Healthcare Platform Research Articles

Анализ требований к конфиденциальности и обмену данными цифрового здравоохранения

The article provides answers to immediate questions associated with the state regulation of confidentiality of information and exchange of data in the era of digital healthcare. The institute of medical confidentiality which originated in the ancient world is still evolving throughout the development of medical law. In the current era of global digitalization, however, the issues related to data confidentiality have become more relevant than ever. With all the modern technologies and digital health care platforms on the rise, new challenges associated with protection of these patients are emerging. To ensure the reliable protection of patient’s personal and medical information, doctors and medical institutions have to meet data security standards. It becomes vital to develop effective strategies and mechanisms to prevent unauthorized access and data leakage due to a larger volume of electronic medical records and digital data exchange. Strict rules and standards regulating collection, storage and transfer of medical data belong to a key aspect in this area. The Russian Federation is making great efforts to create the legislation which could protect the rights of patients and made medical establishments to follow the high standards of confidentiality, and to develop technical aids that provide data encryption and protection against hacker attacks.

HSD75 Optimizing Preoperative Assessment Through a Digital Healthcare Platform for Triage and Stratification in Joint Replacement Surgery: A Real-World Evaluation

HSD75 Optimizing Preoperative Assessment Through a Digital Healthcare Platform for Triage and Stratification in Joint Replacement Surgery: A Real-World Evaluation

Assessing the Quality of Health Content on Arabic Digital Platforms: Insights from Healthcare Professionals and the Public

Fundamentally, human well-being serves as the bedrock upon which individuals can lead enriching lives and contribute positively to their communities and the global society. Most industries across the board employ social media to disseminate their offerings and facilitate customer engagement. This has also found its way into the healthcare sector, with numerous websites and social media platforms. These platforms host a wealth of health-related information and empower the public to seek out health insights that pique their interest. Given the vital nature of the healthcare sector, it becomes imperative to disseminate health information with censorship and ensure continuous monitoring and updates.
 This study endeavors to explore the assessment of healthcare sector professionals, encompassing doctors, medical students, nurses, and other healthcare professionals. Additionally, it seeks to gauge the opinions of the public who frequent these online platforms. The evaluation was conducted based on various criteria derived from prior research, employing a questionnaire methodology to gather the necessary feedback. The outcomes of the evaluation yielded positive results in both participant categories. However, it is important to acknowledge that this evaluation does not include all healthcare platforms or all inquiries. This underscores the urgent need to establish controls, as stated in the study's concluding observations.

Shaping the future of chronic disease management: Insights into patient needs for AI-based homecare systems

BackgroundThe rising demand for healthcare resources, especially in chronic disease management, has elevated the importance of Artificial Intelligence (AI) in healthcare. While AI-based homecare systems are being developed, the perspectives of chronic patients, who are one of the primary beneficiaries and risk bearers of these technologies, remain largely under-researched. While recent research has highlighted the importance of AI-based homecare systems, the current understanding of patients’ desired designs and features is still limited. ObjectiveThis paper explores chronic patients’ perspectives regarding AI-based homecare systems, an area currently underrepresented in research. We aim to identify the factors influencing their decision to use such systems, elucidate the potential roles of government and other concerned authorities, and provide feedback to AI developers to enhance adoption, system design, and usability and improve the overall healthcare experiences of chronic patients. MethodA web-based open-ended questionnaire was designed to gather the perspectives of chronic patients about AI-based homecare systems. In total, responses from 181 participants were collected. Using Krippendorff's clustering technique, an inductive thematic analysis was performed to identify the main themes and their respective subthemes. ResultThrough rigorous coding and thematic analysis of the collected responses, we identified four major themes further segmented into thirteen subthemes. These four primary themes were: 1) “Personalized Design”, emphasizing the need for patients to manage their health condition better through personalized and educational resources and user-friendly interfaces; 2) “Emotional & Social Support”, underscoring the desire for AI systems to facilitate social connectivity and provide emotional support to improve the well-being of chronic patients at home; 3) “System Integration & Proactive Care”, addressing the importance of seamless communication, proactive patient monitoring and integration with existing healthcare platforms; and 4) “Ethics & Regulation”, prioritizing ethical guidelines, regulatory compliance, and affordability in the design. ConclusionThis study has offered significant insights into the needs and expectations of chronic patients regarding AI-based home care systems. ‘The findings highlight the importance of personalized and accessible care, emotional and social support, seamless system integration, proactive care, and ethical considerations in designing and implementing such systems. By aligning the design and operation of these systems with the lived experiences and expectations of patients, we can better ensure their acceptance and effectiveness.

