Patients’ online descriptions of their experiences as a measure of healthcare quality

Introduction Patients are describing their healthcare experiences online using rating websites. There has been substantial professional opposition to this, but the government in England has promoted the idea as a mechanism to improve healthcare quality. Little is known about the content and effect of healthcare rating and review sites. This thesis aims to look at comments left online and assess whether they might be a useful measure of healthcare quality. Method I used a variety of different approaches to examine patients’ comments and ratings about care online. I performed an examination of the comments left on the NHS Choices website, and analysed whether there was a relationship between the comments and traditional patient surveys or other measures of clinical quality. I used discrete choice experiments to look at the value patients place on online care reviews when making decisions about which hospital to go to. I used natural language processing techniques to explore the comments left in free text reviews. I analysed the tweets sent to NHS hospitals in England over a year to see if they contained useful information for understanding care quality. Results The analysis of ratings on NHS Choices demonstrates that reviews left online are largely positive. There are associations between online ratings and both traditional survey methods of patient experience and outcome measures. There is evidence of a selection bias in those who both read and contribute ratings online – with younger age groups and those with higher educational attainment more likely to use them. Discrete choice experiments suggest that people will use online ratings in their decisions about where to seek care, and the effect is similar to that of a recommendation by friends and family. I found that sentiment analysis techniques can be used classify free text comments left online into meaningful information that relates to data in the national patient surveys. However, the analysis of comments on Twitter found that only 11% of tweets were related to care quality. Conclusions Patients rating their care online may have a useful role as a measure of care quality. It has some drawbacks, not least the non-random group of people who leave their comments. However, it provides information that is complementary to current approaches to measuring quality and patient experiences, may be used by patients in their decision-making, and provides timely information for quality improvement. I hypothesise that it is possible to measure a ‘cloud of patient experience’ from all of the sources where patients describe their care online, including social media, and use this to make inferences about care quality. I find this idea has potential, but there are many technical and practical limitations that need to be overcome before it is useful.Open Acces

Multidisciplinary group performance—measuring integration intensity in the context of the North West London Integrated Care Pilot

Introduction: Multidisciplinary Group meetings (MDGs) are seen as key facilitators of integration, moving from individual to multidisciplinary decision-making, and from a focus on individual patients to a focus on patient groups. We have developed a method for coding MDG transcripts to identify whether they are or are not vehicles for delivering the anticipated efficiency improvements across various providers and apply it to a test case in the North West London Integrated Care Pilot. Methods: We defined ‘integrating’ as the process within the MDG meeting that enables or promotes an improved collaboration, improved understanding, and improved awareness of self and others within the local healthcare economy such that efficiency improvements could be identified and action taken. Utterances within the MDGs are coded according to three distinct domains grounded in concepts from communication, group decision-making, and integrated care literatures—the Valence, the Focus, and the Level. Standardized weighted integrative intensity scores are calculated across ten time deciles in the Case Discussion providing a graphical representation of its integrative intensity. Results: Intra- and Inter-rater reliability of the coding scheme was very good as measured by the Prevalence and Bias-adjusted Kappa Score. Standardized Weighted Integrative Intensity graph mirrored closely the verbatim transcript and is a convenient representation of complex communication dynamics. Trend in integrative intensity can be calculated and the characteristics of the MDG can be pragmatically described. Conclusion: This is a novel and potentially useful method for researchers, managers and practitioners to better understand MDG dynamics and to identify whether participants are integrating. The degree to which participants use MDG meetings to develop an integrated way of working is likely to require management, leadership and shared values

Computing complexity measures of degenerate graphs

We show that the VC-dimension of a graph can be computed in time $n^{\log d+1} d^{O(d)}$, where $d$ is the degeneracy of the input graph. The core idea of our algorithm is a data structure to efficiently query the number of vertices that see a specific subset of vertices inside of a (small) query set. The construction of this data structure takes time $O(d2^dn)$, afterwards queries can be computed efficiently using fast M\"obius inversion. This data structure turns out to be useful for a range of tasks, especially for finding bipartite patterns in degenerate graphs, and we outline an efficient algorithms for counting the number of times specific patterns occur in a graph. The largest factor in the running time of this algorithm is $O(n^c)$, where $c$ is a parameter of the pattern we call its left covering number. Concrete applications of this algorithm include counting the number of (non-induced) bicliques in linear time, the number of co-matchings in quadratic time, as well as a constant-factor approximation of the ladder index in linear time. Finally, we supplement our theoretical results with several implementations and run experiments on more than 200 real-world datasets -- the largest of which has 8 million edges -- where we obtain interesting insights into the VC-dimension of real-world networks.Comment: Accepted for publication in the 18th International Symposium on Parameterized and Exact Computation (IPEC 2023

