Explore the vast range of titles available.

This study aimed to explore the gap between patients' expectations of healthcare service quality in ‎Jordanian hospitals against their perceptions of service received using SERVQUAL model. The study used a cross-sectional design. The study data were collected randomly from 415 patients (participants) ‎who completed the SERVEQUAL questionnaire. The data were analyzed using ‎statistical procedures such as descriptive, -test, and ANOVA. The results showed ‎that there is a gap between mean score of patients' expectations of what should be available in the ‎hospital and patients' perceptions of the service received in the hospital. Patients' expectations were higher than their perceptions on all five SERVQUAL domains (Tangibles, Reliability, Responsiveness, Assurance, and Empathy). Hospital managers should take necessary actions to improve healthcare services in their hospitals with respect to all SERVQUAL domains. These actions should be directed to reduce the gap between patients' expectation and their perceptions in order to provide services meet patients' needs.

Background Reducing 30-day hospital readmissions has become a focus of the current national payment policies. Medicare requires that hospitals collect and report patients’ experience with their care as a condition of payment. However, the extent to which patients’ experience with hospital care is related to hospital readmission is unknown. Methods We established multivariate regression models in which 30-day risk-adjusted readmission rates were the dependent variables and patients’ perceptions of the responsiveness of the hospital staff and communication (as measured by the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores) were the independent variables of interest. We selected six different clinical conditions for analyses, including acute myocardial infarction (AMI), chronic obstructive pulmonary disease (COPD), heart failure, hip/knee surgery, pneumonia, and stroke. Data included all acute care hospitals reporting in Hospital Compare in 2014. Results The number of hospitals with reported readmissions ranged from 2234 hospitals for AMI to 3758 hospitals for pneumonia. The average 30-day readmission rates ranged from 5.19% for knee/hip surgery to 22.7% for COPD. Patient experience of hospital-staff responsiveness as “top-box” ranged from 64% to 67% across the six clinical conditions, communication with nurses ranged from 77% to 79% and communication with doctors ranged from 80% to 81% (higher numbers are better). Our finding suggests that hospitals with better staff responsiveness were significantly more likely to have lower 30-day readmissions for all conditions. The effect size depended on the baseline readmission rates, with the largest effect on hospitals in the upper 75th quartile. A ten-percentage-point increase in staff responsiveness led to a 0.03–0.18 percentage point decrease in readmission rates. We found that neither communication with physicians nor communication with nurses was significantly associated with hospital readmissions. Conclusions Our findings suggest that elements of care related to staff responsiveness during patients’ stay may influence rehospitalization rates. Changes in staff responsiveness may offer an additional tool for hospitals to employ ongoing efforts to achieve reductions in readmissions, an important objective both financially and for patient health outcomes.

The main objective of this study was to assess quality of life (QoL) and treatment satisfaction in a group of patients with type 1 diabetes (T1D) and explore their needs regarding and their perception of QoL living with diabetes. Patients with type 1 diabetes attending the outpatient endocrinology clinics of a reference hospital were invited to participate in a cross-sectional study. Clinical and sociodemographic data were obtained (interview and clinical records), and diabetes-related QoL was assessed using a standardized questionnaire. In 67 participants, satisfaction with treatment was also assessed, and an open interview was performed, assessing the impact of diabetes, long-term worries, flexibility, restrictions, and self-perception of QoL. Descriptive statistical analysis, bivariate analysis, and multivariate analysis were performed in order to find factors associated with QoL. Interviews were analyzed and summarized questionwise. Mean patient age was 31.4±11.6 years, diabetes duration 14.2±9.3 years, and glycated hemoglobin (HbA1c) 8.5%±1.9% (69±20.8 mmol/mol International Federation of Clinical Chemistry [IFCC]). The questionnaires showed good average QoL scores (94.6+22.9) and treatment satisfaction scores (25.7±6.7). QoL worsened with increasing HbA1c, female sex, severity of complications, and lower education (r (2)=0.283, P<0.005). In the open interview, 68.5% of the patients reported that diabetes had changed their lives, 83.5% identified complications as their most important long-term concern, and 59.7% said that they needed more training to manage the disease. Poor glycemic control, lower education, complications, and female sex are associated with worse QoL. Semi-structured interviews identified aspects not included in the standardized questionnaires.

Objective Nursing care is one of the most important components of health care and patient expectation toward nursing care is being rising. Accordingly, patients’ expectation needs to be managed adequately in order to improve outcomes and decrease liability through their perception. To improve the outcome based on the expectation of patients, we need to consider patients’ perception to the care they received. So this study aims to identifies the perceptions toward nursing care and their associated factors. Result From a total of 281 admitted patients 151 (53.7%) were females; 136 (48.4%) were found in the age group of 21–30 years with mean age of 30 (11 ± SD) years. The mean score of overall perception were 62.6 ± 17.9 (95% CI 60.79–64.37). Among all 154 (54.8%) participants had poor perception to nursing care. Occupation, ward and expectation had association with perception. Patient’s level of perception towards nursing care was poor (54.7%) and ward where patients admitted, expectation of patients, occupation of patients and duration of hospital stay were significantly associated with patients’ perception. So that health institutions and nurses should focus on perception of their clients.

