Publications by authors named "Siaw-Teng Liaw"

113 Publications

National Heart Foundation of Australia: position statement on coronary artery calcium scoring for the primary prevention of cardiovascular disease in Australia.

Med J Aust 2021 May 7. Epub 2021 May 7.

National Heart Foundation of Australia, Melbourne, VIC.

Introduction: This position statement considers the evolving evidence on the use of coronary artery calcium scoring (CAC) for defining cardiovascular risk in the context of Australian practice and provides advice to health professionals regarding the use of CAC scoring in primary prevention of cardiovascular disease in Australia. Main recommendations: CAC scoring could be considered for selected people with moderate absolute cardiovascular risk, as assessed by the National Vascular Disease Prevention Alliance (NVDPA) absolute cardiovascular risk algorithm, and for whom the findings are likely to influence the intensity of risk management. (GRADE evidence certainty: Low. GRADE recommendation strength: Conditional.) CAC scoring could be considered for selected people with low absolute cardiovascular risk, as assessed by the NVDPA absolute cardiovascular risk algorithm, and who have additional risk-enhancing factors that may result in the underestimation of risk. (GRADE evidence certainty: Low. GRADE recommendation strength: Conditional.) If CAC scoring is undertaken, a CAC score of 0 AU could reclassify a person to a low absolute cardiovascular risk status, with subsequent management to be informed by patient-clinician discussion and follow contemporary recommendations for low absolute cardiovascular risk. (GRADE evidence certainty: Very low. GRADE recommendation strength: Conditional.) If CAC scoring is undertaken, a CAC score > 99 AU or ≥ 75th percentile for age and sex could reclassify a person to a high absolute cardiovascular risk status, with subsequent management to be informed by patient-clinician discussion and follow contemporary recommendations for high absolute cardiovascular risk. (GRADE evidence certainty: Very low. GRADE recommendation strength: Conditional.) CHANGES IN MANAGEMENT AS A RESULT OF THIS STATEMENT: CAC scoring can have a role in reclassification of absolute cardiovascular risk for selected patients in Australia, in conjunction with traditional absolute risk assessment and as part of a shared decision-making approach that considers the preferences and values of individual patients.
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http://dx.doi.org/10.5694/mja2.51039DOI Listing
May 2021

Characterizing database granularity using SNOMED-CT hierarchy.

AMIA Annu Symp Proc 2020 25;2020:983-992. Epub 2021 Jan 25.

Columbia University, New York, NY, USA.

Multi-center observational studies require recognition and reconciliation of differences in patient representations arising from underlying populations, disparate coding practices and specifics of data capture. This leads to different granularity or detail of concepts representing the clinical facts. For researchers studying certain populations of interest, it is important to ensure that concepts at the right level are used for the definition of these populations. We studied the granularity of concepts within 22 data sources in the OHDSI network and calculated a composite granularity score for each dataset. Three alternative SNOMED-based approaches for such score showed consistency in classifying data sources into three levels of granularity (low, moderate and high), which correlated with the provenance of data and country of origin. However, they performed unsatisfactorily in ordering data sources within these groups and showed inconsistency for small data sources. Further studies on examining approaches to data source granularity are needed.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8075504PMC
January 2021

Primary Care Informatics Response to Covid-19 Pandemic: Adaptation, Progress, and Lessons from Four Countries with High ICT Development.

Yearb Med Inform 2021 Apr 21. Epub 2021 Apr 21.

Nuffield Department of Primary Care Health Sciences, University of Oxford, UK.

Objective: Internationally, primary care practice had to transform in response to the COVID pandemic. Informatics issues included access, privacy, and security, as well as patient concerns of equity, safety, quality, and trust. This paper describes progress and lessons learned.

Methods: IMIA Primary Care Informatics Working Group members from Australia, Canada, United Kingdom and United States developed a standardised template for collection of information. The template guided a rapid literature review. We also included experiential learning from primary care and public health perspectives.

Results: All countries responded rapidly. Common themes included rapid reductions then transformation to virtual visits, pausing of non-COVID related informatics projects, all against a background of non-standardized digital development and disparate territory or state regulations and guidance. Common barriers in these four and in less-resourced countries included disparities in internet access and availability including bandwidth limitations when internet access was available, initial lack of coding standards, and fears of primary care clinicians that patients were delaying care despite the availability of televisits.

Conclusions: Primary care clinicians were able to respond to the COVID crisis through telehealth and electronic record enabled change. However, the lack of coordinated national strategies and regulation, assurance of financial viability, and working in silos remained limitations. The potential for primary care informatics to transform current practice was highlighted. More research is needed to confirm preliminary observations and trends noted.
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http://dx.doi.org/10.1055/s-0041-1726489DOI Listing
April 2021

Implementation of the COVID-19 Vulnerability Index Across an International Network of Health Care Data Sets: Collaborative External Validation Study.

JMIR Med Inform 2021 Apr 5;9(4):e21547. Epub 2021 Apr 5.

Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Republic of Korea.

Background: SARS-CoV-2 is straining health care systems globally. The burden on hospitals during the pandemic could be reduced by implementing prediction models that can discriminate patients who require hospitalization from those who do not. The COVID-19 vulnerability (C-19) index, a model that predicts which patients will be admitted to hospital for treatment of pneumonia or pneumonia proxies, has been developed and proposed as a valuable tool for decision-making during the pandemic. However, the model is at high risk of bias according to the "prediction model risk of bias assessment" criteria, and it has not been externally validated.

Objective: The aim of this study was to externally validate the C-19 index across a range of health care settings to determine how well it broadly predicts hospitalization due to pneumonia in COVID-19 cases.

