-
Sensors (Basel, Switzerland) Oct 2023The outreach of healthcare services is a challenge to remote areas with affected populations. Fortunately, remote health monitoring (RHM) has improved the hospital...
The outreach of healthcare services is a challenge to remote areas with affected populations. Fortunately, remote health monitoring (RHM) has improved the hospital service quality and has proved its sustainable growth. However, the absence of security may breach the health insurance portability and accountability act (HIPAA), which has an exclusive set of rules for the privacy of medical data. Therefore, the goal of this work is to design and implement the adaptive Autonomous Protocol (AutoPro) on the patient's emote ealthare (RHC) monitoring data for the hospital using fully homomorphic encryption (FHE). The aim is to perform adaptive autonomous FHE computations on recent RHM data for providing health status reporting and maintaining the confidentiality of every patient. The autonomous protocol works independently within the group of prime hospital servers without the dependency on the third-party system. The adaptiveness of the protocol modes is based on the patient's affected level of slight, medium, and severe cases. Related applications are given as glucose monitoring for diabetes, digital blood pressure for stroke, pulse oximeter for COVID-19, electrocardiogram (ECG) for cardiac arrest, etc. The design for this work consists of an autonomous protocol, hospital servers combining multiple prime/local hospitals, and an algorithm based on fast fully homomorphic encryption over the torus (TFHE) library with a ring-variant by the Gentry, Sahai, and Waters (GSW) scheme. The concrete-ML model used within this work is trained using an open heart disease dataset from the UCI machine learning repository. Preprocessing is performed to recover the lost and incomplete data in the dataset. The concrete-ML model is evaluated both on the workstation and cloud server. Also, the FHE protocol is implemented on the AWS cloud network with performance details. The advantages entail providing confidentiality to the patient's data/report while saving the travel and waiting time for the hospital services. The patient's data will be completely confidential and can receive emergency services immediately. The FHE results show that the highest accuracy is achieved by support vector classification (SVC) of 88% and linear regression (LR) of 86% with the area under curve (AUC) of 91% and 90%, respectively. Ultimately, the FHE-based protocol presents a novel system that is successfully demonstrated on the cloud network.
Topics: Humans; Blood Glucose Self-Monitoring; Computer Security; Blood Glucose; Confidentiality; Privacy; Delivery of Health Care
PubMed: 37896596
DOI: 10.3390/s23208504 -
JMIR Formative Research Nov 2023In tuberculosis (TB) control, nonadherence to treatment persists as a barrier. The traditional method of ensuring adherence, that is, directly observed therapy, faces...
Acceptability, Usefulness, and Ease of Use of an Enhanced Video Directly Observed Treatment System for Supporting Patients With Tuberculosis in Kampala, Uganda: Explanatory Qualitative Study.
BACKGROUND
In tuberculosis (TB) control, nonadherence to treatment persists as a barrier. The traditional method of ensuring adherence, that is, directly observed therapy, faces significant challenges that hinder its widespread adoption. Digital adherence technologies such as video directly observed therapy (VDOT) are emerging as promising solutions. However, as these novel technologies gain momentum, a critical gap is the lack of comprehensive studies evaluating their efficacy and the unique experiences of patients in Africa.
OBJECTIVE
The aim of this study was to assess patients' experiences that affected acceptability, usefulness, and ease of use with an enhanced VDOT system during monitoring of TB treatment.
METHODS
We conducted individual open-ended interviews in a cross-sectional exit qualitative study in Kampala, Uganda. Thirty participants aged 18-65 years who had completed the VDOT randomized trial were purposively selected to represent variability in sex, adherence level, and HIV status. We used a hybrid process of deductive and inductive coding to identify content related to the experience of study participation with VDOT. Codes were organized into themes and subthemes, which were used to develop overarching categories guided by constructs adapted from the modified Technology Acceptance Model for Resource-Limited Settings. We explored participants' experiences regarding the ease of use and usefulness of VDOT, thereby identifying the facilitators and barriers to its acceptability. Perceived usefulness refers to the benefits users expect from the technology, while perceived ease of use refers to how easily users navigate its various features. We adapted by shifting from assessing perceived to experienced constructs.
