62.
11. United States Census Bureau Health insurance coverage. Vol 1999. Washington, DC: US Census Bureau; 1998.
12. Andrulis DP. Access to care is the centerpiece in the elimination of socioeconomic disparities in health. Ann Intern Med 1998;129:412-16.
13. Regier DA, Goldberg ID, Taube CA. The de facto US mental health services system: a public health perspective. Arch Gen Psychiatry 1978;35:685-93.
14. Regier DA, Narrow WE, Rae DS, Manderscheid RW, Locke BZ, Goodwin FK. The de facto US mental and addictive disorders service system: epidemiologic catchment area prospective 1-year prevalence rates of disorders and services. Arch Gen Psychiatry 1993;50:85-94.
15. Miranda J, Azocar F, Komaromy M, Golding JM. Unmet mental health needs of women in public-sector gynecologic clinics. Am J Obstet Gynecol 1998;178:212-17.
16. Olfson M, Shea S, Feder A, et al. Prevalence of anxiety, depression and substance use disorders in an urban general medicine practice. Arch Fam Med 2000;9:876-83.
17. Woolf SH, Rothemich SF, Johnson RE, Marsland DW. The functional status of inner-city primary care patients: diminished function in a family practice population and its potential determinants. J Fam Pract 1998;47:312-15.
18. American Academy of Family Physicians. White paper on the provision of mental health services by family physicians. Kansas City, Kan: AAFP Commission on Health Care Services, 1994.
19. Surgeon General Mental health: a report of the Surgeon General. Washington, DC: Department of Health and Human Services; 1999.
20. Seaburn DB, Gawanski BA, Gunn WB, Lorenz A, Mauksch L. Models of collaboration: a guide for mental health professionals and health care practitioners. New York, NY: Basic Books; 1996.
21. Blount A, ed. Integrated primary care: the future of medical and mental health collaboration. New York, NY: W.W. Norton; 1998.
22. Katon W, Von Korff M, Lin E, et al. Collaborative management to achieve depression treatment guidelines. J Clin Psychiatry 1997;58:20-23.
23. Rubenstein LV, Jackson-Triche M, Unutzer J, et al. Evidence-based care for depression in managed primary care practices. Health Aff 1999;18:89-105.
24. Wells KB, Sherbourne C, Schoenbaum M, et al. Impact of disseminating quality improvement programs for depression in managed primary care: a randomized controlled trial. JAMA 2000;283:212-20.
25. Hemmings A. A systematic review of brief psychological therapies in primary health care. Fam Syst Health 2000;18:279-314.
26. Von Korff M, Katon W, Bush T, et al. Treatment costs, cost offset, and cost-effectiveness of collaborative management of depression. Psychosom Med 1998;60:143-49.
27. Olfson M, Sing M, Schlesinger HJ. Mental health/medical care cost offsets: opportunities for managed care. Health Aff 1999;18:79-90.
28. Mauksch L. An evidenced based recipe for primary care, psychotherapy and patient p. Fam Syst Health 2000;18:315-22.
29. Mesa County: our picture of health. Grand Junction, Colo: Civic Forum; 1998.
30. Spitzer RL, Kroenke K, Williams JB. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study: Primary Care Evaluation of Mental Disorders Patient Health Questionnaire. JAMA 1999;282:1737-44.
31. Stewart AL, Hays RD, Ware JE, Jr. The MOS short-form general health survey. Reliability and validity in a patient population. Med Care. 1988;26:724-35.
32. Spitzer RL, Williams JB, Kroenke K, et al. Utility of a new procedure for diagnosing mental disorders in primary care: the PRIME-MD 1000 study. JAMA 1994;272:1749-56.
33. Jackson JL, Kroenke K. Difficult patient encounters in the ambulatory clinic: clinical predictors and outcomes. Arch Intern Med 1999;159:1069-75.
34. Ormel J, Vonkorff M, Oldehinkel AJ, Simon G, Tiemens BG, Ustun TB. Onset of disability in depressed and non-depressed primary care patients. Psychol Med 1999;29:847-53.
35. Katon W. The effect of major depression on chronic medical illness. Semin Clin Neuropsychiatry 1998;3:82-86.
36. Pincus T, Callahan LF. What explains the association between socioeconomic status and health: primarily access to medical care or mind-body variables? Adv 1995;11:4-36.
37. Williams G, Frankel R, Campbell T, Deci E. Research on relationship-centered care and healthcare outcomes from the Rochester Biosychosocial Program: a self-determination theory integration. Fam Syst Health 2000;18:79-90.
38. Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist 2000;55:68-78.
39. Bloch DA, Doherty WJ. The Collaborative Family Healthcare Coalition. Fam Syst Health 1998;16:3-5.
40. Von Korff M, Gruman J, Schaefer J, Curry SJ, Wagner EH. Collaborative management of chronic illness. Ann Intern Med 1997;127:1097-102.
41. Stewart M, Brown JB, Boon H, Galajda J, Meredith L, Sangster M. Evidence on patient-doctor communication. Cancer Prev Control 1999;3:25-30.
42. Fisher L, Weihs KL. Can addressing family relationships improve outcomes in chronic disease? J Fam Pract 2000;49:561-66.
43. McDaniel S, Hepworth J, Doherty WJ. Medical family therapy: a biopsychosocial approach to families with health problems. New York, NY: Basic Books; 1992.
44. Rolland J. Families, illness and disability: an integrative treatment model. New York, NY: Basic Books; 1994.
45. Wagner EH, Austin BT, Von Korff M. Organizing care for patients with chronic illness. Milbank Q 1996;74:511-44.
46. Katon W, Von Korff M, Lin E, et al. Population-based care of depression: effective disease management strategies to decrease prevalence. Gen Hosp Psychiatry 1997;19:169-78.
47. Mauksch LB. Grand Junction reflections on collaborative care. Fam Syst Health 1999;17:437-46.
48. Kroenke K, Mangelsdorff AD. Common symptoms in ambulatory care: incidence, evaluation, therapy, and outcome. Am J Med 1989;86:262-66.
