Perceptions of primary care staff on a regional data quality intervention in Australian general practice: a qualitative study

The impact of eHealth use on general practice workload in the pre-COVID-19 era: a systematic review

BACKGROUND

In recent years, eHealth has received much attention as an opportunity to increase efficiency within healthcare organizations. Adoption of eHealth might consequently help to solve perceived health workforce challenges, including labor shortages and increasing workloads among primary care professionals, who serve as the first point of contact for healthcare in many countries. The purpose of this systematic review was to investigate the impact of general eHealth use and specific eHealth services use on general practice workload in the pre-COVID-19 era.

METHODS

The databases of CINAHL, Cochrane, Embase, IEEE Xplore, Medline ALL, PsycINFO, Web of Science, and Google Scholar were searched, using combinations of keywords including 'eHealth', 'workload', and 'general practice'. Data extraction and quality assessment of the included studies were independently performed by at least two reviewers. Publications were included for the period 2010 - 2020, before the start of the COVID-19 pandemic.

RESULTS

In total, 208 studies describing the impact of eHealth services use on general practice workload were identified. We found that two eHealth services were mainly investigated within this context, namely electronic health records and digital communication services, and that the largest share of the included studies used a qualitative study design. Overall, a small majority of the studies found that eHealth led to an increase in general practice workload. However, results differed between the various types of eHealth services, as a large share of the studies also reported a reduction or no change in workload.

CONCLUSIONS

The impact of eHealth services use on general practice workload is ambiguous. While a small majority of the effects indicated that eHealth increased workload in general practice, a large share of the effects also showed that eHealth use reduced workload or had no impact. These results do not imply a definitive conclusion, which underscores the need for further explanatory research. Various factors, including the study setting, system design, and the phase of implementation, may influence this impact and should be taken into account when general practices adopt new eHealth services.

STUDY REGISTRATION NUMBER

PROSPERO (International Prospective Register of Systematic Reviews) CRD42020199897; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=199897 .

Automating Electronic Health Record Data Quality Assessment

Information systems such as Electronic Health Record (EHR) systems are susceptible to data quality (DQ) issues. Given the growing importance of EHR data, there is an increasing demand for strategies and tools to help ensure that available data are fit for use. However, developing reliable data quality assessment (DQA) tools necessary for guiding and evaluating improvement efforts has remained a fundamental challenge. This review examines the state of research on operationalising EHR DQA, mainly automated tooling, and highlights necessary considerations for future implementations. We reviewed 1841 articles from PubMed, Web of Science, and Scopus published between 2011 and 2021. 23 DQA programs deployed in real-world settings to assess EHR data quality (n = 14), and a few experimental prototypes (n = 9), were identified. Many of these programs investigate completeness (n = 15) and value conformance (n = 12) quality dimensions and are backed by knowledge items gathered from domain experts (n = 9), literature reviews and existing DQ measurements (n = 3). A few DQA programs also explore the feasibility of using data-driven techniques to assess EHR data quality automatically. Overall, the automation of EHR DQA is gaining traction, but current efforts are fragmented and not backed by relevant theory. Existing programs also vary in scope, type of data supported, and how measurements are sourced. There is a need to standardise programs for assessing EHR data quality, as current evidence suggests their quality may be unknown.

Australian general practitioner perceptions to sharing clinical data for secondary use: a mixed method approach

OBJECTIVE

The potential for data collected in general practice to be linked and used to address health system challenges of maintaining quality care, accessibility and safety, including pandemic support, has led to an increased interest in public acceptability of data sharing, however practitioners have rarely been asked to share their opinions on the topic. This paper attempts to gain an understanding of general practitioner's perceptions on sharing routinely collected data for the purposes of healthcare planning and research. It also compares findings with data sharing perceptions in an international context.  MATERIALS AND METHODS: A mixed methods approach combining an initial online survey followed by face-to-face interviews (before and during COVID-19), designed to identify the barriers and facilitators to sharing data, were conducted on a cross sectional convenience sample of general practitioners across Western Australia (WA).

RESULTS

Eighty online surveys and ten face-to-face interviews with general practitioners were conducted from November 2020 - May 2021. Although respondents overwhelmingly identified the importance of population health research, their willingness to participate in data sharing programs was determined by a perception of trust associated with the organisation collecting and analysing shared data; a clearly defined purpose and process of collected data; including a governance structure providing confidence in the data sharing initiative simultaneously enabling a process of data sovereignty and autonomy.

