Essential Research Strategies for MD Graduates in Clinical Informatics Residency

Why Research During Residency Matters for the Aspiring Clinical Informatician

For an MD graduate interested in clinical informatics, research during residency is more than a checkbox on your CV—it’s your proving ground. Whether you are in an internal medicine, pediatrics, EM, pathology, or another allopathic medical school match specialty, your residency years are the best time to build the scholarly foundation that will support a future clinical informatics fellowship and a career in health IT.

Clinical informatics is fundamentally a translational field: it connects patient care, data, and technology. That means the most competitive applicants bring:

• A track record of resident research projects with measurable impact
• Experience in health IT training and implementation
• Evidence of systems thinking, data literacy, and workflow improvement
• A clear interest in academic medicine (e.g., an academic residency track)

This article walks you step-by-step through how to design, execute, and showcase research during residency tailored to clinical informatics—regardless of whether your program already has a strong informatics presence.

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Understanding the Role of Research in a Clinical Informatics Career

How Research Fits into the Clinical Informatics Pathway

For an MD graduate residency trainee, especially from an allopathic medical school match, research can feel like “extra work.” In clinical informatics, it’s actually core to the field. The discipline asks questions like:

• How can we make the EHR safer and more usable for clinicians?
• What CDS (clinical decision support) tools actually change practice?
• How do we use real-world data for quality improvement and population health?

These questions are best explored through structured research and quality-improvement methodologies.

Research builds:

1. Credibility in a data-driven specialty

   • Clinical informatics fellowship directors want to see that you can ask a question, choose a method, manage data, and interpret results.
   • Even a modest retrospective chart review or usability project demonstrates analytic skills and scientific thinking.

2. Transferable skills for health IT roles
   Research during residency can cultivate:

   • EHR data extraction and basic analytics
   • Understanding of workflow mapping and human factors
   • Familiarity with implementation science (how to introduce and sustain change)
   • Collaboration with IT, data science, and analytics teams

3. Academic and leadership opportunities
   Residents with a scholarly track record often become:

   • Chief residents with informatics or QI portfolios
   • Early-career faculty leading digital health initiatives
   • Project leads for EHR optimization, telehealth, or AI pilots

Research vs. QI vs. Operations: All Are Valuable

Not every project needs to be an RCT or a complex AI algorithm. In clinical informatics, quality improvement (QI), implementation projects, and operational pilots are often as valuable as traditional “hypothesis-driven” research.

Think in three overlapping buckets:

1. Research – more formal, IRB-approved, generalizable knowledge

   • Example: Evaluating the effect of a sepsis alert redesign on time-to-antibiotics across multiple units.

2. Quality Improvement – iterative, rapid-cycle tests of change

   • Example: Implementing a redesigned discharge summary template and tracking 30-day readmissions or documentation completeness.

3. Operational / Health IT projects – system-level changes and evaluations

   • Example: Rolling out a new patient portal feature and measuring adoption, patient engagement, and message volume.

For a future clinical informatician, any of these can count as resident research projects, as long as they are systematic, measurable, and well-documented.

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Finding and Designing Research Opportunities in Residency

You do not need a formal clinical informatics department to do informatics-oriented research during residency. You do need curiosity, a basic strategy, and the right mentors.

Step 1: Map Your Local Ecosystem

Start by identifying existing resources in your institution:

• Informatics and IT stakeholders:

  • CMIO, CNIO, or associate CMIOs
  • EHR physician builders or clinical champions
  • Clinical decision support committee members
  • Data analytics or enterprise data warehouse teams

• Academic and research infrastructure:

  • Department of Biomedical Informatics or Health Services Research
  • QI office or quality/safety department
  • Clinical and Translational Science Institute (CTSI/CTSA hub)
  • Residency academic residency track or scholarly concentration

Ask specifically:

“Which ongoing projects involve EHR data, CDS, telehealth, patient portals, or data analytics that could use a resident collaborator?”

Your goal is not to “invent” a standalone project right away; it’s to plug into an existing stream of work where you can contribute meaningfully and get mentorship.

