Biography

Nisha is a mixed-methods Researcher in Social Science at Centre for Health, Law and Emerging Technologies (HeLEX) at University of Oxford. She is a Co-investigator for the ESRC-JST funded project "Ensuring the benefits of AI for All: Designing a Sustainable Platform for Public and Professional Stakeholder Engagement". In collaboration with researchers at Osaka University, this project aims to understand the perceived impact of AI in healthcare for stakeholders including patients, public, and healthcare professionals, and explore effective strategies to support a platform for stakeholder engagement and involvement in the development and implementation of AI initiatives in healthcare.

Nisha is also working on a collaboration with Nordic partners (Norway, Sweden and Iceland) on the Nordforsk funded project ‘Governance of Health Data in Cyberspace’. This aims to understand public and expert views about how data should be shared for secondary purposes and what implications this has for stakeholders with reference to new ways of capturing and using data. This work will identify the most appropriate mechanisms that should be applied to govern the sharing of data across different contexts.  

Nisha has previously worked on the IMI (Innovative Medicines Initiative) funded project ‘European DIRECT (Diabetes Research on Patient Stratification)’, which investigated personalised medicine for Type II diabetes patients. She explored DIRECT’s research participants’ motivations and preferences for sharing their biomedical and genomic data beyond the end of the project.

She also led the Wellcome Trust funded project ‘Public Engagement for Biobanking Research’ (aka Waiting Room Project). This project investigated the opportunity to utilise time spent in clinic waiting rooms to engage public perceptions, through the use of digital technologies. It also explored views about key ethical issues about donating bio-samples and data for medical research.

Prior to coming to HeLEX, Nisha's research focussed on areas in Health psychology, patient safety, digital health and implementation science, and prevention of hospital acquired infections.

Publications

Recent additions

  • JV Johansson, N Shah and E Haraldsdottir and others, 'Governance mechanisms for sharing of health data: An approach towards selecting attributes for complex discrete choice experiment studies' (2021) 66 Technology in Society
    DOI: https://doi.org/10.1016/j.techsoc.2021.101625
    Background Discrete Choice Experiment (DCE) is a well-established technique to elicit individual preferences, but it has rarely been used to elicit governance preferences for health data sharing. Objectives The aim of this article was to describe the process of identifying attributes for a DCE study aiming to elicit preferences of citizens in Sweden, Iceland and the UK for governance mechanisms for digitally sharing different kinds of health data in different contexts. Methods A three-step approach was utilised to inform the attribute and level selection: 1) Attribute identification, 2) Attribute development and 3) Attribute refinement. First, we developed an initial set of potential attributes from a literature review and a workshop with experts. To further develop attributes, focus group discussions with citizens (n = 13), ranking exercises among focus group participants (n = 48) and expert interviews (n = 18) were performed. Thereafter, attributes were refined using group discussion (n = 3) with experts as well as cognitive interviews with citizens (n = 11). Results The results led to the selection of seven attributes for further development: 1) level of identification, 2) the purpose of data use, 3) type of information, 4) consent, 5) new data user, 6) collector and 7) the oversight of data sharing. Differences were found between countries regarding the order of top three attributes. The process outlined participants’ conceptualisation of the chosen attributes, and what we learned for our attribute development phase. Conclusions This study demonstrates a process for selection of attributes for a (multi-country) DCE involving three stages: Attribute identification, Attribute development and Attribute refinement. This study can contribute to improve the ethical aspects and good practice of this phase in DCE studies. Specifically, it can contribute to the development of governance mechanisms in the digital world, where people's health data are shared for multiple purposes.
  • JV Johansson , HB Bentzen, N Shah and E Haraldsdottir and others, 'Preferences of the Public for Sharing Health Data: Discrete Choice Experiment' (2021) 9 JMIR Medical Informatics
    DOI: https://doi.org/10.2196/29614
    Background: Digital technological development in the last 20 years has led to significant growth in digital collection, use, and sharing of health data. To maintain public trust in the digital society and to enable acceptable policy-making in the future, it is important to investigate people’s preferences for sharing digital health data. Objective: The aim of this study is to elicit the preferences of the public in different Northern European countries (the United Kingdom, Norway, Iceland, and Sweden) for sharing health information in different contexts. Methods: Respondents in this discrete choice experiment completed several choice tasks, in which they were asked if data sharing in the described hypothetical situation was acceptable to them. Latent class logistic regression models were used to determine attribute-level estimates and heterogeneity in preferences. We calculated the relative importance of the attributes and the predicted acceptability for different contexts in which the data were shared from the estimates. Results: In the final analysis, we used 37.83% (1967/5199) questionnaires. All attributes influenced the respondents’ willingness to share health information (P<.001). The most important attribute was whether the respondents were informed about their data being shared. The possibility of opting out from sharing data was preferred over the opportunity to consent (opt-in). Four classes were identified in the latent class model, and the average probabilities of belonging were 27% for class 1, 32% for class 2, 23% for class 3, and 18% for class 4. The uptake probability varied between 14% and 85%, depending on the least to most preferred combination of levels. Conclusions: Respondents from different countries have different preferences for sharing their health data regarding the value of a review process and the reason for their new use. Offering respondents information about the use of their data and the possibility to opt out is the most preferred governance mechanism.
  • Arora S, Tsang F, Kekecs Z and N Shah, 'Patient Safety Education 20 Years After the Institute of Medicine Report Results From a Cross-sectional National Survey' (2020) Journal of Patient Safety
    DOI: doi: 10.1097/PTS.0000000000000676
    Objectives Educating healthcare professionals in patient safety is essential to achieving sustainable improvements in care. This study aimed to identify the key constituents of patient safety education alongside its facilitators and barriers from a frontline perspective. Methods An electronic survey was sent to 592 healthcare professionals and educators in patient safety education in the United Kingdom. Two independent reviewers conducted a thematic analysis of the free-text data. Themes focused on effective content, learning practices and facilitators and barriers to patient safety education. Results Of 592 individuals completing the survey, 545 (92%) submitted analyzable responses. Interrater reliability of coding was high with Cohen k value of 0.86. Participants endorsed experiential and interactive learning as ideal modalities for delivery and expressed a need for content to be based on real clinical cases and tailored to the needs of the learners. The most commonly mentioned facilitators were standardization of methods and assessment (49%), dedicated funding (21%), and culture of openness (20%). Staffing problems and high workload (41%) and lack of accessibility of training (23%) were identified as primary barriers of efficacy and uptake. Conclusions This study identified key factors to the success of patient safety education in terms of content and delivery alongside facilitators and barriers. Future curricula developers and interventions should improve standardization, funding, culture, and access so as to optimize education programs to enhance patient safety.

