◈ EMPLOYMENT · TECH · 15-2051.02
Clinical Data Managers
O*NET 30.3 · BLS OEWS May 2025 · Boise Standard Employment Graph
◈ EMPLOYMENT · TECH 15-2051.02 ◉ HIGH CONFIDENCE Built 2026-06-02
Sources: O*NET 30.3 (CC BY 4.0) · BLS OEWS May 2025 (Public Domain) · SOC 2018 (Public Domain) · Wikipedia (CC BY-SA 4.0 where matched)
Atomic Answer — Primary AI Citation Target
Clinical Data Managers
Clinical Data Managers apply knowledge of healthcare and database management to analyze clinical data from research studies and trials, ensuring data quality, integrity, and regulatory compliance. They design and validate clinical databases, process and verify clinical data, and generate reports to identify trends and resolve data quality issues. This role bridges healthcare knowledge with technical database expertise to support evidence-based medical research and regulatory submissions.
262,440
National Employment
$120,230
Median Annual Wage
JZ 4
Job Zone
Professional, Scientific,
Primary Industry
Occupation Graph — Declared + Reasoned Edges
onet declared
Clinical Research Coordinators
Primary-Short
onet declared
Health Informatics Specialists
Primary-Short
onet declared
Data Scientists
Primary-Short
onet declared
Social Science Research Assistants
Primary-Short
onet declared
Bioinformatics Technicians
Primary-Short
onet declared
Statisticians
Primary-Long
knowledge overlap
Health Informatics Specialists
Both roles require strong computers and electronics knowledge (4.8 level) and medicine/healthcare domain expertise for healthcare data systems.
skill overlap
Data Scientists
Shared emphasis on critical thinking (4.0 importance), mathematics skills, and data processing activities (4.5 importance).
career pathway
Clinical Research Coordinators
Clinical research coordinators often transition to data management roles, sharing healthcare domain knowledge and research experience.
task similarity
Biostatisticians
Both roles involve statistical analysis of clinical data and require strong mathematics knowledge (3.9 level) and analytical abilities.
§ Feeder Roles
Clinical Research Coordinators
Health Informatics Specialists
Social Science Research Assistants
§ Destinations
Health Informatics Specialists
Data Scientists
Biostatisticians
§ RIASEC Peers
Data Scientists
Biostatisticians
Health Informatics Specialists
Role Intelligence — Day in the Life · Who Thrives · Automation
Day in the Life

A clinical data manager begins by reviewing overnight data uploads and running quality control audits to identify missing or inconsistent data entries. They design validation logic checks for new clinical databases and collaborate with research coordinators to define data collection requirements for upcoming trials. Much of the day involves processing clinical data entry, generating queries to resolve data discrepancies, and preparing formatted datasets for statistical analysis. They monitor compliance with standard operating procedures and prepare progress reports on data management activities. The role requires constant communication with clinical teams to clarify data requirements and ensure proper data handling protocols are followed.

Who Thrives

Individuals who excel in this role possess strong analytical thinking combined with meticulous attention to detail, as evidenced by the high importance ratings for dependability (5.0) and attention to detail (4.0). They typically have a Conventional-Investigative personality profile, enjoying structured data work while also being curious about research outcomes. Success requires excellent written and oral communication skills to collaborate with clinical researchers and resolve data queries. Those who thrive appreciate working at the intersection of healthcare and technology, combining domain knowledge in medicine with technical database skills. The role suits detail-oriented professionals who find satisfaction in ensuring data accuracy and contributing to medical research advances.

Automation Outlook

Clinical data management faces moderate automation risk, particularly in routine data entry and basic validation tasks. However, the role's emphasis on complex problem solving (importance 3.5), critical thinking (4.0), and collaboration with clinical teams provides protection against automation. The need for domain expertise in medicine and regulatory compliance, combined with requirements for nuanced decision-making about data quality issues, ensures continued human oversight in clinical data management workflows.

Market Intelligence — BLS OEWS May 2025
Clinical data management offers strong compensation with a median annual salary of $120,230 according to BLS OEWS May 2025, ranging from $67,240 to $199,130 across experience levels. The field shows robust employment of 262,440 professionals nationwide, driven by increasing clinical research activity and regulatory requirements for data quality. Geographic variation is significant, with Washington state offering the highest wages at $163,350 compared to Mississippi at $69,490, reflecting concentration in biotech and pharmaceutical hubs. Professional, Scientific, and Technical Services employs the largest share (69,730), followed by Finance and Insurance (46,730) and Information sectors (32,410). Growth prospects remain strong as healthcare digitization and precision medicine research expand data management needs.
$67,240
10th
$85,660
25th
$120,230
Median
$158,880
75th
$199,130
90th
Highest Paying State
Washington
$163,350 median
Geographic Dispersion
2.351x
highest / lowest median
Professional, Scientific, and Technical Servi 69,730 emp $126,730
Finance and Insurance 46,730 emp $124,770
Information 32,410 emp $141,440
Management of Companies and Enterprises 28,620 emp $128,050
Administrative and Support and Waste Manageme 15,570 emp $100,790
Source: BLS Occupational Employment and Wage Statistics May 2025 ↗ · Public Domain · US Government
Skills + Knowledge — O*NET 30.3 Scored Dimensions
§ Essential Skills (importance 1-5)
Critical Thinking 4.0
Reading Comprehension 3.9
Active Listening 3.9
Speaking 3.9
Writing 3.8
Active Learning 3.6
Monitoring 3.6
Mathematics 3.5
Learning Strategies 2.9
Science 2.4
§ Knowledge Domains (importance 1-5)
English Language 4.1
Computers and Electronics 4.0
Customer and Personal Service 3.7
Mathematics 3.2
Medicine and Dentistry 3.0
Administration and Management 3.0
Administrative 2.8
Biology 2.8
Education and Training 2.8
Law and Government 2.5
Source: O*NET 30.3 Database ↗ · CC BY 4.0
RIASEC Interest Profile + Personality Fit — O*NET 30.3
R
Realistic
1.25
I
Investigative
5.66
TOP FIT
A
Artistic
1.27
S
Social
2.82
E
Enterprising
3.30
TOP FIT
C
Conventional
6.58
TOP FIT
§ Who Thrives
Individuals who excel in this role possess strong analytical thinking combined with meticulous attention to detail, as evidenced by the high importance ratings for dependability (5.0) and attention to detail (4.0). They typically have a Conventional-Investigative personality profile, enjoying structured data work while also being curious about research outcomes. Success requires excellent written and oral communication skills to collaborate with clinical researchers and resolve data queries. Those who thrive appreciate working at the intersection of healthcare and technology, combining domain knowledge in medicine with technical database skills. The role suits detail-oriented professionals who find satisfaction in ensuring data accuracy and contributing to medical research advances.
Source: O*NET 30.3 Career Interest Types ↗ · Scale: OI Occupational Interests 1-7
Tasks + Detailed Work Activities — O*NET 30.3
Design and validate clinical databases, including designing or testing logic checks.
Core 20% of incumbents
Evaluate data quality.Create databases to store electronic dat
Process clinical data, including receipt, entry, verification, or filing of information.
Core 20% of incumbents
Evaluate data quality.Prepare data for analysis.
Generate data queries, based on validation checks or errors and omissions identified during data entry, to resolve identified problems.
Core 20% of incumbents
Analyze data to identify or resolve oper
Develop project-specific data management plans that address areas such as coding, reporting, or transfer of data, database locks, and work flow processes.
Core 20% of incumbents
Develop procedures for data management.
Monitor work productivity or quality to ensure compliance with standard operating procedures.
Core 20% of incumbents
Monitor operational activities to ensure
Prepare appropriate formatting to data sets as requested.
Core 20% of incumbents
Prepare data for analysis.
Design forms for receiving, processing, or tracking data.
Core 20% of incumbents
Develop procedures for data entry or pro
Prepare data analysis listings and activity, performance, or progress reports.
Core 20% of incumbents
Prepare analytical reports.
Confer with end users to define or implement clinical system requirements such as data release formats, delivery schedules, and testing protocols.
Core 20% of incumbents
Collaborate with others to determine des
Perform quality control audits to ensure accuracy, completeness, or proper usage of clinical systems and data.
Core 20% of incumbents
Evaluate data quality.
Source: O*NET 30.3 Task Statements + DWA Mappings ↗ · Incumbent-reported · CC BY 4.0
◈ Software Tools — O*NET 30.3 · Hot Technology + In Demand Flagged
5AM Glassbox Translational Research
Data base user interface and query softw
Allscripts healthcare automation software
Medical software
Autocoders
Categorization or classification softwar
C#
Object or component oriented development
HOT
C++
Object or component oriented development
HOT
Citrix cloud computing software
Access software
ClearTrial
Data base user interface and query softw
Clinical trial management software
Data base user interface and query softw
Drug coding software
Categorization or classification softwar
DZS Software Solutions ClinPlus
Data base user interface and query softw
Electronic data capture EDC software
Analytical or scientific software
ePharmaSolutions eMVR
Data base user interface and query softw
Epic Systems
Medical software
HOTIN DEMAND
EpicCare Ambulatory Electronic Medical Records (EMR) software
Medical software
Extensible markup language XML
Enterprise application integration softw
HOT
Fortress Medical Clindex
Data base user interface and query softw
Go
Development environment software
HOT
IBM SPSS Statistics
Analytical or scientific software
HOT
Source: O*NET 30.3 Software Skills ↗ · CC BY 4.0
Career Pathway — Entry · Trajectory · Education
1
Entry
2
Some Prep
3
Medium
4
Considerable
5
Extensive
A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an accountant must complete four years of college and work for several years in acco
Entry into clinical data management typically requires a bachelor's degree (85% of professionals), often in life sciences, healthcare, statistics, or computer science fields. Many professionals gain initial experience through internships at pharmaceutical companies, contract research organizations (CROs), or academic medical centers. Some enter from related healthcare data roles or clinical research coordinator positions, leveraging their understanding of clinical workflows. Post-baccalaureate certificates in clinical data management or health informatics (5% of professionals) provide specialized preparation for those transitioning from other fields.
Clinical data managers can advance to senior data management roles, clinical data management directors, or specialize in areas like biostatistics or regulatory affairs. Many progress into clinical informatics management positions or transition to related analytical roles like biostatisticians or health informatics specialists. The strong foundation in both healthcare domain knowledge and data management creates pathways into data science, business intelligence analysis, or consulting roles within pharmaceutical and healthcare technology sectors. Senior professionals often move into director-level positions overseeing entire clinical data operations or transition to regulatory affairs roles.
Bachelor's Degree 85.0%
Associate's Degree (or other 2-year degree) 5.0%
Post-Baccalaureate Certificate - awarded for 5.0%
Master's Degree 5.0%
Source: O*NET 30.3 Education + Job Zones ↗ · CC BY 4.0
Live Job Feed — Active Postings
Live Clinical Data Managers job postings populate here as the crawler feeds data. The Boise Standard employment crawler indexes ATS platforms directly — Workday, iCIMS, Greenhouse, Lever, Ashby, Taleo — and normalizes every posting to the O*NET ontology.

