International comparisons of health system performance among OECD countries: Opportunities and data privacy protection challenges

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.

Multirole of the internet of medical things (IoMT) in biomedical systems for managing smart healthcare systems: An overview of current and future innovative trends

Internet of Medical Things (IoMT) is an emerging subset of Internet of Things (IoT), often called as IoT in healthcare, refers to medical devices and applications with internet connectivity, is exponentially gaining researchers' attention due to its wide-ranging applicability in biomedical systems for Smart Healthcare systems. IoMT facilitates remote health biomedical system and plays a crucial role within the healthcare industry to enhance precision, reliability, consistency and productivity of electronic devices used for various healthcare purposes. It comprises a conceptualized architecture for providing information retrieval strategies to extract the data from patient records using sensors for biomedical analysis and diagnostics against manifold diseases to provide cost-effective medical solutions, quick hospital treatments, and personalized healthcare. This article provides a comprehensive overview of IoMT with special emphasis on its current and future trends used in biomedical systems, such as deep learning, machine learning, blockchains, artificial intelligence, radio frequency identification, and industry 5.0.

Comparing risk-adjusted inpatient fall rates internationally: validation of a risk-adjustment model using multicentre cross-sectional data from hospitals in Switzerland and Austria

BACKGROUND

Inpatient falls in hospitals are an acknowledged indicator of quality of care. International comparisons could highlight quality improvement potential and enable cross-national learning. Key to fair cross-national comparison is the availability of a risk adjustment model validated in an international context. This study aimed to 1) ascertain that the variables of the inpatient fall risk adjustment model do not interact with country and thus can be used for risk adjustment, 2) compare the risk of falling in hospitals between Switzerland and Austria after risk adjustment.

METHODS

The data on inpatient falls from Swiss and Austrian acute care hospitals were collected on a single measurement day in 2017, 2018 and 2019 as part of an international multicentre cross-sectional study. Multilevel logistic regression models were used to screen for interaction effects between the patient-related fall risk factors and the countries. The risks of falling in hospital in Switzerland and in Austria were compared after applying the risk-adjustment model.

RESULTS

Data from 176 hospitals and 43,984 patients revealed an inpatient fall rate of 3.4% in Switzerland and 3.9% in Austria. Two of 15 patient-related fall risk variables showed an interaction effect with country: Patients who had fallen in the last 12 months (OR 1.49, 95% CI 1.10-2.01, p = 0.009) or had taken sedatives/psychotropic medication (OR 1.40, 95% CI 1.05-1.87, p = 0.022) had higher odds of falling in Austrian hospitals. Significantly higher odds of falling were observed in Austrian (OR 1.38, 95% CI 1.13-1.68, p = 0.002) compared to Swiss hospitals after applying the risk-adjustment model.

CONCLUSIONS

Almost all patient-related fall risk factors in the model are suitable for a risk-adjusted cross-country comparison, as they do not interact with the countries. Further model validation with additional countries is warranted, particularly to assess the interaction of risk factors "fall in the last 12 months" and "sedatives/psychotropic medication intake" with country variable. The study underscores the crucial role of an appropriate risk-adjustment model in ensuring fair international comparisons of inpatient falls, as the risk-adjusted, as opposed to the non-risk-adjusted country comparison, indicated significantly higher odds of falling in Austrian compared to Swiss hospitals.

Challenges in oral health research for older adults

BACKGROUND

The high burden of chronic disease in older adults presents significant organisational and funding challenges to healthcare policymakers. However, it is a matter of debate whether research is informing oral healthcare policy at scale.

OBJECTIVE

The objective of the study was to identify barriers to translation of research into oral healthcare policy and practice for older adults and suggest strategies to address these barriers.

