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 for The Johns Hopkins Hospital. I graduated from South Florida in 2015 with a Ph.D. in operations research where I worked under the guidance of Jose Zayas-Castro in health systems and complexity science. From 2015 to 2017, I was a research fellow with Scott Levin's data science group at the Johns Hopkins School of Medicine. I joined the Hopkins faculty in 2017.
Today, my group and I are developing algorithms that can help us make healthcare more efficient.
Today, my group and I are developing algorithms that can help us make healthcare more efficient.
Current
Data-to-Decisions. Extracting meaning from large and sparse data, and creating real-time clinical 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 patient prioritization tools to more accurately differentiate patients with respect clinical outcomes in hospital waiting lists. With the support of the Johns Hopkins Alliance for a Healthier World.
- ML MI Community Structure (with Sean Barnes). Representing healthcare delivery processes in networks and identifying communities of nodes within them to better understand its dynamics. Currently, we are using networks for algorithmic hospital asset fleet management. With the support of The Johns Hopkins Hospital.
- MM ML Epidemics on Networks (with Eili Klein). Investigating the epidemic processes by which diseases spread over networks of contact between humans. In particular, we use Bayesian MCMC modeling to measure the impact of contact precautions in preventing transmission of bacteria that are resistant to multiple drugs used to treat them. 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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January 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 the AUGE Plan in Chile |
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 describe how we designed and implemented a command center to manage patient flow at a large 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
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
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 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 |
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 and implemented a clinical practice guideline to reduce unnecesary testing in a tertiary pediatric ICU |
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.
