Search results

As healthcare continues to become more expensive and complex, considering the voice of the patient in the design and operation of healthcare practices is important. Wound care and rural healthcare scenarios pose additional complexities for providers and patients. This study sought to identify key determinants of patient service quality in wound care.

Patients at the wound care/ostomy clinic (WOC) in a rural hospital were surveyed using the Kano model. The Kano model enables the categorization of quality attributes based on the attributes' contribution to the subject's overall satisfaction (and dissatisfaction). Chi-square goodness-of-fit testing, multinomial analysis and power analysis were then used to determine the Kano categories for each satisfaction-related attribute.

The analyses resulted in 14 one-dimensional attributes and 3 indeterminable attributes. For the one-dimensional attributes, customer satisfaction is directly proportional to the level of performance for that attribute. The one-dimensional attributes included providing correct care on the first, provision of necessary supplies for care, appropriately qualified medical staff and confidence in care provided by medical staff, among others. Understanding the attributes important to the patient drive patient-centered care, which improves positive patient outcomes and recovery. These attributes can then be used by healthcare professionals to design patient-centric processes and services. This research provides a framework for incorporating the voice of the patient into healthcare services.

While the research methodology can be used in other healthcare settings, the findings are not generalizable to other wound care clinics. This research was conducted in one small, rural hospital. In addition, the sample size was small due to the size of the wound clinic; therefore, an analysis of the differences between demographics could not be performed.

Considering the perspectives of rural wound care patients is important, as the patients are an under-served population with unique challenges related to patient care. The research findings detail rural patients' expectations during wound care treatments, which enable the clinic to focus on improving patient satisfaction. This research contributes to understanding the factors that are important to patient satisfaction in wound care. Further, the methodology presented can be applied to other healthcare settings.

While studies exist using the Kano model in healthcare and the literature is sparse in rural healthcare, this is the first case study using the Kano model in wound care to understand patient preferences.

Health care systems aspire to adopt integration strategies shifting the focus from acute care to a broader focus on community-based health and social services. Real-world examples demonstrating effective delivery of integrated care are essential.

In this article, we introduce UHN Connected Care Hub, an innovative model of care comprising an interdisciplinary team designing sustainable, shareable practices across the continuum of care alongside community and health organization partnerships.

We describe UHN Connected Care Hub’s ability to identify patients from high-risk population and collaborate to delivery timely care, in detailing the real world experience of this model of care in the organization of a centralized system of micro-clinics to administer a therapeutic for pre-exposure prophylaxis against COVID-19 (Tixagevimab/cilgavimab [Evusheld]) in a population of immunocompromised patients.

Having a centralized system of micro-clinics for care delivery presents opportunities for increased adaptability, patient accessibility, enhanced community partnerships and integratedness. Expansion in the scope of services could also create new opportunities in preventative therapies for optimizing the cost effectiveness and quality of health care provided at the population level.

There is limited evidence on how to efficiently deliver integrated care, particularly to vulnerable and co-morbid patients. We discuss how dynamic organizations with proper infrastructure and a network of healthcare partnerships may allow a more fluid response to rapidly changing policies and procedures and facilitate preparedness for future health care crises or pandemics.

While digital transformation holds immense promise, organizations often fail to realize its benefits. This study aims to address how policies for digital transformation benefits realization are translated into practice.

The authors apply a qualitative, comparative case study of two large, public-sector health care organizations in Sweden. Through document and interview data, the authors analyze the process of translation.

The study finds that practice variation is primarily caused by two types of decoupling: policy-practice and means-ends. Contrary to previous studies, coercion in policy compliance is not found to decrease practice variation.

The limitations primarily stem from the empirical selection of two large public health-care organizations in Sweden, affecting the study’s generalizability. Reducing practice variation is more effectively achieved through goal alignment than coercion, leading to implications for the design of governance and control.

Policymakers should, instead of focusing on control-related compliance, work to align organizational objectives and policies to decrease practice variation for successful benefits realization.

