Free CPHQ Practice Test Questions and Answers (2026)

A sentinel event is a patient safety event that reaches a patient and results in any of the following:

Death

Severe temporary harm

Permanent harm

An intervention required to sustain life

Option D, "An intervention to sustain life," aligns with the definition of a sentinel event. Such

interventions may include actions like cardiopulmonary resuscitation (CPR), defibrillation, or other

emergency procedures necessary to keep the patient alive following a significant adverse event.

The storming phase is the second stage of team development, where conflicts and differences in

opinions may arise12. During this phase, the team is still figuring out how to work well together1.

The leader’s role is crucial at this stage. They need to provide clear direction for the project and help

individuals on the team get to know and accept each other3. This involves directing the team and

providing role clarification3, which aligns with option A.

The expectation to maintain continuous survey readiness must be supported and driven by the

executive team. Leadership commitment from the highest levels of the organization is crucial for

fostering a culture of readiness and ensuring that all staff are engaged in maintaining compliance

with accreditation standards. The executive team's support ensures that the necessary resources,

policies, and procedures are in place to sustain continuous readiness.

Quality team (B): The quality team plays a key role in survey readiness, but their efforts must be

supported by the executive team.

Risk manager (C): The risk manager contributes to readiness by identifying and mitigating risks, but

they cannot drive the organization-wide effort alone.

Compliance officer (D): The compliance officer ensures adherence to regulations, but continuous

readiness requires broader leadership involvement.

Reference

NAHQ Body of Knowledge: Leadership and Continuous Survey Readiness

NAHQ CPHQ Exam Preparation Materials: Roles in Maintaining Survey Readiness

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Errors of omission can lead to delayed or missed diagnosis1. In the context of healthcare quality,

these errors are often preventable and can be mitigated through varioussystems and strategies23.

Option A, a reminder system that is in close proximity to the task and provides sufficient information

about what needs to be done, aligns with the strategies to prevent errors of omission. This system

serves as a proactive measure to ensure that necessary actions are taken and important steps are not

missed. It provides healthcare professionals with timely and relevant information, thereby reducing

the likelihood of errors of omission1.

Option B, a warning system that is contiguous to the task and cues that the individual is about to

initiate the wrong intervention, while useful, is more aligned with preventing errors of commission

(doing something wrong) rather than errors of omission (failing to do something right).

Option C, a proactive risk assessment system that integrates with the task and automatically notifies

the risk manager, is also a valuable tool in healthcare quality. However, it is more focused on

identifying and managing risks rather than preventing errors of omission.

Option D, a detection system that notifies the team when an error has occurred and provides a

checklist for mitigation measures, is a reactive measure. While it is crucial for mitigating the impact

of errors, it does not directly prevent errors of omission.

Therefore, based on the information available, option A would most likely be the most effective

system in assisting an organization with evaluating patient safety actions that will prevent errors of

omission231.

Preparing care team members for interacting with accreditation surveyors is a crucial part of the

accreditation process. The best approach is to brief them onsurvey activities and what questions to

expect (Option C). This involves providing them with an understanding of the survey objectives, the

day’s schedule, and the types of questions that surveyors may ask1. This approach helps to ensure

that team members are well-prepared and confident when interacting with surveyors. Reviewing

patient records proactively (Option A) and summarizing and discussing past survey findings (Option

B) can also be helpful, but these activities are more focused on identifying and addressing potential

issues before the survey, rather than preparing team members for the survey itself. Providing

techniques to defer surveyor questions to leaders (Option D) could potentially create a perception of

lack of transparency or evasion, which could negatively impact the survey results.

Reference:

https://www.jointcommission.org/what-we-offer/accreditation/health-care-settings/laboratoryservices/prepare/prepare-support/8-best-practices-to-prepare-for-the-survey/

The HEDIS measure of the percent of diabetic patients with a HgA1c greater than 9.0% is an indicator

of poor glycemiccontrol and a risk factor for complications12. Reducing this measure is a quality

improvement goal that requires a multidisciplinary approach and data-driven strategies34.

A quality improvement team is a group of individuals with different roles and responsibilities who

work together to achieve a common aim56. The team should include representatives from various

areas of the clinic, such as management, clinical staff, and data analysts78.