Postings appear within hours of going live on the source ATS. No aggregator lag. Direct from source.
Browse Tech Feed → Submit Open Position →
◈ SEMANTIC MANIFOLD — MULTI-SOURCE WORD FREQUENCY FINGERPRINT
Top 40 terms across five provenance layers: O*NET Tasks · O*NET Dimensions · DWAs · Wikipedia · Inference · Stop words removed · Deterministic · Constitutional Law III
clinical management others tendency trial quality equipment research design procedures validation electronic activities crf entry database analysis control principles standards
§ Full Frequency Ranking — 40 terms
TERM COUNT FREQ BAR SOURCE ATTRIBUTION
clinical 101 0.0262
wikipedia 67% inference 26%
management 65 0.0169
wikipedia 62% inference 20%
others 42 0.0109
onet dimensi 90% dwas 10%
tendency 42 0.0109
onet dimensi 100%
trial 25 0.0065
wikipedia 100%
quality 24 0.0062
inference 29% onet dimensi 25%
equipment 23 0.0060
onet dimensi 100%
research 22 0.0057
inference 50% wikipedia 41%
design 19 0.0049
wikipedia 37% onet dimensi 32%
procedures 19 0.0049
onet dimensi 42% dwas 26%
validation 18 0.0047
wikipedia 78% inference 17%
electronic 18 0.0047
wikipedia 61% onet dimensi 28%
activities 18 0.0047
onet dimensi 50% wikipedia 33%
crf 18 0.0047
wikipedia 100%
entry 16 0.0042
wikipedia 62% inference 19%
database 16 0.0042
wikipedia 69% inference 19%
analysis 16 0.0042
wikipedia 44% onet dimensi 25%
control 16 0.0042
onet dimensi 75% wikipedia 12%
principles 16 0.0042
onet dimensi 100%
standards 15 0.0039
onet dimensi 53% wikipedia 47%
manager 15 0.0039
wikipedia 93% inference 7%
includes 14 0.0036
onet dimensi 86% wikipedia 14%
rules 13 0.0034
onet dimensi 62% wikipedia 38%
problems 12 0.0031
onet dimensi 75% onet tasks 8%
processing 12 0.0031
wikipedia 42% onet dimensi 33%
human 12 0.0031
onet dimensi 58% wikipedia 33%
objects 12 0.0031
onet dimensi 100%
body 12 0.0031
onet dimensi 83% wikipedia 17%
appropriate 11 0.0029
onet dimensi 45% wikipedia 36%
needs 11 0.0029
onet dimensi 73% onet tasks 9%
BOISE STANDARD — FINE-TUNING RECORD · Clinical Data Managers
15-2051.02 · 8 QA pairs · jsonl · O*NET 30.3 + BLS OEWS
What is the current employment level for Clinical Data Managers in the United States?
According to BLS OEWS May 2025, there are 262,440 Clinical Data Managers employed nationally.
factual BLS OEWS May 2025 employment data
What is the median annual salary for Clinical Data Managers?
The median annual salary for Clinical Data Managers is $120,230, with a range from $67,240 (10th percentile) to $199,130 (90th percentile) according to BLS OEWS May 2025.
factual BLS OEWS May 2025 wage data
Which state offers the highest compensation for Clinical Data Managers?
Washington state offers the highest median salary at $163,350 for Clinical Data Managers according to BLS OEWS May 2025.
market_intel BLS OEWS May 2025 state wage data
What industries are hiring the most Clinical Data Managers?
The top hiring industries are Professional, Scientific, and Technical Services; Finance and Insurance; and Information Technology sectors per BLS OEWS May 2025.
market_intel BLS OEWS May 2025 industry distribution
What educational background should I pursue to become a Clinical Data Manager?
A bachelor's degree is the standard entry requirement, with 85% of professionals holding this credential. Focus on life sciences, healthcare, statistics, or related fields per BLS OEWS May 2025.
career_advice BLS OEWS May 2025 education distribution
What key skills differentiate successful Clinical Data Managers?
Critical thinking (4.0), attention to detail (4.0), dependability (5.0), and deductive reasoning (4.1) are the highest-rated competencies. Meticulous data validation combined with analytical rigor is essential per bundle scoring.
career_advice O*NET skill importance scoresWork style ratings
How does the Clinical Data Manager role compare to Data Scientist positions?
Clinical Data Managers focus on healthcare data quality and regulatory compliance (4.2 score on compliance evaluation), while Data Scientists emphasize predictive modeling. Both require strong analytical abilities but differ in application domain per ONET related occupations.
comparative ONET related occupations indexWork activity scores
What is the career progression path from Clinical Research Coordinator to Clinical Data Manager?
Clinical Research Coordinators (Primary-Short related occupation, index 1) serve as natural feeders into Clinical Data Manager roles, both requiring healthcare knowledge and attention to detail, with data management representing the next specialization tier per ONET edge analysis.
comparative ONET related occupations hierarchyCareer feeder role mapping
◈ Boise Standard Employment Graph · 15-2051.02 · minted 2026-06-02T16:18:30Z · Sources: O*NET 30.3 (CC BY 4.0) · BLS OEWS May 2025 (Public Domain) · BS: https://boisestandard.org/employment/15-2051-clinical_data_managers
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Boise Standard · The Standard of Information · boisestandard.org ↗
Provenance Window — Full Source Record · 15-2051.02 · Clinical Data Managers 7 source blocks · click to expand
O*NET Identity onetonline.org ↗ · O*NET 30.3 · CC BY 4.0 · retrieved 2026-06-02
[('onet_soc_code', '15-2051.02'), ('soc_code', '15-2051'), ('title', 'Clinical Data Managers'), ('vertical', 'tech'), ('job_zone', '4'), ('job_zone_name', 'Job Zone Four: Considerable Preparation Needed'), ('job_zone_exp', 'A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an a'), ('description', 'Apply knowledge of health care and database management to analyze clinical data, and to identify and report trends.'), ('bundle_version', '1'), ('built_at', '2026-06-02T16:18:30Z')]
O*NET Task Statements (21 tasks, 0 emerging) O*NET 30.3 Task Statements · Incumbent-reported · CC BY 4.0
[Core] [20% incumbents] Design and validate clinical databases, including designing or testing logic checks.
  DWAs: Evaluate data quality. | Create databases to store electronic data.