The study contributes to better benefits realization of digital transformation initiatives in health care. As such, the authors contribute to a better functioning and more transformative health care in times of increased demand and decreased supply of health-care services.

The study challenges conventional wisdom by identifying that coercion is less effective than goal alignment in reducing practice variation, thereby enhancing the understanding of policy implementation dynamics in health-care settings.

This paper aims to explore the antecedents and consequences of service chain flexibility (SCF) in healthcare service delivery.

A structural model was developed based on a literature review. A 29-indicator questionnaire was circulated among service providers in the healthcare system across India, and 253 valid responses were received, corresponding to a response rate of 46%. The research model was assessed using a cross-sectional research design, and the data were analyzed by structural equation modeling using analysis of moment structures (AMOS) software.

Service orientation (SO), technology integration (TI), knowledge sharing (KS) and supply chain integration (SCI) were identified as antecedents of SCF, the consequence of which is responsiveness in service delivery (RSD). Furthermore, patient-centered care moderates the relationship between SCF and RSD.

This paper highlights the impact of SCF on RSD in healthcare organizations. Consideration of the four constructs of SO, TI, KS and SCI as antecedents of SCF and, in turn, RSD may be one of the limitations. Future work may identify other theoretical constructs with potential impacts on SCF and RSD. Furthermore, eight months for data collection could have resulted in early-late response bias. This study was operationalized in India and may reflect political, economic, social, technological, environmental and legal factors unique to India.

The study provides suggestions to practitioners for building RSD by leveraging SO, TI, KS and SCI in flexibility-driven service chain processes. Recognizing the relationships among these constructs can aid in the timely formulation of corrective actions and patient-centric policies.

This paper highlights how focusing on a SCF can promote RSD. This understanding may aid the design of processes that develop patient-centricity and deliver health as a social good in an effective manner.

The empirical evidence from this study can help hospitals integrate and build flexibility in their functions, thus enabling them to deliver responsiveness in care.

This paper proposes a Web-based patient portal based on the electronic medical record. Such a portal can allow patients to manage their own health care, reduce health-care visits and significantly improve the quality of their health care.

A patient portal prototype and an accompanying online survey were distributed to assess the adoption readiness among a group of people in the United Arab Emirates (UAE).

The results from 470 survey participants demonstrated an enhanced awareness of this technology, and support the study hypotheses indicating that both intrinsic and extrinsic factors are important when considering the implementation of a patient portal in the UAE.

This study adds value to the few research studies undertaken in the Middle East discussing online health information technology and its adoption and usage among the population at large. The extended technology acceptance model, which contains two additional constructs, had not been previously validated in terms of a patient portal in the UAE, according to the author’s knowledge, adding more value. The UAE’s health-care system must use the benefits from the available IT infrastructure to provide a user-friendly online portal to encourage patients to manage their health care and health information.

This study was carried out to examine the volume and annual growth pattern of research on e-health literacy research, investigate the open-access types of e-health literacy research and perform document production by country and by sources. The study also mapped the keywords used by authors to represent e-health literacy research and performed an analysis of the clusters of the keywords to reveal the thematic focus of research in the area.

The research was guided by a bibliometric approach involving visualization using VosViewer. Data were sourced from Scopus database using a syntax that was tested and verified to be capable of yielding reliable data on the subject matter. The analysis in this study was based on bibliographic data and keywords.

A total number of 1,176 documents were produced during 2006 and 2022. The majority of the documents (18.90%) were published based on hybrid open-access processes, and the USA has the highest contributions. The Journal of Medical Internet Research is the venue for most of the documents on the subject. The 1,176 documents were described by 5,047 keywords, 4.29 keywords per document, and the keywords were classified into five clusters that aptly capture the thematic structure of research in the area.

e-Health literacy has experienced significant growth in research production from 2006 to 2022, with an average of 69 documents per year. Research on e-health literacy initially had low output but began to increase in 2018. The majority of e-health literacy documents are available through open access, with the USA being the leading contributor. The analysis of keywords reveals the multifaceted nature of e-health literacy, including access to information, attitudes, measurement tools, awareness, age factors and communication. Clusters of keywords highlight different aspects of e-health literacy research, such as accessibility, attitudes, awareness, measurement tools and the importance of age, cancer, caregivers and effective communication in healthcare.

