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Running head: QUALITY IMPROVEMENT IN DIRECT PRIMARY CARE 1

Quality Improvement Project within a Direct Primary Care Clinic

A Scholarly Project Presented to

The Faculty of the Maryville University

Catherine McAuley School of Nursing

In Fulfillment of the Requirements

For the Degree of Doctor of Nursing Practice

STEVIE CAMP, BSN, RN

APRIL 18, 2019

QUALITY IMPROVEMENT IN DIRECT PRIMARY CARE 2

TABLE OF CONTENTS

Title Page 1

Table of Contents 2

Abstract 3

Chapter 1: Introduction 4

Chapter II: Review of Related Literature 10

Chapter III: Methods 18

Chapter IV: Findings 26

Chapter V: Discussion 33

References 39

Appendices 43


ABSTRACT


Background: Patient satisfaction is becoming a crucial component of healthcare delivery systems nationwide. In part, this is due to mandates set forth by the Centers for Medicare and Medicaid (CMS) and the overarching goal to transition healthcare to a quality-based system from a quantity-based system (Centers for Medicare & Medicaid Services, 2017). An innovative healthcare model, direct primary care (DPC), is at the forefront of this movement. Direct primary care boasts the ability to provide patients with more time and access to providers at a lower cost compared to traditional models (American Academy of Family Physicians, 2019).

Objective: The purpose of this doctor of nursing practice (DNP) project was to evaluate the results of patient satisfaction surveys within a DPC clinic located in the Southeast region of the United States to assess for strengths, weaknesses, and associations related to the perception of the patients who received care at the clinic.

Design: The study design was an exploratory quantitative design. A retrospective review was performed using patient satisfaction surveys collected over three months. Nine target variables were assessed based on the survey questions. Twenty-one patient satisfaction surveys were utilized for the study.

Results: Descriptive statistics were utilized to examine survey responses. Overall, the findings reflected that respondents were satisfied with the care they received at the DPC clinic. All respondents indicated that their provider listened to them, knew pertinent information regarding their health, respected them, and that their visit was of adequate length. The provider of the DPC clinic was rated as a 9.9 on a Likert scale with 10 being the best possible provider.

Conclusions: Measuring patient satisfaction is becoming commonplace within healthcare delivery systems. Patient satisfaction surveys are an effective way to solicit patient feedback to gauge satisfaction. This project demonstrated the successful implementation of a patient satisfaction evaluation program and determined that patients were satisfied with the care they received at a DPC clinic located in the Southeast region of the United States.

Key words: Direct primary care, patient satisfaction, patient experience



Chapter I: Introduction

Introduction to the Problem

Patient satisfaction surveys are an integral part of healthcare delivery systems. This can

be partially attributed to the 2007 mandates set forth by the CMS (CMS, 2017). Furthermore,

eliciting patient feedback through satisfaction surveys has been shown to improve

communication between patients and providers, improve patient outcomes by preventing

complications and mortality, and increase revenue from CMS (Bogner et al., 2016; CMS, 2018a;

Farrington, Burt, Boiko, Campbell, & Roland, 2016; Overveld et al., 2017). Patient satisfaction

surveys should be implemented in all areas of practice to ensure the highest level of care is being

rendered.

Interest and Level of Expertise

The author of this DNP project has no prior experience with patient satisfaction surveys.

However, working in the medical field as a registered nurse provides exposure to prompting

patient feedback and providing appropriate follow up interventions similar to the patient

satisfaction survey process. Additionally, Maryville University’s DNP program has prepared

this author to evaluate and implement evidence-based research.

Purpose and Aims

The purpose of this DNP project was to evaluate the results of patient satisfaction surveys

within a DPC clinic to assess for strengths, weaknesses, and associations related to the

perception of the patients who received care at the clinic. The overall aim was to improve the

care provided by the clinic and to comply with regulations set forth by the CMS to evaluate

patients’ satisfaction of their healthcare experience at the clinic (CMS, 2012). Furthermore,


examining patient satisfaction surveys in the DPC healthcare model will highlight the uniqueness

of this model and will hopefully support that this model lends a more positive patient experience

along with better health outcomes.

Patterns of Knowing

Barbara Carper divided the concept nursing knowledge into four essential patterns of

knowing in 1978. Carper argued that one must be able to examine each of these patterns of

knowing to be able to teach and learn different concepts in nursing (Carper, 1978).

Implementing a doctoral project regarding the concept of patient satisfaction can help inform

each pattern of knowing in the following ways.

The first pattern of knowing is empirics, the science of nursing. Carper described this

pattern as developing explanations behind theories (Carper, 1978). This project evaluated patient

satisfaction in a unique healthcare setting that is not supported by a strong body of evidence.

The results of the project were descriptive, scientifically analyzed, and publicly verifiable, which

are components of Carpers first pattern of knowing (Carper, 1978). This doctoral project has the

ability to add to the science of nursing by contributing to the body of literature supporting patient

satisfaction within the DPC model.

Carper noted that the pattern of personal knowledge, although one of the most important,

is often the most difficult to master and teach. A nurse must have a therapeutic use of self to be

able to view a patient as something more than an object (Carper, 1978). This doctoral project

strived to evaluate the patients’ perception and experience to ensure that all aspects of care and

wellness were met. By warranting a patient’s personal experience, the project is incorporating

the pattern of personal knowledge.


Carpers ethical pattern of knowing focuses on morality, obligation, and doing what is

best for the patient regardless of the provider’s personal beliefs (Carper, 1978). This project

eliminated all patient identifiers to ensure that the confidentiality of all patients was maintained.

Additionally, the project was a retrospective review so participants were not engaged or subject

to coercion. The purpose of this project was to highlight negative and positive findings within

the healthcare model. This ties into Carper’s ethical pattern of knowing as it focuses on ensuring

that the best level of care is rendered.

The final pattern of knowing is the esthetic pattern or the “art of nursing.” This pattern

can be difficult to define as the concept of art cannot be summarized in a few words (Carper,

1978). This doctoral project ties into the art of nursing by looking beyond the scientific results

that were yielded from this project. For example, the overall aim of this project was to improve

the quality of care provided within a clinic. The scientific results will not improve the care

rendered, rather, it will initiate follow-up interventions that will be address the experience of the

patients. The interventions that will be developed incorporate the art of nursing in that they will

not be solely scientific or rigid.

Background

Patient satisfaction is a standard of care within the medical field. This can be partially

credited to the mandates and evolution of patient satisfaction surveys set forth by the CMS.

Dating back to 2002, the CMS partnered with the Agency for Healthcare Research and Quality

(AHRQ) to develop the first national, standardized patient satisfaction survey called Hospital

Consumer Assessment of Healthcare Providers and Systems (HCAHPS). After rigorous testing,

the survey was first available for public use in October of 2006. To encourage participation, the

Deficit Reduction Act of 2005 created financial incentives for acute care hospitals who


participated in the HCAHPS. Hospitals who received the Inpatient Prospective Payment System

provisions were made to participate in the HCAHPS in order to receive full annual payments.

Lastly, in 2010, the Patient Protection and Affordable Care Act of 2010 indicated that HCAHPS

results would be used to determine value-based incentive payments for those participants in the

Hospital Value Based Purchasing program (CMS, 2018a).

Since the implementation of patient satisfaction surveys, research has been conducted to

determine how satisfaction impacts the care that is rendered. Research has found that several

outcomes from eliciting patients’ feedback of their healthcare experience have been identified.

