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Summarize Research Articles Write a summary of each of the articles that you identified in Topic 2. Address the following: Must Use the format template attached and Articles are listed already on the template – attached are the articles. Write one research summary that uses a quantitative research design – article provided. Write one research summary that uses a qualitative research design – article provided. Each summary should be 250-500 words on each article (total of 500-1000) and should follow the template provided in “Summarize Research Articles.” Use APA Level Heading 2 to separate the distinct parts of the study. These article summaries will form the basis of the Critique of Research Studies Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required. Book used Chapters 9-11 and 20 in Nursing Research: Generating and Assessing Evidence for Nursing Practice. and Articles attached This assignment uses a rubric listed below: Comprehensive description of author(s), article type, type of design, model summary in text, and why this article’s design fits summary demonstrates command of research terminology. Problem statement and statement of purpose fully described using accurate and precise research language. Research question(s) fully identified using accurate and precise research language. Study methods and key findings fully described using accurate and precise research language. Comprehensive description of author(s), article type, type of design, model summary in text, and why this article’s design fits summary demonstrates command of research terminology. Problem statement and statement of purpose fully described using accurate and precise research language. Research question(s) fully identified using accurate and precise research language Study methods and key findings fully described using accurate and precise research language. Writer is clearly in command of standard, written, academic English. Correct APA format is consistently used in the paper: cover page, margins, double-spacing, font size, and all other elements of APA, including headings and pagination. In-text citations and a reference page are complete. The documentation of cited sources is free of error.


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Thornton et al. BMC Health Services Research (2017) 17:361
DOI 10.1186/s12913-017-2307-z
Open Access
Influences on patient satisfaction in
healthcare centers: a semi-quantitative
study over 5 years
Ruth D. Thornton1, Nicole Nurse2, Laura Snavely3, Stacey Hackett-Zahler4, Kenice Frank5 and Robert A. DiTomasso1*
Background: Knowledge of ambulatory patients’ satisfaction with clinic visits help improve communication and
delivery of healthcare. The goal was to examine patient satisfaction in a primary care setting, identify how selected
patient and physician setting and characteristics affected satisfaction, and determine if feedback provided to
medical directors over time impacted patient satisfaction.
Methods: A three-phase, semi-quantitative analysis was performed using anonymous, validated patient satisfaction
surveys collected from 889 ambulatory outpatients in 6 healthcare centers over 5-years. Patients’ responses to 21
questions were analyzed by principal components varimax rotated factor analysis. Three classifiable components
emerged: Satisfaction with Physician, Availability/Convenience, and Orderly/Time. To study the effects of several
independent variables (location of clinics, patients’ and physicians’ age, education level and duration at the clinic),
data were subjected to multivariate analysis of variance (MANOVA)..
Results: Changes in the healthcare centers over time were not significantly related to patient satisfaction. However,
location of the center did affect satisfaction. Urban patients were more satisfied with their physicians than rural, and
inner city patients were less satisfied than urban or rural on Availability/Convenience and less satisfied than urban
patients on Orderly/Time.
How long a patient attended a center most affected satisfaction, with patients attending >10 years more satisfied in all
three components than those attending <1–5 years. Level of education affected patients’ satisfaction only in the component Orderly/Time; patients without a high school education were significantly less satisfied than those with more. Patients in their 40′s were significantly less satisfied in Availability/Convenience than those >60 years old.
Patients were significantly more satisfied with their 30–40 year-old physicians compared with those over 60. On
Orderly/Time, patients were more satisfied with physicians who were in their 50′s than physicians >60.
Conclusions: Improvement in patient satisfaction includes a need for immediate, specific feedback. Although Medical
Directors received feedback yearly, we found no significant changes in patient satisfaction over time. Our results
suggest that, to increase satisfaction, patients with lower education, those who are sicker, and those who are new to
the center likely would benefit from additional high quality interactions with their physicians.
Keywords: Patient satisfaction, Health care delivery, Community health
* Correspondence: [email protected]
Department of Psychology, Philadelphia College of Osteopathic Medicine,
4170 City Ave., Philadelphia, PA 19131, USA
Full list of author information is available at the end of the article
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (, which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
( applies to the data made available in this article, unless otherwise stated.
Thornton et al. BMC Health Services Research (2017) 17:361
Patient satisfaction surveys are often used to understand
patients’ concerns and determine areas for improvement,
including improving communication between physicians
and patients. Survey results document progress and
allow physicians and staff to maintain high standards.
