HIPAA Research Articles

Implementing Resourcefulness Training© with Parent Caregivers of Children Dependent on Medical Technology During the COVID-19 Pandemic: Lessons Learned from a Randomized Controlled Trial.

Parent caregivers of children requiring life-saving medical technology (e.g., mechanical ventilation) report higher levels of stress and poorer health than other caregivers, often neglecting health-promoting behaviors for themselves. This article describes an iterative implementation science strategy used to improve intervention delivery for a randomized controlled trial testing a telehealth, cognitive-behavioral resourcefulness intervention with this population during the COVID-19 pandemic. This process consisted of reflective team meetings and content analysis. Initial adjustments were made after content analysis of pilot study materials before intervention delivery including an intervention script, checklist, online daily log, Health Insurance Portability and Accountability Act (HIPAA)-compliant texting option, training material access, and fidelity checks. In vivo adjustments were implemented in four areas: recruitment/engagement, participation and use of resources, in-person delivery, and virtual delivery. Our efforts to streamline intervention delivery were enhanced by incorporating an iterative implementation science strategy including analysis and adjustment of intervention delivery procedures to decrease participant burden and promote intervention adherence. Reflective team meetings and a collaborative, problem-solving approach to resolve the various barriers and challenges with the randomized controlled trial were integral components of intervention delivery. This study informs future intervention research by providing details of barriers faced, pragmatic adjustments made to intervention implementation, and lessons learned (NCT0410524; www.clinicaltrials.gov).

Developing remote patient monitoring infrastructure using commercially available cloud platforms

Wearable sensor devices for continuous patient monitoring produce a large volume of data, necessitating scalable infrastructures for efficient data processing, management and security, especially concerning Patient Health Information (PHI). Adherence to the Health Insurance Portability and Accountability Act (HIPAA), a legislation that mandates developers and healthcare providers to uphold a set of standards for safeguarding patients’ health information and privacy, further complicates the development of remote patient monitoring within healthcare ecosystems. This paper presents an Internet of Things (IoT) architecture designed for the healthcare sector, utilizing commercial cloud platforms like Microsoft Azure and Amazon Web Services (AWS) to develop HIPAA-compliant health monitoring systems. By leveraging cloud functionalities such as scalability, security, and load balancing, the architecture simplifies the creation of infrastructures adhering to HIPAA standards. The study includes a cost analysis of Azure and AWS infrastructures and evaluates data processing speeds and database query latencies, offering insights into their performance for healthcare applications.

Enhancing early detection of cognitive decline in the elderly: a comparative study utilizing large language models in clinical notes

BackgroundLarge language models (LLMs) have shown promising performance in various healthcare domains, but their effectiveness in identifying specific clinical conditions in real medical records is less explored. This study evaluates LLMs for detecting signs of cognitive decline in real electronic health record (EHR) clinical notes, comparing their error profiles with traditional models. The insights gained will inform strategies for performance enhancement. MethodsThis study, conducted at Mass General Brigham in Boston, MA, analysed clinical notes from the four years prior to a 2019 diagnosis of mild cognitive impairment in patients aged 50 and older. We developed prompts for two LLMs, Llama 2 and GPT-4, on Health Insurance Portability and Accountability Act (HIPAA)-compliant cloud-computing platforms using multiple approaches (e.g., hard prompting, retrieval augmented generation, and error analysis-based instructions) to select the optimal LLM-based method. Baseline models included a hierarchical attention-based neural network and XGBoost. Subsequently, we constructed an ensemble of the three models using a majority vote approach. Confusion-matrix-based scores were used for model evaluation. FindingsWe used a randomly annotated sample of 4,949 note sections from 1,969 patients (women: 1,046 [53.1%]; age: mean, 76.0 [SD, 13.3] years), filtered with keywords related to cognitive functions, for model development. For testing, a random annotated sample of 1,996 note sections from 1,161 patients (women: 619 [53.3%]; age: mean, 76.5 [SD, 10.2] years) without keyword filtering was utilised. GPT-4 demonstrated superior accuracy and efficiency compared to Llama 2, but did not outperform traditional models. The ensemble model outperformed the individual models in terms of all evaluation metrics with statistical significance (p<0.01), achieving a precision of 90.2% [95% CI: 81.9%-96.8%], a recall of 94.2% [95% CI: 87.9%-98.7%], and an F1-score of 92.1% [95% CI: 86.8%-96.4%]. Notably, the ensemble model showed a significant improvement in precision, increasing from a range of 70%-79% to above 90%, compared to the best-performing single model. Error analysis revealed that 63 samples were incorrectly predicted by at least one model; however, only 2 cases (3.2%) were mutual errors across all models, indicating diverse error profiles among them. InterpretationLLMs and traditional machine learning models trained using local EHR data exhibited diverse error profiles. The ensemble of these models was found to be complementary, enhancing diagnostic performance. Future research should investigate integrating LLMs with smaller, localised models and incorporating medical data and domain knowledge to enhance performance on specific tasks.