49. Goldman HH. The obligation of mental health services to the least well off. Psychiatr Serv 1999;50:659-63.
STUDY DESIGN: We compared a survey of consecutive primary care adults in April and May 1999 with a 1997-98 survey of 3000 general population primary care patients. Both studies used the Primary Care Evaluation of Mental Disorders Patient Health Questionnaire and the 20-question Medical Outcomes Study Short Form.
POPULATION: The patients were from a private nonprofit primary care clinic in Grand Junction, Colorado, that served only low-income uninsured people. We approached a total of 589 consecutive patients and enrolled 500 of them.
MAIN OUTCOME MEASURE: The main outcomes were the prevalence of psychiatric illnesses and the relationship with functional impairment. We compared our findings with a more generalizable primary care population.
RESULTS: This low-income uninsured population had a higher prevalence of 1 or more psychiatric disorders (51% vs 28%): mood disorders (33% vs 16%), anxiety disorders (36% vs 11%), probable alcohol abuse (17% vs 7%), and eating disorders (10% vs 7%). Having psychiatric disorders was associated with lower functional status and more disability days compared with not having mental illness. Patients indicated a preference for mental health providers and medical providers to communicate about their care.
CONCLUSIONS: This low-income uninsured primary care population has an extremely high prevalence of mental disorders with impaired function. It may be important in low-income primary care settings to include collaborative care designs to effectively treat common mental disorders, improve functional status, and enhance patient self-care.
Poverty is bad for a person’s health,1 diminishing physical, cognitive, and psychological2 well-being.3 Attempts to understand why persons with low socioeconomic status have poor health point to psychosocial and behavioral variables,4 such as smoking, bad dietary habits, exposure to trauma and violence, sedentary lifestyles, hopelessness, hostility, and depression.5 Mental illnesses6 (particularly depression7) cause more disability8 and diminished functional status than most physical illnesses.9 It is no surprise, therefore, that people with untreated mental illness use a disproportionate amount of health care resources.10 Thus, the more than 11 million11 people living in poverty who are uninsured are a particularly vulnerable sector of our society.12
In primary care settings the prevalence of mental illness13,14 and its relationship to functional status9 and health care use10 is well studied. However, we know little about these issues in indigent primary care populations. Miranda and colleagues15 studied 205 women at an urban, public sector, gynecology clinic and found that 48% had at least 1 psychiatric disorder. Olfson and coworkers16 studied an urban, older, low-income, mostly Hispanic, general medical population and found a high prevalence of depression, anxiety, substance use, and suicidal ideation associated with decreased function. A recent study by Woolf and colleagues17 found the functional status of inner city, indigent, primary care patients to be lower than the general population and lower than a national sample of patients with common chronic illnesses. We found no studies examining the prevalence of mental disorders and their relationship with functional status and health care use in low-income uninsured patients in primary care settings.
Family physicians18 and the Surgeon General19 have advocated for the integration of mental health into medical settings to improve care and reduce the stigmatization of mental illness. Models of collaboration20,21 between mental health and medical providers have been shown to be effective22-25 and cost-effective.26,27 Attending to patient preferences about therapeutic modality enhances the effectiveness of mental disorder treatments.28 However, we found no studies examining indigent patient preferences regarding the separation versus integration of medical and mental health services.
We predicted that an underprivileged, uninsured sample of primary care patients would have higher levels of mental illness and more impaired function than has been reported in general primary care samples. We also suspected that heath care utilization would be higher for indigent patients with more psychiatric symptoms compared with indigent primary care patients without psychiatric distress. Because policy,19 provider,18 and research23,25 recommendations endorse collaborative care designs, we wanted to initiate exploration of patient preferences for these service structures, since attending to patient wishes might enhance the effectiveness of future interventions.
Methods
Setting
We conducted our study at the Marillac Clinic in Grand Junction, Colorado. Marillac is a privately funded, nonprofit, primary care clinic serving Mesa County, Colorado (3313 square miles), with a population of 113,000 in 1999. Marillac serves only people without any form of health insurance (no Medicare or Medicaid) and with household incomes less than 150% of federal poverty guidelines. In 1998,14.5% of the Mesa County population lived below the poverty level, 16.6% lacked health insurance, 4.5% were unemployed, 90% were white, and 8% were Hispanic.29 The Human Subjects Review committee of St. Mary’s Hospital, Grand Junction, Colorado, approved our study.
Selection of Subjects
During April and early May 1999, all consecutive patients aged 18 years and older with clinic medical appointments were invited to participate in our study. One of 4 medical office assistants explained the study to each patient. The participants could allow or not allow study findings to be shared with their care providers after the clinic visit. Trained readers were available for those patients unable to read the survey. This service was used on 3 occasions. Participants received a $5 coupon to a local grocery store. Of the 589 patients approached, 68 refused and 21 were missed, for an enrollment of 500 patients (85%), representing 19% of the patients seen at the clinic in 1999. Of those refusing participation, 18 were not interested, 17 were too sick, 23 were too busy, and 10 cited other reasons. There were no significant differences in age or sex between the study participants and those who refused. The mean age for those who refused was 40 years (standard deviation [SD]=11.2) versus 38 years (SD=12.1) for study participants, (t(588)=1.88). Of those who refused 59% were women; 68% of the study participants were women (c2=2.42; df=1).
Data Collection
Patients. The patients completed a questionnaire before being seen by their health care providers. For patients who agreed, providers were alerted when survey results indicated the presence of 1 or more mental disorders.
