Adaptation and Formative Evaluation of Online Decision Support to Implement Evidence-Based Strategies to Increase HPV Vaccination Rates in Pediatric Clinics.

Human papilloma virus (HPV) vaccination rates remain below national goals in the United States despite the availability of evidence-based strategies to increase rates. The Adolescent Vaccination Program (AVP) is a multi-component intervention demonstrated to increase HPV vaccination rates in pediatric clinics through the implementation of six evidence-based strategies. The purpose of this study, conducted in Houston, Texas, from 2019-2021, was to adapt the AVP into an online decision support implementation tool for standalone use and to evaluate its feasibility for use in community clinics. Phase 1 (Adaptation) comprised clinic interviews (n = 23), literature review, Adolescent Vaccination Program Implementation Tool (AVP-IT) design documentation, and AVP-IT development. Phase 2 (Evaluation) comprised usability testing with healthcare providers (HCPs) (n = 5) and feasibility testing in community-based clinics (n = 2). AVP-IT decision support provides an Action Plan with tailored guidance on implementing six evidence-based strategies (immunization champions, assessment and feedback, continuing education, provider prompts, parent reminders, and parent education). HCPs rated the AVP-IT as acceptable, credible, easy, helpful, impactful, and appealing (≥80% agreement). They rated AVP-IT supported implementation as easier and more effective compared to usual practice (p ≤ 0.05). The clinic-based AVP-IT uses facilitated strategy implementation by 3-month follow-up. The AVP-IT promises accessible, utilitarian, and scalable decision support on strategies to increase HPV vaccination rates in pediatric clinic settings. Further feasibility and efficacy testing is indicated.

Exploratory Factor Analysis of a Patient-Centered Cancer Care Measure to Support Improved Assessment of Patients' Experiences.

OBJECTIVE: To increase the understanding of patient-centered care (PCC) and address the need for cross-cutting quality cancer care measures that are relevant to both patients and providers. METHODS: An exploratory factor analysis (EFA) was performed on a short version of the Patients and the Cancer Care Experience Survey, a patient-reported measure of perceived importance of social, emotional, physical, and informational aspects of care, administered to adult patients (n = 104) at a National Cancer Institute-designated comprehensive cancer center. Relationships between PCC dimensions and patient characteristics were also assessed. Principal axis factoring was applied and bivariate analyses were performed using Wilcoxon rank-sum tests. RESULTS: Most of our sample was over 60 years old (63.4%), female (57.4%), and white (74.2%), with either breast (41.2%) or prostate cancer (27.5%). A 5-factor model was identified: (1) quality of life (α = .91), (2) provider social support (α = .83), (3) psychosocial needs (α = .91), (4) nonprovider social support (α = .79), and (5) health information and decision-making support (α = .88). No statistically significant associations were found between these factors and patients' characteristics. CONCLUSIONS: A preliminary factor structure for a cancer PCC measure was identified. Our findings reinforce the interrelated nature of PCC dimensions. The lessons learned from this study may be used to develop a single PCC measure that identifies patient priorities across the cancer care continuum. Data collected from such a measure can be used to support patient engagement in treatment planning and decision-making.

Improving pilot project application and review processes: A novel application of lean six sigma in translational science.

Each year our Clinical and Translational Science Award pilot projects program awards approximately $500,000 in translational pilot funding to advance health in South Texas. We identified needs to improve the timeliness, transparency, and efficiency of the review process by surveying applicants. Lean six sigma methodologies, following a "Define, Measure, Analyze, Improve, Control" approach, were used to streamline the pilot project application and review by identifying and removing bottlenecks from process flows. We evaluated the impact of our reorganized review process by surveying applicants and reviewers. Process mapping identified pilot project review as the main source of delay, leading to the implementation of a study section-style review mechanism. After one cycle, 90.3% of pilot applicants and 100% of reviewers were highly satisfied with the new processes and time to award notice was reduced by 2 months. All reviewers familiar with both review processes preferred the study section. We demonstrated how lean six sigma, a methodology not commonly applied in research administration, can be used to evaluate processes in translational science in academic health centers. Through our efforts, we were able to improve timeliness, transparency, and efficiency of the review process.