Standard HIPAA Authorization Forms Decreased Response Rates for a Multi-site Pragmatic Trial.

The Health Insurance Portability and Accountability Act (HIPAA) aims to safeguard patient information; however, complex legal language may lead to confusion and mistrust, and hinder enrollment in clinical trials. To evaluate the effect of a standard HIPAA authorization included in mailed survey packets on study enrollment for a multi-site pragmatic trial. This study is nested within an advance care planning pragmatic trial at 50 primary care clinics across three University of California (UC) Health Systems. We included English and Spanish-speaking seriously ill patients. One third of eligible patients received and 2/3 did not receive the HIPAA authorization in their enrollment packet. We compared enrollment rates at 3months and assessed the readability, understandability, and actionability of the standard HIPAA form using the Federal Plain Language Guidelines Checklist for Plain Language, the Automatic Readability Checker consensus calculator (grade 8 is the average reading level for US adults), and the Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P, 0-100%, 70% considered the minimum). Of 4632 eligible patients (mean age 71, 48% women, 11% Spanish-speaking, 40% racial/ethnic minority); 1543 received a mailed enrollment packet with a HIPAA form and 3089 did not. Patients mailed the HIPAA form were less likely to enroll (10.2% vs. 14.8%, p < 0.001). The standard HIPAA form scored at the 12th grade reading level, had a PEMAT-P Understandability score of 42%, had an Actionability score of 40%, and only met 50% of Federal Plain Language Guideline Checklist items. The inclusion of a standard HIPAA authorization in mailed enrollment packets for a large pragmatic trial led to lower rates of study enrollment. This study informs how HIPAA authorization forms should be redesigned to be more accessible to patients to prevent unnecessary barriers to research enrollment.

Optimizing trainee handoffs on a busy transfusion medicine service

Abstract Objective Within the healthcare system, handoff processes are critical to maintain safety &amp; continuality of care. Many handoff platforms exist for clinical inpatient housestaff specialties. However, these do not always align with the needs of clinical pathologists. Academic transfusion medicine (TM) services often oversee a hybrid of laboratory management, clinical services including apheresis therapy, and blood product management. To date, the literature is limited in describing the effectiveness of TM handoff in addressing these needs. Methods Our institution transitioned from using Microsoft Word document-based handoff to a Microsoft Sharepoint, browser-based handoff accessible via campus intranet or virtual private network (VPN). A verbal handoff accompanying the document remains unchanged. The previous Word document-based handoff followed the known structured communication framework (situation, background, assessment, and recommendation (SBAR)) structure for each patient. This document could only be concurrently edited by one user and was distributed via closed-loop encrypted email to ensure Health Insurance Portability and Accountability Act (HIPAA) compliance. The new Sharepoint-based handoff features an expanded format including patient name/medical record number (MRN), date of contact, category of service, history, assessment and a task (to-do) list. This site can be concurrently edited and viewed by multiple users. It is version-controlled and searchable. It is also customizable to enable tracking of issues that are not associated with a MRN, such as product inventory, on-call staffing, and product investigation. Six months following the handoff transition, trainees’ feedback towards both formats were solicited with a Likert scale-based survey. The survey was open to any trainee that had rotated on the TM service, regardless of whether they had experienced both handoff formats. Handoff measures that were surveyed included effectiveness at communicating important information, ease of use, time spent, impact on patient care, amount of detail, integration in patient management and general attitudes towards TM call. Trainee demographics were also collected. Results Out of 18 potential participants, 15 trainees responded to the survey. Trainees reported that the Word document-based handoff contained significantly more extraneous detail, took excessive time to write and required more time overall to draft compared to the Sharepoint-based handoff (all p=&amp;lt;0.05). They also found that the Sharepoint-based handoff was significantly easier to use compared to the Word document-based handoff (p=&amp;lt;0.05). Additionally, the Sharepoint-based handoff was reported to convey important information more effectively and reduced the duration of verbal handoff compared to the Word document-based handoff, though these were not statistically significant. Conclusions TM services have unique responsibilities and benefit from customized handoffs with discrete categories that reflect the TM service’s distinct role. Such structure can help create a more standardized, focused handoff that requires less drafting time and improves efficiency and user satisfaction.

