What type of feedback to clinicians best improves conformance to supportive care quality measures?

2013 ◽  
Vol 31 (31_suppl) ◽  
pp. 102-102
Author(s):  
Arif Kamal ◽  
Amy Pickar Abernethy ◽  
Janet Bull ◽  
Jonathan Nicolla ◽  
Joseph Kelly ◽  
...  
Keyword(s):  
Palliative Care ◽  
Quality Improvement ◽  
Supportive Care ◽  
Symptom Assessment ◽  
Quality Measures ◽  
Care Quality ◽  
Quality Data ◽  
Improvement Project ◽  
Edmonton Symptom Assessment Scale ◽  
Comparative Feedback

102 Background: Supportive care is under-addressed in oncology and an important area for quality improvement. Regular, directed feedback is an important component of effective quality management. What type of feedback yields the highest conformance to supportive care measures? Methods: Within the Carolinas Palliative Care Consortium, we conducted a series of three PDSA cycles, each one month-long, to evaluate various types of clinician-directed feedback on conformance to two supportive care measures. We collected data using a web-based, mobile health platform called QDACT-PC (Quality Data Collection Tool for Palliative Care). Every four weeks, feedback to clinicians on performance was changed in a stepwise fashion, from “no feedback” to “personal feedback” to “comparative feedback” (personal conformance compared to the rest of the Consortium). We monitored weekly changes to conformance to two quality measures: documentation of timely management of constipation and dyspnea. To meet the measures, symptoms with intensity of >3/10 on the Edmonton Symptom Assessment Scale required documentation of intervention within 24 hours. Conformance rates were calculated and compared to a historical baseline. Results: 23 providers participated in this quality improvement project, which spanned 465 patient encounters across 104 unique patients. Baseline data generated from 3/2008-10/2011 demonstrated baseline conformance to the dyspnea and constipation measures at 6% (27/457) and 4% (14/398), respectively. After addition of an electronic, prospective quality monitoring system alone (QDACT-PC), conformance increased to 93% (42/45) and 92% (23/25), respectively. With personalized, weekly feedback, these rates increased to 94% for dyspnea and 100% for constipation. Feedback comparing personal performance to the average of the rest of the Consortium further increased this to 100% for both. Conclusions: Regular, weekly feedback on performance increases conformance to supportive care quality measures. Adding comparative feedback versus other peers solidifies this effect. Duration of the effect is being evaluated.

scholarly journals Piloting A Self-Reported Symptom Assessment Tool In Three Outpatient Oncology Palliative Care Clinics

2021 ◽  
Author(s):  
Mallikaben Bhanubhai Patel ◽  
Ashley Leak Bryant ◽  
Deborah K Mayer ◽  
Gary Winzelberg
Keyword(s):  
Quality Of Life ◽  
Palliative Care ◽  
Quality Improvement ◽  
Symptom Assessment ◽  
Comprehensive Cancer Center ◽  
Staff Turnover ◽  
Improvement Project ◽  
Pdsa Cycle ◽  
Edmonton Symptom Assessment Scale

Abstract Background: Palliative care outpatient clinics should assess patients’ symptoms and quality of life prior to visits to guide care and response to treatments. We describe the implementation of a quality improvement initiative to increase symptom and quality of life screening in the outpatient oncology palliative care (OOPC) clinics of one National Cancer Institute-designated Comprehensive Cancer Center. Method: Our quality improvement project structure was based on the RE-AIM framework. Guided by the Plan-Do-Study-Act (PDSA) approach, we focused on assessing effective implementation of the Edmonton Symptom Assessment Scale (ESAS-r ) and one Quality of Life (QoL) question at each OOPC visit. At the end of each 3-week PDSA cycle, barriers and facilitators were recognized and addressed. The implementation’s effectiveness was determined by percentage of adherence using the following formula: [(number of ESAS-r +1 QoL forms completed per clinic/Number of OOPC completed patient appointments per clinic) x 100].Results: A total of 372 patient appointments were completed during the four PDSA cycles, with overall 59% adherence. The first PDSA cycle compliance was 69%, 58% in the second, 52% in the third, and 65% at the last PDSA cycle. The primary barrier was staff turnover.Conclusion: We were able to implement the ESAS-r + 1 QoL form in a complex clinical outpatient setting. We identified barriers for sustainability, including staff turnover. We addressed these barriers by providing robust instructions that outlined an overview of the clinic workflow and education for all staff members involved in the implementation process. Based on our experience, we suggest integrating this form into the electronic medical record to monitor patient outcomes in the outpatient oncology clinics.

