TY - GEN
T1 - Patient Data Sharing and Reduction of Overtime Work of Nurses by Innovation of Nursing Records Using Structured Clinical Knowledge
AU - Tsuru, Satoko
AU - Tamamoto, Tetsuro
AU - Nakao, Akihiro
AU - Tanizaki, Kouichi
AU - Yahagi, Naohisa
N1 - Funding Information:
We are deeply grateful for the collaboration of the project members and organizations. This work was supported by JSPS KAKENHI (Grant-in-Aid for Scientific Research) No. 17H01608.
Publisher Copyright:
© 2022 European Federation for Medical Informatics (EFMI) and IOS Press.
PY - 2022/5/25
Y1 - 2022/5/25
N2 - Half of nurses' overtime hours are due to records. Nursing records, which are mainly narrative records, cost a large amount of money. However, it has been pointed out that there are problems with their quality and post-use. In this study, we analyzed the value of nursing records for physicians. As a result, we found that the use of standard observation terms in nursing records can create an environment in which patients' conditions can be shared. To create this environment, the physicians of the clinical path committee classified hospitalized patients in terms of disease, treatment, and examination, and created a list of 778 process paths. Physicians, nurses, and researchers collaborated to develop digital contents with high-priority observation items and care actions adapted to patient conditions for each path. We developed a clinical support system equipped with these digital contents. In May 2019, we installed the system in a 900-bed university hospital. Then, in October 2020, we installed the system in a 400-bed general hospital. We used 'nurses' overtime hours for recording' and 'reduction rate' as indicators of the usefulness of this system. In the 900-bed university hospital, we compared the previous year's results for March, the end of the fiscal year. This overtime hours were 2,944 hours 00 minutes in March 2019 and 2,141 hours 55 minutes in March 2020. 27% reduction was indicated. The respective bed occupancy rates were 90.80 percent and 90.60 percent, with no difference. In the 400-bed general hospital, This overtime hours were compared to the previous year, covering November and December after one month of implementation. 386 hours in November 2019 and 204.5 hours in November 2020. 47% reduction indicated. 366 hours in December 2019 and 214.5 hours in December 2020. A reduction of 41% was shown. These results suggest that the implementation of this system can both improve the quality of team care and reduce overtime.
AB - Half of nurses' overtime hours are due to records. Nursing records, which are mainly narrative records, cost a large amount of money. However, it has been pointed out that there are problems with their quality and post-use. In this study, we analyzed the value of nursing records for physicians. As a result, we found that the use of standard observation terms in nursing records can create an environment in which patients' conditions can be shared. To create this environment, the physicians of the clinical path committee classified hospitalized patients in terms of disease, treatment, and examination, and created a list of 778 process paths. Physicians, nurses, and researchers collaborated to develop digital contents with high-priority observation items and care actions adapted to patient conditions for each path. We developed a clinical support system equipped with these digital contents. In May 2019, we installed the system in a 900-bed university hospital. Then, in October 2020, we installed the system in a 400-bed general hospital. We used 'nurses' overtime hours for recording' and 'reduction rate' as indicators of the usefulness of this system. In the 900-bed university hospital, we compared the previous year's results for March, the end of the fiscal year. This overtime hours were 2,944 hours 00 minutes in March 2019 and 2,141 hours 55 minutes in March 2020. 27% reduction was indicated. The respective bed occupancy rates were 90.80 percent and 90.60 percent, with no difference. In the 400-bed general hospital, This overtime hours were compared to the previous year, covering November and December after one month of implementation. 386 hours in November 2019 and 204.5 hours in November 2020. 47% reduction indicated. 366 hours in December 2019 and 214.5 hours in December 2020. A reduction of 41% was shown. These results suggest that the implementation of this system can both improve the quality of team care and reduce overtime.
KW - overtime work
KW - quality management
KW - structured knowledge
UR - http://www.scopus.com/inward/record.url?scp=85131106249&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85131106249&partnerID=8YFLogxK
U2 - 10.3233/SHTI220514
DO - 10.3233/SHTI220514
M3 - Conference contribution
C2 - 35612135
AN - SCOPUS:85131106249
T3 - Studies in Health Technology and Informatics
SP - 525
EP - 529
BT - Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022
A2 - Seroussi, Brigitte
A2 - Weber, Patrick
A2 - Dhombres, Ferdinand
A2 - Grouin, Cyril
A2 - Liebe, Jan-David
A2 - Liebe, Jan-David
A2 - Liebe, Jan-David
A2 - Pelayo, Sylvia
A2 - Pinna, Andrea
A2 - Rance, Bastien
A2 - Rance, Bastien
A2 - Sacchi, Lucia
A2 - Ugon, Adrien
A2 - Ugon, Adrien
A2 - Benis, Arriel
A2 - Gallos, Parisis
PB - IOS Press BV
T2 - 32nd Medical Informatics Europe Conference, MIE 2022
Y2 - 27 May 2022 through 30 May 2022
ER -