Enhancing Sustainability through Accessible Health Platforms: A Scoping Review

The digital transformation of healthcare platforms has ushered in a new era of accessibility, making health information and services widely available. This comprehensive scoping review delves into the accessibility landscape of health platforms by analyzing 29 carefully selected research articles. These studies employ automated tools and manual evaluations to evaluate platform accessibility comprehensively. This study revealed that (52%) of these articles are based on automated methods, while 34% combine automated and manual approaches. Most studies show compliance with the latest versions of the Web Content Accessibility Guidelines (WCAG), with a significant focus (70%) on compliance with level A. This study reveals recurring issues within the perceivable operable, understandable, and robust categories, underscoring the pressing need for strict the accessibility testing of health platforms. This study demonstrates substantial agreement between raters, reinforced by a Cohen’s kappa coefficient of 0.613, indicating their reliability in classifying the articles. Future efforts should persist in refining accessibility standards, advocating for compliance with the WCAG, exploring innovative methods to assess the accessibility of healthcare platforms, and conducting user-centered research. This review highlights the paramount importance of ensuring equitable access to health information and services for people, regardless of their abilities or conditions, which resonates significantly with the issue of sustainability in healthcare and its socioeconomic and environmental implications.

The Role of HTA for Essential Health Benefit Package Design in Low or Middle-Income Countries

ABSTRACT This Commentary explores the relationship between Health Technology Assessment (HTA) and Health Benefits Package (HBP) design to achieve Universal Health Coverage (UHC) in low- and middle-income countries. It emphasizes that while HTA evaluates individual healthcare interventions, HBP reform aims to create comprehensive service sets considering overall population health needs and available resources. Challenges in LMICs include limited local data and technical capacity, leading to reliance on cost-effectiveness estimates from other settings. We suggest a practical approach by combining HTA and HBP elements through a hybrid or compartmentalized method. This approach sets differentiated cost-effectiveness thresholds for specific healthcare platforms or programs (e.g., primary care or essential surgery), aligning priority-setting with organizational considerations, ethics, and implementation strategies. Strong institutions and academic support are vital for evidence-informed priority-setting processes. In summary, HTA can play a pivotal role in designing HBPs for UHC in LMICs, and a compartmentalized approach can enhance priority-setting while considering budget constraints and equity.

Age disparity among severe aortic stenosis patients: AVR treatment rates and clinical outcomes among octogenarians

Abstract Introduction Aortic valve replacement (AVR) is considered one of the most effective disease-modifying procedures among patients with severe Aortic Stenosis (sAS). Accordingly, we can witness a consistent increase in procedure rates in recent years. Nevertheless, the elderly population, particularly octogenarians, remains relatively undertreated. Purpose The current study aims to document the baseline characteristics, disparities in AVR rates, and prognostic significance of AVR among octogenarian vs. non-octogenarian patients with sAS. Methods A vast database of Maccabi health services, the second largest health maintenance organization (HMO) in Israel, counting nearly 2.8 million members, was retrospectively analyzed from 2005 to 2021 for all patients over 60 years, with a detailed echocardiography report compatible with a diagnosis of sAS. Patients who underwent AVR previously or on the same day of their diagnostic echocardiography were excluded. The database was extracted using the MDClone ADAMS healthcare data platform, generating synthetic data reliably representing the original population. All-cause mortality was set to be the primary outcome, and survival models utilizing adjusted multivariable analyses for several clinical and echocardiographic parameters were applied. Results A total of 1359 patients with high-gradient sAS were included in the final analysis, of which 574 (42%) are octogenarians. The octogenarian group included more females (56% vs. 48%), and they had a significantly higher prevalence of hypertension (83% vs. 78%), atrial fibrillation (22% vs. 14%), previous myocardial infarction (12% vs. 8%) and heart failure (20% vs. 10%). Substantial differences were documented regarding AVR-treatment rates between the two groups, with the undertreatment of the octogenarian group (39% vs. 60% of AVR within 18 months from diagnosis of sAS, p<0.001). Differences remained significant in a fully adjusted time-to-event model (HR 0.54, 95% CI 0.46-0.64, p<0.001 for octogenarians) A time-dependent analysis showed that AVR was associated with reduced all-cause mortality (HR 0.30, 95% CI 0.23-0.41, p<0.001) within the octogenarian group in 5 years. A similar protective effect was shown in the non-octogenarian group (HR 0.32, 95% CI 0.22-0.46, p<0.001). Conclusions Despite having comparable survival benefits, octogenarian patients with sAS still receive lower AVR treatment rates than non-octogenarians

