Mental Illness and Warfarin Use in Atrial Fibrillation

Objectives: To determine whether atrial fibrillation (AF) patients with mental health conditions (MHCs) were less likely than AF patients without MHCs to be prescribed warfarin and, if receiving warfarin, to maintain an International Normalized Ratio (INR) within the therapeutic range.

Study Design:

Detailed chart review of AF patients using a Veterans Health Administration (VHA) facility in 2003.

Methods:

For a random sample of 296 AF patients, records identified clinician-diagnosed MHCs (independent variable) and AF-related care in 2003 (dependent variables), receipt of warfarin, INR values below/above key thresholds, and time spent within the therapeutic range (2.0-3.0) or highly out of range. Differences between the MHC and comparison groups were examined using X² tests and logistic regression controlling for age and comorbidity.

Results:

Among warfarin-eligible AF patients (n = 246), 48.5% of those with MHCs versus 28.9% of those without MHCs were not treated with warfarin (P = .004). Among those receiving warfarin and monitored in VHA, highly supratherapeutic INRs were more common in the MHC group; for example, 27.3% versus 1.6% had any INR >5.0 (P <.001). Differences persisted after adjusting for age and comorbidity.

Conclusions:

MHC patients with AF were less likely than those without MHC to have adequate management of their AF care. Interventions directed at AF patients with MHC may help to optimize their outcomes.

(Am J Manag Care. 2011;17(9):617-624)

Mental illness decreased likelihood of warfarin receipt among patients without recorded contraindications, but clinicians did not list mental illness as a rationale for withholding warfarin.

• Among warfarin-treated patients, those with mental illness were more likely to have some International Normalized Ratio (INR) values substantially above the therapeutic range, but some with mental illness consistently maintained therapeutic INRs.

• Identifying subgroups with mental illness who can/cannot safely take warfarin would inform interventions and guidelines.

The Veterans Health Administration (VHA) National Mental Health Strategic Plan has recently called attention to optimizing treatment of coexisting medical conditions in patients with mental illness. Research is beginning to amass suggesting that patients with mental health conditions (MHCs), representing nearly one third of Americans,¹ may receive less intensive care for a range of conditions from diabetes to coronary artery disease to chronic pain.^2-7 However, the influence of mental illness on the management of atrial fibrillation (AF) is not yet well understood. This is important because AF is highly prevalent, especially among older adults, and is associated with increased stroke risk.^8,9 An oral anticoagulant, warfarin, reduces AF-related stroke risk from approximately 5% per year to 1% to 2% per year,^8,10 but also has downsides: it increases major bleeding risk, it typically involves a complex and rigorous dosing schedule, and it requires frequent blood monitoring of coagulation status (International Normalized Ratio [INR]). Given warfarin’s narrow therapeutic window, clinicians may have concerns about whether patients with MHC can safely take warfarin as prescribed and follow through with necessary monitoring tests.

Unfortunately, major AF practice guidelines do not currently address whether mental illness should influence anticoagulant therapy decision making.^11-13 This is concerning, since there are potential adverse consequences of prescribing warfarin for a patient who cannot use it safely: excess major bleeding if overdosed or thromboembolic events if underdosed. Likewise, there are potential adverse consequences of not prescribing warfarin for a patient who could take it safely, such as unnecessarily increased stroke risk.

Therefore, a detailed medical chart review methodology was used at 1 VHA facility to determine:

• Whether VHA AF patients with MHCs were less likely than those without MHCs to receive warfarin, even in the absence of contraindications.

• Whether, among those treated with warfarin and monitored in VHA, those with MHCs were more likely than those without MHCs to have INRs falling outside the standard therapeutic range.

