Factors influencing harmonized health data collection, sharing and linkage in Denmark and Switzerland: A systematic review

Organ Donation and Transplantation Registries Across the Globe: A Review of the Current State

BACKGROUND

The current landscape of organ donation and transplantation (ODT) registries is not well established. This narrative review sought to identify and characterize the coverage, structure, and data capture of ODT registries globally.

METHODS

We conducted a literature search using Ovid Medline and web searches to identify ODT registries from 2000 to 2023. A list of ODT registries was compiled based on publications of registry design, studies, and reports. Extracted data elements included operational features of registries and the types of donor and recipient data captured.

RESULTS

We identified 129 registries encompassing patients from all continents except Antarctica. Most registries were active, received funding from government or professional societies, were national in scope, included both adult and pediatric patients, and reported patient-level data. Registries included kidney (n = 99), pancreas (n = 32), liver (n = 44), heart (n = 35), lung (n = 30), intestine (n = 15), and islet cell (n = 5) transplants. Most registries captured donor data (including living versus deceased) and recipient features (including demographics, cause of organ failure, and posttransplant outcomes) but there was underreporting of other domains (eg, donor comorbidities, deceased donor referral rates, waitlist statistics).

CONCLUSIONS

This review highlights existing ODT registries globally and serves as a call for increased visibility and transparency in data management and reporting practices. We propose that standards for ODT registries, a common data model, and technical platforms for collaboration, will enable a high-functioning global ODT system responsive to the needs of transplant candidates, recipients, and donors.

System interoperability and data linkage in the era of health information management: A bibliometric analysis

Background: Across the world, health data generation is growing exponentially. The continuous rise of new and diversified technology to obtain and handle health data places health information management and governance under pressure. Lack of data linkage and interoperability between systems undermines best efforts to optimise integrated health information technology solutions. Objective: This research aimed to provide a bibliometric overview of the role of interoperability and linkage in health data management and governance. Method: Data were acquired by entering selected search queries into Google Scholar, PubMed, and Web of Science databases and bibliometric data obtained were then imported to Endnote and checked for duplicates. The refined data were exported to Excel, where several levels of filtration were applied to obtain the final sample. These sample data were analysed using Microsoft Excel (Microsoft Corporation, Washington, USA), WORDSTAT (Provalis Research, Montreal, Canada) and VOSviewer software (Leiden University, Leiden, Netherlands). Results: The literature sample was retrieved from 3799 unique results and consisted of 63 articles, present in 45 different publications, both evaluated by two specific in-house global impact rankings. Through VOSviewer, three main clusters were identified: (i) e-health information stakeholder needs; (ii) e-health information quality assessment; and (iii) e-health information technological governance trends. A residual correlation between interoperability and linkage studies in the sample was also found. Conclusion: Assessing stakeholders' needs is crucial for establishing an efficient and effective health information system. Further and diversified research is needed to assess the integrated placement of interoperability and linkage in health information management and governance. Implications: This research has provided valuable managerial and theoretical contributions to optimise system interoperability and data linkage within health information research and information technology solutions.

Exploring evidence use and capacity for health services management and planning in Swiss health administrations: A mixed-method interview study

BACKGROUND

Health administrations require evidence, meaning robust information, data, and research, on health services and systems. Little is known about the resources and processes available within administrations to support evidence-informed policymaking. This study assessed Swiss health administrations' capacity for evidence use and investigated civil servants' needs and perspectives regarding the role and use of evidence in health services management and planning.

METHODS

In this mixed-method study, we interviewed civil servants from Swiss German-speaking cantonal health administrations. We quantitatively assessed administrations' organization-level capacity by applying six structured interviews using an existing measurement tool (ORACLe). Individual-level needs and perspectives regarding evidence use and capacity were qualitatively explored with twelve in-depth interviews that were analyzed using the framework method.