The clinic manager is responsible for providing effective and consistent leadership, communicating

the vision and the steps for improvement, engaging the team in planning and monitoring, allocating

resources and training, and fostering a culture of open communication and continuous learning78.

The quality improvement specialist is responsible for analyzing and reviewing the clinical and

business data, suggesting and selecting the key priority areas, implementing and evaluating the

improvement interventions, and reporting the results and outcomes78.

The provider champion is responsible for modeling enthusiasm and support for quality

improvement, leading the clinical discussions and decisions, influencing and educating other

providers and staff, and ensuring adherence to evidence-based guidelines and best practices78.

The HEDIS chart abstractor, the coder, and the primary care provider are also important members of

the quality improvement process, but they are not sufficient to form a comprehensive and effective

team. The HEDIS chart abstractor and the coder are mainly involved in collecting and coding the

data, while the primary care provider is mainly involved in delivering the care. They need the

guidance and coordination of the clinic manager, the quality improvement specialist, and the

provider champion to align their efforts and achieve the desired

outcomes78. Reference: 1: Hemoglobin A1c Control for Patients with Diabetes (HBD) 2: Glycemic

Status Assessment for Patients with Diabetes 3: Quality Improvement Team Roles and

Responsibilities - PracticeAssist 4: The Roles & Responsibilities of A Quality Management

Team 5: QUALITY IMPROVEMENT TEAMS COMPOSITION 6: Comprehensive Diabetes Care -

NCQA 7: HEDIS 2022 Manual - Johns Hopkins Medicine 8: HEDIS® Hemoglobin A1c Control for

Patients with Diabetes (HBD) 9: GSD - Glycemic Status Assessment for Patients With Diabetes

A scatter plot is a graphical tool that shows the relationship between two continuous variables by

plotting data points at their corresponding values on the x-axis and y-axis1.

To interpret a scatter plot, we need to look at the direction, strength, and shape of the relationship

between the variables2.

The direction of the relationship indicates whether the variables tend to increase or decrease

together (positive correlation) or in opposite directions (negative correlation).

The strength of the relationship indicates how closely the data points cluster around a line or curve

that best fits the data. A common measure of the strength of the linear relationship is the correlation

coefficient ®, which ranges from -1 to 1. The closer the absolute value of R is to 1, the stronger the

linear relationship2.

The shape of the relationship indicates whether the data points follow a straight line (linear

relationship) or a curved pattern (nonlinear relationship).

Based on these criteria, we can analyze the scatter plots for Setting 1 and Setting 2 as follows:

Setting 1: The scatter plot shows a clear upward trend, indicating a positive correlation between

complication rate and time to positive outcome. Thedata points are tightly clustered around a line,

indicating a strong linear relationship. The R^2 value of 0.9533 on the plot is close to 1, which means

that the linear model explains 95.33% of the variation in the complication rate. Therefore, we can

conclude that Setting 1 has a strong positive correlation between complication rate and time to

positive outcome.

Setting 2: The scatter plot shows a scattered pattern, indicating a weak or no correlation between

complication rate and time to positive outcome. The data points are widely spread around a line,

indicating a weak linear relationship. The R^2 value of 0.4923 on the plot is far from 1, which means

that the linear model explains only 49.23% of the variation in the complication rate. Therefore, we

cannot conclude that Setting 2 has a significant correlation between complication rate and time to

positive outcome, or that complication rates are causing longer time to positive outcome at setting 2.

Reference: 1: 8.8 Scatter Plots, Correlation, and Regression Lines 2: Scatterplots: Using, Examples,

and Interpreting

In the context of performance improvement and quality control, variations in a process are typically

categorized as either common cause or special cause12345.

Common cause variation is the kind of variation that is part of a stable process. These are variations

that are natural to a system and are quantifiable and expected1. They are predictable, ongoing, and

consistent1. Major changes would typically have to be made in order to change the common cause

variations1. You can identify common cause variation points on the control chart of a process

measure by its random pattern of variation and its adherence to the control limits1.

Special cause variation, on the other hand, is unexpected variation in the process14. There is a

specific cause that can be assigned to the variation4. These variations are unusual, unquantifiable,

and are variations that have not been observed previously, so they cannot be planned for and

accounted for1. These causes are typically the result of a specific change that has occurred in the

process, with the result being a chaotic problem1. You can identify special cause variation on a

control chart by their non-random patterns and out-of-control points15.