METHODS

Subjects and Chart Abstraction Procedure

Patients were drawn from a national database of AF/atrial flutter cases developed for another ongoing study, where AF was identified by the presence of International Classification of Diseases, Ninth Revision (ICD-9) code 427.3x in fiscal year 2001-2002 VHA or Medicare outpatient or inpatient administrative data. Patients with AF/atrial flutter were included regardless of whether or not the arrhythmia was thought to be paroxysmal, and regardless of duration of the diagnosis (except for transient AF; see below). From the 2490 members of this database who received more than 50% of their VHA outpatient care in both 2002 and 2003 at a suburban, West Coast VHA facility, a random sample of 450 was selected for detailed chart review of electronic medical records. After refining the standardized abstraction protocol on 50 cases not included in the study, a trained senior medical student identified information on variables of interest and recorded them on a standardized abstraction form. Ongoing quality control occurred at weekly meetings of the research team to ensure consistency in coding.¹⁴ Administrative data supplemented chart data for some variables.

Excluded were 6 patients with inaccurate chart record identifiers, 33 patients who died prior to the end of 2003, 17 patients with transient AF (occurring only during an acute hospitalization, or within 30 days of cardiac surgery or cardiac catheterization), and 98 with no VHA chart evidence of AF based on data from available electrocardiograms, patient problem list, or outpatient provider diagnoses from progress notes. (Among this latter subgroup, 75 were identified as having AF by Medicare ICD-9 codes only; likely their AF was managed by a non-VHA provider, and thus the diagnosis did not appear in VHA files.) A total of 296 AF cases (full cohort) were thus included in the study. Of these, 51 patients had evidence of 1 or more potential contraindications to warfarin: history of nonadherence, hemorrhage, falls, dementia, advanced liver disease, or malignancy.¹⁵ Among the remaining 246 patients, all of whom were apparently eligible to receive warfarin (warfarin-eligible subcohort), 161 (65.4%) received warfarin within or outside of VHA. Among them, 84 received their INR monitoring in the VHA Anticoagulation Clinic and had reliable INR data available, such that warfarin effect could be assessed; they constituted the warfarin-treated-VHA-monitored subcohort. This study was approved by the Institutional Review Board at Stanford University, Stanford, California.

Variables

The primary independent variable was MHC. MHC was defined as (1) 1 or more provider diagnosis of substance use disorder, depressive disorder, anxiety disorder, psychotic disorder, dysfunctional personality disorder, or bipolar disorder (in progress notes or problem lists) during 2001-2003; or (2) receipt of psychopharmacologic agents including antidepressants, antipsychotics, or mood stabilizers (based on the VHA medication log or based on a progress note referring to a non-VHA prescription) during 2001-2003.

Dependent variables included (1) receipt of warfarin in 2003 (yes/no), based upon the chart medication log or a progress note referring to a warfarin prescription by a non-VHA provider; (2) presence of at least 1 subtherapeutic INR in 2003 (<1.5, <2.0) based on laboratory result file data; and (3) presence of at least 1 supratherapeutic INR in 2003 (>3.0, >3.5, >4.0, >4.5, >5.0). A standard procedure was used to calculate time in therapeutic range (ie, the percentage of days in 2003 during which the INR fell within the 2.0 to 3.0 range, linearly interpolating INR values for days on which an actual value was not available).¹⁶ Time highly out of therapeutic range was calculated as percentage of days in 2003 during which the INR was less than 1.5 or greater than 4.0.

Other variables included known stroke risk factors for AF patients¹⁷: age 75 years or older, congestive heart failure, hypertension, diabetes, and prior nonhemorrhagic stroke or transient ischemic attack, based on 2001-2002 VHA outpatient or inpatient administrative data. Comorbidity was identified from the medical component of the Comorbidity Index (a count of medical conditions common in veterans and used for ambulatory care case-mix adjustment), using VHA administrative data.^18,19 A count of primary care visits in 2003 came from clinic type codes in VHA administrative files. Patients were considered to have received only VHA care if they lacked any forms of outside insurance, based on the medical record, and if there was no mention of receipt of outside medical care or medications, based on primary care and cardiology clinic progress notes.