DISCUSSION

Results indicate strong agreement around the importance of sharing patient's medical data for population and health research and planning. Concerns pertaining to lack of trust, governance and secondary use of data continue to be a setback to data sharing with implications for primary care business models being raised.

CONCLUSION

To further increase general practitioner's confidence in sharing their clinical data, efforts should be directed towards implementing a robust data governance structure with an emphasis on transparency and representative stakeholder inclusion as well as identifying the role of government and government funded organisations, as well as building trust with the entities collecting and analysing the data.

Identifying primary care datasets and perspectives on their secondary use: a survey of Australian data users and custodians

Background

Most people receive most of their health care in in Australia in primary care, yet researchers and policymakers have limited access to resulting clinical data. Widening access to primary care data and linking it with hospital or other data can contribute to research informing policy and provision of services and care; however, limitations of primary care data and barriers to access curtail its use. The Australian Health Research Alliance (AHRA) is seeking to build capacity in data-driven healthcare improvement; this study formed part of its workplan.

Methods

The study aimed to build capacity for data driven healthcare improvement through identifying primary care datasets in Australia available for secondary use and understand data quality frameworks being applied to them, and factors affecting national capacity for secondary use of primary care data from the perspectives of data custodians and users. Purposive and snowball sampling were used to disseminate a questionnaire and respondents were invited to contribute additional information via semi-structured interviews.

Results

Sixty-two respondents collectively named 106 datasets from eclectic sources, indicating a broad conceptualisation of what a primary care dataset available for secondary use is. The datasets were generated from multiple clinical software systems, using different data extraction tools, resulting in non-standardised data structures. Use of non-standard data quality frameworks were described by two-thirds of data custodians. Building trust between citizens, clinicians, third party data custodians and data end-users was considered by many to be a key enabler to improve primary care data quality and efficiencies related to secondary use. Trust building qualities included meaningful stakeholder engagement, transparency, strong leadership, shared vision, robust data security and data privacy protection. Resources to improve capacity for primary care data access and use were sought for data collection tool improvements, workforce upskilling and education, incentivising data collection and making data access more affordable.

Conclusions

The large number of identified Australian primary care related datasets suggests duplication of labour related to data collection, preparation and utilisation. Benefits of secondary use of primary care data were many, and strong national leadership is required to reach consensus on how to address limitations and barriers, for example accreditation of EMR clinical software systems and the adoption of agreed data and quality standards at all stages of the clinical and research data-use lifecycle. The study informed the workplan of AHRA’s Transformational Data Collaboration to improve partner engagement and use of clinical data for research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-01830-9.

Undertaking general practice quality improvement to improve cancer screening - a thematic analysis of provider experiences

Background

Cancer is a major cause of illness and death, and its incidence and mortality can be reduced through effective screening. In order to improve below target screening rates in one region of Australia, the local Primary Health Network supported local general practices to implement a range of quality improvement initiatives.

Methods

We used a qualitative approach and interviewed 18 general practice staff and five Primary Health Network staff and contractors to understand their experiences with these quality improvement initiatives.

Results

In a thematic analysis, we identified four key themes related to program set-up and implementation; patient and community education and promotion; engaging patients and communities in screening; and general practice enhancement. Program roles were clear and understood, and the program received strong oversight and support. Practice staff felt supported and motivated. Information Technology was a challenge for many practices often requiring tailored assistance. Education provided by practices facilitated patient empowerment but practice staff noted difficulties engaging patients in screening. Practices were enhanced though strong leadership and teamwork and practice learning activities.

Conclusions

The tailored evidence-based quality improvement initiatives were considered effective in supporting general practices to increase their cancer screening. Key facilitators reported by participants included use of Plan-Do-Study-Act cycles, enhanced data entry and audit capacity, effective recall and reminder systems and maintaining staff motivation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-021-01581-y.

Clinical researchers' lived experiences with data quality monitoring in clinical trials: a qualitative study

BACKGROUND

Fundamental to the success of clinical research that involves human participants is the quality of the data that is generated. To ensure data quality, clinical trials must comply with the Good Clinical Practice guideline which recommends data monitoring. To date, the guideline is broad, requires technology for enforcement, follows strict industry standards, mostly designed for drug-registration trials and based on informal consensus. It is also unknown what challenges clinical trials and researchers face in implementing data monitoring procedures. Thus, this study aimed to describe researcher experiences with data quality monitoring in clinical trials.

