Sage Journals: Discover world-class research

Abstract

Aim:

Public health lifestyle databases at local authority level are currently poorly aligned across the UK. The integration of lifestyle databases at a regional level could provide a rich resource to support research and help inform public health leads and service commissioners in improving service delivery, facilitating decision-making and developing key public health policies. Prior to its implementation, the acceptability of an integrated lifestyle database should be explored. The aim of this study was to consult with public health stakeholders to explore the acceptability of developing and implementing a regional integrated lifestyle database across four key areas of public health: smoking cessation, diet, physical activity and alcohol consumption.

Method:

Qualitative interviews were conducted with public health stakeholders recruited from across the East Midlands region of England. All interviews were conducted using video conferencing software and recorded, transcribed, and analysed using the Framework approach. Sixteen public health stakeholders were purposively identified and invited to participate in interviews.

Results:

Stakeholders viewed the integrated database as having potential to support research, service development and commissioning decisions. Barriers such as providers’ reluctance to reveal their business strategies to rival organisations, cost of setting up and running the proposed database, complex information-sharing and governance were identified.

Conclusion:

An integrated lifestyle database has the potential to support research and service commissioning regionally. However, several barriers were identified that must be addressed prior to the development and implementation of an integrated database.

Keywords

public health stakeholders lifestyle service commissioning perceptions barriers and facilitators acceptability integrated database

Introduction

High-risk lifestyle behaviours including, smoking, poor diet, physical inactivity, and excessive alcohol consumption contribute to poor health and are widely acknowledged as prominent risk factors for the development of long-term conditions.^1–6 There is a national drive within the UK towards preventing illness by tackling unhealthy behaviours and promoting health and well-being. The Health and Social Care Act⁷ for England outlined specific duties for local government authorities to protect and promote health while reducing health inequalities. Local authorities therefore now provide interventions that reduce risks to health and the impact of disease,⁸ in addition to exploring innovative ways of evaluating and improving their services,⁹ such as data integration and sharing, and secondary analysis of existing data to identify risk factors and trends in patterns of behaviour.^10,11

Electronic healthcare records from the UK are accessible to researchers via a number of platforms, but they tend to include data from a limited subset of health and care service providers,¹¹ or from separate geographical areas, unlinked across larger regions. Research in public health is now starting to explore the potential to transition away from siloed data systems to more accessible and integrated data resources.^12,13 Several large integrated health databases, which involve the connection or linkage of multiple databases or datasets, now do exist within the UK, examples of which include the Clinical Practice Research Datalink (CPRD),¹⁴ The Health Improvement Network (THIN)¹⁵ and QResearch.¹⁶ However, many of these contain mostly data from primary care records, with many local authorities in England lacking lifestyle data platforms that cover their whole population.¹¹ Existing lifestyle-related datasets such as ‘fingertips datasets’¹⁷ do collate local authority lifestyle datasets and can be useful in potentially informing service development and commissioning, but these are aggregated at population-level data and may not be suitable for research studies requiring individual-level data analysis across and between local authorities or regions.

While there remains an underwhelming lack of research concerning the development of integrated public health datasets across the UK, Lewer etal.¹¹ provide an excellent example of the potential usefulness of data integration through the development of the Kent Integrated Database (KID). The KID comprises individual-level linked Electronic Healthcare Records (EHRs) extracted from a wide range of services located across the Kent and Medway region including primary care providers, community health providers, mental health services and services commissioned outside of the National Health Service (NHS) including public health services, adult social care, and palliative care hospices¹¹. Although focused primarily on healthcare utilisation, the KID provides data integration across the whole of Kent and Medway, providing a valuable resource for researchers who are investigating a broad range of public health questions while also supporting service commissioning based on patient needs.¹¹ There is great potential to learn from the KID in exploring how integrated systems can be achieved in different regions and with a focus on individual-level health behaviours.

This study has been designed to examine the potential for a fully integrated public health lifestyle dataset, using the East Midlands region of England as an initial pilot study area. We aim to explore the potential for the development of a model, which incorporates different individual-level lifestyle datasets across different geographical areas or local authorities across the East Midlands region and how lessons learned could be applicable elsewhere. This could help to inform public health policy, service delivery and commissioning decisions. It could also provide a rich data source for more in-depth analysis in future research studies, allowing for greater geographical comparisons of determinants and prevalence of lifestyle behaviours, alongside comparisons between and across lifestyle areas. Furthermore, building an integrated lifestyle database could help to inform regional and national efforts to promote health, support post-COVID recovery and return to business as usual. For example, aligning with the government’s recent obesity strategy promoting the nation’s health and to protect against COVID-19¹⁸ or the new government white paper on improving healthcare and social care for all,¹⁹ targeting improvements in the delivery of public health and social care interventions to support local systems to deliver high-quality care to their communities. Finally, lessons around data linkage and usage could also be learnt and applied across other local authorities within the UK and beyond.

