Assessment of Regional Variability in COVID-19 Outcomes Among Patients With Cancer in the United States.

Importance: The COVID-19 pandemic has had a distinct spatiotemporal pattern in the United States. Patients with cancer are at higher risk of severe complications from COVID-19, but it is not well known whether COVID-19 outcomes in this patient population were associated with geography. Objective: To quantify spatiotemporal variation in COVID-19 outcomes among patients with cancer. Design, Setting, and Participants: This registry-based retrospective cohort study included patients with a historical diagnosis of invasive malignant neoplasm and laboratory-confirmed SARS-CoV-2 infection between March and November 2020. Data were collected from cancer care delivery centers in the United States. Exposures: Patient residence was categorized into 9 US census divisions. Cancer center characteristics included academic or community classification, rural-urban continuum code (RUCC), and social vulnerability index. Main Outcomes and Measures: The primary outcome was 30-day all-cause mortality. The secondary composite outcome consisted of receipt of mechanical ventilation, intensive care unit admission, and all-cause death. Multilevel mixed-effects models estimated associations of center-level and census division-level exposures with outcomes after adjustment for patient-level risk factors and quantified variation in adjusted outcomes across centers, census divisions, and calendar time. Results: Data for 4749 patients (median [IQR] age, 66 [56-76] years; 2439 [51.4%] female individuals, 1079 [22.7%] non-Hispanic Black individuals, and 690 [14.5%] Hispanic individuals) were reported from 83 centers in the Northeast (1564 patients [32.9%]), Midwest (1638 [34.5%]), South (894 [18.8%]), and West (653 [13.8%]). After adjustment for patient characteristics, including month of COVID-19 diagnosis, estimated 30-day mortality rates ranged from 5.2% to 26.6% across centers. Patients from centers located in metropolitan areas with population less than 250 000 (RUCC 3) had lower odds of 30-day mortality compared with patients from centers in metropolitan areas with population at least 1 million (RUCC 1) (adjusted odds ratio [aOR], 0.31; 95% CI, 0.11-0.84). The type of center was not significantly associated with primary or secondary outcomes. There were no statistically significant differences in outcome rates across the 9 census divisions, but adjusted mortality rates significantly improved over time (eg, September to November vs March to May: aOR, 0.32; 95% CI, 0.17-0.58). Conclusions and Relevance: In this registry-based cohort study, significant differences in COVID-19 outcomes across US census divisions were not observed. However, substantial heterogeneity in COVID-19 outcomes across cancer care delivery centers was found. Attention to implementing standardized guidelines for the care of patients with cancer and COVID-19 could improve outcomes for these vulnerable patients.

Association of Convalescent Plasma Therapy With Survival in Patients With Hematologic Cancers and COVID-19.

Importance: COVID-19 is a life-threatening illness for many patients. Prior studies have established hematologic cancers as a risk factor associated with particularly poor outcomes from COVID-19. To our knowledge, no studies have established a beneficial role for anti-COVID-19 interventions in this at-risk population. Convalescent plasma therapy may benefit immunocompromised individuals with COVID-19, including those with hematologic cancers. Objective: To evaluate the association of convalescent plasma treatment with 30-day mortality in hospitalized adults with hematologic cancers and COVID-19 from a multi-institutional cohort. Design, Setting, and Participants: This retrospective cohort study using data from the COVID-19 and Cancer Consortium registry with propensity score matching evaluated patients with hematologic cancers who were hospitalized for COVID-19. Data were collected between March 17, 2020, and January 21, 2021. Exposures: Convalescent plasma treatment at any time during hospitalization. Main Outcomes and Measures: The main outcome was 30-day all-cause mortality. Cox proportional hazards regression analysis with adjustment for potential confounders was performed. Hazard ratios (HRs) are reported with 95% CIs. Secondary subgroup analyses were conducted on patients with severe COVID-19 who required mechanical ventilatory support and/or intensive care unit admission. Results: A total of 966 individuals (mean [SD] age, 65 [15] years; 539 [55.8%] male) were evaluated in this study; 143 convalescent plasma recipients were compared with 823 untreated control patients. After adjustment for potential confounding factors, convalescent plasma treatment was associated with improved 30-day mortality (HR, 0.60; 95% CI, 0.37-0.97). This association remained significant after propensity score matching (HR, 0.52; 95% CI, 0.29-0.92). Among the 338 patients admitted to the intensive care unit, mortality was significantly lower in convalescent plasma recipients compared with nonrecipients (HR for propensity score-matched comparison, 0.40; 95% CI, 0.20-0.80). Among the 227 patients who required mechanical ventilatory support, mortality was significantly lower in convalescent plasma recipients compared with nonrecipients (HR for propensity score-matched comparison, 0.32; 95% CI, 0.14-0.72). Conclusions and Relevance: The findings of this cohort study suggest a potential survival benefit in the administration of convalescent plasma to patients with hematologic cancers and COVID-19.

