Maricela Cruz, PhD

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“Developing flexible yet pragmatic and robust statistical methodology that can accommodate the intricacies of real-world circumstances is paramount in addressing public health concerns.”

Maricela Cruz, PhD

Assistant Biostatistics Investigator, Kaiser Permanente Washington Health Research Institute

Biography

Maricela Cruz, PhD, strives to create useful and widely applicable methodology to tackle real-world problems in public health. Her research primarily focuses on developing novel statistical methods to assess and evaluate the impact of complex health care interventions. In her research, she uses statistical techniques for interrupted time series, time series, correlated data, change point detection, longitudinal data and interventions research.

Dr. Cruz received her PhD in statistics from the University of California Irvine. During her time there, she was a National Science Foundation Graduate Research Fellowship awardee and Eugene Cota-Robles fellow. She worked with care delivery experts and practitioners to design and conduct statistical analyses that assessed health care interventions across multiple hospitals and hospital units. She developed two novel interrupted time series models that allow for complex correlation structures that can change post intervention and are adequate for single- and multi-unit continuous data. To communicate and encourage access to her methods by non-statisticians in the broader public health community, Dr. Cruz produced an application in R Shiny that analyzes interrupted time series data. As a graduate student, she was a summer associate at the RAND Corporation. While at RAND, she led a collaborative study examining the relationship between group cohesion and climate with alcohol use outcomes in a group therapy intervention for individuals with a first-time offense for driving under the influence.

At KPWHRI, Dr. Cruz works alongside researchers in behavioral health, mental health, and insurance design. She explores the relationship between weight change and diabetes measures and the built environment, aids in the development of suicide risk prediction algorithms, and evaluates interventions that encourage high-value use of health care services.

Recent Publications

Buszkiewicz JH, Bobb JF, Hurvitz PM, Arterburn D, Moudon AV, Cook A, Mooney SJ, Cruz M, Gupta S, Lozano P, Rosenberg DE, Theis MK, Anau J, Drewnowski A. Does the built environment have independent obesogenic power? urban form and trajectories of weight gain. Int J Obes (Lond). 2021 Sep;45(9):1914-1924. doi: 10.1038/s41366-021-00836-z. Epub 2021 May 11. PubMed

Bender M, Williams M, Cruz MF, Rubinson C. A study protocol to evaluate the implementation and effectiveness of the clinical nurse leader care model in improving quality and safety outcomes. Nurs Open. 2021 May 3. doi: 10.1002/nop2.910. Online ahead of print. PubMed

Coley RY, Johnson E, Simon GE, Cruz M, Shortreed SM. Racial/ethnic disparities in the performance of prediction models for death by suicide after mental health visits. JAMA Psychiatry. 2021 Apr 28:e210493. doi: 10.1001/jamapsychiatry.2021.0493. [Epub ahead of print]. PubMed

Cruz M, Osilla KC, Paddock SM. Group cohesion and climate in cognitive behavioral therapy for first-time DUI offenders. Alcohol Treat Q. 2019 https://doi.org/10.1080/07347324.2019.1613941.

Cruz M, Gillen DL, Bender M, Ombao H. Assessing health care interventions via an interrupted time series model: Study power and design considerations. Stat Med. 2019 May 10;38(10):1734-1752. doi: 10.1002/sim.8067. Epub 2019 Jan 7. PubMed

 

New findings

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Simpler models to identify suicide risk perform similarly to more complex ones

Models that are easier to explain, use could have better uptake in health care settings.

M2H study

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Can where you move impact future weight gain?

A new study finds that moving from low- to high-density neighborhoods might be related to reductions in weight gain.

Research

urban setting apartments and skyscrapers obesity and the built environment

Built environment plays little role in weight gain

New research suggests fast food and other aspects of built environments don’t affect weight, contrary to earlier findings.