An Efficient Multilayer approach for Securing E-Healthcare Data in Cloud using Crypto – Stego Technique

Healthcare data has been moving to cloud platforms in recent years, which has increased accessibility and scalability but also raised security issues. Ensuring data integrity and safeguarding private health information from unwanted access are critical. This paper presents a comprehensive strategy to integrate effective Elliptic Curve Cryptography ECC-AES with steganography techniques to improve the security of healthcare data in the cloud. ECCAES is especially well-suited for cloud situations with limited resources since it provides strong security with reduced key sizes. Confidentiality is guaranteed by encrypting healthcare data using ECC- AES before storage, reducing the possibility of data breaches. Steganography techniques are also integrated to improve security against skilled adversaries by adding an extra degree of obfuscation by concealing encrypted data inside innocuous files or images. Strict key management procedures, access control systems, and frequent security audits are important components of the proposed system that ensure adherence to Health Insurance Portability and Accountability Act (HIPAA) and General Data Protection Regulation (GDPR) compliance requirements pertaining to healthcare data protection. Programs for employee awareness and training are also crucial for reducing the likelihood of human mistakes. Healthcare businesses can safely use cloud technology while protecting patient data integrity and privacy by putting in place multi-layered security safeguards. The proposed system provides the multilayer security on healthcare data in cloud environment than other existing systems.

LEGAL REGULATION OF DIGITISING AND OUTSOURCING MEDICAL RECORDS DEPARTMENT IN INDIA

The whole deal with digitizing and outsourcing medical records in India is complicated. You've got a bunch of laws, guidelines, and ethical considerations all playing a role in ensuring data privacy, security, and patient confidentiality are on point. As the healthcare sector embraces digital solutions more and more, moving from old-fashioned paper records to electronic health records (EHRs) has become a big part of managing healthcare. The Information Technology (IT) Act of 2000, along with its updates, lays the groundwork for all the legal stuff surrounding electronic data and how it's kept secure. Then there's the Personal Data Protection Bill of 2019, which hasn't been passed yet but has some pretty comprehensive measures in place to protect personal data, including health info. On top of all that, the Ministry of Health and Family Welfare (MoHFW) has introduced the National Digital Health Mission (NDHM). This aims to create a national digital health system and puts a lot of emphasis on making sure data privacy and security are top-notch. When it comes to outsourcing the management of medical records to outside parties, there's a need to stick to legal standards and international best practices, like the ones laid out by the Health Insurance Portability and Accountability Act (HIPAA) in the United States. Healthcare providers need to make sure that the folks they outsource to are following confidentiality agreements and data protection protocols. It's all about reducing the risks of data breaches and unauthorized access. The legal framework also requires regular audits, safe data storage solutions, and using fancy encryption technology. To wrap it up, digitizing and outsourcing medical records in India is all about blending existing IT laws, upcoming data protection rules, and specific guidelines for the healthcare industry. The goal is to keep patient data safe while making healthcare more efficient. As the world of digital health data keeps changing, ongoing legal reforms and clear regulatory standards will be important to keep everything in check.

Feasibility and Acceptability of a REDCap-Embedded HIPAA-Compliant Text Messaging Application to Track Medication Adherence in Adolescents With Lupus.

