Introduction Waiting, an experience we can no longer afford Gerald. L. Barlow Canterbury Business School University of Kent at Canterbury Email:g.l.barlow@ukc.ac.uk This research was carried out during July 2001, at a large NHS hospital in the West Midlands U.K., it was a repeat of research carried out in the same hospital exactly 12 months earlier. The research was testing the level of patient satisfaction in a busy out patient clinic. The work carried out the previous year had indicated that there was a general level of dissatisfaction amongst patients with regards to their waiting experience. The work confirmed many of the propositions of Maister (1985) and other queueing research of Davis and Heineke, (1994), Jones, Pappiatt (196), Katz et.al. and (1991) Larson(1987). However, this research contradicted one of Maister's (1985) eight propositions and one which all other researchers in this area have in the past confirmed. The initial research found that all patients expectations of waiting times were generally similar, but that their perception of the wait varied, and the one critically and unexpected area where there was a difference from all previous research was that of the accompanied and unaccompanied patients. All previous research, confirmed Maister's 1985 proposition that "Solo Waits Feel Longer than Group Waits". However, in the 2000 research programme the results clearly found the opposite, that groups/accompanied patients perceived their wait as longer than the solo waiting patients. The actual results were "Of the 280 patients observed and interviewed, 130 were accompanied, and they had a wait expectancy of 39.27 minutes and an actual wait of 54.28 minutes but perceived the wait to be 51.96 minutes. Whereas the solo waiting patients, of which there were 150, expected to wait 39.58 minutes (a difference of +0.31 minutes), an actual wait of 55.72 minutes ( a difference of +1.44 minutes), but perceived this wait as being of 46.19 minutes, 5.77 minutes less than the accompanied group." (Barlow 2002a.) The Importance of Queueing Management Previous research, mainly in the United States, indicates that waiting for a physician or consultant beyond the patients appointment time in an outpatients setting is an experience common to most countries and patients. (Hunt. and Taylor.1994; Young, Wasserman et. Al 1985; Bredfeldt & Clutterback 1987; Spendlove, et. al, 1987; Gotein,1990; Hanning, Spangber 2000). Further literature relating to the effects of waiting times on the patient-consultant/doctor relationship are identified by Young, Wasserman et. al. 1985; Ware, et al 1978; and Gotein 1990. However, these works do not contain studies which measure the direct effect of waiting on patients satisfaction. Specific research into the psychology of queueing, Osuna, (1985), Maister,(1985), Koepp (1987); Katz et al. (1991); Davis and Heineke (1994); Jones and Pappiatt (1996) and Hornik (1992), Larson (1987), does not relate to the hospital sector, nor does any of the research fully test Maister s proposition. Most investigate the actual time waited against the expected waiting time, whilst two papers concentrate on the actual time waited as compared to the perceived time waited. Over the past few years waiting has become a major issue within many countries with regards to their national health service. As early as 1991 waiting times in Swedish hospitals were guaranteed, (although the policy was abandoned on 31 st December 1996. (Hanning and Spanberg 2000) In both the UK and Canada, waiting times and waiting lists have become major issues in the lead-up to national government elections. These lists, however real, and however long, are
only virtual queues as far as the actual patients are concerned. Whereas, the actual waiting time and the real queue that the patient meets when they eventually arrive at the hospital to meet with their consultant/doctor, is seldom mentioned. But, these waits, be they in an Accident and Emergency clinic or in an out-patients day clinic are perhaps the hardest to explain and condone. Most patients can understand or at least accept the issues relating to their wait: financial constraints, the priority of more complex cases, or the increasing complexity of costs brought about by medical advances permitting previously incurable problems to be treated or operated on Amed News (1999), ASL (1997). But, a wait of three or four hours in an EMERGENCY department seems to be at conflict with the patients concept of emergency, or a one hour wait after their appointed time in an outpatient clinic seems, at the least, somewhat inefficient. One of the more memorable television advertisements run by Federal Express stated, Waiting is frustrating, demoralising, agonising, annoying, time consuming and incredibly expensive. (Fortune 1980). There can be few patients in the NHS service who probably have not felt one or more of these emotions, and who will not agree with these sentiments, during some stage of their hospital experience. Irrespective of how well the nurse