Using linked hospitalisation data to detect nursing sensitive outcomes: A retrospective cohort study.

Background: Nursing sensitive outcomes are adverse patient health outcomes that have been shown to be associated with nursing care. Researchers have developed specific algorithms to identify nursing sensitive outcomes using administrative data sources, although contention still surrounds the ability...

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Publicado en:International Journal of Nursing Studies Vol. 51; no. 3; pp. 470 - 479
Autores principales: Schreuders, Louise Winton, Bremner, Alexandra P., Geelhoed, Elizabeth, Finn, Judith
Formato: equations & formulas research tables/charts Journal Article
Publicado: Elsevier B.V. 2014
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Using linked hospitalisation data to detect nursing sensitive outcomes: A retrospective cohort study.
      aug:
        au:
          Schreuders, Louise Winton
          Bremner, Alexandra P.
          Geelhoed, Elizabeth
          Finn, Judith
        affil: University of Western Australia, Australia
      sug:
        subj:
          Quality of Nursing Care
          Hospitalization
          Medical Record Linkage
          Clinical Indicators
          Nursing Outcomes
          Outcome Assessment
          Human
          Funding Source
          Prospective Studies
          Hospitals, Urban
          Western Australia
          Retrospective Design
          Survival Analysis
          International Classification of Diseases
          Scales
          Data Analysis Software
          T-Tests
          Chi Square Test
          Male
          Female
          Adult
          Middle Age
          Aged
          Aged, 80 and Over
          Inpatients
          Length of Stay
          Algorithms
          Confidence Intervals
          Descriptive Statistics
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Aged, 80 & over
          Male
          Female
      ab: Background: Nursing sensitive outcomes are adverse patient health outcomes that have been shown to be associated with nursing care. Researchers have developed specific algorithms to identify nursing sensitive outcomes using administrative data sources, although contention still surrounds the ability to adjust for pre-existing conditions. Existing nursing sensitive outcome detection methods could be improved by using lookback periods that incorporate relevant health information from patient's previous hospitalisations. Design and setting: Retrospective cohort study at three tertiary metropolitan hospitals in Perth, Western Australia. Objectives: The objective of this research was to explore the effect of using linked hospitalisation data on estimated incidence rates of eleven adverse nursing sensitive outcomes by retrospectively extending the timeframe during which relevant patient disease information may be identified. The research also explored whether patient demographics and/or the characteristics of their hospitalisations were associated with nursing sensitive outcomes. Results: During the 5 year study period there were 356,948 hospitalisation episodes involving 189,240 patients for a total of 2,493,654 inpatient days at the three tertiary metropolitan hospitals. There was a reduction in estimated rates for all nursing sensitive outcomes when a look-back period was applied to identify relevant health information from earlier hospitalisations within the preceding 2 years. Survival analysis demonstrates that the majority of relevant patient disease information is identified within approximately 2 years of the baseline nursing sensitive outcomes hospitalisation. Compared to patients without, patients with nursing sensitive outcomes were significantly more likely to be older (70 versus 58 years), female, have Charleson comorbidities, be direct transfers from another hospital, have a longer inpatient stay and spend time in intensive care units (p ≤ 0.001). Conclusions: The results of this research suggest that nursing sensitive outcome rates may be over-estimated using current detection methods. Linked hospitalisation data enables the use of look-back periods to identify clinically relevant diagnosis codes recorded prior to the hospitalisation in which a nursing sensitive outcome is detected. Using linked hospitalisation data to incorporate look-back periods offers an opportunity to increase the accuracy of nursing sensitive outcome detection when using administrative data sources.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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