Relationship Between Quality Perception and Patient Expectations with Patient Demographic Structure in Health Care Institutions and Organizations: Atatürk University Faculty of Dentistry Example

TL;DR

This study explores how patient and relative perceptions of healthcare quality and expectations vary based on demographic factors like age and income.

Contribution

The study identifies specific demographic factors influencing quality perception and expectations in healthcare settings.

Findings

Patients' quality perceptions and expectations did not differ by gender, education, or marital status.

Quality perceptions and expectations varied significantly by age, profession, and monthly income.

Nonparametric tests were used due to non-normal data distribution.

Abstract

To reveal whether the quality perceptions service expectations of patients and their relatives who come to health institutions for examination and treatment differ according to their demographic structures.

The data collection tool used was the Patient Satisfaction Survey. The sample of the study consisted of 428 patients aged 21 and over 21 years who applied to Atatürk University Faculty of Dentistry for dental examinations between April 1, 2022 and July 31, 2022. The descriptive scanning method, one of the quantitative research methods, was used in the study. Survey analyzes were evaluated using scientific statistical analysis techniques described in the literature, and IBM Statistical Package for the Social Sciences (IBM SPSS Corp.; Armonk, NY, USA) Statistics 20 software was used.

Since the normal distribution condition was not met in normality tests, nonparametric tests were performed. Nonparametric tests revealed that patients’ perceptions of quality and expectations did not differ according to gender, education, or marital status. On the other hand, patients’ perceptions of quality and expectations differed according to age, profession, and monthly income.

As a result of the statistical evaluation of the survey results, it was revealed that the quality perception and patient expectations in health institutions and organizations vary according to the demographic structures of the patients such as gender, age, education level, and monthly income.

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Full text

Introductıon

Public and university hospitals, whose primary purpose is to diagnose human diseases and provide services for the treatment of these diseases, fulfill their public responsibilities without making a profit and provide health services in line with this purpose. Although public hospitals have been providing medical services for many years, significant changes have occurred in the field of medical services in our country, as well as all over the world, and private health institutions have also taken their place in this field. In this field, commercial gain and health services go hand in hand and seem to continue to do so.

Since the main purpose of quality research in both manufacturing and service sectors is to achieve maximum efficiency at minimum cost, companies try to achieve greater efficiency through quality improvement research.

Health services, which were socialized in the 1960s, began to weaken in the face of liberal movements that began to develop in the 1980s and were forced to change. The 2003 Health Transformation Program, in addition to taking the country’s health system to a completely different position, was also the first result of the process of change in the perception of health.^1^

As private healthcare providers compete with each other commercially, these institutions have begun to focus on quality, thinking about how to provide better service to patients, rather than just examining and treating them. Public hospitals have also joined this competitive environment and have made efforts to ensure that patients feel the treatment, other social expectations, and psychological comfort.

The “Quality and Accreditation in Healthcare Institutions” research, which is 1 of the 8 main components of the Health Transformation Program and aims to provide quality healthcare services, was implemented institutionally and systematically by our Ministry in 2005.^2^

If healthcare institutions lag behind in their efforts to improve the quality of their healthcare services and cannot meet patient expectations in the future, they will not be able to compete with institutions and organizations that attach great importance to this field and develop and implement service quality criteria, and they will have difficulty maintaining their existence in the social arena.

Improving the quality of healthcare services will provide the highest level of benefit for patients. When creating satisfaction-based and problem-solving focused healthcare services become a top priority, patients will be sure that they are getting the full value of their choices. Such a belief increases patients’ trust in healthcare institutions.^3^

Since the main purpose of research on the quality of care and treatment in health institutions and organizations is to increase patient satisfaction, surveys are conducted as evaluation and development criteria regarding these facts. Survey results are examined using scientific statistical methods, and the results are interpreted. Based on the obtained data, conclusions regarding improvement and correction are reached.

Many studies have been conducted on this subject in the world and in our country, and positive developments have been reported as a result of the reflection of these studies into practice.

According to Kajral,^4^ in the first approach, researchers evaluate quality in 3 dimensions. These are:

Physical quality,interaction quality, andbusiness quality.

There are several main factors that affect patient satisfaction. These factors can depend on the patient, staff, and physical and environmental characteristics. The patient’s sociodemographic characteristics, such as age, education, income, occupation, gender, language, religion, race, and family structure play different roles in patient satisfaction. These criteria vary from person to person and are closely related to the level of satisfaction with health services. Similarly, the staff providing the service and the physical environment can also affect satisfaction with the service.^5^

In this study, which we conducted to determine whether performance standards and patient expectations are perceived differently according to demographic structures at Atatürk University Faculty of Dentistry, quality measurement was used in accordance with the first approach. In this study, survey topics and survey questions were selected in line with this purpose.

