Our goal was to combine clinical evidence and provider insight to develop a sustainable, paediatric-relevant surveillance model that yields trendable data for ADE monitoring. A review of voluntarily reported safety incidents revealed electrolyte and TPN/lipid preparations underlie many ADEs. No rule targeting lab abnormalities detected ADEs in this study, although we improved hypoglycaemia ADE capture.
Our results are consistent with other paediatric trigger development efforts. Sharek and colleagues developed a neonatal intensive care unit (NICU)-focused manual tool for adverse event discovery.21
They included rule logic for rising creatinine (PPV=11%) and an ‘abnormal electrolytes’ rule with a PPV of 8%. Since this latter rule is not retained in the trigger tool online (http://www.chca.com
), we infer it was ineffective. A second trigger tool for paediatrics was deployed across 12 children's hospitals,4
and compound rule logic produced better PPVs. Although a single-value hyperglycaemia trigger resulted in a PPV of only 0.60%, combining absolute lab values with age logic to detect hyperkalaemia or nephrotoxicity resulted in PPVs of 3.57% and 3.85%. A recent study modifying a surveillance system for paediatrics had limited success with ADE detection using hypokalaemia and hypomagnesaemia rules.22
The authors also report a PPV of 0.08 for hyperkalaemia combined with age logic (potassium >6.0 mEq/l and age >1 year), whereas our PPV for potassium >7.0 mEq/l was 0.
These studies indicate that the use of compound rule logic improves paediatric ADE discovery. At DUH, the issue with using absolute lab values for ADE-S may lie in how they are drawn. For example, NICU heel sticks are used to obtain small blood samples, yet they frequently haemolyse, resulting in elevated potassium values. In the case of elevated lipid levels, the nurse may have drawn the sample from the line infusing lipids. Such details go undocumented, meaning relying on lab values retrospectively to suggest that ADE occurrence is ineffective for our goals. Options to improve rules using compound logic include reasoning over lab value changes (eg, rising bilirubin), since utilising more than two values may bypass unwanted alerts from a single, aberrant result. Additionally, concomitant active drug orders and lab results (eg, use of electrolyte preparations, potassium supplements, or potassium-sparing diuretics and hyperkalaemia) may be of value. Institutions with text scanning capabilities may be able to combine keywords from the medical record relevant to a lab result (eg, altered mental status and the presence of hyponatremia). Since ADE-S runs in a batch process, we are evaluating logistics for real-time alerting of concerning lab trends. Takata and colleagues reported two-thirds of their ADEs were due to lapses in monitoring medications, including assessment of lab results.4
This series of strategies may reduce false-positive alerts and improve ADE detection. Although lowering lab value thresholds may capture more ADEs, the expected increase in alert volume without improving the PPV would be a barrier to sustainable review—a central goal of this study.
There are several limitations to this work. DUH has a large paediatric ICU population (53% of study patient days), which accounts for 61% of trigger alerts. This may limit the generalisability of our findings to hospitals with a similar composition, yet these are likely the same facilities that would have IT resources to implement a computerised surveillance programme. A second limitation is that rules were evaluated over 2.5 months, which may have under-represented detection of rare ADEs. The authors felt that 2.5 months was adequate to evaluate alert utility given the goals of (1) sustainability and (2) data capture for aggregate ADE rate monitoring. Though not useful for our purposes, other organisations may have more success with these rules if able to sustain a longer study period. However, a recent 6-month study with over 40
000 patient days similarly reported low PPVs for electrolyte-based rules (except hypokalaemia and hypomagnesaemia).22
They also noted the need to modify or eliminate low-performing rules to balance reviewer effort and event discovery despite the possibility of rare ADE detection.22
A final limitation to any surveillance approach is its reliance on objective data in the medical record to confirm ADE occurrence. Near misses cannot be captured if errors did not reach the patient.