Computing Complexity Measures of Degenerate Graphs

We show that the VC-dimension of a graph can be computed in time n^{⌈log d+1⌉} d^{O(d)}, where d is the degeneracy of the input graph. The core idea of our algorithm is a data structure to efficiently query the number of vertices that see a specific subset of vertices inside of a (small) query set. The construction of this data structure takes time O(d2^dn), afterwards queries can be computed efficiently using fast Möbius inversion. This data structure turns out to be useful for a range of tasks, especially for finding bipartite patterns in degenerate graphs, and we outline an efficient algorithm for counting the number of times specific patterns occur in a graph. The largest factor in the running time of this algorithm is O(n^c), where c is a parameter of the pattern we call its left covering number. Concrete applications of this algorithm include counting the number of (non-induced) bicliques in linear time, the number of co-matchings in quadratic time, as well as a constant-factor approximation of the ladder index in linear time. Finally, we supplement our theoretical results with several implementations and run experiments on more than 200 real-world datasets - the largest of which has 8 million edges - where we obtain interesting insights into the VC-dimension of real-world networks.publishedVersio

Evaluation of complex integrated care programmes: the approach in North West London

Background: Several local attempts to introduce integrated care in the English National Health Service have been tried, with limited success. The Northwest London Integrated Care Pilot attempts to improve the quality of care of the elderly and people with diabetes by providing a novel integration process across primary, secondary and social care organisations. It involves predictive risk modelling, care planning, multidisciplinary management of complex cases and an information technology tool to support information sharing. This paper sets out the evaluation approach adopted to measure its effect. Study design: We present a mixed methods evaluation methodology. It includes a quantitative approach measuring changes in service utilization, costs, clinical outcomes and quality of care using routine primary and secondary data sources. It also contains a qualitative component, involving observations, interviews and focus groups with patients and professionals, to understand participant experiences and to understand the pilot within the national policy context. Theory and discussion: This study considers the complexity of evaluating a large, multi-organisational intervention in a changing healthcare economy. We locate the evaluation within the theory of evaluation of complex interventions. We present the specific challenges faced by evaluating an intervention of this sort, and the responses made to mitigate against them. Conclusions: We hope this broad, dynamic and responsive evaluation will allow us to clarify the contribution of the pilot, and provide a potential model for evaluation of other similar interventions. Because of the priority given to the integrated agenda by governments internationally, the need to develop and improve strong evaluation methodologies remains strikingly important

Understanding Marketing Responses to a Tax on Sugary Drinks: A Qualitative Interview Study in the United Kingdom, 2019.

BACKGROUND: The World Health Organization (WHO) recommends that countries implement fiscal policies to reduce the health impacts of sugary drinks. Few studies have fully examined the responses of industry to these policies, and whether they support or undermine health benefits of sugary drinks taxes. We aimed to explore the changes that sugary drinks companies may make to their marketing, and underlying decision-making processes, in response to such a tax. METHODS: Following introduction of the UK Soft Drinks Industry Levy (SDIL) in 2018, we undertook one-to-one semi-structured interviews with UK stakeholders with experience of the strategic decision-making or marketing of soft drinks companies. We purposively recruited interviewees using seed and snowball sampling. We conducted telephone interviews with 6 representatives from each of industry, academia and civil society (total n=18), which were transcribed verbatim and thematically analysed. Four transcripts were double-coded, three were excluded from initial coding to allow comparison; and findings were checked by interviewees. RESULTS: Themes were organised into a theoretical framework that reveals a cyclical, iterative and ongoing process of soft drinks company marketing decision-making, which was accelerated by the SDIL. Decisions about marketing affect a product's position, or niche, in the market and were primarily intended to maintain profits. A product's position is enacted through various marketing activities including reformulation and price variation, and non-marketing activities like lobbying. A soft drinks company's selection of marketing activities appeared to be influenced by their internal context, such as brand strength, and external context, such as consumer trends and policy. For example, a company with low brand strength and an awareness of trends for reducing sugar consumption may be more likely to reformulate to lower-sugar alternatives. CONCLUSION: The theoretical framework suggests that marketing responses following the SDIL were coordinated and context-dependent, potentially explaining observed heterogeneity in responses across the industry

Understanding Marketing Responses to a Tax on Sugary Drinks: A Qualitative Interview Study in the United Kingdom, 2019.

