Use of Computerized Physician Order Entry with Clinical Decision Support to Prevent Dose Errors in Pediatric Medication Orders: A Systematic Review

3.1 Study Characteristics

A total of 17 studies were included from the 4207 identified publications published between 2007 and 2021 (Fig. 1; Table 2). The majority of the publications (65%, n = 11/17) were conducted in the USA, followed by the Middle East (18%, n = 3/17), Europe (12%, n = 2/17), and Asia (6%, n = 1/17). The studies applied pre–post (n = 10) and cross-sectional (n = 7) designs with varying data collecting methods; the most common method (n = 16) was retrospective register data analysis (Supplementary Table S8) [22, 23, 46,47,48,49,50,51,52,53,54,55,56,57,58,59]. In pre–post studies, the effects of implementation or modification of CPOE–CDS system was measured by comparing the rates of dose errors or alert rates before and after intervention. Cross-sectional studies involved data from various time periods to evaluate the impact of CPOS–CDS systems, e.g., on dosing error rates over time. In pre–post studies, a period of time before and after an implementation or modification of the CPOE–CDS system was used to evaluate the effects on dose errors or alert rates, whereas cross-sectional studies involved data from various point of times to evaluate, e.g., the impact on dosing error rates over time. All included studies were conducted in pediatric settings. Pediatric intensive care units (PICU) or other intensive care units were the most common settings (29%, n = 5/17) when the study focused on a specific ward instead of the whole hospital [48, 50, 55, 56, 58].

Fig. 1figure 1Table 2 Description of the included studies (n = 17)

The most studies (71%, n = 12/17) included only inpatient orders (Table 2) [46, 48, 50,51,52,53,54,55,56,57,58,59]. Two studies were conducted in outpatient settings, and in one study, outpatient medications were prescribed in a pediatric emergency department [22, 24, 47]. Only 12% (n = 2/17) of the studies included both inpatient orders and outpatient prescriptions [23, 49]. The comprehensive study characteristics are presented in Supplementary Table S8.

3.2 Characteristics of the CPOE–CDS Systems

The studies reported several different CPOE–CDS systems (Table 3 and Supplementary Table S9). In the majority of the studies (94%, n = 16/17), the organization or unit had either a self-developed (homegrown) CDS system or a customized commercial CDS system (Table 4) [22, 23, 46,47,48,49,50,51,52,53,54,55,56,57,58,59]. One study reported a commercial CPOE–CDS system with no additional customizations [24]. In total, 13 different CDS tools were identified, of which 9 were reported as homegrown or customized (Table 3).

Table 3 The identified clinical decision support (CDS) tools and their characteristics assessed in the studiesTable 4 The customization of the computerized physician order entry (CPOE) systems with clinical decision support (CDS)

The number of CDS tools in one study ranged from 1 to 6 and, when excluding the study that considered multiple different institutions [47], the average number of different CDS tools in one setting was three (mean 3.1 and median 3). The most common CDS tool was dose range check (in 82% of the studies, n = 14/17; Table 3). Other common tools were dosing frequency check and dose calculator (in 47% of studies, n = 8/17). The most customized tools were dose range check (86%, n = 12/14), maximum dose limits (83%, n = 5/6), and frequency check (75%, n = 6/8). In thirteen studies, the used CDS system was basic [22,23,24, 46,47,48,49, 52,53,54, 56, 58, 59], and three were considered as advanced [50, 55, 57]. One study had a basic CDS system with optional advanced tools [51].

3.3 CDS Systems with Alert Functions

In 15 studies, the CDS within the CPOE system comprised soft-stop alerts that can be overridden by the user (Table 1) [22,23,24, 48,49,50,51,52,53,54,55,56,57,58,59]. In four of these studies [48, 55, 56, 58], the CDS also included hard-stop alerts, which cannot be self-overridden (Table 1). When implementing new, or customizing an existing, CPOE–CDS system, usually alert functions were added (n = 9) [23, 24, 48, 50,51,52, 55, 58, 59]. Alternatively, the existing alert systems were modified by either changing the alert logic (n = 2) [54, 57], or modifying other CDS tools (e.g., customizing dose ranges) that had an effect on the alert rate (n = 2) [49, 53]. The prevalence of soft-stop alerts was reported in 59% (n = 10/17) [22, 24, 50,51,52,53,54,55,

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