In the given scenario, the performance improvement team has been examining delays in getting

admissions from the emergency room to the nursing units. After six months of collecting data, the

upper control limit was 150 minutes, and the lower control limit was 60 minutes. The next month’s

data shows a time of 155 minutes. This time of 155 minutes is beyond the established upper control

limit of 150 minutes. Therefore, this represents a special cause variation15, as it is an unexpected

variation that significantly deviates from the established control limits.

Reference: 12345

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The question is asking which patient population is at the highest risk for falling.

By analyzing the provided table, it can be observed that patients who had “falls prior to admission”

have the highest number of falls after admission (30 patients) compared to other categories.

This data indicates that having a history of falls before being admitted increases the risk of falling

again.

Although I don’t have direct access to external websites including NAHQ, it’s generally understood in

healthcare quality and safety that ahistory of falls is a significant risk factor for future falls. This is

likely supported by resources and documents on patient safety and fall prevention available on

professional healthcare quality websites.

Active surveillance in healthcare is a proactive approach to identifying and monitoring health-related

events or diseases123. It involves the continuous, systematic collection, analysis, and interpretation

of health-related data needed for the planning, implementation, and evaluation of public health

practice1.

Option B, “Identifying disease outbreaks through public health contact tracing,” is an example of

active surveillance. Contact tracing is a key strategy for preventing the further spread of infectious

diseases. It involves identifying people who have an infectious disease (cases) and their contacts

(people who may have been exposed) and working with them to interrupt disease transmission12.

Option A, “analyzing laboratory data for disease testing utilization,” could be part of both active and

passive surveillance, depending on the context. However, it does not necessarily involve the

proactive steps typically associated with active surveillance13.

Option C, “analyzing infectious diseases based on hospital discharge final coding,” is more related to

passive surveillance, which involves the collection of data as they become available, or the data that

are passively received by health care providers or health information systems13.

Option D, “reporting of infectious diseases data quarterly to local health departments,” is also more

related to passive surveillance, as it involves regular reporting of health data from various sources13.

The most logical sequence for the phases of shifting from top-down leadership to participatory

management is to start with making the commitment, then gathering baseline data, implementing

the program, and evaluating effectiveness and improvement.

Making the commitment is the first step because it involves creating a shared vision, setting goals

and objectives, and securing support and resources for the change process12. Without a clear and

strong commitment, the other steps may not be feasible or successful.

Gathering baseline data is the second step because it helps to assess the current situation, identify

the gaps and needs, and establish a baseline for comparison and measurement13. Data can be

collected from various sources, such as surveys, interviews, observations, and records, and can cover

aspects such as organizational culture, performance, quality, satisfaction, and costs13.

Implementing the program is the third step because it involves putting the plan into action, engaging

and empowering the staff and stakeholders, and monitoring and adjusting the process as

needed14. Implementation can be done in phases, pilots, or trials, depending on the scope and

complexity of the program14.

Evaluating effectiveness and improvement is the fourth step because it helps to measure the

outcomes, impacts, and benefits of the program, compare them with the baseline data and the goals

and objectives, and identify the strengths, weaknesses, and areas for improvement15. Evaluation can

be done using quantitative and qualitative methods, such as indicators, metrics, feedback, and

stories, and can be conducted at different levels, such as individual, team, and organizational15.

Reference: 1: Participatory Leadership for Health 2: Quality improvement and person-centredness: a

participatory mixed methods study to develop the ‘always event’ concept for primary care 3: Why

healthcare leadership should embrace quality improvement 4: PARTICIPATIVE MANAGEMENT IN

HEALTH CARE SERVICES 5: [Utilization of Improvement Methodologies by Healthcare Quality

Professionals During the COVID-19 Pandemic]

Ongoing Professional Practice Evaluation (OPPE) is part of the credentialing process for medical staff

aimed at evaluating a provider’s clinical competence and professional behavior on an ongoing basis,

rather than at the time of reappointment only. OPPE is typically used to monitor providers with

identified practice issues. It involves collecting data about a provider’s performance over time,

reviewing the information regularly, and using it to ensure that the provider meets professional

standards. This proactive monitoring can lead to early identification and resolution of potential

issues.

