Publications

Take a deeper look into all the publications produced by researchers at The Dartmouth Institute.

Arakelyan M, Schaefer AP, Freyleue SD, Moen EL, O'Malley AJ, Goodman DC, Leyenaar JK

2026 Jan;42(1):e70122doi: 10.1111/jrh.70122

Rural-residing children with medical complexity (CMC) may receive fragmented care given clinician shortages in rural communities. This study characterized differences in continuity of care between rural- and urban-residing CMC, applying novel measures of geographic care continuity and assessing associations between continuity, neighborhood social disadvantage, and unplanned hospital utilization.

J Rural Health|2026 Jan

Fay KA, Schifferdecker KE, Kinney LM, Kyung EJ, Bardach SH, Boardman MB, Savellano DH, Bridges C, Halloran SR, Youkilis S, Bird T, Hasson RM

2026 Jan 29;319:1-9doi: 10.1016/j.jss.2025.12.042

Uptake of lung cancer screening (LCS) suffers from the misconception that LCS produces high false-positive findings. The purpose of this study was to assess LCS results to better quantify these rates.

J Surg Res|2026 Jan 29

Yogurtcu ON, Gressler LE, Eldrup-Jorgensen J, Haqqi K, Shepard C, Panagiotou OA, Molina SJ, Goodney PP, Abbasi AB, Anderson BS, Hadden WC, Tcheng JE, Skapik J, Pappas G

2025 Dec 20;9(Suppl 1):S26-S36doi: 10.25259/ijtmrph_75_2024

Coordinated Registry Networks (CRNs) are networks of healthcare partners that create and utilize information from clinical society registries and other sources to drive evidence-based improvements in healthcare. In Part I of this three-part series, we introduced the systemic coordinated inter-organizational networks (SCIONs) theory, which is proposed as a unique mode of societal coordination that fosters trust, cooperation, and adaptability among partner organizations to address complex societal problems, including healthcare. In this article, we analyze how CRNs function like SCIONs to better understand how CRNs can promote innovation to improve outcomes, quality, and efficiency.

Int J Transl Med Res Public Health|2025 Dec 20

Dasgupta T, Russell E, Carbajal C, Horgan G, Peterson L, Mistry HD, Buabeng R, Wilson M, Smith V, Boulding H, Sheen KS, Van Citters AD, Nelson EC, Duncan EL, von Dadelszen P, RESILIENT Study Group, Silverio SA, Magee LA

2025;7:1734456doi: 10.3389/frph.2025.1734456

The pandemic created global disruption acting as a health system shock not seen before in living memory. As a consequence, there were significant implications for healthcare delivery in low- and middle-income countries. Challenges such as lockdown restrictions created substantial modifications to the delivery of maternity care. This review aims to explore the experiences of maternity care by women, specifically in low- and middle-income countries, during the pandemic global health system shock.

Front Reprod Health|2025

Kraft S, Colgan M, Carlos H, Savage S

2025;5:1682447doi: 10.3389/frhs.2025.1682447

As the United States faces mounting challenges to improving health outcomes, new strategies are needed to address root drivers of health and engage community partners to change the community conditions that impact health and health disparities. Project ECHO (Extension for Community Healthcare Outcomes) is a telementoring model developed in 2003 at the University of New Mexico to disseminate knowledge, share evidence-based care practices, and create communities of learning. The ECHO model has been shown to improve clinical outcomes by training primary care care clinicians to provde care often delegated to specialists. This paper describes modifications to ECHO programming to improve population health through engagement of diverse, community audiences in order to impact non-clinical contributors to health. During these community-facing ECHO courses, participants learn from short didactic sessions, share best practices through case-based presentations, and increase connections between sectors of the community and the health system. Implementation of this novel ECHO program is described using the RE-AIM and CFIR frameworks. Adapting the ECHO model to support collaborative learning to impact upstream drivers of health may be an important innovation for improving population health.

Front Health Serv|2025

Yogurtcu ON, Gressler LE, Eldrup-Jorgensen J, Haqqi K, Shepard C, Panagiotou OA, Molina SJ, Goodney PP, Abbasi AB, Anderson BS, Hadden WC, Tcheng JE, Skapik J, Pappas G

2025 Dec 20;9(Suppl 1):S15-S25doi: 10.25259/ijtmrph_74_2024

Over the past decade substantial government and market-driven efforts focused on the use of real-world evidence (RWE) to improve healthcare decision-making. A successful strategy has been mounted by specialty societies and their registries that have created RWE through a model known as the Coordinated Registry Network (CRN), which has accelerated innovation, improved care quality, addressed the safety and efficacy of medical products, and supported medical research. This three-part manuscript works to understand how the CRNs have succeeded by applying organizational sociology and the theory of Systemic Coordinated Inter-Organizational Networks (SCIONs).

Int J Transl Med Res Public Health|2025 Dec 20

Bellamkonda KS, Newton L, Korves C, Weinberger D, Zwain G, Eid M, Fowler X, Ponukumati A, Robertson D, Wilson MZ, Justice AC, Vashi A, Goodney PP, Davies L

2026 Jan 23;:102344doi: 10.1016/j.gassur.2026.102344

Colorectal cancer is the fourth most common cancer in the U.S., and early detection decreases mortality. We evaluated recent trends in colon cancer incidence and changes in rates of presentation with bowel obstruction before and during the COVID-19 pandemic.

J Gastrointest Surg|2026 Jan 23

Schnitzer ME, Talbot D, Liu Y, Berger D, Wang G, O'Loughlin J, Sylvestre MP, Ertefaie A

2026 Jan;45(1-2):e70316doi: 10.1002/sim.70316

Causal variable selection in time-varying treatment settings is challenging due to evolving confounding effects. Existing methods mainly focus on time-fixed exposures and are not directly applicable to time-varying scenarios. We propose a novel two-step procedure for variable selection when modeling the treatment probability at each time point. We first introduce a novel approach to longitudinal confounder selection using a Longitudinal Outcome Adaptive LASSO (LOAL) that will data-adaptively select covariates with theoretical justification of variance reduction of the estimator of the causal effect. We then propose an adaptive fused LASSO that can collapse treatment model parameters over time points with the goal of simplifying the models in order to improve the efficiency of the estimator while minimizing model misspecification bias compared with naive pooled logistic regression models. Our simulation studies highlight the need for and usefulness of the proposed approach in practice. We implemented our method on data from the Nicotine Dependence in Teens study to estimate the effect of the timing of alcohol initiation during adolescence on depressive symptoms in early adulthood.

Stat Med|2026 Jan

Dominitz JA, Robertson DJ

2026 Jan 21;pii: S0016-5085(26)00004-1. doi: 10.1053/j.gastro.2026.01.001

Gastroenterology|2026 Jan 21

Longacre MR, Kinney LM, Carluzzo KL, Watts BV, Schifferdecker KE

2026 Jan;42(1):e70115doi: 10.1111/jrh.70115

Healthcare workforce shortages are acute in rural areas. Using a holistic workforce retention framework, we examined evidence and identified gaps in recruitment and retention programs, using the Veterans Health Administration as a case study.

J Rural Health|2026 Jan

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