Early cardiologist follow-up determines treatment rates and survival among aortic stenosis patients

Abstract Background Aortic valve replacement (AVR) has been constant as it is considered an effective disease-modifying procedure for patients with severe aortic stenosis (sAS). However, the implanter is only one part of it. Patients with sAS generally require ongoing care and support from a multidisciplinary team that includes general cardiologists (GC) and other primary care providers, who guide and manage the patient through the therapeutic process. Purpose The current study aims to assess the impact of a cardiologist or other primary care provider managing the therapeutic process in the early period first phase following the sAS diagnosis. Methods A large-scale database of Maccabi Health Services, the second largest health maintenance organization (HMO) in Israel, counting Israel with nearly 2.8 million members, was retrospectively analyzed from 2005 to 2021 for all patients over 60 years, with detailed echocardiography compatible with a diagnosis of sAS. The database was extracted using the MDClone healthcare data platform, generating the synthetic cohort database reliably representing the original population. sAS patients managed by GC versus non-GC care providers were assessed for differences in AVR rates, and all-cause mortality was assessed in sAS patients managed by GC versus non-GC care providers. Results A total of 1570 sAS patients were included in the final analysis. Of them, GCs managed GC managed 65% in the early phase (3 months) following the sAS diagnosis. sAS with heart failure (21% vs. 17%) and atrial fibrillation (26% vs. 19%) were less likely managed by GC. No statistically significant differences were observed in other baseline characteristics, including age, gender, and comorbidities. A propensity score matching analysis revealed a significant difference in 12-month and 24-month AVR rates following diagnosis between the GC versus non-GG groups (19% vs. 3%, and 28% vs. 9%, respectively. P<0.01 for both). sAS patients managed by a GC show a significant survival benefit, 31% vs. 36% within five years after diagnosis P < 0.05. Conclusions Patients with sAS managed by a GC within three months after diagnosis had significantly higher chances for AVR and, consequently, better prognosis. These findings emphasize the importance of GC management in sAS.

A Study on the Local Environment and the Usage of Healthcare Platform in China

A Study on the Local Environment and the Usage of Healthcare Platform in China

The Need for a Public Oral Health Platform and Dentist Perception Survey

Purpose: To examine the current status and limitations of several healthcare platform cases and develop effective content and models for a public oral health platform through a survey of dentists.Methods: Survey on public platforms was conducted on 362 dentists belonging to the Gyeonggi Dental Association. The survey questions consisted of 4 questions on awareness of recent issues related to platforms, 4 questions on the need for platforms, and 9 questions on essential content for public platforms.Results: In the survey, 77.9% of dentists recognized the importance of public platforms. The main features that should be included in public platforms are "student oral examination function" and "dentist locator function". And 84.3% of respondents answer they would be willing to use a platform with these features.Conclusion: This study emphasizes the need for active participation in public platforms to offset the drawbacks of private platforms.

Behavior integration for a sustainable COVID-19 vaccination in Serbia, North Macedonia, and Moldova

Abstract Issue/Problem In Serbia, North Macedonia, and Moldova, USAID's MOMENTUM Routine Immunization Transformation and Equity project is using a behavioral integration approach to increase COVID-19 vaccine uptake in priority populations. This approach is aimed at changing provider and community behaviors to embrace COVID-19 vaccination as part of a healthy lifestyle. This approach may be applicable and replicable in countries around the world. Description In an effort to implement a sustainable model for COVID-19 integration into the primary healthcare system, the project applied a behavioural integration approach to understand barriers and motivators to COVID-19 vaccination. In all three countries, we collected qualitative data through interviews with public health decision-makers, immunization health professionals, and other key partners, and focus group discussions with members of the priority populations. Results The project created profiles for each priority behaviour, detailing barriers and motivators to adopt it, and supporting people and their actions. We conducted participatory workshops with relevant immunization stakeholders that validated and prioritized key behaviors, and conceptualized integrating COVID-19 vaccination into a healthy lifestyles’ framework. We identified effective messages to promote vaccine uptake, and a course curriculum focused on healthy lifestyles, life-course immunization, and person-centred care. Lessons Behavioural insights and the behavioural integration approach helped identify and prioritize critical COVID-related behaviours to increase vaccine uptake amongst key priority populations. For the first time in the region, we proposed the integration of COVID-19 vaccination into a primary healthcare platform, focused on healthy lifestyles and life course immunization, as well as person-centered care, which aligned well with both governments’ and populations’ priorities. Key messages • Behavioral insights and behavioral integration helped identify priority populations and behaviors, and better align the respective priorities of populations and governments for COVID-19 vaccination. • Participatory workshops with relevant stakeholders, together with evidence from qualitative and quantitative research, allowed us to design and adapt public health interventions.

