Electronic Patient Data Confidentiality Practices Among Surgical Trainees: Questionnaire Study

Introduction: The future of healthcare systems relies on faster communication between sensors and smart devices, which can assist in taking decisions for betterment of patients. The responsiveness of wireless health care system in case of medical urgencies is crucial factor for survival of patient’s life. The routing protocol of infrastructure less based are playing key role in sending the information in such medical related emergencies. Therefore, it is important to study and identify the best routing protocol in wireless healthcare based system using Mobile Ad-hoc networks (MANETS). Methods: MANET routing protocols such as Ad-hoc On Demand Vector (AODV), Secure AODV (SAODV) and Hybrid Wireless Mesh Protocol (HWMP) through their routing environment are simulated through this research study. It is essential to highlight the effect of various attacks affecting the routing methodology of these protocols. Since Distributed Denial of Service (DDoS) attack is popularly talked about and is most vulnerable attack present in MANET environment, so this research study analyses AODV, SAODV and HWMP under DDoS attacks through various simulation parameters. Results: In this research study, most suitable routing protocols to handle DDoS attacks are simulated and estimated in terms of delay and packet delivery ratio in the scenario of changing nodes. This aids in providing implications to enhance existing protocols and alleviate the consequences of DDoS investigation by such attacks. Discussion: For ensuring the optimized routing, privacy and security of patient’s data during transmission in healthcare sector, MANET could be used as one of the important technology combined with IoT. For dealing with end to end data transmission of patient's sensitive data, MANET protocol plays a vital role in sending the information securely. Conclusion: The performance of AODV, SAODV and HWMP (Hybrid Wireless Mesh Protocol) are compared and tabularized which are the most popularly utilized protocols in healthcare environment. The simulation results shows that the HWMP out performed than AODV and SAODV routing protocol, in terms of evaluation metrics namely end-to-end delay and Packet Delivery Ratio (PDR) and could be considered as much less vulnerable against DDoS attacks prevailing in wireless healthcare sector using MANET.

We thank Ahmad and colleagues for their positive comments regarding our article and share in their concern about the quality and quantity of training to which basic surgical trainees are exposed. Although their suggestion that basic trainees should be exposed to more laparoscopic cases is laudable, we are concerned as to how this would work in practice. Increasing amounts of the SHOs' time are now given over to acute day- and night-time service provision, which includes cross-cover for a number of specialities. This environment offers little in the way of training opportunities and we are finding that SHOs are increasingly unavailable to involve themselves in simple out-of-hours operations like abscess drainage or appendicectomy. Moreover, this schedule of acute commitments, along with enforced leave to maintain compliant weekly hours, is compressing the day-time elective exposure of trainees. This includes access to CEPOD lists along with the opportunity to pick up operative experience (laparoscopic or otherwise). As a result, we are now finding that some newly appointed higher surgical trainees are lacking experience in basic surgical procedures. This perpetuates the problem as the higher trainees then utilise training opportunities of interest to the basic trainees, in order to acquire proficiency in these procedures. We believe that any solution must ultimately lie in freeing up training opportunities for basic trainees and providing them with their own dedicated training lists.

Current cloud computing systems pose serious limitation to protecting users' data confidentiality. Since users' sensitive data is presented in unencrypted forms to remote machines owned and operated by third party service providers, the risks of unauthorized disclosure of the users' sensitive data by service providers may be quite high. There are many techniques for protecting users' data from outside attackers, but currently no effective way is available for protecting users' sensitive data from service providers in cloud computing. In this paper, an approach is presented to protecting the confidentiality of users' data from service providers, and ensures service providers cannot collect users' confidential data while the data is processed and stored in cloud computing systems. Our approach has three major aspects: (1) separating software service providers and infrastructure service providers in cloud computing, (2) hiding information about the owners of data, and (3) data obfuscation. An example to show how our approach can protect the confidentiality of users' data from service providers in cloud computing is given.

