Informatics in Primary Care (BCS, The Chartered Institute for IT)
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The adoption of an electronic health record did not improve A1c values in Type 2 diabetes
Full text linkBackground: A major justification for the clinical adoption of electronic health records (EHRs) was the expectation that it would improve the quality of medical care. No longitudinal study has tested this assumption.Objective: We used hemoglobin A1c, a recognized clinical quality measure directly related to diabetes outcomes, to assess the effect of EHR use on clinical quality.Methods: We performed a five-and-one-half-year multicentre longitudinal retrospective study of the A1c values of 537 type 2 diabetic patients. The same patients had to have been seen on at least three occasions: once approximately six months prior to EHR adoption (before-EHR), once approximately six monthsafter EHR adoption (after-EHR) and once approximately five years after EHR adoption (five-years), for a total of 1,611 notes.Results: The overall mean confidence interval (CI) A1c values for the before- EHR, after-EHR and five-years were 7.07 (6.91 – 7.23), 7.33 (7.14 – 7.52) and 7.19 (7.06 – 7.32), respectively. There was a small but significant increase in A1c values between before-EHR and after-EHR, p = .04; there were no other significant differences. There was a significant decrease in notes missing at least one A1c value, from 42% before-EHR to 16% five-years (p < .001).Conclusion: We found that based on patient’s A1c values, EHRs did not improve the clinical quality of diabetic care in six months and five years after EHR adoption. To our knowledge, this is the first longitudinal study to directly assess the relationshipbetween the use of an EHR and clinical quality.
Using routinely collected health data for surveillance, quality improvement and research: Framework and key questions to assess ethics, privacy and data access
Full text linkBackground 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
Tightrope walking towards maximising secondary uses of digitised health data: a qualitative study.
Full text linkBackground Timely progress with attaining benefits from Health Information Technology (HIT) investments requires UK policymakers and others to negotiate challenges in developing structures and processes to catalyse the trustworthy secondary uses of HIT-derived data.Aims We aimed to uncover expert insights into perceived barriers and facilitators for maximising safe and secure secondary uses of HIT-derived data in the UK.Methods We purposively selected individuals from a range of disciplines in the UK and abroad to participate in a thematically analysed, semi-structured interview study.Results We identified a main theme of ‘tightrope walking’ from our interviews (n = 23), reflecting trying to balance different stakeholders’ views and priorities, with sub-themes of ‘a culture of caution’, ‘fuzzy boundaries’ and ‘cultivating the ground’. The public interest concept was fundamental to interviewees’ support for secondary uses of HIT-derived data. Small scale and prior collaborative relationships facilitated progress. Involving commercial companies, improving data quality, achieving proportionate governance and capacity building remained challenges.Conclusions One challenge will be scaling up data linkage successes more evident internationally with regional population datasets. Within the UK, devolved nations have the advantage that ‘small scale’ encompasses national datasets. Proportionate governance principles developed in Scotland could be more widely applicable, while lessons on public engagement might be learned from Western Australia. A UK policy focus now should be on expediting large-scale demonstrator projects and effectively communicating their findings and impact. Progress could be jeopardised if national data protection laws were superseded by any Europen Union-wide regulation governing personal data
Patient-facing Technology for Identification of COPD in Primary Care
No full textThe proliferation of mobile devices and emergence of interoperable ‘mHealth’ apps is accelerating development and deployment of patient-facing risk assessments in primary care. The present study describes a user-centered design and an agile development approach to creation of an app for assessing lungfunction as part of a randomized controlled trial for the dentification of chronic obstructive lung disease in primary care. Seventeen patients recruited from a hospital-based, ambulatory family medicine clinic agreed to be videotaped while using the app, Lung Age, on a first-generation iPad prior to their providerencounter. Subsequently, participants were interviewed using a semi-structured interview guide upon exiting their medical visit. Observational data indicated that participants took advantage of the portability and flexibility of the tablet device in the exam room to engage with the Lung Age app with the optionto share and discuss their results with their providers. Results from the semistructured interviews indicated that participants perceived the Lung Age app as intuitive and easy to use. These results demonstrate that tablet computers and mHealth apps can be used to deploy acceptable and useable electronic risk assessments in primary care settings. Future research focused on the impact and outcomes of patient-centered, mHealth apps for risk screening in primary care is warranted