Analytic Approach

Among the full cohort, the warfarin-eligible subcohort, and the warfarin-treated-VHA-monitored subcohort, the following characteristics were examined for patients with and without MHC: demographics, stroke risk factors, Comorbidity Index, and utilization.

Among warfarin-eligible patients, the next analyses compared the proportions of those with and without MHC who were receiving warfarin, using a X² test. In this group, multivariable logistic regression was performed to examine receipt of warfarin as a function of the presence of MHC, first unadjusted, then controlling for age, and then controlling for age and Comorbidity Index.

Next, among warfarin-treated-VHA-monitored patients, proportions were sequentially compared for those with and without MHC who had at least 1 low INR (<2.0, <1.5) and for those with and without MHC who had at least 1 high INR (>3.0, >3.5, >4.0, >4.5, >5.0), using a X² test. Fisher’s exact test was used to calculate P values in instances of small cell size. Then logistic regression was used to examine high or low INR as a function of MHC, first unadjusted, then controlling for age, and then controlling for age and Comorbidity Index.

Among warfarin-treated-VHA-monitored patients, patients with and without MHC were compared with respect to mean time in therapeutic range and to mean time highly out of therapeutic range, using t tests.

Sensitivity analyses tested the stability of findings. Because of a concern that some VHA patients may receive their AF care from non-VHA providers, sensitivity analysis 1 examined the effect of restricting analyses to patients who used VHA as their exclusive source of care (ie, for whom all AF care could be reliably captured). Because of the possibility that some patients with a single recording of an AF diagnosis could have been miscoded as being an AF case, or could have had transient AF (despite efforts to exclude transient AF cases), sensitivity analysis 2 examined the effect of restricting analyses to patients who had at least 2 instances of an AF diagnosis from electrocardiograms or primary care/cardiology clinic notes.

RESULTS

Table 1

Among the full cohort (n = 296), 29.7% had at least 1 diagnosed MHC: substance abuse 7.8%, depression 18.9%, anxiety 15.2%, psychosis 3.0%, dysfunctional personality 1.0%, and mania 0.7%. Patients with MHC tended to be younger than those without MHC, yet tended to have greater medical comorbidity, including stroke risk factors (). Among the 17.2% of patients with a listed contraindication to warfarin, the most common contraindications cited were dementia (7.8%), history of falls (2.7%), and history of hemorrhage (3.7%). Of note, no records mentioned MHC as a contraindication to warfarin.

Figure

Table 2

In the warfarin-eligible subcohort, 48.5% of those with MHC versus 28.9% of those without MHC were not treated with warfarin (P = .004; ); even after adjustment for age and comorbidity, those with MHC were significantly less likely to receive warfarin (). The frequency of not being treated with warfarin varied by specific MHC, as follows: substance abuse 66.7%, depression 50.0%, anxiety 47.4%, psychosis 25.0%, and personality disorder 50.0%. Note that among the warfarin-eligible subcohort (n = 246), 19.7% of patients with MHC and 15.6% of patients without MHC had a CHADS2 (congestive heart failure, hypertension, age 75 years or older, diabetes mellitus, previous stroke or transient ischemic attack) score below 2, a level at which alternatives to warfarin may be appropriate.

Among the warfarin-treated-VHA-monitored subcohort (n = 84), patients with MHC were more likely than patients without MHC to have high INR values, both before and after adjustment for age. This would put them at increased risk for hemorrhage. There was a trend toward the same effect after additionally adjusting for Comorbidity Index. Differences between patients with versus without MHC were even more pronounced at higher INR thresholds. There was also a nonsignificant trend toward higher rates of subtherapeutic INR (<1.5) among patients with MHC.