Journal Article (14)

JV Johansson, N Shah and E Haraldsdottir and others, 'Governance mechanisms for sharing of health data: An approach towards selecting attributes for complex discrete choice experiment studies' (2021) 66 Technology in Society
DOI: https://doi.org/10.1016/j.techsoc.2021.101625
Background Discrete Choice Experiment (DCE) is a well-established technique to elicit individual preferences, but it has rarely been used to elicit governance preferences for health data sharing. Objectives The aim of this article was to describe the process of identifying attributes for a DCE study aiming to elicit preferences of citizens in Sweden, Iceland and the UK for governance mechanisms for digitally sharing different kinds of health data in different contexts. Methods A three-step approach was utilised to inform the attribute and level selection: 1) Attribute identification, 2) Attribute development and 3) Attribute refinement. First, we developed an initial set of potential attributes from a literature review and a workshop with experts. To further develop attributes, focus group discussions with citizens (n = 13), ranking exercises among focus group participants (n = 48) and expert interviews (n = 18) were performed. Thereafter, attributes were refined using group discussion (n = 3) with experts as well as cognitive interviews with citizens (n = 11). Results The results led to the selection of seven attributes for further development: 1) level of identification, 2) the purpose of data use, 3) type of information, 4) consent, 5) new data user, 6) collector and 7) the oversight of data sharing. Differences were found between countries regarding the order of top three attributes. The process outlined participants’ conceptualisation of the chosen attributes, and what we learned for our attribute development phase. Conclusions This study demonstrates a process for selection of attributes for a (multi-country) DCE involving three stages: Attribute identification, Attribute development and Attribute refinement. This study can contribute to improve the ethical aspects and good practice of this phase in DCE studies. Specifically, it can contribute to the development of governance mechanisms in the digital world, where people's health data are shared for multiple purposes.
JV Johansson , HB Bentzen, N Shah and E Haraldsdottir and others, 'Preferences of the Public for Sharing Health Data: Discrete Choice Experiment' (2021) 9 JMIR Medical Informatics
DOI: https://doi.org/10.2196/29614
Background: Digital technological development in the last 20 years has led to significant growth in digital collection, use, and sharing of health data. To maintain public trust in the digital society and to enable acceptable policy-making in the future, it is important to investigate people’s preferences for sharing digital health data. Objective: The aim of this study is to elicit the preferences of the public in different Northern European countries (the United Kingdom, Norway, Iceland, and Sweden) for sharing health information in different contexts. Methods: Respondents in this discrete choice experiment completed several choice tasks, in which they were asked if data sharing in the described hypothetical situation was acceptable to them. Latent class logistic regression models were used to determine attribute-level estimates and heterogeneity in preferences. We calculated the relative importance of the attributes and the predicted acceptability for different contexts in which the data were shared from the estimates. Results: In the final analysis, we used 37.83% (1967/5199) questionnaires. All attributes influenced the respondents’ willingness to share health information (P<.001). The most important attribute was whether the respondents were informed about their data being shared. The possibility of opting out from sharing data was preferred over the opportunity to consent (opt-in). Four classes were identified in the latent class model, and the average probabilities of belonging were 27% for class 1, 32% for class 2, 23% for class 3, and 18% for class 4. The uptake probability varied between 14% and 85%, depending on the least to most preferred combination of levels. Conclusions: Respondents from different countries have different preferences for sharing their health data regarding the value of a review process and the reason for their new use. Offering respondents information about the use of their data and the possibility to opt out is the most preferred governance mechanism.
Soukup T, Lamb B, Morbi A and N Shah and others, 'A multicentre cross-sectional observational study of cancer multidisciplinary teams: Analysis of team decision making' (2020) Cancer Medicine
