Validation of a new method for patient classification, the Oulu Patient Classification

J Adv Nurs. 2000 Feb;31(2):481-90. doi: 10.1046/j.1365-2648.2000.01277.x.


At Vasa Central Hospital in Western Finland a further development of the Oulu Patient Classification (OPC) has been made by the development of weight coefficients and by estimating the nursing care intensity per nurse. The daily level of nursing care intensity of a ward is expressed by the number of nursing care intensity points per nurse. This article presents results from a validity test of the OPC at Vasa Central Hospital. The test was carried out by comparing the daily patient classifications by means of the OPC against measurements made by means of a new measuring instrument, the 'Professional Assessment of Optimal Nursing Care Intensity Level' (PAONCIL) developed at the Vasa Central Hospital. The study was implemented in eight wards during a period of 3 months. The data material consisted of two parts, the daily patient classifications based on the OPC (n = 19 324) and the measurements by means of the PAONCIL forms (n = 8458). Simple and multiple linear regression analyses were used as statistical methods in quantifying the linear relationship between the two interval-scaled variables. In the test of concurrent validity the coefficient of determination was 0.366, i.e. the association between these two indicators is fairly strong (36.6%). The testing of construct validity showed that the construct validity of the indicator hardly deteriorates as a result of the patients being placed in separate nursing care intensity categories. There was a clear correlation between the scores allotted by the indicator to the six different sub-areas of nursing care. When examining the construct validity of the OPC, no factors with independent explanatory power in predicting PAONCIL values were discovered other than those of the OPC. The OPC proved on the basis of this research material and these statistical methods to possess fairly adequate validity, and thus there is a good basis for further research and a development of nursing care.

Publication types

  • Comparative Study

MeSH terms

  • Analysis of Variance
  • Classification / methods
  • Finland
  • Hospitals, University
  • Humans
  • Linear Models
  • Nursing Care / classification
  • Nursing Care / statistics & numerical data
  • Patients / classification*
  • Patients / statistics & numerical data
  • Reproducibility of Results