Reference:This aligns with best practices as outlined by the Joint Commission and is reflected in the

guidelines and educational materials provided by NAHQ. OPPE is a standard element in healthcare

quality and credentialing that focuses on continuous evaluation of a provider's ability to provide

quality care.

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.

Failure Mode and Effects Analysis (FMEA) is a systematic method for evaluating a process to identify

where and how it might fail, to assess the relative impact of different failures, and to identify the

parts of the process that are most in need of change. FMEA includes review of the following:

Steps in the process: Identify what could go wrong during each step.

Failure modes: Identify potential failure modes for each step.

Failure effects: For each failure mode, identify potential effects.

Severity: Assign a severity rating for each effect of failure.

Occurrence: Assign an occurrence rating foreach failure mode.

Detection: Assign a detection rating for each failure mode and effect.

Risk Priority Number (RPN): Calculate the RPN for each effect.

FMEA is particularly useful in healthcare for risk assessment of a new or modified process because it

not only identifies potential failures, but also prioritizes them based on their impact, frequency of

occurrence, and detectability, allowing for targeted and efficient process improvement.

Reference:

Quality improvement tools are standalone strategies or processes that can help you better

understand, analyze, or communicate your QI efforts1.

The 7 Basic Quality Tools for Process Improvement2.

A guide to quality improvement tools3.

An Ishikawa diagram, also known as a fishbone diagram, is a tool used to identify and organize

potential causes of a problem12. It’s often used by teams to graphically display the relationship of

the causes to the effect and to each other2. However, creating and interpreting an Ishikawa diagram

can be challenging if the team does not have a clear focus or agreement3.

In this case, the most likely cause for the challenge in completing an Ishikawa diagram is that the

charter did not provide a specific problem statement4. A clear and specific problem statement is

crucial as it provides the team with a clear understanding of what they are trying to solve4. Without

it, the team may struggle to identify and agree on the potential causes of the problem4.

Therefore, to overcome this challenge, the team should revisit the charter and work together to

define a specific problem statement. This will provide them with a clear focus and help them come to

an agreement on the potential causes of the problem, thereby facilitating the completion of the

Ishikawa diagram4.

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High-reliability organizations (HROs) operate in complex, high-hazard domains for extended periods

without serious accidents or catastrophic failures1. They prioritize safety over other performance

pressures1.

The principles of high reliability go beyond standardization; high reliability is better described as a

condition of persistent mindfulness within an organization1. HROs work to create an environment in

which potential problems are anticipated, detected early, and virtually always responded to early

enough to prevent catastrophic consequences1.

One of the key characteristics of HROs is a preoccupation with failure1. Everyone is aware of and

thinking about the potential for failure1. Near misses are viewed as opportunities to learn about

systems issues and potential improvements, rather than as evidence of safety1.

Another important characteristic is deference to frontline expertise1. This means that those closest

to the work, who have the most direct knowledge of the situation at hand, have the authority to

make decisions1.

In the given scenario, meeting with the staff involved in the errors to gain additional insight (Option

B) aligns with these principles. It shows a preoccupation with failure and deference to frontline

expertise. By meeting with the staff, leadership can understand what led to the errors and how to

prevent them in the future. This approach is consistent with the principles of high reliability and is

likely to contribute to the clinic’s goal of becoming a high-reliability organization.

Tracers are a method of assessing the quality and safety of care, treatment, or services by following

the experience of a patient or a process through the entire health care delivery system1.

Tracers are used by The Joint Commission and other accreditation bodies to evaluate the compliance

of health care organizations with the standards and requirements for accreditation1.

Tracers can help identify the strengths and weaknesses of an organization’s processes and practices,

as well as the risks and opportunities for improvement23.

Tracers can also help engage staff and stakeholders in continuous improvement activities and foster a

culture of quality and safety24.

Therefore, the main purpose of conducting tracers as a part of continuous readiness is to identify

current gaps in processes of quality and patient safety that need correcting, as this will help the

organization achieve better outcomes and meet the expectations of

accreditation1234. Reference: 1: Tracer Methodology Fact Sheet | The Joint Commission 2: How

tracer rounds can support effective continuous improvement in healthcare 3: Unlocking QTRACER’s

secret to ensure continuous improvement in healthcare 4: Continuous Service Readiness | Joint

Commission Resources

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