Clinical SAS (Statistical Analysis System) refers to the application of SAS software specifically within the context of clinical research and healthcare. SAS is a powerful tool widely used in the pharmaceutical and biotechnology industries for managing, analysing, and reporting clinical trial data. Here’s an in-depth look at its key aspects and applications in clinical research:
Applications of Clinical SAS
- Data Management: SAS is extensively used for managing clinical trial data throughout the data
- Data Integration: Combining data from multiple sources (e.g., EDC systems, laboratory databases).
- Data Cleaning: Identifying and resolving data discrepancies and errors.
- Data Transformation: Preparing data for analysis by transforming variables, creating derived variables, etc.
- Data Quality Assurance: Ensuring data integrity and consistency.
- Statistical Analysis: SAS provides a comprehensive suite of statistical procedures for analysing
- Descriptive Statistics: Summary statistics (mean, median, standard deviation, etc.).
- Inferential Statistics: Hypothesis testing, confidence intervals, correlation, regression analysis.
- Advanced Modelling: Survival analysis, logistic regression, mixed models, non-parametric tests.
- Reporting and Visualization: SAS allows for the creation of standardized and customized reports required for clinical trial monitoring, regulatory submissions, and scientific publications:
- Graphical Output: Generating graphs (e.g., bar charts, scatter plots, Kaplan-Meier plots) to visualize data.
- Tabular Output: Producing tables summarizing study results, adverse events, patient demographics, etc.
- Ad Hoc Reporting: Creating ad hoc reports based on specific data queries and analyses.
- CDISC Standards: SAS supports CDISC (Clinical Data Interchange Standards Consortium) standards for data formatting and submission to regulatory agencies:
- SDTM (Study Data Tabulation Model): Standardizes the structure and content of clinical trial data for analysis.
- ADaM (Analysis Data Model): Defines datasets and metadata for statistical analysis.
- Safety Analysis and Pharmacovigilance: SAS is used for analysing safety data and adverse events
- Signal Detection: Identifying potential safety signals based on adverse event patterns.
- Safety Surveillance: Monitoring safety profiles of investigational drugs throughout clinical development.
Skills Required for Clinical SAS
- SAS Programming: Proficiency in SAS programming languages including Base SAS, SAS Macro Language, SAS/STAT, and SAS/GRAPH.
- Clinical Trial Knowledge: Understanding of clinical trial design, protocols, and regulatory requirements.
- Data Management Skills: Ability to manage and manipulate large datasets, ensure data quality, and perform data transformations.
- Statistical Analysis: Knowledge of statistical methods and their application in clinical research using SAS procedures.
- CDISC Standards: Familiarity with CDISC standards (SDTM, ADaM) and their implementation in SAS.
Eligibility – Diploma in SAS – 6 months
- Life Science and Health Care Graduates or Diploma in any Discipline
- B.Sc/M.Sc.,Biotechnology, Microbiology, Genetics, Biochemistry, DMLT, MLT
- M.B.B.S.M.D., MS.
- B.D.S., M.D.S., B.V.SC, M.V.Sc, B.PTh, M.PTh, OPTh, ANM, GNM.
- B.H.M.S., B.A.M.S, B.U.M.S, B.Sc Nursing
- B. Pharma, M.Pharma, D.Pharma
- For SAS: B.C.A, B.com, BCCA, B.E. Any Other Graduates.
- Highly interested participate in the final year can also apply.
Career Opportunities
Professionals proficient in Clinical SAS can pursue various roles in the pharmaceutical, biotechnology, and healthcare industries, including:
- SAS Programmer: Specializes in programming SAS for clinical trials, focusing on data management, analysis, and reporting.
- Statistical Programmer: Works on statistical analysis and programming using SAS for clinical trial data.
- Clinical Data Manager: Handles data collection, cleaning, and management using SAS.
- Biostatistician: Utilizes SAS for advanced statistical modelling and analysis in clinical research.
Training and Certification
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- SAS Certification: IICRM offers certifications such as SAS Certified Programmer, Clinical Trials Programmer, which validate proficiency in SAS skills relevant to clinical research.
In summary, Clinical SAS is essential for ensuring data integrity, conducting robust statistical analyses, and generating accurate reports in clinical research. Its versatility and powerful analytical capabilities make it a cornerstone in the pharmaceutical industry’s efforts to develop safe and effective treatments through rigorous clinical trials.
- SAS Certification: IICRM offers certifications such as SAS Certified Programmer, Clinical Trials Programmer, which validate proficiency in SAS skills relevant to clinical research.
Diploma in Medical coding: 6 months
Medical coding is the process of converting a patient’s healthcare information, including medical procedures, diagnoses, necessary medical equipment, and medical services, from the physician’s notes. A medical coder transforms this information into universal medical alphanumeric codes.
Eligibility – Diploma in Medical coding
- Life Science and Health Care Graduates or Diploma in any Discipline
- B.Sc/M.Sc.,Biotechnology, Microbiology, Genetics, Biochemistry, DMLT, MLT
- M.B.B.S.M.D., MS.
- B.D.S., M.D.S., B.V.SC, M.V.Sc, B.PTh, M.PTh, OPTh, ANM, GNM.
- B.H.M.S., B.A.M.S, B.U.M.S, B.Sc Nursing
- B. Pharma, M.Pharma, D.Pharma
- For SAS: B.C.A, B.com, BCCA, B.E. Any Other Graduates.
- Highly interested participate in the final year can also apply.
AI application in medical coding
Cognitive Automation for Personalized Coding: AI can analyse a patient’s medical history, genetics, and current condition to predict the most likely future procedures and diagnoses. This allows for pre-emptive coding, streamlining billing processes and ensuring accurate reimbursement for complex or evolving cases.
Career Opportunities
- Assigning Codes: Accurately assign ICD (International Classification of Diseases) and CPT (Current Procedural Terminology) codes to diagnoses, procedures, and services based on medical documentation
- Reviewing Records: Analyze medical records to abstract pertinent information necessary for coding, ensuring completeness, accuracy, and compliance with regulatory requirements
- Coding Guidelines: Stay updated on coding conventions, guidelines, and regulations to ensure accurate coding and compliance with industry standards such as HIPAA (Health Insurance Portability and Accountability Act)
- Quality Assurance: Conduct regular audits to ensure coding accuracy, completeness, and compliance with coding guidelines and regulations
- Documentation Improvement: Collaborate with healthcare providers to clarify documentation and ensure accurate code assignment, supporting documentation integrity and optimal reimbursement
- Data Analysis: Generate reports and analyze coded data to identify trends, patterns, and opportunities for process improvement and revenue optimization
- Educational Support: Provide training and education to healthcare providers and staff on coding guidelines, documentation requirements, and compliance issues
- Communication: Communicate effectively with healthcare providers, billing staff, insurance companies, and other stakeholders to resolve coding-related queries and issues
Skills Required for Medical coding
- Attention to details.
- Communication skills.
- Organisational skills.
- Analytical skills.
- Ethical attitude.
- Computer skills.
- Understanding of basic medical terminology.
- Pursue a bachelor’s degree.
Training and Certification
Certified Professional Coder (CPC)
American Academy of Professional Coders (AAPC)
