Chasm Between Cancer Quality Measures and Electronic Health Record Data Quality.

PURPOSE: The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) requires eligible clinicians to report clinical quality measures (CQMs) in the Merit-Based Incentive Payment System (MIPS) to maximize reimbursement. To determine whether structured data in electronic health records (EHRs) were adequate to report MIPS CQMs, EHR data aggregated by ASCO's CancerLinQ platform were analyzed. MATERIALS AND METHODS: Using the CancerLinQ health technology platform, 19 Oncology MIPS (oMIPS) CQMs were evaluated to determine the presence of data elements (DEs) necessary to satisfy each CQM and the DE percent population with patient data (fill rates). At the time of this analysis, the CancerLinQ network comprised 63 active practices, representing eight different EHR vendors and containing records for more than 1.63 million unique patients with one or more malignant neoplasms (1.73 million cancer cases). RESULTS: Fill rates for the 63 oMIPS-associated DEs varied widely among the practices. The average site had at least one filled DE for 52% of the DEs. Only 35% of the DEs were populated for at least one patient record in 95% of the practices. However, the average DE fill rate of all practices was 23%. No data were found at any practice for 22% of the DEs. Since any oMIPS CQM with an unpopulated DE component resulted in an inability to compute the measure, only two (10.5%) of the 19 oMIPS CQMs were computable for more than 1% of the patients. CONCLUSION: Although EHR systems had relatively high DE fill rates for some DEs, underfilling and inconsistency of DEs in EHRs render automated oncology MIPS CQM calculations impractical.

Multiscale-omic assessment of EWSR1-NFATc2 fusion positive sarcomas identifies the mTOR pathway as a potential therapeutic target.

Sarcomas harboring EWSR1-NFATc2 fusions have historically been categorized and treated as Ewing sarcoma. Emerging evidence suggests unique molecular characteristics and chemotherapy sensitivities in EWSR1-NFATc2 fusion positive sarcomas. Comprehensive genomic profiles of 1024 EWSR1 fusion positive sarcomas, including 14 EWSR1-NFATc2 fusions, were identified in the FoundationCore® database. Additional data from the Gene Expression Omnibus, the Genomics of Drug Sensitivity in Cancer and The Cancer Genome Atlas datasets were included for analysis. EWSR1-NFATc2 fusion positive sarcomas were genomically distinct from traditional Ewing sarcoma and demonstrated upregulation of the mTOR pathway. We also present a case of a 58-year-old male patient with metastatic EWSR1-NFATc2 fusion positive sarcoma who achieved 47 months of disease stabilization when treated with combination mTOR and VEGF inhibition. EWSR1-NFATc2 fusion positive sarcomas are molecularly distinct entities with overactive mTOR signaling; which may be therapeutically targetable. These findings support the use of precision medicine in the Ewing family of tumors.

The Impact of Big Data Research on Practice, Policy, and Cancer Care.

The concept of "big data" research-the aggregation and analysis of biologic, clinical, administrative, and other data sources to drive new advances in biomedical knowledge-has been embraced by the cancer research enterprise. Although much of the conversation has concentrated on the amalgamation of basic biologic data (e.g., genomics, metabolomics, tumor tissue), new opportunities to extend potential contributions of big data to clinical practice and policy abound. This article examines these opportunities through discussion of three major data sources: aggregated clinical trial data, administrative data (including insurance claims data), and data from electronic health records. We will discuss the benefits of data use to answer key oncology practice and policy research questions, along with limitations inherent in these complex data sources. Finally, the article will discuss overarching themes across data types and offer next steps for the research, practice, and policy communities. The use of multiple sources of big data has the promise of improving knowledge and providing more accurate data for clinicians and policy decision makers. In the future, optimization of machine learning may allow for current limitations of big data analyses to be attenuated, thereby resulting in improved patient care and outcomes.

Prospective Decision Analysis Study of Clinical Genomic Testing in Metastatic Breast Cancer: Impact on Outcomes and Patient Perceptions.

PURPOSE: To evaluate the impact of targeted DNA sequencing on selection of cancer therapy for patients with metastatic breast cancer (MBC). PATIENTS AND METHODS: In this prospective, single-center, single-arm trial, patients with MBC were enrolled within 10 weeks of starting a new therapy. At enrollment, tumor samples underwent next-generation sequencing for any of 315 cancer-related genes to high depth (> 500×) using FoundationOne CDx. Sequencing results were released to providers at the time of disease progression, and physician treatment recommendations were assessed via questionnaire. We evaluated three prespecified questions to assess patients' perceptions of genomic testing. RESULTS: In all, 100 patients underwent genomic testing, with a median of five mutations (range, 0 to 13 mutations) detected per patient. Genomic testing revealed one or more potential therapies in 98% of patients (98 of 100), and 60% of patients (60 of 100) had one or more recommended treatments with level I/II evidence for actionability. Among the 94 genomic text reports that were released, there was physician questionnaire data for 87 patients (response rate, 92.6%) and 31.0% of patients (27 of 87) had treatment change recommended by their physician. Of these, 37.0% (10 of 27) received the treatment supported by genomic testing. We did not detect a statistically significant difference in time-to-treatment failure (log-rank P = .87) or overall survival (P = .71) among patients who had treatment change supported by genomic testing versus those who had no treatment change. For patients who completed surveys before and after genomic testing, there was a significant decrease in confidence of treatment success, specifically among patients who did not have treatment change supported by genomic testing (McNemar's test of agreement P = .001). CONCLUSION: In this prospective study, genomic profiling of tumors in patients with MBC frequently identified potential treatments and resulted in treatment change in a minority of patients. Patients whose therapy was not changed on the basis of genomic testing seemed to have a decrease in confidence of treatment success.