Despite advances in clinical care and treatment options, adolescents with lupus continue to experience adverse health outcomes. Poor adherence to medication regimens is a major contributor to these negative outcomes. The utility of short message service (SMS) in tracking barriers to adherence prospectively remains untested for adolescents with lupus. Our objectives were (1) feasibility of incorporating a Health Insurance Portability and Accountability Act (HIPAA)-compliant SMS text messaging application into REDCap and (2) acceptability of using SMS text messaging to track barriers to medication adherence in adolescents with lupus. This study is a 12-week pilot cohort study of adolescents with SLE per the 1997 revised American College of Rheumatology. A REDCap-embedded HIPAA-compliant text messaging application was used to send biweekly messages with survey link to track medication adherence. Measures were completed. Descriptive statistics were used to summarize demographics, medical, and acceptability data. Response to text messages and survey completion rates were reported as a measure of feasibility. Most eligible adolescents approached agreed to participate (n = 17, 71% enrollment rate). The cellphone ownership rate among adolescents eligible for participation was 92%. Nine subjects responded to all text messages sent (53% response and completion rate). Eleven subjects (65%) responded to two thirds of the text messages. Overall, 77% of enrolled subjects completed at least half of the surveys sent. Reminders to complete surveys were sent to 30% of enrolled adolescents. This study shows that embedding a HIPAA-compliant SMS text message application in REDCap is feasible and can be used to engage adolescents with chronic conditions in monitoring between clinic visits.

Cybersecurity in Healthcare: Securing Patient Health Information (PHI), HIPPA compliance framework and the responsibilities of healthcare providers.

Healthcare industry is major target for cyberattacks, making the protection of public health information (PHI) and Personal Identifiable Information (PII) a prime issue. In this digital era, with health organizations shifting to electronic health records and telemedicine, they are facing a major cybersecurity attack such as ransomware, phishing, and data breaches. These attacks compromise patient privacy, pose serious risks to patient safety, and hinder healthcare operations. The Health Insurance Portability and Accountability Act (HIPAA) provides a comprehensive compliance framework to protect PHI, wherein health providers shall undertake administrative, physical and technical safeguards. Despite these regulations, many healthcare providers struggle with achieving and maintaining HIPAA compliance due to limited resources, outdated technologies, and the rapidly evolving nature of cyber threats. This paper explores the HIPAA compliance framework, examining the specific responsibilities of healthcare providers to secure PHI. Key measures taken include periodic analysis of risks, establishment of encryption and access control systems, and comprehensive employee training to minimize risks of cyber-attacks. The study highlights that there is a growing need for healthcare providers to adopt proactive, adaptive cybersecurity strategies to deal with emerging threats. By following HIPAA regulations and updating security practices continuously, healthcare providers can protect the PHI, ensure regulatory compliance and safeguarding patient trust. The findings emphasize the role of adhering to regulation and innovation both in managing cyber risks for the healthcare sector.

Utilization of Real-World Data in the Intervention to Reduce Early Peanut Allergy in Children (iREACH) Trial

ObjectiveTo demonstrate the use of linked, real-world data in the context of a pediatric practice-based clinical trial. ApproachThe Intervention to Reduce Early Peanut Allergy in Children (iREACH) is a two-arm, cluster randomized, controlled trial. The intervention included clinician education and clinical decision support to increase pediatric clinician adherence to the NIAID’s 2017 Prevention of Peanut Allergy guidelines during infants’ 4- and 6-month well child care visits. Electronic health record (EHR) data were shared with the data coordinating center under a Health Insurance Portability and Accountability Act (HIPAA) waiver. All caregivers of eligible infants were invited to complete two surveys via REDCap, an online survey platform. The consents included an optional HIPAA authorization to link EHR data with survey responses and authorization to collect and link administrative data from the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) program, if applicable. ResultsOverall, 30 Illinois pediatric practices participated. EHR data was collected for 18,480 infants of whom 4,331 had any caregiver survey data (23.4% response rate). Permission to link survey responses to EHR data was obtained for 3,950 infants among those with any survey data (91.2%). Consent for linking WIC data with study data was obtained for 229 infants and 194 mothers. ConclusionsAuthorization for data linkage in the consent forms allowed investigators to amass data to compare caregiver and clinician responses, generate hypotheses, and propose future research outside the scope of the main trial. ImplicationsMultiple real-world data sources can be effectively combined to extend the findings of clinical trials.