attends to them, how often the reception/administrator apologises to them, how polite, clinically efficient, courteous, complete and successful their treatment was, the overall perception of the hospital service and in particular that specific clinic, will be clouded by their initial unnecessary and ill informed wait. Their first impressions of the hospital and its clinics are formed by their initial wait for an appointment, the knowledge/belief that they have a specific timed appointment, and then the dissatisfaction of the wait on arrival. This research sets out to investigate these issues, using David Maister s (1985) proposal that customer satisfaction is the effect of customers perception of their service minus their expectation. Which translates into: Patient satisfaction = Patient Perception Patient Expectation Calling the patient a customer is still not deemed the ideal in the modern twenty first century NHS hospital, as the writer quickly discovered on the first meeting with a senior consultant, thus the adaptation of the proposal. David Maister s (1985) proposition was based upon, what he called, two laws of service; Law one: that Customer Satisfaction = customer perception less customer expectation When this is achieved the customer will be satisfied, when the service provider fails to meet this the customer will be dissatisfied. Law two; it is too hard to play catch up ball. By this he meant, that first impressions are very important and if the customer receives a bad first impression then it is going to be very difficult, if not almost impossible, to change their perception of the service. He went on to relate this to queueing experiences and suggested eight propositions: 1. Unoccupied Time feels Longer than Occupied Times 2. Pre-process Waits Feels Longer than In-Process Waits 3. Anxiety Makes Waits Seem Longer 4. Uncertain Waits are Longer than Known, Finite Waits 5. Unexplained Waits are Longer than Explained Waits 6. Unfair Waits are Longer than Equitable Waits 7. The More Valuable the Service, the Longer the Customer Will Wait 8. Solo Waits Feel Longer than Group Waits. David Maister outlined his thoughts on a series of propositions in his chapter in Soloman's et.al. (1985) seminal text "The service Encounter", however, they were simply propositions, based on
observations not ones that he had actually tested. This chapter was an extension of his "Notes on the Management of Queues" 9-680-053, Harvard Business School Case Services, 1979, rev.17.3.95. However, all of these propositions have been tested by queueing psychology research such as Davis, M.M., and Heineke,J. (1994); Jones,P, and Pappiatt, E.(1996), Larson, B.M. (1987) Katz, K.l., et. al., (1991) and this author. As far as one can be aware, there is no or very little reported study of waiting lines conducted where the researchers undertook to fully test Maister s (1985) proposition, that of perception minus expectation. Most research carried out in this area seems to have concentrated on either, expectation and real time, Davis and Heineke (1994), or perception and real time Katz et. al. (1992), Jones and Pappiatt (1996). This study, aimed at measuring and comparing the two, perception and expectation, was based on the concept that the actual time is not of significant importance, it is the difference between perception and expectation that creates the level of satisfaction. Customers frequently have to wait during the process of acquiring a service. These waiting experiences are typically negative and have been shown to affect the customers overall satisfaction and their evaluation of the service encounter Larson (1987). Traditional queueing theory and productivity measurement techniques look at the speed of a service, the actual waiting times, the effectiveness of both, and the style and design of the layout. However, a more appropriate and increasingly recognised approach is to manage the customers experience and levels of satisfaction Fitzsimmons and Fitzsimmons (2001). Customers may wait within a variety of contextual settings, service operations such as the check-out queues at the supermarket, the cashier/receptionist s desk at a hotel to book-in or check-out, the service counter at a burger restaurant or the outpatients waiting areas of an Eye clinic. The inevitability of demand exceeding capacity causes the queue. Within the hospital sector, this may be caused by an emergency calling a member of the medical team away. It may be caused by external factors, for example a serious traffic congestion causing the late arrival of one or more of the medical team, (as happened during the research period). Queues may, however, be both visual and virtual, but the daily eyesore of a room of patients waiting for a prearranged or booked appointment, must surely be one of the most difficult to accept, either as a patient or an impartial observer. As service industries continue to grow in importance, customers voice increasing irritation, frustration and dissatisfaction with individual service encounters, (Koepp cited in Bitner 1990). This is an important issue that hospital clinics and management need to acknowledge and address. As patients experience increasing publicised delays and waits, so their dissatisfaction is increased only to be expressed when they eventually get the opportunity in the hospital, often during a meeting with the nurse or doctor, (Barlow 2002b). Evidence cited by Jones and Dent (1994) suggested that nearly two thirds of service complaints in retail operations are time-related in terms of 'too long to pay' or 'too long to be served'. This form of time related dissatisfaction can be extended into many service areas, including the hospital sector, where waiting has now become a political issue.