Among the warfarin-treated-VHA-monitored subcohort, mean time spent in the 2.0 to 3.0 therapeutic range was lower for the MHC group than for the group without MHC: 56.8 (standard deviation [SD] 16.9) versus 65.9 (SD 18.2) percent of days (P = .04). Mean time spent highly out of range was higher for the MHC group than for the group without MHC: 9.0 (SD 9.8) versus 3.4 (SD 7.1) percent of days (P = .01).

Table 3

In sensitivity analysis 1 (restricting to patients who received all care in VHA), the magnitude and direction of unadjusted differences were similar to those in the main analyses. The same was true in sensitivity analysis 2, restricting to patients with 2 or more AF diagnoses ().

CONCLUSION

Warfarin-eligible AF patients with MHC were substantially less likely than those without MHC to receive warfarin, even after controlling for age and comorbidity. This is of potential concern, since stroke risk factors were greater in AF patients with MHC than in those without MHC. When prescribed warfarin, patients with MHC were substantially more likely than those without MHC to have INRs in the highly supratherapeutic range, with 27% having at least 1 INR value above 5.0. There was also a trend for them to have greater risk of having INRs in the highly subtherapeutic range. As a result, these patients could have increased risk of either thromboembolism (in the setting of low INR) or hemorrhage (in the setting of high INR).^20,21

The differences in warfarin receipt observed here are consistent with emerging literature documenting lower-intensity care provided to patients with MHC for a range of medical conditions,^{2,3,6,7,22,23} and could reflect several potential mechanisms. Patient preferences could be important,²⁴ but have not been well characterized with respect to MHC. Mental illness can influence physicians’ perceptions of patients,^25,26 and physician expectations of patients—founded or not&mdash;may affect management.²⁷ Alternatively, physicians’ threshold for concluding that falls, dementia, or nonadherence (known to affect prescribing behavior^28,29) should be counted as a warfarin contraindication may be lower for patients with MHCs. Mental illness may also affect communication between physician and patient, or may cause patients to be labeled as “difficult.”^8,25,30 While sample sizes were small for specific MHCs, this study did find preliminary evidence that warfarin receipt varied by specific MHC, and that rates were particularly low for patients with substance use disorders, suggesting that risky behaviors could factor into clinical decision making. Other possibilities are that providers may simply assume that patients will be nonadherent,²⁶ or may worry about drug interactions with psychiatric medications, some of which can increase bleeding risk.³¹ Patient and provider-level contributors to this effect merit more inquiry.

While these findings reflect care provided at a single site and thus will require replication, they raise several issues of serious clinical relevance. Findings shed light on actual physician behavior: in the absence of explicit national guidelines to shape their decisions, clinicians are prescribing warfarin substantially less often to AF patients with MHC than to AF patients without MHC. This suggests that the presence of MHC may be influencing their decisions, even though no physicians in this study listed the presence of MHC as the rationale for withholding warfarin. But is this concern warranted? In one sense, the answer is yes: patients with MHC were more likely to have supratherapeutic INR values, which may explain why another study (which focused on warfarin-treated Medicaid patients) found higher rates of bleeds in those with MHC than in those without MHC.³² In another sense, the answer is no: nearly 20% of patients with MHC were able to maintain an INR level below 3.0 throughout the full year of surveillance. Thus, for at least a subset of AF patients with MHC, it may be possible to administer warfarin safely. Perhaps, for example, different types of MHC have different effects upon patients’ ability to take warfarin safely. More work with larger samples is needed to help clinicians distinguish which patients with MHC are likely to have adverse effects, and which are likely to do well on warfarin.

Some have suggested that perhaps newer agents like dabigatran that do not require monitoring³³ may be better options for patients with MHC. This may be true: perhaps the simpler dosing regimen that dabigatran provides would facilitate adherence, which can be an issue for patients with MHC.³⁴ The reverse may also be true: perhaps patients with MHC do well in anticoagulation clinics that provide close, mandatory follow-up and that allow clinicians to monitor them. In contrast, medications like dabigatran, which lack an easy laboratory test for monitoring and currently lack a reversal agent for use if taken in overdose or with bleeding, may not offer this advantage. Further research will be needed to understand the pros and cons of dabigatran in patients with MHC.

