Developing a survey instrument to assess the readiness of primary care data, genetic and disease registries to conduct linked research: TRANSFoRm International Research Readiness (TIRRE) survey instrument.

BACKGROUND: Clinical data are collected for routine care in family practice; there are also a growing number of genetic and cancer registry data repositories. The Translational Research and Patient Safety in Europe (TRANSFoRm) project seeks to facilitate research using linked data from more than one source. We performed a requirements analysis which identified a wide range of data and business process requirements that need to be met before linking primary care and either genetic or disease registry data. OBJECTIVES: To develop a survey to assess the readiness of data repositories to participate in linked research - the Transform International Research Readiness (TIRRE) survey. METHOD: We develop the questionnaire based on our requirement analysis; with questions at micro-, meso- and macro levels of granularity, study-specific questions about diabetes and gastro-oesophageal reflux disease (GORD), and research track record. The scope of the data required was extensive. We piloted this instrument, conducting ten preliminary telephone interviews to evaluate the response to the questionnaire. RESULTS: Using feedback gained from these interviews we revised the questionnaire; clarifying questions that were difficult to answer and utilising skip logic to create different series of questions for the various types of data repository. We simplified the questionnaire replacing free-text responses with yes/no or picking list options, wherever possible. We placed the final questionnaire online and encouraged its use (www.clininf.eu/jointirre/info.html). CONCLUSION: Limited field testing suggests that TIRRE is capable of collecting comprehensive and relevant data about the suitability and readiness of data repositories to participate in linked data research.

The provision and impact of online patient access to their electronic health records (EHR) and transactional services on the quality and safety of health care: systematic review protocol.

BACKGROUND: Innovators have piloted improvements in communication, changed patterns of practice and patient empowerment from online access to electronic health records (EHR). International studies of online services, such as prescription ordering, online appointment booking and secure communications with primary care, show good uptake of email consultations, accessing test results and booking appointments; when technologies and business process are in place. Online access and transactional services are due to be rolled out across England by 2015; this review seeks to explore the impact of online access to health records and other online services on the quality and safety of primary health care. OBJECTIVE: To assess the factors that may affect the provision of online patient access to their EHR and transactional services, and the impact of such access on the quality and safety of health care. METHOD: Two reviewers independently searched 11 international databases during the period 1999-2012. A range of papers including descriptive studies using qualitative or quantitative methods, hypothesis-testing studies and systematic reviews were included. A detailed eligibility criterion will be used to shape study inclusion. A team of experts will review these papers for eligibility, extract data using a customised extraction form and use the Grading of Recommendations Assessment, Development and Evaluation (GRADE) instrument to determine the quality of the evidence and the strengths of any recommendation. Data will then be descriptively summarised and thematically synthesised. Where feasible, we will perform a quantitative meta-analysis. Prospero (International Prospective Register of Systematic Reviews) registration number: crd42012003091.

Conducting requirements analyses for research using routinely collected health data: a model driven approach.

BACKGROUND: Medical research increasingly requires the linkage of data from different sources. Conducting a requirements analysis for a new application is an established part of software engineering, but rarely reported in the biomedical literature; and no generic approaches have been published as to how to link heterogeneous health data. METHODS: Literature review, followed by a consensus process to define how requirements for research, using, multiple data sources might be modeled. RESULTS: We have developed a requirements analysis: i-ScheDULEs - The first components of the modeling process are indexing and create a rich picture of the research study. Secondly, we developed a series of reference models of progressive complexity: Data flow diagrams (DFD) to define data requirements; unified modeling language (UML) use case diagrams to capture study specific and governance requirements; and finally, business process models, using business process modeling notation (BPMN). DISCUSSION: These requirements and their associated models should become part of research study protocols.

Consistent data recording across a health system and web-enablement allow service quality comparisons: online data for commissioning dermatology services.

A new distributed model of health care management is being introduced in England. Family practitioners have new responsibilities for the management of health care budgets and commissioning of services. There are national datasets available about health care providers and the geographical areas they serve. These data could be better used to assist the family practitioner turned health service commissioners. Unfortunately these data are not in a form that is readily usable by these fledgling family commissioning groups. We therefore Web enabled all the national hospital dermatology treatment data in England combining it with locality data to provide a smart commissioning tool for local communities. We used open-source software including the Ruby on Rails Web framework and MySQL. The system has a Web front-end, which uses hypertext markup language cascading style sheets (HTML/CSS) and JavaScript to deliver and present data provided by the database. A combination of advanced caching and schema structures allows for faster data retrieval on every execution. The system provides an intuitive environment for data analysis and processing across a large health system dataset. Web-enablement has enabled data about in patients, day cases and outpatients to be readily grouped, viewed, and linked to other data. The combination of web-enablement, consistent data collection from all providers; readily available locality data; and a registration based primary system enables the creation of data, which can be used to commission dermatology services in small areas. Standardized datasets collected across large health enterprises when web enabled can readily benchmark local services and inform commissioning decisions.

Defining datasets and creating data dictionaries for quality improvement and research in chronic disease using routinely collected data: an ontology-driven approach.