Accurate and appropriate assessment of surgical trainees requires clear determination of the skills needed for surgical competence. This study was designed to identify those skills, rank them in order of importance and translate them into behavioural terms. A Delphi technique, using anonymous postal questionnaires, was used. All consultant surgeons in South-East Scotland were asked to identify the skills they expected of surgical trainees. Skills identified were then returned to all consultants for weighting. Differences among specialties in the importance of each item were identified using analysis of variance. The qualities identified fell into five domains: technical skills, clinical skills, interaction with patients and relatives, teamwork, and application of knowledge. Consultants from all specialties gave high weightings to the generic domains of clinical skills, teamwork, and interaction with patients and relatives. This study has identified the skills considered necessary by consultant surgeons in Scotland for a successful surgical career. Contrary to expectation, consultant surgeons value many generic skills more highly than technical skills, indicating that they value well rounded doctors, not just those with technical ability. The characteristics identified are being used to develop an assessment tool for use on basic surgical trainees.

PurposeFocusing on the Indian context, with the increase in the amount of data and its analysis in health-care knowledge management (KM), the privacy concerns rise which results in loss of trust of an individual in e-health-care systems. Privacy issues in health care, specific to India, are caused by prevalent complacency, culture, politics, budget limitations, large population and infrastructures. Because of these factors, data security requires a backseat that allows easy access to confidential information. Furthermore, the prevalent culture affects health-care disclosure in India. In many cultures, disclosing sensitive personal health-care data is considered ill mannered. This leads to discrepancies in the recorded health-care data and a decrease in the level of treatment meted out. The results and statistics of treatments given do not match the records because of inaccurate data reporting. With the significant rise in the analysis and use of technology in health-care KM systems, it is important to understand the perception of KM in terms of its use and awareness about data sharing in the KM system. The purpose of the paper is to measure the perception of privacy issues in the context of Indian healthcare management systems.Design/methodology/approachTo measure the perception of the use of the KM system, a set of 20 questions was circulated with a sample size of 337 which includes health-care researchers, doctors, practitioners and patients. The questions focused upon the use, share the sensitive health data in the KM platform. All the demographic information such as age, sex, religion, occupation is recorded. The privacy of the individual is maintained while circulating the questionnaire. The usage of health KM system and its privacy is measured through means and t-test.FindingsThe results of the t-test were found positive. This research study finds that the privacy factor is important among the Indians to share the information with the KM repository. It is also found that medical practitioners or data custodians are not much serious about sensitive data is being stored for analysis. From the statistical perception of usage of KM and its privacy, new architecture and privacy guidelines were suggested which can be considered in future research.Research limitations/implicationsFrom the literature review, the questionnaire has developed which can help policymakers and hospital administrators collect information about KM processes in health-care organizations, and this can result in higher performance of health organizations. The privacy factor can also be included in typical health KM architecture ensure that while knowledge acquisition process, privacy of individual or organization can be maintained.Social implicationsKM enhances the value of corporations and business industries through knowledge production, distribution and provides reliable access to the knowledge resources. KM in health care can comprise a confluence of formal methodologies and techniques to facilitate the creation, identification, acquisition, development, preservation, dissemination and finally the utilization of the various facets of a health-care enterprise’s knowledge assets. According to IBM Global executive report in the year 2012, the entire health-care system has changed from diseases-centric to patient-centric. India is emerging in terms of revenue and employment in the health-care field. The advances of information and communication technology help the health-care sector streamline for data structure and access and health analytics.Originality/valueIn India, the KM is frequently used in health-care industries majorly by health-care practitioners and professionals. As health-care data and knowledge are considered to be sensitive, the privacy of an individual while using the data cannot be compromised. The proposed empirical work will provide a solution in determining the main barriers of implementing privacy policies that need to be solved first and to ensure effective implementation of KM in the health care of India.

