NAHQ Updated CPHQ Exam Questions and Answers by steven

Implementing patient portals is the best example of a patient-centered approach in healthcare. Patient portals empower patients by giving them access to their health information, enabling them to communicate with their providers, schedule appointments, and manage their health more effectively. This approach aligns with the principles of patient-centered care, which emphasize respect for patients' preferences, needs, and values, and encourage active patient participation in their own care.

Providing pre-printed dischargeinstructions (A): While useful, this is more of a standard practice and not as interactive or empowering as a patient portal.

Checking two patient identifiers (C): This is a safety procedure focused on preventing errors rather than patient-centered care.

Using age-based medication dosing (D): This is a clinical best practice but does not directly engage the patient in their care.

References

NAHQ Body of Knowledge: Patient-Centered Care and Engagement

NAHQ CPHQ Exam Preparation Materials: Implementing Patient-Centered Approaches

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Detailed Explanation:

Monitoring for continuous compliance is essential for sustaining improvement, as it ensures that performance is consistently tracked and deviations are promptly addressed.

Option C: Monitor for continuous compliance

Ongoing monitoring helps maintain high performance and catch any lapses in compliance early.

To determine which provider does not earn pay-for-performance, we must compare each provider’s performance against the 50th and 75th percentiles for all measures. A provider must meet at least the 50th percentile on at least one measure to qualify.

Physician A: Diabetic Retinal Eye Exam (75% > 65% [50th], > 70% [75th]), Nephropathy (53% > 50% [50th], > 52% [75th]), HbA1c Testing (76% = 76% [75th], > 72% [50th]). Meets 50th and 75th percentiles on multiple measures, qualifying for payout.

Physician B: Diabetic Retinal Eye Exam (80% > 65% [50th], > 70% [75th]), Nephropathy (43% < 50% [50th]), HbA1c Testing (80% > 72% [50th], > 76% [75th]). Meets 50th and 75th percentiles on two measures, qualifying for payout.

Nurse Practitioner C: Diabetic Retinal Eye Exam (60% < 65% [50th]), Nephropathy (50% = 50% [50th], < 52% [75th]), HbA1c Testing (52% < 72% [50th]). Meets only the 50th percentile for Nephropathy, but performance is below 50th for other measures, and no 75th percentile is met, making this the weakest performer.

Physician Assistant D: Diabetic Retinal Eye Exam (63% < 65% [50th]), Nephropathy (48% < 50% [50th]), HbA1c Testing (70% < 72% [50th]). Does not meet 50th percentile on any measure, potentially disqualifying them.

Analysis: The question asks for the provider who does not earn pay-for-performance based on reaching either percentile. Nurse Practitioner C meets the 50th percentile for Nephropathy (50%), while Physician Assistant D meets no percentiles. However, the phrasing suggests a single provider, and C’s minimal achievement (only one measure at 50th) may be interpreted as insufficient for payout, depending on program rules. Given C’s overall poor performance (below 50th on two measures), it is the most likely answer.

CPHQ Objective Reference: Domain 2: Health Data Analytics, Objective 2.4, “Interpret performance data for pay-for-performance programs,” requires comparing provider data against benchmarks. The NAHQ study guide notes, “Providers must meet or exceed percentile thresholds to qualify for pay-for-performance incentives” (Domain 2).

Rationale: Nurse Practitioner C’s marginal performance (only one measure at 50th, none at 75th) makes them the least likely to earn payout, aligning with CPHQ’s focus on data-driven performance evaluation.

The median is a measure of central tendency in statistics that represents the middle value of an ordered data set.

Data Set Ordering: To find the median, the data set must first be arranged in ascending or descending order.

Middle Value Identification: The median is the value that divides the data set into two equal parts, with 50% of the data points lying below it and 50% above it. If the number of observations is odd, the median is the middle number; if even, it is the average of the two middle numbers.

Robustness: Unlike the mean, the median is not affected by extreme values (outliers), making it a more robust measure of central tendency in skewed distributions.