Staying Ahead of the Curve: The Case for Recovery Curves in Total Knee Arthroplasty

BackgroundSensor technology embedded within the total knee arthroplasty (TKA) implant has the potential to record data that can track recovery and provide diagnostic information. In this study, we introduce the concept of physical function recovery curve analytics, which are created from daily spatial-temporal gait metrics and step counts from a large cohort of TKA patients. MethodsIn our study population, 258 patients underwent a primary TKA with a smart implanted tibial extension between October 4, 2021, and July 15, 2022, by 33 surgeons. The average age was 63 years, with 138 (54%) women. All kinematic data was collected on a Health Insurance Portability and Accountability Act (HIPAA)-compliant cloud data management platform. ResultsSummaries of the gait parameters at 6 weeks are suggestive of differences between people over and under 65 years, with the older patients walking more slowly and having shorter stride lengths. The 6-week percentiles demonstrated a strong, linear correlation to the 12-week percentiles for each gait parameter, with correlation coefficients ranging from 0.87 to 0.92. ConclusionsA novel screening gait test at 6 weeks shows promising results for predicting patients who will likely have poor recovery based on at least 1 gait parameter recovery curve at 12 weeks with high sensitivity and specificity. A future study is needed to validate the screening tool with an independent set of patients.

Umbilical Artery Doppler and Adverse Outcomes in Severe Preeclampsia Without Fetal Growth Restriction: A Retrospective Cohort Study.

Background and objective Severe preeclampsia may be managed expectantly before 34 weeks gestation with close surveillance.Utilized in fetal growth restriction (FGR), evidence supports umbilical artery (UA) Dopplerpreventing neonatal morbidity from hypertensive disease and predicting adverse outcomes in preeclampsia. We evaluated the association of abnormal UA Doppler waveforms with early delivery (before 34 weeks gestation) and adverse maternal-fetal outcomes in patients with early severe preeclampsia without FGR. Methodology This is a retrospective cohort study of singleton pregnancies with International Classification of Diseases (ICD) Ninth or Tenth Revision, defined severe preeclampsia diagnosed before 34 weeks gestation without FGR from January 1, 2018, through January 27, 2023, at a large tertiary care center where S/D ratios were calculated from UA Doppler interrogation of a free loop of cord at least once weekly. This study was approved by the IRB (ID:00002216) and granted a full Health Insurance Portability and Accountability Act (HIPAA) waiver of consent. Exclusion criteria were major congenital anomalies, congenital infection, aneuploidy, leaving against medical advice >24 hours, and patient instability on admission defined as condition(s) precluding expectant management by the American College of Obstetrics and Gynecology. The primary outcome was delivery before 34 weeks gestation. Secondary outcomes were the mode of delivery and maternal/fetal complications. Patient characteristics and outcomes for normal versus abnormal UA Doppler groups were compared with chi-square, t-tests, and Fisher's exact test. Odds ratios and relative risks were calculated to compare outcomes. Results Of 194 patients with severe preeclampsia, 107 met inclusion criteria. Thirty-four patients had abnormal UA Doppler studies. There were no differences in demographic and clinical data between patients with normal and abnormal UA Doppler studies. Patients with abnormal UA Doppler studies were more likely to deliver before 34 weeks (OR=3.91; 95%CI 1.24-12.33) for worsening severe features (OR=3.85; 95% CI 1.42-10.41), and were less likely to deliver vaginally (OR=0.12; 95% CI 0.03-0.54). Abnormal UA Doppler studies were associatedwith an increased risk of neonatal complications (OR=6.46; 95% CI 1.42-29.42) and respiratory distress syndrome (RDS) (OR=4.75; 95%CI 1.32-17.16). Abnormal UA Doppler subgroups were divided into patients with elevated S/D >95% Acharya (N=22) and absent end-diastolic flow (EDF) (N=10). The elevated S/D group tended to deliver before 34 weeks gestation for worsening severe features (OR=3.71, 95% CI 1.144-12.050) and had a higher risk of neonatal complications (RR 1.404; 95% CI 1.213-1.624). The absent EDF subgroup was more likely to deliver before 34 weeks (RR=1.52; 95%CI 1.29-1.79) for abnormal fetal testing (OR=6.92; 95%CI 1.71-28.08) and undergo primary cesarean delivery (OR=7.23; 95%CI 1.43-36.61). Conclusion Pregnancies with severe preeclampsia without FGR displayed a high incidence of abnormal UA Doppler waveforms associated with loss of clinical stability and adverse fetal outcomes. The groups with more impedance to umbilical artery flow tended to deliver earlier, and as the Doppler shifted from elevated S/D to absent end-diastolic flow, the mode of delivery shifted to cesarean delivery with increased risk of abnormal fetal testing. These results support the utility of UA Doppler surveillance in severe preeclampsia.

