Evaluating the impact of the ICNET® clinical decision support system for antimicrobial stewardship

• Main Authors: Katie L. Heard, Stephen Hughes, Nabeela Mughal, Berge S. Azadian, Luke S. P. Moore
• Format: Article
• Language: English
• Published: BMC 2019-03-01
• Series: Antimicrobial Resistance and Infection Control
• Subjects: Antimicrobial resistance; Antimicrobial stewardship; Clinical decision support system; eHealth; mHealth
• Online Access: http://link.springer.com/article/10.1186/s13756-019-0496-4

Abstract Background Antimicrobial resistance (AMR) is an ecological and economic crisis and stewardship of available antimicrobials is required. Electronic prescribing, where available, enables auditing of practice, yet in order to be efficient and effective in addressing inappropriate antimicrobial prescribing, better use of current and new technological interventions is needed. This retrospective observational evaluation looked at the impact of a commercial clinical decision support system (CDSS) on the workflow of an established antimicrobial stewardship (AMS) team. Material/methods Clinical, workflow, and pharmaceutical data from 3 months post implementation of CDSS were collated, and compared to the same 3 month periods in preceding years. The evaluation considered total interventions made, the types of intervention made, impact of said interventions, and time spent executing interventions. All antimicrobial data were adjusted for total daily defined doses (DDD) of intravenous antimicrobials. Results Productivity: In the 3 month evaluation period (Jun-Aug 2016) a total of 264 case reviews resulting in 298 AMS interventions were made. Compared to preceding years where 138 and 169 interventions were made (2013 and 2014 respectively). In 2013 49% of interventions were stopping medication and 30% change of therapy based on cultures and sensitivities compared to 25 and 17% in 2016. In contrast to previous years’, the CDSS instead enabled a greater number of dose/drug optimisation (13%), escalation of antimicrobials (12%) and intravenous (IV) to oral switch (11%) interventions. Patient Identification: Despite increased patient numbers post-CDSS, on average 46 min per day was spent compiling a patient list for review, compared to 59 min in 2014. The use of CDSS facilitated 15 interventions/1000DDD, compared to pre-intervention (9.4/1000DDD in 2013; 11.5/1000DDD in 2014). Conclusions Initial evaluation of the impact of this CDSS on AMS at the organisation has demonstrated effectiveness in terms of case finding, AMS team productivity, and workflow auditing. More importantly, patient infection management has been optimised with a shift in the emphasis of AMS interventions. It has contributed to the success of the healthcare provider achieving nationally set remunerated AMS targets.