Overview
Rebekah is a PhD student based in the Health Economics Group. Her research centres around the elicitation of preferences towards cancer diagnostic testing and screening.
Prior to beginning her PhD, Rebekah worked as a Graduate Trainee Assistant in the department and worked on a mixture of projects relating to health economics.
Qualifications
- BSc (Hons) Economics
- MSc Health Economics and Decision Modelling
Research
Research interests
My primary research interests focus around methods used to elicit preferences towards healthcare interventions, specifically discrete choice experiments and best-worst scaling.
Research projects
- Thesis title: Exploring preferences towards testing for ovarian cancer
Publications
Key publications | Publications by category | Publications by year
Publications by category
Journal articles
Hall R, Medina-Lara A, Hamilton W, Spencer A (In Press). Attributes used for cancer screening discrete choice experiments: a systematic review. The Patient: Patient Centered Outcomes Research
Hall R, Medina-Lara A, Hamilton W, Spencer AE (2022). Correction to: Attributes Used for Cancer Screening Discrete Choice Experiments: a Systematic Review.
Patient,
15(3), 379-381.
Author URL.
Hall R, Medina-Lara A, Hamilton W, Spencer A (2022). Women’s priorities towards ovarian cancer testing: a best–worst scaling study.
BMJ Open,
12(9), e061625-e061625.
Abstract:
Women’s priorities towards ovarian cancer testing: a best–worst scaling study
ObjectiveTo investigate the importance of key characteristics relating to diagnostic testing for ovarian cancer and to understand how previous test experience influences priorities.DesignCase 1 best–worst scaling embedded in an online survey.SettingPrimary care diagnostic testing in England and Wales.Participants150 women with ovaries over 40 years old living in England and Wales.MethodsWe used best–worst scaling, a preference-based survey method, to elicit the relative importance of 25 characteristics relating to ovarian cancer testing following a systematic review. Responses were modelled using conditional logit regression. Subgroup analysis investigated variations based on testing history.Main outcome measuresRelative importance scores.Results‘Chance of dying from ovarian cancer’ (0.380, 95% CI 0.26 to 0.49) was the most important factor to respondents, closely followed by ‘test sensitivity’ (0.308, 95% CI 0.21 to 0.40). In contrast, ‘time away from usual activities’ (−0.244, 95% CI −0.33 to −0.15) and ‘gender of healthcare provider’ (−0.243, 95% CI −0.35 to −0.14) were least important to respondents overall. Women who had previously undergone testing placed higher importance on certain characteristics including ‘openness of healthcare providers’ and ‘chance of diagnosing another condition’ at the expense of reduced emphasis on characteristics such as ‘pain and discomfort’ and ‘time away from usual activities’.ConclusionsThe results clearly demonstrated items at the extreme, which were most and least important to women considering ovarian cancer testing. Differences in priorities by testing history demonstrate an experience effect, whereby preferences adapt over time based on evidence and experience. Acknowledging these differences helps to identify underlying barriers and facilitators for women with no test experience as well as shortcomings of current service based on women with experience.
Abstract.
Publications by year
In Press
Hall R, Medina-Lara A, Hamilton W, Spencer A (In Press). Attributes used for cancer screening discrete choice experiments: a systematic review. The Patient: Patient Centered Outcomes Research
2022
Hall R, Medina-Lara A, Hamilton W, Spencer AE (2022). Correction to: Attributes Used for Cancer Screening Discrete Choice Experiments: a Systematic Review.
Patient,
15(3), 379-381.
Author URL.
Hall R (2022). Exploring women’s preferences towards ovarian cancer testing: applications of discrete choice experiments.
Abstract:
Exploring women’s preferences towards ovarian cancer testing: applications of discrete choice experiments
Background
Despite an increasing emphasis on shared decision-making in healthcare settings, judgements relating to diagnostic testing for cancer remain largely provider-driven. Evidence suggests involving patients in care and treatment decisions improves outcomes, boosts satisfaction and increases knowledge, self-advocacy and adherence. This thesis used ovarian cancer as an exemplar to demonstrate how discrete choice experiments (DCEs) can be used to understand preferences towards cancer testing with the purpose of improving diagnostic outcomes in primary care.