RESULTS

The effectiveness of current models of oral health care, particularly for vulnerable older adults with special needs, is not well established. Researchers need to engage more proactively with stakeholders such as policymakers and end-users from the study design phase. This is particularly relevant for research in residential care settings. Building a rapport and developing trust with these groups will enable researchers to align their research with the priorities of policymakers. The evidence-based care paradigm, which is underpinned by randomised clinical trials (RCTs), may not be practical in population oral health research involving older adults. Alternative methods should be considered to develop an evidence-informed paradigm for oral health care in older adults. Since the pandemic, there are opportunities to use electronic health record data and digital technology. Further research is needed to evaluate the effectiveness of tele-health in oral health of older adults.

CONCLUSION

Use of a wider range of co-designed studies rooted in the practicalities of "real world" health service delivery is recommended. This may address issues of concern to policymakers and stakeholders regarding oral health and increase the likelihood of translation of geriatric oral health research into oral healthcare policy and practice.

Developing a Conceptual Framework for Socioeconomic Impact Research in European Cancer Patients: A 'Best-Fit' Framework Synthesis

BACKGROUND

Multiple studies have indicated a socioeconomic impact of cancer and cancer care on patients and their families. Existing instruments designed to measure this impact lack consensus in their conceptualization of the issue. Further, various terminologies have been used in the literature (e.g., financial burden, financial hardship, financial stress) without clear definitions and consistent conceptual background. Based on a targeted review of existing models addressing the socioeconomic impact of cancer, our goal was to develop a comprehensive framework from a European perspective.

METHOD

A 'best-fit' framework synthesis was applied. First, we systematically identified existing models to generate a priori concepts. Second, we systematically identified relevant European qualitative studies and coded their results against these a priori concepts. Inclusion and exclusion criteria were predefined and applied thoroughly in these processes. Thematic analysis and team discussions were applied to finalize the (sub)themes in our proposed conceptual framework. Third, we examined model structures and quotes from qualitative studies to explore relationships among (sub)themes. This process was repeated until no further change in (sub)themes and their relationships emerged.

RESULT

Eighteen studies containing conceptual models and seven qualitative studies were identified. Eight concepts and 20 sub-concepts were derived from the included models. After coding the included qualitative studies against the a priori concepts and following discussions among team members, seven themes and 15 sub-themes were included in our proposed conceptual framework. Based on the identified relationships, we categorized themes into four groups: causes, intermediate consequences, outcomes and risk factors.

CONCLUSION

We propose a Socioeconomic Impact Framework based on a targeted review and synthesis of existing models in the field and adapted to the European perspective. Our work contributes as an input to a European consensus project on socioeconomic impact research by an Organization European Cancer Institute (OECI) Task Force.

A smart hospital-driven approach to precision pharmacovigilance

Researchers, regulatory agencies, and the pharmaceutical industry are moving towards precision pharmacovigilance as a comprehensive framework for drug safety assessment, at the service of the individual patient, by clustering specific risk groups in different databases. This article explores its implementation by focusing on: (i) designing a new data collection infrastructure, (ii) exploring new computational methods suitable for drug safety data, and (iii) providing a computer-aided framework for distributed clinical decisions with the aim of compiling a personalized information leaflet with specific reference to a drug's risks and adverse drug reactions. These goals can be achieved by using 'smart hospitals' as the principal data sources and by employing methods of precision medicine and medical statistics to supplement current public health decisions.

Stakes, positions and logics: An institutional field analysis of cross-border health IT policy

The concepts field and habitus are used widely and variably in institutional theory. The intellectual antecedents are found in the work of the French Sociologist, Pierre Bourdieu. This study presents a field-level analysis of pan-European policy on cross-border health information technology. Using field theory and institutional theory, we situate field as a multi-level concept which extends institutional and organizational levels of analysis. Empirical data is gathered from European policymakers, health professionals and patient advocacy groups on the diffusion of supra-national health information technology across European Member States. Findings reveal four scenarios depicting field tensions, as ideological and practical imperatives of supra-national health information technology policy mis-align with Member State health systems. This study has implications for policy-makers and other stakeholders, who seek to narrow the digital divide across health fields and sub-fields.