scholarly journals Piloting a Self-Reported Symptom Assessment Tool in Three Outpatient Oncology Palliative Care Clinics

2021 ◽  
Author(s):  
Mallikaben Bhanubhai Patel ◽  
Ashley Leak Bryant ◽  
Deborah K Mayer ◽  
Gary Winzelberg
Keyword(s):  
Quality Of Life ◽  
Palliative Care ◽  
Quality Improvement ◽  
Symptom Assessment ◽  
Comprehensive Cancer Center ◽  
Staff Turnover ◽  
Improvement Project ◽  
Pdsa Cycle ◽  
Edmonton Symptom Assessment Scale

Abstract Background: Palliative care outpatient clinics should assess patients’ symptoms and quality of life prior to visits to guide care and response to treatments. We describe the implementation of a quality improvement initiative to increase symptom and quality of life screening in the outpatient oncology palliative care (OOPC) clinics of one National Cancer Institute-designated Comprehensive Cancer Center. Method: Our quality improvement project structure was based on the RE-AIM framework. Guided by the Plan-Do-Study-Act (PDSA) approach, we focused on assessing effective implementation of the Edmonton Symptom Assessment Scale (ESAS-r ) and one Quality of Life (QoL) question at each OOPC visit. At the end of each 3-week PDSA cycle, barriers and facilitators were recognized and addressed. The implementation’s effectiveness was determined by percentage of adherence using the following formula: [(number of ESAS-r +1 QoL forms completed per clinic/Number of OOPC completed patient appointments per clinic) x 100].Results: A total of 372 patient appointments were completed during the four PDSA cycles, with overall 59% adherence. The first PDSA cycle compliance was 69%, 58% in the second, 52% in the third, and 65% at the last PDSA cycle. The primary barrier was staff turnover.Conclusion: We were able to implement the ESAS-r + 1 QoL form in a complex clinical outpatient setting. We identified barriers for sustainability, including staff turnover. We addressed these barriers by providing robust instructions that outlined an overview of the clinic workflow and education for all staff members involved in the implementation process. Based on our experience, we suggest integrating this form into the electronic medical record to monitor patient outcomes in the outpatient oncology clinics.

Toward proven and prioritized quality measures: Which ASCO QOPI and other supportive care measures associate with improved quality of life (QOL)?

2012 ◽  
Vol 30 (34_suppl) ◽  
pp. 165-165
Author(s):  
Arif Kamal ◽  
Janet Bull ◽  
Amy Pickar Abernethy
Keyword(s):  
Systematic Review ◽  
Palliative Care ◽  
Supportive Care ◽  
Cancer Patients ◽  
Clinical Care ◽  
Performance Status ◽  
Quality Measures ◽  
Well Being ◽  
Care Quality ◽  
The Impact

