Vol. 49 No. 2 February 2015
Journal of Pain and Symptom Management 289
Brief Quality Improvement Report
Quality of Palliative Care for Patients With Advanced Cancer in a Community Consortium Arif H. Kamal, MD, Ryan D. Nipp, MD, Janet H. Bull, MD, Charles S. Stinson, MD, Ashlei W. Lowery, MD, Jonathan M. Nicolla, M.B.A., and Amy P. Abernethy, MD, PhD Duke Center for Learning Health Care (A.H.K., J.M.N., A.P.A.); Division of Medical Oncology (A.H.K., A.P.A.); Center for Palliative Care (A.H.K., A.P.A.) and Duke Cancer Institute (A.H.K., A.P.A.), Duke University Medical Center, Durham, North Carolina; Dana Farber Cancer Institute (R.D.N.), Boston, Massachusetts; Four Seasons (J.H.B.), Flat Rock, North Carolina; Forsyth Medical Center Palliative Care Services (C.S.S.), Winston-Salem, North Carolina; and Capital Caring (A.W.L.), Falls Church, Virginia, USA
Abstract 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 communitybased palliative care consortium. Outcomes. We demonstrate that measures evaluating process assessment (range 63%e100%), as opposed to interventions (range 3%e17%), 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. J Pain Symptom Manage 2015;49:289e292. Ó 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved. Key Words Oncology, quality, symptoms, performance status, palliative care
Background Health care systems are currently evolving to meet the triple aims for highly effective health care proposed by the Institute for Healthcare Improvement, including delivering high-quality, low-cost care to large populations. To date, data collection efforts around quality have been limited by scope (e.g., analyses limited to institutional level), validity (e.g., retrospective, aggregated data parsed from administrative and billing databases), and clinical relevance (e.g., limited capability of data to impact ongoing patient care). As pay-for-performance models are phased in, quality
Address correspondence to: Arif H. Kamal, MD, Duke University Medical Center, Box 3436, Durham, NC 27710, USA. E-mail: [email protected] Ó 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.
measurement will be needed for regular demonstration of quality of care and improving patient outcomes. Consequently, the portfolio of quality measures to evaluate structure, process, and outcomes is rapidly expanding in all fields of medicine, including consultative palliative care. With the dramatic growth in clinical palliative care services over the last decade comes the unique opportunity to collaborate, compare, and learn from each other. Indeed, new collaborations are forming, such as the Palliative Care Research Cooperative Group,1 the first American national clinical research network for palliative care; the Coalition of Hospices Organized to
Accepted for publication: May 28, 2014.
0885-3924/$ - see front matter http://dx.doi.org/10.1016/j.jpainsymman.2014.05.024
290
Kamal et al.
Investigate Comparative Effectiveness,2 a distributed hospice network providing data for comparison of quality of care and benchmarking; and several regional palliative care quality monitoring networks such as those in California and the Carolinas.3,4 Multisite efforts require a transition toward information exchange and standardization of data to contribute to aggregate understanding. The Carolinas Palliative Care Consortium is a novel academic-community collaboration established in 2007.4 The vision is to ‘‘improve the quality of care of patients with advanced illness through benchmarking and quality initiatives using a data-driven system that monitors outcomes.’’ The resultant ongoing, collaborative venture has demonstrated capabilities for data collection and performance improvement.5 A novel technology environment supports efficient data collection at point of care. Herein, we present the first analysis of data collected regarding rates of adherence to quality measures, explore possible rationales for shortcomings, and signal opportunities for quality improvement projects.
Measures/Intervention We included all patients with a cancer diagnosis (Table 1) between March 1, 2008, and October 1, 2011, in the Carolina Consortium Palliative Care Database,4 an institutional review board-approved registry combining information from four member sites (Four Table 1 Demographics of Patients With Cancer (N ¼ 459) Variable
Categories
n
%
Age, yrs
Journal of Pain and Symptom Management 289
Brief Quality Improvement Report
Quality of Palliative Care for Patients With Advanced Cancer in a Community Consortium Arif H. Kamal, MD, Ryan D. Nipp, MD, Janet H. Bull, MD, Charles S. Stinson, MD, Ashlei W. Lowery, MD, Jonathan M. Nicolla, M.B.A., and Amy P. Abernethy, MD, PhD Duke Center for Learning Health Care (A.H.K., J.M.N., A.P.A.); Division of Medical Oncology (A.H.K., A.P.A.); Center for Palliative Care (A.H.K., A.P.A.) and Duke Cancer Institute (A.H.K., A.P.A.), Duke University Medical Center, Durham, North Carolina; Dana Farber Cancer Institute (R.D.N.), Boston, Massachusetts; Four Seasons (J.H.B.), Flat Rock, North Carolina; Forsyth Medical Center Palliative Care Services (C.S.S.), Winston-Salem, North Carolina; and Capital Caring (A.W.L.), Falls Church, Virginia, USA
Abstract 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 communitybased palliative care consortium. Outcomes. We demonstrate that measures evaluating process assessment (range 63%e100%), as opposed to interventions (range 3%e17%), 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. J Pain Symptom Manage 2015;49:289e292. Ó 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved. Key Words Oncology, quality, symptoms, performance status, palliative care
Background Health care systems are currently evolving to meet the triple aims for highly effective health care proposed by the Institute for Healthcare Improvement, including delivering high-quality, low-cost care to large populations. To date, data collection efforts around quality have been limited by scope (e.g., analyses limited to institutional level), validity (e.g., retrospective, aggregated data parsed from administrative and billing databases), and clinical relevance (e.g., limited capability of data to impact ongoing patient care). As pay-for-performance models are phased in, quality
Address correspondence to: Arif H. Kamal, MD, Duke University Medical Center, Box 3436, Durham, NC 27710, USA. E-mail: [email protected] Ó 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.
measurement will be needed for regular demonstration of quality of care and improving patient outcomes. Consequently, the portfolio of quality measures to evaluate structure, process, and outcomes is rapidly expanding in all fields of medicine, including consultative palliative care. With the dramatic growth in clinical palliative care services over the last decade comes the unique opportunity to collaborate, compare, and learn from each other. Indeed, new collaborations are forming, such as the Palliative Care Research Cooperative Group,1 the first American national clinical research network for palliative care; the Coalition of Hospices Organized to
Accepted for publication: May 28, 2014.
0885-3924/$ - see front matter http://dx.doi.org/10.1016/j.jpainsymman.2014.05.024
290
Kamal et al.
Investigate Comparative Effectiveness,2 a distributed hospice network providing data for comparison of quality of care and benchmarking; and several regional palliative care quality monitoring networks such as those in California and the Carolinas.3,4 Multisite efforts require a transition toward information exchange and standardization of data to contribute to aggregate understanding. The Carolinas Palliative Care Consortium is a novel academic-community collaboration established in 2007.4 The vision is to ‘‘improve the quality of care of patients with advanced illness through benchmarking and quality initiatives using a data-driven system that monitors outcomes.’’ The resultant ongoing, collaborative venture has demonstrated capabilities for data collection and performance improvement.5 A novel technology environment supports efficient data collection at point of care. Herein, we present the first analysis of data collected regarding rates of adherence to quality measures, explore possible rationales for shortcomings, and signal opportunities for quality improvement projects.
Measures/Intervention We included all patients with a cancer diagnosis (Table 1) between March 1, 2008, and October 1, 2011, in the Carolina Consortium Palliative Care Database,4 an institutional review board-approved registry combining information from four member sites (Four Table 1 Demographics of Patients With Cancer (N ¼ 459) Variable
Categories
n
%
Age, yrs