Prior to development and implementation of such a model, it is important to explore views on the acceptability and potential demand of an integrated lifestyle database. Therefore, the aim of this research was to conduct in-depth qualitative interviews with key public heath stakeholders to explore the acceptability of developing and sharing an integrated lifestyle dataset to support service development, commissioning and research across the East Midlands region.

This study was informed by a feasibility framework,²⁰ which outlines eight key concepts (acceptability, demand, implementation, practicality, adaptation, integration, expansion, limited-efficacy testing). As the study aimed to explore participant perceptions of a proposed integrated lifestyle database, we focused on the acceptability, demand and practicality elements of this framework, which were adopted to inform the structuring of the topic guide for the consultations. The concepts of acceptability and demand more directly help to explain how practitioners perceived the benefits or usefulness of the proposed integrated database, while practicality helps to explain the potential barriers to the development and implementation of the database.

Methods

Study design

When conducting a research study, it is important for researchers to reflect on their philosophical perspective and position their research within a paradigm.²¹ As the aim of this study was to use in-depth interviews to explore the perspectives of stakeholders and to understand issues around the acceptability of a proposed integrated database, the interpretivist approach was considered appropriate for this research.

The interpretive research paradigm is based on a subjective point of view as it seeks to gather understanding from the perspective of the participant rather than the objective observer (usually associated with the positivist paradigm) of an action.²² Unlike a positivist approach, as well as understanding participant perspectives, the interpretivist paradigm seeks to establish trustworthiness through dependability, credibility, confirmability and transferability of the research.^23–25 A positivist approach is typically associated with deductive reasoning; however, there are no fixed rules as some qualitative studies may have deductive elements,²⁶ and individual qualitative researchers may use both deductive and inductive approaches.²⁷ Therefore, this study adopted an interpretivist position with the flexibility of beginning with a deductive or theory-driven data collection (the topic guide structure and content being informed by a theoretical framework) and coding, and adding new codes inductively.^28,29

Study participants

A range of public health professionals were purposively recruited from local authorities and local public health organisations from within the East Midlands region of the UK to participate in this study. To identify and recruit from local authorities, a key contact from each of the five County Council areas in the East Midlands region was identified and an invitation via email (with information about the research) was sent to them to facilitate the recruitment of eligible stakeholders to participate in the study. Stakeholders were recruited from within local authorities using the following inclusion criteria: currently engaged as a lifestyle service commissioner, public health consultant, public health manager, intelligence officer, service provider or user in any of the East Midlands local authorities, willing to participate in the study and consent to their data being used for the research. Relevant stakeholders were also identified from regional public health organisations and were invited to take part in this study through an invitational email.

Ten stakeholders from the five County Council responded and agreed to participate in the qualitative interviews. Six stakeholders working for Public Health England (now known as Office for Health Improvement and Disparities) and Population Health Management Implementation in the East Midlands region were also consulted, as they were identified as having the potential to provide relevant or expert information for the study.

Qualitative interviews

Working in collaboration with the National Institute of Health Research (NIHR)–Clinical Research Network (CRN) Public Health Speciality, the East Midlands Directors of Public Health and our Patient and Public Involvement (PPI) group, we conducted qualitative interviews with public health stakeholders across the East Midlands region of England, from September 2020 to February 2021.

Qualitative interviews were conducted using an interview topic guide that was underpinned by the feasibility framework²⁰ in addition to discussion meetings with the study steering group and PPI. Key questions from the topic guide are outlined in Table 1. Qualitative interviews were conducted using video conferencing software and ranged from 30 to 60 min with an average time of 45 min. Stakeholders were informed that they could withdraw from the study up to the point of data anonymity and integration without having to give reason. Some stakeholders attended the interviews in groups, and there was one group of 2 and another group of 3. Other stakeholders opted to give extensive written feedback to questions on the interview guide, sent in advance, for discussion at the interviews. This written feedback was incorporated into the audio-recorded data for analysis.

Table 1.

Key questions from the topic guide relating to feasibility framework concepts of acceptability/demand and practicality.²⁰

Background questions	Acceptability related questions	Practicality related questions
1. Your local authority	1. How do you currently use lifestyle intervention datasets?	1. Are you willing to share details of the template (a blank lists of variables) used to collect data across the lifestyle areas so that we can determine whether the variables can be linked to form one database?
2. Your current role	2. How are the datasets used to inform service development?	2. What datasets exist in your area that you are aware of?
3. Area of lifestyle service	3. How can a shared dataset fit into your lifestyle service?	3. Are the datasets in your area separate (for different lifestyles: smoking cessation, alcohol consumption, reduction in physical inactivity and diet/weight management) or integrated?
	4. How can an existing dataset be modified for shared use across East Midlands?	4. What are the barriers to creating an East Midlands wide dataset? What are the disadvantages?
	5. How useful would a shared dataset across the whole East Midlands be? What are the advantages?	5. How cost-effective will a shared dataset across East Midlands be?
	6. What factors will facilitate the implementation of a shared dataset across East Midlands?	6. Where are data shared already and with whom?
	7. Who are the datasets used by?
	8. How is evidence base used (how can it be used) to steer decision-making in your organisation

In total, 16 stakeholders responded and participated in the qualitative interviews which were arranged by email (including in some cases the provision of additional information and response to questions on the interview guide) and followed up by a virtual meeting via MS TEAMS. See Table 2 for participant details.