The medical industry is growing significantly along with emerging technologies like IoT., The fundamental idea behind integrating IoT into healthcare facilities is to enable it remotely accessible. The contact between patient and his doc tor is easy as well detection of disease. The purpose of this research is to provide a secure healthcare framework. This framework used blockchain technique to encrypt the patients' data on cloud servers. The blockchain is adopted in the healthcare industry since data is vulnerable to attacks and patients' record is having sensitive information that should be secure from attacks. For the last few years, different blockchain models have been put forth in the health system. However, these models' decentralized nature-a hallmark of blockchain technology-has led to the emergence of an issue known as illness overlaps as the chains expands. This problem is addressed using a blockchain, which has the ability to add a new block of data in the chain whenever there is an updating in patients' record. Additionally, multilayer blockchain approach is considered to secure the sensitive patient's data. This strategy protects data as well as maintain trust for the user. In this framework, AES 128-bit key is generated which is then provides support to SHA-256. Data is arranged into different blocks and then each block is encrypted to prevent unauthorized access. A system is created to demonstrate how the suggested approach is applied in the real healthcare sector. The efficiency of the proposed framework is compared with the RSA and DSA that are the two widely used encryption methods. Such algorithms, which are essential to blockchain technology and are used in the proposed work, are later evaluated by comparing their performances to one another. According on research findings, the framework has the shortest encryption and decryption time, making its efficiency more reliable and effective. Additionally, it is more durable and effective.

The healthcare industry is increasingly vulnerable to cyberattacks, with sensitive patient data and critical operations becoming prime targets for malicious actors. In response, healthcare organizations are embracing the Zero Trust security model, which operates on the principle of "never trust, always verify." This model assumes that threats can emerge both outside and within the network and requires strict identity verification for every user and device attempting to access resources, regardless of their location. When combined with DevOps practices, Zero Trust strengthens security while maintaining the speed and agility necessary for modern healthcare systems. By embedding security into every phase of the development lifecycle, DevOps enables healthcare organizations to continuously monitor, test, and update their systems, ensuring that security measures evolve alongside emerging threats. Infrastructure as Code (IaC) plays a key role in this integration, automating the deployment and management of secure, scalable infrastructure, while continuous integration/continuous delivery (CI/CD) pipelines ensure that updates are deployed swiftly and securely. The synergy between Zero Trust and DevOps transforms healthcare IT operations, enabling real-time monitoring, dynamic threat response, and better protection of sensitive patient data. This article explores how healthcare providers are adopting this approach to meet compliance requirements, improve system resilience, and safeguard patient privacy, all while maintaining the operational efficiency and innovation required in today?s fast-paced digital landscape. With Zero Trust and DevOps working hand in hand, healthcare organizations can build a more secure, agile, and future-proof foundation for their digital transformation initiatives.

Background: Immuno-oncology (IO) therapies, particularly immune checkpoint inhibitors, have transformed cancer care but benefit only a subset of patients. Existing biomarkers such as PD-L1 expression, tumor mutational burden, and microsatellite instability have limited predictive power and are often cancer-type specific. Efforts to identify more generalizable biomarkers are hampered by tumor heterogeneity, restricted access to high-quality datasets, and stringent data privacy regulations, making traditional centralized discovery approaches difficult to scale. To address these challenges, we developed a distributed pipeline for discovering predictive transcriptomic biomarkers across diverse clinical datasets without sharing sensitive patient data. Methods: We developed a scalable, cloud-based distributed pipeline for biomarker discovery that operates across institutions without transferring sensitive patient data. Using curated gene expression profiles, we assessed tumor microenvironment and IO-related signatures in pan-cancer, cancer-specific, and treatment-specific contexts. A multivariable XGBoost model was trained within this distributed framework while maintaining local data governance. Model performance was evaluated against univariable signature-based models and multivariable models trained locally on individual datasets. Results: We implemented a distributed meta-integration pipeline to 18 datasets comprising 967 patients across seven cancer types treated with PD-1/PD-L1, CTLA-4, or combination immunotherapies. This analysis identified biomarkers specific to lung cancer and CTLA-4 therapy that were not detected in pan-cancer analyses, highlighting the value of context-specific associations. Several gene expression signatures were consistently linked to progression-free survival and treatment response in both pan-cancer and melanoma datasets, with notable overlap between PD-1/PD-L1 and dual checkpoint blockade therapies. Distributed multivariable models outperformed locally trained models on average, indicating improved generalizability, though performance often depended on cancer type and dataset composition, with univariable signature-based models outperforming in some settings. Conclusion: This study demonstrates a distributed framework for IO biomarker discovery that preserves patient privacy and facilitates collaboration across institutions. Our findings highlight the value of multi-institutional, diverse datasets in refining context-specific biomarkers and advancing precision IO therapies. Citation Format: Farnoosh Abbas-Aghababazadeh, Kewei Ni, Kevin (Xin) Wang, Sisira Kadambat Nair, Nasim BondarSahebi, John Stagg, Benjamin Haibe-Kains. Distributed Transcriptomic Modeling for Biomarker Discovery in Immuno-Oncology [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Artificial Intelligence and Machine Learning; 2025 Jul 10-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(13_Suppl):Abstract nr B044.

