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Hire a Dedicated Electronic Health Records (EHR) Data Analyst in the Philippines
Recruitment, HR, payroll, workspace and infrastructure support
Turn authorised electronic health record data into clear, checked reporting with a dedicated EHR data analyst. KamelBPO employs your analyst in the Philippines; your healthcare and data owners define access, measures and clinical interpretation.
Request Your QuoteElectronic Health Records (EHR) Data Analyst Outsourcing Cost Calculator
Your calculator selections will accompany your request.
How We Recruit and Support Your Electronic Health Records (EHR) Data Analyst
From your first brief to ongoing support, here is how offshoring with KamelBPO works.
Recruitment is always free for new and existing clients. No recruitment contract or commitment to hire.
Our client service agreements are month-to-month.
Share your job description
Send us the responsibilities, skills and experience you need. Include the tools, working hours and other requirements, including any duties that require someone at your premises.
Receive your quote
We provide a quote based on your requirements, so you can review the staffing cost before recruitment begins.
Talk through the role
On a discovery call, we discuss your business, priorities and expectations to clarify the brief and what a suitable candidate looks like. We also explore your broader business needs and plans to scale, identifying other ways we can support your team.
Review pre-screened candidates
We begin recruiting and send you pre-screened resumes. Choose the applicants you would like to meet, and we refine the search together as your preferences become clearer.
Meet candidates and share feedback
We arrange video interviews so you can meet applicants face-to-face, with your KamelBPO account manager joining the conversation. Be candid about what fits and what does not. Your feedback at any stage helps us focus the search.
Choose your hire and onboard
KamelBPO employs and onboards your chosen candidate with a six-month probationary period. Assess long-term fit against performance standards made clear at the start, with our support through regularization.
Ongoing support for you and your EHR data analyst
Manage your EHR data analyst’s day-to-day work as you would an in-office team member. Bring them into your company culture and, if useful, give them an email address on your domain; we also provide a KamelBPO email address.
Alongside the HR, payroll, benefits, workplace infrastructure, security and 24/7 IT support included in your monthly fee, your dedicated account manager can help you establish KPIs, review progress, deliver constructive feedback and address performance concerns through documented improvement plans. Additional support can include coordinating bonuses and incentives, team activities, work arrangements and equipment requests.
Based in Clark, Pampanga, KamelBPO provides 24/7 client support, with as much or as little involvement as you prefer.
Have a role in mind? Tell us what you need.
Request Your QuoteWhat Your Electronic Health Records (EHR) Data Analyst Can Handle
Build reporting that your operational and clinical stakeholders can interpret, trace and review.
- Data preparation: Extract or work from approved EHR datasets, clean records and document transformations.
- Quality checks: Investigate missing fields, duplicate records, inconsistent codes and unexpected changes in reporting totals.
- Reports and dashboards: Produce agreed operational or quality reports with clear definitions, date ranges and caveats.
- Trend analysis: Explore patterns in approved measures and explain possible data or workflow causes without making clinical conclusions.
- Change validation: Compare outputs after approved report, mapping or migration changes and document unresolved differences.
Electronic Health Records (EHR) Data Analyst Skills, Tools and Experience
Examples to guide your hire. The skills, tools and qualifications below are not an exhaustive list; requirements depend on your brief.
Technical Skills
Healthcare data knowledge combined with reproducible analysis and access discipline.
- Healthcare records
- Understand patients, encounters, appointments and relevant clinical or administrative terminology.
- Recognise that coding, timing and workflow changes can affect a measure.
- Queries and preparation
- Use appropriate joins, filters and aggregation without duplicating encounters or changing the denominator.
- Document transformations and keep source-to-report logic reproducible.
- Data quality
- Check completeness, consistency and unexpected variation against agreed rules.
- Distinguish missing data from a true zero and investigate outliers before reporting them.
- Reporting and confidentiality
- Explain definitions, exclusions, refresh dates and limitations to stakeholders.
- Use approved access and minimum necessary data; keep sensitive information out of unauthorised exports and test files.
Soft Skills
How an analyst works with clinical, operational and information teams.
- Careful questioning
- Clarify what a measure is intended to support before building the report.
- Analytical judgement
- Challenge surprising results and identify limitations rather than presenting false precision.
- Plain-language explanation
- Explain data issues and technical findings to non-technical stakeholders.
- Discretion and collaboration
- Handle sensitive records carefully and seek validation from the appropriate subject-matter owner.
Tools and Platforms
Match experience to the systems your team uses. These are alternatives and specialisms; every candidate need not know every tool, and software licences depend on your agreed setup.
- EHR reporting
- Epic reporting tools, including SlicerDicer — explore authorised healthcare measures where your organisation uses Epic. Specify any Clarity or Caboodle reporting requirements separately.
- Queries and preparation
- SQL with your approved database tools — query and reconcile reporting datasets.
- Microsoft Excel and Power Query — clean authorised extracts and perform repeatable checks.
- Dashboards
- Microsoft Power BI — build or maintain approved data models and reporting views.
- Tableau — create interactive reporting within a team already using Tableau.
- Programmatic analysis
- Python with pandas — automate repeatable data checks where coding and an approved analysis environment are part of the brief.
Which Experience Level Fits Your Team?
The skills and tools above apply across levels. Compare the work, judgement, relevant background and support your brief requires.
For established extracts, checks and reporting definitions
- Scope of work
- Prepare routine reports and investigate straightforward data-quality exceptions.
- Technical proficiency
- Use basic queries, spreadsheets and documented report logic under review.
- Problem-solving
- Identify missing data, duplicate rows or mismatched totals and raise uncertainty early.
- Quality checks
- Reconcile counts and totals with a reference report and document changes.
