Maricela Cruz, PhD, is a biostatistician passionate about conducting public health research with a specific focus on improving the health of disenfranchised communities.
Dr. Cruz’s research centers on developing flexible and robust statistical methods to evaluate health care interventions, particularly using electronic health records, to inform clinical and public health practices. She specializes in analytic methods for pre-post longitudinal correlated data, including interrupted time series (ITS), time series analysis, longitudinal data, change-point detection, and difference-in-differences. Dr. Cruz additionally has experience in developing and evaluating prediction models. The pre-post methods she develops allow health systems to evaluate interventions over time, while her prediction model work helps identify at-risk encounters — both are critical in shaping effective health practices.
Dr. Cruz has developed and evaluated several ITS models to estimate the impact of new nursing structures (and similar health care interventions) on patient experience outcomes in the presence of potentially lagged (or anticipatory) treatment effects. To communicate and encourage access to her methods in the broader public health community, Dr. Cruz co-created the Robust Interrupted Time Series toolbox (https://biostatistics-kaust.github.io/robust_time_series_toolbox/), a stand-alone, user-friendly application implementing the Robust Multiple ITS model that Dr. Cruz developed in 2019 for single and multiple ITS.
Dr. Cruz provides statistical and scientific leadership in collaborative public health and health care delivery projects aimed at improving health outcomes for disenfranchised communities. She collaborates on several projects aiming to improve care for people with a history of suicide ideation and on projects designing and evaluating health care interventions, such as value-based drug formularies and clinical decision support systems for at-risk encounters.
Dr. Cruz obtained her PhD in statistics from the University of California Irvine in 2019. She is an affiliate assistant professor in biostatistics at the University of Washington.
Buszkiewicz JH, Bobb JF, Kapos F, Hurvitz PM, Arterburn D, Moudon AV, Cook A, Mooney SJ, Cruz M, Gupta S, Lozano P, Rosenberg DE, Theis MK, Anau J, Drewnowski A Differential associations of the built environment on weight gain by sex and race/ethnicity but not age 2021 Dec;45(12):2648-2656. doi: 10.1038/s41366-021-00937-9. Epub 2021-08-27. 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 2021 Nov;8(6):3688-3696. doi: 10.1002/nop2.910. Epub 2021-05-03. PubMed
Coley RY, Walker RL, Cruz M, Simon GE, Shortreed SM Clinical risk prediction models and informative cluster size: Assessing the performance of a suicide risk prediction algorithm 2021 Oct;63(7):1375-1388. doi: 10.1002/bimj.202000199. Epub 2021-05-24. PubMed
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 2021 Sep;45(9):1914-1924. doi: 10.1038/s41366-021-00836-z. Epub 2021-05-11. PubMed
Cruz M, Pinto-Orellana MA, Gillen DL, Ombao HC RITS: a toolbox for assessing complex interventions via interrupted time series models 2021 Jul 8;21(1):143. doi: 10.1186/s12874-021-01322-w. Epub 2021-07-08. PubMed
Safety planning and risk screening improved outcomes for adult patients.
Study uses geographic data to track change over time.
JSM TV, Aug. 6, 2024