Study Instrument. The study instruments included the recently validated Primary Care Evaluation of Mental Disorders (PRIME-MD) Patient Health Questionnaire (PHQ)30; the 20-item Medical Outcomes Study Short Form (SF-20), a validated31 tool to assess functional status; and other questions described below. The PRIME-MD PHQ is a self-report version of the original PRIME-MD32 that allows researchers to assess the presence of 7 psychiatric disorders. Like the original PRIME-MD, the PHQ assessed threshold disorders (major depression, panic disorder, other anxiety disorder, bulimia) and subthreshold disorders (minor depression, binge-eating disorder, probable alcohol abuse, somatoform disorder). Because providers were blind to patient response, diagnosis of somatoform disorder was not included. Some patients were classified as symptom screen positive because they indicated distress but failed to meet criteria for a subthreshold or a threshold diagnosis. Patients who screened positive reported depressed mood or low interest on more than half the days, a panic attack in the previous 4 weeks, feeling nervous more than half the days, often feeling “you cannot control what or how much you eat,” or being “bothered a lot” by more than 6 of the 13 PHQ physical symptoms. The SF-20 measures functional status in 6 dimensions. We defined the term “disability days” as the number of days in the past 3 months patients were kept from usual activities because of not feeling well. Health care use was defined by the number of separate times during the past 3 months that patients went to a medical physician in an office, clinic, or emergency room because of not feeling well, not counting the present visit.
Other questions added to the questionnaire included a 20-item list of current physical illnesses (medical comorbidity)24 and demographic questions. A question to assess patient preferences for service design asked: “In the future, if you desire mental health care, please check your top 2 preferred designs:” (A) your medical provider and mental health provider work in the same setting and communicate with one another about your care; (B) communication between providers with service at separate settings; (C) providers do not communicate with service at the same setting; and (D) providers do not communicate, and service is provided at separate settings (alternatives B, C, and D are abbreviated).
Statistical Analyses
We examined descriptive data for the sample. To test the hypothesis that poor, uninsured primary care patients will have higher rates of mental illness compared with a general primary care sample, we compared prevalence data for psychiatric disorders in the study sample against a representative primary care PHQ sample of 3000 patients. Since the PHQ study is from a different population with different sociodemographic and medical characteristics and different sampling techniques, we could not directly compare its data with statistical tests to discern differences in the populations. To determine if there were more problems with functional status and disability days and higher health care use for patients with more psychiatric symptoms, we classified patients into 3 groups based on psychiatric diagnoses: symptom screen negative, screen positive/subthreshold, and threshold groups. Originally the screen-positive and subthreshold groups were analyzed separately. However, because of nearly identical means they were combined for subsequent analyses. Analyses of covariance were used to examine differences in functioning and disability days. The covariates we used were personal income and number of physical health problems. We performed a chi-square analysis to determine if the psychiatric patient groups differed in the proportion with 3 or more physician visits in the past 3 months.
Results
Prevalence of Psychiatric Diagnoses
Table 1 shows the study sample demographics. Table 2 presents a comparison of the prevalence of current disorders in the Marillac study with those in the PHQ 3000 study. The percentage of Marillac patients with at least 1 current psychiatric diagnosis is almost twice the prevalence of the PHQ study (51% vs 28%). Marillac patients had between 2 and 3 times as many of each of the current threshold diagnoses. The rates of each current subthreshold disorder are mildly higher than the PHQ study except for probable alcohol abuse, which is more than twice as high.
Functional Status, Disability Days, and Health Care Use
Figure 1 displays the adjusted means for the 6 scales of the SF-20 and shows that patients with one or more current threshold psychiatric disorders have significantly (P <.001) lower functional status on all SF-20 scales compared with the other 2 groups, which did not differ except for mental health. The percentage of patients in each of the 3 psychiatric symptom groups were: symptom screen negative, 31%; symptom screen positive/subthreshold diagnosis, 34%; and threshold diagnosis, 35%.
Screen-negative patients reported a mean (SD) of 4.3 (8.5) disability days; screen-positive/subthreshold patients reported 5.6 (12.2) days; and threshold diagnosis patients reported 18.9 (25.6) days. Controlling for physical comorbidity and personal income, patients with threshold psychiatric diagnoses had significantly more disability days than either of the 2 other groups, which did not differ from one another (F[2453]=30.20; P <.001). The 3 groups differed in number of physician visits in the previous 3 months. Controlling for physical comorbidity and personal income, percentages of patients within each diagnostic group with 3 or more physician visits were: screen negative, 15.7%; screen positive/subthreshold, 21.7%; and threshold, 34.5%. Patients in the threshold group were more likely to report 3 or more visits than patients in the other 2 groups (c2=16.27; df=2; P <.001). Differences between the screen-positive/subthreshold and the threshold group were also significant (c2=6.77; P <.009), but differences between screen-negative and screen-positive/subthreshold groups did not reach significance (c2=1.87; P <.17).
Patient Preferences for Medical and Mental Health Service Designs
Table 3 shows patient preferences. After choosing a first option patients were asked to make a second choice, which meant changing the location of service to maintain interprovider communication or eliminating communication to maintain service at a preferred location. Of the 284 patients who marked 2 votes, 246 (87%) chose the 2 options for providers to communicate with one another. The proportion of votes for the 2 communication options within each of the symptom groups was: threshold, 91%, subthreshold/screen positive, 86%, and screen negative, 90%.
Discussion
Using an instrument recently validated across 3000 primary care patients (the PRIME-MD PHQ) we found the proportion of the patients in this clinic with current major mental illnesses to be roughly twice the number in the general population (35% vs 15%). Overall, a larger proportion of patients in the Marillac population report some current psychiatric distress compared with the sample from Spitzer and coworkers30 (51% vs 28%). Because the PHQ does not diagnose dysthymia, non-alcohol–related substance abuse, or other chronic mental illnesses such as bipolar disorder, these findings represent a conservative view of the prevalence of mental illness and addictive disorders in this sample. Also, because primary care providers did not evaluate whether physical symptoms were secondary to a medical illness, somatoform disorders were not diagnosed.
