Factors Influencing Satisfaction with Patient-Controlled Analgesia Among Postoperative Patients Using a Generalized Ordinal Logistic Regression Model

Capabilities Toward Intravenous Patient-Controlled Analgesia: A Cross-Sectional Study of Registered Nurses Working in Two Tertiary Hospitals in China and Thailand

BACKGROUND

An increased interest has been observed in the wide use of intravenous patient-controlled analgesia (IV-PCA) to control acute postoperative pain in both China and Thailand. The safety and efficacy of IV-PCA in patient care requires competent and capable staff nurses. This study aimed to appraise the capabilities of Thai and Chinese registered nurses regarding IV-PCA as a guide to develop educational programs.

METHOD

A descriptive cross-sectional survey was conducted with 203 Chinese and 270 Thai registered nurses. An anonymous self-report questionnaire addressing 6 domains of capabilities toward IV-PCA was used to collect the data. Descriptive and inferential statistics were employed to analyze the data.

RESULTS

The study found that the mean percentage scores (MPS) of the overall capability on IV-PCA of the Thai and Chinese nurse participants were 55.5 (mean [M] = 57.3, standard deviation [SD] = 4.9) and 62.6 (M = 58.7, SD = 13.0), respectively, which indicated very low and low levels. Barriers to the use and care of patients receiving IV-PCA after surgery according to the Thai and Chinese nurse participants included a lack of knowledge and systematic training regarding IV-PCA and a lack of first-hand experience in providing care for IV-PCA patients.

CONCLUSION

The study results call for intensive and effective training and education concerning all domains for registered nurses involved with patients receiving IV-PCA.

Identifying Early Opioid-Induced Respiratory Depression and Rapid Response Team Activation

BACKGROUND

Opioids can cause respiratory depression, which could lead to patient harm. The project site noted a gap in identifying and monitoring postsurgical thoracic patients at risk for opioid-induced respiratory depression (OIRD), so an evidence-based solution was sought.

AIMS

The purpose of this quality improvement project was to determine if translating the research by Khanna et al. (2020) on implementing the prediction of opioid-induced respiratory depression in patients monitored by capnography (PRODIGY) risk prediction tool would affect rapid response team (RRT) activation among postsurgical thoracic patients in a cardiovascular and thoracic care unit (CVTCU) at John Muir Medical Center, Concord Campus over four weeks.

METHODS

The four-week quantitative quasi-experimental project had a total sample size of 29 participants. Pulse oximetry was used to identify OIRD in the comparison group (n = 12). The implementation group consisted of patients identified as at-risk for OIRD by the PRODIGY risk prediction tool and were monitored with pulse oximetry and capnography (n = 17).

RESULTS

A χ2 analysis showed χ2 (1, n = 29) = .73, p = .393 for activation of the RRT using the PRODIGY risk prediction tool, which was not statistically significant. However, clinical significance was supported by a 5.9% increase in RRT activations.

CONCLUSION

Based on the results, implementing the PRODIGY risk prediction tool and capnography monitoring on at-risk patients may affect RRT activation in this population.

Patient satisfaction with post-operative pain management and associated factors among surgical patients at Tikur Anbessa Specialized Hospital: Cross-sectional study

Background

Objective

Method

Result

Conclusion

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Patient satisfaction with postoperative pain management was suboptimal.

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ASA status, pain, analgesic techniques & management were significantly associated.

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Patient satisfaction also associated with empathy, patient education, & communication.

Effective Analysis of Inpatient Satisfaction: The Random Forest Algorithm

PURPOSE

To identify the factors influencing inpatient satisfaction by fitting the optimal discriminant model.

PATIENTS AND METHODS

A cross-sectional survey of inpatient satisfaction was conducted with 3888 patients in 16 large public hospitals in Zhejiang Province. Independent variables were screened by single-factor analysis, and the importance of all variables was comprehensively evaluated. The relationship between patients' overall satisfaction and influencing factors was established, the relative risk was evaluated by marginal benefit, and the optimal model was fitted using the receiver operating characteristic curve.

RESULTS

Patients' overall satisfaction was 79.73%. The five most influential factors on inpatient satisfaction, in this order, were: patients' right to know, timely nursing response, satisfaction with medical staff service, integrity of medical staff, and accuracy of diagnosis. The prediction accuracy of the random forest model was higher than that of the multiple logistic regression and naive Bayesian models.

CONCLUSION

Inpatient satisfaction is related to healthcare quality, diagnosis, and treatment process. Rapid identification and active improvement of the factors affecting patient satisfaction can reduce public hospital operating costs and improve patient experiences and the efficiency of health resource allocation. Public hospitals should strengthen the exchange of medical information between doctors and patients, shorten waiting time, and improve the level of medical technology, service attitude, and transparency of information disclosure.