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Description : The outpatient department serves as a pivotal revenue stream for hospitals. The hospital's chair board has raised concerns over a substantial decline exceeding 40% in both patient volume and associated revenue. The chair board has initiated a business research endeavor aimed at identifying the underlying causes of this decline. Preliminary observations by the research team have highlighted a notable increase in patient dissatisfaction with healthcare services over the past three months.

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Published on : Aug 27, 2024 | Views : 182 | Downloads : 0

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Slide 1-

Diagnosing Revenue Decline: A Case Study of Outpatient Department Income Reduction Supervised by Prof.Dr.sherif Elaasi
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CONTENTS
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INTRODUCTION The outpatient department serves as a pivotal revenue stream for hospitals. The hospital's chair board has raised concerns over a substantial decline exceeding 40% in both patient volume and associated revenue. The chair board has initiated a business research endeavor aimed at identifying the underlying causes of this decline. Preliminary observations by the research team have highlighted a notable increase in patient dissatisfaction with healthcare services over the past three months.
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Problem statment Decline is directly attributed to escalating patient dissatisfaction The recent increase in service prices. Inconsistent adherence of doctors to appointment schedules Issues related to hospitality and patient comfort.
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Research Questions 5 Is there a significant correlation between between poor hospitality practices and patient dissatisfaction within the outpatient department? Is there a significant correlation between inconsistent adherence to schedules by doctors’ impact patient dissatisfaction in the outpatient department? Is there a significant correlation between recent price increases and patient dissatisfaction within the outpatient department?
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Null Hypothesis (H0): There is no significant relationship between patient dissatisfaction and the recent increase in service prices Alternative Hypothesis (H1): There is a significant relationship between doctor's adherence to schedule and patient dissatisfaction Alternative Hypothesis (H1): There is a significant relationship between patient dissatisfaction and the recent increase in service prices. Null Hypothesis (H0): There is no significant relationship between doctor's adherence to schedule and patient dissatisfaction. Null Hypothesis (H0): There is no significant relationship between the availability of free parking and patient dissatisfaction with hospital hospitality Alternative Hypothesis (H1): There is a significant relationship between the availability of free parking and patient dissatisfaction with hospital hospitality Hypotheses
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Research Design Quantitative Descriptive Design quantitative approach to describe and quantify the extent of patient dissatisfaction and its impact on outpatient department income.
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Variables Dependent Independent Patient dissatisfaction Increased service price Doctors comittement Free parking service
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Sampling Method Simple Random Sampling Selecting a subset of individuals from a larger population in such a way that each individual has an equal probability of being chosen. Ensure every patient in the outpatient department population has an equal chance of being included in the study This method helps minimize bias and ensures the sample is representative of the entire patient population : Based on a population size of approximately 20,000 patients and a confidence level of 95%, the researcher determined a sample size of 377 patients
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Data Collection Method Call Center Administration: Trained personnel from the hospital's call center will contact selected patients. Survey Administration: Patients will be administered a structured questionnaire consisting of closed-ended and open-ended questions. Duration: Surveys will be conducted during designated hours to accommodate patient availability and ensure comprehensive data collection.
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Questionnaire Designcontains Open ended and closed ended questionsSection 1: Demographic InformationSection 2: Patient SatisfactionSection 3: Service Specific QuestionsSection 4: Additional Comments
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Descriptive Data Analysis 13 used to summarize and describe the quantitative and qualitative data collected from the survey responses. Advantages of Descriptive Data Analysis: Provides a clear and concise summary of survey findings. Enables comparison of responses across different variables. Helps in identifying trends and patterns in patient satisfaction and dissatisfaction.
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Inferential Data Analysis 14 Non-parametric Techniques: Given that some variables (price increases, doctor schedule adherence, parking service) are qualitative and do not follow a normal distribution, non-parametric tests will be appropriate. Chi-square Test of Independence: This test will be used to analyze the association between categorical variables, such as patient satisfaction (dependent variable) and the independent variables (price increase, doctor schedule adherence, parking service). It will help determine if there is a significant relationship between these variables. The Chi-square test is suitable as it assesses the independence of categorical variables and is robust with nominal (non-numeric) data.
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Results Interpretation 15 Price Increase: Hypothesis: Null hypothesis (H0): There is no significant relationship between patient dissatisfaction and price increase. Expected Result: If the Chi-square test results in a non-significant p-value (typically p > 0.05), we would fail to reject the null hypothesis, suggesting that price increases do not significantly correlate with patient dissatisfaction. Doctor Schedule Adherence and Parking Service: Hypotheses: Alternative hypothesis (H1): There is a significant relationship between patient dissatisfaction and doctor schedule adherence / parking service. Expected Results: If the Chi-square test results in a significant p-value (typically p < 0.05), we would reject the null hypothesis, indicating a significant relationship between patient dissatisfaction and either doctor schedule adherence or parking service.
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Recommendations Optimize Schedule Management Enhance Appointment Coordination Revise Scheduling Practices Parking Facility Optimization 16

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