Consistent with other studies9,33 patients with threshold disorders report significantly lower functional status compared with patients with subthreshold diagnoses or who are screen positive for psychiatric distress or without any psychiatric symptoms. However, these other studies have found a gradient of functional status inversely proportional to the degree of psychiatric impairment that was absent in the Marillac sample. The mean scores for Marillac symptom screen-negative patients are 7 to 15 points lower than the PHQ 3000 symptom screen-negative patients across all 6 SF-20 scales. These findings are consistent with findings reported by Woolf and colleagues17 who found mean scores on all the functional status indices for low-income patients to be significantly lower than their overall population means. It is unclear whether these findings are because of more severe mental disorders, a higher prevalence of physical disorders, or other characteristics of low-income populations.
Consistent with other studies,10,30 patients at Marillac with higher levels of psychiatric symptoms report increasing numbers of disability days and physician visits. Comparing disability days in PHQ 3000 patients in the threshold diagnosis (17), subthreshold (6.6), and screen-positive (4.8) groups shows similar numbers to our sample. However, the number of disability days for the Marillac patients without any psychiatric symptoms is almost twice as high as that in the PHQ 3000 sample (2.4) and consistent with the lower levels of functional status in the Marillac screen-negative group.
Although the prevalence of virtually all biomedical, psychosocial, and psychiatric illnesses is greater in the underprivileged, special attention needs to be paid to addressing cognitive, psychosocial, and psychiatric issues. The high prevalence of mental disorders may lead to chronic disability,34 perpetuating poverty. Mental illness complicates the management of chronic medical illness and increases risks for illness and death.35 Diminished sense of control of life compromises self-care36,37 and well-being.38
The majority (90%) of Marillac patients preferred their medical providers and mental health providers to communicate with one another about their health care. These patient preferences combined with research supporting the use of collaborative designs represented a compelling argument for system redesign. The findings of this study helped secure 4 years of funding from the Robert Wood Johnson 2000 Local Initiative Funding Partners Program to match funding from local contributors lead by the Colorado Trust. These funds will pay for on-site counselors, case managers, psychiatric and substance abuse assessments, group treatments, and ongoing training to create stronger linkages with a variety of community agencies (The Mesa County Coalition on Health). Marillac has adopted Collaborative Family Health Care,39 a model emphasizing teamwork between biomedical, nursing, and psychosocial providers, and that views the patient40,41 and family42-44 as crucial in treatment design and implementation. System adjustments emphasized the management of chronic illness45 with a focus on the psychosocial needs of this population.46 More details of these changes are described elsewhere.47
Limitations
The major limitation of our study may be lack of generalizability to other indigent primary care populations. More studies are needed that examine the prevalence of mental illnesses and relationships with functional status and disability in poor, urban populations with and without health insurance. Most subjects in our study are white and speak English. The prevalence and nature of mental disorders among urban diverse primary care patients may differ from the profiles we have described. In our study the method used to assess medical comorbidity relied on patient report. Patients may have under-reported or over-reported physical illness. Some symptoms reported on the PHQ could be caused by medical illnesses, and many may be medically unexplained.48 In the PHQ study, mental health professionals interviewed patients to validate survey findings. We assume that responses from this low-income population are valid, but future studies may want to further validate the PHQ in indigent samples. Our data probably underestimate overall prevalence of mental disorders in Marillac patients, because the number of disorders detected by the PHQ is limited. The Marillac population was younger (18-64 years) than the PHQ-3000 sample (19-99 years). An older population may have a different prevalence of mental disorders, levels of functional status, and service use. The relationships among these variables may also be different.
Conclusions
We found an indigent uninsured primary care adult population to have an extremely high prevalence of current mental disorders. Also, in addition to the expected decrease in functional status for those with severe mental disorders, the functional status of the entire clinic population was quite low. A sizable portion of the literature suggests that much of this diminished health-related quality of life might be the expression of an impoverished existence. Beyond financial poverty and limited education, the chronically poor person suffers from a higher prevalence of mental illness and a limited sense of being able to control the future. Patient preferences support provider and policy recommendations for the integration of mental health and primary care services. These health care designs may increase our potential to improve the health of those with the greatest need.49
Acknowledgments
Between August 1998 and July 1999 Mr Mauksch was on leave from the University of Washington Department of Family Medicine as a consultant in collaborative care to the Marillac Clinic. Funding for his position came from the Brownson Memorial Fund, the Victim/Witness Assistance and Law Enforcement Fund—21st Judicial District of Colorado, the Sisters of Charity, and St. Mary’s Hospital.
We wish to thank the Marillac Clinic medical assistants, administrative staff, community volunteers, and clinicians who contributed to this study in many essential ways. Because no additional financial support was used to fund this study, the role of the entire clinic community was critical for its successful completion.
The authors thank Jurgen Unützer, MD, for help in selecting an instrument to measure medical comorbidity.
Related Resources:
- The Collaborative Family HealthCare Coalition www.cfhcc.org
- The Institute for Healthcare Improvement-Information on “Improving Care for People with Chronic Conditions,” a national congress with a focus on asthma and depression www.ihi.org
- Anxiety Disorders Association of America www.adaa.org
- National Depressive and Manic Depressive Association www.ndmda.org
STUDY DESIGN: We compared a survey of consecutive primary care adults in April and May 1999 with a 1997-98 survey of 3000 general population primary care patients. Both studies used the Primary Care Evaluation of Mental Disorders Patient Health Questionnaire and the 20-question Medical Outcomes Study Short Form.
POPULATION: The patients were from a private nonprofit primary care clinic in Grand Junction, Colorado, that served only low-income uninsured people. We approached a total of 589 consecutive patients and enrolled 500 of them.
MAIN OUTCOME MEASURE: The main outcomes were the prevalence of psychiatric illnesses and the relationship with functional impairment. We compared our findings with a more generalizable primary care population.
RESULTS: This low-income uninsured population had a higher prevalence of 1 or more psychiatric disorders (51% vs 28%): mood disorders (33% vs 16%), anxiety disorders (36% vs 11%), probable alcohol abuse (17% vs 7%), and eating disorders (10% vs 7%). Having psychiatric disorders was associated with lower functional status and more disability days compared with not having mental illness. Patients indicated a preference for mental health providers and medical providers to communicate about their care.
