Malnutrition is a leading cause of morbidity and mortality, especially among older adults. However, diagnosis and treatment of malnutrition in the hospital setting are often overlooked. In recent years, quality improvement (QI) initiatives to increase the assessment and treatment of malnutrition in hospital settings have been implemented and shown to improve both patient health and economic outcomes. The Malnutrition Quality Improvement Initiative (MQii) Toolkit was designed in an effort to support hospitals seeking to implement malnutrition QI initiatives. The Toolkit has been implemented, studied, and updated for optimization of content, adaptability, and usability over several cycles of improvement from 2016-2017 at more than 50 hospital centers in the United States. The result is an open access, customizable, and user-friendly MQii Toolkit that can facilitate the implementation of malnutrition QI initiatives in individual facilities. This article introduces the MQii Toolkit, describes the process by which it was designed and improved, and orients clinical care teams to its use.

261 Background: Acute myeloid leukemia (AML) is a rare, but deadly hematological, disease with 20,830 new cases estimated in 2015 in the United States (US). As new treatments emerge, quality measures (QMs) will become important to assess the value of care. Our aim was to evaluate the current US AML QM landscape. Methods: We reviewed literature and online resources (eg, National Quality Measures Clearinghouse, Centers for Medicare & Medicaid Services, etc.) published within the last 5 years to identify AML-specific and AML-related QMs. All QMs were categorized using a “continuum of care” framework according to the 5 stages of AML: 1) symptom assessment, 2) diagnosis/risk stratification, 3) initial treatment, 4) monitoring/additional treatment, and 5) advanced/late stage care. Quality measures were categorized by the measure type (eg, process or outcome measure) and use by the Centers for Medicare & Medicaid Services (CMS). Results: In total, 30 QMs were identified: 1 leukemia-specific QM and 29 general oncology QMs. The leukemia-specific QM is a clinician-level process measure that evaluates the percentage of patients aged ≥ 18 years with a diagnosis of myelodysplastic syndrome or acute leukemia who had baseline bone marrow cytogenetic testing performed. Among the 29 general QMs: 8 are specific to stem cell transplantation, 13 are specific to chemotherapy, and 8 are general to oncology. Across the AML continuum of care: 2 QMs focus on symptom assessment, 1 supports diagnosis/risk stratification, 11 are for initial treatment, 9 for monitoring/additional treatment, and 7 for late-stage care. Twenty-seven QMs are based on process of care: 1 addresses resource utilization and 2 are outcomes based. The single leukemia-specific QM is used in CMS quality improvement programs, along with 3 other oncology-related QMs. Conclusions: While only one identified QM was specific to leukemia, other general oncology QMs may also apply. Unfortunately, QMs addressing AML-related morbidity and mortality are still lacking. Research into patient-centered communication, shared decision-making, patient-reported outcomes and resource use by AML patients may inform development of new QMs. Sponsorship: This research was funded by Astellas Pharma, Inc.

273 Background: Prostate cancer (PCa) is the leading cancer for men in the United States (US) and identified by the Centers for Medicare & Medicaid Services (CMS) as one of the top 20 high-impact Medicare conditions experienced by beneficiaries. Thus, there is increasing focus by stakeholders to measure and achieve high-value, quality care in PCa. However, quality measurement is particularly difficult in oncology. Our aim was to assess the current landscape of PCa quality measures (QMs) in the US. Methods: Published literature and online resources from the past 5 years were reviewed to identify PCa QMs and general oncology QMs relevant to PCa. PCa QMs were categorized using a “continuum of care” framework across 5 stages: 1) symptom assessment and screening; 2) diagnosis and risk stratification; 3) initial treatment; 4) monitoring and additional treatment; and 5) advanced- or late-stage care. Finally, PCa QMs were evaluated for their type (eg. process, outcomes), and use by CMS. Results: We identified 16 PCa-specific QMs and 20 general oncology QMs relevant to PCa. The majority of PCa QMs were developed by the American Medical Association–Physician Consortium for Performance Improvements (6 measures) and the Michigan Urological Surgery Improvement Collaborative (6 measures). There are 3 QMs for symptom assessment and screening, 5 QMs for diagnosis and risk stratification, 6 QMs for initial treatment, 2 QMs for monitoring and additional treatment, and 0 QMs for advanced- or late-stage care. Fourteen PCa QMs focus on process of care, but only 2 PCa QMs address outcomes. Nine PCa QMs are part of CMS quality improvement programs, 6 of which are reportable through the Michigan Urological Surgery Improvement Collaborative. Three new PCa QMs are under consideration by CMS. Conclusions: We found few PCa QMs that capture outcomes of patient experience or care, and no PCa-specific QMs available for advanced disease and late-stage care, demonstrating a need to better define quality in this setting. Opportunities to increase the focus on innovative, real-world data-generation strategies, such as PCa disease registries that collect clinical outcomes, patient preferences, and comorbidities, may inform stakeholder development and adoption of new QMs in the US.

142 Background: Regional, state, and local variations in cancer care necessitate a more thorough understanding of the key drivers of quality at these levels. In this study, Avalere sought to understand how local quality and health information technology (HIT) infrastructures may influence the quality of care to which a cancer patient has access. Methods: Avalere conducted an analysis of the primary influencers of quality and value in each state, cataloguing over 500 public and private quality improvement organizations, including payers; employer groups; and hospitals and alternative care delivery models, such as accountable care organizations and patient-centered medical homes, among others. Recognizing the critical role that health information technology (HIT) plays in underpinning quality improvement efforts, Avalere also catalogued the primary HIT organizations in each state. From this, Avalere conducted a sub-analysis of those initiatives with a specific focus on cancer care to determine how the number of cancer-related initiatives relates to the sophistication of a region’s or state’s quality and HIT sophistication. Results: Avalere found that the sophistication of the quality and HIT infrastructures varied widely from state-to-state and region-to-region, with some areas being significantly less developed than others. Similarly, the number of cancer-related quality initiatives also varied widely, with fewer initiatives found in areas with less sophisticated quality and HIT infrastructures. In addition, major urban areas tend to have significantly more sophisticated infrastructures—and an associated higher number of cancer-related initiatives—than non-urban areas, regardless of regional or state quality or HIT trends, more generally. Conclusions: While national quality improvement efforts receive the most media attention and funding, patient care, including cancer care, is delivered at the local level. As such, in order to improve the quality and value of care cancer patients receive, it is imperative to understand and improve local quality and HIT infrastructures and the barriers to quality associated therewith. This is particularly important in locales without major urban access, such as found in large parts of the Midwest and West.