165 Background: An expanding array of quality measures, including the Quality Oncology Practice Initiative (QOPI) metrics, is being developed for oncology. To date, evidence demonstrating the impact of each metric on outcomes, ultimately aiding in prioritization of individual measures, remains immature. We investigated the relationship between conformance with quality measures and higher patient QOL among cancer patients receiving palliative care. Methods: A comprehensive systematic review of PUBMED and the gray literature (1995-2012) identifed all described supportive care quality measures. Patients receiving palliative care in 4 community-based programs were entered into a longitudinal quality registry; analyses focused on cancer patients registered between 6/08-10/11. To find predictors of higher QOL, conformance cohorts were examined for demographic variables, performance status (measured by palliative performance scale, PPS) and provider estimation of prognosis and included in univariate and multivariate regression. Results: The systematic review yielded 303 quality measures. Of these, 18 measures, representing components of the ASCO QOPI, Hospice PEACE, and Cancer-ASSIST measure sets, were evaluable using registry data. 460 cancer patients were included. 60% of patients had weeks to 6 months expected prognosis. Among QOPI measures, conformance with two measures was significantly associated with better QOL: constipation assessment at time of narcotic prescription and emotional well-being assessment (both p<0.05). Other significant findings were conformance with screening of symptoms at first visit (p=0.017), timely treatment for uncontrolled dyspnea (p=0.005), and assessment of fatigue (p=0.007). In a multivariate model predicting higher QOL, measures involving emotional well-being assessment (OR 1.60; p=0.026) and screening of symptoms (OR 1.74, p=0.008) remained significant. Conclusions: Clinical care that conforms to quality measures reflecting regular symptom and emotional assessment is significantly associated with better patient experiences (QOL) and should be prioritized in quality assessment efforts.

Formation of an international quality improvement collaborative for palliative care: The Global Palliative Care Quality Alliance (GPCQA).

2014 ◽  
Vol 32 (31_suppl) ◽  
pp. 91-91
Author(s):  
Arif Kamal ◽  
Jonathan Nicolla ◽  
Fred Friedman ◽  
Charles S. Stinson ◽  
Laura Patel ◽  
...  
Keyword(s):  
Palliative Care ◽  
Quality Improvement ◽  
Data Collection ◽  
Best Practices ◽  
Point Of Care ◽  
Shared Vision ◽  
Care Quality ◽  
Quality Data ◽  
Spiritual Assessment ◽  
National Quality

91 Background: Formal mechanisms to share data on quality remain immature in specialty palliative care. As the field grows, infrastructure that promotes collaboration among academic and community-based practice will be required to foster comparisons and benchmarking of data to inform areas for quality improvement. Further, such relationships will create a palliative care “quality improvement laboratory”, where proposed guidelines and best practices can be developed, implemented, and tested. Methods: We set out to bring together specialty palliative care practices with a shared vision for collaborative quality improvement. We modeled our approach after the Institute for Healthcare Improvement Breakthrough Series alongside our Rapid Learning Quality Improvement paradigm. We use a set of common data collection procedures, across an electronic point-of-care platform called Quality Data Collection Tool (QDACT), alongside a centralized data registry. Further, we meet and discuss challenges and issues, compare best practices, and brainstorm new projects through biweekly conference calls. Results: We have created a multi-institutional collaboration for quality assessment and improvement in specialty palliative care. Termed the Global Palliative Care Quality Alliance, we have brought together 11 academic and community organizations, both general and oncology-specific, across six states to study various areas of quality practice. Short-term, we will conduct rapid-cycling quality improvement projects addressing National Quality Forum domains for quality palliative care, including documentation of spiritual assessment and timely advance care planning. Long-term, we aim to study the link between quality measure adherence and outcomes and further align our initiatives with those of other large consortia, like the Palliative Care Research Cooperative and Palliative Care Quality Network. Conclusions: Collaborative quality improvement is needed in specialty palliative care across a national platform. Developing the infrastructure to perform standardized quality improvement is achievable across multiple palliative care settings.

scholarly journals Evolution of the Quality Oncology Practice Initiative Supportive Care Quality Measures Portfolio and Conformance at a Veterans Affairs Medical Center