Towards a universal patient-centric health record sharing platform

ObjectivesThis paper provides a practical approach to evaluate health record sharing platforms in terms of their ability to deliver interoperable healthcare of quality at a systems level. We use our previously published interoperability evaluation framework to evaluate our proposed System-level Record Sharing (SLRS) platform against four other common categories of health record sharing platforms in Canada, the United States, and Norway. MethodsIn this paper, we compare the SLRS platform architecture that we previously developed against 4 health record sharing platform categories. We conducted this comparative evaluation of 5 categories of healthcare platforms: SLRS, Commercial-Multi (CM), Commercial-Independent (CI), Governmental-Multi (GM), and Governmental-Independent (GI) using our proposed evaluation framework that is built upon quadruple aim, triple aim and Canadian Institute for Health Information (CIHI) health platform evaluation frameworks. ResultsSLRS and platforms managed by government organizations that provide a technology-independent or compatible platform were the most effective in terms of satisfying data interoperability, providing meaningful and effective information exchange, being compliant with health privacy regulations across a range of contexts, and having many of the costs paid for at a central level. All platforms struggled with context and process interoperability requirements, as well as providing evidence-based information across an entire health system. ConclusionTo optimize health management, both clinicians and patients need sharing of personal health information (PHI) across applications. Our findings indicate that commercial platforms in this study need to improve their governance structure and employ a consistent ontology that can be adopted by all EHR applications across a health system. Our proposed SLRS platform can support the sharing of health data across multiple health care organizations at a system-level, allowing clinicians to access patient health data to inform treatment and care decisions. Public interest abstractHealthcare organizations face barriers when exchanging information across their boundaries. Many obstacles are caused by varying technical requirements of the EHR applications they have, and their contextual regulations. Most healthcare organizations have a portal in which the patients can view their care history. However, the breadth of the information provided limits to the number of healthcare providers subscribed to that specific platform. Viewing the full history across the entire health system, requires maintaining multiple accounts.In this paper we refer to a new framework for sharing health information and its prototyped platform (SLRS) that we have previously developed in our lab. In this paper we report on how we evaluated the SLRS platform against four prominent practices of Health Information Exchange. We used our interoperability evaluation framework that was developed based on well-acknowledged criteria from literature and practice. We found areas of improvement for existing health information platforms so they can share their records across an entire health system.

Social VR: A Promising Platform for Enhancing Mental Wellness among College Students

ABSTRACTIn recent decades, there has been an alarming increase in the number of university and college students struggling with intensifying psychological distress, which has become a mental health crisis on campuses. To address this issue, this study proposes social VR as a potential platform to promote social interaction and improve mental well‐ being for college students. In this study, 68 students explored a variety of social VR applications in a classroom setting. Results showed that a) virtual space, audio, avatar, communication types, and activities were key contributing features that facilitated social interaction among college students in social VR and have the potential to enhance mental wellness, and b) the anonymous nature, communicative cues, and designated private areas provided by social VR platforms were effective in facilitating self‐disclosure, indicating social VR's potential in delivering mental health services such as individual and group counseling and therapy. This study provides evidence that social VR can enhance social interaction and communication while serving as a platform for professional mental health care, a venue that has yet to be explored in previous studies.

Factors influencing engagement in online dual practice by public hospital doctors in three large cities: A mixed-methods study in China.

