Coding Manager Jobs in Gaithersburg, MD (NOW HIRING)

General Summary of Position
The Coding Revenue Cycle Data Analyst is responsible for analyzing interpreting and reporting on revenue cycle performance data to support operational efficiency financial optimization regulatory compliance and strategic decision-making across the organization. This role partners closely with Revenue Cycle Operations Coding CDI HIM Revenue Integrity Quality to identify trends monitor coding performance support auditing activities and improve documentation and coding outcomes.

Primary Duties and Responsibilities

• Contributes to the achievement of established department goals and objectives and adheres to department policies procedures quality standards and safety standards. Complies with governmental and accreditation regulations.
• Validates data integrity across reporting systems and ensures accuracy consistency and reliability of all coding-related data outputs.
• Analyzes coding accuracy productivity reimbursement and quality performance metrics.
• Monitors and trends coding-related KPIs including: DNFB (Discharged not final billed); denial trends coding productivity and accuracy audit findings DRG shifts case Mix Index severity of illness (SOI) Risk of Mortality (ROM) query rates and outcomes coding turnaround times physician documentation trends CC/MCC capture rates and quality measure impacts.
• Develops and maintains coding dashboards scorecards operational reports and executive reporting tools to support leadership decision-making & department stakeholders.
• Creates visualizations and dashboards using business intelligence tools such as: Power BI Tableau Epic reporting tools Solventum reporting tools and Excel.
• Utilizes advanced analytics to forecast trends identify risk areas and support proactive operational planning.
• Identifies coding trends documentation gaps compliance risks and opportunities for operational improvement.
• Supports internal and external coding audit programs through data collection analysis and reporting.
• Supports denial prevention and recovery initiatives by performing root cause analysis related to coding denials reimbursement variances and audit findings.
• Participates in revenue cycle optimization projects and system implementations.
• Analyzes the impact of coding and documentation on reimbursement quality scores and public reporting metrics.
• Participates in multi-disciplinary quality and service improvement teams.

Minimal Qualifications
Education

• Bachelor's degree in Health Information Management; Healthcare Administration; Data Analytics; Business Administration; Health Informatics; Finance required and
• Master's degree preferred

Experience

• 3-4 years Healthcare coding, HIM, CDI revenue cycle analytics required and
• 1-2 years Inpatient and/or outpatient coding operations required and
• 1-2 years Coding audits quality reviews and reimbursement analytics required and
• 1-2 years Working with healthcare data systems and reporting platforms required

Licenses and Certifications

• CCS (Certified Coding Specialist) preferred or
• CPC (Certified Professional Coder) preferred or
• RHIA (Registered Health Information Administrator) preferred or
• CRCR (Certified Revenue Cycle Representative) preferred or
• CHFP (Certified Healthcare Financial Professional) preferred

Knowledge Skills and Abilities

• Excellent verbal and written communication skills.
• Excellent computer skills required.
• Clinical system software skills (e.g. Solventum electronic medical record).
• Strong knowledge of Outpatient Payment and regulatory systems.
• Strong knowledge of MS-DRG and APR-DRG methodologies
• Strong knowledge of ICD-10-CM/PCS
• Strong knowledge of CPT/HCPCS coding
• Strong knowledge of medical necessity
• Strong knowledge of quality reporting programs
• Strong analytical and critical thinking skills
• Ability to interpret complex coding reimbursement and quality data.
• Excellent organizational and problem-solving abilities.
• Ability to work independently and collaboratively in a fast-paced healthcare environment.
• Attention to detail and commitment to data accuracy.