Although results of patient satisfaction surveys are used
by payer systems to profile individual physicians and
guide physician compensation, one study showed that < 25% of primary care physicians found profiles useful for improving patient care and fewer used the profiles to change [1]. Improvements are more likely to occur if staff receives more immediate feedback [2]. Data collection methods play a role in outcomes. Onsite surveys provide an immediate outlet for patients who are experiencing problems, although higher ratings for on-site surveys may also relate directly to doctorpatient communication. Surveys administered later after a clinic visit may yield lower ratings, possibly due to the course of treatment [2, 3]. Many factors influence patient satisfaction. Patient demographics such as age, gender, income, socioeconomic and general health status impact patients’ responses [3, 4]. Characteristics of the medical provider, including demographics and experience, also affect their interactions with patients [5–9]. Other factors include the type of setting the patient is in [10] and the amount of time patients had to wait [11]. However, Anderson found that complaints about wait time can be moderated by time spent with the physician [12]. Physician characteristics extend beyond the obvious. Physician-patient concordance in race, gender or age may be important in patient satisfaction, but many other factors such as primary language, parental status, sexual orientation, values, beliefs, or communication style may be associated [13, 14]. How long the patient has been with this physician and the degree to which the physicians’ communication is patientcentered are significant [13]. A physician’s experience plays a role, with lowest patient satisfaction with firstyear residents; interestingly, residents with some more Page 2 of 9 experience attained similar satisfaction ratings to those of the faculty attendings, suggesting that the requisite skills are acquired during the first year of training [7]. Whether to administer patient satisfaction surveys depends on the overall goals of the medical facility and on physician buy-in to change [1, 15]. The views of the medical director and administrator are key components as to whether the surveys are taken seriously and acted upon by physicians [16]. Patient satisfaction can become a success criterion of the center when physicians and staff meet regularly to discuss improvements in a context of cooperation and mutual support. Methods We initiated this study of patient satisfaction to help physicians better understand their patients at the healthcare centers (HCCs) of a not-for-profit medical school’s outpatient primary care centers on the east coast. Physicians were provided raw data and results of open-ended questions very soon after each year’s study. However, we decided to statistically analyze the overall data in order to understand where patients were most and least satisfied and what influenced their satisfaction. Our goal was to provide information which could help focus physician directors’ changes to improve patient satisfaction. The research was under the auspices of a medical college (Philadelphia College of Osteopathic Medicine, PCOM) which owns and operates five outpatient HCCs, four of which are located within the city limits of Philadelphia and the fifth HCC located in a rural area. [17] Two within Philadelphia are considered urban, while two are in the inner city [18]. An additional nonaffiliated, inner city HCC located within Philadelphia was also used in the research. We considered the nonaffiliated HCC as a control, but expected it to likely agree with data from the affiliated inner city HCCs. The quantity of surveys administered are listed in Table 1. This research arose from a need to quickly and inexpensively conduct patient satisfaction surveys in the Healthcare Centers, incorporating a research component Table 1 Numbers of patients surveyed from each Healthcare center during year 1 (Fall, 2005), year 2 (Summer, 2007), and year 3 (Summer 2010) HCC Location Year 1 # surveyed Year 2 # surveyed Year 3 # surveyed TOTAL surveyed 1 Inner City (PCOM) 40 68 90 198 2 Urban (PCOM) 34 54 69 157 3 Inner City (PCOM) 21 43 70 134 4 Rural (PCOM) 30 19 25 74 5 Urban (PCOM) 25 51 45 121 6 Inner City (non-PCOM) TOTALS 50 75 80 205 200 310 379 889 Thornton et al. BMC Health Services Research (2017) 17:361 involving graduate students interested in health related careers. Surveys were administered to patients at the five HCCs. Patient questions were adapted from the validated DiTomasso-Willard Patient Satisfaction Questionnaire [19] (questions are listed in Table 2). Demographic information and responses to open-ended questions were also collected. In 2005 (year 1), 2007 (year 2), and 2010 (year 3), students in a master’s program at the medical school approached patients in the waiting areas at each HCC asking them to complete a survey. Patients could take the surveys with them into the examination room, but they returned the survey before leaving the HCC. If requested, the student helped a patient read the questions. Each surveying period was conducted over an approximately