Table 2.

Participant roles

Local authority public health stakeholders
1 × Senior representative1 × Integrated Lifestyle Service Manager1 × Lifestyle Service Manager1 × Lifestyle Service User2 × Consultants in Public Health1 × Senior Public Health and Commissioning Manager1 × Health Improvement Principal1 × Public Health Intelligence and Insight Manager1 × Data Health Checks and Smoking Cessation Officer
Regional public health organisation stakeholder
1 × Health and Wellbeing Programme Lead1 × Population Health Analysis and Nutrition, Diet, Obesity and Physical Activity Lead.1 × Associate Director, Local Knowledge & Intelligence Service1 x Performance & Intelligence Lead1 × Lifestyle Service Lead1 × Health Inequalities/Population Lead

Strength, Weaknesses, Opportunities and Threats analysis

A Strengths, Weaknesses, Opportunities and Threats (SWOT) Analysis³⁰ was conducted using the identified qualitative themes to identify the factors that are either supportive or unfavourable to the implementation of an integrated lifestyle database. SWOT analysis is a common tool used in research as part of the strategic planning process and can be used to facilitate a better understanding of a situation and inform decision-making.³⁰

Data analysis

Audio data were transcribed verbatim and entered into NVivo 12 qualitative data analysis software system (QRS International Pty Ltd) to organise data and facilitate analysis. The collection of the data and analysis were undertaken until saturation had been reached.³¹ In line with the philosophical position outlined above, a Framework analysis of the data^32,33 was conducted, which allowed the researcher to explore deductive (a priori) and inductive (emergent) themes using the following stages: familiarisation, identifying a thematic framework, indexing, charting, mapping and interpretation.^32,33 The feasibility framework concepts of acceptability, demand and practicality guided the deductive coding of the data, while ideas emerging from the data were coded inductively. The perceived benefits of the proposed database expressed by stakeholders were classified in the context of acceptability and demand, while concerns were classified as barriers in the context of practicality to the development and implementation of the database. This approach was deemed systematic and provided a clear audit trail from raw data to final themes, ensuring the trustworthiness of the results.^34,35 In addition, an open, critical and reflexive approach was maintained to ensure a rigorous qualitative data analysis.³⁶ The Consolidated Criteria for Reporting Qualitative Studies³⁷ (see Supplemental Table S1) was also followed to add transparency and trustworthiness in reporting the research findings.

Results

The data were organised into two key themes: (1) benefits relating to the acceptability and demand for an integrated lifestyle database and (2) barriers relating to the practicality of constructing and implementing an integrated lifestyle database.

Benefits Relating to the Acceptability and Demand for an Integrated Lifestyle Database

Several subthemes concerning the benefits of the development and implementation of a regional integrated lifestyle database were identified, with evidence suggesting that it may be a useful resource for research development and informing service commissioning through ease of information access.

A rich resource for research

Many of the stakeholders expressed the view that an integrated lifestyle dataset would be a potentially rich resource for research:

. . . I think it is more of a potential research resource. (Stakeholder 1)

Actually, if you’re relating all the provider datasets, that would be a bigger job and it would be potentially more useful for research purposes because it’s got those individual level variables. (Stakeholder 2)

Elaborating further on how an integrated database could support research, stakeholders also suggested that it could be useful for comparing service performance across geographical areas within the region:

. . . and looking at makeup of the community or the geographical sort of you know . . . and comparing similar areas to ourselves. And looking at performance in terms of what are they doing, what are they doing differently that we could perhaps adapt and use locally? (Stakeholder 3)

It would give you the opportunity to compare how well things are doing in Lincolnshire compared to say Nottinghamshire because we would have both sets of information, yeah. (Stakeholder 4)

Ease of information access

Stakeholders expressed the view that a regional integrated dataset may have the potential to make it easier or quicker to access and search for lifestyle service information within a region:

. . . you’ve got five minutes and you want to know about smoking cessation services in Derbyshire. Where would you go to? You’ve got half an hour to do a bit deeper dive. Where would you go to? (Stakeholder 8)

Supporting service commissioning

Some stakeholders suggested that they would fully embrace the concept of having an integrated and shared dataset because it would be useful for service commissioning:

Having a national collection and reporting process like that of the Department of Health smoking reports would be useful. (Stakeholder 3)

As a service provider we would embrace a shared dataset across the East Midlands – there are several considerations; however, I believe it would add value to service delivery and best practice. (Stakeholder 7)

Modification of existing datasets into an integrated database

Stakeholders supported the construction of a regional integrated dataset and suggested that some datasets already existed in each of the local authority areas across the East Midlands region and within each provider organisation, which could facilitate the data integration process:

For the commissioned lifestyle service two data sets exist, one which is used for smoking cessation and another which is used for lifestyle. (Stakeholder 5)

It was also noted that some standardisation in reporting mechanisms and the variables collected are already in place, particularly for smoking cessation, which could facilitate the dataset integration process:

But you know it’s quite sort of standardized that people actually think this has got potential. (Stakeholder 3)

Barriers Relating to the Practicality of Developing and Implementing an Integrated Database

Several subthemes emerged relating to the barriers or concerns of the practicality of developing and implementing an integrated lifestyle database: wide variety of commissioned services and unstandardised collection of variables, unaligned information technology (IT) systems and expense of initial setup, sensitivity of data and the need for service user consent, governance and data access issues, and reluctance of providers to share business strategies with competitors.

Wide variety of commissioned services and unstandardised collection of variables

Although some standardisation in reporting mechanisms and variables collected was already in place, particularly for smoking cessation data, some stakeholders suggested that a wide variety of commissioned services and unstandardised collection of variables existed in other areas:

Yeah, . . . it’s about the standardising of what people would commission, and another service which may be a private provider. Or it might be an NHS provider. So, provided you’ve got those two levels of understanding . . . (Stakeholder 6)

Reluctance of providers to share business strategies with competitors

Lifestyle service providers are often in competition for contracts and may not want to data share because of fear of revealing their service provision strategies to other service providers:

The data we collect and the way that we designed the processes are key in securing future business and are therefore not something that we want readily available to competitors in the public domain. (Stakeholder 7)

That makes sense because yeah, I imagine some of them may have objections potentially, if they think they’re going to be compared with other areas of the effectiveness of other services. (Stakeholder 2)

Unaligned IT systems and expense of standardised software

Despite the benefits outlined by stakeholders, currently there are unaligned IT systems and expense of standardised software, in addition to the concerns that it would be costly to migrate from current datasets to a new integrated system and that the cost benefits may not emerge until the dataset is fully established:

I think you need to talk to providers . . . and Commissioners directly about it; I think there are insurmountable barriers that cost money. (Stakeholder 1)

Time and capacity to support any implementation as well as any budgetary or procurement processes or other local arrangements. (Stakeholder 5)

Governance and data access issues

Stakeholders identified several concerns relating to data sharing and governance. Specifically, concerns were raised surrounding the difficulties in fully establishing data sharing agreements across all parties. There also remains unanswered questions about Information Governance and location and security of the dataset:

If you’re going to make it useful, then you have to have a way for us to access it whilst maintaining data protection and ensuring that we’re using it in a way that you agreed with providers that it will be used. Anyway, a whole lot of issues about holding it in data protection. (Stakeholder 2)

. . . and especially with data sharing agreements that would need to be put in place between all the different providers. (Stakeholder 10)

Furthermore, a concern around the sensitive nature of some of the lifestyle data was expressed, with variation in the extent to which organisations are prepared to fully share their data:

Datasets and data collection methods vary greatly between services and there would be significant information governance issues with trying to combine them at a local level, let alone regional. (Stakeholder 11)

Well, I would be a bit concerned because I know that all the names and addresses are attached to that information. (Stakeholder 4)

Need for user involvement and consent

In planning for the construction and implementation of a regional integrated database, some stakeholders believed that there was a need for service users to fully understand, be involved in and consent to the use of their personal (albeit anonymised) data for research or commissioning purposes:

. . . and you to have, I guess consent from the service users as well, it’s going to be shared in a different way. You know, it depends on how the providers want it shared, because many of them will likely have some agreement already. (Stakeholder 10)

Data sharing would have to be done with client consent and how reasonable is it to ask clients to agree to their data being shared with numerous other stakeholders with no direct involvement in whatever intervention they’re receiving. (Stakeholder 11)

SWOT Analysis

A SWOT Analysis³⁰ was completed using the qualitative data to organise the identified themes to outline the strength, weakness, opportunities and threats for the potential implementation of an integrated lifestyle database (see Table 3).

Table 3.

Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis of data from the consultation exercise with public health professionals

Strengths	Weaknesses
• Datasets already exist in each of the local authority areas across the East Midlands region and within each provider organisation• Data are already routinely collected.• Some alignment with information technology (IT) systems already in place• Some standardisation in reporting mechanisms and variables collected already in place (particularly in relation to smoking cessation)• Evidence that some stakeholders would fully embrace the concept of having an integrated and shared dataset	• Collection of variables not completely standardised across the region• IT systems and processes not fully aligned across the region• Wide variety of currently commissioned providers of public health services currently in place• Areas vary in the profile of service provision: some offer fully integrated services encompassing all four key lifestyle areas, whereas others have separately delivered services• There is an initial need to map out provision across the region• Evidence to suggest that some stakeholders are sceptical about the practicalities and utility of having an integrated and shared dataset• Expensive to standardise software and approaches• Reluctance of companies to share their private commercial products• Commissioner expectations and demands vary wildly across Localities
Opportunities	Threats
• Great potential for a rich and well-powered resource for research and commissioning decisions• Potential for geographical comparisons in both Key Performance Indicators (KPIs) (from commissioner-level dataset) and individual-level lifestyle/sociodemographic data (provider-level dataset).• Potential for comparison across and between the four key public health lifestyle areas (would allow for comparison between individually commissioned and integrated lifestyle services)	• Data are sensitive and there is variation in the extent to which organisations are prepared to fully share their data• Difficulties in fully establishing data sharing agreements across all parties. Unanswered questions about Information Governance and location/security of dataset. Mechanisms for data access and permissions might be difficult to establish• Need to fully understand user involvement and consent to use personal (albeit anonymised) data for research/commissioning purposes• May be costly initially (to migrate from current dataset to a new integrated dataset) with cost benefits not emerging until dataset is fully established (high risk as difficult to accurately project/model)• Lifestyle service providers seem to be in competition for contracts and may not want to data share because of fear of revealing their service provision strategy

Discussion

The aim of this study was to explore the views of public health stakeholders regarding the acceptability of developing and implementing an integrated lifestyle dataset to support services across the East Midlands region of England. There were clear benefits identified by stakeholders, including its potential for easing information access, supporting service commissioning and its potential as a rich resource for supporting research. Several barriers were identified, including reluctance to reveal business strategies to rival organisations, cost of setting up and running the proposed database, complex information-sharing and governance, which would need addressing prior to the development and implementation of a formal integrated database. The present study provides important insight into some of the perceived facilitators and barriers that could be used to guide and inform future researchers when considering the development and implementation of an integrated public health database.

Improved access to large-scale, multimodal data has previously been viewed as essential to creating an environment where research, healthcare delivery and population health are underpinned by data-driven approaches.³⁸ Previous evidence has shown that improving access to data can largely increase the quantity, quality and diversity of scientific research,³⁹ and the facilitation of a more efficient secondary use of data.^40,41 Furthermore, the development of a regional integrated database has the potential to draw data from a wide range of providers and services allowing for a system-level insight into patient journeys and care utilisation while providing a unique epidemiological insight into key health determinants.¹¹ In addition to easing information access and its use as a rich resource for research, an integrated public health dataset was also viewed as useful in supporting and informing service commissioning. Evidence has previously highlighted the usefulness of integrated datasets in better assessing the magnitude of health problems, including identifying vulnerable populations, developing policy and evaluating interventions and initiatives.⁴² A poignant example involves the recent COVID-19 pandemic where the development and maintenance of many integrated public health databases have been integral in informing rapid decision-making at a local, regional, national and international level.^38,43

The potential benefit of easing information access is supported by evidence that combining data can enhance access to information at minimal cost.¹³ The ease in accessing information can enhance other potential benefits of service commissioning and research. As a rich resource for research, the proposed integrated database could contain individual-level variables for more detailed and stratified data analysis, as previous integrated database-related studies found a research-related benefit of increased power for secondary data statistical analysis.^10,11 Overall, these findings around benefits align with the views of experts and policymakers from a previous study, suggesting that Electronic Health Records offer significant benefits when they are used appropriately.⁴⁴ Hence, the proposed integrated lifestyle database could be useful not only within the East Midlands region but also in other regions of UK, and further afield, as it could be used to provide a snapshot of current situations and continually maintained to provide an ongoing source of data for researchers and local authorities. Specifically, like the Kent Integrated Database,¹¹ the proposed integrated database could be developed by linking individual-level lifestyle service data and updated regularly (e.g. monthly) for data to be available for research within a few months, easing access to information and allowing for rapid evaluation of service changes.¹¹

Despite the potential benefits surrounding the development of an integrated database, there are still important barriers to consider when integrating public health data, which need to be addressed and fully understood. In line with the views of public health stakeholders in the current study, both economic and technical barriers are widely considered major obstacles to data integration.^45,46 The cost of both human and technical resources to prepare data, and annotate and communicate with recipients in addition to technical solutions to collect, integrate and share complex, heterogeneous data is often problematic within the public health sector.^45,46 This is supported by previous evidence that show high acquisition and maintenance costs when implementing new electronic systems⁴⁴ in addition to restrictions of data harmonisation due the heterogeneity across outcomes.¹⁰