Methods: We followed the Observational Health Data Sciences and Informatics (OHDSI) framework for external validation to assess the reliability of the C-19 index. We evaluated the model on two different target populations, 41,381 patients who presented with SARS-CoV-2 at an outpatient or emergency department visit and 9,429,285 patients who presented with influenza or related symptoms during an outpatient or emergency department visit, to predict their risk of hospitalization with pneumonia during the following 0-30 days. In total, we validated the model across a network of 14 databases spanning the United States, Europe, Australia, and Asia.

Results: The internal validation performance of the C-19 index had a C statistic of 0.73, and the calibration was not reported by the authors. When we externally validated it by transporting it to SARS-CoV-2 data, the model obtained C statistics of 0.36, 0.53 (0.473-0.584) and 0.56 (0.488-0.636) on Spanish, US, and South Korean data sets, respectively. The calibration was poor, with the model underestimating risk. When validated on 12 data sets containing influenza patients across the OHDSI network, the C statistics ranged between 0.40 and 0.68.

Conclusions: Our results show that the discriminative performance of the C-19 index model is low for influenza cohorts and even worse among patients with COVID-19 in the United States, Spain, and South Korea. These results suggest that C-19 should not be used to aid decision-making during the COVID-19 pandemic. Our findings highlight the importance of performing external validation across a range of settings, especially when a prediction model is being extrapolated to a different population. In the field of prediction, extensive validation is required to create appropriate trust in a model.
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http://dx.doi.org/10.2196/21547DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8023380PMC
April 2021

Toolkits for implementing and evaluating digital health: A systematic review of rigor and reporting.

J Am Med Inform Assoc 2021 Feb 23. Epub 2021 Feb 23.

WHO Collaborating Centre on eHealth (AUS-135), School of Population Health, UNSW Sydney, New South Wales, Australia.

Objective: Toolkits are an important knowledge translation strategy for implementing digital health. We studied how toolkits for the implementation and evaluation of digital health were developed, tested, and reported.

Materials And Methods: We conducted a systematic review of toolkits that had been used, field tested or evaluated in practice, and published in the English language from 2009 to July 2019. We searched several electronic literature sources to identify both peer-reviewed and gray literature, and records were screened as per systematic review conventions.

Results: Thirteen toolkits were eventually identified, all of which were developed in North America, Europe, or Australia. All reported their intended purpose, as well as their development process. Eight of the 13 toolkits involved a literature review, 3 did not, and 2 were unclear. Twelve reported an underlying conceptual framework, theory, or model: 3 cited the normalization process theory and 3 others cited the World Health Organization and International Telecommunication Union eHealth Strategy. Seven toolkits were reportedly evaluated, but details were unavailable. Forty-three toolkits were excluded for lack of field-testing.

Discussion: Despite a plethora of published toolkits, few were tested, and even fewer were evaluated. Methodological rigor was of concern, as several did not include an underlying conceptual framework, literature review, or evaluation and refinement in real-world settings. Reporting was often inconsistent and unclear, and toolkits rarely reported being evaluated.

Conclusion: Greater attention needs to be paid to rigor and reporting when developing, evaluating, and reporting toolkits for implementing and evaluating digital health so that they can effectively function as a knowledge translation strategy.
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http://dx.doi.org/10.1093/jamia/ocab010DOI Listing
February 2021

A New Method for Estimating the Incidence of Infectious Diseases.

Am J Epidemiol 2021 Feb 4. Epub 2021 Feb 4.

The Kirby Institute, UNSW Sydney, Sydney, NSW, Australia.

Ambitious World Health Organization targets for disease elimination require monitoring of epidemics using routine health data in settings of decreasing and low incidence. We evaluated two methods commonly applied to routine testing results to estimate incidence rates that assume uniform probability of infection between consecutive negative and positive tests based on: 1. the midpoint of this interval; and 2. a randomly selected point on this interval. We compared these with an approximation to the Poisson-binomial distribution which assigns partial incidence to time-periods based on the uniform probability of occurrence in these intervals. We assessed bias, variance and convergence of estimates using simulations of Weibull distributed failure times with systematically varied baseline incidence, and varying trend. We considered results for quarterly, half-yearly and yearly incidence estimation frequencies. We applied methods to assess human immunodeficiency virus (HIV) incidence in HIV-negative patients from the Treatment with Antiretrovirals and their Impact on Positive And Negative men study between 2012 and 2018. The Poisson-binomial method had reduced bias and variance at low levels of incidence and for increased estimation frequency, with increased consistency of estimation. Application of methods to real-world assessment of HIV incidence found decreased variance in Poisson-binomial model estimates, with observed incidence declining to levels where simulation results had indicated bias in midpoint and random-point methods.
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http://dx.doi.org/10.1093/aje/kwab014DOI Listing
February 2021

Quality assessment of real-world data repositories across the data life cycle: A literature review.

J Am Med Inform Assoc 2021 Jan 26. Epub 2021 Jan 26.

Department of Pediatrics (Section of Informatics and Data Sciences), University of Colorado Anschutz Medical Campus, Denver, Colorado, USA.

Objective: Data quality (DQ) must be consistently defined in context. The attributes, metadata, and context of longitudinal real-world data (RWD) have not been formalized for quality improvement across the data production and curation life cycle. We sought to complete a literature review on DQ assessment frameworks, indicators and tools for research, public health, service, and quality improvement across the data life cycle.

Materials And Methods: The review followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Databases from health, physical and social sciences were used: Cinahl, Embase, Scopus, ProQuest, Emcare, PsycINFO, Compendex, and Inspec. Embase was used instead of PubMed (an interface to search MEDLINE) because it includes all MeSH (Medical Subject Headings) terms used and journals in MEDLINE as well as additional unique journals and conference abstracts. A combined data life cycle and quality framework guided the search of published and gray literature for DQ frameworks, indicators, and tools. At least 2 authors independently identified articles for inclusion and extracted and categorized DQ concepts and constructs. All authors discussed findings iteratively until consensus was reached.