one month of time. Students varied their sampling by time of day and day of week. Therefore, the sample was comprised of a random representation of patients attending each HCC during each one-month period of surveying. The students approached anyone who was in the waiting room during sampling times, but Page 3 of 9 patients were free to refuse if they wished. The goal was to obtain approximately 10% of the average number of patients seen by each HCC in a month. The protocol (Protocol #H05-022X) was approved by the Institutional Review Board (IRB) of PCOM that determined it to be exempt from informed consent requirements under 45 CFR 46.101(b)(2)–survey research in which the responses will be recorded in such a manner that the human subjects cannot be identified, directly or through identifiers linked to the subjects (e.g., name, Social Security number). Further, no master list existed linking such identifiers to the subjects. Approximately 5–15% of the average numbers of patients coming to each HCC in a month were surveyed. Inclusion criteria included patients willing to respond, patient age of at least 18 years, and patients who spoke English. Patients were assured the questionnaire was confidential without any identifying information, the results would be presented in aggregate form, and that their responses would not affect their specific care at the HCC. In order to maintain anonymity, a patient’s medical status was Table 2 Grouping of the 21 survey questions using factor analysis, Rotated Component Matrix Component: Question: 1 2 3 Q1. During a typical visit, my doctor spends enough time explaining my medical condition to me. 0.773 0.151 0.162 Q2. My doctor gives me the best quality of care. 0.869 0.190 0.133 Q3. I would recommend my doctor to friends. 0.827 0.191 0.112 Q4. The staff are helpful to the patients. 0.311 0.562 0.127 Q5. My doctor uses technical terms that confuse me. 0.109 −0.200 0.628 Q6. My doctor is available when I need him/her.b 0.412 0.491 0.076 Q7. The waiting room time is too long. −0.084 0.402 0.442 Q8. My doctor really follows through. 0.751 0.230 0.082 Q9. I plan to return to this center for care. 0.713 0.370 0.148 Q10. It’s easy to get an appointment when I need one. 0.223 0.665 0.122 Q11. My doctor wastes time talking about things that don’t really matter to me.a 0.271 −0.014 0.702 Q12. My doctor treats the “whole” person. 0.640 0.300 0.143 Q13. The staff accommodates my needs over the phone. 0.241 0.677 0.070 Q14. I am satisfied with the quality of the medical care I receive here. 0.724 0.398 0.171 a b Q15. I receive prompt attention while waiting in this facility. 0.285 0.658 0.132 Q16. I have to tell my story several times before getting an appointment.a 0.001 0.409 0.631 Q17. I am treated the same as other people who get care here. 0.366 0.511 0.105 Q18. Check-out time at the front desk is too time-consuming.a −0.030 0.338 0.648 Q19. I would not recommend this center to a friend. 0.250 0.101 0.530 Q20. Everything seems so confusing at this center.a 0.199 0.160 0.731 Q21. When I’m sick I can get an appointment pretty quickly. 0.229 0.712 0.057 a Component 1: Satisfaction with Doctor (Questions 1, 2, 3, 8, 9, 12, 14) Component 2: Availability/Convenience (Questions 4, 10, 13, 15, 17, 20) Component 3: Orderly/Time (Questions 5, 11, 16, 18, 19, 20) a Questions worded in the negative were reversed for statistical analysis b Question not classified by component Thornton et al. BMC Health Services Research (2017) 17:361 not requested, although in retrospect, it may have been helpful. From observation, students reported that those with acute medical issues were less inclined to participate. Although an absolute count was not performed, students who administered surveys consistently estimated that only about 5% of the patients in the waiting room refused to participate. Survey results were entered into IBM’s Statistical Package for the Social Sciences (SPSS 18.0) for analysis. Missing data were filled in using Linear Interpolation, and any negative questions were transformed to the positive on the Likert scale, so that, for all questions, 5 (strongly agree) meant “most satisfied.” All 21 survey statements were subjected to a principal components varimax rotated factor analysis according to Kaiser’s criterion [20] which ultimately allowed for a reduction of statements into three classifiable components, Satisfaction with Physician, Availability/Convenience, and Orderly/Time (Table 2). Following each survey period, the data were analyzed in SPSS to collapse the questions into three classifiable components/categories. These three categories did not vary during the 3 data collection periods. After each survey period, study staff attended face-to-face meetings with Medical Directors of each healthcare center, the Dean of the Medical School, and the Chair of Family Medicine to present the results. HCC staff were provided with mean scores for each question for their HCC compared with a composite of all HCC’s. They also received the data collapsed into the three categories for their HCC compared with a composite of all HCC’s, but without statistical analysis. For analysis of the composite data, multivariate