Technical Feasibility and Safety of Image-Guided Biphasic Monopolar Pulsed Electric Field Ablation of Metastatic and Primary Malignancies

PurposeTo assess the technical feasibility and safety of image-guided percutaneous biphasic monopolar pulsed electric field (PEF) ablation of primary and metastatic tumors. Materials and MethodsWith institutional review board (IRB) approval and Health Insurance Portability and Accountability Act (HIPAA) compliance, this retrospective, single-institution study cohort of 17 patients (mean age, 53.5 years; range, 20–94 years) with overall progressive disease underwent 26 PEF ablation procedures for 30 metastatic (90%) and primary (10%) target lesions in the thorax (n = 20), abdomen (n = 7), and head and neck (n = 3). Concurrent systemic therapy was used in 14 of the 17 patients (82%). Follow-up imaging was scheduled for 1, 3, and 6 months after PEF ablation, and target and off-target lesion sizes were recorded. The overall response was assessed by the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 criteria with imaging immediately before PEF serving as baseline. Adverse events (AEs) were determined by the Society of Interventional Radiology (SIR) classification. ResultsPEF ablation procedures were well tolerated and technically feasible for all 17 patients. The mean initial sizes of the target and off-target tumors were 2.6 cm (standard deviation [SD] ± 1.5; range, 0.4–6.9 cm) and 2.2 cm (SD ± 1.1; range, 1.0–5.2 cm), respectively. Overall, 15 of the 30 (50%) target lesions and 12 of the 24 (50%) off-target lesions were unchanged or decreased in size at the patient’s last follow-up. Eight patients had overall stable disease (47%) at the last follow-up. Of the 26 AEs, there were 9 mild (35%) and 1 moderate (4%) AE. ConclusionsAll PEF procedures were technically feasible with 1 moderate AE and stable disease for 47% of patients with a median follow-up period of 3 months.

Increased Vitamin C Intake Is Associated With Decreased Pancreatic Cancer Risk.

Patients with pancreatic cancer have an unfavorable 5-year survival rate of approximately 3% due to diagnosis occurring at advanced stages. Prior research has proposed vitamin C may have a therapeutic and preventative role in pancreatic cancer. A Health Insurance Portability and Accountability Act (HIPAA) compliant national database was utilized to assess pancreatic cancer risk in patients with or without a history of vitamin C intake. The International Classification of Diseases (ICD) codes were used, specifically the International Classification of Diseases, 10th Edition (ICD-10) and International Classification of Diseases, Nineth Edition (ICD-9), between January 2010 and December 2020. Patients were matched, and statistical analyses were implemented. Chi-squared, logistic regression, and odds ratio were used to test for significance and to estimate relative risk. A total of 83,941 patients were identified as utilizing prescribed vitamin C. Subsequent matching by Charlson Comorbidity Index (CCI) score and age resulted in two groups of 50,384 patients. The incidence of pancreatic cancer was 243 (0.48%) in the group with a history of vitamin C intake compared to 442 (0.88%) in the control group. The difference was statistically significant by P < 3.174 × 10-14 with an odds ratio of 0.548 (95% confidence interval (CI): 0.468 - 0.641). Overall, patients without vitamin C prescription had an increased prevalence of pancreatic cancer throughout all ages and regions of the United States when compared to those with a vitamin C prescription. In addition, healthcare costs were higher in total for the control group when compared to the experimental group. This retrospective cohort study found a statistically significant correlation between vitamin C and subsequent incidence of pancreatic cancer. Further studies are recommended to explore vitamin C's redox and cofactor activity in the context of preventing and possibly treating pancreatic cancer, as well as consider pancreatic cancer lifestyle risk factors such as smoking.

