Data display tools visualize performance trends to support quality improvement. The tool best suited for showing changes over time, such as monthly fall rates, must depict sequential data points.
Option A (Run chart): This is the correct answer. The NAHQ CPHQ study guide states, "Run charts are used to display data over time, showing trends, patterns, or shifts in performance" (Domain 2). For monthly fall rates, a run chart plots rates against time, highlighting changes and trends effectively.
Option B (Scatter diagram): Scatter diagrams show relationships between two variables (e.g., fall rates vs.
staffing levels), not time-based trends.
Option C (Fishbone diagram): Fishbone diagrams (cause-and-effect) identify root causes, not display temporal data.
Option D (Pareto chart): Pareto charts prioritize issues by frequency or impact, not suitable for showing monthly trends.
CPHQ Objective Reference: Domain 2: Health Data Analytics, Objective 2.3, "Select appropriate data display tools for quality improvement," identifies run charts as ideal for temporal data analysis. The NAHQ study guide emphasizes their simplicity and effectiveness in tracking performance metrics like fall rates.
Rationale: Run charts are specifically designed to visualize changes over time, making them the best tool for demonstrating monthly fall rate trends, as required for quality monitoring and reporting.
Reference: NAHQ CPHQ Study Guide, Domain 2: Health Data Analytics, Objective 2.3.

Reducing Medicare readmissions is a key focus in population health, as readmissions impact patient outcomes and hospital reimbursement under programs like the Hospital Readmissions Reduction Program (HRRP).
Factors driving readmissions often include inadequate discharge planning, lack of follow-up care, social determinants of health (e.g., transportation, support systems), and patient-specific risks (e.g., comorbidities).
NAHQ CPHQ study materials emphasize a systematic, data-driven approach to quality improvement, particularly for complex issues like readmissions.
Since the specific Medicare readmission findings are not provided, I'll base the answer on CPHQ best practices. The first step in addressing readmissions should always be to analyze data to determine the best approach for readmission reduction (D). This involves reviewing the readmission findings to identify patterns, such as high-risk patient groups, common diagnoses (e.g., heart failure, pneumonia), or process failures (e.g., medication reconciliation issues). Data analysis helps pinpoint root causes and informs targeted interventions, ensuring resources are used effectively. For example, if data show readmissions are due to lack of follow-up care, then strategies like follow-up calls or visits can be prioritized. Without this analysis, interventions may be misdirected.
Instructing physicians to place patients in observation (A) may reduce reported readmissions by reclassifying stays, but this does not address underlying causes and could be seen as gaming the system, which is not aligned with quality improvement principles. Initiating post-discharge follow-up calls (B) or increasing follow-up visits (C) are potential interventions, but they assume specific causes (e.g., lack of follow-up) without evidence from the data. NAHQ emphasizes that quality improvement starts with understanding the problem through data analysis, making option D the first step.
Reference: NAHQ CPHQ Study Guide, Population Health and Care Transitions Section, "Readmission Reduction Strategies"; NAHQ CPHQ Practice Exam, Data-Driven Quality Improvement for Population Health.

According to NAHQ, one of the core competencies for healthcare quality professionals is education and training1, which involves designing, developing, delivering, and evaluating educational programs that support quality improvement and patient safety2.
When developing objectives for an educational program, the quality professional should follow the SMART criteria, which stands for specific, measurable, achievable, relevant, and time-bound3. These criteria help to ensure that the objectives are clear, realistic, and aligned with the desired outcomes of the program4.
Therefore, the quality professional should recommend stating the end result or desired outcome of the program, as this will help to define the purpose, scope, and direction of the program, as well as the criteria for measuring its success. For example, an objective for an educational program on infection prevention and control could be: "By the end of this program, participants will be able to identify and apply the best practices for preventing and managing healthcare-associated infections in their settings." The other options are not the best recommendations for developing objectives for an educational program, because:
A). using the Plan-Do-Study-Act cycle of continuous improvement is a method for implementing and evaluating quality improvement projects, not for developing objectives for an educational program.
C). keeping the objectives specific to the short term may limit the scope and impact of the program, as well as the opportunities for learning and improvement.
D). tying the objectives to the organization's financial performance may not reflect the true value and outcomes of the program, as quality improvement and patient safety may have other benefits that are not easily quantified in monetary terms. References: 1: Competency Framework | NAHQ 2: NAHQ Healthcare Quality Competency Framework 3: [HQ Principles | NAHQ] 4: How to Write SMART Learning Objectives - Convergence Training : Writing Measurable Learning Outcomes - Gavilan College : Infection Prevention and Control Education & Resources - APIC : Plan-Do-Study-Act (PDSA) Worksheet | IHI - Institute for Healthcare Improvement : Setting Goals and Objectives for Projects | Smartsheet : [The Financial Case for Quality as a Business Strategy | NAHQ]