This study has practical implications for health promotion. There is also the element of patient empowerment in which case patients are allowed to take an active role in their healthcare. By understanding their health information and having access to resources that help them manage their conditions, patients can make informed decisions about their healthcare. Finally, there is the issue of improved health outcomes which can be achieved by improving patients' e-health literacy. Visualisation of e-health literacy can help bridge the gap between patients and healthcare providers, promote patient-centered care and improve health outcomes.

Research production on e-Health literacy has experienced significant growth from 2006 to 2022, with an average of 69 documents per year. Many e-health literacy documents are available through open access, and the USA is the leading contributor. The analysis of keywords reveals the nature of e-health literacy, including access to information, attitudes, measurement tools, awareness and communication. The clusters of keywords highlight different aspects of e-health literacy research, such as accessibility, attitudes, awareness, measurement tools and the importance of age, cancer, caregivers, and effective communication in healthcare.

The paper aims to investigate the practices facilitating the transformation of healthcare services, understanding the resulting outcomes in terms of well-being and uplifting changes. a systematic literature review (SLR) focusing on analyzing the healthcare sector under the transformative service research (TSR) theoretical domain is conducted to achieve this goal.

Employing a structured SLR developed based on the PRISMA protocol (Pickering and Byrne, 2014; Pickering et al., 2015) and using Scopus and WoS databases, the study identifies and analyzes 49 papers published between 2021 and 2022. Content analysis is used to classify and analyze the papers.

The SLR reveals four transformative practices (how) within the healthcare sector under the TSR domain, each linked to specific well-being outcomes (what). The analysis shows that both practices and outcomes are mainly patient-related. An integrative framework for transformative healthcare service is presented and critically examined to identify research gaps and define the trajectory for the future development of TSR in healthcare. In addition, managerial implications are provided to guide practitioners.

This research is among the first to analyze TSR literature in the context of healthcare. The study critically examines the TSR’s impact on the sector’s transformation, providing insights for future research and offering a roadmap for healthcare practitioners to facilitate uplifting changes.

This paper aims to explore the intricate relationship between artificial intelligence (AI) and health information literacy (HIL), examining the rise of AI in health care, the intersection of AI and HIL and the imperative for promoting AI literacy and integrating it with HIL. By fostering collaboration, education and innovation, stakeholders can navigate the evolving health-care ecosystem with confidence and agency, ultimately improving health-care delivery and outcomes for all.

This paper adopts a conceptual approach to explore the intricate relationship between AI and HIL, aiming to provide guidance for health-care professionals navigating the evolving landscape of AI-driven health-care delivery. The methodology used in this paper involves a synthesis of existing literature, theoretical analysis and conceptual modeling to develop insights and recommendations regarding the integration of AI literacy with HIL.

Impact of AI on health-care delivery: The integration of AI technologies in health-care is reshaping the industry, offering unparalleled opportunities for improving patient care, optimizing clinical workflows and advancing medical research. Significance of HIL: HIL, encompassing the ability to access, understand and critically evaluate health information, is crucial in the context of AI-driven health-care delivery. It empowers health-care professionals, patients and the broader community to make informed decisions about their health and well-being. Intersection of AI and HIL: The convergence of AI and HIL represents a critical juncture, where technological innovation intersects with human cognition. AI technologies have the potential to revolutionize how health information is generated, disseminated and interpreted, necessitating a deeper understanding of their implications for HIL. Challenges and opportunities: While AI holds tremendous promise for enhancing health-care outcomes, it also introduces new challenges and complexities for individuals navigating the vast landscape of health information. Issues such as algorithmic bias, transparency and accountability pose ethical dilemmas that impact individuals’ ability to critically evaluate and interpret AI-generated health information. Recommendations for health-care professionals: Health-care professionals are encouraged to adopt strategies such as staying informed about developments in AI, continuous education and training in AI literacy, fostering interdisciplinary collaboration and advocating for policies that promote ethical AI practices.