METHODS

We conducted semi-structured telephone interviews following a guided-phenomenological approach. Participants were recruited from the Australian and New Zealand Clinical Trials Registry and were researchers affiliated with a listed clinical study. Each transcript was analysed with inductive thematic analysis before thematic categorisation of themes from all transcripts. Primary, secondary and subthemes were categorised according to the emerging relationships.

RESULTS

Data saturation were reached after interviewing seven participants. Five primary themes, two secondary themes and 21 subthemes in relation to data quality monitoring emerged from the data. The five primary themes included: education and training, ways of working, working with technology, working with data, and working within regulatory requirements. The primary theme 'education and training' influenced the other four primary themes. While 'working with technology' influenced the 'way of working'. All other themes had reciprocal relationships. There was no relationship reported between 'working within regulatory requirements' and 'working with technology'. The researchers experienced challenges in meeting regulatory requirements, using technology and fostering working relationships for data quality monitoring.

CONCLUSION

Clinical trials implemented a variety of data quality monitoring procedures tailored to their situation and study context. Standardised frameworks that are accessible to all types of clinical trials are needed with an emphasis on education and training.

Implementation of the e-SUS Primary Care system: Impact on the routine of Primary Health Care professionals

OBJECTIVE

to understand how the implementation of the e-SUS Primary Care system has been processed and its impact on the daily life of the health teams.

METHOD

a qualitative research study, conducted in a municipality in the inland of the state of São Paulo with professionals who work in Primary Health Care and use the e-SUS Primary Care system as a work tool. Semi-structured interviews and thematic data analysis were used with Kotter's three-phase approach.

RESULTS

a total of 17 professionals, nurses, physicians, dentists and community agents were interviewed. The implementation of e-SUS Primary Care and its impact on the daily life of health teams were understood in terms of mandatory implementation; weaknesses for implementation, such as absence of material resources and implicit imposition for the use of the system; fragile training for deployment and learning from experience.

CONCLUSION

a harmful incentive process was observed, conducted from the perspective of institutional pressure, use of the system to justify the work performed and, on the other hand, there was the creation of collaborative learning mechanisms between the teams.

Evaluating the Implementation of a Pilot Quality Improvement Program to Support Appropriate Antimicrobial Prescribing in General Practice

Inappropriate antimicrobial prescribing contributes to increasing antimicrobial resistance. An antimicrobial stewardship (AMS) program in the form of quality improvement activities that included audit and feedback, clinical decision support and education was developed to help optimise prescribing in general practice. The aim of this study was to evaluate the implementation of this program (Guidance GP) in three general practices in Melbourne, Australia, between November 2019 and August 2020. Thirty-one general practitioners (GPs) participated in the program, with 11 GPs and three practice managers participating in follow-up focus groups and interviews to explore the acceptability and feasibility of the program. Our findings showed that the quality improvement activities were acceptable to GPs, if they accurately fit GPs' decision-making process and workflow. It was also important that they provided clinically meaningful information in the form of audit and feedback to GPs. The time needed to coordinate the program, and costs to implement the program were some of the potential barriers identified. Facilitators of success were a "whole of practice" approach with enthusiastic GPs and practice staff, and an identified practice champion. The findings of this research will inform implementation strategies for both the Guidance GP program and AMS programs more broadly in Australian general practice, which will be critical for general practice participation and engagement.

Data quality in primary care, Scotland

BACKGROUND AND AIMS

This project explores primary care data quality (DQ) across Scotland.

METHODS AND RESULTS

A survey was sent to primary care staff in winter 2019. National data regarding Quality and Outcomes Framework (QOF) performance indicators and the GP software system used was obtained, analysed with T-tests and Chi-squared tests. Overall QOF performance with non-financial incentives from 918 practices was 77%. There was no significant difference with overall QOF performance against GP system (p = 0.46) or if the practice had a coder (p = 0.06). From the survey, search systems that make it hard to search for particular codes was the most important barrier to DQ; 61% of respondents (n = 491) felt there was particular information GPs should code, 16% of respondents stated that hospital discharge letters generally include corresponding codes and 9% for outpatient correspondence; 43% stated their practice had undertaken steps to improve DQ, training was the most common initiative, followed by workflow optimisation, dedicated coder(s), audit, guidelines and using code lists; 80% (n = 475) of respondents had received training in using their GP system, an average of eight years ago.

CONCLUSION

Obtaining improved GP systems, training, agreeing what GPs should code and improving transfer of data should be explored.

