We’re thrilled to introduce you to Melinda Gomez Tellez, a volunteer Data Expert who worked on our Data Integrity project with Medic Mobile, one of our expert partners under our Frontline Health Systems Impact Practice. A Senior Data Scientist at Cogitativo, she started her career in software development and implementation. She’s worked in a number of areas in healthcare, including, Care Management, Palliative Care, Hospital Quality and Safety, Clinical Pathways, and Member and Provider Services, and is passionate about value-based healthcare. As a Data Expert, she is unfazed by messy data and enjoys tinkering and hacking to understand underlying trends and find answers to a project’s data science questions. She holds a B.S. in Biophysics from UCLA and an M.S. in Computer Information Systems and Data Analytics from Boston University.
To learn more about Melinda’s journey as a DataKinder and Data Expert for Medic Mobile, in her own words, read on!
Tell us a little bit about yourself and your background.
I’m currently a senior data scientist working in the healthcare space. I actually started out in software development and implementation before moving into data science. I think this has given me a unique perspective on how to finalize my work into a “product” that businesses can reuse and enhance. I’m extremely passionate about the healthcare industry and have gotten to work with an array of different data sources and projects. Specifically, I’ve enjoyed working on projects centered around care management and improving care to mitigate risk of patients requiring future costly services.
Can you briefly describe the project that you’re currently working on?
I’m currently working with Medic Mobile to target inconsistent or problematic data (IoP) collected with their open source software that is used to track patients and monitor care by Community Health Workers. The deliverable includes developing scripts and algorithms for alerting and reporting of this IoP with some high-level thoughts on how to best visualize this data for the supervisors of the community health workers and their teams to have conversations about data quality closer to where and when the data is generated. This has been the proven intervention point for this project and will ultimately create additional avenues for reliable and trusted data to be leveraged to improve health outcomes for the population served.
What surprised you most about the project?
I think what surprised me the most about the project was the amount of detail that can be collected about a patient from a phone that is most likely not connected to the internet. It’s easy for us to get lost in the data problem we are trying to solve remotely in our own homes, but in some moments, it would really hit me that someone recorded a majority of this detailed and vital data on a very small screen. It’s extremely humbling to think about the community health workers who travel to remote areas and provide not only needed care but also are able to do it with simple technology.
What is the highlight of the project so far?
With so many talented people on our team across different job functions and industries, a highlight has really been learning and observing how different people approach solving a problem.
How has this project shifted your perspective on doing data for good?
I wouldn’t say it’s shifted but more reinforced how important it is to use data for good. I will say that it has made me incredibly interested to work next on a “data for good” project that is outside of healthcare. I’d love to explore topics outside of the healthcare space.
What advice would you like to share with volunteers who are new to DataKind or the Data for Good movement?
Everything you hope DataKind would be is true. The people who work and volunteer here are extremely kind and talented, and you will end up finding immense joy in the projects you work on.
What’s the last book you read?
Uncanny Valley – A Memoir by Anna Wiener (I’m from Silicon Valley so this was a must on my list!)
What’s one piece of advice you’d give to your younger self?
Find what you love to do and do good with it.
