Nursing knowledge captured in electronic health records

Psychometric Testing of the Slovene Version of the Perceived Inventory of Technological Competency as Caring in Nursing

The Perceived Inventory of Technological Competency as Caring in Nursing (PITCCN) questionnaire has been designed to measure technological competency as caring in nursing practice. It incorporates the use of technology with the fundamental principles of caring that are central to nursing. As there were no psychometrically sound instruments to quantify the concept of technological competency as caring in the Slovene language, we adapted the English version of the questionnaire to the local environment. The goal was to assess the level of psychometric properties of the PITCCN investigated in Slovene hospitals.

METHODS

Content validity was conducted with eight experts and quantified by the content validity index (CVI) and the modified Cohen's kappa index. Face validity was assessed through discussions with participants from the target culture in the pilot study. To assess construct validity and internal consistency, a cross-sectional research methodology was used on a convenience sample of 121 nursing personnel from four hospitals. Principal component analysis (PCA) was used to examine construct validity, while Cronbach's alpha and adjusted item-total correlations were used to measure internal consistency.

RESULTS

The content and face validity of PITCCN were adequate. The scale validity index (S-CVI) was 0.97. Cronbach's α was 0.92, and subscale reliabilities ranged from 0.810 to 0.925. PCA showed four components, which explained more than 73.49% of the variance.

CONCLUSIONS

The Slovenian version of PITCCN (PITCCN_SI) has good psychometric properties.

Identifying nursing sensitive indicators from electronic health records in acute cardiac care-Towards intelligent automated assessment of care quality

AIM

The aim of this study is to explore the potential of using electronic health records for assessment of nursing care quality through nursing-sensitive indicators in acute cardiac care.

BACKGROUND

Nursing care quality is a multifaceted phenomenon, making a holistic assessment of it difficult. Quality assessment systems in acute cardiac care units could benefit from big data-based solutions that automatically extract and help interpret data from electronic health records.

METHODS

This is a deductive descriptive study that followed the theory of value-added analysis. A random sample from electronic health records of 230 patients was analysed for selected indicators. The data included documentation in structured and free-text format.

RESULTS

One thousand six hundred seventy-six expressions were extracted and divided into (1) established and (2) unestablished expressions, providing positive, neutral and negative descriptions related to care quality.

CONCLUSIONS

Electronic health records provide a potential source of information for information systems to support assessment of care quality. More research is warranted to develop, test and evaluate the effectiveness of such tools in practice.

IMPLICATIONS FOR NURSING MANAGEMENT

Knowledge-based health care management would benefit from the development and implementation of advanced information systems, which use continuously generated already available real-time big data for improved data access and interpretation to better support nursing management in quality assessment.

A mixed-methods study of quality differences between applied documentation approaches in nursing homes

BACKGROUND

Several approaches to nursing documentation exist. Some address standardised terminology and daily monitoring, whereas the structural model approach focuses on open-ended text information and special incidents. This study aims to identify quality differences between available documentation approaches from the perspectives of nursing professionals in Germany.

METHODS

Between October 2018 and May 2019, a convenience sample of German nursing home practitioners was surveyed concerning the quality of their documentation techniques. The quality measurement was developed from the findings of a literature review on indicators that define successful nursing documentation. Selected indicators were structured according to Donabedian's quality dimensions of structure, process, and outcome. A mean score was calculated for each quality dimension. Non-parametric tests were employed to discover whether organisational and person-related conditions affect score values. The framework method was used to analyse textual data.

RESULTS

Responses from 250 nursing care practitioners show significant differences between users of different documentation approaches in the outcome dimension. Nurses who worked with the structural model were slightly more satisfied with their documentation approach than users of other approaches. In addition, differences between subgroups were identified depending on the mode of the tools employed for nursing documentation, participation in training, and length of time spent using the present documentation tool. Qualitative data reveal that digitalisation, unequal task distribution, and appreciation and motivation are critical topics in nursing homes.

CONCLUSIONS

The results indicate that regular opportunities to reflect on challenges in documentation activities might increase nurses' perceptions of documentation as a valuable part of nursing care. Training might serve this purpose for users of non-structural model approaches. Regardless of the specific recording techniques employed, more investment in digital infrastructure is required.