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How to Get a Return Offer as a Datavant Intern

Datavant

May 20, 2022

Datavant’s internship program is an excellent way for you to find out what it’s like to work here as a full-time software engineer. Here are four tips to enrich your internship experience, and in turn maximize your chances for a return offer!

Be invested in your project

At Datavant, we believe in more responsibility and fewer rules. This means that you’ll be working on a meaningful project from day 1. In other words, your work will live on in our codebase beyond your internship, and could even be used by customers the same day that you ship it.

Throughout the summer, you should spend time communicating with stakeholders to fully understand the context and purpose of your project. This can be done by scheduling 1:1s with members of the team both inside and outside engineering. Additionally, you’ll have plenty of opportunities to showcase your work and get feedback in our biweekly engineering demos. Don’t be afraid to sign up!

Make a timeline

It’s important to keep in mind that your summer internship is limited to 11 weeks. Factoring in onboarding, onsites, and time off, you have 8 weeks at best to implement your project from start to finish. So, it’s crucial that you allocate your time well.

First, I would recommend that you break your project down into small subtasks. This can be done through Jira (the project management software our team uses), a Google Doc, or whatever works best for you. Your subtasks will track what you’ve completed on a more granular level, which can in turn inform your manager about how they can best assist you. As a plus, checking off subtickets will give you a sense of accomplishment, which can help reduce the stress of managing a large project.

Second, I strongly recommend that you split your code up into small PRs. PR (pull request) reviews are an opportunity to receive technical feedback from your team and iterate on your code. (For those of you who aren’t familiar, read more about Github PRs here!) Small PRs not only make the review cycle easier for your team, but also make sure you don’t get overwhelmed with testing too many changes at once and fixing compounding bugs. Smaller PRs also lead to faster feedback, which can speed up your learning process.

Learn how to get unstuck

In order to stay on track to finish your project, you must learn how to ask and find answers to your questions. The high degree of autonomy we get as Datavant engineers requires us to be extra intentional about this.

When setting up your dev environment, you can find numerous troubleshooting tips on our Github Wiki page. Here, you’ll also find useful information such as best practices for API testing and how to run our command-line interface and desktop apps. If you find that something’s missing from our Wiki, we encourage you to update it! (Those of you who attend in-person onboarding sessions will have the chance to work through the dev set up process with the rest of your intern cohort.)

Slack also acts as an extensive log of all questions that have been asked already. Make sure to utilize the Slack search function, which allows you to search for keywords and filter by specific channels and people. E.g. if you’re running into a problem with your dev environment, chances are another Datavanter ran into that same exact issue before you and posted about it in Slack. (For general, non-Datavant specific questions, you can also look to external resources like Google and Stack Overflow.)

Lastly, you should get comfortable communicating with your mentor! For some intern-mentor pairings it makes sense to have daily check-ins and ask questions then, while for others it makes sense to lean on asynchronous communication. Figure out what works best for you. At the end of the day, it’s your mentor’s job to put you in a position to succeed. Even if your mentor isn’t the best person to answer your question, they’ll usually be able to point you to the right people and places. Autonomy is one of Datavant’s core principles, but that doesn’t mean you can’t ask for support. In fact, the ability to ask questions is a key characteristic of an autonomous engineer.

Ask for feedback

One of the most important aspects of communication with your mentor is the practice of giving and receiving actionable feedback. It’s essential to communicate with your mentor about things that aren’t going well early on so that you have a chance to digest feedback and improve on those things by the end of the summer. You will receive structured written feedback from your mentor at the midpoint of your internship. However, it’s totally fair game for you to ask for feedback outside of the scheduled feedback sessions.

You also shouldn’t hesitate to give your mentor feedback since they’re learning too! Due to the autonomy that we give to engineers, it’s largely up to you to find the learning and working environment that suits you — doing so is highly dependent on clear communication between you, your mentor, and your team.

Hopefully, this post gives you a framework that will help you have a successful summer internship. Good luck, and welcome to Datavant!

Interested in learning more about Datavant? Check more of our blog posts. Considering joining the team? Check out our careers page and see us listed on the 2022 Forbes top startup employers in America. We’re currently hiring remotely across teams and would love to speak with any new potential Datavanters who are nice, smart, and get things done.

Special thanks to Anjali Suresh, Walter Paiva, Alex Coda, and Matt Owen for significant input shaping this article.

Spotlight on AnalyticsIQ: Privacy Leadership in State De-Identification

AnalyticsIQ, a marketing data and analytics company, recently adopted Datavant’s state de-identification process to enhance the privacy of its SDOH datasets. By undergoing this privacy analysis prior to linking its data with other datasets, AnalyticsIQ has taken an extra step that could contribute to a more efficient Expert Determination (which is required when its data is linked with others in Datavant’s ecosystem).

