# Clinical decision support system supported interventions in hospitalized older patients: a matter of natural course and adequate timing

## TL;DR

This study examines how Clinical Decision Support Systems (CDSS) are used in hospitals to improve medication safety for older patients and finds that most alerts are resolved around day 4 or 5 of hospitalization.

## Contribution

The study identifies optimal timing for CDSS alerts and suggests ways to reduce alert fatigue by adjusting alert frequency and timing.

## Key findings

- Most CDSS alerts for hospitalized older patients are resolved between day 4 and 5 of hospitalization.
- The level of resolved alerts varies significantly between clinical rules, ranging from over 50% to less than 25%.
- Adjusting the timing and frequency of CDSS alerts could reduce alert fatigue and improve system effectiveness.

## Abstract

Drug-related problems (DRPs) and potentially inappropriate prescribing (PIP) are associated with adverse patient and health care outcomes. In the setting of hospitalized older patients, Clinical Decision Support Systems (CDSSs) could reduce PIP and therefore improve clinical outcomes. However, prior research showed a low proportion of adherence to CDSS recommendations by clinicians with possible explanatory factors such as little clinical relevance and alert fatigue.

To investigate the use of a CDSS in a real-life setting of hospitalized older patients. We aim to (I) report the natural course and interventions based on the top 20 rule alerts (the 20 most frequently generated alerts per clinical rule) of generated red CDSS alerts (those requiring action) over time from day 1 to 7 of hospitalization; and (II) to explore whether an optimal timing can be defined (in terms of day per rule).

All hospitalized patients aged ≥ 60 years, admitted to Zuyderland Medical Centre (the Netherlands) were included. The evaluation of the CDSS was investigated using a database used for standard care. Our CDSS was run daily and was evaluated on day 1 to 7 of hospitalization. We collected demographic and clinical data, and moreover the total number of CDSS alerts; the total number of top 20 rule alerts; those that resulted in an action by the pharmacist and the course of outcome of the alerts on days 1 to 7 of hospitalization.

In total 3574 unique hospitalized patients, mean age 76.7 (SD 8.3) years and 53% female, were included. From these patients, in total 8073 alerts were generated; with the top 20 of rule alerts we covered roughly 90% of the total. For most rules in the top 20 the highest percentage of resolved alerts lies somewhere between day 4 and 5 of hospitalization, after which there is equalization or a decrease. Although for some rules, there is a gradual increase in resolved alerts until day 7. The level of resolved rule alerts varied between the different clinical rules; varying from > 50–70% (potassium levels, anticoagulation, renal function) to less than 25%.

This study reports the course of the 20 most frequently generated alerts of a CDSS in a setting of hospitalized older patients. We have shown that for most rules, irrespective of an intervention by the pharmacist, the highest percentage of resolved rules is between day 4 and 5 of hospitalization. The difference in level of resolved alerts between the different rules, could point to more or less clinical relevance and advocates further research to explore ways of optimizing CDSSs by adjustment in timing and number of alerts to prevent alert fatigue.

The online version contains supplementary material available at 10.1186/s12877-024-04823-7.

• Describing the natural course of alerts of a Clinical Decision Support System (CDSS) provides insight in the (clinical) relevance and adequate timing of clinical rules.

• Assessing the number of alerts by and timing of clinical rules can contribute to a better understanding of how to optimize the use of a CDSS.

• By means of not running the CDSS daily on one hand and maximizing it to day 4 or 5, the total number of alerts per hospitalized patient could be significantly reduced and might therefore counteract alert fatigue.

The online version contains supplementary material available at 10.1186/s12877-024-04823-7.