These include improved patient and provider communication, improved patient outcomes

through prevention of complications and mortality, and increased revenue from CMS

reimbursement and incentives (Bogner et al., 2016; CMS, 2018a; Farrington et al., 2016;

Overveld et al., 2017). Additionally, research has found that patient satisfaction surveys serve as

evidence to support change in the management and delivery of healthcare services for patients

(CMS, 2018a; CMS, 2018b; Farrington et al., 2016).

Significance

Nursing. Nurses are the primary caregivers in all settings of healthcare. Therefore,

nurses have a significant impact on a patient’s experience. Not only do nurses directly impact

patient satisfaction through their intimate contact with patients, but factors such as their work

environment have also proven to impact patient satisfaction. Research has shown that higher

patient satisfaction scores aligned with better working environments (Berkowitz, 2016). Patient

satisfaction surveys have significance within the nursing field as surveys can potentially

highlight areas of concern within nursing environments.


Healthcare. The CMS has three main goals for their patient satisfaction surveys. They

are to provide data to aid consumers in their ability to make meaningful, objective comparisons

of healthcare delivery systems, to improve quality of care through encouraging hospitals to

publicly report findings, and increasing organizational transparency of the quality of care that is

delivered through public reporting (CMS, 2018a). Patient satisfaction surveys are becoming a

mandatory component of healthcare through these goals set forth by the CMS. Overall, patient

satisfaction surveys are shifting healthcare from a quantity approach to the overarching goal of a

value-based delivery system (CMS, 2018b).

Advanced Practice Nursing. Patient satisfaction surveys are intended to aid consumers,

encourage organizational transparency, and improve quality of care. Surveys provide a platform

for patients to express their perceptions and experiences. As primary care providers, advanced

practice nurses (APNs) are on the frontline of patient care and are a vital component of the

patient’s healthcare experience in all settings. APNs have the opportunity to directly impact

patient satisfaction through frequent patient communication and interaction. Working to foster

positive change that translates into positive outcomes for patients is a component of the APNs’

scope of practice (American Association of Colleges of Nursing, 2006; Gerrish et al., 2011).

Knowledge gained from this scholarly project will be translated into practice to improve and

provide quality care to the patients at the project’s clinic.

Support for Project

The DPC clinic that was used for this DNP project vowed support for this project by

providing a written letter of approval to conduct a retrospective chart review of patient

satisfaction surveys. The clinic’s founder previously had requested that this student create and

implement a process for evaluating patient satisfaction. As requested, a pilot patient satisfaction


survey was created and implemented into the practice for approximately three months. Prior to

this project, no formal process to measure patients’ satisfaction scores and patient experience

existed. The clinic’s founder supported this student in analyzing the results of the patient

satisfaction surveys that were collected during the pilot program. Once approval was granted by

Maryville University’s Institutional Review Board (IRB), a retrospective review of the patient

satisfaction surveys was conducted.

Benefit of Project to Practice

To advance and highlight the positive attributes of the DPC model, the clinic’s founder

asked this DNP student to create and implement a process for evaluating patient satisfaction.

Since the DPC model is a relatively new form of delivering healthcare, data regarding patient

experience and patient satisfaction is limited. Implementing and evaluating a patient satisfaction

survey will advance the body of supportive literature for the DPC model. Additionally, results of

the survey highlighted areas of improvement for this specific DPC clinic. From this information,

appropriate follow-up interventions will be formulated to improve the quality of care provided

within this clinic.

Conclusion

Patient satisfaction is becoming a crucial component of healthcare delivery systems as the

shift from quantity-based care to quality-based care occurs. This DNP project has contributed to

this shift through the retrospective review of patient satisfaction surveys that were collected in a

DPC clinic. The results of the review will used to develop interventions that can improve the

quality of care that is rendered. Prior to this project, the DPC clinic did not have any formal

method of measuring patient satisfaction. The clinic requested that this project be performed to

expose strengths and weaknesses of the care rendered. In addition to improving care, this project


has the ability to highlight positive attributes of the DPC model while simultaneously

contributing to the limited body of literature. Maryville University’s DNP program has prepared

this author to perform and implement an evidence-based research project.

Chapter II: Review of Related Literature

Critical Analysis of Conceptual and Theoretical Literature

Patient satisfaction is commonly used as an indicator to evaluate the successes and

shortcomings of healthcare delivery systems (Al-Abri & Al-Balushi, 2014). Historically, patient

satisfaction surveys have been used to measure patients’ perspective of the healthcare they

received. The CMS has defined essential goals for such satisfaction tools (CMS, 2018a; CMS,

2018b). Several outcomes from eliciting patients’ feedback of their healthcare experience have

been identified such as improved patient and provider communication, improved patient

outcomes through prevention of complications and mortality, and increased revenue from CMS

reimbursement and incentives (Bogner et al., 2016; CMS, 2018a; Farrington et al., 2016;

Overveld et al., 2017). Patient satisfaction surveys serve as evidence to support change in the

management and delivery of healthcare services for patients (CMS, 2018a; CMS, 2018b;

Farrington et al., 2016).

Patients’ experiences include aspects of care such as improved patient and provider

communication (CMS, 2018b). A patient’s perspective of being heard is rated as one of the

strongest drivers of patient satisfaction (Al-Abri & Al-Balushi, 2014). Patient feedback

facilitates providers to listen to the concerns of patients (Farrington et al., 2016; Overveld et al.,

2017). Through participation in surveys, patients can engage in reflection, criticism, and

therapeutic communication on topics that may have been less than adequate (Al-Abri & Al-

Balushi, 2014; Farrington et al., 2016).


In addition to improved communication, patient satisfaction can also improve the quality

of care that is rendered. This concept is illustrated by Bogner et al. (2016). Bogner et al. (2016)

performed a quantitative study using a multinomial logistic regression model to assess the

relationship between perceived patient satisfaction and functional decline, institutionalization,

and death. Interviews from 23,470 Medicare beneficiaries 65 years of age or older were

reviewed to establish baseline data. Two years after the survey, the researchers categorized

participants’ functional status and assessed for institutionalization and death. The participants in

the top quartile of patient satisfaction (those with the highest patient satisfaction scores) were

less likely to be institutionalized compared to those in the lower three quartiles “(adjusted RRR =

0.68, 95% CI: 0.54-0.86)” (Bogner et al., 2016, p. 11). Additionally, the participants in the top

quartile were less likely to be functionally declined “(adjusted RRR = 0.87, 95% CI: 0.79-0.97)”

(Bogner et al., 2016, p. 11) or dead “(adjusted RRR = 0.86, 95% CI: 0.75-0.98)” (Bogner et al.,

2016, p. 11). In conclusion, the researchers found that higher perceptions of satisfaction with

access to medical care and care coordination were associated with a lower risk of decline if

functionality, death, and institutionalization (Bogner et al., 2016).

Additional literature that supports the theme that there is a relationship between patient

satisfaction and the quality of care that is provided is the work performed by Boiko et al. (2014).

