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)

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

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.

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Recent unpublished data from CMDHB show a 6% prevalence with an 85% screening rate for GDM.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.

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.

Clinical Registries & Uses Register / Registry Clinical (+quality) / disease / patient registry etc.

Repository of individuals with a certain condition/characteristic

Ease of access to important infoTrack outcomes & processesLongitudinal history of correspondences & interventionsPrompt / feedback to participants and providers

Supporting clinical practice◦ Screening, risk prediction, intervention/recall, safety monitoring

Clinical quality improvement◦ Organisations, clinicians, policy makers

Research & education

Main ConsiderationsPrivacy / 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.

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

Regi

stry

Dire

cted

Golden principle: Minimal data entry, Maximal reuse!

Technical DevelopmentUsed 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

The Dataset

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

Improved Health

Outcomes

Education

ResearchReduce Disparities

Collaboration

Koray Atalagk.atalag@auckland.ac.nz

Vice Chair HL7 New ZealandopenEHR Localisation Program Leader

Health Information Standards Organisation (HISO) Committee MemberNHITB Sector Architects Group Member