TY - GEN
T1 - Assessing data integration and quality for the evaluation of point-of-care testi across rural and remote emergency departments in Australia
AU - Li, Ling
AU - McCaughey, Euan
AU - Iles-Mann, Juliana
AU - Sargeant, Andrew
AU - Dahm, Maria R.
AU - Mumford, Virginia
AU - Westbrook, Johanna I.
AU - Georgiou, Andrew
N1 - Publisher Copyright:
© 2017 International Medical Informatics Association (IMIA) and IOS Press.
PY - 2017
Y1 - 2017
N2 - In Australia, New South Wales Health Pathology's implementation of managed Point-of-Care Testing (PoCT) services across rural and remote emergency departments (EDs) has the potential to significantly improve access to results for certain types of pathology laboratory tests and help to deliver timely patient care. The aim of this study was to assess the quality of the datasets, including the integration of PoCT results into clinical systems, as a precursor to the application of an evaluation framework for monitoring the delivery of PoCT services and their impact on patient care. Three datasets, including laboratory, ED presentations and hospital admissions data were extracted from the relevant clinical information systems. Each dataset was assessed on six dimensions: completeness, uniqueness, timeliness, validity, accuracy, and consistency. Data incompleteness was the largest problem. Assessing the PoCT data integration and data quality is a precondition for the evaluation of PoCT and for monitoring and improving service delivery.
AB - In Australia, New South Wales Health Pathology's implementation of managed Point-of-Care Testing (PoCT) services across rural and remote emergency departments (EDs) has the potential to significantly improve access to results for certain types of pathology laboratory tests and help to deliver timely patient care. The aim of this study was to assess the quality of the datasets, including the integration of PoCT results into clinical systems, as a precursor to the application of an evaluation framework for monitoring the delivery of PoCT services and their impact on patient care. Three datasets, including laboratory, ED presentations and hospital admissions data were extracted from the relevant clinical information systems. Each dataset was assessed on six dimensions: completeness, uniqueness, timeliness, validity, accuracy, and consistency. Data incompleteness was the largest problem. Assessing the PoCT data integration and data quality is a precondition for the evaluation of PoCT and for monitoring and improving service delivery.
KW - Australia
KW - Data accuracy
KW - Point-of-care testing
UR - http://www.scopus.com/inward/record.url?scp=85040525690&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-830-3-471
DO - 10.3233/978-1-61499-830-3-471
M3 - Conference contribution
C2 - 29295139
AN - SCOPUS:85040525690
T3 - Studies in Health Technology and Informatics
SP - 471
EP - 475
BT - MEDINFO 2017
A2 - Gundlapalli, Adi V.
A2 - Marie-Christine, Jaulent
A2 - Dongsheng, Zhao
PB - IOS Press BV
T2 - 16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017
Y2 - 21 August 2017 through 25 August 2017
ER -