FINDINGS

Respondents indicated moderate evidence-use capacity in all administrations. Administrations displayed a similar pattern of high and low capacity in specific capacity areas, generally with considerable variation within administrations. Most administrations indicated high capacity for producing or commissioning evidence and close relationships with research. They showed limited capacity in the documentation of processes and availability of tools, programs, or training opportunities. Administrations place the responsibility for engagement with evidence at the level of individual civil servants rather than at the organizational level. Although administrations highly value evidence-informed policymaking and consider it vital to effective health services management and planning, they face significant constraints in accessing evidence-specific resources and receive little organizational support. Administrations rely on external capacity to compensate for these limitations and engage with evidence pragmatically.

CONCLUSION

Our findings indicate moderate and improvable capacity for evidence use in Swiss health administrations that place limited value on organizational support. Besides strengthening organizational support, leadership buy-in, particular staff needs, and balancing the implementation of specific measures with the provision of more general resources should be considered to unlock the potential of strengthened engagement with evidence.

Socio-Technical Analysis of the Benefits and Barriers to Using a Digital Representation of the Global Horse Population in Equine Veterinary Medicine

There is a consensus that future medicine will benefit from a comprehensive analysis of harmonized, interconnected, and interoperable health data. These data can originate from a variety of sources. In particular, data from veterinary diagnostics and the monitoring of health-related life parameters using the Internet of Medical Things are considered here. To foster the usage of collected data in this way, not only do technical aspects need to be addressed but so do organizational ones, and to this end, a socio-technical matrix is first presented that complements the literature. It is used in an exemplary analysis of the system. Such a socio-technical matrix is an interesting tool for analyzing the process of data sharing between actors in the system dependent on their social relations. With the help of such a socio-technical tool and using equine veterinary medicine as an example, the social system of veterinarians and owners as actors is explored in terms of barriers and enablers of an effective digital representation of the global equine population.

Road traffic death coding quality in the WHO Mortality Database

Objective

To evaluate the precision and dependability of road traffic mortality data recorded in the World Health Organization Mortality Database and investigate how uncorrected data influence vital mortality statistics used in traffic safety programmes worldwide.

Methods

We assessed country and territory-specific data quality from 2015 to 2020 by calculating the proportions of five types of nonspecific cause of death codes related to road traffic mortality. We compared age-adjusted road traffic mortality and changes in the average annual mortality rate before and after correcting the deaths with nonspecific codes. We generated road traffic mortality projections with both corrected and uncorrected codes, and redistributed the data using the proportionate method.

Findings

We analysed data from 124 countries and territories with at least one year of mortality data from 2015 to 2020. The number of countries and territories reporting more than 20% of deaths with ill-defined or unknown cause was 2; countries reporting injury deaths with undetermined intent was 3; countries reporting unspecified unintentional injury deaths was 21; countries reporting unspecified transport crash deaths was 3; and countries reporting unspecified unintentional road traffic deaths was 30. After redistributing deaths with nonspecific codes, road traffic mortality changed by greater than 50% in 7% (5/73) to 18% (9/51) of countries and territories.

Conclusion

Nonspecific codes led to inaccurate mortality estimates in many countries. We recommend that injury researchers and policy-makers acknowledge the potential pitfalls of relying on raw or uncorrected road traffic mortality data and instead use corrected data to ensure more accurate estimates when improving road traffic safety programmes.

Case Study: Using a Shared International Database to Document Veterinary Consumption of Antibiotics in Pakistan

In this paper, we present a case study of Pakistan documenting the use of antimicrobial drugs in poultry flocks in the VetCAb-ID database. Unlike other databases, this system allows international users to upload their data directly. Based on expert interviews and a review of the latest publications on the topic, we provide an alternative approach to harmonizing data collection among countries. This paper will provide impetus to formulate joint requirement documentation for an AMU database on a global level that international users can adapt for their own purposes and projects.

