Company-Sancho MC, Estupiñán-Ramírez M, Sánchez-Janáriz H, Tristancho-Ajamil R. The connection between nursing diagnosis and the use of healthcare resources.
Enferm Clin 2017;
27:214-221. [PMID:
28501464 DOI:
10.1016/j.enfcli.2017.04.002]
[Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2016] [Revised: 03/14/2017] [Accepted: 04/03/2017] [Indexed: 11/29/2022]
Abstract
AIM
The health service invests up to 75% of its resources on chronic care where the focus should be on caring rather than curing. Nursing staff focuses their work on such care. Care requires being redorded in health histories through the standardized languages. These records enable useful analyses to organisational and healthcare decision-making. Our proposal is to know the association of between nursing diagnosis and a higher total expenditure on health.
METHOD
An observational cross-sectional analytical study was performed based on data from electronic health records in Primary Care (Drago-AP), hospital discharges (CMBD-AH) and prescriptions (REC-SCS) of patients over 50 from 2012-2013 in the Canary Islands. A descriptive, bivariate and multivariate analysis was undertaken to create a predictive model on the use of resources.
INDEPENDENT VARIABLES
Sociodemographic (age, sex, type of health-care affiliation, type of prescription charge) and nursing diagnosis (ND) recorded in late 2012. Dependent variables: Resources consumed in 2013.
RESULTS
582,171 patients met the criteria for inclusion. 53.0% of them were women with an average age of 64.3 years (SD 10.8years). 53.2% were pensioners. 49% of the included population had an ND, with an average of 2.1ND per patient. The average costs per patient were 1824.62€ (with a median of 827.5€) 25 and 27 percentiles of 264.1€ and 1824.7€, respectively. The bivariate analysis showed a significant correlation between these expenses and all the demographic variables; the expenses increased when a nursing diagnosis has been made (Spearman's rank=0.37: the more diagnoses, the more expenses). In the multivariate analysis, a first linear regression with the sociodemographic variables as independent variables explains 13.7% of the variability of the logarithm of the full costs (R2=0.137). If we add to this model the presence of nursing diagnoses, the explanatory capacity reaches 19.77% (R2=0.1977).
CONCLUSION
Compared with a model that only consists of sociodemographic variables, nursing diagnoses can enhance the explanatory capacity of the use of healthcare resources.
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