Development and Evaluation of an electronic data management platform for a short-form Inpatient Experience with Nursing Care Scale (IPENCS)

Abstract

This thesis presents our study on the development of the electronic data management platform for the short-form Inpatient Experience with Nursing Care Scale (IPENCS). Our objectives were 1) to develop and validate a short-form Inpatient Experience with Nursing Care Scale (IPENCS), 2) to construct an electronic data management platform, and 3) to evaluate its usability. Our study comprised three stages. First, we conducted a cross-sectional study using questionnaires (Stage 1) with adult inpatients (n=1,565) from ZhongShan Hospital of Fudan University in Shanghai, China to develop the short form of the original 30-item IPENCS. We used multiple regression to analyse our data summing up the scores as outcome variables and pertinent items as individual predictor variables (primary objective). Next, a content validation was conducted through an expert panel (n=12). We also used the Marginal Maximum Likelihood Estimate from the Item Response Theory (IRT) to estimate the parameters of each item with the following criteria as 1) Item Discrimination, (2) Item Difficulty, and (3) Item information function (IIF). To examine the validity and reliability of the short-form IPENCS, we used Pearson correlation analysis and Cronbach's alpha. Second, we conducted a need analysis of nursing managers (n=13) for the platform construction by using descriptive qualitative methods to construct the electronic data management platform, exploring explore their needs for the function and required modules (Stage 2). After finishing the platform construction, quantitative and qualitative methods were conducted with nursing managers (n=20) and patients (n=12) to evaluate its usability (Stage 3). In stage 1, we developed the 17-item short-form IPENCS preserving the seven-domain structure of the original IPENCS. It showed high correlations with the full IPENCS for total score. The Cronbach's alpha coefficient also exceeded 0.9 which indicated an excellent internal consistency. In stage 2, the final version of the electronic data management platform was implemented into the hospital internal system in early December 2023. The electronic data management platform consisted of two parts: a message port and a web port. The message port has relatively simple function which was used to send short-form IPENCS to patients. The web port was comprised of three parts: the patient port was used to verify the situation of the questionnaire delivery and also stored detailed information about patient communications; the management port was designed for managers of the nursing department to access comprehensive results of short-form IPENCS for the entire hospital, along with corresponding platform-generated analysis; and the clinical port was intended for head nurses in various clinical departments and wards, the system gave them the authorization to view short-form IPENCS scores and analysis for their respective areas of responsibility. In stage 3, the overall SUS mean score was 88.38, which showed good usability of the platform. The qualitative results of nursing managers were making simplified and understandable interface presentation with special annotations; fixing data update delay and adding data review function; introducing new platform features for deeper data insights. The qualitative results of patients leaned towards questionnaire delivery time and recipients; enhancing interface simplicity and user-friendliness; emphasizing the measurement of nursing care experience in text messages; adding feedback mechanisms and interactive platforms. In conclusion, this study showcased the combinations of four methods which contained both CTT and IRT to simplify the IPENCS scale, creating a good foundation for the subsequent platform construction. It showed good validity and reliability to be used in the electronic data management platform. The electronic data management platform showed good usability for both patients and nursing managers. It served as a viable solution to collect and analyze patient experience with nursing care data for quality improvement.