Results: The 120 included articles yielded concepts related to contextual (data source, custodian, and user) and technical (interoperability) factors across the data life cycle. Contextual DQ subcategories included relevance, usability, accessibility, timeliness, and trust. Well-tested computable DQ indicators and assessment tools were also found.

Conclusions: A DQ assessment framework that covers intrinsic, technical, and contextual categories across the data life cycle enables assessment and management of RWD repositories to ensure fitness for purpose. Balancing security, privacy, and FAIR principles requires trust and reciprocity, transparent governance, and organizational cultures that value good documentation.
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http://dx.doi.org/10.1093/jamia/ocaa340DOI Listing
January 2021

A digital health profile & maturity assessment toolkit: cocreation and testing in the Pacific Islands.

J Am Med Inform Assoc 2021 Mar;28(3):494-503

WHO Western Pacific Region Office, Manila, Philippines.

Introduction: Countries need to determine their level of digital health capability maturity to assess and mobilize their knowledge, skills, and resources to systematically develop, implement, evaluate, scale up and maintain large-scale implementations of standards-based interoperable digital health tools.

Objective: Develop a Digital Health Profile and Maturity Assessment Toolkit (DHPMAT) to assist Pacific Island Countries (PICs) to harness digital tools to support national health priorities.

Materials And Methods: A literature review guided the development of the conceptual framework to underpin the DHPMAT. Key informants collaborated to collect key digital health features and indicators to inform their country's digital health maturity assessment. The DHPMAT was tested with country stakeholders at a Pacific Health Information Network workshop in 2019.

Results: A comprehensive list of indicators to describe country digital health profiles (DHP). A digital health maturity assessment tool that uses criteria codeveloped with country stakeholders to assess essential digital health foundations and quality improvement. DHPs created and maturity assessed and packaged into individualized DHPMATs for 13 PICs. PIC users perceived the DHPMAT as useful, especially the congruence with the 2017 WHO WPRO Regional Strategy but noted a "cognitive overload" from a plethora of complex digital health toolkits.

Conclusions: The cocreation approach optimized currency, accuracy, and appropriateness of information in the DHP, understanding, and use of the DHPMAT to facilitate informed iterative discussion by PICs on their digital health maturity to harness digital tools to strengthen country health systems. The DHPMAT can rationalize the choice and use of existing tools and reduce cognitive overload.
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http://dx.doi.org/10.1093/jamia/ocaa255DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936524PMC
March 2021

Evaluation of Digital Health & Information Technology in Primary Care.

Int J Med Inform 2020 12 23;144:104285. Epub 2020 Sep 23.

Federal University of São Paulo, Brazil.

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http://dx.doi.org/10.1016/j.ijmedinf.2020.104285DOI Listing
December 2020

mHealth for Integrated People-Centred Health Services in the Western Pacific: A Systematic Review.

Int J Med Inform 2020 10 19;142:104259. Epub 2020 Aug 19.

WHO Collaborating Centre for eHealth, School of Public Health and Community Medicine, UNSW Sydney, Australia. Electronic address:

Objective: This review aimed to examine how mobile health (mHealth) to support integrated people-centred health services has been implemented and evaluated in the World Health Organization (WHO) Western Pacific Region (WPR).

Methods: Eight scientific databases were searched. Two independent reviewers screened the literature in title and abstract stages, followed by full-text appraisal, data extraction, and synthesis of eligible studies. Studies were extracted to capture details of the mhealth tools used, the service issues addressed, the study design, and the outcomes evaluated. We then mapped the included studies using the 20 sub-strategies of the WHO Framework on Integrated People-Centred Health Services (IPCHS); as well as with the RE-AIM (Reach, effectiveness, adoption, implementation and maintenance) framework, to understand how studies implemented and evaluated interventions.

Results: We identified 39 studies, predominantly from Australia (n = 16), China (n = 7), Malaysia (n = 4) and New Zealand (n = 4), and little from low income countries. The mHealth modalities included text messaging, voice and video communication, mobile applications and devices (point-of-care, GPS, and Bluetooth). Health issues addressed included: medication adherence, smoking cessation, cardiovascular disease, heart failure, asthma, diabetes, and lifestyle activities respectively. Almost all were community-based and focused on service issues; only half were disease-specific. mHealth facilitated integrated IPCHS by: enabling citizens and communities to bypass gatekeepers and directly access services; increasing affordability and accessibility of services; strengthening governance over the access, use, safety and quality of clinical care; enabling scheduling and navigation of services; transitioning patients and caregivers between care sectors; and enabling the evaluation of safety and quality outcomes for systemic improvement. Evaluations of mHealth interventions did not always report the underlying theories. They predominantly reported cognitive/behavioural changes rather than patient outcomes. The utility of mHealth to support and improve IPCHS was evident. However, IPCHS strategy 2 (participatory governance and accountability) was addressed least frequently. Implementation was evaluated in regard to reach (n = 30), effectiveness (n = 24); adoption (n = 5), implementation (n = 9), and maintenance (n = 1).

Conclusions: mHealth can transition disease-centred services towards people-centred services. Critical appraisal of studies highlighted methodological issues, raising doubts about validity. The limited evidence for large-scale implementation and international variation in reporting of mHealth practice, modalities used, and health domains addressed requires capacity building. Information-enhanced implementation and evaluation of IPCHS, particularly for participatory governance and accountability, is also important.
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http://dx.doi.org/10.1016/j.ijmedinf.2020.104259DOI Listing
October 2020

Community health alliances as social enterprises that digitally engage citizens and integrate services: A case study in Southwestern Sydney (protocol).