This study was limited by possible underascertainment of medical care received (ie, non-VHA care), although the stability of findings in sensitivity analyses limited to patients who use VHA as their exclusive source of care was reassuring. This study did not distinguish between AF and atrial flutter, nor between continuous and paroxysmal AF. Also, it is unknown how many patients had ablation or surgical procedures for their AF; however, at the time, within the facility studied, ablation and appendage removal were not being offered and surgical procedures were very rare and limited. Contraindications to anticoagulation may also be underdocumented in medical records,³⁵ although from a medicolegal standpoint, clinicians have an incentive to document why they are withholding warfarin. Results may not be generalizable to women or other geographic or healthcare settings.

This study also has several strengths. The mixed-modality approach made it possible to take advantage of information available in administrative data, such as all INR values across an entire year of surveillance. Supplementing this source with medical record review data facilitated identification of factors difficult to elicit from administrative records, such as clinicians’ decision-making logic (eg, the reasons they did not start warfarin) and information about receipt of care outside of VHA (eg, evidence of receipt of care in general and receipt of warfarin in particular from non-VHA sources).

To optimize care for AF patients with MHC, clinicians may need to apply patient-centered approaches that take risk— benefit analyses into account.²⁴ However, the evidence base guiding such decisions is thin. While confirmatory studies in larger populations would be needed before modifying national guidelines about whether presence of MHC should influence candidacy for warfarin, study findings do suggest that, at a minimum, clinicians should monitor warfarin-treated patients with MHC particularly carefully, especially since patients with MHC were overrepresented in the group with very high INR values. Additional research is needed to understand why clinicians do not prescribe warfarin to some patients with MHC and to identify which subgroups of patients with MHC are or are not at particular risk of warfarin-related complications, so as to inform targeted interventions that address this potential quality gap.

Acknowledgments

The authors are grateful to Alex McMillan, PhD, at Stanford’s Spectrum program for his initial statistical consultations.

Author Affiliations: From Center for Health Care Evaluation (GAW, PAH, CSP, VYC, SKS, LA, SMF), VA Palo Alto Health Care System, Palo Alto, CA; Stanford University School of Medicine (GAW, PAH, CSP, SMF), Stanford, CA; Chronic Heart Failure QUERI (PAH), VA Palo Alto Health Care System, Palo Alto, CA; Health Economics Resource Center (CSP, SKS, LA), VA Palo Alto Health Care System, Palo Alto, CA; Division of Research (ASG), Kaiser Permanente of Northern California, Oakland; Departments of Epidemiology, Biostatistics, and Medicine (ASG), University of California, San Francisco.

Funding Source: This work was supported by a grant from VA Health Services Research & Development (IIR 04-248) and by the Stanford University Medical Scholars grant program. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the US government.

Author Disclosures: The authors (GAW, PAH, CSP, ASG, VYC, SKS, LA, SMF) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (GAW, PAH, CSP, ASG, SMF); acquisition of data (GAW, CSP, LA); analysis and interpretation of data (GAW, PAH, CSP, ASG, VYC, SKS, LA, SMF); drafting of the manuscript (GAW, SMF); critical revision of the manuscript for important intellectual content (GAW, PAH, CSP, ASG, VYC, LA, SMF); statistical analysis (GAW, CSP, SKS); provision of study materials or patients (GAW); obtaining funding (GAW, CSP, SMF); administrative, technical, or logistic support (GAW, VYC); and programming support (SKS).

Address correspondence to: Susan M. Frayne, MD, MPH, VA Palo Alto Health Care System, 795 Willow Rd (152-MPD), Menlo Park, CA 94025. E-mail: sfrayne@stanford.edu.