Impact of Merit-Based Immigration Policies on Brain Drain From Low- and Middle-Income Countries.

PURPOSE: Brain drain is the migration of educated and skilled individuals from a less developed region or country to a more economically established one. The Trump administration proposed a merit-based immigration plan. This article addresses its potential impact on health care delivery in low- and middle-income countries (LMICs) and their preparedness to deal with it. MATERIALS AND METHODS: Data on immigration policies, numbers of international medical graduates practicing in high-income countries (HICs), various scientific exchange methods, and efforts for capacity building in LMICs. RESULTS: Talented individuals seek to advance their knowledge and skills, and may stay in HICs because of greater rewards and opportunities. HICs also rely on immigrant international medical graduates to supplement their physician workforces. CONCLUSION: Ambitious individuals from LMICs need and should have opportunities to advance their education and training in more advanced countries. LMICs should increase their educational efforts, research capabilities, infrastructures, and living conditions to better serve their own populations and reduce their brain drain phenomenon.

Challenges in assessing the clinical utility and economic value of immune checkpoint inhibitor therapies of Cancer.

Advances in the immunotherapy of cancer have prolonged survival for cancer patients, but the clinical and financial impact of treatments must be considered in determining the overall clinical utility and economic value of therapeutic agents. Quality-adjusted life years and incremental cost-effectiveness ratios are clinical and economic metrics that can be used to evaluate the value of immune checkpoint inhibitors. This Commentary provides perspective on the limitations, benefits, and potential enhancement of this approach to support value-based medicine.

Quality Improvement at the Health System Level: Measurement, Risk Stratification, Disparity Populations, and Governance.

Value-based health systems encompass a range of care-delivery models from small independent practices to large integrated delivery systems and academic medical centers. In addition, public and private payers, federal and state agencies, professional societies, and not-for-profit organizations collect and analyze data for quality and value improvement in health care-delivery outcomes. In this article, we review the multidimensional aspects of data collection, aggregation, analysis, and use for and by value-based health systems.

Global Health Initiatives of the International Oncology Community.

Cancer has become one of the leading causes of morbidity and mortality in low- and middle-income countries (LMICs), where 60% of the world's total new cases are diagnosed. The challenge for effective control of cancer is multifaceted. It mandates integration of effective cancer prevention, encouraging early detection, and utilization of resource-adapted therapeutic and supportive interventions. In the resource-constrained setting, it becomes challenging to deliver each service optimally, and efficient allocation of resources is the best way to improve the outcome. This concept was translated into action through development of resource-stratified guidelines, pioneered by the Breast Health Global Initiative (BHGI), and later adopted by most oncology societies in an attempt to help physicians deliver the best possible care in a limited-resource setting. Improving outcome entails collaboration between key stakeholders, including the pharmaceutical industry, local and national health authorities, the World Health Organization (WHO), and other nonprofit, patient-oriented organizations. Therefore, we started to observe global health initiatives-led by ASCO, the Union for International Cancer Control (UICC), and the WHO-to address these challenges at the international level. This article discusses some of these initiatives.

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.

Knowledge bases, clinical decision support systems, and rapid learning in oncology.

