The Role of Clinical Uncertainty in Treatment Decisions for Diabetic Patients with Uncontrolled Blood Pressure

Kerr, Eve A.; Zikmund‐Fisher, Brian J.; Klamerus, Mandi L.; Subramanian, Usha; Hogan, Mary M.; Hofer, Timothy P.

doi:10.7326/0003-4819-148-10-200805200-00004

Cited by 151 publications

(162 citation statements)

References 43 publications

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“…36 Others have determined that patients with mental health conditions or chronic pain are at risk for receiving suboptimal care for their hypertension, diabetes, heart failure, arthritis, and chronic obstructive pulmonary disease. 31,[36][37][38][39][40] Other studies, however, suggest that these patterns are not universal. For example, patients with serious mental health conditions sometimes receive more intensive monitoring of their other chronic conditions.…”

Section: The Relationship Between Multimorbidity and Quality Of Carementioning

confidence: 99%

Quality of Care for Patients with Multiple Chronic Conditions: The Role of Comorbidity Interrelatedness

et al. 2013

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Multimorbidity-the presence of multiple chronic conditions in a patient-has a profound impact on health, health care utilization, and associated costs. Definitions of multimorbidity in clinical care and research have evolved over time, initially focusing on a patient's number of comorbidities and the associated magnitude of required care processes, and later recognizing the potential influence of comorbidity characteristics on patient care and outcomes. In this article, we review the relationship between multimorbidity and quality of care, and discuss how this relationship may be mediated by the degree to which conditions interact with one another to generate clinical complexity (comorbidity interrelatedness). Drawing on established theoretical frameworks from cognitive engineering and biomedical informatics, we describe how interactions among conditions result in clinical complexity and may affect quality of care. We discuss how this comorbidity interrelatedness influences the value of existing quality guidelines and performance metrics, and describe opportunities to quantify this construct using data widely available through electronic health records. Incorporating comorbidity interrelatedness into conceptualizations of multimorbidity has the potential to enhance clinical and research efforts that aim to improve care for patients with multiple chronic conditions.

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Section: The Relationship Between Multimorbidity and Quality Of Carementioning

confidence: 99%

Quality of Care for Patients with Multiple Chronic Conditions: The Role of Comorbidity Interrelatedness

et al. 2013

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“…[5][6][7][8] One such study used a conceptual model to systematically identify provider factors associated with a lower likelihood of medication intensification in hypertensive patients with diabetes mellitus. 9 These factors included reported clinical uncertainty regarding BP measurements, competing demands during clinic appointments, inappropriate physician BP goals, lack of timely follow-up of elevated BP, and concern for patient treatment nonadherence.…”

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confidence: 99%

Treatment Intensification in a Hypertension Telemanagement Trial

et al. 2011

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Abstract-Clinical inertia represents a barrier to hypertension management. As part of a hypertension telemanagement trial designed to overcome clinical inertia, we evaluated study physician reactions to elevated home blood pressures. We studied 296 patients from the Hypertension Intervention Nurse Telemedicine Study who received telemonitoring and study physician medication management. When a patient's 2-week mean home blood pressure was elevated, an "intervention alert" prompted study physicians to consider treatment intensification. We examined treatment intensification rates and subsequent blood pressure control. Patients generated 1216 intervention alerts during the 18-month intervention. Of 922 eligible intervention alerts, study physicians intensified treatment in 374 (40.6%). Study physician perception that home blood pressure was acceptable was the most common rationale for nonintensification (53.7%).When "blood pressure acceptable" was the reason for not intensifying treatment, the mean blood pressure was lower than for intervention alerts where treatment intensification occurred (135. Previous studies provide evidence for improved BP control using telemanagement models in selected patient populations. [11][12][13] Compared with clinic BP measurement, home telemonitoring may also better predict cardiovascular risk and is less subject to observer bias (white-coat hypertension and masked hypertension). 14 -18 The Hypertension Intervention Nurse Telemedicine Study (HINTS) was an 18-month randomized, controlled trial designed to circumvent factors contributing to clinical inertia. 19 We examined data from the medication management arms of HINTS to determine how physicians reacted to elevated BP values, why they reacted as they did, and how their decisions impacted subsequent patient BP control after episodes of elevated BP. Our goal was to determine whether clinical inertia persisted in HINTS despite the efforts to overcome it. Methods HINTS DesignHINTS randomized 593 eligible veterans into 4 groups: (1) a nurse-administered behavioral management intervention; (2) a nurse-administered, physician-directed medication management intervention using a validated clinical decision support system; (3) a combined behavioral management and medication management intervention; and (4) usual care. Eligible patients received primary care at the Durham Veterans Affairs Medical Center, had a diagnosis of hypertension, used BP-lowering medication, and had inadequate BP control (Ͼ140/90 mm Hg for all patients) based on the average of the previous 12 months' clinic BP measurements obtained from electronic medical charts. Exclusion criteria were receipt of dialysis; a serum creatinine Ͼ2.5 or no documentation of renal function; history of organ transplant; hospitalization for stroke, myocardial infarction, or coronary artery revascularization within 3 months of contact; diagnosis of metastatic cancer or dementia; lack of a home telephone; residence in a nursing home; receipt of home health care; or severely impaired hearing ...