1. Kessler RC, McGonagle KA, Zhao S, et al. Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. Arch Gen Psychiatry. 1994;51(1):8-19.

2. Redelmeier DA, Tan SH, Booth GL. The treatment of unrelated disorders in patients with chronic medical diseases. N Engl J Med. 1998;338(21):1516-1520.

3. Druss BG, Bradford DW, Rosenheck RA, Radford MJ, Krumholz HM. Mental disorders and use of cardiovascular procedures after myocardial infarction. JAMA. 2000;283(4):506-511.

4. Graber MA, Bergus G, Dawson JD, Wood GB, Levy BT, Levin I. Effect of a patient’s psychiatric history on physicians’ estimation of probability of disease. J Gen Intern Med. 2000;15(3):204-206.

5. Petersen L, Normand S, Druss B, Rosenheck R. Process of care and outcome after acute myocardial infarction for patients with mental illness in the VA health care system: are there disparities? Health Serv Res. 2003;38(1, pt 1):41-63.

6. Desai MM, Rosenheck RA, Druss BG, Perlin JB. Mental disorders and quality of diabetes care in the Veterans Health Administration. Am J Psychiatry. 2002;159(9):1584-1590.

7. Frayne SM, Halanych JH, Miller DR, et al. Disparities in diabetes care: impact of mental illness. Arch Intern Med. 2005;165(22):2631-2638.

8. Feinberg WM, Blackshear JL, Laupacis A, Kronmal R, Hart RG. Prevalence, age distribution, and gender of patients with atrial fibrillation. Analysis and implications. Arch Intern Med. 1995;155(5):469-473.

9. Hill JD, Mottram EM, Killeen PD. Study of the prevalence of atrial fibrillation in general practice patients over 65 years of age. J R Coll Gen Pract. 1987;37(297):172-173.

10. Risk factors for stroke and efficacy of antithrombotic therapy in atrial fibrillation. Analysis of pooled data from five randomized controlled trials [published correction appears in Arch Intern Med. 1994;154(19):2254]. Arch Intern Med. 1994;154(13):1449-1457.

11. European Heart Rhythm Association; European Association for Cardio-Thoracic Surgery; Camm AJ, Kirchhof P, Lip GY, et al. Guidelines for the management of atrial fibrillation: the Task Force for the Management of Atrial Fibrillation of the European Society of Cardiology (ESC). Eur Heart J. 2010;31(19):2369-2429.

12. Fuster V, Rydén LE, Cannom DS, et al; American College of Cardiology/American Heart Association Task Force on Practice Guidelines; European Society of Cardiology Committee for Practice Guidelines; European Heart Rhythm Association; Heart Rhythm Society. ACC/AHA/ESC 2006 Guidelines for the Management of Patients with Atrial

Fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the European Society of Cardiology Committee for Practice Guidelines (Writing Committee to Revise the 2001 Guidelines for the Management of Patients With Atrial Fibrillation): developed in collaboration with the European Heart Rhythm Association and the Heart Rhythm Society. Circulation. 2006;114(7):e257-e354.

13. Wann LS, Curtis AB, January CT, et al. 2011 ACCF/AHA/HRS focused update on the management of patients with atrial fibrillation (updating the 2006 Guideline): a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Heart Rhythm. 2011;8(1):157-176.

14. Gilbert EH, Lowenstein SR, Koziol-McLain J, Barta DC, Steiner J. Chart reviews in emergency medicine research: where are the methods? Ann Emerg Med. 1996;27(3):305-308.

15. Beyth RJ, Quinn LM, Landefeld CS. Prospective evaluation of an index for predicting the risk of major bleeding in outpatients treated with warfarin. Am J Med. 1998;105(2):91-99.

16. Samsa GP, Matchar DB. Relationship between test frequency and outcomes of anticoagulation: a literature review and commentary with implications for the design of randomized trials of patient self-management. J Thromb Thrombolysis. 2000;9(3):283-292.