2013 ◽  
Vol 9 (3) ◽  
pp. e86-e89 ◽  
Author(s):  
Ryan D. Nipp ◽  
Michael J. Kelley ◽  
Christina D. Williams ◽  
Arif H. Kamal
Keyword(s):  
Quality Improvement ◽  
Supportive Care ◽  
Medical Center ◽  
Quality Measures ◽  
Veterans Affairs ◽  
Care Quality ◽  
Processes Of Care ◽  
Treatment Processes ◽  
Standardized Documentation ◽  
Oncology Practice

Most Quality Oncology Practice Initiative quality measures assess diagnosis or treatment processes of care and not supportive care. The authors demonstrate the necessity for standardized documentation methods and quality improvement efforts that remain commensurate with the increasing portfolio of supportive care measures.

scholarly journals Conformance With Supportive Care Quality Measures Is Associated With Better Quality of Life in Patients With Cancer Receiving Palliative Care

2013 ◽  
Vol 9 (3) ◽  
pp. e73-e76 ◽  
Author(s):  
Arif H. Kamal ◽  
Janet Bull ◽  
Charles S. Stinson ◽  
Debra L. Blue ◽  
Amy P. Abernethy
Keyword(s):  
Palliative Care ◽  
Patient Outcomes ◽  
Assessment Tool ◽  
Quality Measures ◽  
Care Quality ◽  
Quality Data ◽  
Patients With Cancer ◽  
Data Assessment ◽  
The Relationship

The authors used a quality data assessment tool to examine the relationship between conformance with palliative care quality measures and patient outcomes.

Evaluation of spiritual needs assessments in oncology palliative care: Results of an improvement project.

2015 ◽  
Vol 33 (29_suppl) ◽  
pp. 161-161
Author(s):  
Sarah Thirlwell ◽  
Valerie Storms ◽  
Mareda Kennedy ◽  
Diane G. Portman
Keyword(s):  
Palliative Care ◽  
Spiritual Care ◽  
Well Being ◽  
Care Quality ◽  
Quality Data ◽  
Evidence Based ◽  
Oncology Patients ◽  
Improvement Project ◽  
Spiritual Assessment ◽  
National Quality

161 Background: Addressing all facets of serious illness requires attention to patients’ spiritual concerns. At our Cancer Center, we sought to ensure that palliative care (PC) inpatients received evidence-based spiritual care. Methods: Chaplaincy Care, Supportive Care Medicine, and Quality and Safety Departments partnered to improve spiritual care using an iterative Plan-Do-Check-Act Cycle approach. Evidence-based spiritual practices were defined in accordance with the Association of Professional Chaplains and Clinical Practice Guidelines for Quality PC of the National Consensus Project. As a member of the Global Palliative Care Quality Alliance, we also used the web-based Quality Data Collection Tool (QDACT) to guide spiritual assessment. Electronic health record templates were revised to support complete and timely documentation. We monitored performance based on National Quality Forum Measure #1647 for discussion of spiritual/religious concerns. Performance was reviewed monthly by Leadership and with the Chaplaincy Staff. Opportunities to improve performance were discussed and adjustments in practice were made. Results: A total of 1609 oncology patients (average of 89/month) were seen by the inpatient PC team from November 2013–April 2015. With transparent performance reporting and resolution of barriers to spiritual assessment, an increase from 36 to 96% was noted for the percentage of patients with documented spiritual or religious concerns. Spiritual assessment using QDACT indicated that most patients report high spiritual well-being, spiritual peace, and a religious affiliation. Conclusions: As the result of our efforts, the majority of PC oncology patients at our center now have assessment and documentation of spiritual and religious concerns. A team-based approach to quality improvement successfully fostered the integration of spiritual care into oncology palliative care. [Table: see text]

