Eve A. Kerr, MD, MPH; Brian J. Zikmund-Fisher, PhD; Mandi L. Klamerus, MPH; Usha Subramanian, MD, MS; Mary M. Hogan, PhD, RN; Timothy P. Hofer, MD, MS
Acknowledgment: The authors thank recruitment coordinator Claire Robinson; research assistants Stacey Hirth, Susan Jaeger, Madhavi Diwanji, Janice Thompson, Caroline Lynch, and Diana Newman, who worked tirelessly to recruit patients; data manager Jennifer Davis; site principal investigators Drs. David Aron, Martin Bermann, and Ketan Shah, without whom the study could not have been done; and the many providers and patients who participated. They also thank Drs. Rodney Hayward, Michele Heisler, and John Piette for their suggestions on earlier drafts of this manuscript. The authors are particularly grateful to Drs. Jane Forman and Richard Frankel for their insightful contributions to the overall study design.
Grant Support: By a research grant from the U.S. Department of Veterans Affairs Health Services Research and Development Service (IIR 02-225) and in part by the Michigan Diabetes Research and Training Center Grant (P60DK-20572) from the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health.
Potential Financial Conflicts of Interest: None disclosed.
Reproducible Research Statement:Study protocol: Available by contacting Dr. Kerr (e-mail, email@example.com). Statistical code: Available by contacting Dr. Hofer (e-mail, firstname.lastname@example.org). Data set: Not available.
Requests for Single Reprints: Eve A. Kerr, MD, MPH, Ann Arbor Veteran Affairs Health Services Research and Development Service Center of Excellence, PO Box 130170, Ann Arbor, Michigan 48113; e-mail, email@example.com.
Current Author Addresses: Drs. Kerr, Hogan and Hofer, and Ms. Klamerus: Ann Arbor Veteran Affairs Health Services Research and Development Service Center of Excellence, PO Box 130170, Ann Arbor, MI 48113-0170.
Dr. Zikmund-Fisher: University of Michigan Division of General Medicine, 300 North Ingalls, #7C27, Ann Arbor, MI 48109-5429.
Dr. Subramanian: Roudebush Veterans Affairs Medical Center and Indiana University, Diabetes Translation Research Center, IF-122, 250 University Boulevard, Indianapolis, IN 46202.
Author Contributions: Conception and design: E.A. Kerr, B.J. Zikmund-Fisher, M.M. Hogan, T.P. Hofer.
Analysis and interpretation of the data: E.A. Kerr, B.J. Zikmund-Fisher, M.L. Klamerus, U. Subramanian, M.M. Hogan, T.P. Hofer.
Drafting of the article: E.A. Kerr, M.L. Klamerus, T.P. Hofer.
Critical revision of the article for important intellectual content: B.J. Zikmund-Fisher, U. Subramanian, M.M. Hogan, T.P. Hofer.
Final approval of the article: E.A. Kerr, B.J. Zikmund-Fisher, M.L. Klamerus, U. Subramanian, T.P. Hofer.
Provision of study materials or patients: U. Subramanian.
Statistical expertise: T.P. Hofer.
Obtaining of funding: E.A. Kerr, T.P. Hofer.
Administrative, technical, or logistic support: M.L. Klamerus.
Collection and assembly of data: M.L. Klamerus, U. Subramanian.
Factors underlying failure to intensify therapy in response to elevated blood pressure have not been systematically studied.
To examine the process of care for diabetic patients with elevated triage blood pressure (≥140/90 mm Hg) during routine primary care visits to assess whether a treatment change occurred and to what degree specific patient and provider factors correlated with the likelihood of treatment change.
Prospective cohort study.
9 Veterans Affairs facilities in 3 midwestern states.
1169 diabetic patients with scheduled visits to 92 primary care providers from February 2005 to March 2006.
Proportion of patients who had a change in a blood pressure treatment (medication intensification or planned follow-up within 4 weeks). Predicted probability of treatment change was calculated from a multilevel logistic model that included variables assessing clinical uncertainty, competing demands and prioritization, and medication-related factors (controlling for blood pressure).
Overall, 573 (49%) patients had a blood pressure treatment change at the visit. The following factors made treatment change less likely: repeated blood pressure by provider recorded as less than 140/90 mm Hg versus 140/90 mm Hg or greater or no recorded repeated blood pressure (13% vs. 61%; P < 0.001); home blood pressure reported by patients as less than 140/90 mm Hg versus 140/90 mm Hg or greater or no recorded home blood pressure (18% vs. 52%; P < 0.001); provider systolic blood pressure goal greater than 130 mm Hg versus 130 mm Hg or less (33% vs. 52%; P = 0.002); discussion of conditions unrelated to hypertension and diabetes versus no discussion (44% vs. 55%; P = 0.008); and discussion of medication issues versus no discussion (23% vs. 52%; P < 0.001).