The Swiss health care atlas-relaunch in scale

Inspired by the Dartmouth Atlas of Health Care, an early version of the Swiss Atlas of Health Care (SAHC) was released in 2017. The SAHC provides an intuitive visualization of regional variations of medical care delivery and thus allows for a broad diffusion of the contents. That is why the SAHC became widely accepted amongst health care stakeholders. In 2021, the relaunch of the SAHC was initiated to update as well as significantly expand the scope of measures depicted on the platform, also integrating indicators for outpatient care in order to better reflect the linkages between inpatient and outpatient health care provision. In the course of this relaunch, the statistical and technical aspects of the SAHC have been reviewed and updated. This paper presents the key aspects of the relaunch project and provides helpful insights for similar endeavors elsewhere.

Sensing the (digital) pulse. Future steps for improving the secondary use of data for research in Switzerland

Introduction

Ensuring that the health data infrastructure and governance permits an efficient secondary use of data for research is a policy priority for many countries. Switzerland is no exception and many initiatives have been launched to improve its health data landscape. The country now stands at an important crossroad, debating the right way forward. We aimed to explore which specific elements of data governance can facilitate - from ethico-legal and socio-cultural perspectives - the sharing and reuse of data for research purposes in Switzerland.

Methods

A modified Delphi methodology was used to collect and structure input from a panel of experts via successive rounds of mediated interaction on the topic of health data governance in Switzerland.

Results

First, we suggested techniques to facilitate data sharing practices, especially when data are shared between researchers or from healthcare institutions to researchers. Second, we identified ways to improve the interaction between data protection law and the reuse of data for research, and the ways of implementing informed consent in this context. Third, we put forth ideas on policy changes, such as the steps necessary to improve coordination between different actors of the data landscape and to win the defensive and risk-adverse attitudes widespread when it comes to health data.

Conclusions

After having engaged with these topics, we highlighted the importance of focusing on non-technical aspects to improve the data-readiness of a country (e.g., attitudes of stakeholders involved) and of having a pro-active debate between the different institutional actors, ethico-legal experts and society at large.

Social determinants of health data in solid organ transplantation: National data sources and future directions

Health equity research in transplantation has largely relied on national data sources, yet the availability of social determinants of health (SDOH) data varies widely among these sources. We sought to characterize the extent to which national data sources contain SDOH data applicable to end-stage organ disease (ESOD) and transplant patients. We reviewed 10 active national data sources based in the United States. For each data source, we examined patient inclusion criteria and explored strengths and limitations regarding SDOH data, using the National Institutes of Health PhenX toolkit of SDOH as a data collection instrument. Of the 28 SDOH variables reviewed, eight-core demographic variables were included in ≥80% of the data sources, and seven variables that described elements of social status ranged between 30 and 60% inclusion. Variables regarding identity, healthcare access, and social need were poorly represented (≤20%) across the data sources, and five of these variables were included in none of the data sources. The results of our review highlight the need for improved SDOH data collection systems in ESOD and transplant patients via: enhanced inter-registry collaboration, incorporation of standardized SDOH variables into existing data sources, and transplant center and consortium-based investigation and innovation.

Development and implementation of a national online application system for cross-jurisdictional linked data

The Population Health Research Network (PHRN) is an Australian national data linkage infrastructure that links a wide range of health and human services data in privacy-preserving ways. The data linkage infrastructure enables researchers to apply for access to routinely collected, linked, administrative data from the six states and two territories which make up the Commonwealth of Australia, as well as data collected by the Australian Government. The PHRN is a distributed network where data is collected and managed at the respective jurisdictional and/or cross-jurisdictional levels. As a result, access to linked data from multiple jurisdictions requires complex approval processes. This paper describes Australia's approach to enabling access to linked data from multiple jurisdictions. It covers the identification of, and agreement to, a minimum set of data items to be included in a unified national application form, the development and implementation of a national online application system and the harmonisation of business processes for cross-jurisdictional research projects. Utilisation of the online application system and the ongoing challenges of data linkage across jurisdictions are discussed. Changes to the data custodian and ethics committee approval criteria were out of scope for this project.

