TY - JOUR
T1 - Developing an integrated clinical decision support system for the early identification and management of kidney disease—building cross-sectoral partnerships
AU - Gorham, Gillian
AU - Abeyaratne, Asanga
AU - Heard, Sam
AU - Moore, Liz
AU - George, Pratish
AU - Kamler, Paul
AU - Majoni, Sandawana William
AU - Chen, Winnie
AU - Balasubramanya, Bhavya
AU - Talukder, Mohammad Radwanur
AU - Pascoe, Sophie
AU - Whitehead, Adam
AU - Sajiv, Cherian
AU - Maple-Brown, Louise
AU - Kangaharan, Nadarajah
AU - Cass, Alan
PY - 2024/3/8
Y1 - 2024/3/8
N2 - Background: The burden of chronic conditions is growing in Australia with people in remote areas experiencing high rates of disease, especially kidney disease. Health care in remote areas of the Northern Territory (NT) is complicated by a mobile population, high staff turnover, poor communication between health services and complex comorbid health conditions requiring multidisciplinary care. Aim: This paper aims to describe the collaborative process between research, government and non-government health services to develop an integrated clinical decision support system to improve patient care. Methods: Building on established partnerships in the government and Aboriginal Community-Controlled Health Service (ACCHS) sectors, we developed a novel digital clinical decision support system for people at risk of developing kidney disease (due to hypertension, diabetes, cardiovascular disease) or with kidney disease. A cross-organisational and multidisciplinary Steering Committee has overseen the design, development and implementation stages. Further, the system’s design and functionality were strongly informed by experts (Clinical Reference Group and Technical Working Group), health service providers, and end-user feedback through a formative evaluation. Results: We established data sharing agreements with 11 ACCHS to link patient level data with 56 government primary health services and six hospitals. Electronic Health Record (EHR) data, based on agreed criteria, is automatically and securely transferred from 15 existing EHR platforms. Through clinician-determined algorithms, the system assists clinicians to diagnose, monitor and provide guideline-based care for individuals, as well as service-level risk stratification and alerts for clinically significant events. Conclusion: Disconnected health services and separate EHRs result in information gaps and a health and safety risk, particularly for patients who access multiple health services. However, barriers to clinical data sharing between health services still exist. In this first phase, we report how robust partnerships and effective governance processes can overcome these barriers to support clinical decision making and contribute to holistic care.
AB - Background: The burden of chronic conditions is growing in Australia with people in remote areas experiencing high rates of disease, especially kidney disease. Health care in remote areas of the Northern Territory (NT) is complicated by a mobile population, high staff turnover, poor communication between health services and complex comorbid health conditions requiring multidisciplinary care. Aim: This paper aims to describe the collaborative process between research, government and non-government health services to develop an integrated clinical decision support system to improve patient care. Methods: Building on established partnerships in the government and Aboriginal Community-Controlled Health Service (ACCHS) sectors, we developed a novel digital clinical decision support system for people at risk of developing kidney disease (due to hypertension, diabetes, cardiovascular disease) or with kidney disease. A cross-organisational and multidisciplinary Steering Committee has overseen the design, development and implementation stages. Further, the system’s design and functionality were strongly informed by experts (Clinical Reference Group and Technical Working Group), health service providers, and end-user feedback through a formative evaluation. Results: We established data sharing agreements with 11 ACCHS to link patient level data with 56 government primary health services and six hospitals. Electronic Health Record (EHR) data, based on agreed criteria, is automatically and securely transferred from 15 existing EHR platforms. Through clinician-determined algorithms, the system assists clinicians to diagnose, monitor and provide guideline-based care for individuals, as well as service-level risk stratification and alerts for clinically significant events. Conclusion: Disconnected health services and separate EHRs result in information gaps and a health and safety risk, particularly for patients who access multiple health services. However, barriers to clinical data sharing between health services still exist. In this first phase, we report how robust partnerships and effective governance processes can overcome these barriers to support clinical decision making and contribute to holistic care.
KW - Chronic disease
KW - Clinical algorithms
KW - Clinical decision support
KW - Clinical information systems
KW - Clinical safety
KW - Integrated patient care
KW - Remote health
UR - http://www.scopus.com/inward/record.url?scp=85187181498&partnerID=8YFLogxK
UR - http://purl.org/au-research/grants/NHMRC/1194677
UR - http://purl.org/au-research/grants/NHMRC/1194698
U2 - 10.1186/s12911-024-02471-w
DO - 10.1186/s12911-024-02471-w
M3 - Article
C2 - 38459531
AN - SCOPUS:85187181498
SN - 1472-6947
VL - 24
JO - BMC Medical Informatics and Decision Making
JF - BMC Medical Informatics and Decision Making
M1 - 69
ER -