CONCLUSIONS: This low-income uninsured primary care population has an extremely high prevalence of mental disorders with impaired function. It may be important in low-income primary care settings to include collaborative care designs to effectively treat common mental disorders, improve functional status, and enhance patient self-care.
Poverty is bad for a person’s health,1 diminishing physical, cognitive, and psychological2 well-being.3 Attempts to understand why persons with low socioeconomic status have poor health point to psychosocial and behavioral variables,4 such as smoking, bad dietary habits, exposure to trauma and violence, sedentary lifestyles, hopelessness, hostility, and depression.5 Mental illnesses6 (particularly depression7) cause more disability8 and diminished functional status than most physical illnesses.9 It is no surprise, therefore, that people with untreated mental illness use a disproportionate amount of health care resources.10 Thus, the more than 11 million11 people living in poverty who are uninsured are a particularly vulnerable sector of our society.12
In primary care settings the prevalence of mental illness13,14 and its relationship to functional status9 and health care use10 is well studied. However, we know little about these issues in indigent primary care populations. Miranda and colleagues15 studied 205 women at an urban, public sector, gynecology clinic and found that 48% had at least 1 psychiatric disorder. Olfson and coworkers16 studied an urban, older, low-income, mostly Hispanic, general medical population and found a high prevalence of depression, anxiety, substance use, and suicidal ideation associated with decreased function. A recent study by Woolf and colleagues17 found the functional status of inner city, indigent, primary care patients to be lower than the general population and lower than a national sample of patients with common chronic illnesses. We found no studies examining the prevalence of mental disorders and their relationship with functional status and health care use in low-income uninsured patients in primary care settings.
Family physicians18 and the Surgeon General19 have advocated for the integration of mental health into medical settings to improve care and reduce the stigmatization of mental illness. Models of collaboration20,21 between mental health and medical providers have been shown to be effective22-25 and cost-effective.26,27 Attending to patient preferences about therapeutic modality enhances the effectiveness of mental disorder treatments.28 However, we found no studies examining indigent patient preferences regarding the separation versus integration of medical and mental health services.
We predicted that an underprivileged, uninsured sample of primary care patients would have higher levels of mental illness and more impaired function than has been reported in general primary care samples. We also suspected that heath care utilization would be higher for indigent patients with more psychiatric symptoms compared with indigent primary care patients without psychiatric distress. Because policy,19 provider,18 and research23,25 recommendations endorse collaborative care designs, we wanted to initiate exploration of patient preferences for these service structures, since attending to patient wishes might enhance the effectiveness of future interventions.
Methods
Setting
We conducted our study at the Marillac Clinic in Grand Junction, Colorado. Marillac is a privately funded, nonprofit, primary care clinic serving Mesa County, Colorado (3313 square miles), with a population of 113,000 in 1999. Marillac serves only people without any form of health insurance (no Medicare or Medicaid) and with household incomes less than 150% of federal poverty guidelines. In 1998,14.5% of the Mesa County population lived below the poverty level, 16.6% lacked health insurance, 4.5% were unemployed, 90% were white, and 8% were Hispanic.29 The Human Subjects Review committee of St. Mary’s Hospital, Grand Junction, Colorado, approved our study.
Selection of Subjects
During April and early May 1999, all consecutive patients aged 18 years and older with clinic medical appointments were invited to participate in our study. One of 4 medical office assistants explained the study to each patient. The participants could allow or not allow study findings to be shared with their care providers after the clinic visit. Trained readers were available for those patients unable to read the survey. This service was used on 3 occasions. Participants received a $5 coupon to a local grocery store. Of the 589 patients approached, 68 refused and 21 were missed, for an enrollment of 500 patients (85%), representing 19% of the patients seen at the clinic in 1999. Of those refusing participation, 18 were not interested, 17 were too sick, 23 were too busy, and 10 cited other reasons. There were no significant differences in age or sex between the study participants and those who refused. The mean age for those who refused was 40 years (standard deviation [SD]=11.2) versus 38 years (SD=12.1) for study participants, (t(588)=1.88). Of those who refused 59% were women; 68% of the study participants were women (c2=2.42; df=1).
Data Collection
Patients. The patients completed a questionnaire before being seen by their health care providers. For patients who agreed, providers were alerted when survey results indicated the presence of 1 or more mental disorders.
Study Instrument. The study instruments included the recently validated Primary Care Evaluation of Mental Disorders (PRIME-MD) Patient Health Questionnaire (PHQ)30; the 20-item Medical Outcomes Study Short Form (SF-20), a validated31 tool to assess functional status; and other questions described below. The PRIME-MD PHQ is a self-report version of the original PRIME-MD32 that allows researchers to assess the presence of 7 psychiatric disorders. Like the original PRIME-MD, the PHQ assessed threshold disorders (major depression, panic disorder, other anxiety disorder, bulimia) and subthreshold disorders (minor depression, binge-eating disorder, probable alcohol abuse, somatoform disorder). Because providers were blind to patient response, diagnosis of somatoform disorder was not included. Some patients were classified as symptom screen positive because they indicated distress but failed to meet criteria for a subthreshold or a threshold diagnosis. Patients who screened positive reported depressed mood or low interest on more than half the days, a panic attack in the previous 4 weeks, feeling nervous more than half the days, often feeling “you cannot control what or how much you eat,” or being “bothered a lot” by more than 6 of the 13 PHQ physical symptoms. The SF-20 measures functional status in 6 dimensions. We defined the term “disability days” as the number of days in the past 3 months patients were kept from usual activities because of not feeling well. Health care use was defined by the number of separate times during the past 3 months that patients went to a medical physician in an office, clinic, or emergency room because of not feeling well, not counting the present visit.