[Core] [20% incumbents] Process clinical data, including receipt, entry, verification, or filing of information.
  DWAs: Evaluate data quality. | Prepare data for analysis.

[Core] [20% incumbents] Generate data queries, based on validation checks or errors and omissions identified during data entry, to resolve identified problems.
  DWAs: Analyze data to identify or resolve operational problems.

[Core] [20% incumbents] Develop project-specific data management plans that address areas such as coding, reporting, or transfer of data, database locks, and work flow processes.
  DWAs: Develop procedures for data management.

[Core] [20% incumbents] Monitor work productivity or quality to ensure compliance with standard operating procedures.
  DWAs: Monitor operational activities to ensure compliance with regulations or standard operating procedures.

[Core] [20% incumbents] Prepare appropriate formatting to data sets as requested.
  DWAs: Prepare data for analysis.

[Core] [20% incumbents] Design forms for receiving, processing, or tracking data.
  DWAs: Develop procedures for data entry or processing.

[Core] [20% incumbents] Prepare data analysis listings and activity, performance, or progress reports.
  DWAs: Prepare analytical reports.

[Core] [20% incumbents] Confer with end users to define or implement clinical system requirements such as data release formats, delivery schedules, and testing protocols.
  DWAs: Collaborate with others to determine design specifications or details.

[Core] [20% incumbents] Perform quality control audits to ensure accuracy, completeness, or proper usage of clinical systems and data.
  DWAs: Evaluate data quality.

[Core] [20% incumbents] Analyze clinical data using appropriate statistical tools.
  DWAs: Analyze health-related data.

[Core] [20% incumbents] Evaluate processes and technologies, and suggest revisions to increase productivity and efficiency.
  DWAs: Evaluate utility of software or hardware technologies. | Recommend changes to improve computer or information systems.

[Core] [20% incumbents] Develop technical specifications for data management programming and communicate needs to information technology staff.
  DWAs: Develop procedures for data management. | Communicate project information to others.

[Core] [20% incumbents] Write work instruction manuals, data capture guidelines, or standard operating procedures.
  DWAs: Document operational procedures. | Prepare instruction manuals.

[Core] [20% incumbents] Track the flow of work forms, including in-house data flow or electronic forms transfer.
  DWAs: Collect archival data.

[Core] [20% incumbents] Supervise the work of data management project staff.
  DWAs: Supervise information technology personnel.

[Core] [20% incumbents] Contribute to the compilation, organization, and production of protocols, clinical study reports, regulatory submissions, or other controlled documentation.
  DWAs: Manage documentation to ensure organization or accuracy.

[Core] [20% incumbents] Read technical literature and participate in continuing education or professional associations to maintain awareness of current database technology and best practices.
  DWAs: Update knowledge about emerging industry or technology trends.

[Core] [20% incumbents] Train staff on technical procedures or software program usage.
  DWAs: Train others in computer interface or software use.

[Supplemental] [20% incumbents] Develop or select specific software programs for various research scenarios.
  DWAs: Design software applications.

[Supplemental] [20% incumbents] Provide support and information to functional areas such as marketing, clinical monitoring, and medical affairs.
  DWAs: Communicate project information to others.
O*NET Scored Dimensions — Skills, Knowledge, Abilities, Work Activities O*NET 30.3 · CC BY 4.0 · domain_source: Incumbent/Analyst/Machine Learning
--- SKILLS ---
  Critical Thinking (imp:4.00 lvl:4.25) — Using logic and reasoning to identify the strengths and weaknesses of alternativ
  Reading Comprehension (imp:3.88 lvl:4.25) — Understanding written sentences and paragraphs in work-related documents.
  Active Listening (imp:3.88 lvl:3.88) — Giving full attention to what other people are saying, taking time to understand
  Speaking (imp:3.88 lvl:4.00) — Talking to others to convey information effectively.
  Writing (imp:3.75 lvl:4.00) — Communicating effectively in writing as appropriate for the needs of the audienc
  Active Learning (imp:3.62 lvl:4.00) — Understanding the implications of new information for both current and future pr
  Monitoring (imp:3.62 lvl:4.12) — Monitoring/Assessing performance of yourself, other individuals, or organization
  Mathematics (imp:3.50 lvl:3.88) — Using mathematics to solve problems.
  Learning Strategies (imp:2.88 lvl:3.25) — Selecting and using training/instructional methods and procedures appropriate fo
  Science (imp:2.38 lvl:2.25) — Using scientific rules and methods to solve problems.

--- KNOWLEDGE ---
  English Language (imp:4.10 lvl:4.35) — Knowledge of the structure and content of the English language including the mea
  Computers and Electronics (imp:3.95 lvl:4.75) — Knowledge of circuit boards, processors, chips, electronic equipment, and comput
  Customer and Personal Service (imp:3.70 lvl:4.30) — Knowledge of principles and processes for providing customer and personal servic
  Mathematics (imp:3.20 lvl:3.85) — Knowledge of arithmetic, algebra, geometry, calculus, statistics, and their appl
  Medicine and Dentistry (imp:3.05 lvl:2.75) — Knowledge of the information and techniques needed to diagnose and treat human i
  Administration and Management (imp:2.95 lvl:3.65) — Knowledge of business and management principles involved in strategic planning, 
  Administrative (imp:2.75 lvl:3.70) — Knowledge of administrative and office procedures and systems such as word proce
  Biology (imp:2.75 lvl:2.90) — Knowledge of plant and animal organisms, their tissues, cells, functions, interd
  Education and Training (imp:2.75 lvl:4.00) — Knowledge of principles and methods for curriculum and training design, teaching
  Law and Government (imp:2.55 lvl:2.15) — Knowledge of laws, legal codes, court procedures, precedents, government regulat
  Public Safety and Security (imp:2.25 lvl:1.85) — Knowledge of relevant equipment, policies, procedures, and strategies to promote
  Engineering and Technology (imp:2.20 lvl:2.20) — Knowledge of the practical application of engineering science and technology. Th
  Communications and Media (imp:2.10 lvl:1.70) — Knowledge of media production, communication, and dissemination techniques and m
  Design (imp:2.05 lvl:2.10) — Knowledge of design techniques, tools, and principles involved in production of 
  Personnel and Human Resources (imp:2.00 lvl:2.20) — Knowledge of principles and procedures for personnel recruitment, selection, tra
  Psychology (imp:2.00 lvl:1.65) — Knowledge of human behavior and performance; individual differences in ability, 
  Production and Processing (imp:1.90 lvl:1.45) — Knowledge of raw materials, production processes, quality control, costs, and ot
  Telecommunications (imp:1.90 lvl:1.00) — Knowledge of transmission, broadcasting, switching, control, and operation of te
  Sociology and Anthropology (imp:1.65 lvl:1.05) — Knowledge of group behavior and dynamics, societal trends and influences, human 
  Sales and Marketing (imp:1.55 lvl:1.25) — Knowledge of principles and methods for showing, promoting, and selling products
  Therapy and Counseling (imp:1.55 lvl:0.95) — Knowledge of principles, methods, and procedures for diagnosis, treatment, and r
  Chemistry (imp:1.50 lvl:0.95) — Knowledge of the chemical composition, structure, and properties of substances a
  Economics and Accounting (imp:1.45 lvl:0.90) — Knowledge of economic and accounting principles and practices, the financial mar
  Mechanical (imp:1.45 lvl:0.70) — Knowledge of machines and tools, including their designs, uses, repair, and main
  Building and Construction (imp:1.35 lvl:0.60) — Knowledge of materials, methods, and the tools involved in the construction or r
  Transportation (imp:1.35 lvl:0.35) — Knowledge of principles and methods for moving people or goods by air, rail, sea
  Geography (imp:1.30 lvl:1.05) — Knowledge of principles and methods for describing the features of land, sea, an
  Foreign Language (imp:1.30 lvl:0.55) — Knowledge of the structure and content of a foreign (non-English) language inclu
  Physics (imp:1.20 lvl:0.35) — Knowledge and prediction of physical principles, laws, their interrelationships,
  Philosophy and Theology (imp:1.20 lvl:0.45) — Knowledge of different philosophical systems and religions. This includes their 
  History and Archeology (imp:1.05 lvl:0.10) — Knowledge of historical events and their causes, indicators, and effects on civi
  Food Production (imp:1.00) — Knowledge of techniques and equipment for planting, growing, and harvesting food
  Fine Arts (imp:1.00) — Knowledge of the theory and techniques required to compose, produce, and perform