(guardian March 9 th. 2002). Increasing standards of living, brought about by the emergence of a single global economy has shifted consumer values to such an extent that this will increasingly become an issue of order winning importance. Consequently more and more customers will be prepared to pay more to avoid queueing, a feature identified as long ago as 1967 by Kleinrock. Queueing is simply a lose-lose strategy Aviel (1996). Patients will lose valuable time and hospitals lose their patients goodwill, which will cause tension and stress within their staff, as well as the hospital gaining a poorer reputation. The trend towards the desire for faster and faster services is set to continue as waiting times constitute a more important determinant in the customer s selection process and therefore firms must respond to this change if they are to remain competitive. (Katz et al 1991)
The Methodology The clinic, in which this research was carried out is a large HNS Hospital situated just outside Birmingham England. The specific area was the Eye Clinic, the hospital's business clinic. This clinic covers a full range of eye treatment including clinics for, glaucoma, cataracts, diabetes, general eye problems, and laser treatment, but excluded children. The average of the patients was over 55, and so the results may be influences by the demographic mix. The research was carried out throughout the month of July 2001, and involved 639 patients (59.7% of the total clinic's population over the period), drawn from all the clinics, with 285 being female and 354 males. The research covered the entire period of service delivery, from 8.30 a.m. until 5.00 p.m. or later, on each day to ensure full and complete coverage of the range of clinics, and patients. Permission was obtained to ask a single question per visit. Two separate questions were designed (the same as the original research) the first designed to investigate the patients expectation, "is this your first visit to the clinic, and how long are you expecting to wait until you actually start your consultation with the doctor/consultant?" This question was asked as patients arrived at the clinic. The second question was designed to investigate the patients perception of their wait. "Is this your first visit to the clinic, how long have you waited from arriving at the clinic, until now?" this was asked as patients were called into their first meeting with the doctor/consultant. These questions were asked on separate visits, with two weeks spent asking each question, if it was noticed during the second set of question that a patient involved in the first set of questions was also present then this patient was not involved in the second series of interviews, to avoid any risk of bias. In the case of the second question, the perception question, the patients were selected on arrival and tracked through out the visits. In the case of the first question, the patients involved were observed and recorded throughout their visit. As well as the question, other elements were observed, the patient identified their age group from the following range, under 35, 36-45, 46-55, 56-65 and over 65. The time of arrival was observed, time of entry into the nurses room for an initial eye test, time of entry into the doctor/consultant and time of departure from the clinic, along with the actual time of their appointment. The actual recorded information was: Patients arrival time Age grouping Patient sex (M/F) Whether they were accompanied or not How long the patient waited before their eye test How long they waited before their first consultation What time they left the clinic. Results. The results of this research provided a large volume of data, therefore only selected results and outcomes that cover the main areas and issues are included. The initial table (table 1.) is a summary of the previous research, as this work was specifically aimed at testing the result of that research. Within this work, the entire sample covered 639 patients, out of a population of the clinic over this period of 1070. Of this population 44.6% were female (385), and 55.4% (354) male. 313 patients were involved in the second question (perception) and 326 in the first question (expectation). These facts can be compared with the initial research statistics in table 2.