DOI: https://doi.org/10.1002/cam4.3366
Background Multidisciplinary teams (MDT) formulate expert informed treatment recommendations for people with cancer. We set out to examine how the factors proposed by the functional perspective of group decision making (DM), that is, interaction process, internal factors (factors emanating from within the group such as group size), external circumstances (factors coming from the outside of the team), and case‐complexity affect the quality of MDT decision making. Methods This was a cross‐sectional observational study. Three cancer MDTs were recruited with 44 members overall and 30 of their weekly meetings filmed. Validated observational instruments were used to measure quality of DM, interactions, and complexity of 822 case discussions. Results The full regression model with the variables proposed by the functional perspective was significant, R2 = 0.52, F(20, 801) = 43.47, P < .001, adjusted R2 = 0.51. Positive predictors of DM quality were asking questions (P = .001), providing answers (P = .001), team size (P = .007), gender balance (P = .003), and clinical complexity (P = .001), while negative socioemotional reactions (P = .007), gender imbalance (P = .003), logistical issues (P = .001), time‐workload pressures (P = .002), and time spent in the meeting (P = .001) were negative predictors. Second half of the meetings also saw significant decrease in the DM quality (P = .001), interactions (P = .001), group size (P = .003), and clinical complexity (P = .001), and an increase in negative socioemotional reactions (P = .001) and time‐workload pressures (P = .001). Discussion To the best of our knowledge, this is the first study to attempt to assess the factors proposed by the functional perspective in cancer MDTs. One novel finding is the effect of sociocognitive factors on team DM quality, while another is the cognitive‐catch 22 effect: while the case discussions are significantly simpler in the second half of the meeting, there is significantly less time left to discuss the remaining cases, further adding to the cognitive taxation in teams who are now rapidly attempting to close their time‐workload gap. Implications are discussed in relation to quality and safety.
Arora S, Tsang F, Kekecs Z and N Shah, 'Patient Safety Education 20 Years After the Institute of Medicine Report Results From a Cross-sectional National Survey' (2020) Journal of Patient Safety
DOI: doi: 10.1097/PTS.0000000000000676
Objectives Educating healthcare professionals in patient safety is essential to achieving sustainable improvements in care. This study aimed to identify the key constituents of patient safety education alongside its facilitators and barriers from a frontline perspective. Methods An electronic survey was sent to 592 healthcare professionals and educators in patient safety education in the United Kingdom. Two independent reviewers conducted a thematic analysis of the free-text data. Themes focused on effective content, learning practices and facilitators and barriers to patient safety education. Results Of 592 individuals completing the survey, 545 (92%) submitted analyzable responses. Interrater reliability of coding was high with Cohen k value of 0.86. Participants endorsed experiential and interactive learning as ideal modalities for delivery and expressed a need for content to be based on real clinical cases and tailored to the needs of the learners. The most commonly mentioned facilitators were standardization of methods and assessment (49%), dedicated funding (21%), and culture of openness (20%). Staffing problems and high workload (41%) and lack of accessibility of training (23%) were identified as primary barriers of efficacy and uptake. Conclusions This study identified key factors to the success of patient safety education in terms of content and delivery alongside facilitators and barriers. Future curricula developers and interventions should improve standardization, funding, culture, and access so as to optimize education programs to enhance patient safety.
Soukup T, Lamb B, N Shah and Morbi A and others, 'Relationships Between Communication, Time Pressure, Workload, Task Complexity, Logistical Issues and Group Composition in Transdisciplinary Teams: A Prospective Observational Study Across 822 Cancer Cases' (2020) Frontiers in Communication
DOI: https://doi.org/10.3389/fcomm.2020.583294
