Gestational Diabetes Mellitus (GDM) increases the risk of type 2 diabetes. A register can be used to follow-up high risk women for early intervention to prevent progression to type 2 diabetes. We ...evaluate the performance of the world's first national gestational diabetes register.
Observational study that used data linkage to merge: (1) pathology data from the Australian states of Victoria (VIC) and South Australia (SA); (2) birth records from the Consultative Council on Obstetric and Paediatric Mortality and Morbidity (CCOPMM, VIC) and the South Australian Perinatal Statistics Collection (SAPSC, SA); (3) GDM and type 2 diabetes register data from the National Gestational Diabetes Register (NGDR). All pregnancies registered on CCOPMM and SAPSC for 2012 and 2013 were included-other data back to 2008 were used to support the analyses. Rates of screening for GDM, rates of registration on the NGDR, and rates of follow-up laboratory screening for type 2 diabetes are reported.
Estimated GDM screening rates were 86% in SA and 97% in VIC. Rates of registration on the NGDR ranged from 73% in SA (2013) to 91% in VIC (2013). During the study period rates of screening at six weeks postpartum ranged from 43% in SA (2012) to 58% in VIC (2013). There was little evidence of recall letters resulting in screening 12 months follow-up.
GDM Screening and NGDR registration was effective in Australia. Recall by mail-out to young mothers and their GP's for type 2 diabetes follow-up testing proved ineffective.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Summary
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.
Abstract Background Diagnosis can often be recorded in electronic medical records (EMRs) as free-text or using a term with a diagnosis code. Researchers, governments, and agencies, including ...organisations that deliver incentivised primary care quality improvement programs, frequently utilise coded data only and often ignore free-text entries. Diagnosis data are reported for population healthcare planning including resource allocation for patient care. This study sought to determine if diagnosis counts based on coded diagnosis data only, led to under-reporting of disease prevalence and if so, to what extent for six common or important chronic diseases. Methods This cross-sectional data quality study used de-identified EMR data from 84 general practices in Victoria, Australia. Data represented 456,125 patients who attended one of the general practices three or more times in two years between January 2021 and December 2022. We reviewed the percentage and proportional difference between patient counts of coded diagnosis entries alone and patient counts of clinically validated free-text entries for asthma, chronic kidney disease, chronic obstructive pulmonary disease, dementia, type 1 diabetes and type 2 diabetes. Results Undercounts were evident in all six diagnoses when using coded diagnoses alone (2.57–36.72% undercount), of these, five were statistically significant. Overall, 26.4% of all patient diagnoses had not been coded. There was high variation between practices in recording of coded diagnoses, but coding for type 2 diabetes was well captured by most practices. Conclusion In Australia clinical decision support and the reporting of aggregated patient diagnosis data to government that relies on coded diagnoses can lead to significant underreporting of diagnoses compared to counts that also incorporate clinically validated free-text diagnoses. Diagnosis underreporting can impact on population health, healthcare planning, resource allocation, and patient care. We propose the use of phenotypes derived from clinically validated text entries to enhance the accuracy of diagnosis and disease reporting. There are existing technologies and collaborations from which to build trusted mechanisms to provide greater reliability of general practice EMR data used for secondary purposes.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Background
Medicines are the most frequent health care intervention type; their safe use provides significant benefits, but inappropriate use can cause harm. Systemic primary care approaches ...can manage serious medication‐related problems in a timely manner.
Objectives
ACTMed (ACTivating primary care for MEDicine safety) uses information technology and financial incentives to encourage pharmacists to work more closely with general practitioners to reduce the risk of harm, improve patients’ experience of care, streamline workflows, and increase the efficiency of medical care.
Methods and analysis
The stepped wedge cluster randomised trial in 42 Queensland primary care practices will assess the effectiveness of the ACTMed intervention. The primary outcome will be the proportion of people at risk of serious medication‐related problems — patients with atrial fibrillation, heart failure, cardiovascular disease, type 2 diabetes, or asthma or chronic obstructive pulmonary disease — who experience such problems. We will also estimate the cost per averted serious medication‐related problem and the cost per averted potentially preventable medication‐related hospitalisation.
Ethics approval
The University of Queensland Human Research Ethics Committee approved the pilot (2021/HE002189) and trial phases of the ACTMed study (2022/HE002136). Access to Patron data was granted by the Patron Data Governance Committee (PAT052ACTMed). Access to linked hospitalisations and deaths data are subject to
Public Health Act
approval (pending).
