The Moore Foundation is providing funding for eight proposals for new measure concepts and approaches for clinical quality measures targeting diagnostic excellence. The foundation announced this new funding opportunity in 2019 as part of its Diagnostic Excellence Initiative, and this will be the second cohort of individuals to receive funding.
Twelve million Americans experience a diagnostic error each year. It is likely that each of us will experience a diagnostic error in our lifetime. Delayed or missed diagnoses result in delays in treatment, allow undiagnosed conditions to persist or even progress, and worsen outcomes. The development of clinical quality measures for diagnosis will provide clinicians and medical institutions the ability to track and measure their success and failure rates and provide them with an opportunity to solve for deficiencies and implement improvements.
The foundation’s Diagnostic Excellence Initiative aims to reduce harm from erroneous or delayed diagnoses. Over the last few decades, significant progress has been made in medication and safety therapeutics, but work has been slow to address diagnosis. This initiative, and the projects of the selected grantees will help move us into the future of new diagnostic strategies.
“The future of diagnosis is rapidly evolving, and these new diverse and varied ideas for measurement will be a great indicator of exciting developments to come,” said Karen Cosby, M.D., program officer for the Diagnostic Excellence Initiative. “We look forward to seeing great results from this second cohort of fellows.”
A full list of awardees can be found below.
Awardees
Patricia C. Dykes, Ph.D., RN, FAAN, FACMI
Brigham and Women’s Hospital & Harvard Medical School
@pdykesPatti
Diagnosis of Venous Thromboembolism (VTE) in Primary Care: A data science and machine learning approach
Venous thromboembolism (VTE) is a commonly missed or delayed diagnosis associated with a high 30-day mortality rate. We propose using electronic health record data to measure VTE diagnostic delay, and machine learning methods to develop clinical decision support to alert primary care providers of patients at risk for delayed VTE diagnosis. We hope that together, the clinical decision support and electronic clinical quality measures will improve clinical practice and reduce delays in VTE diagnosis.
Robert El-Kareh, M.D., MPH, MS
University of California, San Diego
Longitudinal Analysis of Codes to Identify Diagnostic Opportunities (LUCID)
We are applying several techniques to analyze patients' diagnostic codes over time related to three conditions at risk for diagnostic-related harm (venous thromboembolism, colorectal cancer, and spinal abscess). Our goal is to develop methods to better identify cases with diagnostic opportunities for improvement. Our proposed measure is the proportion of these cases that undergo a structured diagnostic case review to learn from this information at the organizational level.
Kelly Gleason, Ph.D., RN
Johns Hopkins School of Nursing
@KTG_RN
Patient-reported Measure Sets for Diagnostic Excellence
Our project seeks to develop and validate a patient-reported measure set of diagnostic excellence. A diagnostic performance measure that gathers information directly from the patient helps assess both the accuracy of the diagnosis (is the diagnosis correct) as well as the patient’s understanding of their diagnosis and how effectively it was communicated to them. Creating this feedback loop centered on the most important person in the diagnostic process – the patient – will provide critical information to achieving diagnostic excellence.
Barbara Jones, M.D., MSC
University of Utah, Salt Lake City
@BarbarajonesMD
Measuring and Improving Diagnostic Excellence in Pneumonia
Pneumonia diagnosis is often uncertain and requires deliberate effort and practice. However, providers rarely receive the feedback they need to excel. This project aims to develop a measure that accommodates for uncertainty, provides meaningful feedback to support excellence, and reduces fragmentation of the diagnostic narrative.
Angela Kennedy, D.C., MBA
American Society of Clinical Oncology
Collaborating with Conquer Cancer, the ASCO Foundation
@ASCO, @ConquerCancerFd
Biomarker and Genomic Testing to Inform Personalized Cancer Therapy
Tumor mutation impacts therapeutic decision making, offers prognostic information to cancer patients, and informs the need for genetic risk evaluation, counseling, or testing for patients’ first- and second-degree relatives. Personalized selection of cancer drugs based on the presence of actionable mutations can optimize patient response to treatment. This project aims to develop two measures addressing the underutilization and workflow variations for biomarker and genomic testing: BRAF testing conducted for prognostic stratification in metastatic colorectal cancer, and germline testing conducted at diagnosis for ovarian cancer.
Katharine Rendle, Ph.D., MSW, MPH
Anil Vachani, M.D., MS
University of Pennsylvania
Collaborating with Kaiser Permanente Colorado, Kaiser Permanente Hawaii, Henry Ford Health System, Marshfield Clinic, and Cleveland Clinic
@kate_rendle
Improving Diagnostic Quality and Safety in Lung Cancer Screening
Lung cancer screening can reduce cancer-specific mortality, but is also associated with harms that may be heightened or variable across community settings. Presently, there are no accepted quality measures for evaluating lung cancer screening. Utilizing a robust electronic health record dataset collected from diverse healthcare systems, this project seeks to develop novel quality measures that address effectiveness and safety within the screening diagnostic process. The measures are designed to help improve quality and equity of care across delivery settings.
Alex Sandhu, M.D., MS
Stanford University
@ATSandhu
Missed Outpatient Diagnosis of Heart Failure
Timely diagnosis of heart failure is important to initiate guideline-directed therapy and reduce heart failure morbidity. However, patients with new heart failure are frequently not diagnosed until decompensation and presentation to the emergency department. We set out to develop a quality measure promoting earlier outpatient diagnosis of heart failure prior to clinical decompensation.
Jennifer M Weiss, M.D., MS
University of Wisconsin School of Medicine and Public Health
Measuring Modality-specific Interval Colorectal Cancer Rates Across Healthcare Systems
The goal of this project is to expand existing definitions of interval colorectal cancers, which are cancers identified after a negative screening or surveillance exam and before the date of the next recommended exam. The definitions would be expanded to include all screening modalities (colonoscopy, CT colonography, flexible sigmoidoscopy, multitarget stool DNA test, and FIT/FOBT). We will develop a measurement implementation strategy with standards for reporting that can be easily adopted and compared across healthcare systems.
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