HSRProj will be retired on September 14, 2021, no updates will be made to HSRProj after this date.
Detailed information about this transition can be found on the
June 3, 2021 Technical Bulletin post.
If you have questions or suggestions, please contact
NLM Customer Service.
Information about ongoing health services research and public health projects
| Quantification of neonatal transport networks through network analysis: a new approach to studying neonatal regionalization | |
|---|---|
| Investigator (PI): | Kunz, Sarah Nicole |
| Performing Organization (PO): |
(Current): Beth Israel Deaconess Medical Center, Department of Neonatology / (617) 667-3276 |
| Supporting Agency (SA): | Agency for Healthcare Research and Quality (AHRQ) |
| Initial Year: | 2018 |
| Final Year: | 2023 |
| Record Source/Award ID: | RePorter/K08HS025749 |
| Funding: | 2018 Award Amount: $150,136 |
| Award Type: | Grant |
| Abstract: | Sarah N. Kunz, MD, MPH, is a neonatologist at Beth Israel Deaconess Medical Center (BIDMC) and an instructor of pediatrics at Harvard Medical School (HMS). Dr. Kunz's research and career plans focus on developing novel and quantitative ways of defining and studying neonatal referral networks and ultimately optimizing these systems to improve quality of care. Outcomes for very low birth weight (VLBW; <1500 grams) babies are highly variable across the United States, arising in part from differential implementation of regionalization, which prioritizes targeting high-risk births at hospitals that can provide adequate care. When VLBW infants are born at hospitals without advanced neonatal intensive care, they require transport to a higher level center, increasing their risk of death and disability. Current tools to measure transport quality are limited to easily measurable characteristics such as transport distance and team composition. More sophisticated methods are required to understand how unmeasured aspects of neonatal transport influence outcomes: specifically, how transports function in the context of the larger hospital referral network and how the strength of hospital relationships affects outcomes. In this application, Dr. Kunz proposes applying network science methods to linked clinical and transport datasets to analyze the VLBW transport network in California, with particular attention to the effect of transport quality and network characteristics on outcomes. The specific aims of this study are to (1) characterize and quantify acute neonatal VLBW referral networks and transport characteristics, (2) empirically define "cohesion" of VLBW infant transport networks, (3) test the association between network cohesion and transport quality and outcomes, and (4) optimize transport networks. To achieve these aims and further her long-term career goal of becoming an independent health services researcher focused on improving care delivery systems, Dr. Kunz has constructed a career development plan combining intensive mentorship, hands-on research experience, and didactic coursework. The oversight of her expert mentors, along with courses in network analysis, advanced statistical methods, health policy, and organizational culture, will build on the strong foundation she gained from her fellowship in health services research and her master's of public health. Her institutional environment bridges two strong academic settings (BIDMC/HMS and the California Perinatal Quality Care Collaborative/Stanford University). Upon completion, the proposed research will elucidate the contribution of patient-, hospital-, transport-, and network-level characteristics to the functioning of neonatal referral systems, and identify concrete approaches for systems-level improvement, methods that will be applicable to other types of patient referral systems. Undertaking the proposed project and career development activities are essential for Dr. Kunz to transition to an independent health services researcher focused on optimizing care for infants by improving the systems that care for them. |
| MeSH Terms: |
|
| Country: | United States |
| State: | Massachusetts |
| Zip Code: | 02215 |
| UI: | 20184047 |
| Project Status: | Ongoing |
