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Determination of Nursing Care Times Based on the Perroca Patient Classification Instrument in the Inpatient Oncology
Güzin Ayan1, Emine Türkmen2, Esra Uğur3
1Department of Medical Services and Techniques, Kutahya University of Health Sciences, Gediz Vocational of Health Services, Kutahya, Turkey.
Seminars in Oncology Nursing
|February 24, 2024
Summary
This study determined daily nursing care times for oncology patients using the Perroca Patient Classification tool. Higher patient acuity scores correlated with increased nursing care hours, aiding in staff assignment planning.
Area of Science:
- Nursing
- Oncology
- Healthcare Management
Background:
- Accurate patient classification is crucial for effective nursing resource allocation in oncology units.
- The Perroca Patient Classification Instrument (PPCI) is a tool to assess patient acuity.
- Understanding daily nursing care time requirements based on acuity is essential for optimizing staffing.
Purpose of the Study:
- To determine the daily nursing care times for hospitalized inpatient oncology patients.
- To correlate nursing care duration with patient acuity levels as measured by the Perroca Patient Classification tool.
Main Methods:
- A mixed-method sequential explanatory design was employed.
- Quantitative data collected via the Nursing Activity Record Form and PPCI, with 175 hours of time-motion study.
- Qualitative data gathered through semi-structured interviews with seven nurses, analyzed thematically.
Main Results:
- Daily nursing care duration ranged from 2-2.5 hours for Type 1 to 4.76-5.5 hours for Type 4 patients.
- A positive correlation was found between patient acuity grade (PPCI) and nursing care hours.
- The PPCI demonstrated discriminative ability in assessing patient acuity.
Conclusions:
- Nursing care hours increase with higher patient acuity in oncology units.
- The PPCI is an effective tool for differentiating patient acuity and informing care time allocation.
- Findings support nurse managers in planning assignments sensitive to patient needs and analyzing staffing-outcome relationships.
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