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Interested in learning how to use AI to enrich your research? 

 

We are here to help.

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Data-Driven LLC, Dr. Leslie Phillips

working for 

a healthy world

"We will help you think about what questions to ask and what solutions to test. The most well-informed solution may fall flat if it is not feasible and acceptable, so

that is where we will start." - Dr. Leslie Phillips

Founder and owner of Data-Driven LLC

General Epidemiologist

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Professional Memberships & Affiliations

 

AAAS - American Association for the Advancement of Science 

SER - Society for Epidemiologic Research

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Certifications

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In-process: Machine Learning (in the healthcare setting)

 

Education

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PhD, Epidemiology, University of Washington

MS, Public Health, Harvard University

About Dr. Leslie Phillips

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Dr. Leslie Phillips is a doctoral-level epidemiologist who brings deep experience

as a research leader.  Dr. Phillips is experienced with Lean Startup, best practices for survey research, occupational health & safety, data analysis & interpretation, and helping clients design robust research. In the age of large language models (like ChatGPT), she is leveraging the power of AI for research through prompt engineering and by augmenting human ingenuity with the speed and volume provided by AI. 

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She founded Data-Driven LLC to offer epidemiologic consulting with an emphasis on helping clients understand, collect, and use real-world data. She is passionate about using epidemiologic methods to deconstruct problems, test solutions, and interpret findings. Dr. Phillips is committed to learning the state of the science and developing studies where insufficient evidence exists. Adept at communicating with a wide range of audiences, from low-wage workers or C-level executives, Dr. Phillips is excited to engage your team at all levels.

 

Data-Driven LLC specializes in helping clients. Whether that is assisting clients in leveraging the best of human and human-guided AI research or guiding the transition from one data platform to another, Data-Driven is agile and empirical. We deliver actionable recommendations for your business.

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Dr. Phillips and Data-Driven LLC find the simplest solutions to even the most complex problems. Sometimes the outcome is as simple as a professional, unbiased referral to services and technology that meet your needs.    

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Data-Driven focuses on synthesizing and communicating data related to health or other outcomes where pattern detection, quantification, and communication are focal part to a successful strategy. Specific to the SARS-CoV-2 virus, Dr. Phillips stays abreast of the current transmission and risk mitigation science and is adept at communicating these findings to workers and clients.

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If you need guidance in the following areas, we have experience in: AI-assisted research, outbreak response, prompt engineering, synthesizing evidence, piloting/testing solutions, designing studies and evaluating studies for common biases, quantitative and qualitative research, primary data collection, secondary data analyses, data transitions, using publicly-available data (e.g., Census) to contextualize decisions, as well as manuscript and report writing/editing.

While a native Texan, Dr. Phillips has lived in Seattle for 20 years, during which time she has come to the data-driven conclusion that nylon is NO match for Gore-Tex.

Confidentiality

Client and Data Confidentiality

Dr. Phillips and all Data-Driven staff and contractors have undergone training and are certified in the Office for Human Research Protections' Human Research Protection Foundational Training. 

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Data-Driven work is conducted in a password-protected Cloud storage environment with 256-bit Advanced Encryption Standard (AES) as well as Secure Sockets Layer (SSL)/Transport Layer Security (TLS) to protect data. 

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Wherever possible Data-Driven works with data that has no personal identifiable information (PII). In situations where PII are necessary for the conduct of a project (e.g., reaching out to participants for a survey or interview), Data-Driven replaces PII with a random code in all files containing health and other confidential participant information and holds the key in a separate password-protected file in secure Cloud storage. 

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All Data-Driven staff and contractors have Non-Disclosure Agreements (NDA's) on file for the protection of clients. Data-Driven is available to sign custom NDAs that address specific client needs. 

Media & Publications

Media & Publications

Comparative Effectiveness of mRNA-1273 and BNT162b2 COVID-19 Vaccines in Immunocompromised Individuals: A Systematic Review and Meta-Analysis Using the GRADE Framework

Xuan Wang, Katrin Haeussler, Anne Spellman, Leslie E. Phillips, Allison Ramiller, Mary T. Bausch-Jurken, Pawana Sharma, Anna Krivelyova, Sonam Vats, Nicolas Van de Velde

medRxiv 2023.04.05.23288195; doi: https://doi.org/10.1101/2023.04.05.23288195

Leslie E Phillips, Paul Dhillon, Andrew Kotas, Renee Kusler, Jeffrey Shih, Juliane Kause. Film production during the Covid-19 pandemic, Occupational Medicine, 2022;, kqac102, https://doi.org/10.1093/occmed/kqac102

Hansell AK, Knaster ES, Phillips LE. Injury Among Home Care Workers in Washington State. New Solut. 2018 Feb;27(4):543-588. doi: 10.1177/1048291117739419. Epub 2017 Nov 7. PMID:29110559. link to abstract: https://pubmed.ncbi.nlm.nih.gov/29110559/

Schoenfisch AL, Lipscomb H, Phillips LE. Safety of union home care aids in Washington State. Am J Ind Med. 2017 Sep;60(9):798-810. doi: 10.1002/ajim.22747. Epub 2017 Jul 26. PMID: 28744929. link to abstract: https://pubmed.ncbi.nlm.nih.gov/28744929/

Knaster ES, Fretts AM, Phillips LE. The association of depression with diabetes management among urban American Indians/Alaska Natives in the United States, 2011. Ethn Dis. 2015 Winter;25(1):83-9. PMID: 25812257. link to abstract: https://pubmed.ncbi.nlm.nih.gov/25812257/

Jacobs-Wingo JL, Espey DK, Groom AV, Phillips LE, Haverkamp DS, Stanley SL. Causes and Disparities in Death Rates Among Urban American Indian and Alaska Native Populations, 1999-2009. Am J Public Health. 2016 May:106(5):906-14. doi:10.2105/AJPH.2015.303033. Epub 2016 Feb 18. PMID:26890168; PMCID: PMC4985112. link to abstract: https://pubmed.ncbi.nlm.nih.gov/26890168/

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