Boiko et al. (2014) performed a qualitative study using 14 different focus groups. The

researchers mailed surveys to patients who recently saw a provider. Once responses were

received, focus groups were created with a variety of staff members to include nurses, providers,

and front-line staff. The researchers held discussions that were aimed to uncover attitudes

toward patient surveys to include past experience with surveys and how survey results are

generally handled. Results indicated that most staff members valued the patient satisfaction


surveys that allowed for feedback regarding their performance and areas of improvement. Boiko

et al. (2014) found that feedback surveys were the first crucial step to making changes within

general practice and gauging the performance of providers.

The work by Farrington, Burt, Boiko, Campbell, and Roland (2016) also supports the

relationship between patient satisfaction and the quality of care that is rendered. Farrington et al.

(2016) performed a qualitative study to explore the perceptions physicians have regarding patient

experience surveys. Forty-one participants from both inpatient and outpatient settings were

utilized for face-to-face semi-structured interviews. The participants were selected as they

recently had received individual feedback from patient satisfaction surveys regarding visits they

had with patients. Farrington et al. (2016) found that physicians from both settings expressed

concerns about the credibility of patient surveys. Regardless of plausibility concerns,

participants articulated strong commitments to utilizing patient feedback for quality

improvement efforts. The researchers concluded that physicians’ views should be considered

with developing quality improvement initiatives in response to patient feedback (Farrington et

al., 2016).

Another incentive for healthcare agencies to administer patient satisfaction surveys is the

financial reward associated with reporting survey results (CMS, 2018a). In addition to

promoting the improvement of quality of care with financial incentives, one could expect the

opposite results if financial incentives were removed or not present. Minchin, Roland,

Richardson, Rowark, and Guthrie (2018) performed a retrospective review of United Kingdom

medical records from 2010 to 2017 to assess for the presence of 12 quality-of-care indicators. In

2014, half of the quality-of-care indicators were no longer associated with financial incentives.

Minchin et al. aimed to assess if removal of the financial incentives for the removed six quality-


of-care indicators decreased the presence of these indicators within medical records. Minchin et

al. examined data from 2,819 English practices and found that the presence of four of the 12

quality-of-care indicators within medical charts was improving prior to the removal of

incentives. Additionally, Minchin et al. (2018) found that there were significant reductions in

the documentation of quality-of-care indicators within one year after the removal of half of the

quality-of-care indicators. Contrarily, after three years, there were no changes in documentation

of the quality-of-care indicators that were still subject to financial incentive. Minchin et al.

(2018) summarized that the decline could be simply due to decreased documentation, however,

the decline of documented items such as laboratory testing is suggestive of changes in the

delivery of care.

Studies have also found that financial and reputational awards can improve performance

practice. Allen, Whittaker, Kontopantelis, and Sutton (2018) performed an observational study

aimed to quantify this notion. The researchers wanted to determine the effects financial and

reputational rewards had on performance status of general practices which were part of a pay-

for-performance program. Through examining data from nine years, the researchers found that

financial and reputational awards were statistically significant indicators of practice performance

within general practices enrolled in the United Kingdom’s (UK) pay-for-performance program.

Additionally, the researchers found that over time, financial rewards became less significant

while reputational rewards became more important. The results of this study highlight that

incentives, whether financial or reputational, can impact the performance of healthcare practice.

Allen et al. (2018) concluded that general practices in the UK might have shifted their efforts

from generating revenue after they achieved their baseline benchmarks to increasing their

reputation.


Wolk et al. (2013) performed a six-month study to evaluate the effects of implementing a

financial incentive for medical residents who have the lowest average time in dictating discharge

notes. The researchers had four research groups; at the end of a monthlong rotation, the medical

resident who had the lowest discharge-to-dictation time was awarded a monetary reward. In

addition to monetary rewards, other interventions such as verbal reminders and a discharge

orientation were performed. At the end of the study, the researchers found that the average

discharge-to-dictation time was 1.84 days with approximately 90% of dictations occurring during

the same day of discharge. The average amount of time for dictating discharge notes for medical

residents was 7.44 days prior to this study. Wolk et al. (2013) concluded that a modest financial

incentive resulted in a significant reduction in the average discharge-to-dictation time. This

study highlights the relationship between financial incentives and improved quality of care.

Overall Gaps, Limitations, Strengths, and Weaknesses

In general, the body of evidence supports that patient satisfaction can impact the quality

of care that is rendered and financial incentives are associated with performance. Soliciting

patient feedback, regardless of the method, can ultimately improve the quality of care that is

rendered. Overall strengths of the aforementioned literature include the design and analysis

methods. Bogner et al. (2016) performed a retrospective review of data using a multinomial

logistic regression model. This method of analysis was appropriate to examine the association

between numerous independent variables and dependent variables (Polit & Beck, 2017). Bogner

et al. (2016) adequately described the sampling strategies and provided detailed characteristics of

participants.

The qualitative works by Boiko et al. and Farrington et al. provide strength to the

available patient satisfaction literature in that the perspective of providers and practice staff were


considered. One weakness of the study by Boiko et al. is the vague explanation of the data

collection and data analysis processes. According to Polit and Beck (2017), qualitative studies

are difficult to describe and explain. In contrast, Farrington et al. thoroughly explained how their

sample was obtained and attempted to eliminate bias by randomly selecting physicians from

practice settings.

A strength of Minchin et al.’s (2018) study was the use of longitudinal data and a time

series analysis. The use of longitudinal data is appropriate if researchers need to assess changes

over time (Polit & Beck, 2017) which aligns with Minchin et al.’s aim to determine if the

removal of financial incentives decreased the presence of quality-of-care indicators.

Additionally, time series designs are ideal if a control group is present, but randomization is

lacking (Polit & Beck, 2017). Polit and Beck (2017) noted that time series designs allow for data

to be collected over an extended timeframe during which some form of intervention is

introduced. In this case, the researchers examined available data prior to and after the removal of

financial incentives which aligns with the time series design. Minchin et al. (2018) provided

95% confidence intervals to describe the significance of their findings. All in all, the researchers

provided adequate detail to describe their study design, data collection, sample, and data analysis

processes.

A significant strength of the research presented by Allen et al. (2018) is the level of detail

they provided when describing their methods and data collection process. However, the

researchers vaguely described their exclusion criteria. To strengthen the understanding and

findings of their research, the researchers should aim to provide a detailed list of inclusion and

exclusion criteria that were used to determine which practices would be included in the sample.


The findings of this survey provided literature regarding performance and reputational rewards

which are not well studied.

The research presented by Wolk et al. (2013) is a study that highlights how financial

incentives impact performance in healthcare. Unfortunately, the researchers failed to illustrate

how data analysis was performed. Although the results of the study show a significant decrease

in the discharge-to-dictation time, there are no statistics to support that the findings were

statistically significant. The lack of statistical analysis is a weakness of this research. A strength

of the study its readability, simplicity, and replicability. Additionally, the findings highlight how

simple monetary incentives can significantly impact performance.

Concepts and Definitions

Numerous concepts and definitions have been used throughout this project to depict the

importance of soliciting patient feedback through means of surveying. Patient satisfaction can be

defined as the degree of which a patient’s expectations were met (Agency for Healthcare

Research and Quality, 2017b). Patient satisfaction is also a performance measure for evaluating

the healthcare quality (New England Journal of Medicine Catalyst, 2018). Similar to patient

satisfaction is the concept of patient experience. In regards to healthcare, many components of

healthcare delivery can encompass patient experience. This may be clear communication with

healthcare staff and the amount of respect and responsiveness a patient receives (AHRQ, 2017b).