Materials and Methods

This study is a cross-sectional study and does not fall into the category of clinical research. Therefore, informed consent was not obtained from the patients participating in the survey. The study was approved by the Ethics Committee of the Faculty of Dentistry of Atatürk University (decision date: September 28, 2023; decision number: 47). The study focuses on patients’ perceptions of quality and service expectations in healthcare and does not include clinical research.

Patients were informed and participated in the survey given in Table 1 on a voluntary basis. In this investigation, the descriptive Survey Design Method was used as a quantitative research method. Descriptive statistics is the process that aims to describe the characteristics of the individuals or objects participating in the research by using the data obtained by observation on a sample or from the whole universe in the accessible situations.^6^

This investigation was a cross-sectional study and did not belong to the clinical research category. Therefore, informed consent was not obtained from the patients participating in this survey. This study was approved by the Local Ethics Committee of our university (decision date: September 28, 2023; decision number: 47). The study focuses on patients’ quality perceptions and service expectations and does not include clinical research.

Patients were informed and participated in the survey given in Table 1 on a voluntary basis. In this investigation, the descriptive Survey Design Method was used as a quantitative research method.

“Descriptive statistics is the process that aims to describe the characteristics of the individuals or objects participating in the research by using the data obtained by observation on a sample or from the whole universe in the accessible situations.”^4^

Population and Sample of the Study

The study group of this research consisted of 428 patients aged 21 and over 21 years who came to the hospital for examination and treatment between April 1, 2022, and July 31, 2022, selected by a random sampling method. There were no invalid questionnaires in our survey study. The distribution of participants according to demographic characteristics is shown in Table 2.

Data Collection Tools

The “Patient Satisfaction Questionnaire” was used as a data collection tool in the study. The preparation of the Patient Satisfaction Questionnaire was carried out in the following stages.

First stage: A literature review and research was conducted on patient expectations and performance criteria.

Second stage: The questions planned to be included in the questionnaire were prepared by examining survey studies in the literature.

Third stage: The survey questions were evaluated with the participation of 1 academic staff member, 1 senior academic staff member at the upper management level, and 1 administrative staff member from the administrative units of the hospital where the research was conducted, and the questionnaire was finalized. Table 1 shows the Patient Satisfaction Questionnaire.

Data Collection

The evaluation criteria of the prepared survey questions were established to be evaluated as Disagree (1), Partially Agree (2), No Opinion (3), Good (4), and Very Good (5).

Data Analysis

The following methods in the IBM SPSS Statistics 20 (IBM SPSS Corp.; Armonk, NY, USA) questionnaire analysis program were used in the analysis of the questionnaires. The following normality tests were performed in the survey study.

Examination of Skewness and Kurtosis values in normality tests.Skewness and Kurtosis values divided by the standard error.Kolmogorov–Smirnov and Shapiro–Wilk tests.

Since all the results of the normality tests did not meet the normal distribution conditions, parametric tests were not performed, and the corresponding nonparametric tests, namely Mann–Whitney U and Kruskal–Wallis tests, were applied.

Results

The questionnaire study on whether there is a difference between demographic structures in determining quality perception and patient expectations in health institutions was examined in 5 areas according to 5 demographic characteristics.

When a general evaluation of the questionnaire results is made, as seen in Table 3, the highest average is question 23, with a value of 4.128. In contrast, the lowest average is question 17, with a value of 2.660.

Statistical Analyses and Results According to Demographic Structures

Normality Tests

Skewness and Kurtosis Test

The range of −2 to 2 was taken as a reference for Skewness and Kurtosis values.

There are specific cut-off points in the literature regarding the Skewness and Kurtosis coefficients to show the normality of the distribution. Accordingly, it is stated that if the distribution is normal, the Skewness and Kurtosis coefficients should be in the range of −1 to 1. If the Skewness coefficient is in the range of −1 to 1, the Kurtosis coefficient can be in the range of −2 to 2, and if the Kurtosis coefficient is in the range of −1 to 1, the Skewness coefficient can be in the range of −2 to 2.5.^7^

As can be seen in Table 4, the Skewness and Kurtosis test values for gender, age, education, occupation, and monthly income categories are between −2 and 2 values, so the data conform to normal distribution.

Skewness and Kurtosis Values Divided by Standard Error

“The Skewness and Kurtosis values divided by the Standard Error should be within −1.96 and 1.96.”^7^

As can be seen in Table 4, in the categories of gender, age, education, occupation, and monthly income, the values of Skewness and Kurtosis values divided by the standard error are −1.96 and 1.96 in some categories. In contrast, in some categories, they are not suitable for normal distribution. For this reason, it is understood that the data distribution is unsuitable for normal distribution.

