Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Babali Nursing Research

Ethnocaring Model in Predicting Patient Satisfaction: How Powerful Is It? Novian Mahayu Adiutama; Wardah Fauziah
Babali Nursing Research Vol 3 No 3 (2022): November
Publisher : Babali Health

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (256.83 KB) | DOI: 10.37363/bnr.2022.33175

Abstract

Introduction: Caring is the most important to get patient satisfaction. However, currently caring is only considered as empathy without regard to the patient's cultural background. This study aims to investigate patient satisfaction regarding nursing services in a multicultural area by using the ethnocaring model as a predictor. Methods: A cross-sectional study was conducted on patients in a nursing service in Subang District (n = 135 using consecutive sampling). Maintaining beliefs (MB), culture care preservation (CP), knowing (KN), being with (BW), negotiating (NE), doing for (DF), enabling (EN), and restructuring (RE) are used as independent variables, and patient satisfaction (PS) as the dependent variable. The instrument used was developed in accordance with ethnocaring model and PSQ-18. Multiple linear regression was used to analyze the ability of the ethnocaring model as a predictor of patient satisfaction. Results: The results showed that patient satisfaction had a mean score of 14.42 (score interval = 0-18). The following are the p-values for each variable: MB (0.021); CP (0.032); KN (0.015); BW (0.038); NE (0.026); DF (0.033); EN (0.043); and RE (0.034); they can all significantly predict PS with R-Square = 0.815. Conclusion: The strength of the ethnocaring model in predicting patient satisfaction was 81.5%. The construct of ethnocaring model could help nurses in understanding patient satisfaction.
The Implementation of Early Warning Score for Early Detection of Death in Adult Inpatient Rooms Wardah Fauziah; Novian Mahayu Adiutama
Babali Nursing Research Vol 3 No 3 (2022): November
Publisher : Babali Health

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (256.019 KB) | DOI: 10.37363/bnr.2022.33191

Abstract

Introduction: The Early Warning Score (EWS) can be used to predict the likelihood of short-term and long-term death. It is associated with abnormalities in the condition of vital signs of patients who are at high risk of death, regardless of the intervention or timeliness of medical personnel. Methods: This research is an innovation for the management of Evidence-based practice-based nursing actions. It was conducted using quantitative research (quasi-experiment) using post-test design with control group. The populations were all hospitalized patients in the adult room of the Subang Hospital. Results: The result showed that the Gross Death Rate in the control group of 29 people with a percentage of 10.54% of the total number of respondents is 275. Then, in the intervention group, the GDR figure was a small percentage of 12 people with a percentage of 4.36%. Meanwhile, the Net Death Rate in the control group was 9 people with a percentage of 3.27%. In the intervention group, the number of NDR was small, namely 4 people with a percentage of 1.45%. Conclusion: Based on the results and analysis of statistical tests that have been conducted on the implementation of the application of Early Warning Score (EWS), it was found that the detection of early death intervention group is lower than the control group. Early Warning scores significantly decreased the GDR and NDR in the intervention group compared to the control group.