CONTEXT: The COVID-19 pandemic exposed governmental public health's outdated information technology and insufficient data science and informatics workforce capacity. The Centers for Disease Control and Prevention's Public Health Informatics Fellowship Program (PHIFP) is well positioned to strengthen public health data science and informatics workforce capacity. PROGRAM: Established in 1996, PHIFP is a 2-year, full-time, on-the-job training program. PHIFP includes a didactic curriculum, applied learning through informatics projects completed at the assigned host site, short-term technical assistance projects, and a final capstone project. EVALUATION: Fellows have learned from and bolstered host site informatics capacity through the development or enhancement of information systems, evaluations, data integration, data visualization, and analysis. Among recent graduates, 54% are employed at Centers for Disease Control and Prevention and 16% are employed at other public health organizations, including local health departments. DISCUSSION: Fellowships such as PHIFP, which recruit and train promising scientists in public health informatics, are important components of efforts to strengthen public health workforce capacity.

CONTEXT: Data can guide decision-making to improve the health of communities, but potential for use can only be realized if public health professionals have data science skills. However, not enough public health professionals possess the quantitative data skills to meet growing data science needs, including at the Centers for Disease Control and Prevention (CDC). PROGRAM: The Data Science Upskilling (DSU) program increases data science literacy among staff and fellows working and training at CDC. The DSU program was established in 2019 as a team-based, project-driven, on-the-job applied upskilling program. Learners, within interdisciplinary teams, use curated learning resources to advance their CDC projects. The program has rapidly expanded from upskilling 13 teams of 31 learners during 2019-2020 to upskilling 36 teams of 143 learners during 2022-2023. EVALUATION: All 2022-2023 cohort respondents to the end-of-project survey reported the program increased their data science knowledge. In addition, 90% agreed DSU improved their data science skills, 93% agreed it improved their confidence making data science decisions, and 96% agreed it improved their ability to perform data science work that benefits CDC. DISCUSSION: DSU is an innovative, inclusive, and successful approach to improving data science literacy at CDC. DSU may serve as an upskilling model for other organizations.

BACKGROUND: Assessment of people affected by opioid-related problems and those receiving care is challenging due to lack of common definitions and scattered information. We sought to fill this gap by demonstrating a method to describe a continuum of opioid addiction care in a large, public safety-net institution. METHODS: Using 2017 clinical and administrative data from Denver Health (DH), we created operational definitions for opioid use disorder (OUD), opioid misuse (OM), and opioid poisoning (OP). Six stages along a continuum of patient engagement in opioid addiction care were developed, and operational definitions assigned patients to stages for a specific time point of analysis. National data was used to estimate the Denver population affected by OUD, OM and OP. RESULTS: In 2017, an estimated 6688 people aged >/=12 years were affected by OUD, OM, or OP in Denver; 48.4% (3238/6688) were medically diagnosed in DH. Of those, 32.5% (1051/3238) were in the medication assisted treatment stage, and, of those, 59.8% (629/1051) in the adhered to treatment stage. Among that latter group, 78.4% (493/629) adhered at least 90 days and 52.3% (329/629) for more than one year. Among patients who received medication assisted treatment, less than one third (31.3%, 329/1051) were adherent for more than one year. CONCLUSIONS: A health-system level view of the continuum of opioid addiction care identified improvement opportunities to better monitor accuracy of diagnosis, treatment capacity, and effectiveness of patient engagement. Applied longitudinally at local, state and national levels, the model could better synergize responses to the opioid crisis.