Digit Health 2020 Jan-Dec;6:2055207620930118. Epub 2020 Jun 22.

World Health Organization Collaborating Centre for eHealth, School of Public Health and Community Medicine, UNSW Sydney, Australia.

South Western Sydney (SWS) is one of the fastest growing regions in the state of New South Wales (Australia). Much of the population live in local government areas (LGAs) with levels of disadvantage higher than the state average, with a predominance of non-communicable and chronic diseases that are typically associated with age-related and behavioural factors. This necessitates the management of social determinants of health through the integrated provision of primary and social care. The SWS Local Health District and Primary Health Network is exploring the potential of community health alliances (CHAs) as an innovative approach to support the provision of integrated health services. CHAs are a population health approach for addressing health challenges faced by people who share a common area of residence, sociocultural characteristic or health need, and are characterised by a shared mission, shared resource needs and acquiring/developing necessary organisational knowledge and skills. We explore how CHAs operate as social enterprises that utilise digital health and citizen engagement to deliver integrated people-centred health services (IPCHS) by conducting two case studies of CHAs operating in SWS: in Wollondilly and Fairfield LGAs. Using this approach, we aim to unpack the conceptual convergence that enables social enterprises to utilise digital health interventions and citizen engagement strategies to co-produce IPCHS with a view to developing theory and a framework for engaging digital citizens in integrated primary health care via social enterprise.
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http://dx.doi.org/10.1177/2055207620930118DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7313330PMC
June 2020

Adoption of enterprise architecture for healthcare in AeHIN member countries.

BMJ Health Care Inform 2020 Jul;27(1)

School of Public Health and Community Medicine, UNSW Sydney, Sydney, New South Wales, Australia.

Background: Healthcare organisations are undergoing a major transformational shift in the use of information and digital health technologies. Enterprise architecture (EA) has been incrementally adopted in many healthcare organisations globally to facilitate this change. EA can increase the effectiveness of an organisation's digital health capabilities and resources. However, little is known about the status of EA adoption in low-income and middle-income countries. This study aimed to evaluate the challenges, goals and benefits associated with adoption of EA for healthcare in the Asia eHealth Information Network (AeHIN) member countries .

Methods: We developed an EA Adoption Evaluation framework with four principal layers: governance, strategy, EA and performance. The framework guided the development of a questionnaire to investigate the goals, challenges and benefits faced before and during EA adoption by healthcare organisations.

Sample: 26 participants from 18 healthcare organisations in the Asia-Pacific region representing 11 countries. Organisations included Ministries of Health, Universities, Non-Governmental Organisations and Technical Advisory Groups.

Findings: Only 5 of the 18 organisations had begun adopting EA. The goals expressed for EA adoption were to address issues such as interoperability, lack of technical infrastructure and poor alignment of business and information technology strategies. Cost reduction was less emphasised. The main challenges to adopting EA was the lack of EA knowledge, leadership and involvement of senior management.

Conclusion: The adoption of EA is incipient in AeHIN member healthcare organisations. To encourage EA adoption, these organisations need to invest in internal capacity building, senior management training and seek independent EA expert advice to systematically identify and address the barriers to adopting EA.
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http://dx.doi.org/10.1136/bmjhci-2020-100136DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333875PMC
July 2020

Ethical Use of Electronic Health Record Data and Artificial Intelligence: Recommendations of the Primary Care Informatics Working Group of the International Medical Informatics Association.

Yearb Med Inform 2020 Aug 17;29(1):51-57. Epub 2020 Apr 17.

Clnical Informatics and Health Outcomes Research Group, Nuffield Department of Primary Care Health Sciences, University of Oxford, Eagle House, 7 Walton Well Road, Oxford, OX2 6ED, UK.

Objective: To create practical recommendations for the curation of routinely collected health data and artificial intelligence (AI) in primary care with a focus on ensuring their ethical use.

Methods: We defined data curation as the process of management of data throughout its lifecycle to ensure it can be used into the future. We used a literature review and Delphi exercises to capture insights from the Primary Care Informatics Working Group (PCIWG) of the International Medical Informatics Association (IMIA).

Results: We created six recommendations: (1) Ensure consent and formal process to govern access and sharing throughout the data life cycle; (2) Sustainable data creation/collection requires trust and permission; (3) Pay attention to Extract-Transform-Load (ETL) processes as they may have unrecognised risks; (4) Integrate data governance and data quality management to support clinical practice in integrated care systems; (5) Recognise the need for new processes to address the ethical issues arising from AI in primary care; (6) Apply an ethical framework mapped to the data life cycle, including an assessment of data quality to achieve effective data curation.

Conclusions: The ethical use of data needs to be integrated within the curation process, hence running throughout the data lifecycle. Current information systems may not fully detect the risks associated with ETL and AI; they need careful scrutiny. With distributed integrated care systems where data are often used remote from documentation, harmonised data quality assessment, management, and governance is important. These recommendations should help maintain trust and connectedness in contemporary information systems and planned developments.
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http://dx.doi.org/10.1055/s-0040-1701980DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442527PMC
August 2020

Comparison of the cohort selection performance of Australian Medicines Terminology to Anatomical Therapeutic Chemical mappings.

J Am Med Inform Assoc 2019 11;26(11):1237-1246

School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia.

Objective: Electronic health records are increasingly utilized for observational and clinical research. Identification of cohorts using electronic health records is an important step in this process. Previous studies largely focused on the methods of cohort selection, but there is little evidence on the impact of underlying vocabularies and mappings between vocabularies used for cohort selection. We aim to compare the cohort selection performance using Australian Medicines Terminology to Anatomical Therapeutic Chemical (ATC) mappings from 2 different sources. These mappings were taken from the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) and the Pharmaceutical Benefits Scheme (PBS) schedule.

