As part of a coalition of associations, patient organizations, scientific societies, and research institutions, AACC is calling on Congress to appropriate at least $200 million for the National Center for Health Statistics (NCHS) within the Centers for Disease Control and Prevention (CDC) for 2022. NCHS’s base budget for the government’s 2021 fiscal year is only $25 million.
“The COVID-19 pandemic highlighted the troubling limitations of the nation’s statistical system,” the coalition’s letter to Congress says. “While NCHS was successful in providing critical information to monitor the impacts of the pandemic, the need for major investments to expand on the scope, timeliness, quality, and useability of information was glaringly apparent.”
The letter notes that during the pandemic, problems getting information on healthcare utilization both for COVID-19 and non-COVID-19 related care “confounded the response.”
With increased funding, NCHS could develop partnerships with electronic health record vendors and providers to standardize and share data for monitoring healthcare at the national, state, and local levels, and could improve linkage and integration of the country’s data collection systems. Another goal: expand the use of machine learning and artificial intelligence (AI) to improve data collection and processing. AI could automate the coding of deaths of high public health interest such as those from emerging infectious diseases, which the agency currently has to code manually.
HHS: Sex Discrimination in Healthcare Includes Sexual Orientation, Gender Identity
The Department of Health and Human Services (HHS) announced that the Office for Civil Rights will interpret and enforce Section 1557 of the Affordable Care Act and Title IX’s prohibitions on discrimination based on sex to include discrimination on the basis of sexual orientation or gender identity. This section of the law prohibits discrimination on the basis of race, color, national origin, sex, age, or disability in covered health programs or activities. HHS is making the update in light of the U.S. Supreme Court’s decision in Bostock v. Clayton County and subsequent court decisions.
“The Supreme Court has made clear that people have a right not to be discriminated against on the basis of sex and receive equal treatment under the law, no matter their gender identity or sexual orientation. That’s why today HHS announced it will act on related reports of discrimination,” said HHS Secretary Xavier Becerra.
In its announcement, HHS cited research showing that one quarter of LGBTQ people who faced discrimination postponed or avoided receiving needed medical care for fear of further discrimination.
The Supreme Court’s June 15, 2020 decision held that the Civil Rights Act of 1964 prohibiting employment discrimination based on sex encompasses discrimination based on sexual orientation and gender identity. HHS also noted that it will comply with the Religious Freedom Restoration Act and all other legal requirements.
CMS AI Challenge Awards $1.23 Million for Predicting Health Outcomes
The Centers for Medicare and Medicaid Services (CMS) has chosen ClosedLoop.ai as the $1 million winner in the agency’s artificial intelligence (AI) Health Outcomes Challenge. Healthcare system Geisinger is the runner-up and will receive $230,000. The competition, operated by the CMS Innovation Center in collaboration with the American Academy of Family Physicians and Arnold Ventures, began in 2019 with the goal of accelerating development of AI solutions for predicting patient health outcomes. From an initial group of more than 300 entries, the challenge progressed through several stages, and participants were narrowed down to the top 25 and then seven finalists before selecting the winners.
The contestants had to show that their software predicted unplanned hospital and skilled nursing facility admissions and adverse events, as well as identify beneficiaries at risk of mortality within 12 months. The finalists also had to tackle sources of bias in their solutions that could have the potential to affect health disparities. Finally, CMS also required them to demonstrate how they would be able to easily explain the predictions to clinicians.