Harshana Liyanage

Serum Phosphate as a Risk Factor for Cardiovascular Events in People with and without Chronic Kidney Disease: A Large Community Based Cohort Study

Background Serum phosphate is a known risk factor for cardiovascular events and mortality in people with chronic kidney disease (CKD), however data on the association of these outcomes with serum phosphate in the general population are scarce. We investigate this relationship in people with and without CKD in a large community-based population. Methods Three groups from an adult cohort of the Quality Improvement in Chronic Kidney Disease (QICKD) cluster randomised trial (ISRCTN56023731) were followed over a period of 2.5 years: people with normal renal function (N = 24,184), people with CKD stages 1–2 (N = 20,356), and people with CKD stages 3–5 (N = 13,292). We used a multilevel logistic regression model to determine the association between serum phosphate, in these groups, and a composite outcome of all-cause mortality, cardiovascular events, and advanced coronary artery disease. We adjusted for known cardiovascular risk factors. Findings Higher phosphate levels were found to correlate with increased cardiovascular risk. In people with normal renal function and CKD stages 1–2, Phosphate levels between 1.25 and 1.50 mmol/l were associated with increased cardiovascular events; odds ratio (OR) 1.36 (95% CI 1.06–1.74; p = 0.016) in people with normal renal function and OR 1.40 (95% CI 1.09–1.81; p = 0.010) in people with CKD stages 1–2. Hypophosphatemia (<0.75 mmol/l) was associated with fewer cardiovascular events in people with normal renal function; OR 0.59 (95% CI 0.36–0.97; p = 0.049). In people with CKD stages 3–5, hyperphosphatemia (>1.50 mmol/l) was associated with increased cardiovascular risk; OR 2.34 (95% CI 1.64–3.32; p<0.001). Other phosphate ranges were not found to have a significant impact on cardiovascular events in people with CKD stages 3–5. Conclusions Serum phosphate is associated with cardiovascular events in people with and without CKD. Further research is required to determine the mechanisms underlying these associations.

Using ontologies to improve semantic interoperability in health data

The present–day health data ecosystem comprises a wide array of complex heterogeneous data sources. A wide range of clinical, health care, social and other clinically relevant information are stored in these data sources. These data exist either as structured data or as free-text. These data are generally individual personbased records, but social care data are generally case based and less formal data sources may be shared by groups. The structured data may be organised in a proprietary way or be coded using one-of-many coding, classification or terminologies that have often evolved in isolation and designed to meet the needs of the context that they have been developed. This has resulted in a wide range of semantic interoperability issues that make the integration of data held on these different systems changing. We present semantic interoperability challenges and describe a classification of these. We propose a four-step process and a toolkit for those wishing to work more ontologically, progressing from the identification and specification of concepts to validating a final ontology. The four steps are: (1) the identification and specification of data sources; (2) the conceptualisation of semantic meaning; (3) defining to what extent routine data can be used as a measure of the process or outcome of care required in a particular study or audit and (4) the formalisation and validation of the final ontology. The toolkit is an extension of a previous schema created to formalise the development of ontologies related to chronic disease management. The extensions are focused on facilitating rapid building of ontologies for time-critical research studies. What is already known on this topic Ontologies are used in health care for (1) modelling the semantics of medical concepts and (2) to facilitate exchange of medical data between disparate systems Diverse range of ontologies has been developed to semantically represent health care concepts What this study adds A classification of semantic interoperability issues is presented in this study An extended toolkit that supports rapid building of ontologies related to chronic disease management is described

Does Informatics Enable or Inhibit the Delivery of Patient-centred, Coordinated, and Quality-assured Care: a Delphi Study. A Contribution of the IMIA Primary Health Care Informatics Working Group.

BACKGROUND Primary care delivers patient-centred and coordinated care, which should be quality-assured. Much of family practice now routinely uses computerised medical record (CMR) systems, these systems being linked at varying levels to laboratories and other care providers. CMR systems have the potential to support care. OBJECTIVE To achieve a consensus among an international panel of health care professionals and informatics experts about the role of informatics in the delivery of patient-centred, coordinated, and quality-assured care. METHOD The consensus building exercise involved 20 individuals, five general practitioners and 15 informatics academics, members of the International Medical Informatics Association Primary Care Informatics Working Group. A thematic analysis of the literature was carried out according to the defined themes. RESULTS The first round of the analysis developed 27 statements on how the CMR, or any other information system, including paper-based medical records, supports care delivery. Round 2 aimed at achieving a consensus about the statements of round one. Round 3 stated that there was an agreement on informatics principles and structures that should be put in place. However, there was a disagreement about the processes involved in the implementation, and about the clinical interaction with the systems after the implementation. CONCLUSIONS The panel had a strong agreement about the core concepts and structures that should be put in place to support high quality care. However, this agreement evaporated over statements related to implementation. These findings reflect literature and personal experiences: whilst there is consensus about how informatics structures and processes support good quality care, implementation is difficult.