BACKGROUND: The World Health Organization (WHO) recommends that countries implement fiscal policies to reduce the health impacts of sugary drinks. Few studies have fully examined the responses of industry to these policies, and whether they support or undermine health benefits of sugary drinks taxes. We aimed to explore the changes that sugary drinks companies may make to their marketing, and underlying decision-making processes, in response to such a tax. METHODS: Following introduction of the UK Soft Drinks Industry Levy (SDIL) in 2018, we undertook one-to-one semi-structured interviews with UK stakeholders with experience of the strategic decision-making or marketing of soft drinks companies. We purposively recruited interviewees using seed and snowball sampling. We conducted telephone interviews with 6 representatives from each of industry, academia and civil society (total n=18), which were transcribed verbatim and thematically analysed. Four transcripts were double-coded, three were excluded from initial coding to allow comparison; and findings were checked by interviewees. RESULTS: Themes were organised into a theoretical framework that reveals a cyclical, iterative and ongoing process of soft drinks company marketing decision-making, which was accelerated by the SDIL. Decisions about marketing affect a product's position, or niche, in the market and were primarily intended to maintain profits. A product's position is enacted through various marketing activities including reformulation and price variation, and non-marketing activities like lobbying. A soft drinks company's selection of marketing activities appeared to be influenced by their internal context, such as brand strength, and external context, such as consumer trends and policy. For example, a company with low brand strength and an awareness of trends for reducing sugar consumption may be more likely to reformulate to lower-sugar alternatives. CONCLUSION: The theoretical framework suggests that marketing responses following the SDIL were coordinated and context-dependent, potentially explaining observed heterogeneity in responses across the industry

Multidisciplinary integration in the context of integrated care - results from the North West London Integrated Care Pilot

Background: In the context of integrated care, Multidisciplinary Group meetings involve participants from diverse professional groups and organisations and are potential vehicles to advance efficiency improvements within the local health economy. We advance a novel method to characterise the communication within Multidisciplinary Group meetings measuring the extent to which participants integrate and whether this integration leads to improved working. Methods: We purposively selected four Multidisciplinary Group meetings and conducted a content analysis of audio-recorded and transcribed Case Discussions. Two coders independently coded utterances according to their 'integrative intensity' which was defined against three a-priori independent domains - the Level (i.e. Individual, Collective and Systems); the Valence (Problem, Information and Solution); the Focus (Concrete and Abstract). Inter- and intra-rater reliability was tested with Kappa scores on one randomly selected Case Discussion. Standardised weighted mean integration scores were calculated for Case Discussions across utterance deciles, indicating how integrative intensity changed during the conversations. Results: Twenty-three Case Discussions in four different Multidisciplinary Groups were transcribed and coded. Inter- and intra-rater reliability was good as shown by the Prevalence and Bias-Adjusted Kappa Scores for one randomly selected Case Discussion. There were differences in the proportion of utterances per participant type (Consultant 14.6%; presenting general practitioner 38.75%; Chair 7.8%; nonpresenting general practitioner 2.25%; Allied Health Professional 4.8%). Utterances were predominantly coded at low levels of integrative intensity; however, there was a gradual increase (R = 0.71) in integrative intensity during the Case Discussions. Based on the analysis of the minutes and action points arising from the Case Discussions, this improved integration did not translate into actions moving forward. Interpretation: We characterise the Multidisciplinary Groups as having consultative characteristics with some trend towards collaboration, but that best resemble Community-Based Ward Rounds. Although integration scores do increase from the beginning to the end of the Case Discussions, this does not tend to translate into actions for the groups to take forward. The role of the Chair and the improved participation of non-presenting general practitioners and Allied Health Professionals seems important, particularly as the latter contribute well to higher integrative scores. Traditional communication patterns of medical dominance seem to be being perpetuated in the Multidisciplinary Groups. This suggests that more could be done to sensitise participants to the value of full participation from all the members of the group. The method we have developed could be used for ongoing and future evaluations of integrated care projects

The Relationship between Self-Reported Exposure to Sugar-Sweetened Beverage Promotions and Intake: Cross-Sectional Analysis of the 2017 International Food Policy Study.

Sugar-sweetened beverage (SSB) consumption is independently associated with several non-communicable diseases, so policymakers are increasingly implementing measures, such as marketing regulation, to reduce intake. To help understand how such measures work, this study examined the association between SSB consumption and self-reported exposure to SSB promotions, both overall and by type of promotion, and whether these relationships vary between the UK, USA, Canada, Mexico, and Australia. Cross-sectional analysis of the online 2017 International Food Policy Study was performed (n = 15,515). Participants were grouped into 5265 (34%) non-, 5117 (33%) low-, and 5133 (33%) high-SSB consumers. Multinomial logistic regression models examined whether SSB consumption varied by exposure to total SSB promotion and by type: traditional, digital, recreational environment, and functional environment. Multiplicative interactions were included to investigate international variations. An additional unit of total self-reported SSB promotion exposure increased the likelihood of participants being low SSB consumers (relative risk ratio (RRR) = 1.08, 95% confidence interval (CI) = 1.06-1.10) and high SSB consumers (RRR = 1.13, 95% CI = 1.11-1.16). Only exposure to traditional and digital promotion increased the likelihood of participants being SSB consumers, though this may be explained by degree of exposure, which was not measured in this study. Some evidence illustrated international variation in these relationships