NAHQ CPHQ Based on Real Exam Environment

A Gantt chart is a type of bar chart that illustrates a project schedule1. This tool is used in project management, and it’s particularly useful in the scenario described because it can help the team visualize their progress on different tasks1.

In this case, the team is at different stages with various tasks: they’re one-fourth finished with identifying benchmark organizations, they haven’t started identifying the current state, and they’re halfway through collecting public data1. A Gantt chart can help them see all these tasks and their progress in one place, making it easier to manage their work and stay on schedule1.

While the other tools mentioned (Model for Improvement, Design of Experiments, Ishikawa diagram) can be useful in certain scenarios, they don’t specifically address the need to visualize and manage progress on multiple tasks23. Therefore, the Gantt chart is the most appropriate tool to recommend in this situation1.

Detailed Explanation:

For a large population, a simple random sample of 400 charts would be sufficient to obtain representative data for statistical analysis:

Option B:Selection of 400 charts using a simple random sampling method

Simple random sampling ensures each patient has an equal chance of selection, providing unbiased and representative results while being more manageable than reviewing all 8,000 records.

Option A: Selection of patients who had a visit during the last month of the year

This could lead to biased results, as it would not be representative of visits throughout the year.

Option C: Selection of 800 patients using a snowball sampling method

Snowball sampling is typically used for hard-to-reach populations and is not appropriate for this scenario.

Option D: Selection of the entire population

Auditing all records would be time-consuming and unnecessary when a statistically valid sample can provide reliable results.

Comprehensive and Detailed Explanation From Exact Extract:

Under the Performance and Process Improvement domain, after data analysis identifies variability or underperformance, the next logical step is to create an action plan in collaboration with responsible department leaders.

This ensures ownership, identification of barriers, and development of specific interventions. Simply monitoring further or sharing data without structured planning will not address underlying causes.

The Root Cause Analysis (RCA) process focuses on identifying contributing system and process factors before implementing process redesign. Training or external hiring (options B and D) are not immediate RCA steps without defined root causes.

A retrospective review of patients with post-surgical respiratory failure (C) identifies root causes, informing interventions. Focus groups (A), FPPE (B), and team identification (D) follow data analysis. NAHQ emphasizes data-driven root cause analysis as the first step.

NAHQ CPHQ Study Guide, Performance and Process Improvement Section, “Data Analysis for Quality Issues”; NAHQ CPHQ Practice Exam, Clinical Outcome Improvement.