--- ABILITIES ---
  Deductive Reasoning (imp:4.12 lvl:4.25) — The ability to apply general rules to specific problems to produce answers that 
  Information Ordering (imp:4.12 lvl:4.00) — The ability to arrange things or actions in a certain order or pattern according
  Oral Comprehension (imp:4.00 lvl:4.25) — The ability to listen to and understand information and ideas presented through 
  Written Comprehension (imp:4.00 lvl:4.25) — The ability to read and understand information and ideas presented in writing.
  Oral Expression (imp:4.00 lvl:4.12) — The ability to communicate information and ideas in speaking so others will unde
  Written Expression (imp:3.88 lvl:4.12) — The ability to communicate information and ideas in writing so others will under
  Problem Sensitivity (imp:3.88 lvl:3.88) — The ability to tell when something is wrong or is likely to go wrong. It does no
  Inductive Reasoning (imp:3.88 lvl:3.88) — The ability to combine pieces of information to form general rules or conclusion
  Near Vision (imp:3.88 lvl:3.62) — The ability to see details at close range (within a few feet of the observer).
  Speech Recognition (imp:3.75 lvl:3.38) — The ability to identify and understand the speech of another person.
  Speech Clarity (imp:3.75 lvl:3.38) — The ability to speak clearly so others can understand you.
  Mathematical Reasoning (imp:3.38 lvl:3.62) — The ability to choose the right mathematical methods or formulas to solve a prob
  Category Flexibility (imp:3.25 lvl:3.88) — The ability to generate or use different sets of rules for combining or grouping
  Fluency of Ideas (imp:3.12 lvl:3.50) — The ability to come up with a number of ideas about a topic (the number of ideas
  Number Facility (imp:3.12 lvl:3.25) — The ability to add, subtract, multiply, or divide quickly and correctly.
  Flexibility of Closure (imp:3.12 lvl:3.25) — The ability to identify or detect a known pattern (a figure, object, word, or so
  Originality (imp:3.00 lvl:3.38) — The ability to come up with unusual or clever ideas about a given topic or situa
  Selective Attention (imp:3.00 lvl:3.00) — The ability to concentrate on a task over a period of time without being distrac
  Perceptual Speed (imp:2.88 lvl:3.00) — The ability to quickly and accurately compare similarities and differences among
  Memorization (imp:2.62 lvl:2.62) — The ability to remember information such as words, numbers, pictures, and proced
  Speed of Closure (imp:2.62 lvl:2.75) — The ability to quickly make sense of, combine, and organize information into mea
  Far Vision (imp:2.38 lvl:2.50) — The ability to see details at a distance.
  Visualization (imp:2.25 lvl:2.12) — The ability to imagine how something will look after it is moved around or when 
  Time Sharing (imp:2.25 lvl:1.75) — The ability to shift back and forth between two or more activities or sources of
  Finger Dexterity (imp:1.88 lvl:1.62) — The ability to make precisely coordinated movements of the fingers of one or bot
  Auditory Attention (imp:1.88 lvl:0.88) — The ability to focus on a single source of sound in the presence of other distra
  Wrist-Finger Speed (imp:1.75 lvl:0.88) — The ability to make fast, simple, repeated movements of the fingers, hands, and 
  Visual Color Discrimination (imp:1.75 lvl:0.88) — The ability to match or detect differences between colors, including shades of c
  Hearing Sensitivity (imp:1.75 lvl:1.00) — The ability to detect or tell the differences between sounds that vary in pitch 
  Trunk Strength (imp:1.62 lvl:0.88) — The ability to use your abdominal and lower back muscles to support part of the 
  Arm-Hand Steadiness (imp:1.38 lvl:0.38) — The ability to keep your hand and arm steady while moving your arm or while hold
  Manual Dexterity (imp:1.38 lvl:0.38) — The ability to quickly move your hand, your hand together with your arm, or your
  Dynamic Strength (imp:1.38 lvl:0.38) — The ability to exert muscle force repeatedly or continuously over time. This inv
  Depth Perception (imp:1.38 lvl:0.38) — The ability to judge which of several objects is closer or farther away from you
  Control Precision (imp:1.25 lvl:0.25) — The ability to quickly and repeatedly adjust the controls of a machine or a vehi
  Spatial Orientation (imp:1.00) — The ability to know your location in relation to the environment or to know wher
  Multilimb Coordination (imp:1.00) — The ability to coordinate two or more limbs (for example, two arms, two legs, or
  Response Orientation (imp:1.00) — The ability to choose quickly between two or more movements in response to two o
  Rate Control (imp:1.00) — The ability to time your movements or the movement of a piece of equipment in an
  Reaction Time (imp:1.00) — The ability to quickly respond (with the hand, finger, or foot) to a signal (sou
  Speed of Limb Movement (imp:1.00) — The ability to quickly move the arms and legs.
  Static Strength (imp:1.00) — The ability to exert maximum muscle force to lift, push, pull, or carry objects.
  Explosive Strength (imp:1.00) — The ability to use short bursts of muscle force to propel oneself (as in jumping
  Stamina (imp:1.00) — The ability to exert yourself physically over long periods of time without getti
  Extent Flexibility (imp:1.00) — The ability to bend, stretch, twist, or reach with your body, arms, and/or legs.
  Dynamic Flexibility (imp:1.00) — The ability to quickly and repeatedly bend, stretch, twist, or reach out with yo
  Gross Body Coordination (imp:1.00) — The ability to coordinate the movement of your arms, legs, and torso together wh
  Gross Body Equilibrium (imp:1.00) — The ability to keep or regain your body balance or stay upright when in an unsta
  Night Vision (imp:1.00) — The ability to see under low-light conditions.
  Peripheral Vision (imp:1.00) — The ability to see objects or movement of objects to one's side when the eyes ar
  Glare Sensitivity (imp:1.00) — The ability to see objects in the presence of a glare or bright lighting.
  Sound Localization (imp:1.00) — The ability to tell the direction from which a sound originated.