Many different methods of soliciting patient satisfaction and experience exist including

surveys. A survey can be defined as a method for gathering information from a sample of people

(Qualtrics, 2018). Patient satisfaction surveys are commonly used as a measuring device for

patient satisfaction as satisfaction is not something that can be directly observed. Satisfaction


surveys attempted to translate subjective data regarding satisfaction and experience into

measurable, quantifiable data (NEJM Catalyst, 2018).

Many different patient satisfaction surveys exist, but the most commonly known surveys

are from the CMS. The CMS is a division of the Department of Health and Human Services who

oversees numerous federal healthcare programs aimed at eliminating health disparities and

achieving the highest level of care for all (CMS, 2018b). The CMS has developed surveys, in

conjunction with the AHRQ, to include the survey used for this project, the Visit Survey 2.0.

The Visit Survey 2.0 is a publicly available survey that elicits patient feedback (AHRQ, 2017a).

Another commonly used term throughout this project is direct primary care. Direct

primary care is an alternative healthcare payment model where patients pay a membership either

monthly, quarterly, or annually for service; insurance is not billed. Benefits of this type of

practice include reduced patient volume, increase visit time with patients and fewer medical

errors (American Academy of Family Physicians, 2019).

Theoretical Framework

Maslow’s Theory of Needs is applicable to the concept of patient satisfaction and

experience and the effect these notions have on quality of care. This theory was developed in

1943 by Abraham Maslow and is a pyramid model depicting five levels of needs. Maslow’s

theory is that one must accomplish each level of need before proceeding to the next. Maslow

theorized is that one person cannot feel the achievement of higher levels until the current level

has been satisfied. The levels of need are the following in level of priority: physiological, safety,

love/belonging, esteem, and self-actualization (Maslow, 1943). The concept of patient

satisfaction is simply to meet one’s expectation and needs. If a patient’s needs, regardless of the


level, are not met, they are going to display dissatisfaction and potentially have poorer health

outcomes.

The first level, physiological needs, applies to this project. Maslow (1943) stated that

above anything else, human beings would be motivated by physiological needs. In regards to

patient satisfaction, if patients are not having their healthcare needs met, which can be

considered a physiological need, it is inferred that they would be unsatisfied with their care and

have poorer health outcomes. If satisfied, one would progress to the second level, safety

(Maslow, 1943). Within healthcare, if patients do not trust their healthcare provider's judgement

and plan of care, they will not be satisfied with the care they receive.

The next level, love/belonging, can be described as the need to give and receive affection

or belongingness. In regards to healthcare, the patient and provider engage in a health focused

relationship. If patients do not feel a sense of belongingness or affection from their healthcare

provider, their healthcare needs may not be met, and they may be dissatisfied with their care.

The fourth level, esteem, was described by Maslow (1943) as the need to have self-esteem or

have esteem from others. Maslow (1943) noted that a lack of esteem could lead to feelings of

helplessness or inferiority. If patients’ esteem is altered due to their health or healthcare

experience, their satisfaction will be impaired. The final stage, self-actualization, will be

fulfilled when people are functioning in a capacity in which they are fit (Maslow, 1943). It is

concluded that a patient’s final level of self-actualization will be supported by ensuring to meet

all four prior levels of need.

Chapter III: Methods

Methodology & Design

Direct primary care is an innovated, alternative payment model for accessing healthcare.


Members of the DPC clinic pay an affordable monthly fee to gain access to a primary care

practice in which there is no third party, insurance, or fee for service billing. This innovative

model provides a unique setting for both patients and providers (American Academy of Family

Physicians, 2019). According to Moran, Burson, and Conrad (2014), non-experimental designs

are valuable in assessing characteristics and needs of a distinct population. Therefore, an

exploratory, quantitative design was used to evaluate patient satisfaction in a DPC clinic. A

retrospective review of patient satisfaction surveys that were implemented in the clinic was

performed (see Appendix A). Questions that directly correlate to patient satisfaction were

converted to nominal data and were reviewed and analyzed using descriptive statistics (Moran,

Burson & Conrad, 2014).

This DNP project took place in a small DPC clinic located in the Southeast region of the

United States. A retrospective review of patient satisfaction surveys was performed after gaining

approval from Maryville University’s IRB. Twenty-five patient satisfaction surveys met

inclusion criteria. The age of the participants were 18 years or older, all genders were included

and comprised of approximately 25% Caucasian, 25% African American, and 50% other ethnic

groups.

Inclusion criteria for the results of selected questions pertaining to patients’ satisfaction

of their healthcare experience were the following: (a) 18 years of age or older; (b) seen at the

clinic from July 9, 2018 through September 9, 2018; and (c) providing a response to questions

five: “In the last 12 months, when you phoned Your Family MD’s office to get an appointment

for care you needed right away, how often did you get an appointment as soon as you needed?”;

seven: “In the last 12 months, when you made an appointment for a check-up or routine care,

how often did you get an appointment as soon as you needed?”; nine “In the last 12 months,


when you phoned Your Family MD’s office during regular office hours, how often did you get an

answer to your medical question that same day?”; 11: “In the last 12 months, when you phoned

Your Family MD’s office after regular office hours, how often did you get an answer to your

medical question as soon as you needed?”; 14: “Wait time includes time spent in the waiting

room and exam room. During your most recent visit, did you see your provider within 15

minutes of your appointment time?”; 15: “During your most recent visit, did the provider listen

carefully to you?”; 16: “During your most recent visit, did the provider explain things in a way

that was easy to understand?”; 17: “During your most recent visit, did you talk with provider

about any health questions or concerns?”; 18: “During your most recent visit, did your provider

give you easy to understand information about these health questions or concerns?”; 19:

“During your most recent visit, did the provider seem to know the important information about

your medical history?”; 20: “During your most recent visit, did the provider show respect for

what you had to say?”; 21: “During your most recent visit, did the provider spend enough time

with you?”; and 24: “Using any number from 0 to 10, where 0 is the worst provider possible and

10 is the best provider possible, what number would you use to rate Your Family MD?”.

The exclusion of the participant’s answers was carefully examined in the following

order: (a) if the participant is not 18 years of age or older, data was not extracted; (b) if services

were initiated at the clinic before July 9, 2018 or after September 9, 2018, no data was not

extracted; and (c) no data was extracted if no response was provided for questions five: “In the

last 12 months, when you phoned Your Family MD’s office to get an appointment for care you

needed right away, how often did you get an appointment as soon as you needed?”; seven: “In

the last 12 months, when you made an appointment for a check-up or routine care, how often did

you get an appointment as soon as you needed?”; nine “In the last 12 months, when you phoned


Your Family MD’s office during regular office hours, how often did you get an answer to your

medical question that same day?”; 11: “In the last 12 months, when you phoned Your Family

MD’s office after regular office hours, how often did you get an answer to your medical question

as soon as you needed?”; 14: “Wait time includes time spent in the waiting room and exam

room. During your most recent visit, did you see your provider within 15 minutes of your

appointment time?”; 15: “During your most recent visit, did the provider listen carefully to

you?”; 16: “During your most recent visit, did the provider explain things in a way that was easy

to understand?”; 17: “During your most recent visit, did you talk with provider about any health

questions or concerns?”; 18: “During your most recent visit, did your provider give you easy to

understand information about these health questions or concerns?”; 19: “During your most

recent visit, did the provider seem to know the important information about your medical

history?”; 20: “During your most recent visit, did the provider show respect for what you had to

say?”; 21: “During your most recent visit, did the provider spend enough time with you?”; and

24: “Using any number from 0 to 10, where 0 is the worst provider possible and 10 is the best

provider possible, what number would you use to rate Your Family MD?”.

