Quality Management in Health Care最新文献

Background and objectives: The practice of medicine involves the risk of causing harm, even under the best circumstances and despite having optimal training. Therefore, patient safety is not only an essential part of healthcare but is also crucial for the training of resilient future doctors. The awareness of medical students regarding patient safety issues is of utmost importance for their professional formation. The objective of the present study was to gain insights into the awareness of medical students at the Autonomous University of Guadalajara about patient safety problems and the expectations of how patient safety is being managed in the health system.

Methods: A descriptive and longitudinal study was carried out in which eighth-semester medical students were invited to participate. The questionnaire was adapted from the World Health Organization Medical School Curricular Guide for Patient Safety questionnaire and applied before and after the course "Seminar on Quality and Safety in Medical Care." In total, 419 students answered the questionnaire.

Results: The data showed a significant increase in the scores on the questionnaire after the course (P < .05).

Conclusion: Students showed satisfactory awareness and positive expectations with regard to reporting and learning from errors and helping others when medical errors occur, which has implications for health care quality. Application of the WHO questionnaire in other settings and countries may contribute to a better comprehension of awareness and expectations of future health professionals in the world.

Background and objectives: Hospitals offered remote health care services to enable seamless and safe execution of health care operations during the pandemic while ensuring all stakeholders' quality of life and well-being. We explore various push and pull motivational factors that can influence customers' intentions to adopt remote health care services. We also examine the mediating role of perceived health care quality in light of their hedonic experience during the pandemic.

Methods: We develop our conceptual framework based on push-pull motivational theory and investigate remote health management intentions. We carried out a case study in a multispecialty hospital in India. We collected data from 482 internet users who accessed their remote services during the pandemic, and we performed statistical analysis.

Results: Our findings show the push and pull motivators significantly influencing internet populations' remote health management intentions. The results also highlight the mediation of perceived health care quality between push factors and remote health management intentions.

Conclusions: The push-pull motivators significantly regulate remote health care intentions among the internet population. Technologists and researchers must address these factors while introducing future remote services to widen adoption. This is one of the pioneering studies investigating people's remote health care intentions post-pandemic.

Background and objectives: The pandemic has severely impacted health services worldwide, making it crucial to document its effects on service quality. This longitudinal study is the first to assess how the COVID-19 pandemic affected the perceived service quality at a public clinic in Mexico and how it affected satisfaction among ambulatory patients.

Methods: The study used the service performance (SERVPERF) survey during the pandemic (period 1, n = 143, 2022) and post-pandemic (period 2, n = 100, 2023-2024) and structural equation modeling to examine the influence of various service quality dimensions on satisfaction during both periods.

Results: Contrary to expectations of a decrease in quality and satisfaction due to the increased demand for services during the pandemic, the findings indicated that overall service quality and patient satisfaction was high in both survey periods. The only exception was in the dimension of "tangible aspects," which experienced a decline in quality attributed to the effects of unexpected hurricanes. Interestingly, there was a relative improvement in service quality during the pandemic. Furthermore, factors related to empathy significantly impacted patient satisfaction during this time.

Conclusion: This study contributes valuable insights into perceived service quality at a public clinic in Mexico during and after the pandemic. It also advocates for an evaluation mechanism based on user perceptions, suggesting that political and economic efforts should focus on enhancing public service.

Background and objectives: There are two methods of studying multiple mediation: network-based and analysis of coefficients in regression equations.

This tutorial shows how multiple mediation analysis can be conducted through first constructing causal networks; and then evaluating the direct and mediated impact within the network. The proposed method is demonstrated in the context of diagnosing COVID-19 from its symptoms.

Methods: 822 individuals who had completed a COVID-19 test were recruited through listservs and via employees and patients of Virginia Commonwealth University Health Center. Participants reported their symptoms and which symptom(s) occurred first. A Causal Network model was established through a repeated chain of regressions in four steps: First, we identified the order of occurrence of symptoms. Second, COVID-19 test results were LASSO regressed on symptoms and demographic variables, establishing direct effects. Third, the direct effects were LASSO regressed on prior symptoms and demographic variables, establishing indirect effects. Fourth, the joint distribution of the variables in the network was simulated by evaluating regression equations at factorial combinations of their direct effects. Fifth, the mediated effect was calculated through twin modeling, where the model derived from the real data was compared to the counterfactual model that represented 'what if' there was no mediation.

