Building a dynamic web-based data capture system, as an eResearch tool, for Australia and New Zealand Neonatal Network

Jishan Dean, Elizabeth Sullivan

Perinatal & reproductive epidemiology research unit

An ANDS funded project for ANZNN, developed by Intersect Australia

Introduction

• ANZNN data collection system – Purpose – monitoring the care of high-risk newborn babies

o Quality improvement and improving clinical practice o Maintaining standards of evidence-based care o Monitoring the use of new technologies/instruments by patient type and

outcome o Identifying areas of priority for research

– ANZNN community o Level III NICUs: 21 in Australia and 6 in New Zealand o Level II NUs: 8 in Australia and 16 in New Zealand o ~ 9,000 babies in 2010, representing <3% live births in ANZ

• Supporting research in neonatal care – In 2012, ANZNN provides data to ~20 research projects

Introduction

• Dynamic nature of ANZNN data collection system – Combined special care with many different disciplines involved – New technologies and instruments involved – Variables changing – adding/changing/deleting 5 variables per year

o In 1994: ~90 o In 2012: 132

– Variables in current system o Maternal characteristics: 21 o Baby characteristics: 22 o Clinical: 82 o Outcome: 7

Manual data process

Building a web-based ANZNN data capture system • Aims – improving data quality and reducing data process

time by – providing an online data entry facility for small units (<50 babies per

year, no computerised medical record system) – providing an online batch data uploading facility for large units (up to

1,000 babies per year, data extracted from hospital medical record system)

– providing an online data validation facility to improve data process and data quality

– providing an online secure data submission facility

• ANDS funding – To UNSW Perinatal & Reproductive Epidemiology Research Unit – 12 months project from March 2012 – Software developer – Intersect Australia Pty Ltd

Benefits of new system to ANZNN community and researchers • Web-based system

– Access from anywhere through web – No additional/special software and licence

• Available to its users – any time any where • Online validations and immediate feedbacks

– Improving data quality and integrity – Ensuring data standard

• Online submission – one-click data submission • Secure system to ensure data privacy and protection

– Secure user accounts by hospitals – Monitoring activities of the system

Web-based ANZNN data capture system

Download CSV

Manage useraccounts

Upload dataReview errors and warnings

Re-upload dataSubmit data

Start data entryReview validation errors

Correct errorsSubmit data

NICUs and NUs in Australia and New

Zealand

Batch process

Data entry form

User access management

facility

User submission

progress monitoring

facility

Data extraction

facility

ANZNN data management

team

User interface

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Web DB

File system:Temporary storage for uploaded batch files

Summary and detail reports for batch files

Batch daemon

Instruct daemon to process file

Store file

Record file details

Store answers

Update status of upload

Process fileCreate reports

Progress review

User accounts

ANZNN long term storage database

Store data

ANZNN data

dictionary: items and options

ANZNN data

validation rules matrix

Data retrieval

A dynamic and flexible system – mechanism to build data entry forms and validation processes

• The system can have different data collections – Two data collections in ANZNN data capture system

o Main ANZNN data collection o Follow-up data collection

• Each data collection based on three data sheets – Questions.csv – Question_options.csv – Cross_question_validations.csv

• Same validation rules used in both individual data entries and batch data uploads

Two data collections in ANZNN data capture system

Question.csv

Question_options.csv

Cross_question_validation.csv

Type of validation rules (examples)

Rule Example/error message Comparison DiedDate must be greater than or equal to DOB Const_implies_const If HiFlo is -1, MinHiFlo must be greater than 0 Const_implies_present If Anom is -1, AnomCode1 must not be blank Const_implies_set If hypotherm is -1, hypothermceased must be

between 0 and 9 Set_implies_present If PlBrth is 1 or 2, PBTH must not be blank Present_implies_present If SurfDate is a date, SurfTime must be a time multi_compare_datetime_quad

SurfDate+SurfTime must be later than or equal to DOB+DOBTime

multi_hours_date_to_date HiFlohrs must be equal to or less than (CeaseHiFloDate+CeaseHiFloTime - StartHiFloDate+StartHiFloTime)

Data Entry Form

Data Entry Form

Data Entry Form - validation

Similar layout but different data entry form – different data collection

Entering and updating data any time

• Access incomplete data any time until submission – Save incomplete data online – Change data – Correct data

• Submit complete data online

Data Entry Form – summary

Data Entry Form – review answers

Batch data uploads

Batch uploading - summary

Batch uploading feedback – validation report

Batch uploading feedback – validation report

System administration – review status

System administration – download data

System administration – view current users

System administration – managing user accounts

System administration – managing user accounts

System administration – managing user accounts

System administration – managing data

System administration – managing data

System administration – managing data

Acknowledgements

• ANDS – funding body • UNSW eResearch Team – support and administration • ANZNN team – support and information (data dictionary

and cross-validation rules) • ANZNN community – support, enthusiasm and

involvement in site testing

• Intersect Australia – software developer • UNSW IT – hosting web server