Other questions added to the questionnaire included a 20-item list of current physical illnesses (medical comorbidity)24 and demographic questions. A question to assess patient preferences for service design asked: “In the future, if you desire mental health care, please check your top 2 preferred designs:” (A) your medical provider and mental health provider work in the same setting and communicate with one another about your care; (B) communication between providers with service at separate settings; (C) providers do not communicate with service at the same setting; and (D) providers do not communicate, and service is provided at separate settings (alternatives B, C, and D are abbreviated).
Statistical Analyses
We examined descriptive data for the sample. To test the hypothesis that poor, uninsured primary care patients will have higher rates of mental illness compared with a general primary care sample, we compared prevalence data for psychiatric disorders in the study sample against a representative primary care PHQ sample of 3000 patients. Since the PHQ study is from a different population with different sociodemographic and medical characteristics and different sampling techniques, we could not directly compare its data with statistical tests to discern differences in the populations. To determine if there were more problems with functional status and disability days and higher health care use for patients with more psychiatric symptoms, we classified patients into 3 groups based on psychiatric diagnoses: symptom screen negative, screen positive/subthreshold, and threshold groups. Originally the screen-positive and subthreshold groups were analyzed separately. However, because of nearly identical means they were combined for subsequent analyses. Analyses of covariance were used to examine differences in functioning and disability days. The covariates we used were personal income and number of physical health problems. We performed a chi-square analysis to determine if the psychiatric patient groups differed in the proportion with 3 or more physician visits in the past 3 months.
Results
Prevalence of Psychiatric Diagnoses
Table 1 shows the study sample demographics. Table 2 presents a comparison of the prevalence of current disorders in the Marillac study with those in the PHQ 3000 study. The percentage of Marillac patients with at least 1 current psychiatric diagnosis is almost twice the prevalence of the PHQ study (51% vs 28%). Marillac patients had between 2 and 3 times as many of each of the current threshold diagnoses. The rates of each current subthreshold disorder are mildly higher than the PHQ study except for probable alcohol abuse, which is more than twice as high.
Functional Status, Disability Days, and Health Care Use
Figure 1 displays the adjusted means for the 6 scales of the SF-20 and shows that patients with one or more current threshold psychiatric disorders have significantly (P <.001) lower functional status on all SF-20 scales compared with the other 2 groups, which did not differ except for mental health. The percentage of patients in each of the 3 psychiatric symptom groups were: symptom screen negative, 31%; symptom screen positive/subthreshold diagnosis, 34%; and threshold diagnosis, 35%.
Screen-negative patients reported a mean (SD) of 4.3 (8.5) disability days; screen-positive/subthreshold patients reported 5.6 (12.2) days; and threshold diagnosis patients reported 18.9 (25.6) days. Controlling for physical comorbidity and personal income, patients with threshold psychiatric diagnoses had significantly more disability days than either of the 2 other groups, which did not differ from one another (F[2453]=30.20; P <.001). The 3 groups differed in number of physician visits in the previous 3 months. Controlling for physical comorbidity and personal income, percentages of patients within each diagnostic group with 3 or more physician visits were: screen negative, 15.7%; screen positive/subthreshold, 21.7%; and threshold, 34.5%. Patients in the threshold group were more likely to report 3 or more visits than patients in the other 2 groups (c2=16.27; df=2; P <.001). Differences between the screen-positive/subthreshold and the threshold group were also significant (c2=6.77; P <.009), but differences between screen-negative and screen-positive/subthreshold groups did not reach significance (c2=1.87; P <.17).
Patient Preferences for Medical and Mental Health Service Designs
Table 3 shows patient preferences. After choosing a first option patients were asked to make a second choice, which meant changing the location of service to maintain interprovider communication or eliminating communication to maintain service at a preferred location. Of the 284 patients who marked 2 votes, 246 (87%) chose the 2 options for providers to communicate with one another. The proportion of votes for the 2 communication options within each of the symptom groups was: threshold, 91%, subthreshold/screen positive, 86%, and screen negative, 90%.
Discussion
Using an instrument recently validated across 3000 primary care patients (the PRIME-MD PHQ) we found the proportion of the patients in this clinic with current major mental illnesses to be roughly twice the number in the general population (35% vs 15%). Overall, a larger proportion of patients in the Marillac population report some current psychiatric distress compared with the sample from Spitzer and coworkers30 (51% vs 28%). Because the PHQ does not diagnose dysthymia, non-alcohol–related substance abuse, or other chronic mental illnesses such as bipolar disorder, these findings represent a conservative view of the prevalence of mental illness and addictive disorders in this sample. Also, because primary care providers did not evaluate whether physical symptoms were secondary to a medical illness, somatoform disorders were not diagnosed.
Consistent with other studies9,33 patients with threshold disorders report significantly lower functional status compared with patients with subthreshold diagnoses or who are screen positive for psychiatric distress or without any psychiatric symptoms. However, these other studies have found a gradient of functional status inversely proportional to the degree of psychiatric impairment that was absent in the Marillac sample. The mean scores for Marillac symptom screen-negative patients are 7 to 15 points lower than the PHQ 3000 symptom screen-negative patients across all 6 SF-20 scales. These findings are consistent with findings reported by Woolf and colleagues17 who found mean scores on all the functional status indices for low-income patients to be significantly lower than their overall population means. It is unclear whether these findings are because of more severe mental disorders, a higher prevalence of physical disorders, or other characteristics of low-income populations.
Consistent with other studies,10,30 patients at Marillac with higher levels of psychiatric symptoms report increasing numbers of disability days and physician visits. Comparing disability days in PHQ 3000 patients in the threshold diagnosis (17), subthreshold (6.6), and screen-positive (4.8) groups shows similar numbers to our sample. However, the number of disability days for the Marillac patients without any psychiatric symptoms is almost twice as high as that in the PHQ 3000 sample (2.4) and consistent with the lower levels of functional status in the Marillac screen-negative group.