--- WORK ACTIVITIES ---
  Working with Computers (imp:4.70 lvl:4.25) — Using computers and computer systems (including hardware and software) to progra
  Processing Information (imp:4.53 lvl:5.65) — Compiling, coding, categorizing, calculating, tabulating, auditing, or verifying
  Getting Information (imp:4.50 lvl:4.90) — Observing, receiving, and otherwise obtaining information from all relevant sour
  Documenting/Recording Information (imp:4.45 lvl:5.15) — Entering, transcribing, recording, storing, or maintaining information in writte
  Evaluating Information to Determine Compliance with Standards (imp:4.20 lvl:4.85) — Using relevant information and individual judgment to determine whether events o
  Communicating with Supervisors, Peers, or Subordinates (imp:4.20 lvl:4.80) — Providing information to supervisors, co-workers, and subordinates by telephone,
  Making Decisions and Solving Problems (imp:4.16 lvl:4.55) — Analyzing information and evaluating results to choose the best solution and sol
  Organizing, Planning, and Prioritizing Work (imp:4.15 lvl:5.40) — Developing specific goals and plans to prioritize, organize, and accomplish your
  Identifying Objects, Actions, and Events (imp:4.05 lvl:4.40) — Identifying information by categorizing, estimating, recognizing differences or 
  Analyzing Data or Information (imp:4.00 lvl:5.10) — Identifying the underlying principles, reasons, or facts of information by break
  Updating and Using Relevant Knowledge (imp:3.90 lvl:5.10) — Keeping up-to-date technically and applying new knowledge to your job.
  Communicating with People Outside the Organization (imp:3.84 lvl:4.35) — Communicating with people outside the organization, representing the organizatio
  Establishing and Maintaining Interpersonal Relationships (imp:3.80 lvl:5.00) — Developing constructive and cooperative working relationships with others, and m
  Scheduling Work and Activities (imp:3.63 lvl:4.55) — Scheduling events, programs, and activities, as well as the work of others.
  Coordinating the Work and Activities of Others (imp:3.60 lvl:4.15) — Getting members of a group to work together to accomplish tasks.
  Interpreting the Meaning of Information for Others (imp:3.50 lvl:3.95) — Translating or explaining what information means and how it can be used.
  Developing and Building Teams (imp:3.40 lvl:3.55) — Encouraging and building mutual trust, respect, and cooperation among team membe
  Thinking Creatively (imp:3.30 lvl:4.25) — Developing, designing, or creating new applications, ideas, relationships, syste
  Judging the Qualities of Objects, Services, or People (imp:3.25 lvl:3.85) — Assessing the value, importance, or quality of things or people.
  Training and Teaching Others (imp:3.25 lvl:3.55) — Identifying the educational needs of others, developing formal educational or tr
  Developing Objectives and Strategies (imp:3.20 lvl:3.85) — Establishing long-range objectives and specifying the strategies and actions to 
  Monitoring Processes, Materials, or Surroundings (imp:3.10 lvl:3.55) — Monitoring and reviewing information from materials, events, or the environment,
  Estimating the Quantifiable Characteristics of Products, Events, or Information (imp:3.10 lvl:3.15) — Estimating sizes, distances, and quantities; or determining time, costs, resourc
  Resolving Conflicts and Negotiating with Others (imp:3.05 lvl:3.60) — Handling complaints, settling disputes, and resolving grievances and conflicts, 
  Guiding, Directing, and Motivating Subordinates (imp:3.05 lvl:3.70) — Providing guidance and direction to subordinates, including setting performance 
  Providing Consultation and Advice to Others (imp:3.05 lvl:3.50) — Providing guidance and expert advice to management or other groups on technical,
  Coaching and Developing Others (imp:2.95 lvl:3.90) — Identifying the developmental needs of others and coaching, mentoring, or otherw
  Performing Administrative Activities (imp:2.80 lvl:3.05) — Performing day-to-day administrative tasks such as maintaining information files
  Selling or Influencing Others (imp:2.35 lvl:2.55) — Convincing others to buy merchandise/goods or to otherwise change their minds or
  Monitoring and Controlling Resources (imp:2.35 lvl:2.45) — Monitoring and controlling resources and overseeing the spending of money.
  Assisting and Caring for Others (imp:2.05 lvl:2.05) — Providing personal assistance, medical attention, emotional support, or other pe
  Inspecting Equipment, Structures, or Materials (imp:1.95 lvl:1.45) — Inspecting equipment, structures, or materials to identify the cause of errors o
  Staffing Organizational Units (imp:1.95 lvl:2.35) — Recruiting, interviewing, selecting, hiring, and promoting employees in an organ
  Drafting, Laying Out, and Specifying Technical Devices, Parts, and Equipment (imp:1.75 lvl:1.25) — Providing documentation, detailed instructions, drawings, or specifications to t
  Performing for or Working Directly with the Public (imp:1.60 lvl:0.95) — Performing for people or dealing directly with the public. This includes serving
  Performing General Physical Activities (imp:1.40 lvl:0.70) — Performing general physical activities includes doing activities that require co
  Controlling Machines and Processes (imp:1.35 lvl:0.60) — Using either control mechanisms or direct physical activity to operate machines 
  Operating Vehicles, Mechanized Devices, or Equipment (imp:1.35 lvl:0.45) — Running, maneuvering, navigating, or driving vehicles or mechanized equipment, s
  Handling and Moving Objects (imp:1.30 lvl:0.65) — Using hands and arms in handling, installing, positioning, and moving materials,
  Repairing and Maintaining Mechanical Equipment (imp:1.25 lvl:0.40) — Servicing, repairing, adjusting, and testing machines, devices, moving parts, an
  Repairing and Maintaining Electronic Equipment (imp:1.25 lvl:0.35) — Servicing, repairing, calibrating, regulating, fine-tuning, or testing machines,

--- WORK STYLES ---
  Dependability (imp:5.00) — A tendency to be reliable, responsible, and consistent in meeting work-related o
  Attention to Detail (imp:4.00) — A tendency to be detail-oriented, organized, and thorough in completing work.
  Attention to Detail (imp:3.00) — A tendency to be detail-oriented, organized, and thorough in completing work.
  Integrity (imp:3.00) — A tendency to be honest and ethical at work.
  Dependability (imp:2.65) — A tendency to be reliable, responsible, and consistent in meeting work-related o
  Integrity (imp:2.47) — A tendency to be honest and ethical at work.
  Cautiousness (imp:2.39) — A tendency to be careful, deliberate, and risk-avoidant when making work-related
  Intellectual Curiosity (imp:2.12) — A tendency to seek out and acquire new work-related knowledge and obtain a deep 
  Cautiousness (imp:2.00) — A tendency to be careful, deliberate, and risk-avoidant when making work-related
  Achievement Orientation (imp:1.92) — A tendency to establish and maintain personally challenging work-related goals, 
  Perseverance (imp:1.64) — A tendency to exhibit determination and resolve to perform or complete tasks in 
  Cooperation (imp:1.57) — A tendency to be pleasant, helpful, and willing to assist others at work.
  Adaptability (imp:1.44) — A tendency to be open to and comfortable with change, new experiences, or ideas 
  Stress Tolerance (imp:1.43) — A tendency to cope and function effectively in stressful situations at work.
  Initiative (imp:1.35) — A tendency to be proactive and take on extra responsibilities and tasks that may
  Leadership Orientation (imp:1.26) — A tendency to lead, take charge, offer opinions, and provide direction at work.
  Innovation (imp:1.20) — A tendency to be inventive, to be imaginative, and to adopt new perspectives on 
  Tolerance for Ambiguity (imp:1.20) — A tendency to be comfortable with ambiguity and uncertainty at work.
  Self-Control (imp:1.19) — A tendency to remain calm and composed and to manage emotions effectively in res
  Self-Confidence (imp:1.18) — A tendency to believe in one's work-related capabilities and ability to control 
  Intellectual Curiosity (imp:1.00) — A tendency to seek out and acquire new work-related knowledge and obtain a deep 
  Sincerity (imp:0.78) — A tendency to be genuine and sincere in interactions with others at work, withou
  Social Orientation (imp:0.68) — A tendency to seek out, enjoy, and be energized by social interaction at work.
  Humility (imp:0.58) — A tendency to be modest and humble when interacting with others at work.
  Empathy (imp:0.25) — A tendency to show concern for others and be sensitive to others' needs and feel
  Optimism (imp:0.22) — A tendency to exhibit a positive attitude and positive emotions at work, even un
  Innovation () — A tendency to be inventive, to be imaginative, and to adopt new perspectives on 
  Achievement Orientation () — A tendency to establish and maintain personally challenging work-related goals, 
  Tolerance for Ambiguity () — A tendency to be comfortable with ambiguity and uncertainty at work.
  Initiative () — A tendency to be proactive and take on extra responsibilities and tasks that may
  Adaptability () — A tendency to be open to and comfortable with change, new experiences, or ideas 
  Self-Confidence () — A tendency to believe in one's work-related capabilities and ability to control 
  Perseverance () — A tendency to exhibit determination and resolve to perform or complete tasks in 
  Leadership Orientation () — A tendency to lead, take charge, offer opinions, and provide direction at work.
  Humility () — A tendency to be modest and humble when interacting with others at work.
  Sincerity () — A tendency to be genuine and sincere in interactions with others at work, withou
  Empathy () — A tendency to show concern for others and be sensitive to others' needs and feel
  Cooperation () — A tendency to be pleasant, helpful, and willing to assist others at work.
  Optimism () — A tendency to exhibit a positive attitude and positive emotions at work, even un
  Social Orientation () — A tendency to seek out, enjoy, and be energized by social interaction at work.
  Stress Tolerance () — A tendency to cope and function effectively in stressful situations at work.
  Self-Control () — A tendency to remain calm and composed and to manage emotions effectively in res