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“…Moreover, the VA has served as a bellwether and model system for evaluating many quality issues with wide applicability. 26,44 In summary, we found that there was a clinically important drop in prescribing rates in older age groups that was not explained by a wide variety of factors, but that these differences were more difficult to detect after accounting for reasons cited in the clinical chart for non-prescribing. Patients in the upper reaches of age are different from their younger counterparts, and unique considerations need to be evaluated in making treatment decisions for this vulnerable group.…”

Section: 41-43mentioning

confidence: 91%

Age and Receipt of Guideline-Recommended Medications for Heart Failure: A Nationwide Study of Veterans

et al. 2011

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BACKGROUND: Older patients often receive less guideline-concordant care for heart failure than younger patients. OBJECTIVE: To determine whether age differences in heart failure care are explained by patient, provider, and health system characteristics and/or by chartdocumented reasons for non-adherence to guidelines. DESIGN AND PATIENTS: Retrospective cohort study of 2,772 ambulatory veterans with heart failure and left ventricular ejection fraction <40% from a 2004 nationwide medical record review program (the VA External Peer Review Program). MAIN MEASURES: Ambulatory use of ACE inhibitors, angiotensin receptor blockers (ARBs), and beta blockers. RESULTS: Among 2,772 patients, mean age was 73 +/− 10 years, 87% received an ACE inhibitor or ARB, and 82% received a beta blocker. When patients with explicit chart-documented reasons for not receiving these drugs were excluded, 95% received an ACE inhibitor or ARB and 89% received a beta blocker. In multivariable analyses controlling for a variety of patient and health system characteristics, the adjusted odds ratio for ACE-inhibitor and ARB use was 0.43 (95% CI 0.24-0.78) for patients age 80 and over vs. those age 50-64 years, and the adjusted odds ratio for beta blocker use was 0.66 (95% CI 0.48-0.93) between the two age groups. The magnitude of these associations was similar but not statistically significant after excluding patients with chart-documented reasons for not prescribing ACE inhibitors or ARBs and beta blockers. CONCLUSIONS: A high proportion of veterans receive guideline-recommended medications for heart failure. Older veterans are consistently less likely to receive these drugs, although these differences were no longer significant when accounting for patients with chart-documented reasons for not prescribing these drugs. Closely evaluating reasons for non-prescribing in older adults is essential to assessing whether non-treatment represents good clinical judgment or missed opportunities to improve care.KEY WORDS: guideline adherence; heart failure; aging; health services research; quality of care.

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The Role of Clinical Uncertainty in Treatment Decisions for Diabetic Patients with Uncontrolled Blood Pressure

Abstract: 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.

Cited by 151 publications

References 43 publications

Quality of Care for Patients with Multiple Chronic Conditions: The Role of Comorbidity Interrelatedness

Quality of Care for Patients with Multiple Chronic Conditions: The Role of Comorbidity Interrelatedness

Treatment Intensification in a Hypertension Telemanagement Trial

Age and Receipt of Guideline-Recommended Medications for Heart Failure: A Nationwide Study of Veterans

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