The 1991 reforms to Britain's health service established a quasi-market where the purchasing function was performed by health authorities and those general practices that joined the fund-holding scheme. Whilst the literature lacked any direct comparison of the performance of these agencies as purchasers, there was much controversy about the equity implications of the system. Most notably this focused upon alleged differences in the waiting times for hospital services of patients registered with fund-holding and non fund-holding practices. However, such allegations were based on anecdotal evidence and open to contradiction. The thesis moves this debate beyond a reliance on anecdotal evidence and for one service, elective surgery, redresses the lack of evaluation in the relative merits of fund-holders and health authorities as purchasers. The waiting times of fund-holding and non fund-holding patients for operations covered by the fund-holding scheme were compared at four public providers over a four-year period. Fund-holding patients from the elective waiting list generally had significantly shorter waits than their non fund-holding counterparts. Because such trends became evident after practices joined the scheme, shorter waits were linked to fund-holding status. Another important aim was to ascertain why this tendency occurred. A series of hypotheses were tested, including the generosity of fund-holders' budgets, contrasts in the surgical case mix of each population, plus differences in the way fund-holders and health authorities perform their purchasing roles. An aspect of this last hypothesis was confirmed. Hospitals admitted fund-holding patients sooner to dissuade fund-holding practices from referring elsewhere. This connects to the income hospitals receive from fund-holders being more closely attributable to actual patient throughput than was the case with their income from health authorities. In discussing the policy implications of the study, the thesis then addresses how public sector quasi-markets can work in the contexts of both equity and efficiency.

Magister Commercii (Information Management) - MCom(IM) / At public sector health facilities in Cape Town, South Africa, patients experience very high waiting times, with a medium waiting time of 3 hours which prevailed at the study facility being common. So the question arose as to why waiting times are so very high and what could be done to reduce them? While for the facility under investigation the immediate causes of the high waiting times were known, the underlying causes were quite opaque. A concern expressed therefore, was that if the underlying causes were not uncovered then efforts to reduce waiting times might not be successful, as they would just address the immediate causes. The legitimacy of the concern derives from the view that if underlying causes are not addressed, then they will continue to exert an influence on the immediate causes, and therefore perpetuate the environment which creates fertile ground for immediate causes to arise and persist, with resultant persistence of high waiting times. Hence, my interest to undertake research to explore the underlying causes of high waiting times. / 2018-12-14

The cumulative likelihood of admission estimated for any given 'time-since-enrolment' depends on how we define membership of the population 'at-risk' and on how we handle right and left censored waiting times. As a result, published statistics will be biased because they assume that the waiting list is both stationary and closed and exclude all those not yet or never to be admitted. The cumulative likelihood of admission within three months was estimated using the Government Statistical Service method and compared with estimates which relaxed the assumption of stationarity and reflected variation in the numbers recruited to, and admitted from, the waiting list each quarter. The difference between the two estimates ranged from +5.5 to -9.1 percentage points among 11 Orthopaedic waiting lists in South Thames Region. In the absence of information on 'times-to-admission', exact 'times-since-enrolment' were extracted from Hospital Episode Statistics and assumed to be similarly distributed. In the absence of information on 'times-to-competing-event', the number of competing events falling in each waiting time category was estimated by differencing. A period lifetable was constructed using these approximations, census counts, counts of the number of new recruits and estimates of the number 'reset-to-zero' each quarter. The results support the view that the method used by the Government Statistical Service overestimates the cumulative likelihood of elective admission among those listed. The Government Statistical Service calculates the cumulative likelihood of admission within three months (range: 0.62-0.27) conditional on the fact of admission. Multiplying by the unconditional likelihood of being admitted (range: 0.93-0.31) estimates the cumulative likelihood of admission within three months among those listed (range: 0.55-0.12) and gives a rather different ranking of waiting list performance among 34 Orthopaedic waiting lists in South Thames Region.

