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Development and validation of the Chinese surgical inpatient satisfaction and comfort questionnaire.

ABSTRACT:

Abstract

Patient feedback can provide insights to assess and improve the quality of healthcare. This study aimed to develop a measure of surgical inpatient satisfaction and comfort and examine its acceptability, validity, and reliability among discharged surgical patients.This multicenter, descriptive, cross-sectional study was conducted at three tertiary hospitals in Shaanxi Province, China. A random sample of patients admitted to the surgical inpatient departments of the three hospitals between November and December 2018 was recruited. An analysis was conducted on the acceptability, validity, and reliability of a newly developed measure of satisfaction with surgical inpatient services.A total of 1582 out of 1805 (87.6%) eligible patients completed the questionnaire (average time taken = 17.1 ± 10.3 minutes), which indicated high acceptability. Sociodemographic differences between the participants and non-participants were not significant. Using factor analysis, the following 7 dimensions (number of items: 65, variance explained: 68.0%) were identified: medical care (19 items), nursing care (15 items), environment and logistics (11 items), postoperative and hospitalization experiences (11 items), feeling nervous and afraid (4 items), operating room services (3 items), and visiting (2 items). The latent structure of the assessment was examined and validated using exploratory and confirmatory factor analyses, respectively. All item loadings were >0.4. All dimensions demonstrated satisfactory internal consistency (Cronbach's alphas = 0.83-0.96) and test-retest reliability (intra-class correlation coefficients = 0.77-0.96).The Chinese Surgical Inpatient Satisfaction and Comfort Questionnaire has strong psychometric properties and can be used to assess patient satisfaction with public hospital surgical inpatient services in China. A distinguishing feature of this questionnaire is the inclusion of a subscale that assesses comfort as a dimension of patient satisfaction. Such instruments can be used to identify the factors that should be addressed to improve the quality of patient care. Further research is needed to determine the role of assessment in quality improvement.

SUBMITTER: Liu B

PROVIDER: S-EPMC8718239 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo develop a self-administered short questionnaire to assess patient satisfaction with medical treatment for hand eczema (dermatitis) with good psychometric properties.MethodThe content of the questionnaire was determined on the basis of clinical consultation with groups of patients, from studying the existing instruments, and from discussions with a panel of seven experts. A first draft version containing 38 items organised in six dimensions was tested on a pilot sample of patients to assess its legibility. The extended version was then tested on a sample of 217 patients of both genders enrolled at 18 hospitals representative of the national distribution. The questionnaire was supplied together with the Morisky-Green compliance questionnaire, the health-related quality of life (HRQL) SF-12 questionnaire, and a visual analogue scale (VAS) of perceived health status to assess concurrent validity. The dimensionality was reduced by means of exploratory factor analysis, and reliability was evaluated on the basis of internal consistency and two halves reliability estimates. Item discriminant capability and questionnaire discriminant validity with respect to known groups of patients (by gender, principal diagnosis, age, disease severity and treatment) were also assessed.ResultsThe reduction and validation sample was composed of 54% women and 46% men, of various educational levels with an average age of 43 years (SD = 13.7). Of those who responded, 26% were diagnosed with hyperkeratotic dermatitis of the palms and 27% of the fingertips, and 47% with recurring palmar dyshidrotic eczema. The questionnaire was shortened to a version containing 17 items grouped in six dimensions: effectiveness, convenience, impact on HRQL, medical follow-up, side effects, and general opinion. Cronbach's alpha coefficient reached a value of 0.9. The dimensions showed different degrees of correlation, and the scores had a normal distribution with an average of 58.4 points (SD = 18.01). Treatment satisfaction scores attained correlations between 0.003 and 0.222 with the HRQL measures, and showed higher correlations with the effectiveness (r = 0.41) and tolerability (0.22) measures, but very low correlation with compliance (r = 0.015). Significant differences were observed between some diagnoses and treatments.ConclusionsThe shortened questionnaire proved to have good psychometric properties, providing excellent reliability, satisfactorily reproducing the proposed structure and supplying evidence of validity.

Project description:Importance:Inpatient overcrowding is associated with delays in care, including the deferral of surgical care until beds are available to accommodate postoperative patients. Timely patient discharge is critical to address inpatient overcrowding and requires coordination among surgeons, nurses, case managers, and others. This is difficult to achieve without early identification and systemwide transparency of discharge candidates and their respective barriers to discharge. Objective:To validate the performance of a clinically interpretable feedforward neural network model that could improve the discharge process by predicting which patients would be discharged within 24 hours and their clinical and nonclinical barriers. Design, Setting, and Participants:This prognostic study included adult patients discharged from inpatient surgical care from May 1, 2016, to August 31, 2017, at a quaternary care teaching hospital. Model performance was assessed with standard cross-validation techniques. The model's performance was compared with a baseline model using historical procedure median length of stay to predict discharges. In prospective cohort analysis, the feedforward neural network model was used to make predictions on general surgical care floors with 63 beds. If patients were not discharged when predicted, the causes of delay were recorded. Main Outcomes and Measures:The primary outcome was the out-of-sample area under the receiver operating characteristic curve of the model. Secondary outcomes included the causes of discharge delay and the number of avoidable bed-days. Results:The model was trained on 15 201 patients (median [interquartile range] age, 60 [46-70] years; 7623 [50.1%] men) discharged from inpatient surgical care. The estimated out-of-sample area under the receiver operating characteristic curve of the model was 0.840 (SD, 0.008; 95% CI, 0.839-0.844). Compared with the baseline model, the neural network model had higher sensitivity (52.5% vs 56.6%) and specificity (51.7% vs 82.6%). The neural network model identified 65 barriers to discharge. In the prospective study of 605 patients, causes of delays included clinical barriers (41 patients [30.1%]), variation in clinical practice (30 patients [22.1%]), and nonclinical reasons (65 patients [47.8%]). Summing patients who were not discharged owing to variation in clinical practice and nonclinical reasons, 128 bed-days, or 1.2 beds per day, were classified as avoidable. Conclusions and Relevance:This cohort study found that a neural network model could predict daily inpatient surgical care discharges and their barriers. The model identified systemic causes of discharge delays. Such models should be studied for their ability to increase the timeliness of discharges.

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Development and validation of the Chinese surgical inpatient satisfaction and comfort questionnaire.

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