About FSCDR
The Foundation for Sickle Cell Disease Research is a growing multisite specialty medical organization dedicated to advancing sickle cell disease care, research, education, and improved patient outcomes.
FSCDR maintains a substantial and growing body of longitudinal clinical data. Our data are used to support clinical operations, population health management, quality improvement, research feasibility, grant initiatives, and organizational decision-making.
Position Summary
FSCDR is seeking an experienced, hands-on Senior Biostatistician and Clinical Analytics Lead to serve as the primary analytical thought partner to physician executive leadership.
This person will bridge the gap between our clinicians, researchers, operational leaders, and external data-development team. The successful candidate must be able to hear a medically or publicly health–framed question, identify the underlying analytical requirements, ask the necessary clinical and methodological questions, and translate the request into a precise, technically executable specification.
The selected consultant will not simply accept a data output because it was produced by a developer. This person will independently assess whether the population, definitions, source data, calculations, and results are clinically and statistically sound.
This is a senior, hands-on role. It is not solely a dashboard-development position, and it is not a management-only position.
Primary Responsibilities
Clinical and Analytical Translation
- Meet regularly with physician executive leadership to understand clinical, research, population health, and operational questions.
- Translate clinically framed questions into clear analytical specifications, including:
- Target population
- Inclusion and exclusion criteria
- Numerators and denominators
- Index dates and measurement periods
- Encounter types and statuses
- Laboratory definitions, units, thresholds, and timing
- Patient-level versus encounter-level calculations
- Required stratifications and comparison groups
- Anticipate analytical questions and data limitations before presenting results.
- Reduce the amount of detailed technical instruction currently required from physician leadership.
- Distinguish between operational reporting, quality improvement, research analysis, and clinical decision-support needs.
EHR and Registry Data Quality
- Evaluate raw and transformed data from eClinicalWorks and FSCDR’s separate patient registry.
- Assess data for completeness, accuracy, consistency, plausibility, timeliness, duplication, missingness, and fitness for the intended use.
- Reconcile dashboard and report counts against source-system data.
- Investigate discrepancies involving patients, encounters, appointments, diagnoses, medications, laboratory results, procedures, locations, and providers.
- Identify duplicate patient records, inconsistent patient identifiers, invalid values, missing variables, unit discrepancies, and incorrect date or encounter logic.
- Develop and maintain a data-quality issue log, including severity, root cause, responsible party, corrective action, and validation status.
- Recommend systematic improvements to data capture and documentation when source-system practices are contributing to unreliable reporting.
Metric Definition and Data Governance
- Establish and maintain a clinical analytics data dictionary.
- Document approved definitions for FSCDR’s core operational, clinical, research, and population health measures.
- Create clear source-to-report lineage showing where each metric originates and how it is calculated.
- Define validation criteria that must be satisfied before a dashboard, report, patient list, or metric is released to leadership.
- Maintain version control and documentation when definitions or business rules change.
- Help establish a consistent process for requesting, prioritizing, developing, testing, approving, and updating analytics products.
Collaboration With Developers and BI Resources
- Serve as FSCDR’s internal clinical and statistical liaison to external developers, data engineers, and Power BI resources.
- Convert leadership requests into complete development specifications rather than forwarding vague or incomplete instructions.
- Review SQL logic, data transformations, joins, filters, calculated fields, and aggregation methods.
- Perform independent SQL queries or other analytical checks to confirm results.
- Conduct user-acceptance testing of new and revised dashboards.
- Verify that Power BI measures, filters, drilldowns, date logic, and patient counts behave as intended.
- Clearly identify when an issue is caused by source data, extraction logic, transformation logic, dashboard logic, or an inappropriate clinical definition.
- Track outstanding developer questions, corrections, validation results, and release decisions.
Biostatistical and Research Support
- Create reproducible analytical datasets from EHR, registry, and other approved data sources.
- Conduct descriptive and inferential analyses appropriate to the question.
- Analyze longitudinal patient data, utilization patterns, treatment patterns, laboratory trends, gaps in care, clinical outcomes, and research feasibility.
- Develop statistical analysis plans and document assumptions, exclusions, missing-data decisions, and methodological limitations.
- Use appropriate methods for categorical, continuous, longitudinal, repeated-measures, time-to-event, and other clinical data when required.
- Support clinical research abstracts, manuscripts, presentations, grant applications, protocol development, and evaluation activities as assigned.
- Provide statistically accurate tables, figures, summaries, and interpretations for clinical and nontechnical audiences.
- Clearly distinguish association, prediction, and causation and prevent overinterpretation of findings.
Communication and Decision Support
- Present findings in clear language that physicians, executives, operational leaders, and developers can understand.
- Explain not only what the data show, but also:
- Whether the result is reliable
- What may be missing
- What assumptions were made
- What limitations apply
- What additional questions should be examined
- Proactively flag clinically implausible findings, unexpected trends, data-quality risks, and material discrepancies.
- Maintain organized documentation so that analyses and metrics can be reproduced without relying on undocumented institutional memory.
Privacy and Security
- Work only within FSCDR-approved data environments and access controls.