Providers knew that the study pertained to diabetes and hypertension, and treatment change was assessed for 1 visit per patient.
Approximately 50% of diabetic patients presenting with a substantially elevated triage blood pressure received treatment change at the visit. Clinical uncertainty about the true blood pressure value was a prominent reason that providers did not intensify therapy.
Why do clinicians fail to intensify antihypertensive therapy when a patient's blood pressure is elevated?
This study involved 1169 diabetic patients seen by 92 primary care providers at 9 Veterans Affairs facilities. All had elevated triage blood pressures, but only half received antihypertensive treatment intensification by providers. Patient reports of home blood pressures or repeated blood pressures by providers within normal limits and discussion of medication issues decreased the likelihood of antihypertensive intensification at clinic visits.
Uncertainty about true blood pressure values may underlie many reasons why physicians do not intensify antihypertensive therapy.
Hypertension clinical action model.
Study flow diagram.
PCP = primary care provider. *Diabetic patients presenting for a primary care visit to 1 of 92 participating providers were referred for eligibility assessment if their lowest triage blood pressure was ≥140/90 mm Hg. *Number of responses varied by individual item.
Table 1. Independent Variables
Table 2. Patient and Provider Characteristics
Table 3. Association of Measured Factors with the Predicted Probability of Treatment Change
Relationship of systolic and diastolic blood pressures at enrollment and mean previous year systolic blood pressure with probability of treatment change.
Each curve is shown with the other 2 blood pressure components adjusted to their mean value and the intensification rate for the average provider and clinic site. For each blood pressure component, the curve is presented only for a range of values actually seen when the other 2 components are both close to their mean (±10 mm Hg of the mean value).
Appendix Table. Three-Level Logistic Regression Models Assessing Associations between Patient, Provider, and Visit Factors and Treatment Change
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Department of General Medicine and Infectious Diseases, Kameda Medical Center
May 23, 2008
It must just happen to be spotted.
The article "The Role of Clinical Uncertainty in Treatment Decisions for Diabetic Patients with Uncontrolled Blood Pressure" by Eve A. Kerr et al is certainly interesting and clinically significant. As a generalist, I have a number of patients who have prescribed antihypertensive drugs. As mentioned, I also tend to delay changing my strategy of the antihypertensive therapy. Certainly we know the clinical uncertainty of the true blood pressure, and the uncertainty always means to us, just "elevated." White coats, timing or the way of measurement would usually produce increased blood pressure. Rarely found the cause of happen to bring down the blood pressure clinically. We want to believe that the high blood pressure just happen to be spotted, it must be lower in an ordinary way.
Michael S Karp
USC - Keck School of Medicine
May 28, 2008
Additional Factors Causing Inertia
I agree with many of the conclusions offered by Kerr et al regarding medical inertia. It is concerning that despite the knowledge of the benefits of blood pressure, blood sugar, and cholesterol control in the diabetic patient, the percent of patients that achieve medical goals is low. Many factors as outlined in the article contribute to this phenomenom. However, a major factor that wasn't studied in this article is medical insurance. It's been well established that those will less insurance are less likely to get the standard of care. Paz and colleagues studied risk factors for noncompliance with ophthalmologic exam in diabetics. They found, among other factors, the lack of insurance gave an odds ratio of 2.5 (95% CI, 1.7-3.7) for noncompliance. It's conceivable that physicians are consciously or unconsciously influenced by patient's insurance status when deciding to optimize or intensify medical management. Are we indirectly deciding who gets the best care? Are these decisions being made for us before the patient even comes into the clinic? How much does the presence of formulary restrictions and prior authorizations play a role? I'm concerned that we may be hardwiring our own thought processes around this issue more than we realize.
References: Paz et al. Noncompliance with vision care guidelines in Latinos with type 2 diabetes mellitus: the Los Angeles Latino Eye Study. Ophthalmology. 113(8):1372-7, 2006 Aug.
Victor O. Kolade
University of Buffalo
June 22, 2008
Tobacco Use qualifies as a Concordant Condition
Perhaps Kerr and colleagues should have classified tobacco use as a concordant condition (1). It is a chronic disease characterized by relapses and remissions (2) that is associated with some of the concordant conditions included in the study. Besides, smoking may be more prevalent among Veterans (3), possibly driven by previous Department of Defense practices offering tobacco to soldiers at a discount (4).