Making Use of Comparable Health Data to Improve Quality of Care and Outcomes in Diabetes: The EUBIROD Review of Diabetes Registries and Data Sources in Europe

Background

Registries and data sources contain information that can be used on an ongoing basis to improve quality of care and outcomes of people with diabetes. As a specific task of the EU Bridge Health project, we carried out a survey of diabetes-related data sources in Europe.

Objectives

We aimed to report on the organization of different sources of diabetes information, including their governance, information infrastructure and dissemination strategies for quality control, service planning, public health, policy and research.

Methods

Survey using a structured questionnaire to collect targeted data from a network of collaborating institutions managing registries and data sources in 17 countries in the year 2017.

Results

The 18 data sources participating in the study were most frequently academic centres (44.4%), national (72.2%), targeting all types of diabetes (61.1%) covering no more than 10% of the target population (44.4%). Although population-based in over a quarter of cases (27.8%), sources relied predominantly on provider-based datasets (38.5%), fewer using administrative data (16.6%). Data collection was continuous in the majority of cases (61.1%), but 50% could not perform data linkage. Public reports were more frequent (72.2%) as well as quality reports (77.8%), but one third did not provide feedback to policy and only half published ten or more peer reviewed papers during the last 5 years.

Conclusions

The heterogeneous implementation of diabetes registries and data sources hampers the comparability of quality and outcomes across Europe. Best practices exist but need to be shared more effectively to accelerate progress and deliver equitable results for people with diabetes.

The road to hell is paved with good intentions: the experience of applying for national data for linkage and suggestions for improvement

BACKGROUND

We can improve healthcare services by better understanding current provision. One way to understand this is by linking data sets from clinical and national audits, national registries and other National Health Service (NHS) encounter data. However, getting to the point of having linked national data sets is challenging.

OBJECTIVE

We describe our experience of the data application and linkage process for our study 'LAUNCHES QI', and the time, processes and resource requirements involved. To help others planning similar projects, we highlight challenges encountered and advice for applications in the current system as well as suggestions for system improvements.

FINDINGS

The study set up for LAUNCHES QI began in March 2018, and the process through to data acquisition took 2.5 years. Several challenges were encountered, including the amount of information required (often duplicate information in different formats across applications), lack of clarity on processes, resource constraints that limit an audit's capacity to fulfil requests and the unexpected amount of time required from the study team. It is incredibly difficult to estimate the resources needed ahead of time, and yet necessary to do so as early on as funding applications. Early decisions can have a significant impact during latter stages and be hard to change, yet it is difficult to get specific information at the beginning of the process.

CONCLUSIONS

The current system is incredibly complex, arduous and slow, stifling innovation and delaying scientific progress. NHS data can inform and improve health services and we believe there is an ethical responsibility to use it to do so. Streamlining the number of applications required for accessing data for health services research and providing clarity to data controllers could facilitate the maintenance of stringent governance, while accelerating scientific studies and progress, leading to swifter application of findings and improvements in healthcare.

Mathematical Reconciliation of Medical Privacy Policies

Healthcare data are arguably the most private of personal data. This very private information in the wrong hands can lead to identity theft, prescription fraud, insurance fraud, and an array of other crimes. Electronic-health systems such as My Health Record in Australia holds great promise in sharing medical data and improving healthcare quality. But, a key privacy issue in these systems is the misuse of healthcare data by “authorities.” The recent General Data Protection Regulation (GDPR) introduced in the EU aims to reduce personal-data misuse. But, there are no tools currently available to accurately reconcile a domestic E-health policy against the GDPR to identify discrepancies. Reconciling privacy policies is also non-trivial, because policies are often written in free text, making them subject to human interpretation.

In this article, we propose a tool that allows the description of E-health privacy policies, represents them using formal constructs making the policies precise and explicit. Using this formal framework, our tool can automatically reconcile a domestic E-health policy against the GDPR to identify violations and omissions. We use our prototype to illustrate several critical flaws in Australia’s My Health Record policy, including a non-compliance with GDPR that allows healthcare providers to access medical records by default.