An important concern is around the wide variety of commissioned services and unstandardised collection of variables, data collection methods and incompatible IT systems, which could make data linkage very challenging. Concerns around the initial cost of aligning IT systems and setting up standardised software have been expressed in this study and supported by evidence from a previous study concerning drawbacks associated with Electronic Health Records including high acquisition and maintenance costs.⁴⁴ Similar concerns were found in another previous study relating to variations in service commissioning and collection of variables alongside the need for a more standardised approach to data collection to maximise the potential for data integration.¹⁰ While these concerns are important, it has been argued that the ultimate benefits of a fully integrated and functioning database could outweigh the initial cost of IT systems and standardised software.⁴⁴ Governance and data access concerns have also been expressed in the current study in terms of how best the proposed database can be housed and maintained. These findings support previous evidence on practical issues around how and where integrated data should be stored, controlled and accessed.¹³ Data sharing could help to harmonise organisations,⁴⁷ but when sensitive information is involved, many lifestyle service providers within organisations like local authorities would be reluctant to share their data governed by privacy conditions.⁴⁸ As expressed by stakeholders in the current study, the concern here is about how service user privacy will be guaranteed. A related barrier is the need for service user involvement and consent, as service providers and users may refuse to share their data, as they may be worried about sharing business strategies with competitors and the risk of giving away person-identifying information. A reluctance to share data could slow research efforts to help reduce illness and prolong life, and taxpayers who contribute to research could be denied the benefits of such research efforts.¹³ However, concerns around data sharing could be resolved if lifestyle service providers and users are reassured of protective measures such as anonymising the information collected into the integrated database. Drawing from the Kent Integrated Database,¹¹ this could be done by incorporating a unique reference number across all datasets, allowing individual lifestyle service users to be tracked across local authorities, leading to high-quality linkage with low risk of identifying personal and sensitive data of service providers and users.¹¹

The findings in the current study closely align with the feasibility framework concepts (Table 1). The benefits to the proposed integrated database found in this study, including ease of information access and potential to support research and lifestyle service commissioning, are aligned with the concepts of acceptability and demand²⁰ for the development and implementation of the proposed integrated database in the East Midlands region of England and lessons learned potentially applicable to other regions. On the other hand, barriers identified relate to the concept of practicality²⁰ which could oppose the development and implementation of the integrated database. However, evidence suggests that such barriers or local factors should be taken into consideration when planning the construction and implementation of an integrated database.^10,11 Hence, one strength of this study is the identification of local factors, which are benefits and barriers, directly from stakeholders across the East Midlands region, which could be important for informing the development and implementation of the proposed integrated database. In addition, this study has provided relevant information from stakeholders that could contribute to the development and implementation of an individual-level integrated database, which currently does not exist particularly in the study region.

Limitations

An observed limitation of this study was that several stakeholders were willing, but unable to participate in the qualitative interviews due to the ongoing COVID-19 pandemic or workload. Public health consultants, practitioners, IT personnel, service providers and users who missed the qualitative interviews could have offered greater insight if they had participated. Furthermore, while this study may be used to inform the development of data integration across other regions of the UK, it is important to acknowledge that the views in the present study were specifically from stakeholders in the East Midlands region.

Implications for practice and further research

The barriers and benefits need to be addressed in planning for the construction and implementation of an integrated database. Further in-depth interviews with more stakeholders, particularly service users and providers, IT personnel, governance and data protection experts, is recommended to explore how barriers to the database construction and implementation can be overcome. Future research should seek to: examine under what conditions people would be willing to work collaboratively with a shared dataset across the East Midlands region; examine any potential benefits and barriers to data access or collation and sharing; and produce a toolkit, outlining the key factors to be considered (and how these could be addressed) in the construction of a regional integrated lifestyle database.

Conclusion

Based on findings from conducting qualitative interviews with public health stakeholders, an integrated lifestyle dataset has the potential to inform public health policy and practice in the East Midlands region of England and other local authorities across the UK in their approach to lifestyle data integration and usage at local authority level. It also has the potential to support in-depth statistical analysis, informing public health lifestyle interventions leading to prevention or reduction in long-term conditions and improvement in health outcomes. However, local factors such as the barriers and benefits identified should be considered.

Supplemental Material

sj-docx-1-rsh-10.1177_17579139221136726 – Supplemental material for Exploring the perceptions and acceptability of an integrated lifestyle database for public health research and service commissioning: a qualitative study

Supplemental material, sj-docx-1-rsh-10.1177_17579139221136726 for Exploring the perceptions and acceptability of an integrated lifestyle database for public health research and service commissioning: a qualitative study by JNA Akanuwe, S Cooke, H Henderson and R Kane in Perspectives in Public Health

Footnotes

Acknowledgements

Acknowledgements go to the Directors of Public Health in the East Midlands, particularly Professor Derek Ward, Director of Public Health, Lincolnshire and Chair of the East Midlands Directors of Public Health for his support throughout this project. Acknowledgements also go to the stakeholders who participated in the consultation exercise and willingly shared their views to inform this study. Thanks also go to Sally Bassett and David Clarke for their role as steering group members who guided the study to completion and to the Community and Health Research Unit Study Review team for reviewing the paper and offering advice.

