John W Scott1, Jeanne D'Arc Nyinawankusi2, Samuel Enumah3, Rebecca Maine4, Eric Uwitonze2, Yihan Hu5, Ignace Kabagema6, Jean Claude Byiringiro7, Robert Riviello3, Sudha Jayaraman8. 1. Center for Surgery and Public Health, Department of Surgery, Brigham & Women's Hospital, Boston, MA, USA; Program in Global Surgery and Social Change, Harvard Medical School, Boston, MA, USA. Electronic address: jwscott@partners.org. 2. Service d'Aide Medicale Urgente, Ministry of Health, Kigali, Rwanda. 3. Center for Surgery and Public Health, Department of Surgery, Brigham & Women's Hospital, Boston, MA, USA; Program in Global Surgery and Social Change, Harvard Medical School, Boston, MA, USA. 4. Program in Global Surgery and Social Change, Harvard Medical School, Boston, MA, USA; Harborview Medical Center, Division of Trauma, Burns and Critical Care, Seattle, WA, USA. 5. Harvard College, Faculty of Arts and Sciences, Boston, MA, USA. 6. Harborview Medical Center, Division of Trauma, Burns and Critical Care, Seattle, WA, USA. 7. Centre Hospitalier Universitaire de Kigali, Kigali, Rwanda. 8. Division of Trauma, Emergency Surgery, and Critical Care, Virginia Commonwealth University, Richmond, VA USA.
Abstract
INTRODUCTION: Injury is a major cause of premature death and disability in East Africa, and high-quality pre-hospital care is essential for optimal trauma outcomes. The Rwandan pre-hospital emergency care service (SAMU) uses an electronic database to evaluate and optimize pre-hospital care through a continuous quality improvement programme (CQIP), beginning March 2014. MATERIALS AND METHODS: The SAMU database was used to assess pre-hospital quality metrics including supplementary oxygen for hypoxia (O2), intravenous fluids for hypotension (IVF), cervical collar placement for head injuries (c-collar), and either splinting (splint) or administration of pain medications (pain) for long bone fractures. Targets of >90% were set for each metric and daily team meetings and monthly feedback sessions were implemented to address opportunities for improvement. These five pre-hospital quality metrics were assessed monthly before and after implementation of the CQIP. Met and unmet needs for O2, IVF, and c-collar were combined into a summative monthly SAMU Trauma Quality Scores (STQ score). An interrupted time series linear regression model compared the STQ score during 14 months before the CQIP implementation to the first 14 months after. RESULTS: During the 29-month study period 3,822 patients met study criteria. 1,028 patients needed one or more of the five studied interventions during the study period. All five endpoints had a significant increase between the pre-CQI and post-CQI periods (p<0.05 for all), and all five achieved a post-CQI average of at least 90% completion. The monthly composite STQ scores ranged from 76.5 to 97.9 pre-CQI, but tightened to 86.1-98.7 during the post-CQI period. Interrupted time series analysis of the STQ score showed that CQI programme led to both an immediate improvement of +6.1% (p=0.017) and sustained monthly improvements in care delivery-improving at a rate of 0.7% per month (p=0.028). CONCLUSION: The SAMU experience demonstrates the utility of a responsive, data-driven quality improvement programme to yield significant immediate and sustained improvements in pre-hospital care for trauma in Rwanda. This programme may be used as an example for additional efforts engaging frontline staff with real-time data feedback in order to rapidly translate data collection efforts into improved care for the injured in a resource-limited setting.
INTRODUCTION: Injury is a major cause of premature death and disability in East Africa, and high-quality pre-hospital care is essential for optimal trauma outcomes. The Rwandan pre-hospital emergency care service (SAMU) uses an electronic database to evaluate and optimize pre-hospital care through a continuous quality improvement programme (CQIP), beginning March 2014. MATERIALS AND METHODS: The SAMU database was used to assess pre-hospital quality metrics including supplementary oxygen for hypoxia (O2), intravenous fluids for hypotension (IVF), cervical collar placement for head injuries (c-collar), and either splinting (splint) or administration of pain medications (pain) for long bone fractures. Targets of >90% were set for each metric and daily team meetings and monthly feedback sessions were implemented to address opportunities for improvement. These five pre-hospital quality metrics were assessed monthly before and after implementation of the CQIP. Met and unmet needs for O2, IVF, and c-collar were combined into a summative monthly SAMU Trauma Quality Scores (STQ score). An interrupted time series linear regression model compared the STQ score during 14 months before the CQIP implementation to the first 14 months after. RESULTS: During the 29-month study period 3,822 patients met study criteria. 1,028 patients needed one or more of the five studied interventions during the study period. All five endpoints had a significant increase between the pre-CQI and post-CQI periods (p<0.05 for all), and all five achieved a post-CQI average of at least 90% completion. The monthly composite STQ scores ranged from 76.5 to 97.9 pre-CQI, but tightened to 86.1-98.7 during the post-CQI period. Interrupted time series analysis of the STQ score showed that CQI programme led to both an immediate improvement of +6.1% (p=0.017) and sustained monthly improvements in care delivery-improving at a rate of 0.7% per month (p=0.028). CONCLUSION: The SAMU experience demonstrates the utility of a responsive, data-driven quality improvement programme to yield significant immediate and sustained improvements in pre-hospital care for trauma in Rwanda. This programme may be used as an example for additional efforts engaging frontline staff with real-time data feedback in order to rapidly translate data collection efforts into improved care for the injured in a resource-limited setting.
Authors: Neelima Navuluri; Maria L Srour; Peter S Kussin; David M Murdoch; Neil R MacIntyre; Loretta G Que; Nathan M Thielman; Eric D McCollum Journal: J Glob Health Date: 2021-05-08 Impact factor: 4.413
Authors: John Whitaker; Nollaig O'Donohoe; Max Denning; Dan Poenaru; Elena Guadagno; Andrew J M Leather; Justine I Davies Journal: BMJ Glob Health Date: 2021-05
Authors: Cátia C Martins Oliveira; Hillegonda Maria Dutih Novaes; Airlane Pereira Alencar; Itamar S Santos; Maria Cecilia T Damasceno; Heraldo Possolo de Souza Journal: Rev Saude Publica Date: 2019-12-02 Impact factor: 2.106