- Follow all applicable HIPAA, privacy, security, confidentiality, human-subject research, and data-use requirements.
- Complete required privacy and security training before receiving access to protected information.
- Use the minimum patient-level information necessary for each approved purpose.
First 90-Day Deliverables
Days 1–30: Discovery and Initial Validation
The consultant will:
- Complete an initial inventory of available EHR, registry, dashboard, and reporting data sources.
- Document the current flow of data from eClinicalWorks and other source systems into Power BI and other reporting outputs.
- Review existing dashboards, extracts, recurring reports, and outstanding leadership concerns.
- Audit at least five high-priority measures or dashboard components as defined by FSCDR President.
- Establish a centralized data-quality and analytics issue log.
- Identify immediate high-risk discrepancies requiring correction.
- Create an initial prioritized analytics and remediation work plan.
Days 31–60: Definitions, QA Standards, and Corrective Work
The consultant will:
- Develop approved definitions for at least 15 priority clinical, operational, and population health measures.
- Create the first version of the FSCDR Clinical Analytics Data Dictionary.
- Establish a standardized dashboard and report validation checklist.
- Develop written specifications for correcting identified high-priority logic or data problems.
- Work with developers to implement and test corrections.
- Conduct at least two priority analyses requested by physician leadership.
- Document known limitations in EHR and registry data and recommend remediation strategies.
- Begin evaluating patient matching, duplication, and reconciliation between the EHR and registry datasets.
Days 61–90: Stabilization and Ongoing Analytics Structure
The consultant will:
- Complete validation of FSCDR’s agreed-upon priority dashboards or dashboard components.
- Deliver a baseline EHR and registry data-quality assessment.
- Present a prioritized remediation roadmap identifying:
- Critical immediate corrections
- Source documentation improvements
- Developer or pipeline changes
- Longer-term data-governance needs
- Finalize the initial metric dictionary and source-to-report documentation.
- Establish a repeatable analytics request, development, testing, and approval process.
- Deliver an initial EHR-to-registry reconciliation or linkage assessment.
- Recommend the appropriate ongoing consultant workload and whether any additional data-engineering or BI support is needed.
- Establish a recurring clinical analytics review with physician and executive leadership.
Required Qualifications
- Master’s degree or doctoral degree in biostatistics, epidemiology, statistics, public health, health services research, clinical informatics, biomedical informatics, or a closely related quantitative discipline.
- At least five years of progressively responsible experience analyzing clinical, EHR, registry, claims, public health, or health-system data.
- Demonstrated experience working directly with raw or minimally processed healthcare data—not only analysis-ready datasets.
- Strong command of epidemiologic and biostatistical principles, including cohort construction, study design, bias, confounding, missing data, statistical inference, and longitudinal analysis.
- Strong SQL skills and the ability to independently inspect, query, reconcile, and validate source data.
- Advanced proficiency in at least one statistical programming environment, such as R, SAS, Stata, or Python.
- Experience evaluating the accuracy of dashboards, calculated metrics, filters, denominators, and patient-level outputs.
- Working knowledge of clinical data structures, medical terminology, diagnoses, encounters, laboratory data, medication data, and longitudinal patient records.
- Ability to translate physician and executive questions into rigorous analytical requirements.
- Ability to identify important questions and methodological concerns without requiring step-by-step direction.
- Exceptional written and verbal communication skills.
- Demonstrated ability to communicate effectively with physicians, researchers, executives, developers, and nontechnical staff.
- Experience working with protected health information and regulated healthcare data.
- Availability for one or two recurring weekly meeting during Eastern Time business hours (and flexibility in the start-up phase for more)
Preferred Qualifications
- Direct experience with eClinicalWorks data.
- Experience with Power BI, including the ability to inspect or validate semantic models, measures, filters, relationships, and DAX logic.
- Experience with patient registries and record linkage across multiple clinical datasets.
- Experience with hematology, sickle cell disease, oncology, rare disease, chronic disease, or complex specialty-care populations.
- Experience in population health, quality improvement, health-services research, or clinical research.
- Familiarity with ICD-10-CM, CPT/HCPCS, LOINC, RxNorm, and other healthcare coding or terminology systems.
- Experience supporting abstracts, manuscripts, grant applications, IRB protocols, or clinical research feasibility analyses.
- Experience working with multisite outpatient healthcare organizations.
- Experience overseeing or directing external data-development vendors.
This Position Is Not a Fit For
This position is not intended for candidates whose experience is limited to:
- Software or dashboard development without healthcare analytics experience
- Dashboard design without responsibility for validating the underlying clinical logic
- Analysis of clean, research-ready datasets without experience investigating raw EHR data
- General business intelligence without biostatistical or epidemiological training
- Purely academic statistical work without direct collaboration with clinicians and technical teams
- Entry-level candidates requiring detailed instructions for each analysis
Work Arrangement
The first 90 days are expected to require approximately 20-25 hours per week due to discovery, data assessment, documentation, and remediation work. Following the initial period, the engagement is anticipated to average approximately 15-20 hours per week depending on organizational priorities.
Pay: $70.00 - $85.00 per hour
People with a criminal record are encouraged to apply
Work Location: Remote