Improving quality and use of routine health information system data in low- and middle-income countries: A scoping review

BACKGROUND

A routine health information system is one of the essential components of a health system. Interventions to improve routine health information system data quality and use for decision-making in low- and middle-income countries differ in design, methods, and scope. There have been limited efforts to synthesise the knowledge across the currently available intervention studies. Thus, this scoping review synthesised published results from interventions that aimed at improving data quality and use in routine health information systems in low- and middle-income countries.

METHOD

We included articles on intervention studies that aimed to improve data quality and use within routine health information systems in low- and middle-income countries, published in English from January 2008 to February 2020. We searched the literature in the databases Medline/PubMed, Web of Science, Embase, and Global Health. After a meticulous screening, we identified 20 articles on data quality and 16 on data use. We prepared and presented the results as a narrative.

RESULTS

Most of the studies were from Sub-Saharan Africa and designed as case studies. Interventions enhancing the quality of data targeted health facilities and staff within districts, and district health managers for improved data use. Combinations of technology enhancement along with capacity building activities, and data quality assessment and feedback system were found useful in improving data quality. Interventions facilitating data availability combined with technology enhancement increased the use of data for planning.

CONCLUSION

The studies in this scoping review showed that a combination of interventions, addressing both behavioural and technical factors, improved data quality and use. Interventions addressing organisational factors were non-existent, but these factors were reported to pose challenges to the implementation and performance of reported interventions.

Gathering data for decisions: best practice use of primary care electronic records for research

In Australia, there is limited use of primary health care data for research and for data linkage between health care settings. This puts Australia behind many developed countries. In addition, without use of primary health care data for research, knowledge about patients’ journeys through the health care system is limited.

There is growing momentum to establish “big data” repositories of primary care clinical data to enable data linkage, primary care and population health research, and quality assurance activities. However, little research has been conducted on the general public's and practitioners’ concerns about secondary use of electronic health records in Australia.

International studies have identified barriers to use of general practice patient records for research. These include legal, technical, ethical, social and resource‐related issues. Examples include concerns about privacy protection, data security, data custodians and the motives for collecting data, as well as a lack of incentives for general practitioners to share data.

Addressing barriers may help define good practices for appropriate use of health data for research. Any model for general practice data sharing for research should be underpinned by transparency and a strong legal, ethical, governance and data security framework.

Mechanisms to collect electronic medical records in ethical, secure and privacy‐controlled ways are available.

Before the potential benefits of health‐related data research can be realised, Australians should be well informed of the risks and benefits so that the necessary social licence can be generated to support such endeavours.

QUality improvement in primary care to prevent hospitalisations and improve Effectiveness and efficiency of care for people Living with coronary heart disease (QUEL): protocol for a 24-month cluster randomised controlled trial in primary care

Background

Cardiovascular disease (CVD), including coronary heart disease (CHD) and stroke, is the leading cause of death and disability globally. A large proportion of mortality occurs in people with prior CHD and effective and scalable strategies are needed to prevent associated deaths and hospitalisations. The aim of this study is to determine if a practice-level collaborative quality improvement program, focused on patients with CHD, reduces the rate of unplanned CVD hospitalisations and major adverse cardiovascular events, and increases the proportion of patients achieving risk factor targets at 24 months.

Methods

Cluster randomised controlled trial (cRCT) to evaluate the effectiveness of a primary care quality improvement program in 50 primary care practices (n~ 10,000 patients) with 24-month follow-up. Eligible practices will be randomised (1:1) to participate in either the intervention (collaborative quality improvement program) or control (standard care) regimens. Outcomes will be assessed based on randomised allocation, according to intention-to-treat. The primary outcome is the proportion of patients with unplanned CVD hospitalisations at 2 years. Secondary outcomes are proportion of patients with major adverse cardiovascular events, proportion of patients who received prescriptions for guideline-recommended medicines, proportion of patients achieving national risk factor targets and proportion with a chronic disease management plan or review. Differences in the proportion of patients who are hospitalised (as well as binary secondary outcomes) will be analysed using log-binomial regression or robust Poisson regression, if necessary.

Discussion

Despite extensive research with surrogate outcomes, to the authors’ knowledge, this is the first randomised controlled trial to evaluate the effectiveness of a data-driven collaborative quality improvement intervention on hospitalisations, CVD events and cardiovascular risk amongst patients with CHD in the primary care setting. The use of data linkage for collection of outcomes will enable evaluation of this potentially efficient strategy for improving management of risk and outcomes for people with heart disease.