Using routinely collected health data for surveillance, quality improvement and research: Framework and key questions to assess ethics, privacy and data access.

Background The use of health data for public health, surveillance, quality improvement and research is crucial to improve health systems and health care. However, bodies responsible for privacy and ethics often limit access to routinely collected health data. Ethical approvals, issues around protecting privacy and data access are often dealt with by different layers of regulations, making approval processes appear disjointed. Objective To create a comprehensive framework for defining the ethical and privacy status of a project and for providing guidance on data access. Method The framework comprises principles and related questions. The core of the framework will be built using standard terminology definitions such as ethics-related controlled vocabularies and regional directives. It is built in this way to reduce ambiguity between different definitions. The framework is extensible: principles can be retired or added to, as can their related questions. Responses to these questions should allow data processors to define ethical issues, privacy risk and other unintended consequences. Results The framework contains three steps: (1) identifying possible ethical and privacy principles relevant to the project; (2) providing ethics and privacy guidance questions that inform the type of approval needed; and (3) assessing case-specific ethics and privacy issues. The outputs from this process should inform whether the balance between public interests and privacy breach and any ethical considerations are tipped in favour of societal benefits. If they are then this should be the basis on which data access is permitted. Tightly linking ethical principles to governance and data access may help maintain public trust.

Accessible Modelling of Complexity in Health (AMoCH) and associated data flows: asthma as an exemplar

Background Modelling is an important part of information science. Models are abstractions of reality. We use models in the following contexts: (1) to describe the data and information flows in clinical practice to information scientists, (2) to compare health systems and care pathways, (3) to understand how clinical cases are recorded in record systems and (4) to model health care business models. Asthma is an important condition associated with a substantial mortality and morbidity. However, there are difficulties in determining who has the condition, making both its incidence and prevalence uncertain. Objective To demonstrate an approach for modelling complexity in health using asthma prevalence and incidence as an exemplar. Method The four steps in our process are: Drawing a rich picture, following Checkland’s soft systems methodology; Constructing data flow diagrams (DFDs); Creating Unified Modelling Language (UML) use case diagrams to describe the interaction of the key actors with the system; Activity diagrams, either UML activity diagram or business process modelling notation diagram. Results Our rich picture flagged the complexity of factors that might impact on asthma diagnosis. There was consensus that the principle issue was that there were undiagnosed and misdiagnosed cases as well as correctly diagnosed. Genetic predisposition to atopy; exposure to environmental triggers; impact of respiratory health on earnings or ability to attend education or participate in sport, charities, pressure groups and the pharmaceutical industry all increased the likelihood of a diagnosis of asthma. Stigma and some factors within the health system diminished the likelihood of a diagnosis. The DFDs and other elements focused on better case finding. Conclusions This approach flagged the factors that might impact on the reported prevalence or incidence of asthma. The models suggested that applying selection criteria may improve the specificity of new or confirmed diagnosis.

Ethnicity Recording in Primary Care Computerised Medical Record Systems: An Ontological Approach

Background Ethnicity recording within primary care computerised medical record (CMR) systems is suboptimal, exacerbated by tangled taxonomies within current coding systems. Objective To develop a method for extending ethnicity identification using routinely collected data. Methods We used an ontological method to maximise the reliability and prevalence of ethnicity information in the Royal College of General Practitioner’s Research and Surveillance database. Clinical codes were either directly mapped to ethnicity group or utilised as proxy markers (such as language spoken) from which ethnicity could be inferred. We compared the performance of our method with the recording rates that would be identified by code lists utilised by the UK pay for the performance system, with the help of the Quality and Outcomes Framework (QOF). Results Data from 2,059,453 patients across 110 practices were included. The overall categorisable ethnicity using QOF codes was 36.26% (95% confidence interval (CI): 36.20%–36.33%). This rose to 48.57% (CI:48.50%–48.64%) using the described ethnicity mapping process. Mapping increased across all ethnic groups. The largest increase was seen in the white ethnicity category (30.61%; CI: 30.55%–30.67% to 40.24%; CI: 40.17%–40.30%). The highest relative increase was in the ethnic group categorised as the other (0.04%; CI: 0.03%–0.04% to 0.92%; CI: 0.91%–0.93%). Conclusions This mapping method substantially increases the prevalence of known ethnicity in CMR data and may aid future epidemiological research based on routine data.