Materials And Methods: We retrieved patients from the electronic Practice Based Research Network data repository using 3 ATC classification groups (A10, N02A, N06A). The retrieved patients were further verified manually and pooled to form a reference standard which was used to assess the accuracy of mappings using precision, recall, and F measure metrics.

Results: The OMOP-CDM mappings identified 2.6%, 15.2%, and 24.4% more drugs than the PBS mappings in the A10, N02A and N06A groups respectively. Despite this, the PBS mappings generally performed the same in cohort selection as OMOP-CDM mappings except for the N02A Opioids group, where a significantly greater number of patients were retrieved. Both mappings exhibited variable recall, but perfect precision, with all drugs found to be correctly identified.

Conclusion: We found that 1 of the 3 ATC groups had a significant difference and this affected cohort selection performance. Our findings highlighted that underlying terminology mappings can greatly impact cohort selection accuracy. Clinical researchers should carefully evaluate vocabulary mapping sources including methodologies used to develop those mappings.
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http://dx.doi.org/10.1093/jamia/ocz143DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7647230PMC
November 2019

Generation of Surrogates for De-Identification of Electronic Health Records.

Stud Health Technol Inform 2019 Aug;264:70-73

School of Public Health and Community Medicine, UNSW Sydney, Australia.

Unstructured electronic health records are valuable resources for research. Before they are shared with researchers, protected health information needs to be removed from these unstructured documents to protect patient privacy. The main steps involved in removing protected health information are accurately identifying sensitive information in the documents and removing the identified information. To keep the documents as realistic as possible, the step of omitting sensitive information is often followed by replacement of identified sensitive information with surrogates. In this study, we present an algorithm to generate surrogates for unstructured electronic health records. We used this algorithm to generate realistic surrogates on a Health Science Alliance corpus, which is constructed specifically for the use of development of automated de-identification systems.
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http://dx.doi.org/10.3233/SHTI190185DOI Listing
August 2019

A Realist Synthesis of Literature Informing Programme Theories for Well Child Care in Primary Health Systems of Developed Economies.

Int J Integr Care 2019 Jul 24;19(3). Epub 2019 Jul 24.

Ingham Institute of Applied Medical Research, Liverpool, NSW, AU.

Introduction: Well-child Care is the provision of preventative health care services for children and their families. The approach, however, to the universal provision of those services is contentious.

Methods: We undertook a realist synthesis to enhance understanding of the theoretical mechanisms driving Well-child Care by searching for published and grey literature from multiple databases.

Findings: Well-child Care is re-conceptualised as an integrated program delivered in the continuum of pregnancy, infancy and childhood. Depending on the context, Well-child Care can be a policy, a strategy, or an actual clinical practice that promotes child and family health. The main mechanisms include: role, training and continuity of health providers; administrators' views of the return of investment on achieved outcomes; access to services by families; and the adaptation of programs to meet the dynamic needs of stakeholders. Evidence indicates that for most outcomes, Well-child Care is best delivered in partnerships between community health, social care, and early childhood education sectors.

Conclusions: We conclude that Well-child Care policy and program leaders should shift their focus to the integration of: human and physical resources; policy instruments; and shared agreement on outcomes measures across health, social and education sectors. In addition, countries should work towards strengthening universal early education programs and parents' health literacy regarding child development, health and safety.
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http://dx.doi.org/10.5334/ijic.4177DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6659757PMC
July 2019

Linking observational data from general practice, hospital admissions and diabetes clinic databases: can it be used to predict hospital admission?

BMC Health Serv Res 2019 Jul 29;19(1):526. Epub 2019 Jul 29.

Centre for Primary Health Care and Equity, University of New South Wales Australia, Sydney, NSW, 2052, Australia.

Background: Linking process of care data from general practice (GP) and hospital data may provide more information about the risk of hospital admission and re-admission for people with type-2 diabetes mellitus (T2DM). This study aimed to extract and link data from a hospital, a diabetes clinic (DC). A second aim was to determine whether the data could be used to predict hospital admission for people with T2DM.

Methods: Data were extracted using the GRHANITE™ extraction and linkage tool. The data from nine GPs and the DC included data from the two years prior to the hospital admission. The date of the first hospital admission for patients with one or more admissions was the index admission. For those patients without an admission, the census date 31/03/2014 was used in all outputs requiring results prior to an admission. Readmission was any admission following the index admission. The data were summarised to provide a comparison between two groups of patients: 1) Patients with a diagnosis of T2DM who had been treated at a GP and had a hospital admission and 2) Patients with a diagnosis of T2DM who had been treated at a GP and did not have a hospital admission.

Results: Data were extracted for 161,575 patients from the three data sources, 644 patients with T2DM had data linked between the GPs and the hospital. Of these, 170 also had data linked with the DC. Combining the data from the different data sources improved the overall data quality for some attributes particularly those attributes that were recorded consistently in the hospital admission data. The results from the modelling to predict hospital admission were plausible given the issues with data completeness.

Conclusion: This project has established the methodology (tools and processes) to extract, link, aggregate and analyse data from general practices, hospital admission data and DC data. This study methodology involved the establishment of a comparator/control group from the same sites to compare and contrast the predictors of admission, addressing a limitation of most published risk stratification and admission prediction studies. Data completeness needs to be improved for this to be useful to predict hospital admissions.
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http://dx.doi.org/10.1186/s12913-019-4337-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6661817PMC
July 2019

Guest editorial: Special issue in biomedical data quality assessment methods.

Comput Methods Programs Biomed 2019 Nov 13;181:104954. Epub 2019 Jun 13.

Biomedical Data Science Lab, Instituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), Universitat Politècnica de València (UPV), Camino de Vera s/n, Valencia 46022, Spain. Electronic address:

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http://dx.doi.org/10.1016/j.cmpb.2019.06.013DOI Listing
November 2019

Statistical supervised meta-ensemble algorithm for medical record linkage.