Enhancing healthcare data privacy and security: A comparative study of regulations and best practices in the US and Nigeria

The imperative for robust healthcare data privacy and security is escalating as healthcare systems worldwide are increasingly digitized. This review paper presents a comprehensive comparative analysis of the regulatory frameworks, challenges, and best practices related to healthcare data privacy and security in the United States and Nigeria. By examining the Health Insurance Portability and Accountability Act (HIPAA) in the US and the Nigeria Data Protection Regulation (NDPR) alongside other local regulations, this study highlights the nuances of each country's approach to safeguarding patient data. The analysis extends to the effectiveness of technological solutions like encryption and blockchain, and assesses the role of governance in policy implementation. Case studies from both nations offer insights into successful strategies and underscore the gaps and opportunities for cross-country learning and improvement. The paper concludes with targeted recommendations for policymakers and healthcare providers, aiming to strengthen the security measures and propose areas for further research and development in healthcare data management. This comparative study not only sheds light on current practices but also charts a course for future collaborative efforts to enhance data privacy and security in healthcare on a global scale.

FedGMMAT: Federated generalized linear mixed model association tests.

Increasing genetic and phenotypic data size is critical for understanding the genetic determinants of diseases. Evidently, establishing practical means for collaboration and data sharing among institutions is a fundamental methodological barrier for performing high-powered studies. As the sample sizes become more heterogeneous, complex statistical approaches, such as generalized linear mixed effects models, must be used to correct for the confounders that may bias results. On another front, due to the privacy concerns around Protected Health Information (PHI), genetic information is restrictively protected by sharing according to regulations such as Health Insurance Portability and Accountability Act (HIPAA). This limits data sharing among institutions and hampers efforts around executing high-powered collaborative studies. Federated approaches are promising to alleviate the issues around privacy and performance, since sensitive data never leaves the local sites. Motivated by these, we developed FedGMMAT, a federated genetic association testing tool that utilizes a federated statistical testing approach for efficient association tests that can correct for confounding fixed and additive polygenic random effects among different collaborating sites. Genetic data is never shared among collaborating sites, and the intermediate statistics are protected by encryption. Using simulated and real datasets, we demonstrate FedGMMAT can achieve the virtually same results as pooled analysis under a privacy-preserving framework with practical resource requirements.

Regulatory compliance in the age of data privacy: A comparative study of the Nigerian and U.S. legal landscapes

This comparative study delves into the intricate regulatory compliance mechanisms governing data privacy in Nigeria and the United States. Employing a qualitative methodology, this research synthesizes existing literature and case studies to highlight the pivotal role of data protection regulations in safeguarding personal information in an increasingly digital world. The analysis begins with an exploration of the conceptual framework of data privacy, emphasizing key principles such as transparency, accountability, and data minimization. It then meticulously examines the Nigerian Data Protection Regulation (NDPR) and the diverse U.S. legal landscape, including the California Consumer Privacy Act (CCPA) and the Health Insurance Portability and Accountability Act (HIPAA). The main findings reveal significant differences in regulatory approaches, with Nigeria's centralized enforcement by the National Information Technology Development Agency (NITDA) contrasting sharply with the U.S.'s fragmented state and federal oversight. Case studies underscore the challenges faced by both jurisdictions in ensuring compliance, ranging from resource constraints in Nigeria to the complexities of navigating multiple regulatory requirements in the U.S. The study concludes that while both countries emphasize the importance of data privacy, their divergent legal landscapes reflect unique cultural, economic, and operational contexts. The research recommends harmonizing data protection standards, enhancing enforcement mechanisms, and fostering greater public awareness to address the evolving challenges of data privacy. This study contributes to the global discourse on data privacy by offering insights into the strengths and weaknesses of different regulatory frameworks, thereby providing a roadmap for policymakers, businesses, and other stakeholders to navigate the complexities of data privacy compliance. Keywords: Data Privacy, Regulatory Compliance, Nigeria, United States, Data Protection, Legal Frameworks.

Using Electronic Health Record Mortality Data to Promote Goals-of-Care Discussions in Seriously Ill Transferred Patients: A Pilot Study