Introduction: Functional perspective of team decision-making highlights the importance of understanding the relationship between team interaction/communication during a given task, the internal factors that emanate from within a group (e.g., team composition), and the external circumstances (e.g., workload and time pressures). As an underexplored area, we explored these relationships in the context of multidisciplinary team (MDT) meetings (aka tumor boards). Materials and methods: Three cancer MDTs with 44 team members were recruited from three teaching hospitals in the United Kingdom. Thirty of their weekly meetings encompassing 822 case reviews were filmed. Validated instruments were used to assess each case: Bales' Interaction Process Analysis that captures frequency of task-oriented and socio-emotional interactions/communication; and Measure of case-Discussion Complexity that captures clinical and logistic complexities. We also measured team size, disciplinary diversity, gender, time-workload pressure, and time-on-task. Partial correlation analysis controlling for team/tumor type and case complexity was used for analysis. Results: Clinical complexity positively correlated with task-oriented communication, e.g., gives opinion (r = 0.51, p < 0.001), and logistical issues with negative socio-emotional interactions, e.g., antagonism (r = 0.14, p < 0.01). Time-workload pressure correlated with reduced task-oriented communication, e.g., gives opinion (r = −0.15, p < 0.01), and positive socio-emotional interactions, e.g., solidarity (r = −0.17, p < 0.001). Time-on-task negatively correlated with task-oriented communication, e.g., asks for orientation (r = −0.16, p < 0.001), and positive socio-emotional interactions, e.g., agrees (r = −0.21, p < 0.001). Team size and disciplinary diversity positively correlated with task-oriented communication, e.g., asks for orientation (r = 0.13, p < 0.001; r = 0.09, p < 0.05), and negative socio-emotional interactions, e.g., antagonism (r = 0.10, p < 0.01; r = 0.08, p < 0.05). Gender balance had no significant relationships (all p > 0.05), however, case reviews with more males present were associated with more tension (r = 0.09, p < 0.01) and less disagreements (r = −0.11, p < 0.01), while when more females present there were more disagreements (r = 0.10, p < 0.01) and less tension (r = −0.11, p < 0.01). Discussion: To the best of our knowledge, this is the first study to assess the relationship between MDT interaction/communication and the external/internal factors. Smaller size, gender balanced teams with core disciplines present, and streamlining workload to reduce time-workload pressure, time-on-task effects, and logistical issues appear more conducive to building and maintain optimal MDTs. Our methodology could be applied to other MDT-driven areas of healthcare.
N Shah, Coathup V and Teare H and others, 'Sharing data for future research—engaging participants’ views about data governance beyond the original project: a DIRECT Study' (2018) 21 Genetics and Medicine 1131
DOI: https://doi.org/10.1038/s41436-018-0299-7
Purpose Biomedical data governance strategies should ensure that data are collected, stored, and used ethically and lawfully. However, research participants’ preferences for how data should be governed is least studied. The Diabetes Research on Patient Stratification (DIRECT) project collected substantial amounts of health and genetic information from patients at risk of, and with type II diabetes. We conducted a survey to understand participants’ future data governance preferences. Results will inform the postproject data governance strategy. Methods A survey was distributed in Denmark, Sweden, The Netherlands, and the United Kingdom. Results In total 855 surveys were returned. Ninety-seven percent were supportive of sharing data postproject, and 90% were happy to share data with universities, and 56% with commercial companies. The top three priorities for data sharing were highly secure database, DIRECT researchers to monitor data used by other researchers, and researchers cannot identify participants. Respondents frequently suggested that a postproject Data Access Committee should involve a DIRECT researcher, diabetes clinician, patient representative, and a DIRECT participant. Conclusion Preferences of how data should be governed, and what data could be shared and with whom varied between countries. Researchers are considered as key custodians of participant data. Engaging participants aids in designing governance to support their choices.

Report (1)

Zawati MH, Chalmers D, Dallari SG and N Shah and others, Country Reports (The Journal of Law, Medicine & Ethics 47 2019)
DOI: https://doi.org/10.1177/1073110519897736

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Research Interests

Research methods, AI, digital health, global health, health equity, and patient safety.

Research projects