In the digital age, a rising number of public sector doctors are providing private telemedicine and telehealth services on online health care platforms. This novel practice pattern - termed online dual practice - may profoundly impact health system performance in both developed and developing countries. This study aims to understand the factors influencing doctors' engagement in online dual practice. Using a mixed-methods design, this study concurrently collects quantitative demographic and practice data (n = 71 944) and semi-structured interview data (n = 32) on secondary and tertiary public hospital doctors in three large Chinese cities: Beijing, Shanghai and Guangzhou. We use the quantitative data to examine the prevalence of the online dual practice and its associated factors via the binary logit regression model. The qualitative data are used to further explore associated factors of online dual practice via thematic analysis. The findings about associated factors from the two parts were merged using the categories of personal, professional, and organisational characteristics. Our quantitative analysis shows that at least 47.1% of public hospital doctors are involved in online dual practice. The shares in Beijing, Shanghai, and Guangzhou are 43.7%, 53.1%, and 44.8%, respectively. This practice is more prevalent among doctors who are male, senior, and non-managerial. Different specialties, hospital ownership, hospital levels, and locations are also significantly associated with this practice. The qualitative analysis further suggests that financial returns, perceived effectiveness of telemedicine, and hospital directors' attitude towards telemedicine may affect doctors' engagement with online dual practice. Online dual practice is prevalent among doctors at tertiary and secondary public hospitals in Beijing, Shanghai, and Guangzhou. Personal, professional, and organisational characteristics are all associated with doctors' choice to engage in online dual practice. The findings in this study provide implications for promoting telemedicine adoption and developing relevant regulatory policies in China and other countries.

A Strategic Framework for the Development, Implementation and Management of Digital Platform Ecosystems in Healthcare

Purpose: Several studies have shown that community management and platform engagements promote value co-creation in the automobile, housing, e-commerce, education and IT industries. The potential of digital technologies to support more inclusive and sustainable growth is transforming traditional business ecosystems. However, this value co-creation in digital platform ecosystems has struggled across healthcare due to the challenges associated with privacy, security and data management. By viewing healthcare as a business rather than a social intervention, this study aims to design a strategic framework supporting the development, implementation and management of digital platform ecosystems within the business environment.Design/methodology/approach: This study builds upon existing literature on value co-creation strategies, implementation initiatives, and interoperability management requirements, as well as leveraging data and insights from a survey to develop a management framework for digital platform ecosystems in healthcare.Findings: The study shows that a strategic framework provides a systematic approach to integrating multiple actors in developing, implementing and managing healthcare platform ecosystems. It also offers practical implications and recommendations for healthcare delivery and service providers.Originality/value: The researchers present an original framework based on in-depth theoretical and empirical studies of the digital platform ecosystem in healthcare. Moreover, they demonstrate the application of this framework by assessing a selected digital platform ecosystem. Keywords: digital platform ecosystems, healthcare, management, value co-creation, interoperability, actor engagement.

Using Machine Learning Algorithms to Design Personalized Exercise Programs for Health and Wellness

The research paper showcases an elaborate study of machine learning, which is used in healthcare or medical platforms and can be used by healthcare professionals to adopt better diagnostic instruments and tools for examining medical issues or images. The paper highlights that a machine learning algorithm can be utilized in X-rays or MRI scans to examine disease and health issues. This paper will also discuss how this algorithm can help healthcare professionals, doctors, and nurses make accurate diagnoses for better services and patient outcomes. One of the major advantages of using the secondary research method in the following research is the abundance of the literature. All the data being used here are previously collected and evaluated with the result, and using these will increase the impact of the study overall. This method saves resources, including money, time, and manpower. This research method allows the researcher to build new knowledge and draw new conclusions based on existing expertise and knowledge. The chosen research philosophy is the Interpretivism research philosophy. The chosen research approach here is the inductive research approach. The chosen research design for this study is exploratory. All these help the research to achieve its objectives and reach the proposed goal of this research.

Efficient Classification of ECG Images Using a Lightweight CNN with Attention Module and IoT.

Cardiac disorders are a leading cause of global casualties, emphasizing the need for the initial diagnosis and prevention of cardiovascular diseases (CVDs). Electrocardiogram (ECG) procedures are highly recommended as they provide crucial cardiology information. Telemedicine offers an opportunity to provide low-cost tools and widespread availability for CVD management. In this research, we proposed an IoT-based monitoring and detection system for cardiac patients, employing a two-stage approach. In the initial stage, we used a routing protocol that combines routing by energy and link quality (REL) with dynamic source routing (DSR) to efficiently collect data on an IoT healthcare platform. The second stage involves the classification of ECG images using hybrid-based deep features. Our classification system utilizes the "ECG Images dataset of Cardiac Patients", comprising 12-lead ECG images with four distinct categories: abnormal heartbeat, myocardial infarction (MI), previous history of MI, and normal ECG. For feature extraction, we employed a lightweight CNN, which automatically extracts relevant ECG features. These features were further optimized through an attention module, which is the method's main focus. The model achieved a remarkable accuracy of 98.39%. Our findings suggest that this system can effectively aid in the identification of cardiac disorders. The proposed approach combines IoT, deep learning, and efficient routing protocols, showcasing its potential for improving CVD diagnosis and management.