Dissemination of findings
A comprehensive dissemination plan will be co‐developed by the researchers, the ACTMed steering committee and consumer advisory group, project partners, and trial site representatives. Aboriginal and Torres Strait Islander communities will be supported in leading community‐level dissemination.
Trial registration
Australian New Zealand Clinical Trials Registry (pilot: ACTRN12622000595718; 21 April 2022; full trial: ACTRN12622000574741; 14 April 2022).
•An automated de-identification tool is needed to access Australian clinical notes.•The solution must be suitable for de-identification prior to transfer of data.•The suitability of existing NLP ...tools for general practice progress notes is unknown.•Four tools were evaluated for their performance and adaptability to real-world use.•One rule-based tool that uses statistical modelling stood out as a viable solution.
Digitized patient progress notes from general practice represent a significant resource for clinical and public health research but cannot feasibly and ethically be used for these purposes without automated de-identification. Internationally, several open-source natural language processing tools have been developed, however, given wide variations in clinical documentation practices, these cannot be utilized without appropriate review. We evaluated the performance of four de-identification tools and assessed their suitability for customization to Australian general practice progress notes.
Four tools were selected: three rule-based (HMS Scrubber, MIT De-id, Philter) and one machine learning (MIST). 300 patient progress notes from three general practice clinics were manually annotated with personally identifying information. We conducted a pairwise comparison between the manual annotations and patient identifiers automatically detected by each tool, measuring recall (sensitivity), precision (positive predictive value), f1-score (harmonic mean of precision and recall), and f2-score (weighs recall 2x higher than precision). Error analysis was also conducted to better understand each tool’s structure and performance.
Manual annotation detected 701 identifiers in seven categories. The rule-based tools detected identifiers in six categories and MIST in three. Philter achieved the highest aggregate recall (67%) and the highest recall for NAME (87%). HMS Scrubber achieved the highest recall for DATE (94%) and all tools performed poorly on LOCATION. MIST achieved the highest precision for NAME and DATE while also achieving similar recall to the rule-based tools for DATE and highest recall for LOCATION. Philter had the lowest aggregate precision (37%), however preliminary adjustments of its rules and dictionaries showed a substantial reduction in false positives.
Existing off-the-shelf solutions for automated de-identification of clinical text are not immediately suitable for our context without modification. Philter is the most promising candidate due to its high recall and flexibility however will require extensive revising of its pattern matching rules and dictionaries.
In Australia, as a result of the distributed, often private nature of health provision, tight privacy legislation, even tighter organizational policies, access to data covering the whole patient ...journey of care is a common aspiration that has been almost impossible to achieve. Access to primary care data in a manner that is record-linkable has been a particular challenge. Since 2006 The University of Melbourne has been developing GRHANITE™ Middleware and GRHANITE™ Data Linkage technologies designed to overcome these barriers. With over 10% of Australian primary care data now being routinely extracted utilising this technology, we believe the principal technical challenges have now been overcome. We believe this technology to be at the forefront ethically of providing data for research. This poster describes the principal issues involved and the approaches taken in the technical solution underpinning GRHANITE™.
Intensive insulin treatment effectively delays the onset and slows the progression of microvascular complications in insulin-dependent diabetes mellitus (IDDM). Variable adherence to insulin ...treatment is thought to contribute to poor glycaemic control, diabetic ketoacidosis, and brittle diabetes in adolescents and young adults with IDDM. We assessed the association between the prescribed insulin dose and the amount dispensed from all community pharmacies with the Diabetes Audit and Research in Tayside Scotland (DARTS) database.
We studied 89 patients, mean age 16 (SD 7) years, diabetes duration 8 (4) years, and glycosylated haemoglobin (HbA
1c) 8·4 (1·9)%, who attended a teaching hospital paediatric or young-adult diabetes clinic in 1993 and 1994. The medically recommended insulin dose and cumulative volume of insulin prescriptions supplied were used to calculate the days of maximum possible insulin coverage per annum, expressed as the adherence index. Associations between glycaemic control (HbA
1c), episodes of diabetic ketoacidosis, and all hospital admissions for acute complications and the adherence index were modelled.
Insulin was prescribed at 48 (19) IU/day and mean insulin collected from pharmacies was 58 (25) IU/day. 25 (28%) of the 89 patients obtained less insulin than their prescribed dose (mean deficit 115 68; range 9–246 insulin days/annum). There was a significant inverse association between HbA
1c and the adherence index (R
2
=0·39; p<0·001). In the top quartile (HbA
1c≥10%), 14 (64%) of individuals had an adherence index suggestive of a missed dose of insulin (mean deficit 55 insulin days/annum). There were 36 admissions for complications related to diabetes. The adherence index was inversely related to hospital admissions for diabetic ketoacidosis (p<0·001) and all hospital admissions related to acute diabetes complications (p=0·008). The deterioration in glycaemic control observed in patients aged 10–20 years was associated with a significant reduction (p=0·01) in the adherence index.