Design and rationale of DISCOVER global registry in type 2 diabetes: Real-world insights of treatment patterns and its relationship with cardiovascular, renal, and metabolic multimorbidities

AIM

The DISCOVER Global Registry (DGR) aims to provide insights into patient attributes and treatment patterns in patients with type 2 diabetes mellitus (T2DM) seen in clinical practice and understand the patterns and impact of treatment strategies on cardio-renal-metabolic multimorbidities. It aims to augment the real-world evidence base created by the DISCOVER study.

METHODS

The ongoing study is a global, prospective, open-source, physician-led registry and involves non-interventional data collection through cloud-based electronic case report form platform from participants with T2DM receiving care as part of routine clinical practice. The DGR will collect longitudinal prospective data on the following: (a) patient, healthcare provider, and healthcare system characteristics; (b) treatment patterns and factors influencing therapy changes; (c) disease duration and glycemic control; (d) management of micro and/or macrovascular complications; (e) management of associated risk factors; (f) outcomes (hospitalization/death), (g) quality of care indicators (eye/foot examination); (h) healthcare resource utilization; and (i) patient-reported outcomes.

CONCLUSION

Establishment of this long-term, scalable, and sustainable global registry offers opportunities to enhance understanding of care gaps, establish quality benchmarks, and understand the role of various treatment strategies in addressing the multifactorial pathophysiology of T2DM and associated comorbidities- potentially enabling transformation of clinical data into actionable insights for improving patient outcomes.

National and international kidney failure registries: characteristics, commonalities, and contrasts

Registries are essential for health infrastructure planning, benchmarking, continuous quality improvement, hypothesis generation, and real-world trials. To date, data from these registries have predominantly been analyzed in isolated "silos," hampering efforts to analyze "big data" at the international level, an approach that provides wide-ranging benefits, including enhanced statistical power, an ability to conduct international comparisons, and greater capacity to study rare diseases. This review serves as a valuable resource to clinicians, researchers, and policymakers, by comprehensively describing kidney failure registries active in 2021, before proposing approaches for inter-registry research under current conditions, as well as solutions to enhance global capacity for data collaboration. We identified 79 kidney-failure registries spanning 77 countries worldwide. International Society of Nephrology exemplar initiatives, including the Global Kidney Health Atlas and Sharing Expertise to support the set-up of Renal Registries (SharE-RR), continue to raise awareness regarding international healthcare disparities and support the development of universal kidney-disease registries. Current barriers to inter-registry collaboration include underrepresentation of lower-income countries, poor syntactic and semantic interoperability, absence of clear consensus guidelines for healthcare data sharing, and limited researcher incentives. This review represents a call to action for international stakeholders to enact systemic change that will harmonize the current fragmented approaches to kidney-failure registry data collection and research.

Individual notions of fair data sharing from the perspectives of Swiss stakeholders

Background

The meaningful sharing of health data between different stakeholders is central to the advancement of science and to improve care offered to individual patients. However, it is important that the interests of individual stakeholders involved in this data sharing ecosystem are taken into account to ensure fair data sharing practices. In this regard, this qualitative study investigates such practices from the perspectives of a subset of relevant Swiss expert stakeholders, using a distributive justice lens.

Methods

Using purposive and snowball sampling methodologies, 48 expert stakeholders from the Swiss healthcare and research domains were recruited for semi-structured interviews. After the experts had consented, the interviews were audio-recorded and transcribed verbatim, but omitting identifying information to ensure confidentiality and anonymity. A thematic analysis using a deductive approach was conducted to identify fair data sharing practices for secondary research purposes. Themes and subthemes were then identified and developed during the analysis.