analysis of variance (MANOVA) was performed for groups of data, using post hoc Tukey to distinguish specific significance between groups. Independent t-test was used for gender analysis, and Chi square analysis was done to compare the observed gender data from patients who completed surveys with patient demographics of each HCC. See Additional Data for more specific information. In using factor analysis, it is common practice to require 10 subjects per number of items. In the present case, this criterion was far exceeded. For the separate MANOVA analyses using 3 dependent variables, setting power at 95% for a medium effect size at the 0.05 level of significance comparing 2 levels (male vs. female) of the independent variable, 3 levels (3 locations) and 5 levels (physician age groups), the required number of subjects was 280, 171, and 145 respectively. In all cases there was sufficient power. Results Surveys were administered to a total of 889 patients who visited one of the HCCs for treatment (Table 1). These Page 4 of 9 numbers represented between 5–15% of the average number of patients seen monthly in the affiliated HCCs, and comparable numbers of surveys were obtained from the much larger, non-affiliated HCC. Applying principal components varimax rotated factor analysis to the survey responses resulted in groups of identifiable questions that constituted factors (Rotated component matrix for all questions is shown on Table 2). Three classifiable factors, Satisfaction with Physician, Availability/Convenience, and Orderly/Time, emerged from the analysis and are used throughout this research. Two questions (Q6 and Q7) were not included as the items did not load on any of the factors (Table 2). Using the survey questions that constituted each factor (Table 2), the three factors have the following characteristics: Satisfaction with Physician involves being satisfied with the quality of medical care received, as well as the physician spending enough time with the patient. Availability/Convenience involves being satisfied with the staff and their helpfulness in making appointments, whether in person or by phone. Orderly/Time has to do with patients’ time being respected, and interactions with staff and physicians being clear and to the point, avoiding confusion. Overall, patients were quite satisfied with their HCCs, as evidenced by overall mean scores greater than 3.89 on a Likert scale of 1–5 (see Additional file 1: Table S3A). Mean scores were highest in Satisfaction with Physician (4.27 ± 0.65), while Availability/Convenience (3.92 ± 0.69) and Orderly/Time (3.89 ± 0.66) were somewhat lower. Even so, a score of 3.9 represents the top 20–25% of satisfaction. The open-ended responses emphasized the importance of patients’ satisfaction with their physician, even if patients were somewhat less satisfied with other aspects of their visit (see Additional file 2: Table S6). The goal of this research was to identify areas found to be statistically significant. More complete data can be found in the Additional files 1, 2, 3,and 4. Based on MANOVA, there was no significance over time in any of the three categories (see Additional file 1: Table S3B). This points to a consistency over time in the operations and functioning of these HCC’s. The following areas were found to be statistically significant by MANOVA: Analyzing satisfaction in inner city, urban and rural HCCs (Fig. 1), significance was observed in the following area.: Patients in inner city HCCs were less satisfied than those in urban or rural HCC’s on Availability/Convenience, and those in inner city HCCs were less satisfied than urban patients in the area of Orderly/Time. Urban patients were more satisfied with their Physician than were rural patients while inner city patients’ satisfaction with Thornton et al. BMC Health Services Research (2017) 17:361 Fig. 1 Satisfaction by location (Inner City, Urban and Rural). Lines/ Brackets indicate comparisons by color that were significantly different in each of the categories their Physician was not significantly different from the other localities (See Additional file 1: Table S3C, for more detail). When individual HCCs were analyzed (Fig. 2), one urban HCC (#5) had significantly higher satisfaction with their Physician than the other urban HCC (#2) or one inner city HCC (#6). The other urban HCC (#2) had more satisfaction in the category of Orderly/Time than two of the three inner city HCCs (#3 and #6). Two inner city HCCs (#1 and #6) had significantly lower satisfaction in the category of Availability/Convenience than the rural HCC (#4). (See Additional file 1: Table S3D, for details.) Patients’ demographics appear to play a role in the level of satisfaction. Patients over 60 years old were more satisfied with the Availability/Convenience of the HCC than patients who were in their 40′s (Fig. 3). Those with more education (in the range from graduating high school through graduate Fig. 2 Satisfaction by individual HCCs. Lines/Brackets indicate comparisons by color that were significantly different in each of the categories Page 5 of 9 school) were more satis ... 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