We found direct evidence of poor compliance with insulin therapy in young patients with IDDM. We suggest that poor adherence to insulin treatment is the major factor that contributes to long-term poor glycaemic control and diabetic ketoacidosis in this age group.
New biomedical prevention interventions make the control or elimination of some blood-borne viruses (BBVs) and sexually transmissible infections (STIs) increasingly feasible. In response, the World ...Health Organization and governments around the world have established elimination targets and associated timelines. To monitor progress toward such targets, enhanced systems of data collection are required. This paper describes the Australian Collaboration for Coordinated Enhanced Sentinel Surveillance (ACCESS).
This study aims to establish a national surveillance network designed to monitor public health outcomes and evaluate the impact of strategies aimed at controlling BBVs and STIs.
ACCESS is a sentinel surveillance system comprising health services (sexual health clinics, general practice clinics, drug and alcohol services, community-led testing services, and hospital outpatient clinics) and pathology laboratories in each of Australia's 8 states and territories. Scoping was undertaken in each jurisdiction to identify sites that provide a significant volume of testing or management of BBVs or STIs or to see populations with particular risks for these infections ("priority populations"). Nationally, we identified 115 health services and 24 pathology laboratories as relevant to BBVs or STIs; purposive sampling was undertaken. As of March 2018, we had recruited 92.0% (104/113) of health services and 71% (17/24) of laboratories among those identified as relevant to ACCESS. ACCESS is based on the regular and automated extraction of deidentified patient data using specialized software called GRHANITE, which creates an anonymous unique identifier from patient details. This identifier allows anonymous linkage between and within participating sites, creating a national cohort to facilitate epidemiological monitoring and the evaluation of clinical and public health interventions.
Between 2009 and 2017, 1,171,658 individual patients attended a health service participating in ACCESS network comprising 7,992,241 consultations. Regarding those with unique BBV and STI-related health needs, ACCESS captured data on 366,441 young heterosexuals, 96,985 gay and bisexual men, and 21,598 people living with HIV.
ACCESS is a unique system with the ability to track efforts to control STIs and BBVs-including through the calculation of powerful epidemiological indicators-by identifying response gaps and facilitating the evaluation of programs and interventions. By anonymously linking patients between and within services and over time, ACCESS has exciting potential as a research and evaluation platform. Establishing a national health surveillance system requires close partnerships across the research, government, community, health, and technology sectors.
DERR1-10.2196/11028.
OBJECTIVE
There are few U.K. data on the incidence rates of amputation in diabetic subjects compared with the nondiabetic population.
RESEARCH DESIGN AND METHODS
We performed a historical cohort ...study of first lower-extremity amputations based in Tayside, Scotland (population 364,880) from 1 January 1993 to 31 December 1994. The Diabetes Audit and Research in Tayside Scotland (DARTS) database was used to identify a prevalence cohort of 7,079 diabetic patients on 1 January 1993. We estimated age-specific and standardized incidence rates of lower-limb amputations in the diabetic and nondiabetic cohorts. Results were compared with a previous study that evaluated lower-extremity amputations in diabetic patients in Tayside in 1980–1982.
RESULTS
There were 221 subjects who underwent a total of 258 nontraumatic amputations. Of the 221 subjects, 60 (27%) patients were diabetic (93% NIDDM), and 63% were first amputations. The median duration of diabetes was 6 years (range: newly diagnosed to 41 years). Nonhealing ulceration (31%) and gangrene (29%) were the two main indications for amputation in the diabetic subjects. Of the 161 nondiabetic subjects, 140 (80%) underwent first amputations. The adjusted incidences in the diabetic and nondiabetic groups were 248 and 20 per 100,000 person-years, respectively. Tayside patients with diabetes thus had a 12.3-fold risk of an amputation compared with nondiabetic residents (95% Cl 8.6–17.5). The estimated proportion of diabetic patients in the population rose from 0.81% in 1980–1982 to 1.94% in 1993–1994, whereas the absolute rate of amputation in diabetic subjects was unchanged from that in 1980–1982.
CONCLUSIONS
These population-based U.K. amputation data are similar to amputation rates in the U.S. Amputation rates appear to have decreased significantly since 1980–1982. The impact of diabetes education and prevention programs that target the processes leading to amputation can now be evaluated.
PDF