J Biomed Inform 2019 07 31;95:103220. Epub 2019 May 31.

School of Public Health and Community Medicine, UNSW Sydney, Australia; WHO Collaborating Centre for eHealth, UNSW Sydney, Australia.

Identifying unique patients across multiple care facilities or services is a major challenge in providing continuous care and undertaking health research. Identifying and linking patients without compromising privacy and security is an emerging issue in the big data era. The large quantity and complexity of the patient data emphasize the need for effective linkage methods that are both scalable and accurate. In this study, we aim to develop and evaluate an ensemble classification method using the three most typically used supervised learning methods, namely support vector machines, logistic regression and standard feed-forward neural networks, to link records that belong to the same patient across multiple service locations. Our ensemble method is the combination of bagging and stacking. Each base learner's critical hyperparameters were selected through grid search technique. Two synthetic datasets were used in this study namely FEBRL and ePBRN. ePBRN linkage dataset was based on linkage errors noticed in the Australian primary care setting. The overall linkage performance was determined by assessing the blocking performance and classification performance. Our ensemble method outperformed the base learners in all evaluation metrics on one dataset. More specifically, the precision, which is average of individual precision scores in case of base learners increased from 90.70% to 94.85% in FEBRL, and from 62.17% to 99.28% in ePBRN. Similarly, the F-score increased from 94.92% to 98.18% in FEBRL, and from 72.99% to 91.72% in ePBRN. Our experiments suggest that we can significantly improve the linkage performance of individual algorithms by employing ensemble strategies.
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http://dx.doi.org/10.1016/j.jbi.2019.103220DOI Listing
July 2019

Cultural respect in general practice: a cluster randomised controlled trial.

Med J Aust 2019 07 30;211(1):43-43.e1. Epub 2019 May 30.

RHD Australia, Menzies School Health Research, Darwin, NT.

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http://dx.doi.org/10.5694/mja2.50214DOI Listing
July 2019

Artificial Intelligence in Primary Health Care: Perceptions, Issues, and Challenges.

Yearb Med Inform 2019 Aug 25;28(1):41-46. Epub 2019 Apr 25.

Department of Clinical & Experimental Medicine, University of Surrey, Guildford, Surrey, UK.

Background: Artificial intelligence (AI) is heralded as an approach that might augment or substitute for the limited processing power of the human brain of primary health care (PHC) professionals. However, there are concerns that AI-mediated decisions may be hard to validate and challenge, or may result in rogue decisions.

Objective: To form consensus about perceptions, issues, and challenges of AI in primary care.

Method: A three-round Delphi study was conducted. Round 1 explored experts' viewpoints on AI in PHC (n=20). Round 2 rated the appropriateness of statements arising from round one (n=12). The third round was an online panel discussion of findings (n=8) with the members of both the International Medical Informatics Association and the European Federation of Medical Informatics Primary Health Care Informatics Working Groups.

Results: PHC and informatics experts reported AI has potential to improve managerial and clinical decisions and processes, and this would be facilitated by common data standards. The respondents did not agree that AI applications should learn and adapt to clinician preferences or behaviour and they did not agree on the extent of AI potential for harm to patients. It was more difficult to assess the impact of AI-based applications on continuity and coordination of care.

Conclusion: While the use of AI in medicine should enhance healthcare delivery, we need to ensure meticulous design and evaluation of AI applications. The primary care informatics community needs to be proactive and to guide the ethical and rigorous development of AI applications so that they will be safe and effective.
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http://dx.doi.org/10.1055/s-0039-1677901DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697547PMC
August 2019

Cultural respect in general practice: a cluster randomised controlled trial.

Med J Aust 2019 04 25;210(6):263-268. Epub 2019 Feb 25.

UNSW Sydney, Sydney, NSW.

Objective: To examine whether the Ways of Thinking and Ways of Doing (WoTWoD) cultural respect framework improves clinically appropriate anticipatory care in general practice and the cultural respect levels of medical practice staff.

Design: Mixed methods, cluster randomised controlled trial with a participatory action research approach.

Setting, Participants: Fifty-six general practices in Sydney and Melbourne, 2014-2017.

Intervention: WoTWoD encompasses a toolkit (ten scenarios illustrating cross-cultural behaviour in clinical practice), one half-day workshop, cultural mentor support for practices, and a local care partnership between participating Medicare locals/primary health networks and local Aboriginal Community Controlled Health Services for guiding the program and facilitating community engagement. The intervention lasted 12 months at each practice.

Major Outcomes: Rates of claims for MBS item 715 (health assessment for Aboriginal and Torres Strait Islander People) and recording of chronic disease risk factors; changes in cultural quotient (CQ) scores of practice staff.

Results: Complete results were available for 28 intervention (135 GPs, 807 Indigenous patients) and 25 control practices (210 GPs, 1554 Indigenous patients). 12-Month rates of MBS item 715 claims and recording of risk factors for the two groups were not statistically significantly different, nor were mean changes in CQ scores, regardless of staff category and practice attributes.

Conclusion: The WoTWoD program did not increase the rate of Indigenous health checks or improve cultural respect scores in general practice. Conceptual, methodologic, and contextual factors that influence cultural mentorship, culturally respectful clinical practice, and Indigenous health care require further investigation.

Trial Registration: Australia New Zealand Clinical Trials Registry ACTRN12614000797673.
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http://dx.doi.org/10.5694/mja2.50031DOI Listing
April 2019

A case study of well child care visits at general practices in a region of disadvantage in Sydney.

PLoS One 2018 11;13(10):e0205235. Epub 2018 Oct 11.

