Evaluation of clinical rules in a standalone pharmacy based clinical decision support system for hospitalized and nursing home patients
H.A.J.M. de Wit*, C. Mestres Gonzalvo, J. Cardenas, H.J. Derijks, R. Janknegt, P.H.M. van der Kuy, B. Winkens, J.M.G.A. Schols
FHML Methodologie & Statistiek
CAPHRI School for Public Health and Primary Care
CAPHRI - Ageing and Long-Term Care
CAPHRI - Promoting Health & Personalised Care
Objectives: To improve the current standalone pharmacy clinical decision support system (CDSS) by identifying and quantifying the benefits and limitations of the system. Methods: Alerts and handling of the executed clinical rules were extracted from the CDSS from the period September 2011 to December 2011. The number of executed clinical rule alerts, number of actions on alerts, and the reason why alerts were classified as not relevant were analyzed. The alerts where considered clinically relevant when the pharmacist needed to contact the physician. Results: The 4065 alerts have been separated into: 1137 (28.0%) new alerts, 2797 (68.8%) repeat alerts and 131 (3.2%) double alerts. When the alerts were analyzed, only 3.6% were considered clinically relevant. Reasons why alerts were considered as not to be relevant were: (a) the dosage was correct or already adjusted, (b) the drug was (temporarily) stopped and (c) the monitored laboratory value or drug dosage had already reverted to be within the reference limits. The reasons for no action were linked to three categorical limitations of the used system: 'algorithm alert criteria', 'CDSS optimization', and 'data delivery'. Conclusion: This study highlighted a number of ways in which the CDSS could be improved. These different aspects have been identified as important for developing an efficient CDSS.
de Wit, H. A. J. M., Mestres Gonzalvo, C., Cardenas, J., Derijks, H. J., Janknegt, R., van der Kuy, P. H. M., Winkens, B., & Schols, J. M. G. A. (2015). Evaluation of clinical rules in a standalone pharmacy based clinical decision support system for hospitalized and nursing home patients. International Journal of Medical Informatics, 84(6), 396-405. https://doi.org/10.1016/j.ijmedinf.2015.02.004
de Wit, H.A.J.M. ; Mestres Gonzalvo, C. ; Cardenas, J. et al. / Evaluation of clinical rules in a standalone pharmacy based clinical decision support system for hospitalized and nursing home patients. In: International Journal of Medical Informatics. 2015 ; Vol. 84, No. 6. pp. 396-405.
@article{4d383f2964744749886af035f25f18c4,
title = "Evaluation of clinical rules in a standalone pharmacy based clinical decision support system for hospitalized and nursing home patients",
abstract = "Objectives: To improve the current standalone pharmacy clinical decision support system (CDSS) by identifying and quantifying the benefits and limitations of the system. Methods: Alerts and handling of the executed clinical rules were extracted from the CDSS from the period September 2011 to December 2011. The number of executed clinical rule alerts, number of actions on alerts, and the reason why alerts were classified as not relevant were analyzed. The alerts where considered clinically relevant when the pharmacist needed to contact the physician. Results: The 4065 alerts have been separated into: 1137 (28.0%) new alerts, 2797 (68.8%) repeat alerts and 131 (3.2%) double alerts. When the alerts were analyzed, only 3.6% were considered clinically relevant. Reasons why alerts were considered as not to be relevant were: (a) the dosage was correct or already adjusted, (b) the drug was (temporarily) stopped and (c) the monitored laboratory value or drug dosage had already reverted to be within the reference limits. The reasons for no action were linked to three categorical limitations of the used system: 'algorithm alert criteria', 'CDSS optimization', and 'data delivery'. Conclusion: This study highlighted a number of ways in which the CDSS could be improved. These different aspects have been identified as important for developing an efficient CDSS.",
author = "{de Wit}, H.A.J.M. and {Mestres Gonzalvo}, C. and J. Cardenas and H.J. Derijks and R. Janknegt and {van der Kuy}, P.H.M. and B. Winkens and J.M.G.A. Schols",
de Wit, HAJM, Mestres Gonzalvo, C, Cardenas, J, Derijks, HJ, Janknegt, R, van der Kuy, PHM, Winkens, B & Schols, JMGA 2015, 'Evaluation of clinical rules in a standalone pharmacy based clinical decision support system for hospitalized and nursing home patients', International Journal of Medical Informatics, vol. 84, no. 6, pp. 396-405. https://doi.org/10.1016/j.ijmedinf.2015.02.004
Evaluation of clinical rules in a standalone pharmacy based clinical decision support system for hospitalized and nursing home patients. / de Wit, H.A.J.M.; Mestres Gonzalvo, C.; Cardenas, J. et al.