RESULTS
The participants' mean age was 35.3 (SD 12) years. Of the 30 participants, 15 (50%) were females, 13 (43%) had low education levels, and 22 (73%) owned cellphones, of which 10 (45%) had smartphones. Nine (28%) were TB/HIV-coinfected, receiving antiretroviral therapy. Emergent subthemes for facilitators of experienced usefulness and ease of VDOT use were SMS text message reminders, technology training support to patients by health care providers, timely patient-provider communication, family social support, and financial incentives. TB/HIV-coinfected patients reported the added benefit of adherence support for their antiretroviral medication. The external barriers to VDOT's usefulness and ease of use were unstable electricity, technological malfunctions in the app, and lack of cellular network coverage in rural areas. Concerns about stigma, disease disclosure, and fear of breach in privacy and confidentiality affected the ease of VDOT use.
CONCLUSIONS
Overall, participants had positive experiences with the enhanced VDOT. They found the enhanced VDOT system user-friendly, beneficial, and acceptable, particularly due to the supportive features such as SMS text message reminders, incentives, technology training by health care providers, and family support. However, it is crucial to address the barriers related to technological infrastructure as well as the privacy, confidentiality, and stigma concerns related to VDOT.
PubMed: 37948121
DOI: 10.2196/46203 -
Surgical Endoscopy Aug 2023Laparoscopic videos are increasingly being used for surgical artificial intelligence (AI) and big data analysis. The purpose of this study was to ensure data privacy in...
BACKGROUND
Laparoscopic videos are increasingly being used for surgical artificial intelligence (AI) and big data analysis. The purpose of this study was to ensure data privacy in video recordings of laparoscopic surgery by censoring extraabdominal parts. An inside-outside-discrimination algorithm (IODA) was developed to ensure privacy protection while maximizing the remaining video data.
METHODS
IODAs neural network architecture was based on a pretrained AlexNet augmented with a long-short-term-memory. The data set for algorithm training and testing contained a total of 100 laparoscopic surgery videos of 23 different operations with a total video length of 207 h (124 min ± 100 min per video) resulting in 18,507,217 frames (185,965 ± 149,718 frames per video). Each video frame was tagged either as abdominal cavity, trocar, operation site, outside for cleaning, or translucent trocar. For algorithm testing, a stratified fivefold cross-validation was used.
RESULTS
The distribution of annotated classes were abdominal cavity 81.39%, trocar 1.39%, outside operation site 16.07%, outside for cleaning 1.08%, and translucent trocar 0.07%. Algorithm training on binary or all five classes showed similar excellent results for classifying outside frames with a mean F1-score of 0.96 ± 0.01 and 0.97 ± 0.01, sensitivity of 0.97 ± 0.02 and 0.0.97 ± 0.01, and a false positive rate of 0.99 ± 0.01 and 0.99 ± 0.01, respectively.
CONCLUSION
IODA is able to discriminate between inside and outside with a high certainty. In particular, only a few outside frames are misclassified as inside and therefore at risk for privacy breach. The anonymized videos can be used for multi-centric development of surgical AI, quality management or educational purposes. In contrast to expensive commercial solutions, IODA is made open source and can be improved by the scientific community.
Topics: Humans; Artificial Intelligence; Privacy; Laparoscopy; Algorithms; Neural Networks, Computer; Video Recording
PubMed: 37145173
DOI: 10.1007/s00464-023-10078-x -
JMIRx Med Apr 2024To address the pandemic, the Defense Health Agency (DHA) expanded its TRICARE civilian provider network by 30.1%. In 2022, the DHA Annual Report stated that TRICARE's...
BACKGROUND
To address the pandemic, the Defense Health Agency (DHA) expanded its TRICARE civilian provider network by 30.1%. In 2022, the DHA Annual Report stated that TRICARE's provider directories were only 80% accurate. Unlike Medicare, the DHA does not publicly reveal National Provider Identification (NPI) numbers. As a result, TRICARE's 9.6 million beneficiaries lack the means to verify their doctor's credentials. Since 2013, the Department of Health and Human Services' (HHS) Office of Inspector General (OIG) has excluded 17,706 physicians and other providers from federal health programs due to billing fraud, neglect, drug-related convictions, and other offenses. These providers and their NPIs are included on the OIG's List of Excluded Individuals and Entities (LEIE). Patients who receive care from excluded providers face higher risks of hospitalization and mortality.
OBJECTIVE
We sought to assess the extent to which TRICARE screens health care provider names on their referral website against criminal databases.