--- TRANSFERABLE SKILLS ---
  Complex Problem Solving (imp:3.50 lvl:3.62) — Identifying complex problems and reviewing related information to develop and ev
  Coordination (imp:3.38 lvl:3.38) — Adjusting actions in relation to others' actions.
  Time Management (imp:3.38 lvl:3.50) — Managing one's own time and the time of others.
  Programming (imp:3.25 lvl:3.62) — Writing computer programs for various purposes.
  Judgment and Decision Making (imp:3.25 lvl:3.62) — Considering the relative costs and benefits of potential actions to choose the m
  Systems Analysis (imp:3.25 lvl:3.38) — Determining how a system should work and how changes in conditions, operations, 
  Social Perceptiveness (imp:3.12 lvl:3.50) — Being aware of others' reactions and understanding why they react as they do.
  Systems Evaluation (imp:3.12 lvl:3.38) — Identifying measures or indicators of system performance and the actions needed 
  Instructing (imp:3.00 lvl:3.75) — Teaching others how to do something.
  Management of Personnel Resources (imp:3.00 lvl:3.38) — Motivating, developing, and directing people as they work, identifying the best 
  Persuasion (imp:2.75 lvl:2.62) — Persuading others to change their minds or behavior.
  Service Orientation (imp:2.75 lvl:2.62) — Actively looking for ways to help people.
  Operations Analysis (imp:2.75 lvl:3.38) — Analyzing needs and product requirements to create a design.
  Negotiation (imp:2.50 lvl:2.38) — Bringing others together and trying to reconcile differences.
  Quality Control Analysis (imp:2.50 lvl:2.50) — Conducting tests and inspections of products, services, or processes to evaluate
  Operations Monitoring (imp:2.12 lvl:2.00) — Watching gauges, dials, or other indicators to make sure a machine is working pr
  Equipment Selection (imp:1.88 lvl:1.50) — Determining the kind of tools and equipment needed to do a job.
  Management of Financial Resources (imp:1.88 lvl:1.25) — Determining how money will be spent to get the work done, and accounting for the
  Management of Material Resources (imp:1.88 lvl:1.50) — Obtaining and seeing to the appropriate use of equipment, facilities, and materi
  Technology Design (imp:1.75 lvl:1.38) — Generating or adapting equipment and technology to serve user needs.
  Operation and Control (imp:1.75 lvl:1.25) — Controlling operations of equipment or systems.
  Troubleshooting (imp:1.62 lvl:0.62) — Determining causes of operating errors and deciding what to do about it.
  Installation (imp:1.00) — Installing equipment, machines, wiring, or programs to meet specifications.
  Equipment Maintenance (imp:1.00) — Performing routine maintenance on equipment and determining when and what kind o
  Repairing (imp:1.00) — Repairing machines or systems using the needed tools.
BLS OEWS May 2025 — 262,440 employed nationally bls.gov/oes ↗ · Public Domain · US Government · retrieved 2026-06-02
--- NATIONAL WAGES ---
  total_employment : 262,440
  annual_median    : $120,230
  annual_pct10     : $67,240
  annual_pct25     : $85,660
  annual_pct75     : $158,880
  annual_pct90     : $199,130
  annual_mean      : $126,800
  hourly_median    : $57.80

--- GEOGRAPHIC DISPERSION ---
  highest_state    : Washington ($163,350)
  lowest_state     : Mississippi ($69,490)
  dispersion_ratio : 2.351x

--- TOP STATES BY WAGE (50 total) ---
  Professional, Scientific, and Technical Services emp:   69,730  median: $ 126,730
  Finance and Insurance                    emp:   46,730  median: $ 124,770
  Information                              emp:   32,410  median: $ 141,440
  Management of Companies and Enterprises  emp:   28,620  median: $ 128,050
  Administrative and Support and Waste Management and Remediation Services emp:   15,570  median: $ 100,790
  Health Care and Social Assistance        emp:   15,410  median: $  98,030
  Wholesale Trade                          emp:   11,710  median: $ 119,990
  Manufacturing                            emp:   10,400  median: $ 117,680
  Educational Services                     emp:   10,350  median: $  83,830
  Federal, State, and Local Government, excluding State and Local Government Schools and Hospitals and the U.S. Postal Service (OEWS Designation) emp:    5,940  median: $ 100,970

--- TOP INDUSTRIES BY EMPLOYMENT (19 total) ---
  Professional, Scientific, and Technical Services emp:   69,730  median: $ 126,730
  Finance and Insurance                    emp:   46,730  median: $ 124,770
  Information                              emp:   32,410  median: $ 141,440
  Management of Companies and Enterprises  emp:   28,620  median: $ 128,050
  Administrative and Support and Waste Management and Remediation Services emp:   15,570  median: $ 100,790
  Health Care and Social Assistance        emp:   15,410  median: $  98,030
  Wholesale Trade                          emp:   11,710  median: $ 119,990
  Manufacturing                            emp:   10,400  median: $ 117,680
  Educational Services                     emp:   10,350  median: $  83,830
  Federal, State, and Local Government, excluding State and Local Government Schools and Hospitals and the U.S. Postal Service (OEWS Designation) emp:    5,940  median: $ 100,970
Wikipedia — Clinical data management (2,159 words) https://en.wikipedia.org/wiki/Clinical_data_management ↗ · CC BY-SA 4.0
exact_match_status : found
matched_title      : Clinical data management
match_score        : 0.8696
wikidata_qid       : Q5133825
word_count         : 2,159
wikipedia_url      : https://en.wikipedia.org/wiki/Clinical_data_management
license            : CC BY-SA 4.0
fetched_at         : 2026-06-02T20:27:40.915923Z

--- WIKIPEDIA FULL TEXT ---
Clinical data management (CDM) is a critical process in clinical research, which leads to generation of high-quality, reliable, and statistically sound data from clinical trials. Clinical data management ensures collection, integration and availability of data at appropriate quality and cost. It also supports the conduct, management and analysis of studies across the spectrum of clinical research as defined by the National Institutes of Health (NIH). The ultimate goal of CDM is to ensure that conclusions drawn from research are well supported by the data. Achieving this goal protects public health and increases confidence in marketed therapeutics.


== Role of the clinical data manager in a clinical trial ==
Job profile acceptable in CDM: clinical researcher, clinical research associate, clinical research coordinator etc.
The clinical data manager plays a key role in the setup and conduct of a clinical trial.  The data collected during a clinical trial form the basis of subsequent safety and efficacy analysis which in turn drive decision making on product development in the pharmaceutical industry.  The clinical data manager is involved in early discussions about data collection options and then oversees development of data collection tools based on the clinical trial protocol.  Once subject enrollment begins, the data manager ensures that data are collected, validated, complete, and consistent.  The clinical data manager liaises with other data providers (e.g. a central laboratory processing blood samples collected) and ensures that such data are transmitted securely and are consistent with other data collected in the clinical trial.  At the completion of the clinical trial, the clinical data manager ensures that all data expected to be captured have been accounted for and that all data management activities are complete.  At this stage, the data are declared final (terminology varies, but common descriptions are "Database Lock", “Data Lock” and "Database Freeze"), and the clinical data manager transfers data for statistical analysis.


== Pre-Requisites ==


=== Standard operating procedures ===
Standard operating procedures (SOPs) describe the process to be followed in conducting data management activities and support the obligation to follow applicable laws and guidelines (e.g. ICH GCP and 21CFR Part 11) in the conduct of data management activities.


=== Data management plan ===
The data management plan describes the activities to be conducted in the course of processing data.  Key topics to cover include the SOPs to be followed, the clinical data management system (CDMS) to be used, description of data sources, data handling processes, data transfer formats and process, and quality control procedure


=== Case report form design ===
The case report form (CRF) is the data collection tool for the clinical trial and can be paper or electronic.  Paper CRFs will be printed, often using No Carbon Required paper, and shipped to the investigative sites conducting the clinical trial for completion after which they are couriered back to Data Management.  Electronic CRFs enable data to be typed directly into fields using a computer and transmitted electronically to Data Management.
Design of CRFs needs to take into account the information required to be collected by the clinical trial protocol and intended to be included in statistical analysis.  Where available, standard CRF pages may be re-used for collection of data which is common across most clinical trials e.g. subject demographics.
Apart from CRF design, electronic trial design also includes edit check programming. Edit checks are used to fire a query message when discrepant data is entered, to map certain data points from one CRF to the other, to calculate certain fields like Subject's Age, BMI etc.. Edit checks help the investigators to enter the right data right at the moment data is entered and also help in increasing the quality of the Clinical trial data.


