FY 2024 Annual Performance Plan and Report - Strategic Goal 4: Objective 4.1

Fiscal Year 2024
Released March, 2023

Topics on this page: Objective 4.1: Improve the design, delivery, and outcomes of HHS programs by prioritizing science, evidence, and inclusion | Objective 4.1 Table of Related Performance Measures

Objective 4.1: Improve the design, delivery, and outcomes of HHS programs by prioritizing science, evidence, and inclusion

HHS works on strategies to improve the design, delivery, and outcomes of HHS programs by prioritizing science, evidence, and inclusion. The Department leverages stakeholder engagement, communication, and collaboration to build and implement evidence-based interventions and approaches for stronger health, public health, and human services outcomes. ,

The Office of the Secretary leads this objective. All divisions are responsible for implementing programs under this strategic objective. In consultation with OMB, HHS has determined that performance toward this objective is progressing. The narrative below provides a brief summary of progress made and achievements or challenges, as well as plans to improve or maintain performance.

Objective 4.1 Table of Related Performance Measures

Health information technology (health IT) refers to a variety of electronic methods that can be used to manage information about people’s health and health care. Although health IT holds much promise for reducing disparities in populations that are medically underserved by facilitating behavior change and improving quality of health care services and health outcomes, few studies have examined the impact of health IT adoption on improving health outcomes and reducing health disparities among racial and ethnic minority individuals, people of less privileged socioeconomic status, underserved rural populations, and sexual and gender minority populations. Thus, NIH is investing in research to explore the potential of health IT for improving the health of underserved populations and reducing health disparities using technologies such as decision support tools, mobile apps, and new technologies such as artificial intelligence and natural language processing.

In the U.S., Hispanic or Latina women have one of the highest rates of gestational diabetes mellitus (GDM), a major risk factor for developing type 2 diabetes. In FY 2022, NIH-funded investigators launched and began testing the effectiveness of ¡Hola Bebé, Adiós Diabetes!, a mobile app intended to help reduce risk factors for type 2 diabetes in Hispanic or Latina women who experienced GDM in the past five years. Phase 1 of the study offered promising results: Through the eight-week pilot program, participants showed increased self-efficacy for physical activity and reduced their weight. They also provided positive feedback on the app’s personalized action plans, motivational text messages, at-home exercise videos, and recipes. During Phase II, the study experienced delays in recruiting participants due to the COVID-19 pandemic, which prevented the investigators from finishing the study in a timely manner. They are now in the final stage of testing the effectiveness of the app, with 97 participants (out of 150) having completed the study. If successful, the app will offer a culturally-tailored, user-centered, low-cost, and evidence-based intervention to reduce risk factors for developing type 2 diabetes among Hispanic or Latina women with a recent history of GDM.

In FY 2023, NIH willassess the feasibility of using data mining, natural language processing (NLP), and/or other technological advances to improve the health or healthcare for individuals who experience health disparities. In FY 2024, NIH will identify barriers and enhancers to adoption of health information technologies, such as clinical decision aids, from the perspective of physicians who care for populations who experience health disparities.

The most efficient and effective programs often use evidence-based and evidence-informed practices. ACF developed an efficiency measure to gauge progress towards programs’ use of these types of practices. ACF is working closely with the states to promote more rigorous evaluations of their funded programs. Over time, ACF expects to increase the number of effective programs and practices that are implemented, thereby maximizing the impact and efficiency of Community-Based Child Abuse Prevention (CBCAP) funds. For the purposes of this efficiency measure, ACF defines evidence-based and evidence-informed programs and practices along a continuum, which includes the following four categories of programs or practices: Emerging and Evidence Informed; Promising; Supported; and Well-Supported. Programs determined to fall within specified program parameters will be considered to be implementing “evidence-informed” or “evidence-based” practices (collective referred to as “EBPs”), as opposed to programs that have not been evaluated using any set criteria. The funding directed towards these types of programs (weighted by EBP level) will be calculated over the total amount of CBCAP funding used for direct service programs to determine the percentage of total funding that supports evidence-based and evidence-informed programs and practices. A baseline of 27 percent was established for this measure in FY 2006. The target of a three percentage point annual increase in the amount of funds devoted to evidence-based practice was selected as a meaningful increment of improvement that takes into account the fact that this is the first time that the program has required grantees to target their funding towards evidence-based and evidence-informed programs, and it will take time for states to adjust their funding priorities to meet these new requirements.

In general, the majority of CBCAP funding is directed toward EBPs. Fiscal year 2018 represented an increase with grantees reporting 61.5 percent of funds being directed at EBPs. Fiscal year 2019 also saw an increase with grantees reporting 62.8 percent of funds directed toward EBPs. Despite this increase, it did not meet the target of 64.5 percent. In FY 2020, however, the percentage spent on EBPs increased to 66.3 percent, exceeding the target of 65.8 percent. In FY 2021, the target of 69.3 was not met, as states reported 61.4 percent of funds were used for evidence-informed and evidence-based programs. Based on report narratives and engagement with grant recipients, ACF believes that impacts of the public health pandemic have influenced this decrease. For example, ACF experienced increased requests from grant recipients to use CBCAP funds to address concrete needs (e.g. housing, food, clothing, child care assistance, etc.), which often do not have as much research demonstrating effectiveness. States further reported decreased administration of evidence-informed and evidence-based programs during the pandemic due to restrictions with in-person interactions, as well as limited capacity, resulting from increased resignations from personnel. While CBCAP programs were able to carry out many evidence-informed and evidence-baesd programs virtually, they reported that it still had decreased from pre-pandemic levels. Moreover, ACF has worked to tailor training and technical assistance activities to address these challenges and increase state capacity to use funds for evidence-based and evidence-informed programs. Efforts will further continue to promote evaluation and innovation, so as to expand the availability and use of evidence-informed and evidence-based programs over time and continue to set the target of an annual three percentage point increase over the prior year