METHODS
Between January 1-31, 2023, we used TRICARE West's provider directory to search for all providers within a 5-mile radius of 798 zip codes (38 per state, ≥10,000 residents each, randomly entered). We then copied and pasted all directory results' first and last names, business names, addresses, phone numbers, fax numbers, degree types, practice specialties, and active or closed statuses into a CSV file. We cross-referenced the search results against US and state databases for medical and criminal misconduct, including the OIG-LEIE and General Services Administration's (GSA) SAM.gov exclusion lists, the HHS Office of Civil Rights Health Insurance Portability and Accountability Act (HIPAA) breach reports, 15 available state Medicaid exclusion lists (state), the International Trade Administration's Consolidated Screening List (CSL), 3 Food and Drug Administration (FDA) debarment lists, the Federal Bureau of Investigation's (FBI) list of January 6 federal defendants, and the OIG-HHS list of fugitives (FUG).
RESULTS
Our provider search yielded 111,619 raw results; 54 zip codes contained no data. After removing 72,156 (64.65%) duplicate entries, closed offices, and non-TRICARE West locations, we identified 39,463 active provider names. Within this baseline sample group, there were 2398 (6.08%) total matches against all exclusion and sanction databases, including 2197 on the OIG-LEIE, 2311 on the GSA-SAM.gov list, 2 on the HIPAA list, 54 on the state Medicaid exclusion lists, 69 on the CSL, 3 on the FDA lists, 53 on the FBI list, and 10 on the FUG.
CONCLUSIONS
TRICARE's civilian provider roster merits further scrutiny by law enforcement. Following the National Institute of Standards and Technology 800, the DHA can mitigate privacy, safety, and security clearance threats by implementing an insider threat management model, robust enforcement of the False Claims Act, and mandatory security risk assessments. These are the views of the author, not the Department of Defense or the US government.
PubMed: 38602314
DOI: 10.2196/52198 -
Journal of the American Medical... Nov 2023To describe real-world practices and variation in implementation of the Information Blocking provisions amongst healthcare organizations caring for pediatric patients.
OBJECTIVE
To describe real-world practices and variation in implementation of the Information Blocking provisions amongst healthcare organizations caring for pediatric patients.
MATERIALS AND METHODS
An online survey regarding implementation practices was distributed to representatives from 10 participating US healthcare organizations located in 6 different states. The survey was followed by structured interviews conducted through video conference. Information was gathered about implementation practices at each organization, with a focus on patient and proxy portal access to, and segmentation capabilities of, certain data classes listed in the United States Core Data for Interoperability Version 1.
RESULTS
All organizations had implemented the information blocking provisions at their institution. All organizations utilized different portal account types for proxies and users. All organizations reported the capability of sharing labs, medications, problem lists, imaging, and notes with the parent/guardian of the non-adolescent minor user with differences in how sensitive elements within the data classes were protected. Variability existed in how data was shared with the remaining user types.
DISCUSSION
Significant variability exists in how organizations have implemented the information blocking rules. Variation in data sharing and data access between institutions can result in privacy breaches and create confusion about completeness of data for patients and families.
CONCLUSION
Healthcare organizations have utilized varying strategies to comply with the information blocking provisions of the 21st Century Cures Act. Increased clarity from the Office of the National Coordinator for Health Information Technology on minor, adolescent, and caregiver privacy and improved segmentation capabilities from Electronic Health Record vendors is needed.
Topics: Humans; Adolescent; United States; Child; Electronic Health Records; Confidentiality; Information Dissemination; Privacy; Medical Informatics
PubMed: 37643734
DOI: 10.1093/jamia/ocad172 -
Computer Methods in Biomechanics and... Oct 2023Medical health records comprise sensitive patient data for precise diagnosis and successive treatment. However, it must be stored and shared securely to protect data...
Medical health records comprise sensitive patient data for precise diagnosis and successive treatment. However, it must be stored and shared securely to protect data privacy. Generally, health records are kept on centralized servers, which raise the risk of security breaches and involve trust in a single authority that cannot efficiently defend data from internal attacks. Blockchain (BC) is extensively used in medical health records management because of its decentralized and tamper-proof properties. This work introduces a public-permissioned BC technology with a decentralized ledger (DL) to manage medical health records in the fog computing layer. The considered BC is decentralized and allows the transmission of records within the decentralized network of records. The data blocks are hashed using the SHA-256 hash algorithm. Especially, an Adaptive RSA Digital Signature Algorithm (ARSA-DS) is developed to prevent data tampering with medical health records in the fog computing layer. Moreover, an Ebola Search Optimization based Key Selection (ESO-KS) technique is employed to find the ideal key from the randomly generated keys to reduce processing time and increase overall efficiency. The proposed decentralized BC framework will help to preserve patient privacy and prevent the tampering of health records by attacks; moreover, it is efficient in terms of confidentiality, integrity, and availability.