Although the prevalence of virtually all biomedical, psychosocial, and psychiatric illnesses is greater in the underprivileged, special attention needs to be paid to addressing cognitive, psychosocial, and psychiatric issues. The high prevalence of mental disorders may lead to chronic disability,34 perpetuating poverty. Mental illness complicates the management of chronic medical illness and increases risks for illness and death.35 Diminished sense of control of life compromises self-care36,37 and well-being.38
The majority (90%) of Marillac patients preferred their medical providers and mental health providers to communicate with one another about their health care. These patient preferences combined with research supporting the use of collaborative designs represented a compelling argument for system redesign. The findings of this study helped secure 4 years of funding from the Robert Wood Johnson 2000 Local Initiative Funding Partners Program to match funding from local contributors lead by the Colorado Trust. These funds will pay for on-site counselors, case managers, psychiatric and substance abuse assessments, group treatments, and ongoing training to create stronger linkages with a variety of community agencies (The Mesa County Coalition on Health). Marillac has adopted Collaborative Family Health Care,39 a model emphasizing teamwork between biomedical, nursing, and psychosocial providers, and that views the patient40,41 and family42-44 as crucial in treatment design and implementation. System adjustments emphasized the management of chronic illness45 with a focus on the psychosocial needs of this population.46 More details of these changes are described elsewhere.47
Limitations
The major limitation of our study may be lack of generalizability to other indigent primary care populations. More studies are needed that examine the prevalence of mental illnesses and relationships with functional status and disability in poor, urban populations with and without health insurance. Most subjects in our study are white and speak English. The prevalence and nature of mental disorders among urban diverse primary care patients may differ from the profiles we have described. In our study the method used to assess medical comorbidity relied on patient report. Patients may have under-reported or over-reported physical illness. Some symptoms reported on the PHQ could be caused by medical illnesses, and many may be medically unexplained.48 In the PHQ study, mental health professionals interviewed patients to validate survey findings. We assume that responses from this low-income population are valid, but future studies may want to further validate the PHQ in indigent samples. Our data probably underestimate overall prevalence of mental disorders in Marillac patients, because the number of disorders detected by the PHQ is limited. The Marillac population was younger (18-64 years) than the PHQ-3000 sample (19-99 years). An older population may have a different prevalence of mental disorders, levels of functional status, and service use. The relationships among these variables may also be different.
Conclusions
We found an indigent uninsured primary care adult population to have an extremely high prevalence of current mental disorders. Also, in addition to the expected decrease in functional status for those with severe mental disorders, the functional status of the entire clinic population was quite low. A sizable portion of the literature suggests that much of this diminished health-related quality of life might be the expression of an impoverished existence. Beyond financial poverty and limited education, the chronically poor person suffers from a higher prevalence of mental illness and a limited sense of being able to control the future. Patient preferences support provider and policy recommendations for the integration of mental health and primary care services. These health care designs may increase our potential to improve the health of those with the greatest need.49
Acknowledgments
Between August 1998 and July 1999 Mr Mauksch was on leave from the University of Washington Department of Family Medicine as a consultant in collaborative care to the Marillac Clinic. Funding for his position came from the Brownson Memorial Fund, the Victim/Witness Assistance and Law Enforcement Fund—21st Judicial District of Colorado, the Sisters of Charity, and St. Mary’s Hospital.
We wish to thank the Marillac Clinic medical assistants, administrative staff, community volunteers, and clinicians who contributed to this study in many essential ways. Because no additional financial support was used to fund this study, the role of the entire clinic community was critical for its successful completion.
The authors thank Jurgen Unützer, MD, for help in selecting an instrument to measure medical comorbidity.
Related Resources:
- The Collaborative Family HealthCare Coalition www.cfhcc.org
- The Institute for Healthcare Improvement-Information on “Improving Care for People with Chronic Conditions,” a national congress with a focus on asthma and depression www.ihi.org
- Anxiety Disorders Association of America www.adaa.org
- National Depressive and Manic Depressive Association www.ndmda.org
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2. Bruce ML, Takeuchi DT, Leaf PJ. Poverty and psychiatric status: longitudinal evidence from the New Haven Epidemiologic Catchment Area study. Arch Gen Psychiatry 1991;48:470-74.
3. Lynch JW, Kaplan GA, Shema SJ. Cumulative impact of sustained economic hardship on physical, cognitive, psychological, and social functioning. N Engl J Med 1997;337:1889-95.
4. Stronks K, van de Mheen HD, Mackenbach JP. A higher prevalence of health problems in low income groups: does it reflect relative deprivation? J Epidemiol Community Health. 1998;52:548-57.
5. Lynch JW, Kaplan GA, Salonen JT. Why do poor people behave poorly? Variation in adult health behaviours and psychosocial characteristics by stages of the socioeconomic lifecourse. Soc Sci Med 1997;44:809-19.
6. Norquist G, Hyman SE. Advances in understanding and treating mental illness: implications for policy. Health Aff 1999;18:32-47.
7. Hays RD, Wells KB, Sherbourne CD, Rogers W, Spritzer K. Functioning and well-being outcomes of patients with depression compared with chronic general medical illnesses. Arch Gen Psychiatry 1995;52:11-19.
8. Ormel J, VonKorff M, Ustun TB, Pini S, Korten A, Oldehinkel T. Common mental disorders and disability across cultures: results from the WHO Collaborative Study on Psychological Problems in General Health Care. JAMA 1994;272:1741-48.
9. Spitzer RL, Kroenke K, Linzer M, et al. Health-related quality of life in primary care patients with mental disorders: results from the PRIME-MD 1000 Study. JAMA 1995;274:1511-17.
10. Katon W, Von Korff M, Lin E, et al. Distressed high utilizers of medical care: DSM-III-R diagnoses and treatment needs. Gen Hosp Psychiatry 1990;12:355-62.
11. United States Census Bureau Health insurance coverage. Vol 1999. Washington, DC: US Census Bureau; 1998.
12. Andrulis DP. Access to care is the centerpiece in the elimination of socioeconomic disparities in health. Ann Intern Med 1998;129:412-16.
