TY - JOUR
T1 - Quantifying the advantages and acceptability of linking dialysis machines to an electronic medical record
AU - Holt, Stephen Geoffrey
AU - Nundlall, Anitha
AU - Alameri, Mohamed
AU - Alhosani, Khalid Jamal
AU - Arayaparath, Abdul Vahid
AU - James, Marie Kim
AU - Almansoori, Ali Mohamed Saeed Hammad
AU - Alam, Afroz
AU - Al Obaidli, Ali Abdul Kareem
AU - Al Madani, Ayman Kamal
N1 - Publisher Copyright:
© 2023
PY - 2023/10
Y1 - 2023/10
N2 - Aim: To establish and quantify the time saved by redirecting nursing workload from recording and entering haemodynamic data during chronic dialysis sessions by linking dialysis machines directly to the electronic medical record. Methods: We developed a bespoke interface from the HL7 feed from the dialysis machines (largely Fresenius 5008) to our EMR system (Cerner). We quantified the time nurses spent with the patient, computer, dialysis machine and sorting our patient related issues by observation using independent observers in a time and motion study. We performed these observations before and after implementation of the computer interface. We established patient and nursing acceptance by survey. We established adequacy of observations by counting the number of patients who received the minimum number of observations recorded in the system before and after implementation. Results: Implementation of a dialysis machine direct EMR interface reduced the time the nurses spent with the computer significantly by ∼9 % (around 28 min, p < 0.05) per dialysis shift, and this was accompanied by a similar increase in time spent sorting out patient-related issues. The interface was well accepted by staff and patients. An immediate benefit was a ∼60 % improvement in the adequacy of recording vital signs in our dialysis patients. Then simply by showing these results to the nursing staff there was further improvement. Conclusions: In these days of machine interconnectivity there is really no good reason why dialysis nurses should be used to transfer data between machines. It is far better to utilise their skills in helping patients with their medical issues. We have shown that such a link improves efficiency, patient and staff satisfaction and dialysis governance.
AB - Aim: To establish and quantify the time saved by redirecting nursing workload from recording and entering haemodynamic data during chronic dialysis sessions by linking dialysis machines directly to the electronic medical record. Methods: We developed a bespoke interface from the HL7 feed from the dialysis machines (largely Fresenius 5008) to our EMR system (Cerner). We quantified the time nurses spent with the patient, computer, dialysis machine and sorting our patient related issues by observation using independent observers in a time and motion study. We performed these observations before and after implementation of the computer interface. We established patient and nursing acceptance by survey. We established adequacy of observations by counting the number of patients who received the minimum number of observations recorded in the system before and after implementation. Results: Implementation of a dialysis machine direct EMR interface reduced the time the nurses spent with the computer significantly by ∼9 % (around 28 min, p < 0.05) per dialysis shift, and this was accompanied by a similar increase in time spent sorting out patient-related issues. The interface was well accepted by staff and patients. An immediate benefit was a ∼60 % improvement in the adequacy of recording vital signs in our dialysis patients. Then simply by showing these results to the nursing staff there was further improvement. Conclusions: In these days of machine interconnectivity there is really no good reason why dialysis nurses should be used to transfer data between machines. It is far better to utilise their skills in helping patients with their medical issues. We have shown that such a link improves efficiency, patient and staff satisfaction and dialysis governance.
KW - Dialysis
KW - Governance
KW - Interface
UR - http://www.scopus.com/inward/record.url?scp=85171624059&partnerID=8YFLogxK
U2 - 10.1016/j.ijmedinf.2023.105215
DO - 10.1016/j.ijmedinf.2023.105215
M3 - Article
C2 - 37688833
AN - SCOPUS:85171624059
SN - 1386-5056
VL - 178
JO - International Journal of Medical Informatics
JF - International Journal of Medical Informatics
M1 - 105215
ER -