NAHQ Updated CPHQ Exam Questions and Answers by diana

Comprehensive and Detailed Explanation From Exact Extract:

In the Performance and Process Improvement domain, leadership support is the single most critical factor in achieving sustainable improvement.

Strong leadership commitment ensures alignment with strategic priorities, adequate resource allocation, staff engagement, and accountability for outcomes.

While team formation, data systems, and resources are all essential elements, without visible and consistent leadership support, improvement efforts typically fail to gain momentum or sustain change.

To increase profitability of services covered under bundled payments, the healthcare quality professional should recommend starting with an analysis of efficiency. Bundled payments provide a single payment for all services related to a treatment or condition, incentivizing providers to deliver care more efficiently. Analyzing efficiency can help identify areas where resources can be used more effectively, reducing costs while maintaining or improving quality, which is critical for profitability under bundled payment models.

Safety (B): While crucial, safety alone may not directly impact profitability under bundled payments.

Access (C): Improving access is important but may not directly influence profitability in the context of bundled payments.

Equity (D): Equity is essential for quality care but is not the primary focus when aiming to increase profitability under bundled payments.

References

NAHQ Body ofKnowledge: Efficiency and Cost Management in Healthcare

NAHQ CPHQ Exam Preparation Materials: Analyzing Quality in Bundled Payment Models

=========

The p-value is a statistical measure used in hypothesis testing to determine the probability of observing the data (or more extreme results) assuming the null hypothesis is true. It is commonly referred to as the level of significance, indicating whether the results are statistically significant when compared to a predetermined threshold (e.g., α = 0.05).

Option A (An index of data reliability): Reliability refers to the consistency of a measurement tool, not the function of a p-value. The p-value assesses the likelihood of results occurring by chance, not the reliability of the data collection process.

Option B (A level of significance): This is the correct answer. According to NAHQ CPHQ study materials, the p-value is used to determine statistical significance, helping quality professionals evaluate whether observed differences or outcomes (e.g., in quality improvement interventions) are likely due to chance. A low p-value (e.g., <0.05) suggests the results are significant, leading to rejection of the null hypothesis.

Option C (A measure of central tendency): Measures of central tendency (mean, median, mode) describe the center of a data distribution and are unrelated to the p-value, which is a hypothesis testing metric.

Option D (A degree of deviation): Deviation refers to variability measures like standard deviation, which quantify data spread. The p-value does not measure deviation but rather the significance of observed results.

Comprehensive and Detailed Explanation From Exact Extract:

Within the Population Health and Care Transitions domain, the goal of chronic disease management programs, such as a diabetic management initiative, is to improve patient health outcomes and reduce avoidable utilization of acute care services.

A decrease in hospital admission rates directly demonstrates improved disease control, effective self-management, and continuity of care. This is considered a key outcome measure, reflecting true program success.

In contrast, patient satisfaction, appointment adherence, or follow-up compliance (options A, B, and D) are process measures that support improvement but do not confirm the ultimate impact of the program on population health outcomes.