Optimizing health IT to improve health system performance: A work in progress

Healthcare ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 100483 ◽  
Author(s):  
Robert S. Rudin ◽  
Shira H. Fischer ◽  
Cheryl L. Damberg ◽  
Yunfeng Shi ◽  
Paul G. Shekelle ◽  
...  
Keyword(s):  
Health System ◽  
System Performance ◽  
Health System Performance ◽  
Health It ◽  
Work In Progress ◽  
Improve Health System ◽  
Improve Health

scholarly journals Stakeholder Views on Solutions to Improve Health System Performance

2018 ◽  
Vol 14 (1) ◽  
pp. 71-85 ◽  
Author(s):  
Astrid Brousselle ◽  
Damien Contandriopoulos ◽  
Jeannie Haggerty ◽  
Mylaine Breton ◽  
Michèle Rivard ◽  
...  
Keyword(s):  
Health System ◽  
System Performance ◽  
Health System Performance ◽  
Stakeholder Views ◽  
Improve Health System ◽  
Improve Health

Budgeting practices to improve health system performance

2019 ◽  
Vol 19 (3) ◽  
Author(s):  
Chris James ◽  
Ivor Beazley ◽  
Luciana Rosato ◽  
Caroline Penn
Keyword(s):  
Health System ◽  
System Performance ◽  
Health System Performance ◽  
Improve Health System ◽  
Improve Health

scholarly journals Evaluating the design and implementation fidelity of an adapted Plan-Do-Study-Act approach to improve health system performance in a Nigerian state

2020 ◽  
Author(s):  
Ejemai Amaize Eboreime ◽  
John Olajide Olawepo ◽  
Aduragbemi Banke-Thomas ◽  
Rohit Ramaswamy
Keyword(s):  
Health System ◽  
System Performance ◽  
Implementation Fidelity ◽  
Health System Performance ◽  
Design And Implementation ◽  
Use Of Data ◽  
Pdsa Cycle ◽  
Implementation Gaps ◽  
Improve Health System ◽  
Improve Health

AbstractBackgroundThe Plan-Do-Study-Act (PDSA) cycle is fundamental to many quality improvement (QI) models. For the approach to be effective in the real-world, variants must align with standard elements of the PDSA. This study evaluates the alignment between theory, design and implementation fidelity of a PDSA variant adapted for Nigeria’s health system performance improvement.MethodsAn iterative consensus building approach was used to develop a scorecard evaluating new conceptual indices of design and implementation fidelity of QI interventions (design and implementation index, defects and gaps) based on Taylor’s theoretical framework.ResultsDesign (adaptation) scores were optimal across all standard features indicating that design was well adapted to the typical PDSA. Conversely, implementation fidelity scores were only optimal with two standard features: prediction-based test of change and the use of data over time. The other features, use of multiple iterative cycles and documentation had implementation gaps of 17% and 50% respectively.ConclusionThis study demonstrates how both adaptation and implementation fidelity are important for success of QI interventions. It also presents an approach for evaluating other QI models using Taylor’s PDSA assessment framework as a guide, which might serve to strengthen the theory behind future QI models and provide guidance on their appropriate use.

Sign in / Sign up

Export Citation Format

Share Document