Utilization of an electronic medical record trigger to promote palliative care consultation in ambulatory oncology.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18201-e18201
Author(s):  
Sherri L. Rauenzahn ◽  
Susanne Schmidt ◽  
Nazneen Ali ◽  
Laura LaNiel Tenner
Keyword(s):  
Palliative Care ◽  
Supportive Care ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Symptom Burden ◽  
Symptom Assessment ◽  
Cost Of Care ◽  
Ambulatory Oncology ◽  
Edmonton Symptom Assessment Scale ◽  
The Impact

e18201 Background: Research insupportive care demonstrates improvements in overall survival, quality of life, symptom management, and reductions in the cost of care. Despite the American Society of Clinical Oncology recommendation for early concurrent supportive care in patients with advanced cancer and high symptom burden, integrating supportive services is challenging. Our aims were to 1) implement an electronic medical record (EMR) provider alert of high symptom burden based on Edmonton Symptom Assessment Scale (ESAS) criteria and 2) determine the impact an alert has on supportive service referrals. Methods: ESAS scores were implemented in medical ambulatory oncology clinics to quantitatively assess symptom burden. An EMR alert was programmed for a total ESAS score > 30 and any single response of ≥9 to capture approximately 15% of our high symptom burden patient population. The provider could elect to accept the alert placing an order for palliative consultation or decline the prompt. Referral rates and symptom assessment scores were followed as metrics for EMR alert efficiency. Results: Over 10 months, 9,710 patient visits used the ESAS system resulting in 7,707 fully completed ESAS scores (79.4% completion rate). There were 78 total consults to palliative care, a referral rate of less than 1% of the population, which was unchanged from prior to trigger implementation. Of the total completed ESAS forms, the trigger alerted 686 times (8.9% of patient visits) with only 55 of those triggers leading to a supportive care referral (8.0%). Conclusions: This project highlights the challenges of an EMR based alert system and the need for continued efforts to improve supportive care referrals through provider education and tool implementation. [Table: see text]

Development of an electronic point-of-care quality monitoring system for palliative care.

2012 ◽  
Vol 30 (34_suppl) ◽  
pp. 291-291
Author(s):  
Arif Kamal ◽  
Janet Bull ◽  
Amy Pickar Abernethy
Keyword(s):  
Palliative Care ◽  
User Interface ◽  
Data Collection ◽  
Point Of Care ◽  
Quality Measures ◽  
Care Quality ◽  
Quality Monitoring ◽  
Quality Data ◽  
Usability Study ◽  
Feasibility Testing

291 Background: Most current quality monitoring programs involve retrospective, manual data collection. These are inherently limited by accuracy issues and do not integrate well with national efforts to integrate electronic data documentation in all parts of medical practice. We aimed to build and test a prospective system for continuous quality monitoring in palliative care. Methods: Within a four-organization, academic/community quality consortium, we first conducted a focus group to inventory characteristics of an effective system. Then, with an interdisciplinary team of providers informatics, data security, and software programmers, we created an electronic solution for quality data collection and reporting. A usability study with think-aloud protocols followed using twenty providers and two mock cases across paper, laptop, and tablet computer platforms. Finally, a feasibility test assessing satisfaction, burden, and logistical issues was conducted. Results: Identified priorities for a proposed system were: 1. Use of information technology (IT); 2. Point-of-care use; and 3. Immediate, provider-level reporting on quality conformance. A previous systematic review of quality measures informed the development of a 92 item dataset comprised of variables drawn from validated clinical instruments and aligned with the National Consensus Project quality domains. To foster electronic, point-of-care data capture, the Quality Data Collection Tool (QDACT) user interface was then developed. Use at point-of-care in community-based palliative care settings can inform 82% (125) of identified relevant quality measures; a color-code reminder system provides immediate conformance feedback. The usability study demonstrated high satisfaction with electronic platforms, less than 15 minutes for completion, and a low error rate. Feasibility testing across 572 patient encounters demonstrated high acceptability and further improvements to the user interface. Feedback from an additional cycle of feasibility testing will inform further changes. Conclusions: Electronic systems that can integrate point-of-care quality monitoring and clinical assessments are buildable and usable in palliative care.

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