Discrepancy between Admission and Discharge Diagnoses in Central Serbia: Analysis by the Groups of International Classification of Diseases, 10th Revision

Background

Repeated research while using the same methodology can be useful and it can enable relevant conclusions in the same health care system. The aim of our study was to perform comparative analysis of the agreement between admission and discharge diagnostic groups in period 2014-2017 with period 2006-2013 in the Clinical Center of Kragujevac, Serbia.

Methods

The 5% simple, random sample was made from the basic set of all hospital reports from Clinical Centre Kragujevac, Serbia, in the period 01.01. 2014 - 31.12. 2017 (n=10228). The first four digits of ICD-10 codes at admission and discharge were compared for agreement. We used discharge diagnosis as a "golden standard". Statistical analysis was performed using Cohen's Kappa statistic.

Results

In the period 2014-2017, agreement between diagnosis among the most ICD10 groups increased in comparison with the period 2006-2013. Disagreements between diagnosis in the period 2014-2017 in comparation with period 2006-2013 was associated with increased length of stay in the hospital (7.5 vs. 9.1 days, P<0.01), patients were younger (54 vs 49.6 yr, P<0.01), number of males declined (26.3% vs 16.2%, P<0.05), kappa value decreased in XV ICD10 group and XI ICD10 group and kappa value increased in XIV ICD10 group.

Conclusion

Agreement between admission and discharge diagnosis among the most ICD10 diagnostic groups increased. Introduction of a new web application has increased the quality of data, but interpreting it requires the skill of researchers. Further research should identify modifiable causes of discrepancy between admission and discharge diagnoses.

Ensuring ethical data access: the Sierra Leone Ebola Database (SLED) model

PURPOSE

Organizations responding to the 2014-2016 Ebola epidemic in Sierra Leone collected information from multiple sources and kept it in separate databases, including distinct data systems for Ebola hot line calls, patient information collected by field surveillance officers, laboratory testing results, clinical information from Ebola treatment and isolation facilities, and burial team records.

METHODS

After the conclusion of the epidemic, the Sierra Leone Ministry of Health and Sanitation and the U.S. Centers for Disease Control and Prevention partnered to collect these disparate records and consolidate them in the Sierra Leone Ebola Database.

RESULTS

The Sierra Leone Ebola Database data are providing a lasting resource for postepidemic data analysis and epidemiologic research, including identifying best strategies in outbreak response, and are used to help families locate the graves of family members who died during the epidemic.

CONCLUSION

This report describes the Ministry of Health and Sanitation and Centers for Disease Control and Prevention processes to safeguard Ebola records while making the data available for public health research.

Empowering knowledge generation through international data network: the IMeCCHI-DATANETWORK

Introduction

The International Methodology Consortium for Coded Health Information (IMeCCHI) is a collaboration of health services researchers who promote methodological advances in coded health information. The IMeCCHI-DATANETWORK initiative focuses on developing a multi-purpose distributed data infrastructure and common data model (CDM) to enable cross-border data sharing and international comparisons.

Methods

IMeCCHI consortium partners from six different countries – Canada, Denmark, Italy, New Zealand, South Korea, and Switzerland – used a questionnaire to describe their original databases which differ in size, structure, content and coding systems. To standardize these data, they agreed on a CDM and mapped their population-based databases to meet the CDM specifications. At the end of this process, local data had a more homogenous content and structure, which made them syntactically and semantically interoperable. Data transformation was performed using a common data management software called TheMatrix.

Results

The CDM encompasses four tables of structured data (person characteristics, hospitalizations, outpatient prescription medication and death), linked at the individual level through a person identifier. It can be used to answer research questions across countries using locally converted databases, which facilitates study replication in a distributed fashion. As a proof-of-concept study, an initial research question was addressed using an agreed protocol. Local data were transformed in csv files in the CDM structure and TheMatrix was tested to transform the standardized data from each partner into local analytical datasets. This allowed results to be shared between countries, whilst maintaining local control over each region’s data.