Step 2: Define a Clinically Relevant, Data-Driven Question

High-yield clinical informatics projects share three traits:

1. Clinically meaningful (a recognized pain point)
2. Feasible with available data and time
3. Measurable (clear outcome metrics)

Examples for MD graduate residency trainees:

• EHR Efficiency / Usability

  • “Does deploying a new inpatient progress note template reduce documentation time and nighttime note completion?”
  • Outcome: Note length, time-of-day of completion, time spent in documentation (EHR log data), and provider satisfaction survey.

• Clinical Decision Support

  • “What is the impact of refining drug–drug interaction alert thresholds on alert override rates and prescribing errors?”
  • Outcome: Alert volume, override rates, prescribing error rates, provider feedback.

• Care Transitions & Communication

  • “Can a structured handoff tool integrated into the EHR reduce clinically significant communication failures at sign-out?”
  • Outcome: Handoff completeness scores, adverse event reports, near-miss incidents.

• Population Health & Registries

  • “How effective is an EHR-based hypertension registry plus best-practice alert at improving control rates among patients with uncontrolled BP?”
  • Outcome: Change in mean BP, proportion at goal, follow-up rates.

Start with a one-sentence problem statement, then outline:

• Population (who?)
• Intervention/exposure (what change or factor?)
• Comparison (if applicable)
• Outcome(s) (what are you measuring?)
• Time frame (over what period?)

Step 3: Choose the Right Study Type

For research during residency, aim for feasible yet rigorous designs. Common formats in clinical informatics:

• Retrospective cohort or pre–post EHR data studies
  • Example: Pre- and post-implementation comparison of a CDS alert.
• Prospective QI with PDSA cycles
  • Example: Sequentially refining an order set using rapid cycles and monitoring key process metrics.
• Usability / human factors studies
  • Example: Think-aloud testing of a redesigned note template or order set with residents.
• Mixed-methods evaluations
  • Combine EHR usage metrics with surveys or focus groups to get both quantitative and qualitative insights.

Most resident schedules favor retrospective or pre–post designs, where data already exist, and you don’t have to recruit participants for months.

Step 4: Clarify IRB, Data Access, and Support

Before you dive into data:

• Discuss IRB requirements.

  • Many QI projects may qualify for expedited review or be deemed QI-only; others will need full IRB oversight.
  • Clinical informatics fellowship directors value understanding these distinctions.

• Secure data access early.

  • Identify who can query the data warehouse or EHR reporting system.
  • Clarify what PHI is necessary and how de-identification will be handled.
  • Arrange secure storage (e.g., institution-approved research drives, REDCap).

• Connect with analytic support.

  • A friendly analyst or biostatistician can shortcut months of frustration.
  • Some programs have “resident research consult services” for this purpose.

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Building Skills for a Future in Clinical Informatics Fellowship and Health IT

To stand out for a clinical informatics fellowship and health IT training roles later, be intentional about which skills your resident research projects help you develop.

Core Skill Areas to Target

1. EHR and Clinical Systems Literacy

   • Learn how order sets, note templates, flowsheets, and CDS rules are built and governed.
   • Participate in build or refinement for one project (e.g., new order set or alert logic).

2. Basic Data Analytics

   • Understand:
     • Data structures (tables, encounters, orders, lab results)
     • Common variables (visit IDs, patient IDs, timestamps)
     • Simple statistics: proportions, means, basic regression or time series
   • Tools might include:
     • SQL-based EHR reporting tools
     • Excel or R/Python basics
     • Data visualization platforms (Tableau, Power BI, institution-specific tools)

3. Measurement and Evaluation

   • Define process vs outcome vs balancing metrics:
     • Process: how care is delivered (e.g., percent of orders using new order set)
     • Outcome: patient health or safety (e.g., mortality, readmission)
     • Balancing: unintended consequences (e.g., increased clicks, alert fatigue)

4. Interdisciplinary Collaboration

   • Work with:
     • IT analysts and developers
     • Nursing and pharmacy leaders
     • QI and patient safety teams
     • Data scientists or statisticians
   • This is exactly the team environment you’ll encounter in both a clinical informatics fellowship and future hospital roles.

5. Communication and Change Management

   • Present your project to:
     • Department grand rounds
     • Informatics or CDS committee
     • Resident noon conference
   • Learn how to frame a data-driven story that clinicians and administrators can act on.