- Business and stakeholder understanding
- Understand the intended audience and avoid presenting operational data as clinical advice.
- Independence and delivery
- Work from defined measures with regular technical and subject-matter review.
- Education and relevant experience
- Relevant study in health information, informatics, statistics or computing, or equivalent practical training, can help; assess a de-identified data exercise.
For independently developed and maintained reporting
- Scope of work
- Own a defined reporting area from requirements and extraction through stakeholder review.
- Technical proficiency
- Write reliable queries, prepare datasets and build usable dashboards in the client’s stack.
- Problem-solving
- Trace discrepancies across joins, definitions, source updates and workflow changes.
- Quality checks
- Create repeatable validation checks and maintain a clear data dictionary and change history.
- Business and stakeholder understanding
- Explain denominators, exclusions and refresh timing to clinical or operational users.
- Independence and delivery
- Deliver routine analysis independently while escalating access, clinical interpretation and uncertain definitions.
- Education and relevant experience
- Look for healthcare reporting experience with comparable datasets, plus evidence of accurate and reproducible work.
For complex definitions, cross-system analysis and review
- Scope of work
- Coordinate complex reporting requirements and validation across multiple data sources or stakeholder groups.
- Technical proficiency
- Review analytical design, reusable data models and the effect of source or mapping changes.
- Problem-solving
- Lead investigation of persistent discrepancies and assess alternative explanations with domain owners.
- Quality checks
- Set review standards, challenge misleading measures and support controlled migration or reporting changes.
- Business and stakeholder understanding
- Connect measures to decisions while explaining attribution limits and possible unintended interpretations.
- Independence and delivery
- Work with limited routine oversight and guide analysts when assigned; retain clinical and access approvals with authorised owners.
- Education and relevant experience
- Require substantial evidence in comparable healthcare data work; qualifications such as health-data certifications may help but do not replace system-specific competence.
This is an analytical role, not clinical practice or automatic EHR administration. Coding audits, interface development, statistical modelling and platform certification requirements should be specified separately.
What to Look for in an Electronic Health Records (EHR) Data Analyst
Use these checks to compare candidates against your actual brief.
- De-identified exercise: Ask the candidate to find duplicates, reconcile encounter counts and explain a query.
- Measure definition: Review how they would define a denominator, exclusion and reporting period.
- Healthcare context: Ask how workflow or coding changes can alter a trend without a real change in performance.
- Traceable handoff: Check whether someone else could reproduce the analysis from the documented sources and logic.
Ready to find the right person for your team?
Request Your QuoteWorking With Your Electronic Health Records (EHR) Data Analyst
Set up the work
- Agree the measures: Name each report’s audience, definition, denominator and subject-matter approver.
- Approve data access: Confirm systems, permissions and permitted data handling before sharing records.
- Validate first outputs: Reconcile with a trusted source and document unexplained differences before release.
- Control changes: Keep report definitions, versions and approvals together; reassess outputs after source changes.
Electronic Health Records (EHR) Data Analyst KPI Examples
Choose a small set of measures that reflects the agreed responsibilities. Establish a baseline, review period and quality standard together; these examples are not guaranteed targets.
| Area | What to measure or review |
|---|---|
| Validated reporting accuracy | Sample outputs against approved definitions and reconciled source counts; record material errors and their causes. |
| Data-quality resolution | Track exceptions by severity, owner and age, separating source-system fixes from analyst-controlled work. |
| Reporting timeliness | Measure delivery against agreed schedules after required source data becomes available. |
| Reproducibility | Check whether queries, transformation steps and definitions allow another authorised analyst to reproduce the result. |
| Change validation | Track planned checks completed and unresolved differences after report or data changes. |
| Stakeholder usefulness | Review whether reports answer the agreed question and explain limitations; do not attribute patient outcomes to the analyst alone. |
Electronic Health Records (EHR) Data Analyst FAQs
The requirement depends on the work. Healthcare data and terminology knowledge may be sufficient for defined reporting, while clinical interpretation needs the appropriate qualified owner. Specify any mandatory credential in the brief.
Yes. Specify the product, reporting tools, access and any certification requirements. Experience with general dashboards does not establish competence in every EHR data model.
Your organisation must approve the access arrangement and applicable requirements before work starts. Where suitable, use de-identified or limited datasets. Staffing a role does not by itself establish permission to transfer or access patient records.
They can support mapping checks, reconciliation and validation when included in the brief. Migration engineering, interface changes and production cutover need their own scope and responsible owners.
No clinical decision-making is implied. The analyst prepares and explains data; authorised clinical professionals interpret it for patient care.
Yes. Provide prior outputs, source definitions and relevant system or workflow changes. The analyst should test data and calculation causes before suggesting a real-world explanation.
Which Role Fits Your Needs?
Choose the responsibility you need covered; titles and specialisms can overlap.
Hire an Electronic Health Records (EHR) Data Analyst
Build reporting that your operational and clinical stakeholders can interpret, trace and review.
Data Analyst
Choose a broader data-analysis brief when the data is not primarily healthcare records and EHR workflow knowledge is not central.
EHR Analysis Examples in Healthcare
Illustrative uses and the background that can help a candidate fit your assignment.
Hospitals and health systems
- Example work: Reconcile encounter reporting and investigate operational data-quality exceptions.
- Useful background: Complex encounter structures and approved measure definitions.
Outpatient practices
- Example work: Build checked appointment, activity and documentation reports.
- Useful background: Practice workflows, status changes and source-system limitations.
Healthcare reporting teams
- Example work: Validate reporting datasets or compare results after approved changes.
- Useful background: Data dictionaries, repeatable queries and documented review procedures.
Request Your Electronic Health Records (EHR) Data Analyst Quote
Tell us about the work, experience and tools you need. We will confirm a quote against your requirements.