17. Gage BF, Waterman AD, Shannon W, Boechler M, Rich MW, Radford MJ. Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation. JAMA. 2001;285(22):2864-2870.

18. Selim AJ, Fincke G, Ren XS, et al. Comorbidity assessments based on patient report: results from the Veterans Health Study. J Ambul Care Manage. 2004;27(3):281-295.

19. Selim A, Fincke G, Ren X, et al. The Comorbidity Index. In: Goldfield N, Pine M, Pine J, eds. Measuring and Managing Health Care Quality. New York: Aspen; 2002.

20. Hylek EM, Go AS, Chang Y, et al. Effect of intensity of oral anticoagulation on stroke severity and mortality in atrial fibrillation. N Engl J Med. 2003;349(11):1019-1026.

21. Levine MN, Raskob G, Landefeld S, Kearon C. Hemorrhagic complications of anticoagulant treatment. Chest. 2001;119(1)(suppl): 108S-121S.

22. Druss BG, Rosenheck RA, Desai MM, Perlin JB. Quality of preventive medical care for patients with mental disorders. Med Care. 2002; 40(2):129-136.

23. de Groot M, Jacobson AM, Samson JA, Welch G. Glycemic control and major depression in patients with type 1 and type 2 diabetes mellitus. J Psychosom Res. 1999;46(5):425-435.

24. Braddock CH 3rd, Fihn SD, Levinson W, Jonsen AR, Pearlman RA. How doctors and patients discuss routine clinical decisions. Informed decision making in the outpatient setting. J Gen Intern Med. 1997;12(6): 339-345.

25. Jackson JL, Kroenke K. Difficult patient encounters in the ambulatory clinic: clinical predictors and outcomes. Arch Intern Med. 1999; 159(10):1069-1075.

26. Kravitz RL, Hays RD, Sherbourne CD, et al. Recall of recommendations and adherence to advice among patients with chronic medical conditions. Arch Intern Med. 1993;153(16):1869-1878.

27. van Ryn M. Research on the provider contribution to race/ethnicity disparities in medical care. Med Care. 2002;40(1)(suppl):140-151.

28. Choudhry NK, Anderson GM, Laupacis A, Ross-Degnan D, Normand SL, Soumerai SB. Impact of adverse events on prescribing warfarin in patients with atrial fibrillation: matched pair analysis. BMJ. 2006; 332(7534):141-145.

29. Hollowell J, Ingelgard A, Reddy P, Gold K, Fitzmaurice D. Patient preference and capabilities are at least as important as clinical contraindications as barriers to prescribing warfarin in patients with atrial fibrillation [abstract 2204]. Blood. 2004;104(11, pt 1):606a.

30. Birdwell BG, Herbers JE, Kroenke K. Evaluating chest pain: the patient’s presentation style alters the physician’s diagnostic approach. Arch Intern Med. 1993;153(17):1991-1995.

31. Sansone RA, Sansone LA. Warfarin and antidepressants: happiness without hemorrhaging. Psychiatry (Edgmont). 2009;6(7):24-29.

32. Schauer DP, Moomaw CJ, Wess M, Webb T, Eckman MH. Psychosocial risk factors for adverse outcomes in patients with nonvalvular atrial fibrillation receiving warfarin. J Gen Intern Med. 2005;20(12): 1114-1119.

33. Freeman JV, Zhu RP, Owens DK, et al. Cost-effectiveness of dabigatran compared with warfarin for stroke prevention in atrial fibrillation. Ann Intern Med. 2011;154(1):1-11.

34. Ciechanowski PS, Katon WJ, Russo JE. Depression and diabetes: impact of depressive symptoms on adherence, function, and costs. Arch Intern Med. 2000;160(21):3278-3285.

35. Weisbord SD, Whittle J, Brooks RC. Is warfarin really underused in patients with atrial fibrillation? J Gen Intern Med. 2001;16(11):743-749.

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