BACKGROUND: The burden of chronic disease is increasing, and research and quality improvement will be less effective if case finding strategies are suboptimal. OBJECTIVE: To describe an ontology-driven approach to case finding in chronic disease and how this approach can be used to create a data dictionary and make the codes used in case finding transparent. METHOD: A five-step process: (1) identifying a reference coding system or terminology; (2) using an ontology-driven approach to identify cases; (3) developing metadata that can be used to identify the extracted data; (4) mapping the extracted data to the reference terminology; and (5) creating the data dictionary. RESULTS: Hypertension is presented as an exemplar. A patient with hypertension can be represented by a range of codes including diagnostic, history and administrative. Metadata can link the coding system and data extraction queries to the correct data mapping and translation tool, which then maps it to the equivalent code in the reference terminology. The code extracted, the term, its domain and subdomain, and the name of the data extraction query can then be automatically grouped and published online as a readily searchable data dictionary. An exemplar online is: www.clininf.eu/qickd-data-dictionary.html CONCLUSION: Adopting an ontology-driven approach to case finding could improve the quality of disease registers and of research based on routine data. It would offer considerable advantages over using limited datasets to define cases. This approach should be considered by those involved in research and quality improvement projects which utilise routine data.

What are the barriers to conducting international research using routinely collected primary care data?

BACKGROUND: Primary care is computerized with routine data recorded at the point or care. Secondary use of these data includes: genetic study, epidemiology and clinical trials. However, there are relatively few international studies. OBJECTIVE: To identify the concepts that might predict readiness to collaborate in international research using routinely collected primary care data METHOD: Literature review and data gathering exercise, from international Primary Care Informatics working group workshops, and email modified Delphi exercise. RESULTS: To establish whether primary care data are fit for use in a collaborative study information is needed at the micro-, meso-, and macro-level. At the micro- or data level we need to use documented standards for interoperability, computerized records, to facilitate linkage of data. At the meso-level we need to understand the nature of the electronic patient record (EPR) and specific study requirements. At the macro-level: health system, social and cultural context constrain what data are available. The framework defines the information needed at the point of expression of interest, and joining a study. The initial assessment of readiness should be by self-assessment followed by an in depth appraisal more immediately prior to the start of the study. Finally, a sensitivity analysis should be conducted to test the robustness of the data model. CONCLUSIONS: The literature focuses on technical issues: interoperability, EPR and modeling; the workshops on socio-cultural and organizational. This framework will form the basis for developing a survey instrument of the initial assessment of readiness for collaboration in international research.

A system for solution-orientated reporting of errors associated with the extraction of routinely collected clinical data for research and quality improvement.

BACKGROUND: We have used routinely collected clinical data in epidemiological and quality improvement research for over 10 years. We extract, pseudonymise and link data from heterogeneous distributed databases; inevitably encountering errors and problems. OBJECTIVE: To develop a solution-orientated system of error reporting which enables appropriate corrective action. METHOD: Review of the 94 errors, which occurred in 2008/9. Previously we had described failures in terms of the data missing from our response files; however this provided little information about causation. We therefore developed a taxonomy based on the IT component limiting data extraction. RESULTS: Our final taxonomy categorised errors as: (A) Data extraction Method and Process; (B) Translation Layer and Proxy Specification; (C) Shape and Complexity of the Original Schema; (D) Communication and System (mainly Software-based) Faults; (E) Hardware and Infrastructure; (F) Generic/Uncategorised and/or Human Errors. We found 79 distinct errors among the 94 reported; and the categories were generally predictive of the time needed to develop fixes. CONCLUSIONS: A systematic approach to errors and linking them to problem solving has improved project efficiency and enabled us to better predict any associated delays.

An instrument to identify computerised primary care research networks, genetic and disease registries prepared to conduct linked research: TRANSFoRm International Research Readiness (TIRRE) survey.

PURPOSE: The Translational Research and Patients safety in Europe (TRANSFoRm) project aims to integrate primary care with clinical research whilst improving patient safety. The TRANSFoRm International Research Readiness survey (TIRRE) aims to demonstrate data use through two linked data studies and by identifying clinical data repositories and genetic databases or disease registries prepared to participate in linked research. METHOD: The TIRRE survey collects data at micro-, meso- and macro-levels of granularity; to fulfil data, study specific, business, geographical and readiness requirements of potential data providers for the TRANSFoRm demonstration studies. We used descriptive statistics to differentiate between demonstration-study compliant and non-compliant repositories. We only included surveys with >70% of questions answered in our final analysis, reporting the odds ratio (OR) of positive responses associated with a demonstration-study compliant data provider. RESULTS: We contacted 531 organisations within the Eurpean Union (EU). Two declined to supply information; 56 made a valid response and a further 26 made a partial response. Of the 56 valid responses, 29 were databases of primary care data, 12 were genetic databases and 15 were cancer registries. The demonstration compliant primary care sites made 2098 positive responses compared with 268 in non-use-case compliant data sources [OR: 4.59, 95% confidence interval (CI): 3.93-5.35, p < 0.008]; for genetic databases: 380:44 (OR: 6.13, 95% CI: 4.25-8.85, p < 0.008) and cancer registries: 553:44 (OR: 5.87, 95% CI: 4.13-8.34, p < 0.008). CONCLUSIONS: TIRRE comprehensively assesses the preparedness of data repositories to participate in specific research projects. Multiple contacts about hypothetical participation in research identified few potential sites.