Conflict of Interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This project was funded by the National Institute for Health Research East Midlands Clinical Research Network and the College of Social Science, University of Lincoln.

Ethical Approval

The project was formally logged with the University of Lincoln Ethics system on 16 September 2020 (Ethics review REF number: 2020_3761).

ORCID iD

Joseph N.A Akanuwe

Availability of Data and Materials

The data used to support the findings of this study are available from the corresponding author upon request.

Supplemental Material

Supplemental material for this article is available online.

References

Biswas

Faulkner

et al. Sedentary time and its association with risk for disease incidence, mortality, and hospitalization in adults. Ann Intern Med 2015;162:123.

Jha

The hazards of smoking and the benefits of cessation: a critical summation of the epidemiological evidence in high-income countries. eLife 2020;9:e49979.

Parkin

Boyd

Walker

LC.

The fraction of cancer attributable to lifestyle and environmental factors in the UK in 2010. Br J Cancer 2011;105:S77–81.

Rehm

Baliunas

Borges

et al. The relation between different dimensions of alcohol consumption and burden of disease: an overview external icon. Addiction 2010;105:817–43.

WHO. Physical activity factsheet N°385, 2016. Available online at: https://www.salute.gov.it/imgs/C_17_pubblicazioni_2177_ulterioriallegati_ulterioreallegato_0_alleg.pdf (last accessed 24 November 2020).

Wilmot

Edwardson

Achana

et al. Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and meta-analysis. Diabetologia 2012;55(11):2895–905.

Health Social Care Act 2012, c.7, 2012. Available online at: https://www.legislation.gov.uk/ukpga/2012/7/contents/enacted (last accessed 20 September 2020).

Holding

Fairbrother

Griffin

et al. Exploring the local policy context for reducing health inequalities in children and young people: an in depth qualitative case study of one local authority in the North of England, UK. BMC Public Health 2021;21:887.

Glennon

The ‘death of improvement’: an exploration of the legacy of performance and service improvement reform in English local authorities, 1997-2017, 2017. Available online at: https://repository.lboro.ac.uk/articles/thesis/The_death_of_improvement_an_exploration_of_the_legacy_of_performance_and_service_improvement_reform_in_English_local_authorities_1997-2017/9496703 (last accessed 26 October 2022).

10.

Lakerveld

Loyen

Ling

et al. Identifying and sharing data for secondary data analysis of physical activity, sedentary behaviour and their determinants across the life course in Europe: general principles and an example from DEDIPAC. BMJ Open 2017;7:e017489.

11.

Lewer

Bourne

George

et al. Data resource: the Kent Integrated Dataset (KID). Int J Populat Data Sci 2018;3:6.

12.

Burgun

Bernal-Delgado

Kuchinke

et al. Health data for public health: towards new ways of combining data sources to support research efforts in Europe. Yearb Med Inform 2017;26(1):235–40.

13.

Pisani

AbouZahr

Sharing health data: good intentions are not enough. Bull World Health Organ 2010;88(6):462–6.

14.

Clinical Practice Research Datalink [CPRD]. CPRD. Available online at: https://www.cprd.com/ (last accessed 24 October 2021).

15.

The Health Improvement Network [THIN]. THIN database. Available online at: https://www.the-health-improvement-network.com/ (last accessed 24 October 2021).

16.

Hippisley-Cox

A Description of the 4th Version of the QRESEARCH Database: An analysis using QRESEARCH for the Department of Health. Nottingham: University of Nottingham; 2007.

17.

Public Health England. Public health profiles. Fingertips.phe.org.uk. Available online at: https://fingertips.phe.org.uk/profile/health-profiles (last accessed 23 October 2021).

18.

Department of Health Social Care. New obesity strategy unveiled as country urged to lose weight to beat coronavirus (COVID-19) and protect the NHS. Available online at: https://www.gov.uk/government/news/new-obesity-strategy (last accessed 12 January 2020).

19.

Department of Health Social Care. Integration and innovation: working together to improve health and social care for all. Policy paper. Available online at: https://www.gov.uk/government/publications/working-together-to-improve-health-and-social-care-for-all/integration-and-innovation-working-together-to-improve-health-and-social-care-for-all-html-version (last accessed 3 March 2021).

20.

Bowen

Kreuter

Spring

et al. How we design feasibility studies. Am J Prev Med 2009;36:452–7.

21.