The effectiveness of interactive mobile health technologies in improving antenatal care service utilization in Dodoma region, Tanzania: A quasi-Experimental study.

Antenatal care (ANC) provides a platform for important health care during pregnancy, including health promotion, screening, diagnosis and disease prevention. Timely and appropriate utilization of antenatal care can prevent complications as well as ensure optimal maternal and newborn health care. This study assessed the effectiveness of interactive (two way communication) mobile health technologies during antenatal period to improve maternal and newborn service utilization in Dodoma region, Tanzania. Using quasi-experimental design, participants were randomly selected to achieve a sample size of 450 pregnant women (Intervention = 150 and Control = 300) in Dodoma city from January to November, 2018. Interventions were matched to controls by gravidity, education level and gestational age at a ratio of 1 to 2. The intervention group received health education messages through their mobile phones, while the control group continued with standard antenatal care services offered in local clinics. Pregnant women were followed from their initial visit to the point of delivery. The Chi-square test was used to establish the association and regression analysis were used to test the effect of the intervention. The median age of participants was found to be 25 years that ranged from 16 to 41 years. Generally, 77.3 percent of participants in the intervention group utilized adequate (i. ANC care provided by skilled health personnel, ii. Sufficient number of ANC visits (4 or more visits during pregnancy), iii. Appropriate ANC contents provided (visits included at least 13 out of 15 of the recommended basic care procedures or contents) ANC services compared to 57.7 percent in the control group. Interactive mobile health technology system was observed to be effective on improving antenatal care service utilization (AOR = 2.164, P<0.05, 95% CI = 1.351-3.466) compared to conventional antenatal care health education given in local health facilities. Use of interactive mobile health technologies during antenatal period has the potential of improving access to information and antenatal care service utilization in the study setting. Trial Registration: PACTR202008834066796 "Retrospectively registered".

Ethereum and Smart Contracts based Healthcare Data Management

This paper delivers a comprehensive report on the successful implementation of an Ethereum and Smart Contract based decentralized web application that is a platform for healthcare institutes to maintain their patient medical records. The system allows multiple healthcare institutes to share patient medical data. The immutability of the data is an essential requirement when handling sensitive data like a patient’s medical history, hence the incorporation of blockchain technology which is a digital edger that keeps track of transactions or information in a secure and transparent way. Key Words: Blockchain, Ethereum, Smart Contracts, Healthcare, Security and Privacy.

Nephrology workforce in China: describing current status and evaluating the optimal capacity based on real-world data

ObjectiveThis study aims to characterize the current status of the nephrology workforce in China and evaluate its optimal capacity based on real-world patient mobility data.MethodsData on nephrologists in China were collected from two prominent online healthcare platforms using web crawlers and natural language processing techniques. Hospitalization records of patients with chronic kidney disease (CKD) from January 2014 to December 2018 were extracted from a national administrative database in China. City-level paths of patient mobility were identified. Effects of nephrology workforce on patient mobility were analyzed using multivariate Poisson regression models.ResultsAltogether 9.13 nephrologists per million population (pmp) were in practice, with substantial city-level variations ranging from 0.16 to 88.79. The ratio of nephrologists to the estimated CKD population was 84.57 pmp. Among 6 415 559 hospitalizations of patients with CKD, 21.3% were cross-city hospitalizations and 7441 city-level paths of patient mobility with more than five hospitalizations were identified. After making adjustment for healthcare capacity, healthcare insurance, economic status, and travel characteristics, the Poisson regression models revealed that the number of nephrologists in both the source city (incidence rate ratio [IRR] 0.99, per 1 pmp increase) and destination city (IRR 1.07, per 1 pmp increase) were independently associated with patient mobility. An IRR plateau was observed when the number of nephrologists exceeded 12 pmp in the source city, while a rapidly increasing IRR was observed beyond 20 pmp in the destination city.ConclusionsThe nephrology workforce in China exhibits significant geographic variations. Based on local healthcare needs, an optimal range of 12–20 nephrologists pmp is suggested.