Table 1: A Summary of Results from the Patient Survey from July 2000 Sample size Population Perceived Wait Expected Wait Difference Perception Actual Wait Total Stay expectation Overall Results 280 695 48.81 41.63-7.18 54.32 86.51 % First Visit 44 6.33 41.12 37.19-3.21 51.50 80.21 Repeat visit 236 33.95 50.24 42.32-7.92 54.84 87.68 Female 150 21.58 49.02 42.09-6.93 56.52 84.07 Male 130 18.7 50.86 36.85-14.01 56.09 83.90 Solo 150 21.56 46.19 39.58-6.61 55.72 87.14 Accompanied 130 18.7 51.96 39.27-12.69 54.28 85.04 < 55 156 22.44 49.11 42.66-6.45 57.34 86.53 > 55 88 12.66 46.17 36.14-10.03 53.57 80.14 Table 2: Summary of the 2 years Research Population data 2001 2000 Population % Population % Overall Sample Size 639 59.7 280 40.23 Total clinic population 1070 695 First Visit 111 17.4 44 15.7 Repeat visit 528 82.6 236 84.3 Female 340 53.2 150 53.3 Male 299 46.8 130 46.4 Solo 340 53.2 150 53.6 Accompanied 299 46.8 130 46.4 < 55 530 82.9 156 68.6 > 55 109 17.1 88 31.4 A general summary of the result for the following year's research from 2001 can be seen on table 3. Table 3: A Summary of Results from the Patient Survey from July 2001 Sample size Population Perceived Wait Expected Wait Difference Perception expectation Actual Wait Overall Results 639 % 47.0 34.4-12.6 56.3 83.4 First Visit 111 17.4 51.0 34.4-16.6 58.2 98.4 Repeat visit 528 82.6 46.3 34.4-11.9 55.9 80.3 Female 354 55.4 46.2 35.0-11.2 55.9 86.2 Male 285 44.6 47.9 33.5-14.4 56.8 79.9 Solo 340 53.2 43.2 34.5-8.7 54.9 79.5 Accompanied 299 46.8 51.0 34.4-16.6 58.2 87.6 < 55 530 82.9 42.9 37.9-5.0 57.8 86.0 > 55 109 17.1 47.6 33.6-14.0 56.0 82.9 < 35 19 3.0 67.5 32.7-34.8 53.5 82.8 36-45 31 4.9 43.5 45.7 + 2.2 57.5 88.7 46-55 59 9.2 42.9 36.7-6.2 59.3 85.6 56-65 125 19.6 45.6 34.4-1.2 55.5 83.0 > 65 405 63.3 47.6 33.4-14.2 56.2 82.8 Total Stay
Other Results The patients arrival pattern. Table four shows the arrival time from the entire population Table 4: Arrival times Population No of patients % Early (+) Late (-) minutes Total 639 Over 55 531 83.1 +17.23 Under 55 108 16.9 +12.13 Over 65 406 63.5 +16.5 56-65 125 19.6 +17.6 46-55 58 9.1 +13.7 36-45 31 4.8 +12.2 > 35 19 3.0 +7.2 Over 55 Male 233 36.4 +15.9 Female 298 46.6 +17.6 Under 55 Male 51 8.1 +9.0 Female 57 8.9 +9.6 Over 65 Male 175 27.4 +15.5 Over 65 Female 231 36.0 +17.4 56-65 Male 58 9.1 +17.2 56-65 Female 67 10.5 +18.7 46-55 Male 25 3.9 +18.4 46-55 Female 33 5.2 +10.2 36-45 Male 17 2.7 +14.2 36-45 Female 14 2.2 +9.6 > 35 Male 9 1.4 +6.3 > 35 Female 10 1.6 +7.9 Table five shows the arrivals at specific time intervals. Table 5. The arrival rate Time of arrival No of patients % Over 60 mins late 1 0.1 30-60 mins late 5 0.8 10-29 mins late 12 1.9 5-10 mins late 20 3.1 0-5 mins late 41 6.4 0-5 mins early 79 13.4 5-10 mins early 106 16.6 10-15 mins early 110 17.2 15-30 mins early 171 26.8 30-60 mins early 74 11.6 Over 60 mins early 20 3.1
From these two tables (table 5. and 6.) a series of issues start to emerge, for example the "time rich, time poor" issue. Here 88.7% of the population arrived early. But, those arriving early are more likely to be over 55, the average time of arrivals of the over 55 group as 17.2 minutes, as against an arrival time of 12.2 minutes for those under 55. The younger the age group, the nearer the actual appointment time they arrived, with the under 35 group arriving 7.2 minutes early (the males 6.3 and females 7.9). But the late arrivals show no such correlation, as can be seen in table six. This shows how the younger the patient the more likely they are to be late, with the exception of the over 65 males to the 56-65 male group. The Sample Table 6. Later arrivals Population Mix Number % % of group Total 50 Over 55 39 78 7.3 Under 55 11 22 10.1 <65 Male 18 36 10.3 Female 11 22 4.8 56-65 Male 5 10 8.6 Female 5 10 7.5 46-55 Male 4 8 16 Female 0 0 0 36-45 Male 3 6 17.5 Female 1 2 7.1 >35 Male 0 0 0 Female 3 6 30 In order to compare the two sets of information it is important to consider the format of the two populations, and if the differences might significantly effect the results and therefore the conclusions. Clearly the population was much greater and is a larger percentage of the total clinic population for the month. However, the actual number of patients seen by the clinic had increased by 53.0% from the previous year. Within