To enhance AI literacy and integrate it with HIL, health-care professionals are encouraged to adopt several key strategies. First, staying abreast of developments in AI technologies and their applications in health care is essential. This entails actively engaging with conferences, workshops and publications focused on AI in health care and participating in professional networks dedicated to AI and health-care innovation. Second, continuous education and training are paramount for developing critical thinking skills and ethical awareness in evaluating AI-driven health information (Alowais et al., 2023). Health-care organizations should provide opportunities for ongoing professional development in AI literacy, including workshops, online courses and simulation exercises focused on AI applications in clinical practice and research.

This paper lies in its exploration of the intersection between AI and HIL, offering insights into the evolving health-care landscape. It innovatively synthesizes existing literature, proposes strategies for integrating AI literacy with HIL and provides guidance for health-care professionals to navigate the complexities of AI-driven health-care delivery. By addressing the transformative potential of AI while emphasizing the importance of promoting critical thinking skills and ethical awareness, this paper contributes to advancing understanding in the field and promoting informed decision-making in an increasingly digital health-care environment.

The purpose of this paper is to investigate user satisfaction with digital health solutions by identifying and prioritizing different service attributes on the basis of their impact on improving user satisfaction.

Through a literature review and interviews with health professionals and patients, 20 attributes of digital health services provided in Italy have been identified. User satisfaction with these attributes has been evaluated by adopting the Kano model’s continuous and discrete analyses.

The findings reveal the essential attributes of digital health services that meet users' expectations, identify the attributes that users appreciate or dislike having and highlight unexpected attributes that lead to a significant boost in satisfaction when provided.

This study demonstrates the efficacy of the Kano model in assessing the nonlinear correlation between user satisfaction and the quality of digital health services, thus contributing to fill a gap in the literature in this area. The main limitation of this work is the use of a non-probabilistic sampling method.

This research suggests healthcare institutions and organizations consider user preferences when designing digital health solutions to increase their satisfaction. The results indicate different effects on user satisfaction and dissatisfaction for different categories of attributes in the Italian context.

Previous works studied customer satisfaction with digital health, assuming a linear relationship with service quality, or investigated consumer adoption intentions focusing on the technological factors. This work advances available knowledge by analyzing the nonlinear relationship between digital health attributes and users’ satisfaction and dissatisfaction.

Waiting time, as an important predictor of queue abandonment and patient satisfaction, is important for resource utilization and patient experience management. Medical institutions have given top priority to reforming the appointment system for many years; however, whether the increased information transparency brought about by the appointment scheduling mechanism could improve patient waiting time is not well understood. In this study, the authors examine the effects of information transparency in reducing patient waiting time from an uncertainty perspective.

Leveraging a quasi-natural experiment in a tertiary academic hospital, the authors analyze over one million observational patient visit records and design the propensity score matching plus the difference in difference (PSM-DID) model and hierarchical linear modeling (HLM) to address this issue.

The authors confirm that, on average, improved information transparency significantly reduces the waiting time for patients by approximately 6.43 min, a 4.90% reduction. The authors identify three types of uncertainties (resource, process and outcome uncertainty) in the patient visit process that affect patients' waiting time. Moreover, information transparency moderates the relationship between three sources of uncertainties and waiting time.

The authors’ work not only provides important theoretical explanations for the patient-level factors of in-clinic waiting time and the reasons for information technology (IT)-enabled appointment scheduling by time slot (ITASS) to shorten patient waiting time and improve patient experience but also provides potential solutions for further exploration of measures to reduce patient waiting time.