The main subject matter of this thesis concerns radiotherapy patient scheduling subproblems formulated as four separate shop scheduling problem models (i.e. hybrid flowshop, flowshop, mixed shop and multiple identical parallel machine scheduling problems) based on the characteristics of the intricate real-life treatment processes observed at the Arden Cancer Centre in Coventry, UK. Insight into these processes was gained by developing and using a novel discrete-event simulation (DES) model of the four units of the radiotherapy department. By typifying the subproblems as well-known scheduling problem models, it was intended that methods amenable to them such as heuristics be used in the study. Four novel constructive heuristics based on priority dispatching rules and strategies adapted from some established algorithms have been developed and implemented using the C++ programming language. Further, these heuristics were incorporated into the DES model to create schedules of appointments for the patients generated daily. The effectiveness and efficiency of the constructive heuristics have been tested using the following performance criteria: minimising i) average waiting time to the start of treatment, and ii) average percentage of patients late for their treatment, and iii) the amount of overtime slots used for the patients received in a given period of time. The coordinated constructive heuristics and the DES model have also been tested using possible alternative pathways patients can follow in the treatment unit. The aim of these tests was to compare the efficiency of the radiotherapy department’s current pathway to other possible pathways. Further, strategies for using maximum allowed breaches of targeted due dates, reserved slots for critical treatments and overtime slots was also included in the heuristics. The results of several tests showed that the heuristics created schedules of appointments whose average waiting times for emergency, palliative and radical treatments improved by about 50%, 34% and 41%, respectively, compared to the historical data. However, their major slack was evidenced by the fact that about 13% of the patients needing palliative treatment were expected to be late for treatment compared to about 1% of those requiring radical treatment.

Master of Public Health - MPH / Background: The appointment system learning initiative (ASLI) was introduced in 2016 as a way of implementing appointment systems in the City of Cape Town, in response to lengthy waiting times at PHC facilities It was intended as a safe space for learning, and piloted facility-generated planning in which knowledge was shared in workshops over 18 months. Variability in how well appointment systems had taken root was noted at the second feedback workshop. Currently, there is little information on the experiences, perceptions and roles of managers with regard to the initiative, or what unforeseen issues may have had an impact. Aim: This study aimed to reach an understanding of how the Appointment Systems Learning Initiative approach and its implementation was experienced by participating facility and PPHC managers at City Health facilities in Cape Town. This includes an exploration of the roles and experiences of health managers, including their perceptions of the benefits and challenges of the process. Methods: A qualitative, exploratory design was used. Individual, semi-structured interviews were conducted with a sample of twelve facility managers and two PPHC managers. Manager’s roles were analysed deductively according to Mintzburg’s 2009 framework, while other data analysis was inductive. Ethical clearance was obtained from UWC BMREC prior to commencement. Informed consent was obtained from participants and confidentiality was preserved at all stages of research. Results: Managers viewed the learning experience positively and felt that facility-generated planning was preferable to hierarchical imposition of programmes. They found it motivating to learn how other facilities had solved problems and designed their systems. Contextual changes to the health system affected ASLI by increasing the pace and prescriptiveness of implementation, and impeded the capacity for PPHC managers to offer support. Facility managers fulfilled critical leadership roles according to Mintzberg’s model, but the way in which they carried out roles such as delegation, team building or communicating may have affected implementation. Challenges included issues with human resources, insufficient time available for managing implementation, lack of preparation beforehand, insufficient support and contextual changes. Benefits included shorter working hours for staff, better organisation in facilities, shorter waiting times and improved satisfaction for end-users.

Magister Public Health - MPH / Long waiting times have, for many years, been synonymous with primary health care in South Africa, and this is evident by the long queues and consistent client dissatisfaction. There are multiple contributing factors that exacerbate waiting time in Primary Health Care (PHC) facilities such as shortage of health care providers, increase in the uninsured population and South Africa’s quadruple burden of diseases. Health establishments have initiated numerous strategies to reduce long waiting times with varying degrees of success. These strategies have mostly been quantified and linked to indicators to measure their level of success in relation to quality healthcare. This research explores the clients’ perception of one such intervention, which is the implementation of an appointment system in primary care facilities in the City of Cape Town. Qualitative, exploratory descriptive methods were used to gain understanding of the impact the appointment system has had on the clients’ experience of attending health care services. The researcher also explored how clients perceive their role with regard to the shaping of their clinic’s appointment system. Semi-structured in-depth interviews were conducted with fifteen purposively sampled clients from five City Health clinics, who have implemented an appointment system through the guidance of the Appointment System Learning Initiative (ASLI). Maximum variation in sampling ensured the inclusion of small, medium and larger facilities within different geographical settings. Data analysis was done using a thematic coding approach, the themes were derived from the emerging data and were used to guide the researcher in gaining a rich picture of the clients’ experiences within the clinics. Ethical approval was requested and received from both the University of the Western Cape (UWC) and City Health prior to engaging any participants.

