AHIMA Certified Health Data Analyst Examination Practice Test
Health data analysis turns clinical, operational, and administrative records into evidence for decisions. CHDA practice material samples statistical analysis, database design, data quality controls, visualization, and predictive modeling. These skills help analysts prepare usable datasets, select appropriate measures, interpret patterns, and explain results to health care teams.
Exam overview
About the AHIMA Certified Health Data Analyst Examination Exam
Health data analysts must define measures precisely, distinguish event dates from data-entry dates, and reconcile timestamps from systems using different time zones. Relational data design matters when linking patient records to repeated encounters without losing visit-level detail. Analysts also work with reference tables that map local codes to standardized reporting categories, requiring controls that preserve traceability when mappings change. Statistical judgment includes choosing summaries for nominal data, checking continuous-variable distributions, and assessing change over time. For classification models, measures such as positive predictive value help quantify how often flagged cases meet a review criterion; operational use also calls for evaluation on suitable data and consideration of how model outputs affect workflow. Clear dashboards depend on readable scales and legends so that geographic or rate comparisons are not misinterpreted.
Sample Practice Questions
Review a selection from this exam's published US Practice Tests practice bank.
A team wants to determine whether a new discharge-planning process changed the average time from discharge order to actual departure. The same measure is recorded weekly for several months before and after implementation. Which analysis is most suitable for examining the timing and pattern of change?
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Correct answer: AInterrupted time-series analysis evaluates repeated observations over time and can assess whether an intervention is associated with a change in the level or trend of a measure. The other choices do not examine the temporal pattern of the outcome.
A dataset contains a date-time value recorded in local time, while another source records date-time in Coordinated Universal Time. What should be addressed before combining events chronologically?
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Correct answer: ATime-zone differences can change event ordering and even calendar dates. Applying documented conversions to a consistent time basis supports valid chronology, while retaining source values can aid traceability.
An analyst is comparing a sample mean with a historical benchmark and is unsure whether the sample distribution is approximately normal. Which visual is useful for checking the shape of a continuous variable's distribution?
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Correct answer: AA histogram displays the distribution of a continuous variable and can reveal skewness, multiple peaks, or unusual values. The other displays are not designed to show the shape of a continuous distribution.
A data warehouse uses a reference table to translate source-system codes into standardized reporting categories. Which control is most useful when the reference mapping is revised?
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Correct answer: AEffective dates and version history support traceability and help explain how records were categorized at different times. Overwriting mappings without a record can make prior results difficult to reproduce or audit.
A team is designing a table to store one row per patient and repeated outpatient visits. Which design best represents the one-to-many relationship while preserving visit-level detail?
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Correct answer: BSeparating patient-level and visit-level entities supports multiple visits per patient without placing repeating values in a single field. A linking identifier allows visit records to be associated with the correct patient while retaining visit-level detail.
A database field stores the date a record was entered, but an analyst needs the date the clinical event occurred. What is the key distinction to clarify with the data owner?
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Correct answer: AEvent time and data-entry time can differ substantially. Clarifying which concept the field represents is necessary to interpret timelines and calculate time-based measures correctly.
A binary classifier identifies patients who may need additional review. Which measure describes the proportion of patients flagged by the classifier who truly meet the review criterion?
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Correct answer: CPositive predictive value is the proportion of positive classifications that are true positives. Sensitivity is the proportion of actual positives detected; specificity and negative predictive value describe performance among negatives.
How to use this practice test
Access is free. A session presents up to 20 randomly selected questions from the available 50-question bank, then shows results. Use the questions to identify which analysis, data-management, or interpretation decisions need further practice; review your reasoning against the specific scenario rather than memorizing answer patterns.
Preparation tips
- Practice distinguishing event time, record-entry time, and time-zone representation before joining records from multiple systems.
- For repeated encounters, sketch patient-to-visit relationships and check that each visit retains its own date and outcome fields.
- Choose summaries by variable type: use counts or proportions for nominal categories, and inspect distribution shape before applying methods that rely on assumptions about continuous data.
- Compare measures such as positive predictive value with the operational purpose of a classification model, and consider how errors affect follow-up workload.
- Review dashboard scales, legends, and reference-code mappings for choices that could distort comparisons or obscure category changes.