Results

Three distributive justice themes were identified in the data sharing negotiation processes, and these are: (i) effort, which was subcategorized into two subthemes (i.e. a claim to data reciprocity and other reciprocal advantages, and a claim to transparency on data re-use), (ii) compensation, which was subcategorized into two subthemes (i.e. a claim to an academic compensation and a claim to a financial compensation), and lastly, (iii) contribution, i.e. the significance of data contributions should be matched with a corresponding reward.

Conclusions

This qualitative study provides insights, which could inform policy-making on claims and incentives that encourage Swiss expert stakeholders to share their datasets. Importantly, several claims have been identified and justified under the basis of distributive justice principles, whilst some are more debatable and likely insufficient in justifying data sharing activities. Nonetheless, these claims should be taken seriously and discussed more broadly. Indeed, promoting health research while ensuring that healthcare systems guarantee better services, it is paramount to ensure that solutions developed are sustainable, provide fair criteria for academic careers and promote the sharing of high quality data to advance science.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06906-2.

Variation in approaches to antimicrobial use surveillance in high-income secondary care settings: a systematic review

Introduction

In secondary care, antimicrobial use (AMU) must be monitored to reduce the risk of antimicrobial resistance and infection-related complications. However, there is variation in how hospitals address this challenge, partly driven by each site’s level of digital maturity, expertise and resources available. This systematic review investigated approaches to measuring AMU to explore how these structural differences may present barriers to engagement with AMU surveillance.

Methods

We searched four digital databases and the websites of relevant organizations for studies in high-income, inpatient hospital settings that estimated AMU in adults. Excluded studies focused exclusively on antiviral or antifungal therapies. Data were extracted data on 12 fields (study description, data sources, data extraction methods and professionals involved in surveillance). Proportions were estimated with 95% CIs.

Results

We identified 145 reports of antimicrobial surveillance from Europe (63), North America (53), Oceania (14), Asia (13) and across more than continent (2) between 1977 and 2018. Of 145 studies, 47 carried out surveillance based on digital data sources. In regions with access to electronic patient records, 26/47 studies employed manual methods to extract the data. The majority of identified professionals involved in these studies were clinically trained (87/93).

Conclusions

Even in regions with access to electronic datasets, hospitals rely on manual data extraction for this work. Data extraction is undertaken by healthcare professionals, who may have conflicting priorities. Reducing barriers to engagement in AMU surveillance requires investment in methods, resources and training so that hospitals can extract and analyse data already contained within electronic patient records.

Evolution or Revolution? Recommendations to Improve the Swiss Health Data Framework

Background: Facilitating access to health data for public health and research purposes is an important element in the health policy agenda of many countries. Improvements in this sense can only be achieved with the development of an appropriate data infrastructure and the implementations of policies that also respect societal preferences. Switzerland is a revealing example of a country that has been struggling to achieve this aim. The objective of the study is to reflect on stakeholders' recommendations on how to improve the health data framework of this country.

Methods: We analysed the recommendations collected as part of a qualitative study including 48 expert stakeholders from Switzerland that have been working principally with health databases. Recommendations were divided in themes and subthemes according to applied thematic analysis.

Results: Stakeholders recommended several potential improvements of the health data framework in Switzerland. At the general level of mind-set and attitude, they suggested to foster the development of an explicit health data strategy, better communication and the respect of societal preferences. In terms of infrastructure, there were calls for the creation of a national data center, the improvement of IT solutions and the use of a Unique Identifier for patient data. Lastly, they recommended harmonising procedures for data access and to clarify data protection and consent rules.

Conclusion: Recommendations show several potential improvements of the health data framework, but they have to be reconciled with existing policies, infrastructures and ethico-legal limitations. Achieving a gradual implementation of the recommended solutions is the preferable way forward for Switzerland and a lesson for other countries that are also seeking to improve health data access for public health and research purposes.

