Symptom Burden and Performance Status among Community-Dwelling Patients with Serious Illness.

BACKGROUND: Predicting when burdensome symptoms will arise or worsen is important to preserving quality of life in patients with serious illness. OBJECTIVES: We explored the relationship between prevalence and severity of symptoms and underlying performance status. METHODS: We performed a retrospective cohort analysis of patients receiving community palliative care, investigating relationships between symptom burden and performance status. Patient data were obtained from the Carolinas Palliative Care Consortium Database, a central registry of community consultation data for research and quality improvement. We measured symptom prevalence and severity using the McCorkle Symptom Distress Scale and performance status using the Palliative Performance Scale. RESULTS: We analyzed data of 4994 patients, most (90%) with noncancer, serious illnesses. Thirty percent had one or more moderate/severe symptoms. In addition to identifying the high prevalence of fatigue and pain, we found distinct groupings of symptoms with high burden associated with different levels of performance status. This includes high prevalence of fatigue, anorexia, and dyspnea in patients with high performance. Patients with low performance status, however, reported more pain, depression, and constipation. CONCLUSION: Bothersome symptoms change as patients' performance status worsens. Using performance status as a common language, both medical professionals and informal caregivers can monitor impending changes in symptom burden. This should inform development of community-based delivery systems to detect and manage distress in patients with palliative care needs.

Usability and Acceptability of the QDACT-PC, an Electronic Point-of-Care System for Standardized Quality Monitoring in Palliative Care.

CONTEXT: Few resources exist to support collaborative quality monitoring in palliative care. These tools, if proven efficient through technology-enabled methods, may begin to routinize data collection on quality during usual palliative care delivery. Usability testing is a common approach to assess how easily and effectively users can interact with a newly developed tool. OBJECTIVES: We performed usability testing of the Quality Data Collection Tool for Palliative Care (QDACT-PC) a novel, point-of-care quality monitoring tool for palliative care. METHODS: We used a mixed methods approach to assess community palliative care clinicians' evaluations of five domains of usability. These approaches included clinician surveys after recording mock patient data to assess satisfaction; review of entered data for accuracy and time to completion; and thematic review of "think aloud" protocols to determine issues, barriers, and advantages to the electronic system. RESULTS: We enrolled 14 palliative care clinicians for the study. Testing the electronic system vs. paper-based methods demonstrated similar error rates and time to completion. Overall, 68% of the participants believed that the electronic interface would not pose a moderate or major burden during usual clinical activities, and 65% thought it would improve the care they provided. Thematic analysis revealed significant issues with paper-based methods alongside training needs for future participants on using novel technologies that support the QDACT-PC. CONCLUSION: The QDACT-PC is a usable electronic system for quality monitoring in palliative care. Testing reveals equivalence with paper for data collection time, but with less burden overall for electronic methods across other domains of usability.

Quality of palliative care for patients with advanced cancer in a community consortium.

BACKGROUND: Measuring quality of care delivery is essential to palliative care program growth and sustainability. We formed the Carolinas Consortium for Palliative Care and collected a quality data registry to monitor our practice and inform quality improvement efforts. MEASURES: We analyzed all palliative care consultations in patients with cancer in our quality registry from March 2008 through October 2011 using 18 palliative care quality measures. Descriptive metric adherence was calculated after analyzing the relevant population for measurement. INTERVENTION: We used a paper-based, prospective method to monitor adherence for quality measures in a community-based palliative care consortium. OUTCOMES: We demonstrate that measures evaluating process assessment (range 63%-100%), as opposed to interventions (range 3%-17%), are better documented. CONCLUSIONS/LESSONS LEARNED: Analyzing data on quality is feasible and valuable in community-based palliative care. Overall, processes to collect data on quality using nontechnology methods may underestimate true adherence to quality measures.

Conformance with supportive care quality measures is associated with better quality of life in patients with cancer receiving palliative care.

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.