the sample mix the number of first visit patients rose by 1.7%, the male female split was very similar, 2002 having changed by only 0.4%, a similar change occurring in the solo and accompanied patient sample. However, there was a significant change in the age of the population with an increase of 14.3% in the over 55 group, seeing the population of over 55 group rise to 82.0% from 68.6%. Another element that needs to be considered here is that during the 2001 survey the patients actual age was asked, whereas the age split during the 2000 research was simply an observation of the researcher, which could have caused such a change. Table 7. Demographic of the 2001 population Perception population Expectation population Age Total Male Female Male Female > 35 19 4 2 5 8 36-45 31 10 7 7 7 46-55 59 9 16 16 18 56-65 125 35 25 23 42 < 65 405 90 116 85 114
Other elements of the population that needs to be noted are the size of the age groups, which can be seen in table seven, and the split between female and male. One of the areas that becomes clearer here is the size of the groups, for example the under 35 group, the size of the population of the Male/Female split for the under 35 and 36-45 groups, where the population ranges from 9 to 17, again very small. The issue here is that the size of the population of the groups between under 35 and the 46-55 age range are generally small, too small to really make significant conclusions for these groups particularly the individual male/female split. Although the increase in first visit patients was only 1.7% it was a significant volume, from 44 to 111. A large increase in number of first time glaucoma patients has a significant influence on the overall time spent in the clinic by first time patients, because first visit glaucoma patients can be in the clinic for up to 4 hours (240 minutes) against an overall average of 83.4 minutes. This can be the cause of the increase in first time visit total rising from 80.21 minutes in 2000, some 6.30 minutes less than the average to 98.4 minutes, 15 minutes longer that the average in 2001. The remainder of the basic data show small but acceptable differences. The reason for this research was to revisit the work of the previous year to see if the unexpected outcomes regarding accompanied and unaccompanied patient had been true or a 'one off' exception. In 2000 the research discovered that the difference between expectations and perceptions of the unaccompanied patients was significantly shorter than those of the accompanied patients, whereas the expectations were similar, both as far as the general population and each other (solo patients perception 46.19 minutes expectation 39.58, whereas the accompanied patients perception was 51.96 against an expectation of 39.58). In the repeat sample this was replicated, with the following results set out in table 7. This clearly repeats the unexpected results of the previous year, however there is a difference in the actual wait, so the figures set out in table seven weight the Solo Patients results to show a similar actual waiting time, but here the result still show a significant difference, which again contradicts all previous research in this area. Table 7 weighted waiting times Actual wait Perception of wait Expected wait Solo Patients (340) 2001 54.9 45.8 36.6 Accompanied Patients (299) 2001 58.2 51.0 34.4 Solo Patients (150) 2000 55.7 46.19 39.58 Accompanied Patients (130) 2000 54.3 51.96 39.27 Recommendations and Conclusions This research clearly shows that hospital outpatient clinics have in some way different characteristics in their queueing behaviour to many other queuing operations, which needs consideration if management are to use this in order to improve their queueing management and levels of patient satisfaction. Initially it is worth considering the possible reasons for this outcome occurring. Why, should the accompanied patients, (group waits) feel longer then Solo waits, in this type of situation? The first possible reason for this may lie in the reason for the visit, if we consider Maister's (1985) seventh proposal, the more valuable the service, the longer the customer will be prepared to wait. Consider this with respect to the situation at a hospital's eye clinic, there the
