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022			_a2055-2076
022			_aOnline 2055-2076
040			_cddc
041			_aEnglish
100			_qPeter Andrew Meaney
245			_a Development of pediatric acute care education (PACE) _b An adaptive electronic learning (e-learning) environment for healthcare providers in Tanzania
260			_aMwanza, Tanzania : _bCatholic University of Health and Allied Sciences [CUHAS-Bugando] : _c2023
300			_aPages 01-02
300			_aIncludes References
490			_vDigital Health Volume 9 January-December 2023
520			_aAbstract : Globally, inadequate healthcare provider (HCP) proficiency with evidence-based guidelines contributes to millions of newborn, infant, and child deaths each year. HCP guideline proficiency would improve patient outcomes. Conventional (in person) HCP in-service education is limited in 4 ways: reach, scalability, adaptability, and the ability to contextualize. Adaptive e-learning environments (AEE), a subdomain of e-learning, incorporate artificial intelligence technology to create a unique cognitive model of each HCP to improve education effectiveness. AEEs that use existing internet access and personal mobile devices may overcome limits of conventional education. This paper provides an overview of the development of our AEE HCP in-service education, Pediatric Acute Care Education (PACE). PACE uses an innovative approach to address HCPs’ proficiency in evidence-based guidelines for care of newborns, infants, and children. PACE is novel in 2 ways: 1) its patient-centric approach using clinical audit data or frontline provider input to determine content and 2) its ability to incorporate refresher learning over time to solidify knowledge gains. We describe PACE's integration into the Pediatric Association of Tanzania's (PAT) Clinical Learning Network (CLN), a multifaceted intervention to improve facility-based care along a single referral chain. Using principles of co-design, stakeholder meetings modified PACE's characteristics and optimized integration with CLN. We plan to use three-phase, mixed-methods, implementation process. Phase I will examine the feasibility of PACE and refine its components and protocol. Lessons gained from this initial phase will guide the design of Phase II proof of concept studies which will generate insights into the appropriate empirical framework for (Phase III) implementation at scale to examine effectiveness.
600			_xeHealth
600			_xGeneral
600			_xDigital health
600			_x General education
600			_xLifestyle
600			_xSmartphone
600			_xMedia paediatrics
600			_x Medicine
600			_xmHealth
600			_xPsychology
600			_xMixed methods
600			_x Studies
700			_qAdolfine Hokororo
700			_qTheopista Masenge
700			_qJoseph Mwanga
700			_q Florence Salvatory Kalabamu
700			_q Marc Berg
700			_qBoris Rozenfeld
700			_q Zachary Smith
700			_qNeema Chami
700			_q Namala Mkopi
700			_qCastory Mwanga
700			_qAmbrose Agweyu
856			_uhttps://doi.org/10.1177/20552076231180471 _yhttps://doi.org/10.1177/20552076231180471
942			_2ddc _cVM _n0
999			_c28021 _d28021