Kolmogorov–Smirnov Test

The Kolmogorov–Smirnov test, widely used in the SPSS program and commonly accepted in the literature, determines whether the data set obtained from the sample to which the questionnaires are applied has a normal distribution with the strictest approach. A significance value (asymp. sig.) of P < .05 in the result of the Kolmogorov–Smirnov test means that the data are not normally distributed, while a test result of P > .05 means that the data are normally distributed.^8^

As seen in Table 4, in the categories of gender, age, education, occupation, and monthly income, according to the Kolmogorov–Smirnov test results, it was seen that some of the values were by the normal distribution since P > .05 in some categories, while some values were not by the normal distribution since P < .05. For this reason, it is understood that the data distribution is unsuitable for normal distribution.

Nonparametric Tests

In hypothesis testing, especially in cases where the normality assumption is not met, tests that require very few or no assumptions have been developed. These tests are nonparametric. These tests include nonparametric methods that require almost no assumptions other than that the populations are continuous and that we are not interested in population parameters.^9^

Mann–Whitney U-Test

The Mann–Whitney *U-*test is used to test the null hypothesis stating that “2 independent samples come from the same population” without having to assume that the populations from which the samples were drawn conform to normal distributions.^10^

Since the data in the gender category did not conform to the normal distribution, the Mann–Whitney U and test statistics, which are nonparametric tests, were applied.

The results of these tests are shown in Table 5. According to this test result, gender significantly affects quality perception and service expectations at the 5% error level.

Kruskal–Wallis and Test Statistics

Kruskal–Wallis and test statistics were applied to compare more than 2 independent variables. The results are shown in Table 6.

The reason for choosing this analysis is that it is a technique used to test the significance of the difference between the means of 3 or more groups in groups that do not show normal distribution.^11^

Kruskal–Wallis and Test Statistics by Age Category

Age significantly affects quality perception and service expectations at the 5% error level.

Kruskal–Wallis and Test Statistics by Educational Status Category

Educational status significantly affects quality perception and service expectations at a 5% error level.

Kruskal–Wallis and Test Statistics by Occupation Category

Profession significantly affects quality perception and service expectations at the 5% error level.

Kruskal–Wallis and Test Statistics by Monthly Income Category

Monthly income significantly affects quality perception and service expectations at the 5% error level.

Discussion

According to gender category, 65.7% of the participants are male and 34.3% are female. According to the survey results, gender data do not conform to a normal distribution for both males and females.

According to age category, 26.4% of the participants are in the 21-30 age range, 21.5% in the 31-40 age range, 27.8% in the 41-50 age range, 18.9% in the 51-60 age range, and 5.4% are 61 and above. In the age category, the survey data for 21-30, 31-40, and 51-60 do not conform to a normal distribution, while the data for 41-50 and 61 and above conform to a normal distribution.

According to the education level category, the participants are: 3.8% are primary school graduates, 5.4% middle school and high school graduates, 40.4% college graduates, 15% bachelor’s degree graduates, 24.8% master’s degree graduates, and 10.7% are doctoral graduates. Regarding education, the survey data for middle school and high school graduates follow a normal distribution, while the data for other education groups do not follow a normal distribution.

According to the occupational category, 4.7% of the participants are unemployed, 15% are students, 35.5% are civil servants, 0.5% are private sector managers, 4% are lamu sector managers, 12.4% are housewives, 10.5% are private sector workers, 12.6% are public sector workers, and 4.8% are self-employed. The data for housewives and self-employed workers follow a normal distribution, while the data for other occupational groups do not follow a normal distribution.

According to the monthly income category, the participants are: 15.4% earn less than minimum wage, 7.7% earn minimum wage, 18.5% earn between minimum wage and 6000 TL, 25.9% earn between 6001 and 10 000 TL, and 32.5% earn between 10 001 TL and above. The data of those earning less than minimum wage and those earning at minimum wage level are in line with normal distribution, while the data of other income groups do not conform to normal distribution.

When a general evaluation of the survey results was made in the statistical analysis, it was determined that the average of the survey results was 3.4047. The participants gave the highest evaluation to the question “Did you find the personal care, clothing, and cleanliness of the physician who provided your treatment sufficient?” with an average of 4.1276, and the lowest evaluation to the question “Did you find the cleanliness of the polyclinic and other units where you were examined sufficient?” with an average of 2.6604.

This survey was limited to the hospital, and since it was impossible to survey all patients, it was conducted voluntarily.

It was determined that the survey questions were too many, and the respondents gave random answers due to a lack of knowledge about some questions.

For the article, multiple comparison tests related to demographic structures were conducted, but to comply with the journal format limitation, they could not be included in the article.

Analyzing the questionnaire evaluation based on questions and informing the organization’s managers to take the necessary corrective actions regarding the questions with values below 3.50 will ensure that this study achieves its purpose.

After the corrective actions are taken, it is necessary to verify whether the activities carried out with a questionnaire study covering only these questions have achieved their purpose.

A more comprehensive study can be conducted by dividing the evaluation of the questionnaire questions into categories such as physical, environmental, processes, and management rather than conducting it in general.