In: International Journal of Medical Informatics, Vol. 84, No. 6, 01.01.2015, p. 396-405.
T1 - Evaluation of clinical rules in a standalone pharmacy based clinical decision support system for hospitalized and nursing home patients
AU - de Wit, H.A.J.M.
AU - Mestres Gonzalvo, C.
AU - Cardenas, J.
AU - Derijks, H.J.
AU - Janknegt, R.
AU - van der Kuy, P.H.M.
AU - Winkens, B.
AU - Schols, J.M.G.A.
N2 - Objectives: To improve the current standalone pharmacy clinical decision support system (CDSS) by identifying and quantifying the benefits and limitations of the system. Methods: Alerts and handling of the executed clinical rules were extracted from the CDSS from the period September 2011 to December 2011. The number of executed clinical rule alerts, number of actions on alerts, and the reason why alerts were classified as not relevant were analyzed. The alerts where considered clinically relevant when the pharmacist needed to contact the physician. Results: The 4065 alerts have been separated into: 1137 (28.0%) new alerts, 2797 (68.8%) repeat alerts and 131 (3.2%) double alerts. When the alerts were analyzed, only 3.6% were considered clinically relevant. Reasons why alerts were considered as not to be relevant were: (a) the dosage was correct or already adjusted, (b) the drug was (temporarily) stopped and (c) the monitored laboratory value or drug dosage had already reverted to be within the reference limits. The reasons for no action were linked to three categorical limitations of the used system: 'algorithm alert criteria', 'CDSS optimization', and 'data delivery'. Conclusion: This study highlighted a number of ways in which the CDSS could be improved. These different aspects have been identified as important for developing an efficient CDSS.
AB - Objectives: To improve the current standalone pharmacy clinical decision support system (CDSS) by identifying and quantifying the benefits and limitations of the system. Methods: Alerts and handling of the executed clinical rules were extracted from the CDSS from the period September 2011 to December 2011. The number of executed clinical rule alerts, number of actions on alerts, and the reason why alerts were classified as not relevant were analyzed. The alerts where considered clinically relevant when the pharmacist needed to contact the physician. Results: The 4065 alerts have been separated into: 1137 (28.0%) new alerts, 2797 (68.8%) repeat alerts and 131 (3.2%) double alerts. When the alerts were analyzed, only 3.6% were considered clinically relevant. Reasons why alerts were considered as not to be relevant were: (a) the dosage was correct or already adjusted, (b) the drug was (temporarily) stopped and (c) the monitored laboratory value or drug dosage had already reverted to be within the reference limits. The reasons for no action were linked to three categorical limitations of the used system: 'algorithm alert criteria', 'CDSS optimization', and 'data delivery'. Conclusion: This study highlighted a number of ways in which the CDSS could be improved. These different aspects have been identified as important for developing an efficient CDSS.
de Wit HAJM, Mestres Gonzalvo C, Cardenas J, Derijks HJ, Janknegt R, van der Kuy PHM et al. Evaluation of clinical rules in a standalone pharmacy based clinical decision support system for hospitalized and nursing home patients. International Journal of Medical Informatics. 2015 Jan 1;84(6):396-405. doi: 10.1016/j.ijmedinf.2015.02.004