Open Source Paradigm: A Synopsis of The Cathedral and the Bazaar for Health and Social Care
Full text linkBackground: Open source software (OSS) is becoming more fashionable in health and social care, although the ideas are not new. However progress has been slower than many had expected.Objective: The purpose is to summarise the Free/Libre Open Source Software (FLOSS) paradigm in terms of what it is, how it impacts users and software engineers and how it can work as a business model in health and social care sectors.Method: Much of this paper is a synopsis of Eric Raymond’s seminal book The Cathedral and the Bazaar, which was the first comprehensive description of the open source ecosystem, set out in three long essays. Direct quotes from the book are used liberally, without reference to specific passages. The first part contrasts open and closed source approaches to software development and support. The second part describes the culture and practices of the open source movement. The third part considers business models.Conclusion: A key benefit of open source is that users can access and collaborate on improving the software if they wish. Closed source code may be regarded as a strategic business risk that that may be unacceptable if there is an open source alternative. The sharing culture of the open source movement fits well with that of health and social care
In this issue: Time to replace doctors’ judgement with computers
Full text linkInformaticians continue to rise to the challenge, set by the English Health Minister, of trying to replace doctors’ judgement with computers. This issue describes successes and where there are barriers. However, whilst there is progress this tends to be incremental and there are grand challenges to be overcome before computers can replace clinician. These grand challenges include: (1) improving usability so it is possible to more readily incorporate technology into clinical workflow; (2) rigorous new analytic methods that make use of the mass of available data, ‘Big data’, to create real-world evidence; (3) faster ways of meeting regulatory and legal requirements including ensuring privacy; (4) provision of reimbursement models to fund innovative technology that can substitute for clinical time and (5) recognition that innovations that improve quality also often increase cost. Informatics more is likely to support and augment clinical decision making rather than replace clinicians
A Clinical Decision Support System for Chronic Pain Management in Primary Care: Usability testing and its relevance
Full text linkBackground Clinical decision support systems (CDSSs) that are integrated into electronic medical records may be useful for encouraging practice change compliant with clinical practice guidelines.Objective To engage end users to inform early phase CDSS development through a process of usability testing.Method A sequential exploratory mixed method approach was used. Interprofessional clinician participants (seven in iteration 1 and six in iteration 2) were asked to ‘think aloud’ while performing various tasks on the CDSS and then complete the System Usability Scale (SUS). Changes were made to the CDSS after each iteration.Results Barriers and facilitators were identified: systemic; user interface (most numerous barriers); content (most numerous facilitators) and technical. The mean SUS score was 81.1 (SD = 12.02) in iteration 1 and 70.40 (SD = 6.78) in iteration 2 (p > 0.05).Conclusions Qualitative data from usability testing were valuable in the CDSS development process. SUS scores were of limited value at this development stage.
Using ontologies to improve semantic interoperability in health data
Full text linkThe 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.
In this issue: Unleashing the power of e-Health requires the development of an evidence base for interventions that improve care
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Creating and using real-world evidence to answer questions about clinical effectiveness
Full text linkNew forms of evidence are needed to complement evidence generated from randomised controlled trials (RCTs). Real-World Evidence (RWE) is a potential new form of evidence, but remains undefined.This paper sets to fill that gap by defining RWE as the output from a rigorous research process which: (1) includes a clear a priori statement of a hypothesis to be tested or research question to be answered; (2) defines the data sources that will be used and critically appraises their strengths and weaknesses; and (3) applies appropriate methods, including advanced analytics. These elements should be set out in advance of the study commencing, ideally in a published protocol.The strengths of RWE studies are that they are more inclusive than RCTs and can enable an evidence base to be developed around real-world effectiveness and to start to address the complications of managing other real-world problems such as multimorbidity. Computerised medical record systems and big data provide a rich source of data for RWE studies.However, guidance is needed to help assess the rigour of RWE studies so that the strength of recommendations based on their output can be determined. Additionally, RWE advanced analytics methods need better categorisation and validation.We predict that the core role of RCTs will shift towards assessing safety and achieving regulatory compliance. RWE studies, notwithstanding their limitations, may become established as the best vehicle to assess efficacy.