Perren

Ram

Case-study method in small business and entrepreneurial research: mapping boundaries and perspectives. Int Small Bus J 2004;22(1):83–101.

22.

Leitch

Hill

Harrison

RT.

The philosophy and practice of interpretivist research in entrepreneurship: quality, validation, and trust. Org Res Meth 2010;13(1):67–84.

23.

Lincoln

Guba

EG.

Naturalistic inquiry. Beverly Hills, CA: Sage; 1985.

24.

Glaser

Strauss

The discovery of grounded theory. Chicago, IL: Aldine; 1967.

25.

Bloomberg

Volpe

Completing your qualitative dissertation: A roadmap from beginning to end. Thousand Oaks, CA: Sage; 2008.

26.

Gabriel

Inductive and deductive approaches to research, 2013. Available online at: http://deborahgabriel.com/2013/03/17/inductive-and-deductive-approachesto-research (last accessed 26 July 2022).

27.

Creswell

JW.

Qualitative inquiry & research design: Choosing among five approaches. 3rd edn. Thousand Oaks, CA: Sage; 2013.

28.

Boyatzis

Transforming qualitative information: Thematic analysis and code development. London: Sage; 1998.

29.

Fereday

Muir-Cochrane

Demonstrating rigor using thematic analysis: A hybrid approach of inductive and deductive coding and theme development. Int J Qual Meth 2006;5(1):80–92.

30.

Renault

SWOT analysis: strengths, weaknesses, opportunities, and threats. Community Tool Box, Section 14, 2017. Available online at: http://ctb.ku.edu/en/table-of-contents/assessment/assessing-community-needs-and-resources/swot-analysis/main (last accessed 26 October 2022).

31.

Hennink

Kaiser

Marconi

VC.

Code saturation versus meaning saturation: how many interviews are enough?

Qual Health Res 2017;27:591–608.

32.

Ritchie

Spencer

Qualitative data analysis for applied policy research. In: Bryman

Burgess

(eds) Analysing qualitative data. London: Routledge; 1994, pp. 173–194.

33.

Spencer

Richie

O’Conner

et al. Analysis in practice. In: Ritchie

Lewis

Nicholls

et al. (eds) Qualitative research practice: A guide for social science students and researchers. London: Sage; 2013, pp. 295–345.

34.

Akkerman

Admiral

Brekelmans

et al. Auditing quality of research in social sciences. Qual Quant 2006;42:257–74.

35.

Koch

Establishing rigour in qualitative research: the decision trail. J Adv Nurs 2006;53:91–103.

36.

Gale

Heath

Cameron

et al. Using the framework method for the analysis of qualitative data in multi-disciplinary health research. BMC Med Res Methodol 2013;13:18.

37.

Tong

Sainsbury

Craig

Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care 2007;19(6):349–57.

38.

Foraker

Lai

Kannampallil

et al. Transmission dynamics: data sharing in the COVID-19 era. Learn Health Syst 2021;5(1):e10235.

39.

Nagaraj

Shears

De Vaan

Improving data access democratizes and diversifies science. Proc Natl Acad Sci 2020;117:23490.

40.

Foraker

Mann

Payne

PRO

. Are synthetic data derivatives the future of translational medicine? JACC Basic Transl Sci 2018;3(5):716–8.

41.

Nair

Hsu

Celi

. Challenges and opportunities in secondary analyses of electronic health record data. In: Secondary analysis of electronic health records. Cham: Springer; 2016, pp. 17–26.

42.

Bottle

Cohen

Lucas

et al. How an electronic health record became a real-world research resource: comparison between London’s Whole Systems Integrated Care database and the Clinical Practice Research Datalink. BMC Med Inform Decis Mak 2020;20:71.

43.

Neil-Sztramko

Belita

Traynor

et al. Methods to support evidence-informed decision-making in the midst of COVID-19: creation and evolution of a rapid review service from the National Collaborating Centre for Methods and Tools. BMC Med Res Methodol 2021;21:231.

44.

Menachemi

Collum

TH.

Benefits and drawbacks of electronic health record systems. Risk Manag Healthc Policy 2011;4:47–55.

45.

Schwalbe

Wahl

Song

et al. Data sharing and global public health: defining what we mean by data. Front Dig Health 2929;2:42.

46.

Van Panhuis

Paul

Emerson

et al. A systematic review of barriers to data sharing in public health. BMJ Public Health 2014;14:1144.

47.

Irani

Sharif

Kamal

et al. Visualising a knowledge mapping of information systems investment evaluation. Expert Syst Appl 2014;41:105–25.

48.

Khan

Uddin

Gupta

. Seven vs of big data understanding big data and extract value. In: Proceedings of 2014 zone 1 conference of the American Society for Engineering Education (ASEE Zone 1) – IEEE (2014), Bridgeport, CT, 3–5 April 2014, pp. 1–5. New York: IEEE.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.03 MB