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Measuring implementation progress in kangaroo mother care
Author(s) -
Bergh Annemarie,
Arsalo Irmeli,
Malan Atties F,
Patrick Mark,
Pattinson Robert C,
Phillips Noel
Publication year - 2005
Publication title -
acta pædiatrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 115
eISSN - 1651-2227
pISSN - 0803-5253
DOI - 10.1111/j.1651-2227.2005.tb02052.x
Subject(s) - medicine , outreach , construct (python library) , implementation research , institutionalisation , scale (ratio) , psychological intervention , health care , process (computing) , process management , monitoring and evaluation , nursing , computer science , physics , business , quantum mechanics , psychiatry , political science , law , economics , programming language , economic growth , operating system
Aim: To describe the development and testing of a monitoring model with quantitative indicators or progress markers that could measure the progress of individual hospitals in the implementation of kangaroo mother care (KMC). Methods: Three qualitative data sets in the larger research programme on the implementation of KMC of the MRC Research Unit for Maternal and Infant Health Care Strategies in South Africa were used to develop a progress‐monitoring model and an accompanying instrument. Results: The model was conceptualized around three phases (pre‐implementation, implementation and institutionalization) and six constructs depicting progress (awareness, adopting the concept, mobilization of resources, evidence of practice, evidence of routine and integration, sustainable practice). For each construct, indicators were developed for which data could be collected by means of the monitoring instrument used in a walk‐through visit to a hospital. The instrument has been tested in 65 hospitals. Conclusion: The progress‐monitoring model enables the quantification of individual hospitals' progress in the process of implementing KMC and an objective measurement of the effectiveness of different outreach strategies. The model also has potential to be adapted for measuring progress in other innovative healthcare interventions on a large scale.