Trial registration

Australian New Zealand Clinical Trials Registry (ANZCTR) number ACTRN12619001790134 (dated 20th December 2019).

An intervention model with self-assessment and subsequent multi-professional review might be effective and feasible to improve drug safety in primary healthcare. A survey-based evaluation of SÄKLÄK2

RATIONALE, AIMS, AND OBJECTIVES

Drug-related morbidity is common, which results in suffering for the patients and a high cost to society. SÄKLÄK2 is a multi-professional intervention model aiming at improving drug safety in primary health care. The objective of this study was to elucidate the perceptions of the participants' regarding the efficiency of the intervention and the feasibility to introduce this model widely.

METHOD

SÄKLÄK2 is a multi-professional intervention model in primary health care in Sweden that consisted of self-assessment, peer-review, written feedback, and agreements for change. Web-based surveys were sent to both the management of participating primary health care centres (PHC) and to reviewers. The participating PHCs were fairly well-staffed and had a high interest in improvement work. Descriptive analysis and content analysis was used.

RESULTS

For the PHC management, the following categories were formed: Comprehensive project, Time-consuming, Multi-professional character, Relevant action agreements, and Feasible to implement. For the reviewers, the following categories were formed: Multi-professional character, Relevant action agreements, Feasible to implement, Useful self-assessment questionnaire, and Valuable visit at the PHC. There was a high degree of consistency between the PHC management and the reviewers' answers, especially regarding the efficiency of the model to improve drug safety and the feasibility to implement it on a broad front.

CONCLUSION

SÄKLÄK2, a model with self-assessment, peer review, written feedback, and the formation of action agreements was considered by both the participating heads of the PHC centres and the reviewers to be effective to improve drug safety in primary health care. Though time-consuming, this multi-professional model was considered to be feasible to implement on a broad front and might thereby be one way of working with quality improvement regarding drug safety.

Barriers and facilitators to data quality of electronic health records used for clinical research in China: a qualitative study

OBJECTIVES

There is an increasing trend in the use of electronic health records (EHRs) for clinical research. However, more knowledge is needed on how to assure and improve data quality. This study aimed to explore healthcare professionals' experiences and perceptions of barriers and facilitators of data quality of EHR-based studies in the Chinese context.

SETTING

Four tertiary hospitals in Beijing, China.

PARTICIPANTS

Nineteen healthcare professionals with experience in using EHR data for clinical research participated in the study.

METHODS

A qualitative study based on face-to-face semistructured interviews was conducted from March to July 2018. The interviews were audiorecorded and transcribed verbatim. Data analysis was performed using the inductive thematic analysis approach.

RESULTS

The main themes included factors related to healthcare systems, clinical documentation, EHR systems and researchers. The perceived barriers to data quality included heavy workload, staff rotations, lack of detailed information for specific research, variations in terminology, limited retrieval capabilities, large amounts of unstructured data, challenges with patient identification and matching, problems with data extraction and unfamiliar with data quality assessment. To improve data quality, suggestions from participants included: better staff training, providing monetary incentives, performing daily data verification, improving software functionality and coding structures as well as enhancing multidisciplinary cooperation.

CONCLUSIONS

These results provide a basis to begin to address current barriers and ultimately to improve validity and generalisability of research findings in China.

What attributions do Australian high-performing general practices make for their success? Applying the clinical microsystems framework: a qualitative study

OBJECTIVES

To identify the success attributions of high-performing Australian general practices and the enablers and barriers they envisage for practices wishing to emulate them.

DESIGN

Qualitative study using semi-structured interviews and content analysis of the data. Responses were recorded, transcribed verbatim and coded according to success characteristics of high-performing clinical microsystems.

SETTING

Primary healthcare with the participating general practices representing all Australian states and territories, and representing metropolitan and rural locations.

PARTICIPANTS

Twenty-two general practices identified as high performing via a number of success criteria. The 52 participants were 19 general practitioners, 18 practice managers and 15 practice nurses.

RESULTS

Participants most frequently attributed success to the interdependence of the team members, patient-focused care and leadership of the practice. They most often signalled practice leadership, team interdependence and staff focus as enablers that other organisations would need to emulate their success. They most frequently identified barriers that might be encountered in the form of potential deficits or limitations in practice leadership, staff focus and mesosystem support.

CONCLUSIONS

Practice leaders need to empower their teams to take action through providing inclusive leadership that facilitates team interdependence. Mesosystem support for quality improvement in general practice should focus on enabling this leadership and team building, thereby ensuring improvement efforts are converted into effective healthcare provision.

Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016

BACKGROUND

As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.

METHODS

We estimated prevalence and incidence for 328 diseases and injuries and 2982 sequelae, their non-fatal consequences. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between incidence, prevalence, remission, and cause of death rates for each condition. For some causes, we used alternative modelling strategies if incidence or prevalence needed to be derived from other data. YLDs were estimated as the product of prevalence and a disability weight for all mutually exclusive sequelae, corrected for comorbidity and aggregated to cause level. We updated the Socio-demographic Index (SDI), a summary indicator of income per capita, years of schooling, and total fertility rate. GBD 2016 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).

FINDINGS

Globally, low back pain, migraine, age-related and other hearing loss, iron-deficiency anaemia, and major depressive disorder were the five leading causes of YLDs in 2016, contributing 57·6 million (95% uncertainty interval [UI] 40·8-75·9 million [7·2%, 6·0-8·3]), 45·1 million (29·0-62·8 million [5·6%, 4·0-7·2]), 36·3 million (25·3-50·9 million [4·5%, 3·8-5·3]), 34·7 million (23·0-49·6 million [4·3%, 3·5-5·2]), and 34·1 million (23·5-46·0 million [4·2%, 3·2-5·3]) of total YLDs, respectively. Age-standardised rates of YLDs for all causes combined decreased between 1990 and 2016 by 2·7% (95% UI 2·3-3·1). Despite mostly stagnant age-standardised rates, the absolute number of YLDs from non-communicable diseases has been growing rapidly across all SDI quintiles, partly because of population growth, but also the ageing of populations. The largest absolute increases in total numbers of YLDs globally were between the ages of 40 and 69 years. Age-standardised YLD rates for all conditions combined were 10·4% (95% UI 9·0-11·8) higher in women than in men. Iron-deficiency anaemia, migraine, Alzheimer's disease and other dementias, major depressive disorder, anxiety, and all musculoskeletal disorders apart from gout were the main conditions contributing to higher YLD rates in women. Men had higher age-standardised rates of substance use disorders, diabetes, cardiovascular diseases, cancers, and all injuries apart from sexual violence. Globally, we noted much less geographical variation in disability than has been documented for premature mortality. In 2016, there was a less than two times difference in age-standardised YLD rates for all causes between the location with the lowest rate (China, 9201 YLDs per 100 000, 95% UI 6862-11943) and highest rate (Yemen, 14 774 YLDs per 100 000, 11 018-19 228).

INTERPRETATION

The decrease in death rates since 1990 for most causes has not been matched by a similar decline in age-standardised YLD rates. For many large causes, YLD rates have either been stagnant or have increased for some causes, such as diabetes. As populations are ageing, and the prevalence of disabling disease generally increases steeply with age, health systems will face increasing demand for services that are generally costlier than the interventions that have led to declines in mortality in childhood or for the major causes of mortality in adults. Up-to-date information about the trends of disease and how this varies between countries is essential to plan for an adequate health-system response.

FUNDING

Bill & Melinda Gates Foundation, and the National Institute on Aging and the National Institute of Mental Health of the National Institutes of Health.

Findings from the 2017 Yearbook Section on Health Information Management

Objectives: To summarize the recent literature and research and present a selection of the best papers published in 2016 in the field of Health Information Management (HIM). Methods: A systematic review of the literature for the IMIA Yearbook HIM section was performed by the two section editors with the help of a medical librarian. We searched bibliographic databases for HIM-related papers were searched using both MeSH headings and key words in titles and abstracts. A shortlist of candidate best papers was first selected by section editors before being peer-reviewed by independent external reviewers. Results: The five papers selected as 'Best Papers' illustrate a variety of themes, include authors from a variety of countries, and were published in some of the best journals in the field. The themes of the five best papers include health information exchange, personal health records, patient engagement, data quality, and e-quality measures. Conclusions: The discipline of Health Information Management is increasingly becoming allied with the field of Biomedical Informatics in that both disciplines have interests in common. Traditional HIM areas of expertise (in the pre-electronic health record world), such as coding and privacy and security of health information, are necessary for the electronic exchange and secondary use of health information. With the changes in healthcare delivery brought by the use of electronic health records, addressing issues of information governance is essential. This synopsis discusses these key issues at the intersection of HIM and informatics, examines the potential challenges, and points the way for best practices, future research, and public policy considerations and directions.