Health providers need to share patient information across healthcare networks efficiently and securely to improve medical and health services. Timely data synchronization among relevant parties is crucial for effectively containing and preventing the worsening of the condition. However, ensuring rapid information sharing while maintaining the security of sensitive patient data remains a pressing concern. In this paper, we introduce a cloud storage integrity auditing scheme that can protect auditors from procrastinating and preserve the privacy of sensitive information. Our proposed system requires healthcare institutions to encrypt sensitive patient data before uploading it to the cloud. It mandates the use of a data sanitizer for the secure processing of encrypted data blocks. Auditors must verify data integrity and promptly submit their audit results to the blockchain within a predefined time frame. Leveraging the time-sensitive nature of blockchain technology, healthcare institutions can monitor auditor compliance within the allotted validation timeframe. We conducted comprehensive security analysis and performance evaluations to demonstrate the feasibility and effectiveness of our solution in addressing the challenges of secure and timely cloud storage in healthcare settings.

Data Masking Technique is a system designed to secure sensitive data by replacing the front data but not the original data. For instance, the data masking techniques capable to hide any data from being viewed by any unauthorized users. However, fewer studies about data masking techniques in the attendance system are implemented. Previous studies have primarily concentrated on defining sensitive data exposure and the technique of securing sensitive data using data masking. Therefore, the aim of this paper is to integrate the use of the data masking technique towards the attendance verification system. Thus, it is sufficient to stop unauthorized users from accessing confidential data. This study also applied the iterative model as a software development methodology as well as integrated with the hashing concept. Therefore, the attendance verification system can be used to perform the functionalities of easily manage records. By using this technique, the attendance of a student was added with a security element. The result shows that data masking and hashing techniques ensure the confidentiality of student data from being viewed by unauthorized parties. The authorized person is the ability to see the masked of sensitive student data. The significance of this study is capable to implement the security element on the attendance system and verify the user before entering the system

Context-aware anonymous authentication protocols in the internet of things dedicated to e-health applications

The Internet of Things (IoT) based intelligent medical system possesses sensitive and private patient data. Most data relates to the patient's medical records and highly sensitive information. For this reason, safety and confidentiality of information are crucial. The preservation of patient privacy when sharing medical data is the primary concern of this study. Due to their excellent performance, biological notations based on deoxyribonucleic acid (DNA) are becoming increasingly admired for guaranteeing encryption and image protection. This paper proposes lightweight homomorphic with DNA-based medical image encryption (HDNA_MIE) for heterogeneous IoT in edge computing. The proposed approach contains two steps: In the first step, the secure DNA keys are generated using lightweight operations such as shifting and Josephus ring-based permutation (JRP). In the second step, the lightweight homomorphic cryptographic algorithm with DNA sequence-based encryption algorithm is suggested for secure encryption. The suggested strategy is evaluated using computational time and statistical analysis with several measures to determine its efficacy. The experimental findings of the proposed strategy exhibited a high level of security and a noticeable enhancement in the Number of Pixels Change Rate (NPCR), Unified Average Changing Intensity (UACI) and encryption processing time. The experiment outcomes demonstrate that our technique may be applied to highly confidential image encryption.