Identifying Health Information Technology Needs of Oncologists to Facilitate the Adoption of Genomic Medicine: Recommendations From the 2016 American Society of Clinical Oncology Omics and Precision Oncology Workshop.

At the ASCO Data Standards and Interoperability Summit held in May 2016, it was unanimously decided that four areas of current oncology clinical practice have serious, unmet health information technology needs. The following areas of need were identified: 1) omics and precision oncology, 2) advancing interoperability, 3) patient engagement, and 4) value-based oncology. To begin to address these issues, ASCO convened two complementary workshops: the Omics and Precision Oncology Workshop in October 2016 and the Advancing Interoperability Workshop in December 2016. A common goal was to address the complexity, enormity, and rapidly changing nature of genomic information, which existing electronic health records are ill equipped to manage. The subject matter experts invited to the Omics and Precision Oncology Workgroup were tasked with the responsibility of determining a specific, limited need that could be addressed by a software application (app) in the short-term future, using currently available genomic knowledge bases. Hence, the scope of this workshop was to determine the basic functionality of one app that could serve as a test case for app development. The goal of the second workshop, described separately, was to identify the specifications for such an app. This approach was chosen both to facilitate the development of a useful app and to help ASCO and oncologists better understand the mechanics, difficulties, and gaps in genomic clinical decision support tool development. In this article, we discuss the key challenges and recommendations identified by the workshop participants. Our hope is to narrow the gap between the practicing oncologist and ongoing national efforts to provide precision oncology and value-based care to cancer patients.

Outcome assessment of hand function after radial artery harvesting for coronary artery bypass.

The radial artery has gained widespread acceptance as a conduit for coronary artery bypass. Advantages include minimal donor site discomfort, ease of handling, excellent early patency rates, and the possibility of freedom from late conduit atherosclerosis. Although most series describe minimal morbidity, a significant incidence of radial sensory neuropathy and isolated instances of hand claudication and ischemia have been reported. We performed an outcome study utilizing the Short Form-36, the Upper Limb-Disabilities of Arm, Shoulder and Hand, and a modified self-administered hand diagram to compare 288 patients undergoing coronary artery bypass utilizing the radial artery with a control group of 174 patients undergoing coronary artery bypass without the radial artery. The data were analyzed by the t test for continuous variables and the chi-square test for categorical variables, and subsequently a multivariate regression model was constructed. No patients developed hand claudication or ischemia. Although there was an incidence of radial sensory neuropathy of 9.9% associated with radial artery harvest, it was not significantly higher than the incidence in the control group (5.2%, p =.16). Intrinsic patient factors such as obesity, age, diabetes, and peripheral vascular disease were the principal determinants of overall health and quality of life issues.

New Centers for Disease Control and Prevention's guidelines on HIV counseling and testing for the general population and pregnant women.

We review two new HIV counseling and testing guidelines by the U.S. Centers for Disease Control and Prevention. The guidelines, which address the general population and pregnant women, reflect an important shift in the goals and methods of counseling and testing that has widespread implications. The guidelines' defining characteristic is the greater emphasis on increasing the numbers of people knowing their HIV status while maintaining the historical focus on extensive pretest counseling and consent procedures. We discuss the policy and practice implications by evaluating five factors: 1) Will the guidelines be adopted? 2) Will at-risk and infected individuals be identified for counseling and testing? 3) Will health care providers offer counseling and testing and patients accept counseling and testing, obtain their test results, seek treatment, and change risky behaviors? 4) Will the guidelines be relatively cost-effective? 5) Will the guidelines be compatible with ethical standards?

Impact of the U.S. panel on cost-effectiveness in health and medicine.

OBJECTIVE: To examine whether recommendations made by the U.S. Panel on Cost-Effectiveness in Health and Medicine (Panel Report) have been associated with changes in how cost-effectiveness analyses are conducted. METHODS: We examined whether studies published after the Panel Report was issued and which cited the Panel Report were more likely to follow its recommendations on discounting, quality-adjusted life years (QALYs), and incremental ratios than (1) studies published before the Panel Report, and (2) studies published after the Panel Report but that did not cite the Panel Report. We used the Science Citation Index to identify all studies citing the Panel Report that were also empirical, cost-effectiveness analyses (n=18). We randomly selected two groups for comparison (N=54). Studies were compared using contingency tables. RESULTS: Significantly more studies that cited the Panel Report used a 3% discount rate than did post-report comparison studies (p=0.03) and pre-report comparison studies (p=0.03). There was a nonsignificant trend for studies citing the Panel Report to be more likely to use QALYs and incremental ratios (range of p=0.11 to p=0.20). CONCLUSIONS: We found evidence that the Panel Report had an impact on practice. However, 31% of the studies citing the Panel Report did not follow the recommendation to use a 3% discount rate, and only 28% followed all three recommendations.