Conclusion

The IMeCCHI-DATANETWORK, a model of a distributed data network, demonstrated that it is feasible to analyze international data using standardized analytical methods that enable independent analyses by regions, without relocating datasets thereby protecting local confidentiality obligations. The distributed data infrastructure can produce results that can be generalized to several countries, while facilitating cross-border data sharing and international comparisons.

Keywords

Common data model, international comparison, cross-border data sharing, interoperability, observational data

Developing new ways of measuring the quality and impact of ambulance service care: the PhOEBE mixed-methods research programme

Background

Ambulance service quality measures have focused on response times and a small number of emergency conditions, such as cardiac arrest. These quality measures do not reflect the care for the wide range of problems that ambulance services respond to and the Prehospital Outcomes for Evidence Based Evaluation (PhOEBE) programme sought to address this.

Objectives

The aim was to develop new ways of measuring the impact of ambulance service care by reviewing and synthesising literature on prehospital ambulance outcome measures and using consensus methods to identify measures for further development; creating a data set linking routinely collected ambulance service, hospital and mortality data; and using the linked data to explore the development of case-mix adjustment models to assess differences or changes in processes and outcomes resulting from ambulance service care.

Design

A mixed-methods study using a systematic review and synthesis of performance and outcome measures reported in policy and research literature; qualitative interviews with ambulance service users; a three-stage consensus process to identify candidate indicators; the creation of a data set linking ambulance, hospital and mortality data; and statistical modelling of the linked data set to produce novel case-mix adjustment measures of ambulance service quality.

Setting

East Midlands and Yorkshire, England.

Participants

Ambulance services, patients, public, emergency care clinical academics, commissioners and policy-makers between 2011 and 2015.

Interventions

None.

Main outcome measures

Ambulance performance and quality measures.

Data sources

Ambulance call-and-dispatch and electronic patient report forms, Hospital Episode Statistics, accident and emergency and inpatient data, and Office for National Statistics mortality data.

Results

Seventy-two candidate measures were generated from systematic reviews in four categories: (1) ambulance service operations (n = 14), (2) clinical management of patients (n = 20), (3) impact of care on patients (n = 9) and (4) time measures (n = 29). The most common operations measures were call triage accuracy; clinical management was adherence to care protocols, and for patient outcome it was survival measures. Excluding time measures, nine measures were highly prioritised by participants taking part in the consensus event, including measures relating to pain, patient experience, accuracy of dispatch decisions and patient safety. Twenty experts participated in two Delphi rounds to refine and prioritise measures and 20 measures scored ≥ 8/9 points, which indicated good consensus. Eighteen patient and public representatives attending a consensus workshop identified six measures as important: time to definitive care, response time, reduction in pain score, calls correctly prioritised to appropriate levels of response, proportion of patients with a specific condition who are treated in accordance with established guidelines, and survival to hospital discharge for treatable emergency conditions. From this we developed six new potential indicators using the linked data set, of which five were constructed using case-mix-adjusted predictive models: (1) mean change in pain score; (2) proportion of serious emergency conditions correctly identified at the time of the 999 call; (3) response time (unadjusted); (4) proportion of decisions to leave a patient at scene that were potentially inappropriate; (5) proportion of patients transported to the emergency department by 999 emergency ambulance who did not require treatment or investigation(s); and (6) proportion of ambulance patients with a serious emergency condition who survive to admission, and to 7 days post admission. Two indicators (pain score and response times) did not need case-mix adjustment. Among the four adjusted indicators, we found that accuracy of call triage was 61%, rate of potentially inappropriate decisions to leave at home was 5–10%, unnecessary transport to hospital was 1.7–19.2% and survival to hospital admission was 89.5–96.4% depending on Clinical Commissioning Group area. We were unable to complete a fourth objective to test the indicators in use because of delays in obtaining data. An economic analysis using indicators (4) and (5) showed that incorrect decisions resulted in higher costs.