value of the wait for the patient, is considerable. For example, any patient visiting an eye clinic, clearly has a problem with their eyes, or one of their eyes, and might be worried at the prospect of going blind. In this case the value of the wait would be very high, whereas the accompanying "friend" is likely to have no value to their wait. The reason for their wait is simply to assist/accompany a "friend", that is as a favour, or even a chore. Thus the longer the wait becomes the more testing the wait will become for the "friend", many of these "friends" will have other places to be, jobs which they could be doing, all of which are likely to have a higher value. This means that a clinic should consider the value of encouraging patients to come alone, or suggest that they are left on their own to be collected later, at the end of their visit. The next area for consideration is the effect of the first service encounter, that is the initial arrival and wait for the nurse's eye inspection. Here it is essential to give the right impression to the patient. Since the first research programme, the clinic have changed the letters, they send out to their patients, advising them of the potential wait. This advice is specific to each group, so for example the new glaucoma patients are advised that their first visit may take up to 4 hours, but by the end the consultant will be able to give a full diagnostic decision. Along with this advice the letter tells the patient of their appointment time and asks them to arrive on time, and no more than 15 minutes early. However, from the result seen in tables four and five it appears that this has been interpreted as it is OK to arrive early, and up to 15 minutes is fine. In fact if you couple the arrival times to the information in table 8 related to the time taken to see the nurse, then the issues becomes even clearer. The patients arriving early are likely to be seen by the nurse (the first encounter) before their actual arrival time. This is likely to encourage patients to continue to arrive early, in anticipation of getting seen earlier! Table 8: Arrival times Population No of patients % Early (+) Late (-) minutes Wait for nurse Total 639 Over 55 531 83.1 +17.23 12.2 Under 55 108 16.9 +12.13 11.3 Over 65 406 63.5 +16.5 11.9 56-65 125 19.6 +17.6 13.1 46-55 58 9.1 +13.7 13.9 36-45 31 4.8 +12.2 13.5 > 35 19 3.0 +7.2 16.7 Over 55 Male 233 36.4 +15.9 11.7 Female 298 46.6 +17.6 12.8 Under 55 Male 51 8.1 +9.0 12.0 Female 57 8.9 +9.6 11.7 Over 65 Male 175 27.4 +15.5 11.2 Over 65 Female 231 36.0 +17.4 11.4 56-65 Male 58 9.1 +17.2 10.9 56-65 Female 67 10.5 +18.7 12.9 46-55 Male 25 3.9 +18.4 11.7 46-55 Female 33 5.2 +10.2 14.1 36-45 Male 17 2.7 +14.2 12.3 36-45 Female 14 2.2 +9.6 14.9 > 35 Male 9 1.4 +6.3 15.9 > 35 Female 10 1.6 +7.9 17.4
Table 9 indicates how these facts fit with the arrival rate data. Table 9. The arrival rate Time of arrival No of patients % Wait for nurse Over 60 mins late 1 0.1 5.0 30-60 mins late 5 0.8 9.8 10-29 mins late 12 1.9 9.8 5-10 mins late 20 3.1 9.8 0-5 mins late 41 6.4 10.3 0-5 mins early 79 13.4 10.1 5-10 mins early 106 16.6 13.0 10-15 mins early 110 17.2 12.1 15-30 mins early 171 26.8 12.4 30-60 mins early 74 11.6 13.7 Over 60 mins early 20 3.1 12.0 Both table eight and nine highlight a problem that this poses, if the patients are being seen prior to their appointment, then it will appear as though their early arrival has been beneficial. However, there is a second problem, that if they are seen early they may have to wait longer to see the consultant. This early treatment by the nurse could have a detrimental effect on their overall perception. Whereas, if they were seen within the same time scale after their appointment, this would have the beneficial benefit of being a way of breaking up their wait, an in process activity, which was identified as being beneficial in the proposal of Maister (1983). It is worth noting that of the patients arriving early, only those arriving up to 10 minutes early were, on average, seen after their arrival time. (For example patients arriving between 10 and 15 minutes early were seen within 13 minutes of their appointment time. Major recommendations: A: Patients should be advised of their wait, that is a true maximum time that their wait and stay in the clinic is likely to be. This is an important issue as it will