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HIMSS Certified Professional in Healthcare Information and Management Systems Sample Questions (Q78-Q83):

NEW QUESTION # 78
A healthcare organization is scheduled to decommission 400 computers. An employee committee suggests the computers should be donated to a local charity. Which of the following is the MOST relevant IT policy?

Answer: B

Explanation:
The most relevant IT policy is the media disposal policy because donating decommissioned computers creates a high-risk pathway for unintentional disclosure of sensitive data , including ePHI. Even if the organization's intent is charitable, any storage media inside those computers (hard drives, SSDs, removable media) may contain patient information, employee data, cached credentials, configuration files, audit logs, or locally stored documents. A media disposal policy defines the required processes to prevent data leakage when equipment leaves organizational control, including asset inventory and tracking, approved sanitization methods, verification/validation of data destruction, documentation, and chain-of-custody controls .
In healthcare, secure disposal (or re-use/donation) typically requires sanitization aligned to organizational standards-such as cryptographic wiping, secure erase procedures, degaussing where appropriate, or physical destruction-plus records showing which assets were sanitized, by whom, when, and using what method. This ensures compliance with privacy and security obligations and reduces breach risk.
Conflict of interest and charitable contribution policies may apply to governance and ethics, but they do not address the core IT control required before donation: ensuring all data is irretrievably removed. Release of information policies focus on authorized disclosure of patient records, not device-level data sanitization.
Therefore, media disposal policy is the correct choice.


NEW QUESTION # 79
A balanced scorecard is used to provide visual representation of

Answer: C

Explanation:
A balanced scorecard is a strategic management and performance measurement framework that visually represents an organization's goals and performance across multiple perspectives. Traditionally, it includes four domains: financial, customer (or patient), internal processes, and learning and growth. Rather than focusing solely on financial results, the balanced scorecard links strategic objectives to measurable indicators, allowing leaders to track whether operational activities align with long-term strategy.
In healthcare organizations, this might include measures such as patient satisfaction scores, clinical quality indicators, operational efficiency metrics, workforce development benchmarks, and financial sustainability targets. The balanced scorecard translates mission and vision into specific, quantifiable objectives and displays them in dashboards or scorecards that allow executives and managers to monitor progress at a glance.
Option A (monitoring and assessment) is partially true but too narrow; the balanced scorecard is broader than simple monitoring-it connects strategy to measurable outcomes. Option B resembles SWOT analysis (strengths, weaknesses, opportunities, threats). Option C relates more to organizational culture and values statements.
Therefore, the balanced scorecard's primary purpose is to provide a structured, visual representation of strategic goals and organizational performance , making D the correct answer.


NEW QUESTION # 80
After a new pharmacy dispensing system is implemented, issues are reported regarding pharmacies not being able to process prescriptions that were received before the cutover to the new system. Which testing phase could have identified this issue?

Answer: C

Explanation:
Acceptance testing (User Acceptance Testing/UAT) is the testing phase most likely to identify an inability to process prescriptions that existed before cutover , because UAT validates that the solution supports real operational workflows and business requirements under conditions that mirror production use. A key go-live risk in pharmacy system replacement is data conversion and continuity of care : prescriptions entered in the legacy system prior to cutover must be accessible and actionable in the new environment (e.g., visible in work queues, eligible for verification, dispensing, labeling, adjudication, and documentation). In well-designed acceptance testing, users execute scripted scenarios that include "pre-cutover" items-converted orders, historical prescriptions, and in-flight work-specifically to confirm that the new system can safely continue processing without interruption.
By comparison, unit testing focuses on individual components and would not validate end-to-end prescription processing across converted legacy data. System integration testing emphasizes interfaces between systems (e.
g., EHR-to-pharmacy, claims, automation) but may not adequately validate business readiness with converted pre-cutover prescriptions unless explicitly included. Regression testing checks that changes did not break previously working functions, but it is not the primary phase for validating cutover continuity. Therefore, acceptance testing is the best answer.


NEW QUESTION # 81
Which of the following systems provide physicians with patient safety checks such as maximum dose limit?

Answer: B

Explanation:
Clinical decision support (CDS) is the system capability that provides physicians with patient safety checks such as maximum dose limits, dose-range checking, allergy and drug-drug interaction alerts, duplicate therapy warnings, contraindication notifications, and guideline-based recommendations. These checks are triggered within the clinical workflow-often during computerized provider order entry (CPOE)-so that when a clinician selects a medication, dose, route, or frequency, the CDS engine evaluates the order against medication knowledge bases and patient-specific factors (age, weight, renal function, allergies, current meds).
If the intended dose exceeds safe thresholds or conflicts with patient parameters, CDS generates warnings or
"hard stops," helping prevent adverse drug events before the order is finalized.
A drug vocabulary (or medication terminology/knowledge base) supplies standardized medication identifiers and reference information, but by itself it does not deliver active, workflow-based safety checking; CDS uses that vocabulary as an input. A data warehouse supports analytics and reporting, typically retrospective, rather than real-time prescribing checks. A clinical repository stores clinical data for access and exchange; it does not inherently apply rules to interrupt unsafe ordering in real time. Therefore, the correct answer is Clinical decision support .


NEW QUESTION # 82
Which of the following represents challenges in data quality in today's healthcare environment?

Answer: A

Explanation:
One of the most significant challenges affecting data quality in today's healthcare environment is the sheer volume of data generated . Modern healthcare systems produce massive amounts of information from EHRs, laboratory systems, imaging systems, wearable devices, remote monitoring tools, billing systems, and health information exchanges. As data volume increases, maintaining accuracy, completeness, consistency, timeliness, and integrity becomes more complex. Large datasets increase the likelihood of duplicate records, missing values, inconsistent coding, delayed documentation, and data entry errors. Additionally, high data volume places strain on governance processes, validation controls, and analytic oversight.
Option B (lack of patient portals) relates more to patient engagement than to intrinsic data quality challenges.
Option C (a variety of data dimensions) reflects complexity but does not directly define a core data quality problem; dimensional diversity can be managed through proper data modeling. Option D (lack of system interoperability) is primarily an exchange and integration issue rather than a direct data quality characteristic, although it can indirectly impact data consistency.
In healthcare information management frameworks, data quality challenges are often associated with the "3 Vs" of big data-volume, velocity, and variety-with volume being a primary driver of quality management complexity.


NEW QUESTION # 83
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