Limitations

Creation of a linked data set was complex and time-consuming and data quality was variable. Construction of the indicators was also complex and revealed the effects of other services on outcome, which limits comparisons between services.

Conclusions

We identified and prioritised, through consensus processes, a set of potential ambulance service quality measures that reflected preferences of services and users. Together, these encompass a broad range of domains relevant to the population using the emergency ambulance service. The quality measures can be used to compare ambulance services or regions or measure performance over time if there are improvements in mechanisms for linking data across services.

Future work

The new measures can be used to assess different dimensions of ambulance service delivery but current data challenges prohibit routine use. There are opportunities to improve data linkage processes and to further develop, validate and simplify these measures.

Funding

The National Institute for Health Research Programme Grants for Applied Research programme.

Referrals for head and neck cancer in England and The Netherlands: an international qualitative study of the views of secondary-care surgical specialists

One-year survival after head and neck cancer in England has been reported to be worse than that in Europe, despite five-year conditional survival being similar, which implies that patients present later in England. One country with better rates is The Netherlands. There are many possible causes, one of which may be the system of referral from primary to secondary care. We have compared the views of secondary care specialists in the two countries about their systems for referral, and identified aspects that might have an impact on outcomes. We organised semistructured qualitative interviews of surgical specialists in head and neck cancer in England and The Netherlands (n=12 in each). The most common theme was communication between primary care and specialists. Surgeons in England identified this as the aspect most lacking under the English "two-week" rule, while Dutch specialists felt that the good communication in their system was one of its best points. Other themes included the educational needs of primary care practitioners, criticism of "tick box" referrals in England, and too many patients referred who do not have cancer. Overall, specialists in both countries identified good aspects of their respective referral systems, but those in England felt strongly that the "two-week" rule/NICE guidance system could be improved with better direct communication between primary and secondary care, which might improve the speed and quality of referrals, reduce unnecessary ones, and assist in educating primary care physicians. It is not clear whether such improvements would improve survival, but further research and piloting of such a system should be considered in England.

A Position Statement on Population Data Science: The Science of Data about People

Information is increasingly digital, creating opportunities to respond to pressing issues about human populations using linked datasets that are large, complex, and diverse. The potential social and individual benefits that can come from data-intensive science are large, but raise challenges of balancing individual privacy and the public good, building appropriate socio-technical systems to support data-intensive science, and determining whether defining a new field of inquiry might help move those collective interests and activities forward. A combination of expert engagement, literature review, and iterative conversations led to our conclusion that defining the field of Population Data Science (challenge 3) will help address the other two challenges as well. We define Population Data Science succinctly as the science of data about people and note that it is related to but distinct from the fields of data science and informatics. A broader definition names four characteristics of: data use for positive impact on citizens and society; bringing together and analyzing data from multiple sources; finding population-level insights; and developing safe, privacy-sensitive and ethical infrastructure to support research. One implication of these characteristics is that few people possess all of the requisite knowledge and skills of Population Data Science, so this is by nature a multi-disciplinary field. Other implications include the need to advance various aspects of science, such as data linkage technology, various forms of analytics, and methods of public engagement. These implications are the beginnings of a research agenda for Population Data Science, which if approached as a collective field, can catalyze significant advances in our understanding of trends in society, health, and human behavior.

Public preferences for electronic health data storage, access, and sharing - evidence from a pan-European survey

Objective To assess the public’s preferences regarding potential privacy threats from devices or services storing health-related personal data.

Materials and Methods A pan-European survey based on a stated-preference experiment for assessing preferences for electronic health data storage, access, and sharing.

Results We obtained 20 882 survey responses (94 606 preferences) from 27 EU member countries. Respondents recognized the benefits of storing electronic health information, with 75.5%, 63.9%, and 58.9% agreeing that storage was important for improving treatment quality, preventing epidemics, and reducing delays, respectively. Concerns about different levels of access by third parties were expressed by 48.9% to 60.6% of respondents.