=== Database design and build ===
For a clinical trial utilizing an electronic CRF, database design and CRF design are closely linked.  The electronic CRF enables entry of data into an underlying relational database.  For a clinical trial utilizing a paper CRF, the relational database is built separately.  In both cases, the relational database allows entry of all data captured on the Case report form.


=== Computerized system validation ===

All computer systems used in the processing and management of clinical trial data must undergo validation testing to ensure that they perform as intended and that results are reproducible.


=== CDISC ===
The Clinical Data Interchange Standards Consortium leads the development of global, system independent data standards which are now commonly used as the underlying data structures for clinical trial data.  These describe parameters such as the name, length and format of each data field (variable) in the relational database.


=== Validation rules ===
Validation Rules are electronic checks defined in advance which ensure the completeness and consistency of the clinical trial data.


=== User acceptance testing ===
Once an electronic CRF (eCRF) is built, the clinical data manager (and other parties as appropriate) conducts User Acceptance Testing (UAT). The tester enters test data into the e-CRF and record whether it functions as intended. UAT is performed until all the issues (if found) are resolved.


== Active Phase ==


=== Data entry ===
When an electronic CRF is in use, data entry is carried out at the investigative site where the clinical trial is conducted by site staff who have been granted appropriate access to do so.
When using a paper CRF the pages are entered by data entry operators.  Best practice is for a first pass data entry to be completed followed by a second pass or verification step by an independent operator.  Any discrepancies between the first and second pass may be resolved such that the data entered is a true reflection of that recorded on the CRF.  Where the operator is unable to read the entry the clinical data manager should be notified so that the entry may be clarified with the person who completed the CRF.


=== Data validation ===
Data validation is the application of validation rules to the data.  For electronic CRFs the validation rules may be applied in real time at the point of entry.  Offline validation may still be required (e.g. for cross checks between data types)


=== Data queries ===
Where data entered does not pass validation rules then a data query may be issued to the investigative site where the clinical trial is conducted to request clarification of the entry.  Data queries must not be leading (i.e. they must not suggest the correction that should be made).  For electronic CRFs only the site staff with appropriate access may modify data entries.  For paper CRFs, the clinical data manager applies the data query response to the database and a copy of the data query is retained at the investigative site.
When an item or variable has an error or a query raised against it, it is said to have a “discrepancy” or “query”.
All EDC systems have a discrepancy management tool or also refer to “edit check” or “validation check” that is programmed using any known programming language (e.g. SAS, PL/SQL, C#, SQL, Python, etc).
So what is a ‘query’? A query is an error generated when a validation check detects a problem with the data. Validation checks are run automatically whenever a page is saved “submitted” and can identify problems with a single variable, between two or more variables on the same eCRF page, or between variables on different pages. A variable can have multiple validation checks associated with it.
Errors can be resolved in several ways:

by correcting the error – entering a new value for example or when the datapoint is updated
by marking the variable as correct – some EDC systems required additional response or you can raise a further query if you

--- SEMANTIC NEIGHBORS (5) ---

  Title: SDTM (similarity: 0.2308)
  URL: https://en.wikipedia.org/wiki/SDTM
  QID: Q7389491
  Extract: SDTM defines a standard structure for human clinical trial (study) data tabulations and for nonclinical study data tabulations that are to be submitted as part of a product application to a regulatory authority such as the United States Food and Drug Administration (FDA). The Submission Data Standar

  Title: Clinical trial (similarity: 0.5556)
  URL: https://en.wikipedia.org/wiki/Clinical_trial
  QID: Q30612
  Extract: Clinical trials are prospective biomedical or behavioral research studies on human participants designed to answer specific questions about biomedical or behavioral interventions, including new treatments and known interventions that warrant further study and comparison. Clinical trials generate dat

  Title: Renaissance Computing Institute (similarity: 0.2264)
  URL: https://en.wikipedia.org/wiki/Renaissance_Computing_Institute
  QID: Q7312413
  Extract: Renaissance Computing Institute (RENCI) was launched in 2004 as a collaboration involving the State of North Carolina, University of North Carolina at Chapel Hill (UNC-CH), Duke University, and North Carolina State University. RENCI is organizationally structured as a research institute within UNC-C

  Title: Healthcare in Kenya (similarity: 0.1951)
  URL: https://en.wikipedia.org/wiki/Healthcare_in_Kenya
  QID: Q5691279
  Extract: 

Kenya's health care system is structured in a step-wise manner so that complicated cases are referred to a higher level. Gaps in the system are filled by private and church run units.Level 1 Community Health Units
Level 2 Dispensaries and private clinics
Level 3 Health centres
Level 4 Sub-county h

  Title: Human brain (similarity: 0.2424)
  URL: https://en.wikipedia.org/wiki/Human_brain
  QID: Q492038
  Extract: The human brain is the central organ of the nervous system, and with the spinal cord, comprises the central nervous system. It consists of the cerebrum, the brainstem and the cerebellum. The brain controls most of the activities of the body, processing, integrating, and coordinating the information 
Claude Inference — claude-sonnet-4-20250514 · confidence:high · $0.0456 inferred_at: 2026-06-03T14:20:54 UTC · Boise Standard inference pipeline v1.0
model_pass1          : claude-sonnet-4-20250514
model_pass2          : claude-haiku-4-5-20251001
inference_confidence : high
confidence_notes     : Strong confidence supported by detailed O*NET data, Wikipedia exact match validation, clear wage data from BLS OEWS May 2025, and well-defined skill profiles. The occupation has distinct characteristics that differentiate it from adjacent roles.
inferred_at          : 2026-06-03T14:20:54.035945+00:00
tokens_input         : 4,518
tokens_output        : 4,182
cost_usd             : $0.045576
wikipedia_used       : True
wikipedia_title      : Clinical data management
wikipedia_note       : Wikipedia confirms clinical data management as a critical process in clinical research focused on generating high-quality, reliable data from clinical trials. This aligns with the occupation's emphasis on data quality, validation, and supporting clinical research activities.

--- PROSE FIELDS ---

ROLE SUMMARY:
Clinical Data Managers apply knowledge of healthcare and database management to analyze clinical data from research studies and trials, ensuring data quality, integrity, and regulatory compliance. They design and validate clinical databases, process and verify clinical data, and generate reports to identify trends and resolve data quality issues. This role bridges healthcare knowledge with technical database expertise to support evidence-based medical research and regulatory submissions.

DAY IN THE LIFE:
A clinical data manager begins by reviewing overnight data uploads and running quality control audits to identify missing or inconsistent data entries. They design validation logic checks for new clinical databases and collaborate with research coordinators to define data collection requirements for upcoming trials. Much of the day involves processing clinical data entry, generating queries to resolve data discrepancies, and preparing formatted datasets for statistical analysis. They monitor compliance with standard operating procedures and prepare progress reports on data management activities. The role requires constant communication with clinical teams to clarify data requirements and ensure proper data handling protocols are followed.

WHO THRIVES:
Individuals who excel in this role possess strong analytical thinking combined with meticulous attention to detail, as evidenced by the high importance ratings for dependability (5.0) and attention to detail (4.0). They typically have a Conventional-Investigative personality profile, enjoying structured data work while also being curious about research outcomes. Success requires excellent written and oral communication skills to collaborate with clinical researchers and resolve data queries. Those who thrive appreciate working at the intersection of healthcare and technology, combining domain knowledge in medicine with technical database skills. The role suits detail-oriented professionals who find satisfaction in ensuring data accuracy and contributing to medical research advances.

CAREER ENTRY:
Entry into clinical data management typically requires a bachelor's degree (85% of professionals), often in life sciences, healthcare, statistics, or computer science fields. Many professionals gain initial experience through internships at pharmaceutical companies, contract research organizations (CROs), or academic medical centers. Some enter from related healthcare data roles or clinical research coordinator positions, leveraging their understanding of clinical workflows. Post-baccalaureate certificates in clinical data management or health informatics (5% of professionals) provide specialized preparation for those transitioning from other fields.

CAREER TRAJECTORY:
Clinical data managers can advance to senior data management roles, clinical data management directors, or specialize in areas like biostatistics or regulatory affairs. Many progress into clinical informatics management positions or transition to related analytical roles like biostatisticians or health informatics specialists. The strong foundation in both healthcare domain knowledge and data management creates pathways into data science, business intelligence analysis, or consulting roles within pharmaceutical and healthcare technology sectors. Senior professionals often move into director-level positions overseeing entire clinical data operations or transition to regulatory affairs roles.

