Introduction
It is a common phenomenon in any organisation for customers to wait for some time before they are served. Some of the waiting experiences are known to have a negative impact on the customers’ satisfaction with companies’ and organisations’ service delivery. Time has become a valuable asset to almost everyone, especially with the increase in personal activities in the busy economies.
Since waiting times are directly proportional to customer satisfaction, it is important for the management to develop the notion of rapid service delivery in order to achieve customer satisfaction. This paper examines the effect of waiting times at the Burjeel Hospital on the degree of customer satisfaction by analysing the results of a survey carried out to at the health facility.
Background of the Survey
The survey was carried out between January and March at the Burjeel Hospital. It sought to establish the relationship between waiting time and customer satisfaction at the hospital. The participants (customers at the hospital) were divided according to the ailment they were suffering from or the treatment they were seeking.
The main areas surveyed include cardiovascular, dental, dermatology, emergency, endocrinology, ENT, family medicine, gynaecology, gastroenterology, general surgery, Internal Medicine, IVF, nephrology, neurology, ophthalmology, orthopaedic, paediatric, plastic surgery, pulmunology, urology and vascular. The table on waiting time between the months of January and March was filled by hospital staffs using the hospital’s records. The data collected aimed at finding out how long patients and customers had to wait before being served in the various categories of services the hospital offers.
Results
Quantitative Data
The quantitative data came from the first survey where customers were required to rank the waiting times. The results for each category differed significantly with most of the results of the other areas being rated as very good. Although they performed well, most of them showed inconsistency by depicting significant changes in waiting time between the months of January and March. Although data from all categories were analysed, only those that had large numbers of customers were likely to give more accurate results. In this case cardiology, dental, dermatology, IVF, and physiotherapy had the best records of customers.
The dermatology and dental category had the highest number of customers across the three months. In the dermatology category, 46.80% of the customers rated waiting time as very good while 33.00% rated it as good for the month of January. In the month of February, 65.90% of the customers rated it as very good while 14.30% rated it as good. The rest of the customers (not more than 20%) rated it as average and below. Moreover, this category showed consistency for the two months.
Similarly, the dental category showed consistency during the two months. 68.40% and 69.80% of the customers rated it ‘very good’ for the months of January and February respectively. On the other hand, 20.60% and 20.70% of them rated it as good for the same months respectively. Lastly, the rest of the customers (not more than 10%) rated it as average and below. Other categories which showed inconsistency in customer rating of the waiting times had small samples and as such cannot be relied upon to give the desired results.
The other three categories, cardiology, IVF and Physiotherapy, also had impressive results due to their high number of customers. In the case of cardiology, the combined score for very good and good was 75.80% while less than 26% rated it average and below. IVF almost scored the same as cardiology with 62.50% being the score for very good and good combined.
In this category, less than 39% scored average and below. Finally, in the physiotherapy category, ‘very good’ and ‘good’ combined had a score of 89.00%. On the other hand, less than 10% rated average and below. All the results analysed above are for the months of January only. For the month of February, the results differed by a very small percentage except for IVF which differed by about 20.00%.
Qualitative Data
The second survey was based on the collection of qualitative data. In this survey, the customers were required to rate the services they received from the nurse, doctors and the reception. Furthermore, they were to rate the waiting times and other general issues concerning the hospital. However, this analysis concentrated more on the waiting times.
In this survey, only five patients were used. Each patient rated waiting times on a scale of between 0 and 5. Some of the categories could not be used since they did not achieve the minimum threshold of 5 patients. However since the number of respondents used was small, most of the categories achieved the minimum threshold.
Most of the respondents in all the categories rated the waiting times as 5. Categories with the best rating included dental, family medicine and emergency with at least four of the patients rating it 5. Others that followed them closely included cardiology and dermatology with at least one of the patients rating it 5. The rest of the categories cannot be considered in this analysis. The reason for this is that they cannot give the desired result as they do not meet the minimum requirement of five people.
Null Hypothesis
Reducing the waiting time has no impact on customer satisfaction. H0=5
Alternative hypothesis
Reducing waiting time will impact customer satisfaction positively. Ha<5
Average Waiting Time
The average of the waiting time is arrived at by computing the average of data on customer waiting times collected from the hospital records. In order to increase our level of accuracy we calculate the average percentage of waiting time from the five categories with the highest number of customers. In arriving at the average, we add the waiting time for combined percentage of very good and good, and divide the result by the number of months. After computation the result is 59.5% (0.59). This is the level of confidence. Consequently, the level of significance is 40.5% (0.41).
Test Statistics
The test statistic is derived at by computing the average of the each of the of the five patients’ level of satisfaction.
Total waiting time for January and February = 433.4
Total waiting time for march = 245.8
Total waiting time for Jan-March = 433.4+245.8= 679.2
Average waiting time = (679.2/24)/3 = 9.43
The overall satisfaction level in the four categories fell below 5. As such, the null hypothesis is rejected. The critical level of the five categories fell below 5 making the alternative hypothesis true.
Conclusion
The actual waiting time played a significant role in customer satisfaction. The results of the surveys show that it is important to encourage employees to serve customers as fast as possible. In the case of Burjeel Hospital, being time conscious enables it to realize customer satisfaction. However, there are a few customers who were not satisfied because of the time they had to wait.
It is difficult to attend to a customer immediately. In such cases, the hospital should provide information to customers that will influence positively their view of the waiting times in a positive manner. Customer satisfaction encompasses other things such as quality of service delivery that needs to be considered alongside waiting time in order to achieve the best customer satisfaction levels.