Results: The 10-fold cross-validated area under the receiver curve for the network model was 0.82, which is a moderate to high level of accuracy. The network model identified later symptoms (e.g., chills) mediated the effect of earlier symptoms (e.g. fever).

Conclusions: A network-based multiple mediation analysis led to new insights by integrating findings of 19 separate regressions into a single network model. The procedure showed how artificial intelligence can help in triage of COVID-19 patients from their symptoms, before any home or laboratory tests.

Background and objectives: Preventive care is vital in maintaining health and supporting independence among older persons. In Sweden, a national quality register (Senior Alert) was developed in elder care to support healthcare workers working to prevent malnutrition, falls, pressure ulcers, and poor oral health. However, we predicted that challenges in providing care at home result in preventive work being least used when and where it would be most effective: early in disease processes. The current study examines the preventive care actions planned and performed for older persons with identified risks, to compare quality and equity of care in different care settings.

Methods: Persons from the Swedish Screening Across the Lifespan Twin Study registered in the Senior Alert were included in the study (N = 2914). Descriptive and analytical statistical analyses regarding risk assessment and planned and performed preventive actions were conducted among those persons registered in hospitals, home health care, nursing homes, dementia care homes, or short-term nursing homes.

Results: Almost 80% of the sample had identified risk in at least one of the four risk areas, with falls and malnutrition being most common. Risks differed between care settings, and having any risk was most common among older persons in short-term nursing homes. The largest difference between planned and performed actions was for older persons with home health care, and especially true for the oldest persons (>80 years old).

Conclusions: Preventive care is vital as it is often easier to prevent than treat, and pressure ulcers, malnutrition, poor oral health, and falls are common among older persons. However, preventive actions were less likely to be performed in the home health care, especially for the oldest adults. Reasons for this might be related to challenges of performing care in a person's home, lack of knowledge, and organizational challenges, but further investigation is needed.

Background and objectives: Poor communication complicates patients' understanding of their diagnosis and nursing care, which can jeopardize patients' treatment and prognosis. Streamlined nurse-patient communication interventions are proven to improve patient satisfaction and nursing care quality. Guided by the Plan-Do-Study-Act Quality Improvement Model, we used the Contact, Introduce, Communicate, Ask, Respond, and Exit (CICARE) communication mode aimed at improving nurse-patient communication and patient satisfaction in our outpatient center.

Methods: Nurses in the center were trained on CICARE communication mode in the 1-month training sessions. They incorporated the CICARE communication mode into their routine nursing practices for all outpatients. Data were collected before implementation of the project and at 1-month post-implementation, between October 2023 and March 2024. The CICARE communication mode utilization rate, nurses' communication knowledge, practice skills, and ability, and the patient satisfaction rate were measured.

Results: A total of 28 outpatient nurses attended the education training sessions. The utilization rate of the CICARE communication mode was 86%. Compared to before training, nurses' communication knowledge, practice skills, and ability, and the patient satisfaction scores improved significantly after training ( P < .05).

Conclusion: Application of the CICARE communication mode in outpatient nursing work is beneficial for enhancing nurses' proficiency in nurse-patient communication and improving patient satisfaction, which can help to increase the quality of nursing care.

Background and objectives: Medical risks are considered to endanger patients and impact the health care system. Such iatrogenic risks necessitate hospitals taking a more proactive method to quantitatively analyze medical risk, and then to implement more targeted precautions. To address this problem, a novel quantitative risk assessment framework is proposed and further applied in radiotherapy risk assessment.

Methods: A framework combining DMAIC (Define, Measure, Analyze, Improve, Control) and bow-tie model is used to assess health care risk. The uncertainty of medical risks is quantified with fuzzy set theory. The impact and the priority of medical risks were classified based on the risk matrix, and then the precautions were implemented to mitigate their impact. A case study of radiation treatment is provided.

Results: The probabilities and impacts of risk events for radiation treatment were quantified based on the proposed framework, and risk protection measures were proposed to mitigate the undesired consequence.

Conclusion: The proposed framework showing an effective method of quantitative risk assessment of health care. The study also enriches the risk assessment methods in health care by providing a conductive and normalized framework.