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Revista Española de Salud Pública
On-line version ISSN 2173-9110Print version ISSN 1135-5727
Abstract
PARRO MORENO, Ana et al. Nursing Workforce Characteristics and Control of Diabetes Mellitus in Primary Care: a Multilevel Analysis. Spain. Rev. Esp. Salud Publica [online]. 2016, vol.90, e40005. Epub June 07, 2021. ISSN 2173-9110.
Background:
Nurse activity is determined by the characteristics of nursing staff. The objective was to determine the impact of Primary Health Care (PHC) nursing workforce characteristics on the control of Diabetes Mellitus (DM) in adults.
Method:
Cross-sectional analytical study. Administrative and clinical registries and questionnaire PES-Nursing Work Index from PHC nurses. Participants 44.214 diabetic patients in two health zones within the Community of Madrid, North-West Zone (NWZ) with higher socioeconomic situation and South-West Zone (SWZ) with lower socioeconomic situation, and their 507 reference nurses. Analyses were performed to multivariate multilevel logistic regression models. Primary outcome measure: Poor DM control (figures ≥ 7% HbA1c).
Results:
The prevalence of poor DM control was 40.1% [CI95%: 38.2-42.1]. There was a risk of 25% more of poor control if the patient changed centre and of 27% if changed of doctor-nurse pair. In the multilevel multivariate regression models: in SWZ increasing the ratio of patients over 65 years per nurse increased the poor control (OR=1.00008 [CI95%:1.00006-1.001]); and higher proportion of patients whose Hb1Ac was not measured at the centre contributed to poor DM control (OR=5.1 [CI95%:1.6-15.6]). In two models for health zone, the economic immigration condition increased poor control, in SWZ (OR=1.3 [CI95%:1.03-1.7]); and in NWZ (OR=1.29 [CI95%:1.03-1.6]).
Conclusions:
Higher 65 years old patients ratio per nurse, economic immigration condition and a higher proportion of patients whose Hb1Ac was not measured contribute to worse DM control.
Keywords : Nursing staff; Working Environment; Primary Health Care; Diabetes Mellitus; Nurses; Multivariate analysis; Multilevel analysis.