Reducing Unwarranted Oncology Care Variation Across a Clinically Integrated Network: A Collaborative Physician Engagement Strategy

Abstract

PURPOSE: Addressing unwarranted clinical variation in oncology is a high priority for health systems that aspire to ensure consistent levels of high-quality and cost-effective care. Efforts to improve clinical practice and standardize care have proven challenging. Advocate Physician Partners undertook a patient simulation-based practice measurement and feedback project that was focused on breast and lung cancer to engage oncologists in the care standardization process. METHODS: One hundred three medical oncologists cared for online simulated patients using the Clinical Performance and Value platform, receiving feedback on how their care decisions compared with evidence-based guidelines and their peers. We repeated this process every 4 months over six rounds, measuring changes in quality-of-care scores. We then compared simulated patient results with available patient-level claims data. RESULTS: Over the course of the project, overall quality-of-care scores improved 11.9% ( P < .001). Diagnostic accuracy increased 6.7% ( P < .001) and correlated with improved treatment scores, including a nearly 10-percentage point increase in evidence-based chemotherapy regimens ( P = .009) and a 56% increase in addressing palliative needs for patients with late-stage disease ( P < .001). Unnecessary test ordering declined 25% ( P < .001). We compared these results with available patient data and observed concordance with the metastatic imaging workup order rate for early-stage breast cancer. As unnecessary workups declined in the simulations and became more closely aligned with evidence-based guidelines, we saw similar rates of decline in the patient-level data. CONCLUSION: This study demonstrates that an oncology care standardization system that combines simulated patients with serial feedback increases evidence-based and cost-effective clinical decisions in patient simulations and patient-level data.

Factors impacting the time to ovarian cancer diagnosis based on classic symptom presentation in the United States

“…33 Although this has not specifically been examined in ovarian cancer, improved adherence to guideline recommendations may also minimize cost inefficiencies for both patients and the health care system by reducing unnecessary testing, multiple physician visits, and time costs due to delayed care. 32,34 Targeted education on the modified Goff index and other signs and symptoms of ovarian cancer for providers outside of obstetrics and gynecology, reimbursement incentives for adherence to evidence-based guidelines, and expedited referral pathways to gynecologic oncology providers 15 could be ways to improve guideline recommendation adherence and decrease the TTD for ovarian cancer.…”

Mapping of Current Obstacles for Rationalizing Use of Medicines (CORUM) in Europe: Current Situation and Potential Solutions

“…The results of our study point to the use of clinical guidelines as the most important key intervention to enhance RUM (Figure 1). Whilst clinical guidelines have been instrumental in optimizing care and promoting RUM across settings (Ament et al, 2015;Colbeck et al, 2016;Ebben et al, 2018;Brouwers et al, 2019;Niaz et al, 2019;Richards et al, 2019), there are challenges such as regularly updating the guidance or sufficient government or health authority funding for their development and active dissemination in the first place. There can also be concerns with conflicts of interest among guideline developers unless adequately addressed such as the "Wise List" and guidance in Stockholm, Sweden (Gustafsson et al, 2011;Bjorkhem-Bergman et al, 2013;Shnier et al, 2016;DeJong and Steinbrook, 2018;The Lancet, 2019).…”

Independent External Validation of the METSSS Model Predicting Survival After Palliative Radiotherapy

“…It is clear from previous analyses that overtreatment near the end-of-life might cause harm to patients and healthcare systems (3,(18)(19)(20). In this context, support tools that predict relevant outcomes, including but not limited to overall survival, are needed.…”