Abstract Background Mortality prediction data may aid in identifying seriously ill transferred patients at high risk of dying and facilitate early goals-of-care discussions (GOCD); however, this is rarely evaluated. We recently developed a model for predicting 30-day inpatient mortality, which may be useful for promoting early GOCD. Objectives Our objectives were to examine the effects of sharing model-generated mortality risk with hospitalists by assessing (1) if hospitalists agreed with the mortality risk prediction, (2) if they planned to conduct GOCD or consult palliative care within 72 hours of transfer, and (3) if the communication alert affected GOCD timing and other clinical outcomes. We also aimed to measure the association between both the model-generated and hospitalists' stratified risk assessments with patient mortality. Methods This was a nonrandomized quasi-experimental pilot study with a historical control group. On the second day of hospitalization, the model-generated risk was communicated to the hospitalists. Hospitalists were asked to answer questions via a HIPAA (Health Insurance Portability and Accountability Act)-compliant mobile communication system, and clinical outcomes were extracted via chart review. Results Eighty-four patients (42 in the control and 42 in the intervention group) were included in this study. Hospitalists agreed that all patients in the intervention group were at risk for inpatient mortality. Hospitalists were more likely to indicate a plan to conduct GOCD in the intervention group (n = 9) compared with the control group (n = 4, p &lt; 0.001). In this subset of patients, GOCD was completed within 72 hours in 78% of intervention patients (n = 7) as compared with 50% in the control group (n = 2). The greater absolute value of the model-generated mortality risk was significantly associated with deaths (p = 0.01), similar to the hospitalists' prediction of the mortality risk (p = 0.02). Conclusion Communicating model-generated mortality risk to hospitalists is a promising approach to promote timely GOCD.

GEN-RWD Sandbox: bridging the gap between hospital data privacy and external research insights with distributed analytics

BackgroundArtificial intelligence (AI) has become a pivotal tool in advancing contemporary personalised medicine, with the goal of tailoring treatments to individual patient conditions. This has heightened the demand for access to diverse data from clinical practice and daily life for research, posing challenges due to the sensitive nature of medical information, including genetics and health conditions. Regulations like the Health Insurance Portability and Accountability Act (HIPAA) in the U.S. and the General Data Protection Regulation (GDPR) in Europe aim to strike a balance between data security, privacy, and the imperative for access.ResultsWe present the Gemelli Generator - Real World Data (GEN-RWD) Sandbox, a modular multi-agent platform designed for distributed analytics in healthcare. Its primary objective is to empower external researchers to leverage hospital data while upholding privacy and ownership, obviating the need for direct data sharing. Docker compatibility adds an extra layer of flexibility, and scalability is assured through modular design, facilitating combinations of Proxy and Processor modules with various graphical interfaces. Security and reliability are reinforced through components like Identity and Access Management (IAM) agent, and a Blockchain-based notarisation module. Certification processes verify the identities of information senders and receivers.ConclusionsThe GEN-RWD Sandbox architecture achieves a good level of usability while ensuring a blend of flexibility, scalability, and security. Featuring a user-friendly graphical interface catering to diverse technical expertise, its external accessibility enables personnel outside the hospital to use the platform. Overall, the GEN-RWD Sandbox emerges as a comprehensive solution for healthcare distributed analytics, maintaining a delicate equilibrium between accessibility, scalability, and security.

Mobile Health Interventions: A Frontier for Mitigating the Global Burden of Cardiovascular Disease.

Mobile health (mHealth) interventions have emerged as a promising approach for cardiovascular disease (CVD) prevention and management. The proliferation of smartphones and wearable devices enables convenient access to health monitoring tools, educational resources, and communication with healthcare providers. mHealth interventions encompass mobile apps, wearables, and telehealth services that empower users to monitor vital signs, adhere to medication, and adopt healthier lifestyles. Their effectiveness hinges on user engagement, leveraging behavioral science principles and gamification strategies. While mHealth offers advantages such as personalized support and increased reach, it faces challenges pertaining to data privacy, security concerns, and resistance from healthcare providers. Robust encryption and adherence to regulations like the Health Insurance Portability and Accountability Act (HIPAA) are crucial for safeguarding sensitive health data. Integrating mHealth into clinical workflows can enhance healthcare delivery, but organizational adjustments are necessary. The future of mHealth is closely intertwined with artificial intelligence (AI), enabling remote monitoring, predictive algorithms, and data-driven insights. Tech giants are incorporating advanced health-tracking capabilities into their devices, paving the way for personalized wellness approaches. However, mHealth grapples with ethical dilemmas surrounding data ownership, privacy breaches, and inadvertent data capture. Despite its potential, mHealth necessitates a concerted effort to overcome obstacles and ensure ethical, secure, and practical implementation. Addressing technical challenges, fostering standardization, and promoting equitable access are pivotal for unlocking the transformative impact of mHealth on cardiovascular health and reducing the global burden of CVD.