1. Kerr EA, Zikmund-Fisher BJ, Klamerus ML, Subramanian U, Hogan MM, Hofer TP. The role of clinical uncertainty in treatment decisions for diabetic patients with uncontrolled blood pressure. Ann Intern Med. 2008;148(10):717-27.
2. Steinberg MB, Schmelzer AC, Richardson DL, Foulds J. The case for treating tobacco dependence as a chronic disease. Ann Intern Med. 2008;148(7):554-6.
3. Ross JS, Keyhani S, Keenan PS, et al. Use of Recommended Ambulatory Care Services: Is the Veterans Affairs Quality Gap Narrowing? Archives of Internal Medicine. 2008;168(9):950-958.
4. Smith EA, Blackman VS, Malone RE. Death at a discount: how the tobacco industry thwarted tobacco control policies in US military commissaries. Tobacco Control. 2007;16(1):38-46.
Lawrence R Krakoff
Mount Sinai School of Medicine
July 17, 2008
Uncertainty or Good Judgement
Letter to Editors Annals of Internal Medicine Sent July 7, 2008 RÃ© Uncertainty in management of hypertension in diabetes. Kerr et al and editorial by Phillips.
The article by Kerr et al (1) is a valuable description of choices made by physicians in the VA health care clinics for treatment of hypertension in diabetic patients. Such studies are useful in trying to understand physician behavior in relation to recommendations from guidelines, such as the JNC-7 (2). However, the authors' interpretation of their results and the opinions given in the accompanying editorial by Phillips and Twombly (3) should not go unchallenged as they fail to recognize advances in the role of home blood pressures for management of hypertension.
In about half of the visits, providers relied on screening blood pressures for their treatment decisions regarding hypertension. Is this a reflection of uncertainty or awareness that screening pressures may be inaccurate for treatment decisions in individual cases? The providers who used either home pressures or additional clinic pressures may have been uncertain about the accuracy or the screening pressures, but the basis of their choice to use additional pressures is medically sound and, in fact, recommended. In this case uncertainty reflects better judgment. In particular, the case for relying on home blood pressures for treatment choices is well supported by a robust evidence base(4;5). Relying on limited blood pressure measurements from clinics alone, enhances the likelihood of regression dilution with the potential consequences of over- treatment or undertreatment.
Effective management of hypertension, especially in diabetics, is clearly a mainstay of preventive cardiovascular medicine. The VA health care system has been a major resource for both the clinical trials and the demonstration that control can be achieved in clinic populations. That being the case, attention must now be paid to optimization of all the complex issues of individual patient care for more accurate assessment of usual blood pressure and more nuanced recognition of decisions that will maximize patient satisfaction and prevention of future disease.
(1) Kerr EA, Zikmund-Fisher BJ, Klamerus ML, Subramanian U, Hogan MM, Hofer TP. The role of clinical uncertainty in treatment decisions for diabetic patients with uncontrolled blood pressure. Ann Intern Med. 2008;148:717-27.
(2) Chobanian AV, Bakris GL, Black HR, Green L, Izzo JLJr, Jones DW et al. The seventh report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure: The JNC 7 Report. JAMA. 2003;289:2560-2572.
(3) Phillips LS, Twombly JG. It's time to overcome clinical inertia. Ann Intern Med. 2008;148:783-85.
(4) Verberk WJ, Kroon AA, Kessels AG, de Leeuw PW. Home blood pressure measurement: a systematic review. J Am Coll Cardiol. 2005;46:743- 51.
(5) Pickering TG, Miller NH, Ogedegbe G, Krakoff LR, Artinian NT, Goff D. Call to Action on Use and Reimbursement for Home Blood Pressure Monitoring. A Joint Scientific Statement From the American Heart Association, American Society of Hypertension, and Preventive Cardiovascular Nurses Association. Hypertension. 2008.
Lawrence R Krakoff MD Professor of Medicine Mount Sinai School of Medicine New York NY 10029 E-mail Lawrence.firstname.lastname@example.org
Kerr EA, Zikmund-Fisher BJ, Klamerus ML, et al. The Role of Clinical Uncertainty in Treatment Decisions for Diabetic Patients with Uncontrolled Blood Pressure. Ann Intern Med. 2008;148:717–727. doi: 10.7326/0003-4819-148-10-200805200-00004
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Published: Ann Intern Med. 2008;148(10):717-727.
Cardiology, Coronary Risk Factors, Diabetes, Endocrine and Metabolism, Hypertension.
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