13. Regier DA, Goldberg ID, Taube CA. The de facto US mental health services system: a public health perspective. Arch Gen Psychiatry 1978;35:685-93.
14. Regier DA, Narrow WE, Rae DS, Manderscheid RW, Locke BZ, Goodwin FK. The de facto US mental and addictive disorders service system: epidemiologic catchment area prospective 1-year prevalence rates of disorders and services. Arch Gen Psychiatry 1993;50:85-94.
15. Miranda J, Azocar F, Komaromy M, Golding JM. Unmet mental health needs of women in public-sector gynecologic clinics. Am J Obstet Gynecol 1998;178:212-17.
16. Olfson M, Shea S, Feder A, et al. Prevalence of anxiety, depression and substance use disorders in an urban general medicine practice. Arch Fam Med 2000;9:876-83.
17. Woolf SH, Rothemich SF, Johnson RE, Marsland DW. The functional status of inner-city primary care patients: diminished function in a family practice population and its potential determinants. J Fam Pract 1998;47:312-15.
18. American Academy of Family Physicians. White paper on the provision of mental health services by family physicians. Kansas City, Kan: AAFP Commission on Health Care Services, 1994.
19. Surgeon General Mental health: a report of the Surgeon General. Washington, DC: Department of Health and Human Services; 1999.
20. Seaburn DB, Gawanski BA, Gunn WB, Lorenz A, Mauksch L. Models of collaboration: a guide for mental health professionals and health care practitioners. New York, NY: Basic Books; 1996.
21. Blount A, ed. Integrated primary care: the future of medical and mental health collaboration. New York, NY: W.W. Norton; 1998.
22. Katon W, Von Korff M, Lin E, et al. Collaborative management to achieve depression treatment guidelines. J Clin Psychiatry 1997;58:20-23.
23. Rubenstein LV, Jackson-Triche M, Unutzer J, et al. Evidence-based care for depression in managed primary care practices. Health Aff 1999;18:89-105.
24. Wells KB, Sherbourne C, Schoenbaum M, et al. Impact of disseminating quality improvement programs for depression in managed primary care: a randomized controlled trial. JAMA 2000;283:212-20.
25. Hemmings A. A systematic review of brief psychological therapies in primary health care. Fam Syst Health 2000;18:279-314.
26. Von Korff M, Katon W, Bush T, et al. Treatment costs, cost offset, and cost-effectiveness of collaborative management of depression. Psychosom Med 1998;60:143-49.
27. Olfson M, Sing M, Schlesinger HJ. Mental health/medical care cost offsets: opportunities for managed care. Health Aff 1999;18:79-90.
28. Mauksch L. An evidenced based recipe for primary care, psychotherapy and patient p. Fam Syst Health 2000;18:315-22.
29. Mesa County: our picture of health. Grand Junction, Colo: Civic Forum; 1998.
30. Spitzer RL, Kroenke K, Williams JB. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study: Primary Care Evaluation of Mental Disorders Patient Health Questionnaire. JAMA 1999;282:1737-44.
31. Stewart AL, Hays RD, Ware JE, Jr. The MOS short-form general health survey. Reliability and validity in a patient population. Med Care. 1988;26:724-35.
32. Spitzer RL, Williams JB, Kroenke K, et al. Utility of a new procedure for diagnosing mental disorders in primary care: the PRIME-MD 1000 study. JAMA 1994;272:1749-56.
33. Jackson JL, Kroenke K. Difficult patient encounters in the ambulatory clinic: clinical predictors and outcomes. Arch Intern Med 1999;159:1069-75.
34. Ormel J, Vonkorff M, Oldehinkel AJ, Simon G, Tiemens BG, Ustun TB. Onset of disability in depressed and non-depressed primary care patients. Psychol Med 1999;29:847-53.
35. Katon W. The effect of major depression on chronic medical illness. Semin Clin Neuropsychiatry 1998;3:82-86.
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35. Katon W. The effect of major depression on chronic medical illness. Semin Clin Neuropsychiatry 1998;3:82-86.
36. Pincus T, Callahan LF. What explains the association between socioeconomic status and health: primarily access to medical care or mind-body variables? Adv 1995;11:4-36.
37. Williams G, Frankel R, Campbell T, Deci E. Research on relationship-centered care and healthcare outcomes from the Rochester Biosychosocial Program: a self-determination theory integration. Fam Syst Health 2000;18:79-90.
38. Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist 2000;55:68-78.
39. Bloch DA, Doherty WJ. The Collaborative Family Healthcare Coalition. Fam Syst Health 1998;16:3-5.
40. Von Korff M, Gruman J, Schaefer J, Curry SJ, Wagner EH. Collaborative management of chronic illness. Ann Intern Med 1997;127:1097-102.
41. Stewart M, Brown JB, Boon H, Galajda J, Meredith L, Sangster M. Evidence on patient-doctor communication. Cancer Prev Control 1999;3:25-30.
42. Fisher L, Weihs KL. Can addressing family relationships improve outcomes in chronic disease? J Fam Pract 2000;49:561-66.
43. McDaniel S, Hepworth J, Doherty WJ. Medical family therapy: a biopsychosocial approach to families with health problems. New York, NY: Basic Books; 1992.
44. Rolland J. Families, illness and disability: an integrative treatment model. New York, NY: Basic Books; 1994.
45. Wagner EH, Austin BT, Von Korff M. Organizing care for patients with chronic illness. Milbank Q 1996;74:511-44.
46. Katon W, Von Korff M, Lin E, et al. Population-based care of depression: effective disease management strategies to decrease prevalence. Gen Hosp Psychiatry 1997;19:169-78.
47. Mauksch LB. Grand Junction reflections on collaborative care. Fam Syst Health 1999;17:437-46.
48. Kroenke K, Mangelsdorff AD. Common symptoms in ambulatory care: incidence, evaluation, therapy, and outcome. Am J Med 1989;86:262-66.
49. Goldman HH. The obligation of mental health services to the least well off. Psychiatr Serv 1999;50:659-63.