Methods
The thesis began with a systematic review of existing DCEs in the field of cancer testing. Proceeding chapters described the development and implementation and of a DCE eliciting preferences towards ovarian cancer. Barriers to ovarian cancer diagnosis mean the development of an ovarian cancer screening programme continues to be a priority, despite a lack of efficacy within clinical trials to date. In response, a further DCE investigated preferences towards ovarian cancer screening, specifically focusing on the benefit-harm trade-offs. A final component of this thesis sought to investigate methodological challenges relating to the application of DCEs in the field of cancer testing. Specific investigations included the presence and impact of indifferent preferences and stated attribute non-attendance.
Results
The systematic review demonstrated the current neglect of preferences in diagnostic settings and highlighted several methodological challenges that may limit the application of discrete choice findings to clinical and policy-related settings.
Demand for diagnostic testing was high, even when the risk of cancer was as low as 1%. Preferences appeared to centre around the trade-off between accuracy and timeliness. Although test accuracy was consistently found to be the most important attribute to respondents even where additional waiting times have a substantial impact on survival.
Preferences towards ovarian cancer screening were more heterogeneous. Latent class analysis revealed approximately half of respondents strongly prioritised mortality reduction while remaining respondents placed low importance on this aspect of testing and instead largely focused on the high presence of false positive results.
Conclusion
This thesis demonstrates women’s willingness and ability to engage in diagnostic decision-making. Preference heterogeneity further highlights the importance of an individualised approach to care. Comparisons of preferences in screening and diagnostic settings demonstrate fundamental differences, suggesting the large body of cancer screening DCEs are not automatically transferable to diagnostic settings. A greater understanding of preferences and priorities about testing in symptomatic populations is needed. In response, this thesis provides an insight into some of the challenges when conducting DCEs in this domain and offers suggestions for future researchers.
Abstract.
Hall R, Medina-Lara A, Hamilton W, Spencer A (2022). Women’s priorities towards ovarian cancer testing: a best–worst scaling study.
BMJ Open,
12(9), e061625-e061625.
Abstract:
Women’s priorities towards ovarian cancer testing: a best–worst scaling study
ObjectiveTo investigate the importance of key characteristics relating to diagnostic testing for ovarian cancer and to understand how previous test experience influences priorities.DesignCase 1 best–worst scaling embedded in an online survey.SettingPrimary care diagnostic testing in England and Wales.Participants150 women with ovaries over 40 years old living in England and Wales.MethodsWe used best–worst scaling, a preference-based survey method, to elicit the relative importance of 25 characteristics relating to ovarian cancer testing following a systematic review. Responses were modelled using conditional logit regression. Subgroup analysis investigated variations based on testing history.Main outcome measuresRelative importance scores.Results‘Chance of dying from ovarian cancer’ (0.380, 95% CI 0.26 to 0.49) was the most important factor to respondents, closely followed by ‘test sensitivity’ (0.308, 95% CI 0.21 to 0.40). In contrast, ‘time away from usual activities’ (−0.244, 95% CI −0.33 to −0.15) and ‘gender of healthcare provider’ (−0.243, 95% CI −0.35 to −0.14) were least important to respondents overall. Women who had previously undergone testing placed higher importance on certain characteristics including ‘openness of healthcare providers’ and ‘chance of diagnosing another condition’ at the expense of reduced emphasis on characteristics such as ‘pain and discomfort’ and ‘time away from usual activities’.ConclusionsThe results clearly demonstrated items at the extreme, which were most and least important to women considering ovarian cancer testing. Differences in priorities by testing history demonstrate an experience effect, whereby preferences adapt over time based on evidence and experience. Acknowledging these differences helps to identify underlying barriers and facilitators for women with no test experience as well as shortcomings of current service based on women with experience.
Abstract.
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