Using health worker opinions to assess changes in structural components of quality in a Cluster Randomized Trial.

Naomi Muinga; Philip Ayieko; Charles Opondo ORCID logo; Stephen Ntoburi; Jim Todd ORCID logo; Elizabeth Allen ORCID logo; Mike English; (2014) Using health worker opinions to assess changes in structural components of quality in a Cluster Randomized Trial. BMC health services research, 14 (1). 282-. ISSN 1472-6963 DOI: 10.1186/1472-6963-14-282
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BACKGROUND: The 'resource readiness' of health facilities to provide effective services is captured in the structure component of the classical Donabedian paradigm often used for assessment of the quality of care in the health sector. Periodic inventories are commonly used to confirm the presence (or absence) of equipment or drugs by physical observation or by asking those in charge to indicate whether an item is present or not. It is then assumed that this point observation is representative of the everyday status. However the availability of an item (consumables) may vary. Arguably therefore a more useful assessment for resources would be one that captures this fluctuation in time. Here we report an approach that may circumvent these difficulties. METHODS: We used self-administered questionnaires (SAQ) to seek health worker views of availability of key resources supporting paediatric care linked to a cluster randomized trial of a multifaceted intervention aimed at improving this care conducted in eight rural Kenyan district hospitals. Four hospitals received a full intervention and four a partial intervention. Data were collected pre-intervention and after 6 and 18 months from health workers in three clinical areas asked to score item availability using an 11-point scale. Mean scores for items common to all 3 areas and mean scores for items allocated to domains identified using exploratory factor analysis (EFA) were used to describe availability and explore changes over time. RESULTS: SAQ were collected from 1,156 health workers. EFA identified 11 item domains across the three departments. Mean availability scores for these domains were often <5/10 at baseline reflecting lack of basic resources such as oxygen, nutrition and second line drugs. An improvement in mean scores occurred in 8 out of 11 domains in both control and intervention groups. A calculation of difference in difference of means for intervention vs. control suggested an intervention effect resulting in greater changes in 5 out of 11 domains. CONCLUSION: Using SAQ data to assess resource availability experienced by health workers provides an alternative to direct observations that provide point prevalence estimates. Further the approach was able to demonstrate poor access to resources, change over time and variability across place.


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