Practical Ways to Gain These Skills During Residency

• Join a Committee with a Data or IT Focus

  • EHR steering committee
  • CDS governance committee
  • Quality & safety committee

• Seek an Academic Residency Track or Scholarly Pathway

  • If your program offers an academic residency track, request assignment to mentors with informatics, QI, or health services research expertise.
  • Use required scholarly time to focus on EHR or digital health projects.

• Take Short, Focused Courses

  • Clinical research methods for residents
  • Intro to biostatistics or R/Python workshops
  • Short courses in health informatics or “Introduction to Health IT” offered by your institution or professional societies (e.g., AMIA).

Example Pathway: 3-Year Residency, Informatician Track

Year 1 (PGY-1): Exploration & Foundations

• Identify informatics mentors and projects.
• Complete a small QI project with an EHR component (e.g., order set cleanup).
• Attend institutional research or QI boot camps.
• Learn the basics of EHR usage logs and simple reporting tools.

Year 2 (PGY-2): Primary Project Execution

• Lead a more substantial resident research project:
  • Example: Pre–post evaluation of a redesigned CDS rule for high-risk medications.
• Submit an abstract to a national meeting (e.g., AMIA, your specialty society).
• Begin drafting a manuscript.

Year 3 (PGY-3): Dissemination and Leadership

• Complete and submit at least one manuscript.
• Take on a leadership role (e.g., resident champion for a digital initiative).
• Prepare your portfolio and personal statement for clinical informatics fellowship applications, highlighting your scholarly work.

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Making Your Projects Count: Output, Visibility, and Career Impact

Research matters most when it leads to tangible outputs—presentations, publications, tools, and leadership experiences that clearly support your future goals.

Aim for Multiple Forms of Dissemination

From a single well-designed project, aim for:

1. Local presentation

   • Department grand rounds
   • Resident research day
   • QI/informatics committee meeting

2. Regional or national presentation

   • Specialty society meetings (e.g., SHM, ACP, ACEP, AAP, depending on your residency)
   • Informatics-focused meetings (e.g., AMIA clinical informatics conference)

3. Peer-reviewed publication or short report

   • Traditional original research article
   • Brief report, implementation report, or QI report
   • Educational or perspectives piece describing your health IT experience

4. Institutional impact

   • Measure whether your intervention was adopted widely (e.g., order set made default for certain conditions, CDS rule integrated into standard workflows).

These outputs signal to fellowship directors that your research during residency was not just an academic exercise—it led to real change.

Positioning Your Research for Clinical Informatics Fellowship

When you apply for a clinical informatics fellowship, programs will look for:

• A coherent narrative tying your past experiences (including MD graduate residency research) to your interest in informatics.
• Evidence of:
  • Initiative and leadership
  • Ability to collaborate with IT and QI teams
  • Data literacy and basic analytic skills
  • Persistence in completing projects and publications

On your CV and personal statement, explicitly label relevant activities:

• “Resident Research Project (Clinical Informatics / EHR Optimization)”
• “Health IT Training / Clinical Systems Committee Participation”
• “Academic Residency Track – Informatics and Quality Improvement Focus”

In interviews, be prepared to discuss:

• Your research question and why it mattered clinically
• Your role in design, data collection, and analysis
• Challenges with data, IRB, or implementation—and how you overcame them
• What you learned about the intersection of clinical care, technology, and systems

Example: Turning a Routine QI Project into an Informatics Portfolio Piece

Scenario: Your program requires a QI project. Your team decides to improve VTE prophylaxis ordering.

You elevate this into a clinical informatics–relevant project by:

1. Mapping current EHR workflows and order sets.
2. Designing a CDS intervention (e.g., default prophylaxis orders, best-practice alerts for high-risk inpatients).
3. Quantitatively evaluating:
   • Adherence to prophylaxis guidelines (before vs after)
   • Alert firing and override rates
4. Qualitatively gathering feedback:
   • Short surveys of clinicians on alert usefulness and burden.
5. Publishing:
   • Abstract to a national meeting; manuscript to a QI or informatics journal.

In your fellowship application, you now highlight this as a clinical informatics project: combining EHR design, CDS, analytics, and change management.

