Nursing Diagnoses in the Care of the Hospitalized Patient with Type 2 Diabetes Mellitus: Pattern Analysis and Correlates of Health Disparities Public Deposited

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  • March 22, 2019
  • Onori, Kennedy O.
    • Affiliation: School of Nursing
  • This study examined the human needs of 445 adults admitted to hospital with the primary medical diagnosis of Type 2 Diabetes Mellitus [ICD-9CM 250.0-9] and compared the pattern of nursing diagnoses (human needs) with those of 5321 patients having Type 2 DM but admitted to hospital for other reasons and with the 78,480 inpatients with no DM. Length of hospital stay, intensive care unit use and discharge dispositions were examined, controlling for race, poverty, marital status and age, to determine if the nursing diagnosis variables were distinctive for any of the three patient groups. A subset of 14 nursing diagnoses was identified from the literature on the care of Type 2 DM to determine how they varied among the three groups. The 61 nursing diagnoses were also fitted in regression models to explain variances in patient length of stay and to explore patient diabetes status. A multinomial logistic (logit) regression model that included the predictor variables of patient age, race, marital status, socioeconomic position (insurance type), and sex was used to predict patient discharge disposition. This study was a secondary analysis of data collected over a three-year period by nurses in the daily assessment and care of their hospitalized patients. Donabedian's structure, process, and outcome model of quality of care provided the conceptual framework for this study. The statistical software SAS (9.3) was used for the analysis. Nursing diagnosis use pattern did not consistently distinguish patients with type 2 diabetes mellitus from other patients. Patient information gathered by nurses in the provision of care to their patients is qualitative in nature -with holistic perspective independent of International Classification of Diseases codes. Nursing diagnosis was related to patient length of stay. The number of different nursing diagnoses was the most important predictor of patient length of stay in a model that included patient age, sex, marital status and socioeconomic position. Patient race, age, and socioeconomic position were predictive of patient discharge disposition (discharge to own home, discharge to home with home health services, discharge to nursing homes, or discharge to other healthcare facility) but not substantially related to patient length of stay. This methodological study has helped address two related questions in the negative; when the disease is known are the needs of the patient known and when the needs of the patient are known, is the disease known?
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  • In Copyright
  • Halloran, Edward Joseph
  • Doctor of Philosophy
Graduation year
  • 2013

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