Does Implementation of Biomathematical Models Mitigate Fatigue and Fatigue-related Risks in Emergency Medical Services Operations? A Systematic Review

Figures & data

Figure 1. PRISMA Flow Diagram for PICO#6 PROSPERO 2016:CRD42016040112.

Table 1. Synthesis of individual studies that test implementation of biomathematical models to determine impact on outcomes selected as important to this systematic review

Experimental Study Designs
			Important Outcomes
Author, Year	RefID PMID	Study Design	Patient Safety^*	Personnel Safety	Personnel Performance^†	Acute Fatigue^‡	Sleep and Sleep Quality^§	Long-Term Health^║	Cost to System
Moore-Ede, 2004	RefID-1691 PMID-15018271	Quasi-experimental	—	Favorable	—	—	—	—	Favorable

Findings are classified using a system adapted from Bolster and Rourke (2015) where interpretation of findings was classified as favorable if after implementation of the model, improvements in outcomes were observed. Other categories include: unfavorable, mixed/inconclusive, or no impact.

^* Includes quality of care.

^† Includes external subjective ratings of the study subject's performance including perceived satisfaction with the subject's performance.

^‡ Includes acute states of fatigue, sleepiness, and alertness.

^§ Includes sleep latency, total sleep time, recovery, and related measures.

^║ General wellness or well-being measures included.

Table 2. GRADE evidence profile table

Quality assessment
№ of studies	Study design	Risk of bias	Inconsistency	Indirectness	Imprecision	Other considerations	Impact / Effect	Quality	Importance
Patient Safety
0								—	IMPORTANT
Personnel Safety
1	Experimental study design^*	Serious^†,^‡	Not serious	Serious^§	Serious^║	Relevant data are held private and unpublished.^#	The number of truck accidents decreased 23.3% from 2.30 per million miles traveled during a three-year pre-intervention period to 1.76 million miles during the intervention year. The number of severe accidents decreased by 55% from 0.20 per million miles prior to the intervention to 0.09 per million miles during the intervention.	⊕◯◯◯ VERY LOW	IMPORTANT
Personnel Performance
0								—	IMPORTANT
Sleep / Sleep Quality
0								—	IMPORTANT
Indicators of Long-Term Health
0								—	IMPORTANT
Cost to System
1	Experimental study design^*	Serious^†,^‡	Not serious	Serious^§	Serious^║	Relevant data are held private and unpublished.^#	The mean cost per truck accident decreased 65.8% from $14,088 (SEM $4,307) during a three-year pre-intervention period to $4,820 (SEM $1,437; t-test p < 0.05) during the one-year intervention. The mean cost of “severity accidents” (over $20,000 cost) decreased by 66.7% from $152,384 (SEM $40,841) per accident pre-intervention to $50,809 (SEM $6,080) per accident during the intervention period (t-test p < 0.05).	⊕◯◯◯ VERY LOW	IMPORTANT
Acute Fatigue
0								—	IMPORTANT

EXPLANATIONS

^* Quasi-experimental study design.

^† Experimental: Lack of blinding of participants and/or personnel.

^‡ Experimental: Lack of blinding of outcome assessment.

^§ Shift workers other than EMS personnel.

^║ Sample size: a) one organization; b) unknown number of individual participants.

^# Potential for selective outcome reporting.