PubMed: 37807911
DOI: 10.1080/10255842.2023.2262664 -
JMIR Human Factors Nov 2023Increased use of eHealth technology and user data to drive early identification and intervention algorithms in early psychosis (EP) necessitates the implementation of...
Incorporating Community Partner Perspectives on eHealth Technology Data Sharing Practices for the California Early Psychosis Intervention Network: Qualitative Focus Group Study With a User-Centered Design Approach.
BACKGROUND
Increased use of eHealth technology and user data to drive early identification and intervention algorithms in early psychosis (EP) necessitates the implementation of ethical data use practices to increase user acceptability and trust.
OBJECTIVE
First, the study explored EP community partner perspectives on data sharing best practices, including beliefs, attitudes, and preferences for ethical data sharing and how best to present end-user license agreements (EULAs). Second, we present a test case of adopting a user-centered design approach to develop a EULA protocol consistent with community partner perspectives and priorities.
METHODS
We conducted an exploratory, qualitative, and focus group-based study exploring mental health data sharing and privacy preferences among individuals involved in delivering or receiving EP care within the California Early Psychosis Intervention Network. Key themes were identified through a content analysis of focus group transcripts. Additionally, we conducted workshops using a user-centered design approach to develop a EULA that addresses participant priorities.
RESULTS
In total, 24 participants took part in the study (14 EP providers, 6 clients, and 4 family members). Participants reported being receptive to data sharing despite being acutely aware of widespread third-party sharing across digital domains, the risk of breaches, and motives hidden in the legal language of EULAs. Consequently, they reported feeling a loss of control and a lack of protection over their data. Participants indicated these concerns could be mitigated through user-level control for data sharing with third parties and an understandable, transparent EULA, including multiple presentation modalities, text at no more than an eighth-grade reading level, and a clear definition of key terms. These findings were successfully integrated into the development of a EULA and data opt-in process that resulted in 88.1% (421/478) of clients who reviewed the video agreeing to share data.
CONCLUSIONS
Many of the factors considered pertinent to informing data sharing practices in a mental health setting are consistent among clients, family members, and providers delivering or receiving EP care. These community partners' priorities can be successfully incorporated into developing EULA practices that can lead to high voluntary data sharing rates.
Topics: Humans; Focus Groups; User-Centered Design; Psychotic Disorders; California; Geraniaceae; Information Dissemination
PubMed: 37962921
DOI: 10.2196/44194 -
International Journal of Neonatal... Aug 2023Dried blood spot (DBS) cards from newborn screening (NBS) programs represent a wealth of biological data. They can be stored easily for a long time, have the potential...
Dried blood spot (DBS) cards from newborn screening (NBS) programs represent a wealth of biological data. They can be stored easily for a long time, have the potential to support medical and public health research, and have secondary usages such as quality assurance and forensics, making it the ideal candidate for bio-banking. However, worldwide policies vary with regard to the duration of storage of DBS cards and how it can be used. Recent advances in genomics have also made it possible to perform extended genetic testing on DBS cards in the newborn period to diagnose both actionable and non-actionable childhood and adult diseases. Both storage and secondary uses of DBS cards raise many ethical, clinical, and social questions. The openness of the key stakeholders, namely, parents and healthcare providers (HCPs), to store the DBS cards, and for what duration and purposes, and to extended genetic testing is largely dependent on local cultural-social-specific factors. The study objective is to assess the parents' and HCPs' awareness and receptivity toward DBS retention, its secondary usage, and extended genetic testing. A cross-sectional, self-administrated survey was adopted at three hospitals, out of which two were public hospitals with maternity services, between June and December 2022. In total, 452 parents and 107 HCPs completed and returned the survey. Overall, both HCPs and parents were largely knowledgeable about the potential benefits of DBS card storage for a prolonged period and its secondary uses, and they supported extended genetic testing. Knowledge gaps were found in respondents with a lower education level who did not know that a DBS card could be stored for an extended period ( < 0.001), could support scientific research ( = 0.033), and could aid public health research, and future policy implementation ( = 0.030). Main concerns with regard to DBS card storage related to potential privacy breaches and anonymity (Parents 70%, HCPs 60%). More parents, compared to HCPs, believed that storing DBS cards for secondary research does not lead to a reciprocal benefit to the child ( < 0.005). Regarding extended genetic testing, both groups were receptive and wanted to know about actionable childhood- and adult-onset diseases. More parents (four-fifths) rather than HCPs (three-fifths) were interested in learning about a variant with unknown significance ( < 0.001). Our findings report positive support from both parents and HCPs toward the extended retention of DBS cards for secondary usage and for extended genetic testing. However, more efforts to raise awareness need to be undertaken in addition to addressing the ethical concerns of both parents and HCPs to pave the way forward toward policy-making for DBS bio-banking and extended genetic testing in Hong Kong.
