If you’re a medical student, resident, or fellow looking to publish your first research paper, a chart review study (also known as a retrospective cohort study) is a common and approachable entry point. These studies use existing patient records from your institution to explore clinical questions—like outcomes, correlations, or quality improvement metrics—without recruiting new participants.

But while chart reviews sound simple in concept, they’re often slowed by institutional approvals and the sheer manual effort required to extract and review data. Below, we’ll break down each phase so you can set realistic expectations from idea to submission.

Phase 1: Idea Generation and Feasibility (2–4 weeks)

Every chart review starts with a focused, answerable question—something like, “What is the 30-day readmission rate for patients with heart failure who received early follow-up?”

During this phase:

• Identify a clinical question relevant to your patient population.
  Conduct a quick literature review to ensure your idea adds something new.
• Confirm that your institution’s EMR contains the data fields you’d need (diagnoses, procedures, outcomes, etc.).
  Assemble your study team, including a mentor and possibly a statistician.

Pro tip: Discuss data availability early. Knowing what’s possible in your EMR system will prevent delays later when you need to define your patient list or variables.

If your research question could also be answered using a large public dataset, see our Database Study Timeline, which outlines an alternative approach that doesn’t require EMR access or manual chart abstraction.

Phase 2: IRB and Data Access Approvals (2–3 months)

This phase is often the biggest bottleneck—and unfortunately, it’s one that’s hard to speed up. Even though chart reviews use existing data, you still need institutional review board (IRB) approval before touching any patient information.

During this phase:

• Draft and submit your IRB protocol, detailing your study design, data plan, and privacy safeguards.
• Wait for IRB approval (typically several weeks to months, depending on your institution).
• Once approved, request data access or a patient list from your data warehouse, IT department, or research informatics team.
  

These two steps—IRB approval and data access—cannot happen in parallel. You’re not allowed to access patient data until your IRB approval is finalized.

Common bottleneck: Getting your initial patient list. This requires someone else (often the data warehouse or informatics team) to extract charts that meet your inclusion criteria, which can take several more weeks after IRB approval.

Phase 3: Data Extraction and Chart Abstraction (1 month – 1 year)

Once you have your patient list, it’s time to review charts and collect data. This phase varies dramatically depending on sample size and the number of data points you’re collecting.

During this phase:

• Create a data abstraction form (often in Excel or REDCap).
• Review each chart for relevant variables and enter them manually.
• Check for missing or inconsistent data.
• Periodically meet with your team to confirm you’re interpreting variables consistently.

If you’re working as a team, calibration is key. Spend the first several dozen charts reviewing the same patients together to ensure everyone defines variables the same way. Uncalibrated reviewers can introduce major bias or inconsistencies in your dataset.

Pro tip: Define every variable clearly before you start, including what counts as “present” or “absent.” This consistency can make or break your study.

Phase 4: Analysis and Interpretation (2–4 weeks)

With your dataset ready, it’s time to analyze your results.

During this phase:

• Meet with a statistician to confirm your analytic plan.
• Run descriptive and inferential statistics.
• Create tables and figures.
• Interpret the findings in the context of prior research.

If you’re new to research or statistics, expect some iteration and back-and-forth here as you learn to interpret results and refine your models.

Phase 5: Manuscript Writing and Submission (3–6 weeks)

Now it’s time to bring everything together into a publishable paper.

During this phase:

• Draft your abstract, introduction, methods, results, and discussion.
• Format your manuscript according to your target journal’s guidelines.
• Circulate drafts among co-authors for feedback and revisions.
• Submit to a journal.

Journals that often publish chart reviews include subspecialty, regional, or educational journals, depending on your topic and study design.

Total Estimated Timeline: 6–12 Months (Idea → Submission)

On average, a chart review project takes six months to a year from idea to submission. The biggest delays usually occur during IRB approval and manual data abstraction. While these studies are feasible for motivated trainees, they require sustained organization and persistence.

Even after submission, getting chart reviews published can be challenging. Because they’re often single-center retrospective studies, reviewers may question how generalizable the results are beyond your institution. That’s why it’s important to frame your findings thoughtfully and acknowledge these limitations in your discussion.

The Faster Alternative: Database Studies with Lumono

Unlike chart reviews, database studies eliminate the need for manual chart abstraction altogether. Instead of collecting data one patient at a time, you can analyze large, nationally representative datasets that are already cleaned and structured for research.

With Lumono, you can:

• Instantly explore pre-loaded public health databases (like NHANES)
• Get AI-assisted guidance on forming a strong research question
• Automatically run statistical analyses
• Generate publication-ready outputs in days or weeks, not months

If you’re curious how this compares, check out our Database Study Timeline and Case Report Timeline to see where each type of project fits in your research journey.