Work

A retrospective study of smart spot, a Bluetooth low‑energy real‑time location system supporting quality improvement efforts in Uganda

Year: 2026

Type: article

Abstract: Real-time location systems track assets and individuals, and in high-income clinical settings, they have improved patient flow. However, their use in low- and middle-income countries remains limited. Smart Spot, a low-cost Bluetooth low-energy real-time location system was integrated within the Smart Triage quality improvement platform in the outpatient department of Uganda Martyrs' Hospital Ibanda. The primary objective was to evaluate whether Smart Spot data could be used to detect differences in time spent across clinical locations associated with Smart Triage implementation. The secondary objective was to assess the accuracy of Smart Spot data. At triage, children (or their caregivers) received a beacon attached to a lanyard. The beacons tracked patients' locations throughout their time in the outpatient department. Smart Spot data were collected during a 4‑month baseline phase (pre-Smart Triage) and a 12‑month Smart Triage intervention phase. An algorithm was developed to reduce noise and generate more accurate records of each patient's journey. The resulting pathways were compared to expected paths to evaluate Smart Spot's accuracy. The median durations of patient time spent in specific areas were compared between phases using quantile regression. Data cleaning improved the matching to the expected patient flow from 13.0% to 73.1%. Compared with baseline, the median time patients spent in the assessment area decreased by 51.7% (-81.9 min; CI: -95.1 to -68.8), in the emergency room by 69.1% (-44.3 min; CI: -67.7 to -20.8), and total visit duration by 58.2% (-122.9 min; CI: -138.4 to -107.3), all with p-value < 0.001. Real-time location data supported the demonstration of the Smart Triage platform's benefits. In the cleaned dataset, the intervention phase had shorter total visit time and time reductions within specific areas. Our evaluation demonstrates Smart Spot's feasibility as an effective data-collection platform for quality improvement and its utility for retrospective analyses in low-resource settings.

Source: PLOS Digital Health

DOI: 10.1371/journal.pdig.0001790