Background Many terminally ill patients in Bosnia-Herzegovina (BiH) fail to receive needed medical attention and social support. In 2016 a primary healthcare centreer (PHCC) in Doboj (BiH) requested the methodological and technical support of a local partner (Fondacija fami) and the Geneva University Hospitals to address the needs of terminally ill patients living at home. In order to design acceptable, affordable and sustainable solutions, we involved patients and their families in exploring needs, barriers and available resources. Methods We conducted interviews with 62 purposely selected patients using a semi-structured interview guide designed to elicit patients’ experiences, needs and expectations. Both qualitative and quantitative analyses were conducted, using an inductive thematic approach. Results While patients were aware that their illnesses were incurable, they were poorly informed about medical and social support resources available to them. Family members appeared to be patients’ main source of support, and often suffered from exhaustion and financial strain. Patients expressed feelings of helplessness and lack of control over their health. They wanted more support from health professionals for pain and other symptom management, as well as for anxiety and depression. Patients who were bedridden or with reduced mobility expressed strong feelings of loneliness, social exclusion, and stigma from community members and – occasionally - from health workers. Conclusions Our findings suggest a wide gap between patients’ end-of-life care needs and existing services. In order to address the medical, psychological and social needs of terminally ill patients, a multi-pronged approach is called for, including not only better symptom management through training of health professionals and improved access to medication and equipment, but also a coordinated inter-professional, inter-institutional and multi-stakeholder effort aimed at offering comprehensive medical, psycho-social, educational and spiritual support.

Artificial intelligence and the language models derived from it, such as ChatGPT, offer immense possibilities, particularly in the field of medicine. It is already evident that ChatGPT can provide adequate and, in some cases, expert-level responses to health-related queries and advice for patients. However, it is currently unknown how patients perceive these capabilities, whether they can derive benefit from them, and whether potential risks, such as harmful suggestions, are detected by patients. This study aims to clarify whether patients can get useful and safe health care advice from an artificial intelligence chatbot assistant. This cross-sectional study was conducted using 100 publicly available health-related questions from 5 medical specialties (trauma, general surgery, otolaryngology, pediatrics, and internal medicine) from a web-based platform for patients. Responses generated by ChatGPT-4.0 and by an expert panel (EP) of experienced physicians from the aforementioned web-based platform were packed into 10 sets consisting of 10 questions each. The blinded evaluation was carried out by patients regarding empathy and usefulness (assessed through the question: \"Would this answer have helped you?\") on a scale from 1 to 5. As a control, evaluation was also performed by 3 physicians in each respective medical specialty, who were additionally asked about the potential harm of the response and its correctness. In total, 200 sets of questions were submitted by 64 patients (mean 45.7, SD 15.9 years; 29/64, 45.3% male), resulting in 2000 evaluated answers of ChatGPT and the EP each. ChatGPT scored higher in terms of empathy (4.18 vs 2.7; P<.001) and usefulness (4.04 vs 2.98; P<.001). Subanalysis revealed a small bias in terms of levels of empathy given by women in comparison with men (4.46 vs 4.14; P=.049). Ratings of ChatGPT were high regardless of the participant's age. The same highly significant results were observed in the evaluation of the respective specialist physicians. ChatGPT outperformed significantly in correctness (4.51 vs 3.55; P<.001). Specialists rated the usefulness (3.93 vs 4.59) and correctness (4.62 vs 3.84) significantly lower in potentially harmful responses from ChatGPT (P<.001). This was not the case among patients. The results indicate that ChatGPT is capable of supporting patients in health-related queries better than physicians, at least in terms of written advice through a web-based platform. In this study, ChatGPT's responses had a lower percentage of potentially harmful advice than the web-based EP. However, it is crucial to note that this finding is based on a specific study design and may not generalize to all health care settings. Alarmingly, patients are not able to independently recognize these potential dangers.

Less than 1% adults in the United States who meet body mass index criteria undergo bariatric surgery. Our objective was to identify patient and provider perceptions of individual-level barriers to undergoing bariatric surgery. Adults with severe obesity and obesity care providers described their experiences with the bariatric surgery care process in semi-structured interviews. Using conventional content analysis, individual-level barriers were identified within Andersen's Behavioral Model of Health Services Use. Of the 73 individuals interviewed, 36 (49%) were female, and 15 (21%) were non-white. Six individual-level barriers were identified: fear of surgery, fear of lifestyle change, perception that weight had not reached its “tipping point,” concerns about dietary changes, lack of social support, and patient characteristics influencing referral. Patient and provider education should address patient fears of surgery and the belief that surgery is a “last resort.” Bariatric surgery programs should strengthen social support networks for patients. •Patients and providers identified 6 individual-level barriers to bariatric surgery.•Surgery was feared and felt to be an extreme measure to address obesity.•Patients feared change and committing to a new diet for rest of life.•Fear of judgement & unstable support networks influenced decision to pursue surgery.•Education and longitudinal support are needed to address the barriers.