Magister Commercii (Information Management) - MCom(IM) / Long waiting times before receiving a health service, give rise to long queues and congested health facilities, both of which are unnecessary and avoidable. Since patients in part judge the quality of the service by the length of time they spent waiting for it, it is imperative to measure waiting times, and determine and mitigate the immediate and underlying causes of lengthy waits. The facility under investigation was known to have excessively long waiting times. Since the immediate causes of long waiting times were known, it was thus required to research and understand the underlying causes of long waiting times and consequently whether there were any barriers to implementing recommendations to reduce waiting times at this primary health care facility. AIM: The aim of the study was to determine the underlying causes of long waiting times and the barriers to implementing recommendations to reduce waiting times. METHODS: A quantitative cross-sectional analytical study with a small qualitative component was undertaken. The qualitative study took a workshop format by piggy-backing onto feedback sessions held to present the results of the previously conducted waiting time survey to staff. Staff commentary at the workshops on possible underlying causes and barriers to recommendations to reduce them, were then used to develop a questionnaire for the quantitative portion of the study. The population and sample for the qualitative part of the study were all staff working at the facility who attended the feedback sessions. The cross-sectional descriptive quantitative study intended to uncover what underlying causes affected long waiting times, what recommendations could be explored to mitigate long waiting times and improve the patient experience, and if there were any barriers to these recommendations. The quantitative study population and sample were all staff who worked at the facility for more than six months and all patients who had utilised the services at the facility for three or more times. Data was collected using structured questionnaires, which were different for staff and patients. A detailed descriptive analysis was conducted.

Magister Commercii (Information Management) - MCom(IM) / Long waiting times before receiving a health service, give rise to long queues and congested health facilities, both of which are unnecessary and avoidable. Since patients in part judge the quality of the service by the length of time they spent waiting for it, it is imperative to measure waiting times, and determine and mitigate the immediate and underlying causes of lengthy waits. The facility under investigation was known to have excessively long waiting times. Since the immediate causes of long waiting times were known, it was thus required to research and understand the underlying causes of long waiting times and consequently whether there were any barriers to implementing recommendations to reduce waiting times at this primary health care facility. Aim: The aim of the study was to determine the underlying causes of long waiting times and the barriers to implementing recommendations to reduce waiting times. Methods: A quantitative cross-sectional analytical study with a small qualitative component was undertaken. The qualitative study took a workshop format by piggy-backing onto feedback sessions held to present the results of the previously conducted waiting time survey to staff. Staff commentary at the workshops on possible underlying causes and barriers to recommendations to reduce them, were then used to develop a questionnaire for the quantitative portion of the study. The population and sample for the qualitative part of the study were all staff working at the facility who attended the feedback sessions. The cross-sectional descriptive quantitative study intended to uncover what underlying causes affected long waiting times, what recommendations could be explored to mitigate long waiting times and improve the patient experience, and if there were any barriers to these recommendations. The quantitative study population and sample were all staff who worked at the facility for more than six months and all patients who had utilised the services at the facility for three or more times. Data was collected using structured questionnaires, which were different for staff and patients. A detailed descriptive analysis was conducted. Results: The study found a number of potential underlying causes for each immediate cause of long waiting times at the facility. For early morning batching the underlying causes found were: 45% of patients were given early appointments which caused clients to arrive early; 100% of patients with appointments after 10H00 arrived before 10H00; and 43% of the patients stated that they arrived early because they feared being turned away.

Due to the steady increased in public transportation demand, there is a need to provide more desirable and user-friendly transit systems. Typically, the public transportation timetables are modeled as an assignment problem, which often has objectives such as reducing the cost of operation, minimizing waiting time between transfer points or improving the quality of performance. This research considers the problem of developing synchronized timetables for bus transit systems with fixed routes when a waiting time limit exist at each transfer stops, for the passengers making connections. The objective of this research is to have maximum number of simultaneous arrivals. Different to previous studies, a simultaneous arrival' has been defined as an arrival of buses of different routes at a transfer point such that the time between these arrivals do not exceed the passenger waiting time range associated with the transfer stop. In other words, at each node, an upper bound and a lower bound are set for the arrivals of two buses and these buses are run within this allowable window. The heuristic developed has been modeled as a mixed integer linear programming problem and applied to some real life problems to evaluate the outcomes. The total number of synchronizations obtained by the model was compared to the maximum possible simultaneous arrivals at each node. Results show that a larger number of simultaneous arrivals are obtained when the waiting time ranges are relaxed. Finally some important applications of the proposed model compared to the existing models are presented.

This thesis investigates whether variations in wait times for different medical specialties have a significant impact on the proportion of people who choose to opt out of the public insurance system in their country. Canada presents an interesting case study because it is one of the few nations with a single-payer system for all procedures covered by the public health system. As a result, leaving Canada is the equivalent of opting into the private system in other countries where socialized medicine is available side by side to a private market provider. The results provide some evidence of a positive relationship, but are somewhat sensitive to the chosen sample period.