On average, compared to devices or systems that only store basic health status information, respondents preferred devices that also store identification data (coefficient/relative preference 95% CI = 0.04 [0.00-0.08], P = 0.034) and information on lifelong health conditions (coefficient = 0.13 [0.08 to 0.18], P < 0.001), but there was no evidence of this for devices with information on sensitive health conditions such as mental and sexual health and addictions (coefficient = −0.03 [−0.09 to 0.02], P = 0.24). Respondents were averse to their immediate family (coefficient = −0.05 [−0.05 to −0.01], P = 0.011) and home care nurses (coefficient = −0.06 [−0.11 to −0.02], P = 0.004) viewing this data, and strongly averse to health insurance companies (coefficient = −0.43 [−0.52 to 0.34], P < 0.001), private sector pharmaceutical companies (coefficient = −0.82 [−0.99 to −0.64], P < 0.001), and academic researchers (coefficient = −0.53 [−0.66 to −0.40], P < 0.001) viewing the data.

Conclusions Storing more detailed electronic health data was generally preferred, but respondents were averse to wider access to and sharing of this information. When developing frameworks for the use of electronic health data, policy makers should consider approaches that both highlight the benefits to the individual and minimize the perception of privacy risks.

Individual and Regional-level Factors Contributing to Variation in Length of Stay After Cerebral Infarction in Six European Countries

Using patient-level data for cerebral infarction cases in 2007, gathered from Finland, Hungary, Italy, the Netherlands, Scotland and Sweden, we studied the variation in risk-adjusted length of stay (LoS) of acute hospital care and 1-year mortality, both within and between countries. In addition, we analysed the variance of LoS and associations of selected regional-level factors with LoS and 1-year mortality after cerebral infarction. The data show that LoS distributions are surprisingly different across countries and that there is significant deviation in the risk-adjusted regional-level LoS in all of the countries studied. We used negative binomial regression to model the individual-level LoS, and random intercept models and ordinary least squares regression for the regional-level analysis of risk-adjusted LoS, variance of LoS, 1-year risk-adjusted mortality and crude mortality for a period of 31-365 days. The observed variations between regions and countries in both LoS and mortality were not fully explained by either patient-level or regional-level factors. The results indicate that there may exist potential for efficiency gains in acute hospital care of cerebral infarction and that healthcare managers could learn from best practices.

The link between health governance models and global health innovation: an exploration of OECD nations

PURPOSE

While there is established research that explores individual innovations across countries or developments in a specific health area, there is less work that attempts to match national innovations to specific systems of health governance to uncover themes across nations.

DESIGN/METHODOLOGY/APPROACH

We used a cross-comparison design that employed content analysis of health governance models and innovation patterns in eight OECD nations (Australia, Britain, Canada, France, Germany, The Netherlands, Switzerland, and the United States).

FINDINGS

Country-level model of health governance may impact the focus of health innovation within the eight jurisdictions studied. Innovation across all governance models has targeted consumer engagement in health systems, the integration of health services across the continuum of care, access to care in the community, and financial models that drive competition.

ORIGINALITY/VALUE

Improving our understanding of the linkage between health governance and innovation in health systems may heighten awareness of potential enablers and barriers to innovation success.

International Guidelines for Privacy in Genomic Biobanking (or the Unexpected Virtue of Pluralism)

This article reviews international privacy norms governing human genomic biobanks and databases, and how they address issues related to consent, secondary use, de- identification, access, security, and governance. A range of international instruments were identified, varying in substance - e.g., human rights, data protection, research ethics, biobanks, and genetics - and legal character. Some norms detail processes for broad consent, namely, that even where potential participants cannot consent to specific users and uses, they should be given clear information on access policies, procedures, and governance structures. Some also give guidance about the conditions under which secondary use of data and samples without consent is appropriate, e.g., where consent is impracticable. International norms exhibit a confusing range of terminology relating to de-identification. They also continue to rely heavily on consent and anonymity as the basis for privacy protection, though governance is becoming more prominent. It may not be fatal that such a plurality of norms apply to biobanking; what is essential is that governance be built on shared values, our common interest in the success of genomic research, and practical tools that incentivize responsible, global sharing.

