Data, Systems, Society, and Healthcare
I am an assistant professor at the Johns Hopkins’ Center for Data Science in Emergency Medicine. I am also a member of the Malone Center for Engineering in Healthcare, and I serve as a data scientist at the Johns Hopkins Hospital. I graduated from South Florida in 2015 with a Ph.D. in industrial engineering where I worked under the guidance of Jose Zayas-Castro in healthcare systems engineering. From 2015 to 2017, I was a postdoc within Scott Levin's systems engineering group at Johns Hopkins Medicine. I joined the Johns Hopkins faculty in 2017.
Current
Data-to-Decisions. Extracting meaning from large and sparse data, and creating real-time decision support systems
- ML MO MI GB Emergency Department Triage (with Scott Levin). Investigate the potential for machine learning decision support systems to improve via exchange of information with knowledgeable users. With the support of the NSF and AHRQ
- ML MI Acute Kidney Injury Prediction (with Jeremiah Hinson). Predict the onset of acute kidney injury at ED patient presentation, and build an electronic tool embedded into the electronic medical records to support medical decision-making. With the support of the Emergency Medicine Foundation
- ML MO GB Waiting Lists Management (with Diana Prieto). Develop prioritization tools to more accurately differentiate patients with respect clinical outcomes in hospital waiting lists. With the support of the Alliance for a Healthier World
- ML MI Cascading Failures (with Sean Barnes). Representing healthcare delivery processes in networks and identifying cascading failures. With the support of the Johns Hopkins Hospital
- MM ML Epidemics on Networks (with Eili Klein). Investigating the epidemic processes by which infectious diseases spread over networks of contact between humans. In particular, we are using Bayesian MCMC modeling to determine the effectiveness of contact precautions in preventing transmission of antibiotic-bacteria. With the support of the CDC
MM: markov models, ML: machine learning, MI: informatics, MO: mathematical optimization, GB: global health
2019
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Sep 2019 (JMIR)
Jiang, Siddiqui, Barnes, Barouch, Korley, Martinez, Toerper, Cabral, Hamrock, Levin We developed a dynamic readmission risk prediction model that yields daily predictions for patients hospitalized with heart failure |
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Sep 2019 (IIE Healthcare Systems Engineering)
Martinez, Jalalpour, Efron, Levin We explained how to assess the impact of process improvement interventions with routinely collected longitudinal hospital data |
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Jan 2019 (BMC Public Health)
Martinez, Zhang, Bastias, Feijoo, Hinson, Martinez, Dunstan, Levin, Prieto We measured a possible link between lengthy waits to access health care with an increased risk of mortality in waiting lists not prioritized by universal healthcare (Plan AUGE) in Chile |
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Jan2019 (Emergency Nurses Association)
Whalen, Gardner, Martinez, Henry, McKenzie, Hinson, Levin We quantify and qualify our evolution from traditional ESI triage system to machine-learning-based system as an exemplar of transition from research to practice and nursing integration |
2018
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Nov 2018 (Joint Commission Journal on Quality and Patient Safety)
Kane, Scheulen, Puttgen, Martinez, Levin, Bush, Huffman, Jacobs, Rupani, Efron We designed and implemented a command center to manage patient flow at a large urban academic hospital using systems engineering principles |
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Nov 2018 (AHRQ Research Grant)
Levin (PI), Hinson (PI), Martinez (Co-Inv) To improve decision-making by emergency clinicians that relates to diagnosis, treatment, and disposition of patients with respiratory tract infections in the emergency department |
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Nov 2018 (PUCV, Chile)
Pontifical Catholic University of Valparaiso Data Science Seminar Diego Martinez Invited talk. Valparaiso, Chile |
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Nov 2018 (Annals of Emergency Medicine)
Hinson, Martinez, Cabral, George, Whalen, Hansoti, Levin We synthesized what is known about the performance of emergency department triage systems |
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Jun 2018 (Journal of Medical Systems)
Martinez, Kane, Jalapour, Scheulen, Rupani, Toteja, Barbara, Bush, Levin We created and implemented an electronic dashboard to monitor hospital patient flow |
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May 2018 (Applied Physics Lab)
Johns Hopkins Applied Physics Lab Network Science Seminar Diego Martinez Invited talk. Laurel, MA |
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Jan 2018 (Int J Emergency Medicine)
Hinson, Martinez, Schmitz, Toerper, Radu, Scheulen, Levin, Stewart de Ramirez We measured the extent to which patient characteristics contribute to inaccurate emergency department triage |
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Jan 2018 (Geisinger Health System)
Geisinger Health Operations Research Seminar Diego Martinez Invited talk. Danville, PA |
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Jan 2018 (JHU Research Grant)
Prieto (PI), Martinez (Co-PI) To reduce waiting lists in a health delivery network for low income patients in Chile |
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Jan 2018 (Annals of Emergency Medicine)
Hinson, Martinez, Grams, Levin We use electronic health records and machine learning to develop a predictive model for acute kidney injury (AKI) with capacity for identifying patients at high risk of developing AKI within 7 days of their emergency department visit |
2017
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Dec 2017 (Annals of Emergency Medicine)
Mistry, Steward de Ramirez, Kelen, Schmitz, Levin, Martinez, Psoter, Anton, Hinson We performed an accuracy and reliability evaluation of the emergency severity index for emergency department triage |
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Aug 2017 (CDC Research Grant)
Klein (PI), Martinez (Co-Inv) To improve understanding of how biological factors associated with the transmission of multidrug-resistant organisms impact interventions to reduce hospital-associated infections |
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May 2017 (IIE Healthcare Systems Engineering)
Wan, Zhang, Witz, Musselman, Yi, Mullen, Benneyan, Zayas-Castro, Rico, Cure, Martinez We synthesized what is known about preventable hospital readmissions in the US |
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Feb 2017 (JAMA Pediatrics)
Woods-Hill, Fackler, McMillan, Ascenzi, Voskertchian, Colantuoni, Martinez, Toerper, Levin, Milstone We created a new clinical practice guideline to reduce unnecessary testing in a tertiary pediatric ICU, which reduced blood sample collections without increasing missed sepsis cases |
2016
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Feb 2016 (Trials)
Martinez, Tsalatsanis, Yalcin, Zayas-Castro, Djulvegovic We model and optimize the opening of clinical trials at an academic medical center |
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Sep 2016 (Health Care Management Science)
Martinez, Feijoo, Zayas-Castro, Das, Levin We mathematically model the tension between market incentives and federal regulations in hospital markets |
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May 2016 (Journal for Healthcare Quality)
Rico, Liu, Martinez, Huang, Zayas-Castro, Fabri We measured the extent to which patient and hospital characteristics increase the risk of preventable hospital readmissions |
2015
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October 2015 (BMC Medical Informatics and Decision Making)
Strauss, Martinez, Garcia, Taylor, Mateja, Fabri, Zayas-Castro We identified design features for interoperable electronic medical records from a physician perspective |
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Nov 2015 (Applied Clinical Informatics)
Martinez, Mora, Gemmani, Zayas-Castro We uncover information needs of physicians from outside hospitals while managing patients in the hospitalist service |
Disclaimer: Any opinions, findings, conclusions, or recommendations expressed herein are those of the author and do not necessarily reflect the views of Johns Hopkins University or any other organization supporting our research.