Needs Assessment

The DPC model for accessing healthcare is still a novel concept but is gradually

expanding across the United States. In 2015, it was estimated that the model existed in 39 states

(Eskew & Klink, 2015), whereas now, it is estimated that there are roughly 950 DPC clinics

throughout 48 states (DPC Frontier, 2018). Eskew and Klink (2015) noted that 93.2% of the

practices identified in 2015 consisted of less than or equal to only four providers in the practice.

Therefore, most DPC practices are “young and small thus lack sufficient quality and cost data to

assess outcomes” (Eskew & Klink, 2015, p. 795). Eskew and Klink (2015) noted that future


studies regarding the DPC model should include evaluating the claims that quality of care is

improved with this model. If the DPC model is to continue to grow and be widely adopted, more

literature is needed to document potential improvements (Eskew & Klink, 2015).

The DPC clinic that was used for this DNP project is a small practice located in the

Southeast region of the United States consisting of one provider. To advance and highlight the

positive attributes of the DPC model, the clinic’s founder asked this DNP student to create and

implement a process for evaluating patient satisfaction. Prior to this project, no formal process

to measure patients’ satisfaction scores or patient experience existed. The author of this project

was asked by the clinic’s founder to collaborate with providers and supportive personnel to

develop, implement, and evaluate a patient satisfaction survey.

Furthermore, the clinic’s founder wanted to implement a process that would align with

the guidelines set from the CMS. In 2010, the Affordable Care Act established the Hospital

Value-Based Purchasing Program. This program is a CMS initiative that rewards hospitals for

providing high quality care to Medicare patients (CMS, 2012). Although not an acute care

facility, the DPC clinic wanted to meet the expectations of the CMS by providing quality

healthcare. A CMS based patient satisfaction survey was implemented to demonstrate that

quality healthcare is delivered within the DPC model. Additionally, the clinic’s founder hoped

to identify any areas of improvement to which follow up interventions would be developed to

ensure the highest level of care is being rendered.

Data Collection Instrument

Initially, the author of this project was asked by the clinic’s founder to develop a patient

satisfaction survey that would meet the requirements of the CMS. The patient satisfaction

survey that was chosen is a modified version of the Visit Survey 2.0 developed by the Consumer


Assessment of Healthcare Partners and Systems (CAHPS) (AHRQ, 2017a). The Visit Survey

2.0 is publicly available through the AHRQ and complies with the CMS guidelines. The AHRQ

provides access to the CAHPS surveys and tools for public use at no cost.

The Visit Survey 2.0 was developed to elicit patient feedback over a specific visit as

opposed to over a period of time. Visit specific surveys can elucidate quality information for

improvement (AHRQ, 2017a). The patient satisfaction survey was developed within Survey

Monkey® due to ease of dissemination. Once the clinic’s founder approved the content,

implementation was underway.

Specific Steps

After creating the patient satisfaction survey, the clinic disseminated surveys to all adult

patients actively enrolled in the DPC clinic who had a linked email. The patient satisfaction

survey was piloted at the clinic from July 9, 2018 through September 9, 2018. Emails with a link

to the patient satisfaction survey were sent to participants by supportive personnel on July 21st,

2018, August 15th, 2018, and September 4th, 2018. The emails encouraged participation in

completing the patient satisfaction survey. The patient satisfaction survey was to be a review of

the patient’s last visit in the DPC clinic.

After IRB approval was been obtained from Maryville University, the data collection

process began. The clinic’s founder provided the researcher with a copy of the results of the

selected questions pertaining to patient satisfaction of the surveys that were completed between

July 9, 2018 through September 9, 2018. The clinic’s founder removed demographic information

and other potential identifiers of the participants prior to providing the researcher with the results

of the selected questions. The abstracted data constituted the minimum necessary data to

accomplish the goals of the project.


The researcher sequentially reviewed the results of the selected questions to determine if

the inclusion criteria had been met. A sequential inclusion and exclusion process continued until

the written list provided by the clinic’s founder had been reviewed. Data collection stopped after

the results of the selected questions pertaining to patient satisfaction provided by the clinic’s

founder that met the inclusion criteria had been identified and recorded on the data collection

form.

A data collection document was created specifically for this project within Microsoft

Word®. Each patient satisfaction survey was assigned a numerical number on the data

collection form. Each specific question response was given a correlated numerical number. For

example, 1=never; 2=sometimes; 3=usually; and 4=always (see Appendix B).

After the data collection process was completed, the copy of the results of the selected

questions were returned to the clinic’s founder which will be destroyed after three years. After

the data was collected, Microsoft Excel® was used for data analysis.

Analysis Plan

To describe and provide understanding of the data, descriptive analysis occurred.

Categorical, nominal data were collected in Microsoft Word® for data collection which was then

converted into Microsoft Excel®. After conversion, the data was descriptively analyzed using

Microsoft Excel®.

Descriptive statistics allow researchers to describe or summarize their data. In addition,

descriptive statistics assists researchers in presenting their data in a meaningful way especially

for large amounts of data (Lund Research Ltd, 2018). For this project, numerous responses were

present which contributed to a large data set. Therefore, mode and average were used to

summarize the survey responses per each target variable.


Resources and Budget

An array of resources were needed to complete this project. First, a subscription to

Microsoft Excel® software was required for data analysis. It costs approximately $70 to procure

a yearly subscription for Microsoft Office® (Microsoft, 2019). Additionally, printing materials

such as paper and toner were needed throughout this entire project. It is estimated that one toner

and one ream of paper were used which cost approximately $105.

Other resources that were needed include electricity and internet usage. It is estimated

that electricity requirements costed approximately $142 based on local rates and 160 hours of

usage (Electricity Local, 2018). Internet usage was estimated to cost approximately $50 due to

average monthly internet costs (BroadBandNow, 2018). Lastly, resources included the time it

took the physician to remove all the patient identifiers and traveling via car to and from the DPC

to complete the project. At a rate of $75 per hour, $150 was needed for a physician fee to

download patient satisfaction surveys and remove all identifiers. Traveling fees were estimated

at $308 based on $0.55/mile (Internal Revenue Service, 2018). An estimated budget of $825 was

needed to complete this project.

Timeline

The timeline for this project was approximately nine months. One month was dedicated

to creating the patient satisfaction survey. The next four months were dedicated to composing

and submitting the IRB proposal. The last four months of the project involved data collection

and analysis as well as compiling the full project into this final report. The data collection took

approximately one month, while analysis and the compilation of the final report both took an

additional one-and-a-half months.


Protection of Human Subjects

There were no foreseen physical, psychological, social, economic, or legal risks that

resulted from this project. One possible risk was a potential breach of confidentiality. However,

this risk was minimal as the patient satisfaction surveys returned to the clinic are anonymous per

the protocol set forth by CMS. In addition, the clinic’s founder provided the researcher with a

copy of the results of only the selected questions pertaining to patient satisfaction. The clinic’s

founder removed demographic information and other potential identifiers of the participants

prior to providing the researcher with the results of the selected questions. The abstracted data

constituted the minimum necessary data to accomplish the goals of this project.