The study assessed the correlation among the patients' perception of leg length discrepancy (LLD) after total hip arthroplasty (THA) in patients with unilateral Crowe type IV developmental dysplasia of the hip (DDH) and the four methods of measuring the leg length in the full-length standing anteroposterior radiographs. Sixty patients with unilateral Crowe type IV DDH were recruited in this retrospective study between January 2012 and January 2019. Four methods of measurement were used: 1) TD-TP: distance between the inferior aspect of teardrop (TD) and the midpoint of tibial plafond (TP); 2) CH-TP: distance between the center of the hip (CH) or acetabular cup and the TP; 3) GT-TP: distance between the apex of greater trochanter (GT) and the TP; and 4) FL+TL: the sum of femoral length (FL) and tibial length (TL). Association was found among the patients' perception on LLD with difference in TD-TP (OR=1.157), and the difference in FL+TL (OR=1.166). The area under the curve of the difference in FL+TL and the difference TD-TP (0.704 and 0.679) was significantly higher than those of the difference in CH-TP and the difference in GT-TP (0.564 and 0.483). With the calculated threshold of LLD set at 9.0 mm, the sensitivity and specificity of the difference in TD-TP and the difference in FL+TL were 57.7%, 79.4% and 61.5%, 79.4%, respectively. Patients' perception on LLD had good correlation and reliability on the difference of FL+TL and the difference of TD-TP on both sides in the full-length standing anteroposterior radiographs after THA in patients with unilateral Crowe type IV DDH. The calculated threshold of the difference in FL+TL and the difference in TD-TP was set at 9.0 mm to assess the patients' perception on LLD.

Introduction: Clinician perceptions of patients with low socioeconomic status (SES) have been shown to affect clinical decision making and health care delivery in this group. However, it is unknown how and if low SES patients perceive clinician bias might affect their health care. Methods: In-depth interviews with 80 enrollees in a state Medicaid program were analyzed to identify recurrent themes in their perceptions of care. Results: Most subjects perceived that their SES affected their health care. Common themes included treatment provided, access to care, and patient-provider interaction. Discussion: This study highlights complex perceptions patients have around how SES affects their health care. These results offer opportunities to reduce health care disparities through better understanding of their impact on the individual patient-provider relationship. This work may inform interventions that promote health equity via a multifaceted approach, which targets both providers and the health care system as a whole.

Considerable research is being conducted as to how artificial intelligence (AI) can be effectively applied to health care. However, for the successful implementation of AI, large amounts of health data are required for training and testing algorithms. As such, there is a need to understand the perspectives and viewpoints of patients regarding the use of their health data in AI research.BACKGROUNDConsiderable research is being conducted as to how artificial intelligence (AI) can be effectively applied to health care. However, for the successful implementation of AI, large amounts of health data are required for training and testing algorithms. As such, there is a need to understand the perspectives and viewpoints of patients regarding the use of their health data in AI research.We surveyed a large sample of patients for identifying current awareness regarding health data research, and for obtaining their opinions and views on data sharing for AI research purposes, and on the use of AI technology on health care data.OBJECTIVEWe surveyed a large sample of patients for identifying current awareness regarding health data research, and for obtaining their opinions and views on data sharing for AI research purposes, and on the use of AI technology on health care data.A cross-sectional survey with patients was conducted at a large multisite teaching hospital in the United Kingdom. Data were collected on patient and public views about sharing health data for research and the use of AI on health data.METHODSA cross-sectional survey with patients was conducted at a large multisite teaching hospital in the United Kingdom. Data were collected on patient and public views about sharing health data for research and the use of AI on health data.A total of 408 participants completed the survey. The respondents had generally low levels of prior knowledge about AI. Most were comfortable with sharing health data with the National Health Service (NHS) (318/408, 77.9%) or universities (268/408, 65.7%), but far fewer with commercial organizations such as technology companies (108/408, 26.4%). The majority endorsed AI research on health care data (357/408, 87.4%) and health care imaging (353/408, 86.4%) in a university setting, provided that concerns about privacy, reidentification of anonymized health care data, and consent processes were addressed.RESULTSA total of 408 participants completed the survey. The respondents had generally low levels of prior knowledge about AI. Most were comfortable with sharing health data with the National Health Service (NHS) (318/408, 77.9%) or universities (268/408, 65.7%), but far fewer with commercial organizations such as technology companies (108/408, 26.4%). The majority endorsed AI research on health care data (357/408, 87.4%) and health care imaging (353/408, 86.4%) in a university setting, provided that concerns about privacy, reidentification of anonymized health care data, and consent processes were addressed.There were significant variations in the patient perceptions, levels of support, and understanding of health data research and AI. Greater public engagement levels and debates are necessary to ensure the acceptability of AI research and its successful integration into clinical practice in future.CONCLUSIONSThere were significant variations in the patient perceptions, levels of support, and understanding of health data research and AI. Greater public engagement levels and debates are necessary to ensure the acceptability of AI research and its successful integration into clinical practice in future.