In order to protect the confidentiality and integrity of sensitive data in accounting information processing system, it was necessary to study the sensitive data encryption method. The current encryption method was mainly used different technology to make encryption for the sensitivity of sensitive data, which caused a problem of poor security. In order to improve the security of encryption, a hybrid encryption method for sensitive data of accounting information processing system was proposed. Firstly, the sensitive data was preprocessed. Then, based on the elliptic curve encryption mechanism, the additive and multiplicative homomorphic encryption methods of sensitive data were constructed respectively. Experimental results showed that the cryptographic running time obtained by our proposed method was relatively small and the increase in decryption computation overhead was smaller than the traditional method which was good to improve encryption security.

Traditional surgical training faces challenges related to sustainability, cost, and ethical considerations. Limited access to resources, ethical concerns about cadaver-based learning, limited availability of surgical cases, and the high costs associated with hands-on training impede the effectiveness and accessibility of surgical education. Despite these challenges, the need for direct tactile experience remains critical, as it fosters the development of essential motor skills and tactile abilities vital for surgical practice. However, advancements in immersive technologies such as virtual reality (VR), augmented reality (AR), and haptics offer a promising solution to address these challenges. VR and AR technologies offer realistic, controlled environments where learners can visualise anatomical structures and practice surgical procedures without risks. The integration of haptic feedback in these immersive simulations further enriches the learning process by adding the sense of touch and physical interaction, aiding in mastering critical surgical skills. The incorporation of immersive technologies in surgical training presents an opportunity to address the constraints of conventional methods. These technologies offer the possibility of creating platforms that replicate real-life surgical scenarios, allowing learners to hone their skills and build confidence in a safe and controlled environment. Moreover, immersive learning offers an ethical alternative to cadaver-based training and extends access to training materials irrespective of geographical limitations. Such an approach allows for step-based training, where students may begin acquiring skills through immersive learning, then move to special surgical simulators, and finally to patients. This article deals with the impact of immersive technologies such as VR, AR, and haptics on reshaping conventional surgical training, by focusing specifically on basic surgical skills. Targeting educators, medical experts, and involved parties, the article aims to stimulate additional exploration and adoption of immersive technologies to elevate surgical competencies and patient care standards.

Concern is being expressed about the state of basic surgical training in the context of growing demands to improve service provision in the National Health Service. Taking ophthalmology as a case example, we sent questionnaires to all 466 senior house officers (SHOs) in recognized surgical training posts in England, Wales, Scotland and Northern Ireland. The main outcome measures were intraocular surgery performed in the previous two weeks and since starting as an SHO in ophthalmology; access to protected teaching time or cases on theatre lists; and supervision during surgery. Phakoemulsification, the most common type of cataract surgery, was used as a generic indicator of intraocular procedures. 314 (67%) of the SHOs responded. Of those working in the hospital in the previous two weeks, 50% had performed at least one component part of a phakoemulsification (phako) operation and 44% had performed at least one full phako operation. The average number of full phako operations done per week was 0.741. 77% reported some protected surgical teaching time over the two weeks and those with protected teaching time reported more full phako operations per week. Of those who had performed at least one surgical procedure in the previous two weeks, 79% had been supervised by a consultant. Of those who had completed two or more years' training as an SHO, only 42% met the Royal College of Ophthalmologists minimum requirement of 50 complete intraocular operations performed under supervision. Women were less likely than men, and SHOs in district general hospitals were less likely than those in teaching hospitals, to have achieved this target. As many as half the SHOs in ophthalmology are not receiving an adequate basic surgical training. If this continues it may prove difficult to train sufficient new surgeons to an acceptable standard to meet the increasing demands of an ageing population. This is not an issue for ophthalmology alone but for all surgical specialties.