The data collected on a data collection sheet was stored on a password protected

computer located in the researcher’s locked office. The author of the project was the only person

with access to the password and office. To minimize the risk of breach of confidentiality related

to the list provided by the clinic’s founder, the researcher returned the list to the clinic’s founder

who destroyed the list. The author will destroy the data collected from this project after three

years.

This was a quality improvement project with confidentiality protections in place. There

were no direct benefits to the participants as this was a retrospective review. The results of this

project could potentially benefit future patients at the clinic. The overall aim was to improve the

care provided by the clinic, as well as comply with regulations set forth by CMS to evaluate

patients’ satisfaction of their healthcare experience at the clinic. The results of the retrospective

review provided information on the quality of care provided by the clinic in order to develop and

implement interventions to improve and deliver high quality care and improve patient outcomes.


The burden of the potential breach of confidentiality of the participants was minimal and

did not exceed the benefit of knowledge gained regarding the patients’ perception of their

healthcare service at the clinic. The benefits outweigh the risk associated with this research.

The results of this project were printed in a doctoral project and shared with the

researcher’s Maryville University faculty chair and community members. The results may also

be shared at a poster session at a medical conference or submitted for publication in a reputable

journal. The data was shared with the other healthcare providers and founder of the clinic. All

information was presented without identifiers and in aggregate form.

Chapter IV: Findings

Congruency of the Data Collection Method and Target Variables

This quantitative retrospective review of surveys was performed in the intended DPC

setting and population in the Southeast region of the United States. The data collection process

involved retrieving responses to selected questions aimed at measuring the target variables. The

data collection methods were designed to specifically measure the target variables prior to

conducting the review of surveys. The data collected measured the intended variables that

highlighted patients’ experiences. Implementing a web-based survey and performing a

retrospective review of surveys was the most appropriate method for this study due to potential

bias and confidentiality risks associated with an in-person.

Congruency is also present within the data analysis methods. Due to a small sample size,

descriptive statistics were used to evaluate the survey responses. The data analysis plan was in

congruence with the study’s purpose statement and IRB proposal, as the descriptive statistics met

the project goal of evaluating patient satisfaction surveys for strengths, weaknesses, and

associations related to the perception of the patients who received care at the clinic.


The purpose of this DNP project was to evaluate patient satisfaction surveys within a

DPC clinic to unveil patients’ perceptions of the care they received. The proposed target

variables were accessibility to care, wait time, perceived responsiveness from provider,

comprehension of provided information, opportunity to express concerns, confidence in

provider's knowledge, perceived respect from provider, adequate visit time, and overall

impression of provider. These variables were created based on specific questions from the

patient satisfaction survey that aligned with patient experience. Therefore, there is congruency

within the project’s purpose and the intended areas of measurement.

Study Replication

This DNP project involved implementing a patient satisfaction survey and then

performing a retrospective review of the surveys. This study could be replicated by following

the proposed methodology within the IRB proposal. Depending on the yielded sample size,

descriptive statistics could then be utilized to analyze the data collected in the chart review.

Additionally, if two target variables were identified, chi-square testing could be done to evaluate

the relationship. For example, if patients reported dissatisfaction with the care they received at

the clinic, and it was hypothesized this was due to high wait times, chi-square testing could be

performed to assess the strength of association between these two variables. The results from

this study as well as a replicated study can underscore the positive attributes of the DPC

healthcare model as well as identify areas of improvement.

Validity and Reliability

The data collection tool for this DNP project, the Visit Survey 2.0, was valid and reliable.

Polit & Beck (2017) noted that face validity refers to when the instrument appears to measure the

intended targets. The Visit Survey 2.0 has face validity as the tool measures specific patient


experience variables. Each variable has corresponding questions within the patient experience

survey. Face validity is present as the correlating questions appear to be specifically related to

the corresponding quality measures.

Additionally, the tool has content validity. To ensure content validity, Polit and Beck

(2017) noted that three core components, relevance, comprehensiveness, and balance are

necessary for content validation. When designing the Visit Survey 2.0, the AHRQ warranted

feedback from numerous groups including stakeholders, accrediting bodies, and consumers to

ensure the tool was valid. According to the AHRQ (2016), major steps were taken to ensure

soundness including performing literature reviews, focus groups, and field testing. Lastly, the

Visit Survey 2.0 has construct validity as CAHPS surveys are used as the gold standard for

measuring patient experience (Ginsberg, n.d.).

Polit and Beck (2017) defined reliability as something being consistent, stable, and

replicable. The Visit Survey 2.0 is a CAHPS survey. CAHPS surveys are consistent tools that

are used across a broad spectrum of healthcare delivery systems due to their reliability. For

example, the surveys are used by the CMS to determine compensation while the National

Committee for Quality Assurance uses the surveys for performance evaluation. Additionally, the

Veterans Health Administration and the Department of Defense utilize the Visit Survey 2.0 to

assess patient experience within military and contracted healthcare settings (Agency for

Healthcare Research and Quality, 2016). The use of these surveys across numerous agencies

highlights the tool’s replicability and reliability.

Quality of Data

The quality of data was ensured throughout this project by ensuring the data was

collected from the intended setting and population. The projected sample size was estimated to


be 25 surveys, but only 22 surveys were completed, and only 21 surveys met the inclusion

criteria. A larger sample size would be ideal, but the DPC clinic is a small practice with limited

patients, so a larger sample size was not feasible at the time of the project.

After the IRB granted approval, data collection occurred through a retrospective review

of the patient satisfaction surveys. Each survey was compared against inclusion and exclusion

criteria and numerically transcribed into a Word© document. The data was collected

consistently and was completed within two weeks of obtaining IRB approval. The quality of

data has been maintained throughout this project by ensuring the intended population and sample

size were abided by as strictly as possible, and by ensuring the data collection process was

consistent and timely.

Critique of Quality of Data

The purpose of this project was to analyze patient satisfaction surveys. Questions that

were directly correlated to patient satisfaction were extracted from the surveys and transcribed

into a Word© document during the data collection process. The intended concept of patient

satisfaction was measured by carefully extracting appropriate questions that matched the target

variables.

To evaluate the intended concept of patient satisfaction, electronic patient satisfaction

surveys were utilized. Utilizing a patient satisfaction survey was an ideal method of data

collection as self-reports, or patient-reported outcomes, are a versatile and efficient means of

gathering data. Self-reports can help capture outcomes and personal opinions that may not

otherwise be known (Polit & Beck, 2017).

The patient satisfaction survey was used as a data collection tool. The Visit Survey 2.0 is

a vetted, valid, and publicly available survey that complies with the CMS guidelines. The Visit


Survey 2.0 was developed to elicit patient feedback over a specific visit as opposed to over a

period of time (AHRQ, 2017a).

Descriptive Statistics

Specific demographics including age, gender, and race were eliminated from the patient

satisfaction surveys to reduce potential breaches of confidentiality. However, participants of the

patient satisfaction survey had to be over the age of 18 in order to receive the survey. Nine

different target variables were identified within the survey. Descriptive statistics were used to

analyze the corresponding questions to these target variables. Below, these results will be

discussed.

Results

The first target variable was accessibility to care. The results to questions five, seven,

nine, and 11 were assessed to identify this target variable. Eighty-four responses were included

in the descriptive analysis of this target variable. On average, participants answered that they

usually had access to care. The mode of the responses was always. The standard deviation of

these findings was 0.9.