AnalyticsIQ’s decision to adopt state de-identification standards underscores the importance of privacy in the data ecosystem. By addressing privacy challenges head-on, AnalyticsIQ and similar partners are poised to lead clinical research forward, providing datasets that are not only compliant with privacy requirements, but also ready for seamless integration into larger datasets.

"Stakeholders across the industry are seeking swift, secure access to high-quality, privacy-compliant SDOH data to drive efficiencies and improve patient outcomes,” says Christine Lee, head of health strategy and partnerships at AnalyticsIQ.

“By collaborating with Datavant to proactively perform state de-identification and Expert Determination on our consumer dataset, we help minimize potentially time-consuming steps upfront and enable partners to leverage actionable insights when they need them most. This approach underscores our commitment to supporting healthcare innovation while upholding the highest standards of privacy and compliance."

Building Trust in Privacy-Preserving Data Ecosystems

As the regulatory landscape continues to evolve, Datavant’s state de-identification product offers an innovative tool for privacy officers and data custodians alike. By addressing both state-specific and HIPAA requirements, companies can stay ahead of regulatory demands and build trust across data partners and end-users. For life sciences organizations, this can lead to faster, more reliable access to the datasets they need to drive research and innovation while supporting high privacy standards.

As life sciences companies increasingly rely on SDOH data to drive insights, the need for privacy-preserving solutions grows. Data ecosystems like Datavant’s, which link real-world datasets while safeguarding privacy, are critical to driving innovation in healthcare. By integrating state de-identified SDOH data, life sciences can gain a more comprehensive view of patient populations, uncover social factors that impact health outcomes, and ultimately guide clinical research that improves health.

The Power of SDOH Data with Providers and Payers to Close Gaps in Care

Both payers and providers are increasingly utilizing SDOH data to enhance care delivery and improve health equity. By incorporating SDOH data into their strategies, both groups aim to deliver more personalized care, address disparities, and better understand the social factors affecting patient outcomes.

Payers Deploy Targeted Care Using SDOH Data

Payers increasingly leverage SDOH data to meet health equity requirements and enhance care delivery:

Tailored Member Programs: Payers develop specialized initiatives like nutrition delivery services and transportation to and from medical appointments.
Identifying Care Gaps: SDOH data helps payers identify gaps in care for underserved communities, enabling strategic in-home assessments and interventions.
Future Risk Adjustment Models: The Centers for Medicare & Medicaid Services (CMS) plans to incorporate SDOH-related Z codes into risk adjustment models, recognizing the significance of SDOH data in assessing healthcare needs.

Payers’ consideration of SDOH underscores their commitment to improving health equity, delivering targeted care, and addressing disparities for vulnerable populations.

Example: CDPHP supports physical and mental wellbeing with non-medical assistance

Capital District Physicians’ Health Plan (CDPHP) incorporated SDOH, partnering with Papa, to combat loneliness and isolation in older adults, families, and other vulnerable populations. CDPHP aimed to address:

Social isolation
Loneliness
Transportation barriers
Gaps in care

By integrating SDOH data, CDPHP enhanced their services to deliver comprehensive care for its Medicare Advantage members.

Providers Optimize Value-Based Care Using SDOH Data

Value-based care organizations face challenges in fully understanding their patient panels. SDOH data significantly assists providers to address these challenges and improve patient care. Here are some examples of how:

Onboard Patients Into Care Programs: Providers use SDOH data to identify patients who require additional support and connect them with appropriate resources.
Stratify Patients by Risk: SDOH data combined with clinical information identifies high-risk patients, enabling targeted interventions and resource allocation.
Manage Transition of Care: SDOH data informs post-discharge plans, considering social factors to support smoother transitions and reduce readmissions.

By leveraging SDOH data, providers gain a more comprehensive understanding of their patient population, leading to more targeted and personalized care interventions.

While accessing SDOH data offers significant advantages, challenges can arise from:

Lack of Interoperability and Uniformity: Data exists in fragmented sources like electronic health records (EHRs), public health databases, social service systems, and proprietary databases. Integrating and securing data while ensuring data integrity and confidentiality can be complex, resource-intensive and risky.
Lag in Payer Claims Data: Payers can take weeks or months to release claims data. This delays informed decision-making, care improvement, analysis, and performance evaluation.
Incomplete Data Sets in Health Information Exchanges (HIEs): Not all healthcare providers or organizations participate in HIEs. This reduces the available data pool. Moreover, varying data sharing policies result in data gaps or inconsistencies.

To overcome these challenges, providers must have robust data integration strategies, standardization efforts, and access to health data ecosystems to ensure comprehensive and timely access to SDOH data.

SDOH data holds immense potential in transforming healthcare and addressing health disparities.

With Datavant, healthcare organizations are securely accessing SDOH data, and further enhancing the efficiency of their datasets through state de-identification capabilities - empowering stakeholders across the industry to make data-driven decisions that drive care forward.

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