This is the prezo I have at the Australasian Long-Term Conditions Conference in Auckland on 30 Jul 2014. Focus was on prevention and management of long term conditions and use of clinical registries has proven to be effective. This is a pilot project at a large healthcare provider organisation in Auckland (Counties Manukau District Health Board) where we used the full openEHR stack to build web based front end with the OceanEHR backend.
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Development of the Gestational Diabetes Registry at CMDHB (New Zealand) using openEHR
1. Gestational Diabetes Registry
Development
in CMDHB
Dr. Koray Atalag MD, PhD, FACHI (National Institute for Health Innovation)
Dr. Carl Eagleton MBChB, FRACP (Counties Manukau District Health Board)
Karen Pickering (Diabetes Projects Trust)
2. Aims
100% successful screening of women for type 2
diabetes (T2DM) within 3 months after a pregnancy
with GDM
Annual screening of all women for new onset T2DM
Early warning to healthcare providers (GPs,
Maori/Pacific Health, others) about GDM history in
subsequent pregnancies
3. Gestational Diabetes Mellitus (GDM)
GDM is characterised by glucose intolerance with
onset or first recognition during pregnancy & is
identified by an oral glucose tolerance test (OGTT)
A repeat OGTT performed 6 weeks post-partum
checks for resolution
◦ If normal, an annual fasting glucose or glycosylated
haemoglobin (HbA1c) screening test is recommended for
T2DM, according to New Zealand (NZ) guidelines.
4. The number of deliveries at CMDHB for women with GDM almost
doubled in the last six years to 408 in 2011/12
Maori and Pacific women represent the largest ethnic cohort in
CMDHB service and Maori women have more high risk pregnancies
than non-Maori
Recent unpublished data from CMDHB show a 6% prevalence with
an 85% screening rate for GDM.
GDM has long-term, serious consequences. A study in NZ found
19% of 110 women with GDM developed T2DM after a mean follow
up of only 2.4 years. Women with a history of GDM have an
increased prevalence of CVD risk factors such as hypertension,
dyslipidaemia, and microalbuminuria, and of developing CVD.
Furthermore these women are highly likely to develop GDM in a
subsequent pregnancy.
Children born to women with GDM have been found to have
increased rates of obesity and hypertension as adolescents.
Children of women with unrecognised type 2 diabetes have
increased risk for foetal malformation.
5. Opportunities & Motivation for the Registry
Long term consequences can be prevented by regular
screening for early detection of T2DM or high CVD risk
◦ CMDHB found 20% of women with a history of GDM were not
follow-up tested in a 4 year period; (37% for 2 year period)
◦ Sending out reminders improve adherence / better compliance
with screening recommendations
Risk of developing T2DM can be substantially reduced
by early identification of women at high risk + targeted
lifestyle & pharmacological interventions
Registry can also be used to drive clinical quality
improvement and enhance patient safety
◦ by identifying variations in processes and clinical outcomes.
6. Clinical Registries & Uses
Register / Registry
Clinical (+quality) / disease / patient registry etc.
Repository of individuals with a certain condition/characteristic
Ease of access to important info
Track outcomes & processes
Longitudinal history of correspondences & interventions
Prompt / feedback to participants and providers
Supporting clinical practice
◦ Screening, risk prediction, intervention/recall, safety monitoring
Clinical quality improvement
◦ Organisations, clinicians, policy makers
Research & education
7. Main Considerations
Privacy / Confidentiality
◦ Privacy Act 1993 and Health Information Privacy Code 1994 (“HIPC”)
◦ Recent changes to offshore hosting
◦ Connected Health secure network
Security / Recovery / Availability
◦ Univ. of Auckland’s secure IT infrastructure
IT standards & components
◦ W3C, Microsoft Net, SQL Server, Angular JS
◦ HISO Interoperability Reference Architecture
◦ openEHR
Existing systems
◦ CMDHB: Maternity CIS & others
◦ Regional/National: MoH datamart? VDR, PMS, Shared Care etc.
8. GDM Registry Pathway
Entry
• Referral from primary care with a diagnosis of GDM
Education
• Attendance at Group Session
• Registry information supplied
Consent
• Attendance at DiP Clinic
• Consent obtained and entry into the registry
Postpartum
• 6 week OGTT request or 3 month HbA1c
• GP & Patient advised of results
Annual
• Annual HbA1c with copy to primary care
• GP & Patient advised of results
Next time
• Positive pregnancy test detected in Testsafe
• Requesting healthcare provider advised of Diabetes history by the Registry
RegistryDirected
9. Golden principle: Minimal data entry, Maximal reuse!
Technical Development
Used an international (and HISO) standard:
◦ Consistent dataset
◦ Interoperability / integration
◦ Manage change over time
Used a Web-based data set development tool to
review & finalise
Automatically converted dataset into “software
code” [domain objects]
Built on NIHI’s generic clinical data management
framework
14. Conclusions
Currently in pilot deployment & evaluation phase
No need for Regional Ethics Approval if ‘part of clinical service’
◦ Still issues around data feeds (e.g. TestSafe data in DHB systems)
Model based Dataset development
◦ Very effective and easy to engage clinicians but require tooling and
editorial effort & skills (=cost)
Fully-fledged EHR underpinning Registry
◦ Standards based, scientific rigour in data representation but hard!
Getting ‘information right’ is crucial!
◦ Invest in defining dataset properly, change is costly
◦ Alignment is hard and there’s no formal guidance There is no single
organisation or mechanism to ensure the Sector’s datasets are to be
aligned