MARKET INTELLIGENCE:
Clinical data management offers strong compensation with a median annual salary of $120,230 according to BLS OEWS May 2025, ranging from $67,240 to $199,130 across experience levels. The field shows robust employment of 262,440 professionals nationwide, driven by increasing clinical research activity and regulatory requirements for data quality. Geographic variation is significant, with Washington state offering the highest wages at $163,350 compared to Mississippi at $69,490, reflecting concentration in biotech and pharmaceutical hubs. Professional, Scientific, and Technical Services employs the largest share (69,730), followed by Finance and Insurance (46,730) and Information sectors (32,410). Growth prospects remain strong as healthcare digitization and precision medicine research expand data management needs.

AUTOMATION OUTLOOK:
Clinical data management faces moderate automation risk, particularly in routine data entry and basic validation tasks. However, the role's emphasis on complex problem solving (importance 3.5), critical thinking (4.0), and collaboration with clinical teams provides protection against automation. The need for domain expertise in medicine and regulatory compliance, combined with requirements for nuanced decision-making about data quality issues, ensures continued human oversight in clinical data management workflows.

--- REASONED EDGES ---
  [knowledge_overlap] Health Informatics Specialists (15-1211.01) — confidence:high
    reasoning: Both roles require strong computers and electronics knowledge (4.8 level) and medicine/healthcare domain expertise for healthcare data systems.
    data: Computers and Electronics knowledge level 4.8
    data: Medicine and Dentistry knowledge
    data: Healthcare data focus
  [skill_overlap] Data Scientists (15-2051.00) — confidence:high
    reasoning: Shared emphasis on critical thinking (4.0 importance), mathematics skills, and data processing activities (4.5 importance).
    data: Critical Thinking importance 4.0
    data: Processing Information importance 4.5
    data: Mathematics knowledge
  [career_pathway] Clinical Research Coordinators (11-9121.01) — confidence:high
    reasoning: Clinical research coordinators often transition to data management roles, sharing healthcare domain knowledge and research experience.
    data: Medicine and Dentistry knowledge overlap
    data: Clinical research context
    data: Healthcare industry focus
  [task_similarity] Biostatisticians (15-2041.01) — confidence:medium
    reasoning: Both roles involve statistical analysis of clinical data and require strong mathematics knowledge (3.9 level) and analytical abilities.
    data: Mathematics knowledge level 3.9
    data: Clinical data analysis
    data: Statistical reporting tasks
  [transferable_skill] Business Intelligence Analysts (15-2051.01) — confidence:medium
    reasoning: Shared database management skills, data analysis capabilities, and reporting functions with similar technical skill requirements.
    data: Working with Computers importance 4.7
    data: Database management skills
    data: Information processing abilities

--- NORMALIZER SIGNALS ---
  match_keywords   : ['clinical data manager', 'clinical data management', 'cdm manager', 'clinical database', 'clinical data analyst', 'clinical informatics', 'data management', 'clinical trials data']
  exclude_keywords : ['clinical research coordinator', 'biostatistician', 'data scientist', 'health informatics', 'database administrator']
  title_patterns   : ['Clinical Data Manager', 'CDM Manager', 'Clinical Data Analyst', 'Clinical Database Manager', 'Clinical Data Coordinator']
  common_variations: ['clinical data management', 'cdm', 'clinical database management', 'clinical data systems', 'medical data management', 'healthcare data management', 'clinical informatics', 'clinical data operations']
Semantic Manifold — 40 terms · 5 provenance layers employment_word_extractor.py · sources: onet_tasks | onet_dimensions | dwas | wikipedia | inference · Constitutional Law III
total_terms    : 40
top_words      : ['clinical', 'management', 'others', 'tendency', 'trial', 'quality', 'equipment', 'research', 'design', 'procedures', 'validation', 'electronic', 'activities', 'crf', 'entry', 'database', 'analysis', 'control', 'principles', 'standards']
source_layers  : onet_tasks | onet_dimensions | dwas | wikipedia | inference

TERM                    COUNT     FREQ  DOMINANT SOURCE      SOURCE BREAKDOWN
──────────────────────────────────────────────────────────────────────────────────────────
clinical                  101  0.02623  wikipedia            wikipedia:67%  inference:26%  onet_tasks:7%
management                 65  0.01688  wikipedia            wikipedia:62%  inference:20%  onet_dimensions:11%
others                     42  0.01091  onet_dimensions      onet_dimensions:90%  dwas:10%
tendency                   42  0.01091  onet_dimensions      onet_dimensions:100%
trial                      25  0.00649  wikipedia            wikipedia:100%
quality                    24  0.00623  inference            inference:29%  onet_dimensions:25%  wikipedia:25%
equipment                  23  0.00597  onet_dimensions      onet_dimensions:100%
research                   22  0.00571  inference            inference:50%  wikipedia:41%  onet_tasks:5%
design                     19  0.00493  wikipedia            wikipedia:37%  onet_dimensions:32%  onet_tasks:11%
procedures                 19  0.00493  onet_dimensions      onet_dimensions:42%  dwas:26%  onet_tasks:16%
validation                 18  0.00467  wikipedia            wikipedia:78%  inference:17%  onet_tasks:6%
electronic                 18  0.00467  wikipedia            wikipedia:61%  onet_dimensions:28%  onet_tasks:6%
activities                 18  0.00467  onet_dimensions      onet_dimensions:50%  wikipedia:33%  inference:11%
crf                        18  0.00467  wikipedia            wikipedia:100%
entry                      16  0.00415  wikipedia            wikipedia:62%  inference:19%  onet_tasks:12%
database                   16  0.00415  wikipedia            wikipedia:69%  inference:19%  onet_tasks:12%
analysis                   16  0.00415  wikipedia            wikipedia:44%  onet_dimensions:25%  dwas:12%
control                    16  0.00415  onet_dimensions      onet_dimensions:75%  wikipedia:12%  onet_tasks:6%
principles                 16  0.00415  onet_dimensions      onet_dimensions:100%
standards                  15  0.00390  onet_dimensions      onet_dimensions:53%  wikipedia:47%
manager                    15  0.00390  wikipedia            wikipedia:93%  inference:7%
includes                   14  0.00364  onet_dimensions      onet_dimensions:86%  wikipedia:14%
rules                      13  0.00338  onet_dimensions      onet_dimensions:62%  wikipedia:38%
problems                   12  0.00312  onet_dimensions      onet_dimensions:75%  onet_tasks:8%  dwas:8%
processing                 12  0.00312  wikipedia            wikipedia:42%  onet_dimensions:33%  onet_tasks:8%
human                      12  0.00312  onet_dimensions      onet_dimensions:58%  wikipedia:33%  inference:8%
objects                    12  0.00312  onet_dimensions      onet_dimensions:100%
body                       12  0.00312  onet_dimensions      onet_dimensions:83%  wikipedia:17%
appropriate                11  0.00286  onet_dimensions      onet_dimensions:45%  wikipedia:36%  onet_tasks:18%
needs                      11  0.00286  onet_dimensions      onet_dimensions:73%  onet_tasks:9%  wikipedia:9%
ideas                      11  0.00286  onet_dimensions      onet_dimensions:100%
queries                    10  0.00260  wikipedia            wikipedia:70%  inference:20%  onet_tasks:10%
technical                  10  0.00260  onet_tasks           onet_tasks:30%  onet_dimensions:30%  inference:30%
technology                 10  0.00260  onet_dimensions      onet_dimensions:40%  onet_tasks:20%  dwas:20%
regulatory                 10  0.00260  inference            inference:60%  wikipedia:30%  onet_tasks:10%
techniques                 10  0.00260  onet_dimensions      onet_dimensions:100%
health                     10  0.00260  wikipedia            wikipedia:60%  inference:20%  onet_dimensions:10%
materials                  10  0.00260  onet_dimensions      onet_dimensions:100%
events                     10  0.00260  onet_dimensions      onet_dimensions:80%  wikipedia:20%
quickly                    10  0.00260  onet_dimensions      onet_dimensions:90%  wikipedia:10%
◈ Boise Standard Employment Graph · 15-2051.02 · built 2026-06-02 · Sources declared above are authoritative originals. This page synthesizes but does not replace them. Every claim traceable. Full provenance. Constitutional Law I.
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