Observational research
EDC for Observational Studies and Registries
A managed EDC database for cohort, case-control, cross-sectional and registry studies, built from your protocol and questionnaire/form by researchers who run observational studies themselves.
Observational studies rarely have the budget or the programming team of a clinical trial, yet they need the same things from their data: consistent definitions across sites, complete follow-up, and a record of every change. ResearchGuru builds, hosts and supports the database, so your team can spend its time on recruitment and data quality.
Illustrative example
Study designs
One platform for the main observational designs
Each design puts different demands on the database. We configure the eCRF around yours rather than fitting your study to a template.
What we build
An eCRF that matches your protocol, item by item
You send the approved protocol and questionnaire/form. We turn them into an electronic Case Report Form with short, standard item codes, coded answer lists and the logic your protocol describes, then test it with you before it goes live.
Data can be entered by site staff, reported by participants on their own phone, or both in the same study.
Typical components
| Variable | Values | Rule |
|---|---|---|
smoke_yn | 1 = Yes · 0 = No | Required |
smoke_cpd | Integer 0 to 100 | If smoke_yn = 1 |
visit_dt | Date | Not in future |
Data quality
Clean data while the study is running, not after it closes
In a paper or spreadsheet study, errors surface at analysis, months after the participant has gone home. In the EDC, checks run as data are entered and again overnight, so questions reach the site while they can still be answered.
Built-in controls
| Arm A N = 71 | Arm B N = 71 | Total N = 142 | ||
|---|---|---|---|---|
| Systolic blood pressure (mmHg) | ||||
| n | 70 | 69 | 139 | |
| Mean (SD) | 128.4 (14.2) | 131.1 (15.0) | 129.7 (14.6) | |
| 95% CI | (125.0, 131.8) | (127.5, 134.7) | (127.3, 132.2) | |
| Median (Q1–Q3) | 127 (118–138) | 130 (121–141) | 129 (119–139) | |
| Sex, n (%) | ||||
| Female | 38 (53.5%) | 35 (49.3%) | 73 (51.4%) | |
| Male | 33 (46.5%) | 36 (50.7%) | 69 (48.6%) | |
Illustrative example
Worked example (dummy data)
A case-control study, from enrolment to odds ratios
Our demonstration project is a hospital-based case-control study of risk factors for a first myocardial infarction. It holds 1,000 dummy records: 400 cases and 600 controls, frequency-matched on ten-year age band and sex, entered at three sites.
The same project carries 40 saved outputs in the built-in TFL dashboard: ten tables, ten figures, ten listings and ten analyses, including chi-square tests, odds ratios with confidence intervals and a multivariable logistic regression. All figures are dummy data, generated for demonstration.
Outputs are for study monitoring, exploration and reporting. For a regulatory submission, final analyses are reproduced in the validated statistical software named in the SAP.
Frequently asked questions
Observational studies: common questions
Something else? Get in touch and a senior researcher will answer.
Usually, yes. The cost of a spreadsheet study is paid later, in cleaning, reconciling versions and explaining changes nobody recorded. A managed EDC gives a small study validated entry, an audit trail and controlled exports without a programming team.
Yes. A study can combine staff-entered forms with participant-reported questionnaires, each with its own access route and permissions.
Yes. Visit plans, visit windows and reminders are configured to your protocol, and new items can be added during the study through a documented change-control process.
Tell us about your observational study
Send us your protocol and questionnaire/form. We'll review the proposed structure and come back to you with:
Or email admin@edcstat.com · call +44 7484 816484