Systemic Fairness for Sharing Health Data: Perspectives From Swiss Stakeholders

Introduction: Health research is gradually embracing a more collectivist approach, fueled by a new movement of open science, data sharing and collaborative partnerships. However, the existence of systemic contradictions hinders the sharing of health data and such collectivist endeavor. Therefore, this qualitative study explores these systemic barriers to a fair sharing of health data from the perspectives of Swiss stakeholders.

Methods: Purposive and snowball sampling were used to recruit 48 experts active in the Swiss healthcare domain, from the research/policy-making field and those having a high position in a health data enterprise (e.g., health register, hospital IT data infrastructure or a national health data initiative). Semi-structured interviews were then conducted, audio-recorded, verbatim transcribed with identifying information removed to guarantee the anonymity of participants. A theoretical thematic analysis was then carried out to identify themes and subthemes related to the topic of systemic fairness for sharing health data.

Results: Two themes related to the topic of systemic fairness for sharing health data were identified, namely (i) the hypercompetitive environment and (ii) the legal uncertainty blocking data sharing. The theme, hypercompetitive environment was further divided into two subthemes, (i) systemic contradictions to fair data sharing and the (ii) need of fair systemic attribution mechanisms.

Discussion: From the perspectives of Swiss stakeholders, hypercompetition in the Swiss academic system is hindering the sharing of health data for secondary research purposes, with the downside effect of influencing researchers to embrace individualism for career opportunities, thereby opposing the data sharing movement. In addition, there was a perceived sense of legal uncertainty from legislations governing the sharing of health data, which adds unreasonable burdens on individual researchers, who are often unequipped to deal with such facets of their data sharing activities.

'It’s not something you can take in your hands'. Swiss experts’ perspectives on health data ownership: an interview-based study

Objectives

The evolution of healthcare and biomedical research into data-rich fields has raised several questions concerning data ownership. In this paper, we aimed to analyse the perspectives of Swiss experts on the topic of health data ownership and control.

Design

In our qualitative study, we selected participants through purposive and snowball sampling. Interviews were recorded, transcribed verbatim and then analysed thematically.

Setting

Semi-structured interviews were conducted in person, via phone or online.

Participants

We interviewed 48 experts (researchers, policy makers and other stakeholders) of the Swiss health-data framework.

Results

We identified different themes linked to data ownership. These include: (1) the data owner: data-subjects versus data-processors; (2) uncertainty about data ownership; (3) labour as a justification for data ownership and (4) the market value of data. Our results suggest that experts from Switzerland are still divided about who should be the data owner and also about what ownership would exactly mean. There is ambivalence between the willingness to acknowledge patients as the data owners and the fact that the effort made by data-processors (eg, researchers) to collect and manage the data entitles them to assert ownership claims towards the data themselves. Altogether, a tendency to speak about data in market terms also emerged.

Conclusions

The development of a satisfactory account of data ownership as a concept to organise the relationship between data-subjects, data-processors and data themselves is an important endeavour for Switzerland and other countries who are developing data governance in the healthcare and research domains. Setting clearer rules on who owns data and on what ownership exactly entails would be important. If this proves unfeasible, the idea that health data cannot truly belong to anyone could be promoted. However, this will not be easy, as data are seen as an asset to control and profit from.

How to Design AI-Driven Clinical Trials in Nuclear Medicine

Artificial intelligence (AI) is an overarching term for a multitude of technologies which are currently being discussed and introduced in several areas of medicine and in medical imaging specifically. There is, however, limited literature and information about how AI techniques can be integrated into the design of clinical imaging trials. This article will present several aspects of AI being used in trials today and how imaging departments and especially nuclear medicine departments can prepare themselves to be at the forefront of AI-driven clinical trials. Beginning with some basic explanation on AI techniques currently being used and existing challenges of its implementation, it will also cover the logistical prerequisites which have to be in place in nuclear medicine departments to participate successfully in AI-driven clinical trials.