Faculty of Human Sciences Department: Department of Educational Studies, Macquarie University, Sydney, Australia.

Introduction: Well-Child Care (WCC) is the provision of preventive health care services for children and their families. Prior research has highlighted that several barriers exist for the provision of WCC services.

Objectives: To study "real life" visits of parents and children with health professionals in order to enhance the theoretical understanding of factors affecting WCC.

Methods: Participant observations of a cross-sectional sample of 71 visits at three general practices were analysed using a mixed-methods approach.

Results: The median age of the children was 18 months (IQR, 6-36 months), and the duration of visits was 13 mins (IQR, 9-18 mins). The reasons for the visits were immunisation in 13 (18.5%), general check-up in 10 (13.8%), viral illness in 33 (49.2%) and miscellaneous reasons in 15 (18.5%). Two clusters with low and high WCC emerged; WCC was associated with higher GP patient-centeredness scores, younger age of the child, fewer previous visits, immunisation and general check-up visits, and the solo general practitioner setting. Mothers born overseas received less WCC advice, while longer duration of visit increased WCC. GPs often made observations on physical growth and development and negotiated mothers concerns to provide reassurance to them. The working style of the GP which encouraged informal conversations with the parents enhanced WCC. There was a lack of systematic use of developmental screening measures.

Conclusions: GPs and practice nurses are providing parent/child centered WCC in many visits, particularly when parents present for immunisation and general check-ups. Providing funding and practice nurse support to GPs, and aligning WCC activities with all immunisation visits, rather than just a one-off screening approach, appears to be the best way forward. A cluster randomised trial for doing structured WCC activities with immunisation visits would provide further evidence for cost-effectiveness studies to inform policy change.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0205235PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6181326PMC
March 2019

Common Data Models (CDMs) to Enhance International Big Data Analytics: A Diabetes Use Case to Compare Three CDMs.

Stud Health Technol Inform 2018 ;255:60-64

Department of Clinical & Experimental Medicine, University of Surrey, UK.

Common data models (CDM) have enabled the simultaneous analysis of disparate and large data sources. A literature review identified three relevant CDMs: The Observational Medical Outcomes Partnership (OMOP) was the most cited; next the Sentinel; and then the Patient Centered Outcomes Research Institute (PCORI). We tested these three CDMs with fifteen pre-defined criteria for a diabetes cohort study use case, assessing the benefit (good diabetes control), risk (hypoglycaemia) and cost effectiveness of recently licenced medications. We found all three CDMs have a useful role in planning collaborative research and enhance analysis of data cross jurisdiction. However, the number of pre-defined criteria achieved by these three CDMs varied. OMOP met 14/15, Sentinel 13/15, and PCORI 10/15. None met the privacy level we specified, and most of the other gaps were clinical and cost outcome related data.
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August 2019

Preventing chronic disease in patients with low health literacy using eHealth and teamwork in primary healthcare: protocol for a cluster randomised controlled trial.

BMJ Open 2018 06 4;8(6):e023239. Epub 2018 Jun 4.

Centre for Primary Health Care and Equity, University of New South Wales, Sydney, New South Wales, Australia.

Introduction: Adults with lower levels of health literacy are less likely to engage in health-promoting behaviours. Our trial evaluates the impacts and outcomes of a mobile health-enhanced preventive intervention in primary care for people who are overweight or obese.

Methods And Analysis: A two-arm pragmatic practice-level cluster randomised trial will be conducted in 40 practices in low socioeconomic areas in Sydney and Adelaide, Australia. Forty patients aged 40-70 years with a body mass index ≥28 kg/m will be enrolled per practice. The HeLP-general practitioner (GP) intervention includes a practice-level quality improvement intervention (medical record audit and feedback, staff training and practice facilitation visits) to support practices to implement the clinical intervention for patients. The clinical intervention involves a health check visit with a practice nurse based on the 5As framework (assess, advise, agree, assist and arrange), the use of a purpose-built patient-facing app, , and referral for telephone coaching. The primary outcomes are change in health literacy, lifestyle behaviours, weight, waist circumference and blood pressure. The study will also evaluate changes in quality of life and health service use to determine the cost-effectiveness of the intervention and examine the experiences of practices in implementing the programme.

Ethics And Dissemination: The study has been approved by the University of New South Wales (UNSW) Human Research Ethics Committee (HC17474) and ratified by the University of Adelaide Human Research Ethics committee. There are no restrictions on publication, and findings of the study will be made available to the public via the Centre for Primary Health Care and Equity website and through conference presentations and research publications. Deidentified data and meta-data will be stored in a repository at UNSW and made available subject to ethics committee approval.

Trial Registrationregistration Number: ACTRN12617001508369; Pre-results.
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http://dx.doi.org/10.1136/bmjopen-2018-023239DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988137PMC
June 2018

Benefit-risk of Patients' Online Access to their Medical Records: Consensus Exercise of an International Expert Group.

Yearb Med Inform 2018 Aug 22;27(1):156-162. Epub 2018 Apr 22.

Department of Clinical & Experimental Medicine, University of Surrey, GUILDFORD, Surrey, UK.

Background:  Patients' access to their computerised medical records (CMRs) is a legal right in many countries. However, little is reported about the benefit-risk associated with patients' online access to their CMRs.

Objective:  To conduct a consensus exercise to assess the impact of patients' online access to their CMRs on the quality of care as defined in six domains by the Institute of Medicine (IoM), now the National Academy of Medicine (NAM).

Method:  A five-round Delphi study was conducted. Round One explored experts' (n = 37) viewpoints on providing patients with access to their CMRs. Round Two rated the appropriateness of statements arising from Round One (n = 16). The third round was an online panel discussion of findings (n = 13) with the members of both the International Medical Informatics Association and the European Federation of Medical Informatics Primary Health Care Informatics Working Groups. Two additional rounds, a survey of the revised consensus statements and an online workshop, were carried out to further refine consensus statements.