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Practical Tips to Navigate Time, Mentorship, and Obstacles

Residency is demanding. To make research during residency realistic and sustainable, some practical strategies are essential.

Time Management Strategies

• Start early.
  The first year is ideal to identify mentors and project ideas, even if major work happens PGY-2.

• Protect your elective time.
  Request electives in:

  • Clinical informatics
  • Research/QI
  • Health services research

• Chunk your work.
  Break projects into manageable phases:

  • Month 1: define question and scope
  • Months 2–3: IRB and data access
  • Months 4–6: analysis and initial abstract
  • Months 7–9: refinement, manuscript drafting

• Use templates and institutional resources.

  • QI project charters
  • IRB application templates
  • Standard data request forms

Finding and Leveraging Mentors

You may need more than one mentor:

• Clinical mentor:
  Ensures clinical relevance and helps with departmental support.

• Informatics mentor:
  Offers guidance on EHR systems, data, and CDS design. This might be:

  • A CMIO or associate CMIO
  • An informatics-trained faculty member
  • A clinical informatics fellow

• Methodologic mentor:
  Provides input on study design, statistics, or qualitative methods.

Be explicit with your mentors:

“My goal is to build a portfolio for a future clinical informatics fellowship. I’d like at least one project that could reasonably lead to a presentation and publication. Can we design something together that fits that goal?”

Schedule regular check-ins (e.g., monthly) and arrive with specific updates and questions to keep progress moving forward.

Managing Common Barriers

• Limited data access or analytic support

  • Start smaller: a single clinic, unit, or service.
  • Use structured data elements that are easy to extract (e.g., order code, lab value, timestamps).
  • Collaborate with an existing project where someone already has a data pipeline.

• No formal clinical informatics department

  • Seek out:
    • QI office leaders
    • Hospital IT liaisons
    • Regional or system-level leaders (e.g., network CMIO)
  • Use online communities (AMIA, specialty societies) to find external mentors.

• Project scope creep

  • Start with a clearly defined, limited primary objective.
  • Add exploratory analyses only if time allows.
  • Your priority is to complete a high-quality, focused project, not to design a perfect but unfinished study.

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FAQs: Research During Residency for Clinical Informatics–Bound MD Graduates

1. Do I have to be in an “academic residency track” to do meaningful informatics research?

No. While an academic residency track can provide protected time and structure, many residents in community or hybrid programs successfully conduct informatics-oriented projects. The key is finding mentors and institutional partners (IT, QI, analytics teams) and choosing projects that are feasible in your context. Even smaller-scale initiatives, if well designed and evaluated, can be impressive.

2. How much research is “enough” for a clinical informatics fellowship application?

There is no rigid minimum, but a strong application typically includes:

• At least one primary resident research project with substantial involvement (design, data, analysis, or implementation).
• Ideally one or more abstracts or presentations at regional or national meetings.
• Preferably at least one publication (even as a co-author or in a QI journal).

Programs also value depth over quantity. A single well-executed project demonstrating informatics skills and real impact often outweighs multiple superficial projects.

3. I don’t know statistics or coding. Can I still do informatics research during residency?

Yes. While coding skills (e.g., R, Python, SQL) can be helpful, they are not mandatory at the start. You can:

• Partner with biostatistics or data science experts.
• Use institutional reporting tools that don’t require coding.
• Focus your personal learning on:
  • Understanding data structures and limitations
  • Interpreting results
  • Designing clinically meaningful interventions and metrics

Over time, if you’re motivated, you can gradually learn basic coding or analytics, but it’s not a prerequisite to begin.

4. How do I balance clinical workload with research and still avoid burnout?

Be intentional and realistic:

• Choose one primary project rather than many.
• Integrate your research with your existing clinical environment (e.g., a project in your continuity clinic or primary inpatient unit).
• Use scheduled electives and academic time strategically.
• Work with a mentor who respects your clinical demands and helps scope projects appropriately.
  Good projects should feel like they improve your day-to-day work, not just add to your burden—especially in clinical informatics, where you’re often solving real workflow problems you experience yourself.

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By approaching research during residency with a clear plan, targeted skill-building, and the right mentorship, you can transform your MD graduate residency years into a powerful launchpad for clinical informatics fellowship, health IT training, and a career at the intersection of medicine, data, and technology.