Improved estimates of Belgian private health expenditure can give important lessons to other OECD countries

OECD Health Data are a well-known source for detailed information about health expenditure. These data enable us to analyze health policy issues over time and in comparison with other countries. However, current official Belgian estimates of private expenditure (as published in the OECD Health Data) have proven not to be reliable. We distinguish four potential major sources of problems with estimating private health spending: interpretation of definitions, formulation of assumptions, missing or incomplete data and incorrect data. Using alternative sources of billing information, we have reached more accurate estimates of private and out-of-pocket expenditure. For Belgium we found differences of more than 100% between our estimates and the official Belgian estimates of private health expenditure (as published in the OECD Health Data). For instance, according to OECD Health Data private expenditure on hospitals in Belgium amounts to €3.1 billion, while according to our alternative calculations these expenses represent only €1.1 billion. Total private expenditure differs only 1%, but this is a mere coincidence. This exercise may be of interest to other OECD countries looking to improve their estimates of private expenditure on health.

Health research and systems' governance are at risk: should the right to data protection override health?

The European Union (EU) Data Protection Regulation will have profound implications for public health, health services research and statistics in Europe. The EU Commission's Proposal was a breakthrough in balancing privacy rights and rights to health and healthcare. The European Parliament, however, has proposed extensive amendments. This paper reviews the amendments proposed by the European Parliament Committee on Civil Liberties, Justice and Home Affairs and their implications for health research and statistics. The amendments eliminate most innovations brought by the Proposal. Notably, derogation to the general prohibition of processing sensitive data shall be allowed for public interests such as the management of healthcare services,but not health research, monitoring, surveillance and governance. The processing of personal health data for historical, statistical or scientific purposes shall be allowed only with the consent of the data subject or if the processing serves an exceptionally high public interest, cannot be performed otherwise and is legally authorised. Research, be it academic, government,corporate or market research, falls under the same rule.The proposed amendments will make difficult or render impossible research and statistics involving the linkage and analysis of the wealth of data from clinical,administrative, insurance and survey sources, which have contributed to improving health outcomes and health systems performance and governance; and may illegitimise efforts that have been made in some European countries to enable privacy-respectful data use for research and statistical purposes. If the amendments stand as written, the right to privacy is likely to override the right to health and healthcare in Europe.

Feasibility of using administrative data to compare hospital performance in the EU

OBJECTIVE

To describe hospitals' organizational arrangements relevant to the abstraction of administrative data, to report on the completeness of administrative data collected and to assess associations between organizational arrangements and completeness of data submission.

DESIGN

A cross-sectional

STUDY DESIGN

utilizing administrative data.

SETTING AND PARTICIPANTS

Randomly selected hospitals from seven European countries (The Czech Republic, France, Germany, Poland, Portugal, Spain, and Turkey).

MAIN OUTCOME MEASURES

Completeness of data submission for four quality indicators: mortality after acute myocardial infarction, stroke and hip fractures and complications after normal delivery.

RESULTS

In general, hospitals were able to produce data on the four indicators required for this research study. A substantial proportion had missing data on one or more data items. The proportion of hospitals that was able to produce more detailed indicators of relevance for quality monitoring and improvement was low and ranged from 40.1% for thrombolysis performed on patients with acute ischemic stroke to 63.8% for hip-fracture operations performed within 48 h after admission for patients aged 65 or older. National factors were strong predictors of data completeness on the studied indicators.

CONCLUSIONS

At present, hospital administrative databases do not seem to be an appropriate source of information for comparison of hospital performance across the countries of the EU. However, given that this is a dynamic field, changes to administrative databases may make this possible in the near future. Such changes could be accelerated by an in-depth comparative analysis of the issues of using administrative data for comparisons of hospital performances in EU countries.