PubMed: 37606482
DOI: 10.3390/ijns9030045 -
BMC Medical Ethics Feb 2024To examine the understanding of the ethical dilemmas associated with Big Data and artificial intelligence (AI) among Jordanian medical students, physicians in training,...
Evaluating the understanding of the ethical and moral challenges of Big Data and AI among Jordanian medical students, physicians in training, and senior practitioners: a cross-sectional study.
AIMS
To examine the understanding of the ethical dilemmas associated with Big Data and artificial intelligence (AI) among Jordanian medical students, physicians in training, and senior practitioners.
METHODS
We implemented a literature-validated questionnaire to examine the knowledge, attitudes, and practices of the target population during the period between April and August 2023. Themes of ethical debate included privacy breaches, consent, ownership, augmented biases, epistemology, and accountability. Participants' responses were showcased using descriptive statistics and compared between groups using t-test or ANOVA.
RESULTS
We included 466 participants. The greater majority of respondents were interns and residents (50.2%), followed by medical students (38.0%). Most participants were affiliated with university institutions (62.4%). In terms of privacy, participants acknowledged that Big Data and AI were susceptible to privacy breaches (39.3%); however, 59.0% found such breaches justifiable under certain conditions. For ethical debacles involving informed consent, 41.6% and 44.6% were aware that obtaining informed consent posed an ethical limitation in Big Data and AI applications and denounced the concept of "broad consent", respectively. In terms of ownership, 49.6% acknowledged that data cannot be owned yet accepted that institutions could hold a quasi-control of such data (59.0%). Less than 50% of participants were aware of Big Data and AI's abilities to augment or create new biases in healthcare. Furthermore, participants agreed that researchers, institutions, and legislative bodies were responsible for ensuring the ethical implementation of Big Data and AI. Finally, while demonstrating limited experience with using such technology, participants generally had positive views of the role of Big Data and AI in complementing healthcare.
CONCLUSION
Jordanian medical students, physicians in training and senior practitioners have limited awareness of the ethical risks associated with Big Data and AI. Institutions are responsible for raising awareness, especially with the upsurge of such technology.
Topics: Humans; Cross-Sectional Studies; Big Data; Artificial Intelligence; Jordan; Students, Medical; Morals; Physicians
PubMed: 38368332
DOI: 10.1186/s12910-024-01008-0 -
Cureus Mar 2024Electronic health records (EHR) have revolutionized healthcare by providing efficient access to patient information, but their implementation poses various challenges.... (Review)
Review
Electronic health records (EHR) have revolutionized healthcare by providing efficient access to patient information, but their implementation poses various challenges. This paper examines the ethical and legal issues surrounding EHR adoption, particularly focusing on the healthcare landscape in India. Ethical considerations, including patient autonomy, confidentiality, beneficence, and justice, must guide EHR implementation to protect patient rights and privacy. Legal issues such as medical errors, malpractice, data breaches, and billing inaccuracies underscore the importance of robust policies and security measures. Threats to EHRs, such as phishing attacks, malware, encryption vulnerabilities, and insider threats, emphasize the need for comprehensive cybersecurity strategies. Overcoming challenges in EHR implementation requires meticulous planning, financial investment, staff training, and stakeholder support. Despite the complexities involved, the benefits of EHR adoption in improving patient care and operational efficiency justify the efforts required to address legal, ethical, and technical concerns. Embracing EHRs while mitigating associated risks is essential for delivering high-quality healthcare in the digital age.
PubMed: 38646271
DOI: 10.7759/cureus.56518