Results:  Thirty-seven responses from Round One were used as a basis to initially develop 15 statements which were categorised using IoM's domains of care quality. The experts agreed that providing patients online access to their CMRs for bookings, results, and prescriptions increased efficiency and improved the quality of medical records. Experts also anticipated that patients would proactively use their online access to share data with different health care providers, including emergencies. However, experts differed on whether access to limited or summary data was more useful to patients than accessing their complete records. They thought online access would change recording practice, but they were unclear about the benefit-risk of high and onerous levels of security. The 5-round process, finally, produced 16 consensus statements.

Conclusion:  Patients' online access to their CMRs should be part of all CMR systems. It improves the process of health care, but further evidence is required about outcomes. Online access improves efficiency of bookings and other services. However, there is scope to improve many of the processes of care it purports to support, particularly the provision of a more effective interface and the protection of the vulnerable.
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http://dx.doi.org/10.1055/s-0038-1641202DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6115222PMC
August 2018

Effect of Seasonal Variation on Clinical Outcome in Patients with Chronic Conditions: Analysis of the Commonwealth Scientific and Industrial Research Organization (CSIRO) National Telehealth Trial.

JMIR Med Inform 2018 Mar 16;6(1):e16. Epub 2018 Mar 16.

Biomedical Systems Research Laboratory, University of New South Wales, Kensington, Australia.

Background: Seasonal variation has an impact on the hospitalization rate of patients with a range of cardiovascular diseases, including myocardial infarction and angina. This paper presents findings on the influence of seasonal variation on the results of a recently completed national trial of home telemonitoring of patients with chronic conditions, carried out at five locations along the east coast of Australia.

Objective: The aim is to evaluate the effect of the seasonal timing of hospital admission and length of stay on clinical outcome of a home telemonitoring trial involving patients (age: mean 72.2, SD 9.4 years) with chronic conditions (chronic obstructive pulmonary disease coronary artery disease, hypertensive diseases, congestive heart failure, diabetes, or asthma) and to explore methods of minimizing the influence of seasonal variations in the analysis of the effect of at-home telemonitoring on the number of hospital admissions and length of stay (LOS).

Methods: Patients were selected from a hospital list of eligible patients living with a range of chronic conditions. Each test patient was case matched with at least one control patient. A total of 114 test patients and 173 control patients were available in this trial. However, of the 287 patients, we only considered patients who had one or more admissions in the years from 2010 to 2012. Three different groups were analyzed separately because of substantially different climates: (1) Queensland, (2) Australian Capital Territory and Victoria, and (3) Tasmania. Time series data were analyzed using linear regression for a period of 3 years before the intervention to obtain an average seasonal variation pattern. A novel method that can reduce the impact of seasonal variation on the rate of hospitalization and LOS was used in the analysis of the outcome variables of the at-home telemonitoring trial.

Results: Test patients were monitored for a mean 481 (SD 77) days with 87% (53/61) of patients monitored for more than 12 months. Trends in seasonal variations were obtained from 3 years' of hospitalization data before intervention for the Queensland, Tasmania, and Australian Capital Territory and Victoria subgroups, respectively. The maximum deviation from baseline trends for LOS was 101.7% (SD 42.2%), 60.6% (SD 36.4%), and 158.3% (SD 68.1%). However, by synchronizing outcomes to the start date of intervention, the impact of seasonal variations was minimized to a maximum of 9.5% (SD 7.7%), thus improving the accuracy of the clinical outcomes reported.

Conclusions: Seasonal variations have a significant effect on the rate of hospital admission and LOS in patients with chronic conditions. However, the impact of seasonal variation on clinical outcomes (rate of admissions, number of hospital admissions, and LOS) of at-home telemonitoring can be attenuated by synchronizing the analysis of outcomes to the commencement dates for the telemonitoring of vital signs.

Trial Registration: Australian New Zealand Clinical Trial Registry ACTRN12613000635763; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364030&isReview=true (Archived by WebCite at http://www.webcitation.org/ 6xLPv9QDb).
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http://dx.doi.org/10.2196/medinform.9680DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5878365PMC
March 2018

Global eHealth, Social Business and Citizen Engagement: A Natural Convergence?

Stud Health Technol Inform 2017 ;245:773-777

UNSW Medicine School of Public Health & Community Medicine (including WHO Collaborating Centre on eHealth & Yunus Social Business Health Hub), Randwick, NSW, Australia.

This paper draws on the vision, mission and experience with the WHO Collaborating Centre on eHealth (WHOCC-eHealth) and Yunus Social Business Health Hub (YSBHH) based at UNSW Australia, and the Asia electronic Health Information Network (AeHIN). Global eHealth aims to provide equitable access to ICT and health care, particularly to the poor, vulnerable and disadvantaged. Social business aims to solve social and economic problem. Its best known product is microcredit financial services for the poor which are small loans that enable them to "produce something, sell something, earn something to develop self-reliance and a life of dignity". Citizen engagement and community participation is integral to both constructs within the context of global partnerships for Integrated People-Centred Health Services (IPCHS) and Sustainable Development Goals (SDGs). The eHealth dimension is consumer heath informatics, social media, mHealth and the Internet of Things. The convergence is multidimensional, mutually beneficial and requires good governance and leadership.
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June 2018

Barriers to optimal screening and vaccination of hepatitis B contacts: a survey of general practitioners in NSW, Australia.

Public Health Res Pract 2017 12 7;27(5). Epub 2017 Dec 7.

Public Health Unit, Sydney Local Health District, NSW, Australia.

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http://dx.doi.org/10.17061/phrp2751749DOI Listing
December 2017