A simple clinical coding strategy to improve recording of child maltreatment concerns: an audit study

Background Recording concerns about child maltreatment, including minor concerns, is recommended by the General Medical Council (GMC) and National Institute for Health and Clinical Excellence (NICE) but there is evidence of substantial under-recording. Aim To determine whether a simple coding strategy improved recording of maltreatment-related concerns in electronic primary care records. Design and Setting Clinical audit of rates of maltreatment-related coding before January 2010–December 2011 and after January–December 2012 implementation of a simple coding strategy in 11 English family practices. The strategy included encouraging general practitioners to use, always and as a minimum, the Read code ‘Child is cause for concern’. A total of 25,106 children aged 0–18 years were registered with these practices. We also undertook a qualitative service evaluation to investigate barriers to recording. Method Outcomes were recording of 1) any maltreatment-related codes, 2) child protection proceedings and 3) child was a cause for concern. Results We found increased recording of any maltreatment-related code (rate ratio 1.4; 95% CI 1.1–1.6), child protection procedures (RR 1.4; 95% CI 1.1–1.6) and cause for concern (RR 2.5; 95% CI 1.8–3.4) after implementation of the coding strategy. Clinicians cited the simplicity of the coding strategy as the most important factor assisting implementation. Conclusion This simple coding strategy improved clinician’s recording of maltreatment-related concerns in a small sample of practices with some ‘buy-in’. Further research should investigate how recording can best support the doctor–patient relationship. How this fits in Recording concerns about child maltreatment, including minor concerns, is recommended by the General Medical Council (GMC) and National Institute for Health and Clinical Excellence (NICE), but there is evidence of substantial underrecording. We describe a simple clinical coding strategy that helped general practitioners to improve recording of maltreatment-related concerns. These improvements could improve case finding of children at risk and information sharing.

Defining dimensions of research readiness: a conceptual model for primary care research networks

BackgroundRecruitment to research studies in primary care is challenging despite widespread implementation of electronic patient record (EPR) systems which potentially make it easier to identify eligible cases.MethodsLiterature review and applying the learning from a European research readiness assessment tool, the TRANSFoRm International Research Readiness instrument (TIRRE), to the context of the English NHS in order to develop a model to assess a practice’s research readiness.ResultsSeven dimensions of research readiness were identified: (1) Data readiness: Is there good data quality in EPR systems; (2) Record readiness: Are EPR data able to identify eligible cases and other study data; (3) Organisational readiness: Are the health system and socio-cultural environment supportive; (4) Governance readiness: Does the study meet legal and local health system regulatory compliance; (5) Study-specific readiness; (6) Business process readiness: Are business processes tilted in favour of participation: including capacity and capability to take on extra work, financial incentives as well as intangibles such as social and intellectual capital; (7) Patient readiness: Are systems in place to recruit patients and obtain informed consent?ConclusionsThe model might enable the development of interventions to increase participation in primary care-based research and become a tool to measure the progress of practice networks towards the most advanced state of readiness.

Building a Privacy, Ethics, and Data Access Framework for Real World Computerised Medical Record System Data: A Delphi Study

BACKGROUND Privacy, ethics, and data access issues pose significant challenges to the timely delivery of health research. Whilst the fundamental drivers to ensure that data access is ethical and satisfies privacy requirements are similar, they are often dealt with in varying ways by different approval processes. OBJECTIVE To achieve a consensus across an international panel of health care and informatics professionals on an integrated set of privacy and ethics principles that could accelerate health data access in data-driven health research projects. METHOD A three-round consensus development process was used. In round one, we developed a baseline framework for privacy, ethics, and data access based on a review of existing literature in the health, informatics, and policy domains. This was further developed using a two-round Delphi consensus building process involving 20 experts who were members of the International Medical Informatics Association (IMIA) and European Federation of Medical Informatics (EFMI) Primary Health Care Informatics Working Groups. To achieve consensus we required an extended Delphi process. RESULTS The first round involved feedback on and development of the baseline framework. This consisted of four components: (1) ethical principles, (2) ethical guidance questions, (3) privacy and data access principles, and (4) privacy and data access guidance questions. Round two developed consensus in key areas of the revised framework, allowing the building of a newly, more detailed and descriptive framework. In the final round panel experts expressed their opinions, either as agreements or disagreements, on the ethics and privacy statements of the framework finding some of the previous round disagreements to be surprising in view of established ethical principles. CONCLUSION This study develops a framework for an integrated approach to ethics and privacy. Privacy breech risk should not be considered in isolation but instead balanced by potential ethical benefit.

Computerised medical record systems that guide and protect – reflections on the Bawa-Garba case

Lawrence Weed proposed we develop computerised, problem-oriented medical records that guide and teach. The Bawa-Garba case outcomes might have been different if care had been supported by computerised medical record (CMR) systems. CMR systems can reduce prescribing errors and could be developed to flag gaps in supervision. However, CMR systems are not a panacea and need to be fit for purpose. Our informatics perspective on this case is to call for widespread use of CMR systems – designed to guide and protect.