One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care.

Development, implementation, and initial evaluation of a foundational open interoperability standard for oncology treatment planning and summarization.

OBJECTIVE: Develop and evaluate a foundational oncology-specific standard for the communication and coordination of care throughout the cancer journey, with early-stage breast cancer as the use case. MATERIALS AND METHODS: Owing to broad uptake of the Health Level Seven (HL7) Consolidated Clinical Document Architecture (C-CDA) by health information exchanges and large provider organizations, we developed an implementation guide in congruence with C-CDA. The resultant product was balloted through the HL7 process and subsequently implemented by two groups: the Health Story Project (Health Story) and the Athena Breast Health Network (Athena). RESULTS: The HL7 Implementation Guide for CDA, Release 2: Clinical Oncology Treatment Plan and Summary, DSTU Release 1 (eCOTPS) was successfully balloted and published as a Draft Standard for Trial Use (DSTU) in October 2013. Health Story successfully implemented the eCOTPS the 2014 meeting of the Healthcare Information and Management Systems Society (HIMSS) in a clinical vignette. During the evaluation and implementation of eCOPS, Athena identified two practical concerns: (1) the need for additional CDA templates specific to their use case; (2) the many-to-many mapping of Athena-defined data elements to eCOTPS. DISCUSSION: Early implementation of eCOTPS has demonstrated successful vendor-agnostic transmission of oncology-specific data. The modularity enabled by the C-CDA framework ensures the relatively straightforward expansion of the eCOTPS to include other cancer subtypes. Lessons learned during the process will strengthen future versions of the standard. CONCLUSION: eCOTPS is the first oncology-specific CDA standard to achieve HL7 DSTU status. Oncology standards will improve care throughout the cancer journey by allowing the efficient transmission of reliable, meaningful, and current clinical data between the many involved stakeholders.

Building a rapid learning health care system for oncology: the regulatory framework of CancerLinQ.

Today is a time of unprecedented opportunity and challenge in health care generally and cancer care in particular. An explosion of scientific knowledge, the rapid introduction of new drugs and technologies, and the unprecedented escalation in the cost of health care challenge physicians to quickly assimilate new information and appropriately deploy new advances while also delivering efficient and high-quality care to a rapidly growing and aging patient population. At the same time, big data, with its potential to drive rapid understanding and innovation, promises to transform the health care industry, as it has many others already. CancerLinQ is an initiative of the American Society of Clinical Oncology (ASCO) and its Institute for Quality, developed to build on these opportunities and address these challenges by collecting information from the electronic health records of large numbers of patients with cancer. CancerLinQ is, first and foremost, a quality measurement and reporting system through which oncologists can harness the depth and power of their patients' clinical records and other data to improve the care they deliver. The development and deployment of CancerLinQ raises many important questions about the use of big data in health care. This article focuses on the US federal regulatory pathway by which CancerLinQ will accept patient records and the approach of ASCO toward stewardship of the information.

The evolution of oncology electronic health records.

Health information technology will transform health care delivery over the coming years. The central element of this will be the electronic health record, maintained by health professionals and linked to other health care providers, patients, and research and population health databases. Support of oncology functionality will necessitate special attention to how electronic health records are constructed, cancer-related data represented within, and clinical decision support tools designed to best support the objectives of quality care and cost-effectiveness. Standardization of functions and software will permit data exchange, leading to enhanced interoperability of systems. The present efforts at establishing oncology-related standards for electronic health records are reviewed.

Principles of Safe Practice Using an Oncology EHR System for Chemotherapy Ordering, Preparation, and Administration, Part 1 of 2.

An outline of broad principles that should be considered when integrating an electronic health record, and in particular, a chemotherapy ordering module, into practice.

Principles of Safe Practice Using an Oncology EHR System for Chemotherapy Ordering, Preparation, and Administration, Part 2 of 2.

Integrating electronic health records into the oncology office, while taking into consideration the principles of electronic health record usage, is a great way to improve the chemotherapy ordering and administration process.