PMID- 34795071
OWN - NLM
STAT- MEDLINE
DCOM- 20211122
LR  - 20211122
IS  - 1879-8365 (Electronic)
IS  - 0926-9630 (Linking)
VI  - 287
DP  - 2021 Nov 18
TI  - Assessing Acceptance Level of a Hybrid Clinical Decision Support Systems.
PG  - 18-22
LID - 10.3233/SHTI210802 [doi]
AB  - We present a user acceptance study of a clinical decision support system (CDSS) 
      for Type 2 Diabetes Mellitus (T2DM) risk prediction. We focus on how a 
      combination of data-driven and rule-based models influence the efficiency and 
      acceptance by doctors. To evaluate the perceived usefulness, we randomly 
      generated CDSS output in three different settings: Data-driven (DD) model output; 
      DD model with a presence of known risk scale (FINDRISK); DD model with presence 
      of risk scale and explanation of DD model. For each case, a physician was asked 
      to answer 3 questions: if a doctor agrees with the result, if a doctor 
      understands it, if the result is useful for the practice. We employed a Lankton's 
      model to evaluate the user acceptance of the clinical decision support system. 
      Our analysis has proved that without the presence of scales, a physician trust 
      CDSS blindly. From the answers, we can conclude that interpretability plays an 
      important role in accepting a CDSS.
FAU - Kopanitsa, Georgy
AU  - Kopanitsa G
AD  - ITMO University, 49 Kronverskiy prospect, 197101, Saint Petersburg, Russia.
FAU - Derevitskii, Ilia V
AU  - Derevitskii IV
AD  - ITMO University, 49 Kronverskiy prospect, 197101, Saint Petersburg, Russia.
FAU - Savitskaya, Daria A
AU  - Savitskaya DA
AD  - Almazov National Medical Research Centre, 2 Akkuratova st., 197341, Saint 
      Petersburg, Russia.
FAU - Kovalchuk, Sergey V
AU  - Kovalchuk SV
AD  - ITMO University, 49 Kronverskiy prospect, 197101, Saint Petersburg, Russia.
AD  - Almazov National Medical Research Centre, 2 Akkuratova st., 197341, Saint 
      Petersburg, Russia.
LA  - eng
PT  - Journal Article
PL  - Netherlands
TA  - Stud Health Technol Inform
JT  - Studies in health technology and informatics
JID - 9214582
MH  - *Decision Support Systems, Clinical
MH  - *Diabetes Mellitus, Type 2
MH  - Humans
MH  - *Physicians
OTO - NOTNLM
OT  - CDSS
OT  - data-driven
OT  - rule-based
OT  - user acceptance
EDAT- 2021/11/20 06:00
MHDA- 2021/11/23 06:00
CRDT- 2021/11/19 06:04
PHST- 2021/11/19 06:04 [entrez]
PHST- 2021/11/20 06:00 [pubmed]
PHST- 2021/11/23 06:00 [medline]
AID - SHTI210802 [pii]
AID - 10.3233/SHTI210802 [doi]
PST - ppublish
SO  - Stud Health Technol Inform. 2021 Nov 18;287:18-22. doi: 10.3233/SHTI210802.