The second target variable was wait time. The results of question 14 were utilized to

assess this target variable. Twenty-one responses were included in the descriptive analysis of

this variable. Twenty participants indicated that they were seen by their provider within 15

minutes of their scheduled appointment time. The standard deviation of these finding was 0.2.

The third target variable was perceived responsiveness from provider. The results from

question 15 were utilized to assess this target variable. All participants answered that their

provider, yes, definitely, listened to them carefully during their visit. The standard deviation of

these findings was zero.


The fourth target variable was comprehension of provided information. The results from

questions 16 and 18 were utilized to assess this variable. Forty-two responses were included in

the descriptive analysis of this variable. The average response to questions that correlated to the

patient’s comprehension of provided information answered yes, definitely when asked if their

provider explain things in a way that was easily understood. The standard deviation of these

findings was 0.1.

The fifth target variable was opportunity to express concern. Question 17 was utilized to

assess the results of this variable. Twenty-one responses were available for descriptive analysis

of this variable. On average, participants answered yes in regards to the opportunity to address

questions and concerns during their visit. The standard deviation of these findings was 0.4.

The sixth target variable was confidence in the provider’s knowledge. Responses to

question 19 were utilized to assess this variable. All participants reported yes, definitely when

asked if they felt as though their provider knew important information regarding their medical

history. The standard deviation of these findings was zero.

The seventh target variable was perceived respect from the provider. Responses to

question 20 were utilized to assess this variable. All participants reported yes, definitely when

asked if the provider showed respect for what the participant had to say. The standard deviation

of these findings was zero.

The eighth target variable was adequate visit time. Responses to question 21 were

utilized to assess this variable. All participants reported yes, definitely when asked if the

provider spent enough time with the participants during their visit. The standard deviation of

these findings was zero.


The ninth target variable was overall impression of the provider on a Likert scale with

zero being the worst provider and 10 being the best provider. Twenty-one responses to question

24 were utilized to assess this variable. The average rating of the provider was 9.9. The

standard deviation of these findings was 0.4.

Chapter V: Discussion

Summary of Findings

Patient satisfaction is becoming a core component of healthcare delivery systems (CMS,

2017). Patient satisfaction has been found to improve communication between patients and

providers, improve health outcomes, and increase revenue (Bogner et al., 2016; CMS, 2018a;

Farrington, Burt, Boiko, Campbell, & Roland, 2016; Overveld et al., 2017). Healthcare delivery

systems must recognize that measurement of patient satisfaction is becoming a standard of

practice that benefits themselves and their patients. Additionally, measuring patient satisfaction

may very well be mandated for all areas of practice in the future. Considering this, it is

necessary for healthcare practices to ensure there are proper policies and procedures in place to

measure patient experience. One form of eliciting patient feedback is through implementation of

patient satisfaction surveys. Surveys can assess patient experience which then can elucidate

areas of improvement from which follow-up interventions can be developed. This DNP project

demonstrated the successful development and implementation of a patient satisfaction program

through means of surveying in a practice that had not otherwise examined patient experience.

Interpretation of Findings

Eliciting patient feedback through means of surveying has been found to be a useful and

versatile tool. Polit and Beck (2017) noted that self-reports allow researchers to gather data on

topics that may otherwise be difficult to measure. For example, capturing personal opinion


would be impossible without a self-report tool. The findings of this study are congruent with

Polit and Beck’s statements. The study’s patient satisfaction surveys gathered data specific to

patients' personal opinion on the care they received within the DPC clinic.

Additionally, Al-Abri and Al-Balushi (2014) noted that patient satisfaction can be used to

identify successes and inadequacies within healthcare delivery systems. The study findings are

congruent with the literature as strengths within the DPC practice were identified. Some of these

strengths were perceived responsiveness from provider, confidence in provider’s knowledge,

perceived respect from provider, and adequate visit time. Contrarily, the study highlighted

accessibility to care as a shortcoming of the DPC practice.

Analysis

Polit and Beck (2017) noted that descriptive statistics help provide an understanding of

quantitative research. In this study, descriptive statistics were utilized to provide an

understanding of the results for each of the nine target variables. This report indeed provided the

descriptive statistical findings of each target variable with sufficient detail ensuring

understanding of the results. Additionally, this report refutes the performance of other statistical

analysis such as inferential statistics through the explanation of the pilot study and by noting that

no points of comparison exist at this level of study.

Furthermore, the results of this study were consistently and clearly reported for each

target variable in this report. The results were succinctly described by using mean, mode, and

standard deviation. Also, response rates were listed with each target variable to provide further

understanding of the methodologic features of the study.

Strengths and Limitations

Strength was achieved within this study through the consistency and reliability of the data


collection and data analysis processes. The data collection for this research abided to the IRB

proposal and occurred within two weeks of being granted approval. The collected data was

extracted from patient satisfaction surveys that had all patient identifiers eliminated prior to

dissemination. This helped eliminate any potential bias or confidentiality breaches. Descriptive

statistics were utilized to analyze each target variable. The results were analyzed and reported

consistently for each variable.

The research for this study was conducted by performing a retrospective chart review of

21 patient satisfaction surveys. The surveys were obtained for a DPC clinic in the Southeast

region of the United States. Those completing the survey had to be at least 18 years old. The

retrospective chart review included all surveys that met inclusion criteria. One out of 22 surveys

did not meet inclusion criteria so the results of this survey were not included in the data

collection process. One limitation of the study was the small sample size. A larger sample size

would be ideal but was not feasible as the DPC practice has a limited number of patients.

Additionally, this was a pilot study, so a small sample size was acceptable at this stage of

research.

Another limitation of the study was the unknown level of diversity of the sample. All

potential identifiers including race and gender were eliminated from the surveys before

implementation. Lastly, potential bias could exist within the survey responses as participants

could have felt compelled to provide positive ratings of their healthcare provider. Steps were

taken to eliminate these potential biases by implementing a web-based survey versus an in-

person survey, not providing any compensation for participation, and not actively recruiting

participants.


Implications for Research and Practice

The purpose of this scholarly project was to evaluate the results of the patient satisfaction

surveys that were implemented via a pilot study within a DPC clinic. The project aimed to

determine strengths and weaknesses within the clinic from which follow-up interventions could

be derived. The project aimed to implement a process to measure patient satisfaction to comply

with healthcare standards of practice. Lastly, the project hoped to highlight the strengths and

uniqueness of the DPC healthcare model.

Indeed, this project has successfully met the aims and purpose. The study implemented a

process for measuring patient satisfaction demonstrating that other healthcare practices and

providers are also capable of implementing such a program. Additionally, the results of this

study did uncover that patients are satisfied with the care they received within the DPC

healthcare model. These findings add to the literature of the positive attributes of the DPC

model of care. The overall findings of this study have positive implications for nurse

practitioners, other healthcare providers and practices, and patients.

Nursing and Healthcare

Patient satisfaction surveys help quantify a patient’s experience with the care they

received. The potential to improve the quality of care rendered is possible by quantifying patient

satisfaction. APNs have the ability to directly influence patient satisfaction as they work closely

with patients in a variety of settings across all avenues of healthcare. It is within an APNs scope

of practice to ensure that patients receive positive health outcomes. A component of this is

eliciting patient satisfaction and implementing interventions in response to the feedback that was

produced (American Association of Colleges of Nursing, 2006; Gerrish et al., 2011). The

scholarly project demonstrates how nurse practitioners and other providers can improve the care


provided within their area of practice.

