PURPOSE: As palliative care further integrates into cancer care, descriptions of how supportive care quality measures improve patient outcomes are necessary to establish best practices. METHODS: We assessed the relationship between conformance to 18 palliative care quality measures and quality of life from data obtained using our novel point-of-care, electronic quality monitoring system, the Quality Data Collection Tool for Palliative Care (QDACT-PC). All patients with cancer from January 2008 through March 2011 seen in the Carolinas Palliative Care Consortium were evaluated for demographic, disease, prognostic, performance status, and measure conformance variables. Using univariate and multivariate regression, we examined the relationship between these variable and high quality of life at the initial specialty palliative care consultation. RESULTS: Our cohort included 459 patients, the majority of whom were over age 65 years (66%) and white (84%). Lung (29.1%) and GI (24.7%) cancers were most common. In univariate analyses, conformance to assessment of comprehensive symptoms, fatigue and constipation assessment, timely management of pain and constipation, and timely emotional well-being assessment were associated with highest levels of quality of life (all Ps < .05). In a multivariate model (C-stat = 0.66), performance status (odds ratio [OR], 5.21; P = .003), estimated life expectancy (OR, 22.6; P = .003), conformance to the measure related to emotional well-being assessment (OR, 1.60; P = .026), and comprehensive screening of symptoms (OR, 1.74, P = .008) remained significant. CONCLUSION: Oncology care pathways that routinely incorporate supportive care principles, such as comprehensive symptom and emotional well-being assessments, may improve patient outcomes.
PURPOSE: As palliative care further integrates into cancer care, descriptions of how supportive care quality measures improve patient outcomes are necessary to establish best practices. METHODS: We assessed the relationship between conformance to 18 palliative care quality measures and quality of life from data obtained using our novel point-of-care, electronic quality monitoring system, the Quality Data Collection Tool for Palliative Care (QDACT-PC). All patients with cancer from January 2008 through March 2011 seen in the Carolinas Palliative Care Consortium were evaluated for demographic, disease, prognostic, performance status, and measure conformance variables. Using univariate and multivariate regression, we examined the relationship between these variable and high quality of life at the initial specialty palliative care consultation. RESULTS: Our cohort included 459 patients, the majority of whom were over age 65 years (66%) and white (84%). Lung (29.1%) and GI (24.7%) cancers were most common. In univariate analyses, conformance to assessment of comprehensive symptoms, fatigue and constipation assessment, timely management of pain and constipation, and timely emotional well-being assessment were associated with highest levels of quality of life (all Ps < .05). In a multivariate model (C-stat = 0.66), performance status (odds ratio [OR], 5.21; P = .003), estimated life expectancy (OR, 22.6; P = .003), conformance to the measure related to emotional well-being assessment (OR, 1.60; P = .026), and comprehensive screening of symptoms (OR, 1.74, P = .008) remained significant. CONCLUSION: Oncology care pathways that routinely incorporate supportive care principles, such as comprehensive symptom and emotional well-being assessments, may improve patient outcomes.
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