effect their expectations, and throughout this research the patients expectation have been unrealistic. The average expectation during 2001 was 34.4 minutes, with a high of 37.9 minutes from the over 55 group and 32.7 from the under 35, whereas a year earlier the average expectation was 41.6 minutes with the over 55's expecting a wait of 42.7 and the under 55's a wait of 36.1. Here we can see how the patients expected waiting time has reduced, possibly as an effect of all the publicity from the government about achieving reducing patient's waiting times. It might even be worth considering obfuscating the time, in line with the "Disney" approach where the anticipated waiting time for rides is overstated. This will have a direct effect on patient expectations. B: Patients should be sent away if they arrive more than 15 minutes early, in fact this could be reduced, but it is likely to cause complaints if it is less than 15minutes. This is to emphasise the issue that appointment time s are individual appointment times and not "block booking times", which many patients believe them to be. Therefore encouraging the patient to actually arrive on time. The second point is that this will result in a better appearance to the waiting area, often an over crowded area, which is likely to have a negative effect on the patients approach to waiting. This will have a positive effect on patient perception and expectation. C: The nurses operating the first eye test should be advised/encouraged to see patients only after their arrival time, so emphasising the fact that the times have a reason, and that the clinic
operates a true appointment system. This will also have a positive effect on the patients perception. D: Patients should be encouraged to come on their own, and when they are accompanied, their friend(s) should be encouraged to leave them and return later. The clinic should offer to call them at a specific time prior to the end of their visit, (as is done for patients using the hospital transport system), or given a time for their return. E: In addition to coming on their own, they should be advised to bring with them items to occupy their waiting times, books, walkman etc. This will have a direct effect on patients perception F: The clinic must advise the patients of the clinics running that day, and the anticipated wait for each clinic, along with anticipated time of the total visit. This will have an effect on the patient wait perception, and stop patients getting upset if other patients are seen by the doctor earlier than they are because of differences between the clinical service times. G: Consider effective use of diversionary tactics, such as appropriate use of entertainment, television, radio etc., literature and education. H: Booking allocation - the clinic needs to consider balancing the booking to provide an appropriate mix of first visit and repeat patients, this will help the patient perception. Table 10 Management of Patient Expectation and Perception Actions Expectation Perception A: Advise true or obfuscate the waiting time B: Send patients arriving over 15 minutes early away C: Nurses eye test to operate in line with appointment times D: Come alone E: Patient to bring entertainment materials F: Information G: Entertainment H: Patient booking allocation The aim of this research was to investigate patients waiting experiences in an out-patients clinic, and specifically to see if the research carried out a year earlier, which had contradicted one of Maister's propositions regards queueing psychology, was correct on not. This research involved a larger population, and was more detailed than the first research, it has clearly shown that Maister's proposition that "Solo Waits Feel Longer than Group Waits" is not true in the case of long waits in areas like hospital out patients clinics. References: Aviel 1996 Amednews. (1999) "Council urges plan to expand health coverage, Geri Aston June 14. Assistant Secretary for Legislation (ASL) Dept. of Health & Human Service USA (1997) Testimony on Long-term Future for the Medicare Program by B.C.Vladeck. US Dept. of Health Care Financing Administration Feb. 12. 1997 Barlow, G.L. (2002a) "Audition hospital queueing" Managerial Auditing Journal Vol. No. 7 pp.397-404
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