Benefit of Project to Practice

The DPC healthcare model is a relatively new way of delivering care. There is limited

literature that supports the use of such model. The results of this project add to the existing

literature that patients are satisfied with the care they receive within DPC clinics. An area of

future research could include comparing the results of this study to the satisfaction results within

a traditional healthcare model.

In addition to expanding the DPC existing body of literature, this DNP project has direct

benefit to the DPC clinic where the study took place. First, a patient satisfaction tool has been

created for the clinic’s use. Secondly, this project has developed a method for polling patient

satisfaction within the clinic which previously had no way of measuring a patient’s experience.

Lastly, since the data analysis has concluded, the clinic can utilize the results to develop

appropriate follow-up interventions that may be needed to improve patient satisfaction within the

clinic.

Recommendations

Recommendations regarding future use of this study are as follows. First, further

analysis can be performed on the current data set as only descriptive statistics have been

performed at this time. For example, chi-square testing could be utilized to assess if there is a

relationship between any of the target variables. Secondly, the DPC clinic should make

appropriate follow-up interventions in response to the data analysis. For example, for the first

target variable, accessibility to care, some patients reported something other than always having

access to care. An appropriate follow-up intervention could be to implement a call back

protocol. For instance, the clinic could mandate that every call or email be returned with 24


hours to ensure accessibility to care. Each target variable should be examined closely, and

appropriate interventions should be developed. Now, there is baseline data regarding patient

satisfaction within the DPC clinic, the survey that was developed can be utilized consistently to

track and monitor patient experience.

Conclusion

Measuring patient satisfaction is becoming a crucial component of healthcare delivery

systems. Through eliciting patient feedback, healthcare delivery systems can improve the level

of communication between patients and providers, decrease health complications and mortality,

and increase revenue. This DNP scholarly project served to evaluate the results of patient

satisfaction surveys from a pilot study. This study retrospectively reviewed 21 surveys from a

DPC practice in the Southeast region of the United States. The results were congruent with

literature in that self-reporting via surveys can elucidate personal opinions that may be difficult

to measure otherwise. The results of this study identified numerous areas of strength and minor

areas of weakness within the DPC practice. From the results of this study, the DPC clinic can

now formulate corrective interventions which will ultimately improve the quality of care that is

rendered within the practice. Additionally, this report has modeled how to implement a patient

satisfaction program. Lastly, this study has expanded the body of evidence that supports the

uniqueness of the DPC healthcare model. In conclusion, this is the final chapter of this scholarly

project. It is anticipated that the results from this study will improve the care rendered at the

DPC clinic, encourage other providers to utilize the DPC healthcare model, and inspire over

healthcare delivery systems to measure patient satisfaction.


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Appendix A

Patient Satisfaction Survey Questions Used for this Project

NOTE: Below are the questions that were abstracted from the survey.

CAHPS® Visit Survey 2.0 (English)

Your Privacy is Protected. All information that would let someone identify you or your family will be kept private. Your Family MD will not share your personal information with anyone without your OK. Your responses to this survey are also completely confidential.

Your Participation is Voluntary. You may choose to answer this survey or not. If you choose not to, this will not affect the health care you get.

5. In the last 12 months, when you phoned Your Family MD’s office to get an appointment for care you needed right away, how often did you get an appointment as soon as you needed?

Never

Sometimes

Usually

Always

7. In the last 12 months, when you made an appointment for a check-up or routine care, how often did you get an appointment as soon as you needed?

Never

Sometimes

Usually

Always

9. In the last 12 months, when you phoned Your Family MD’s office during regular office hours, how often did you get an answer to your medical question that same day?


Never

Sometimes

Usually

Always

11. In the last 12 months, when you phoned Your Family MD’s office after regular office hours, how often did you get an answer to your medical question as soon as you needed?

Never

Sometimes

Usually

Always

14. Wait time includes time spent in the waiting room and exam room. During your most recent visit, did you see your provider within 15 minutes of your appointment time?

Yes

No

15. During your most recent visit, did the provider listen carefully to you?

Yes, definitely

Yes, somewhat

No

16. During your most recent visit, did the provider explain things in a way that was easy to understand?

Yes, definitely

Yes, somewhat

No

17. During your most recent visit, did you talk with provider about any health questions or concerns?

Yes

No


18. During your most recent visit, did your provider give you easy to understand information about these health questions or concerns?

Yes, definitely

Yes, somewhat

No

19. During your most recent visit, did the provider seem to know the important information about your medical history?

Yes, definitely

Yes, somewhat

No

20. During your most recent visit, did the provider show respect for what you had to say?

Yes, definitely

Yes, somewhat

No

21. During your most recent visit, did the provider spend enough time with you?

Yes, definitely

Yes, somewhat

No

24. Using any number from 0 to 10, where 0 is the worst provider possible and 10 is the best provider possible, what number would you use to rate Your Family MD?

10 Best 0 WorstProvider ProviderPossible 9 8 7 6 5 4 3 2 1 Possible

.


Appendix B

Data Collection Form

Participants were 18 years or older; all genders were included and were seen at the clinic during

July 9, 2018 through September 9, 2018.

Survey #

Q. 5: “In the last 12 months, when you phoned Your Family MD’s office to get an appointment for care you needed right away, how often did you get an appointment as soon as you needed?”1=never 2=sometimes 3=usually4=always

Q. 7: “In the last 12 months, when you made an appointment for a check-up or routine care, how often did you get an appointment as soon as you needed?”1=never 2=sometimes 3=usually 4=always

Q. 9: “In the last 12 months, when you phoned Your Family MD’s office during regular office hours, how often did you get an answer to your medical question that same day?”1=never 2=sometimes 3=usually4=always

Q. 11: “In the last 12 months, when you phoned Your Family MD’s office after regular office hours, how often did you get an answer to your medical question as soon as you needed?”1=never 2=sometimes 3=usually 4=always

Q. 14: “Wait time includes time spent in the waiting room and exam room. During your most recent visit, did you see your provider within 15 minutes of your appointment time?”1=yes2=no

Q. 15: “During your most recent visit, did the provider listen carefully to you?” 1=yes, definitely 2=yes, somewhat 3=no

Q. 16: “During your most recent visit, did the provider explain things in a way that was easy to understand?” 1=yes, definitely2=yes, somewhat 3=no

123456….25

Survey #

Q. 17: “During your most recent visit, did you talk with provider about any health questions or concerns?” 1=yes 2=no

Q. 18: “During your most recent visit, did your provider give you easy to understand information about these health questions or concerns?”1=yes, definitely2=yes, somewhat3=no

Q. 19: “During your most recent visit, did the provider seem to know the important information about your medical history?”1=yes, definitely 2=yes, somewhat3=no

Q. 20: “During your most recent visit, did the provider show respect for what you had to say?”1=yes, definitely 2=yes, somewhat3=no

Q. 21: “During your most recent visit, did the provider spend enough time with you?” 1=yes, definitely2=yes, somewhat3=no

Q. 24: “Using any number from 0 to 10, where 0 is the worst provider possible and 10 is the best provider possible, what number would you use to rate Your Family MD?”0=worst providerThrough 10=best provider

123456….25

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