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Internet of medical things and blockchain-enabled patient-centric agent through SDN for remote patient monitoring in 5G network
During the COVID-19 pandemic, there has been a significant increase in the use of internet resources for accessing medical care, resulting in the development and advancement of the Internet of Medical Things (IoMT). This technology utilizes a range of medical equipment and testing software to broadcast patient results over the internet, hence enabling the provision of remote healthcare services. Nevertheless, the preservation of privacy and security in the realm of online communication continues to provide a significant and pressing obstacle. Blockchain technology has shown the potential to mitigate security apprehensions across several sectors, such as the healthcare industry. Recent advancements in research have included intelligent agents in patient monitoring systems by integrating blockchain technology. However, the conventional network configuration of the agent and blockchain introduces a level of complexity. In order to address this disparity, we present a proposed architectural framework that combines software defined networking (SDN) with Blockchain technology. This framework is specially tailored for the purpose of facilitating remote patient monitoring systems within the context of a 5G environment. The architectural design contains a patient-centric agent (PCA) inside the SDN control plane for the purpose of managing user data on behalf of the patients. The appropriate handling of patient data is ensured by the PCA via the provision of essential instructions to the forwarding devices. The suggested model is assessed using hyperledger fabric on docker-engine, and its performance is compared to that of current models in fifth generation (5G) networks. The performance of our suggested model surpasses current methodologies, as shown by our extensive study including factors such as throughput, dependability, communication overhead, and packet error rate.
Journal Article
The State of Remote Patient Monitoring for Chronic Disease Management in the United States
Remote patient monitoring (RPM) increased exponentially during the COVID-19 pandemic. RPM programs commonly incorporate tools to capture and transmit health-relevant data from the home to the clinical space to augment the clinical decision-making process of health care providers. Given the potential to improve patient health outcomes, health care systems around the world are actively engaged in fashioning, implementing, and exploring the outcomes of various RPM program models. However, new challenges to health care systems include increasing RPM program enrollment, optimizing condition-specific RPM programs to best address the needs of specific patient groups, integrating new RPM-derived data streams into existing IT infrastructure, overcoming limited availability of desired remote monitoring technologies, and quantifying the health outcomes produced by RPM use. Herein, we identify stakeholders for RPM in the United States, summarize the landscape of RPM tools available for chronic disease management, discuss the current regulatory environment, delve into the benefits and challenges of integrating these tools into clinical practice, summarize aspects of coverage and reimbursement, and examine the knowledge and policy gaps regarding sustained use of RPM in clinical practice, along with associated opportunities.
Journal Article
Associations between remote patient monitoring and uncontrolled blood pressure among patients diagnosed with hypertension: Exploring variations by race/ethnicity
Hypertension (HTN) is a critical public health concern that disproportionately impacts racial/ethnic minorities. The recent COVID-19 pandemic spurred rapid adoption of virtual HTN treatment programs such as remote patient monitoring programs (RPM), including among minority populations. However, it is unclear how utilization patterns differ across racial/ethnic groups and what the implications are for HTN outcomes.
The present study examines whether the association between RPM utilization and uncontrolled BP differs by race/ethnicity among hypertensive patients enrolled in an RPM program.
This study includes an urban sample of HTN patients who were 18 ≥ years old who have been in their RPM programs for three consecutive months or longer. Our primary exposure measures are three widely used dichotomized RPM engagement metrics and uncontrolled BP outcomes were dichotomized as BP ≥ 140/90 and ≥ 130/80. We tested for effect modification by race/ethnicity across RPM utilization variables using multivariable logistic regression models.
Of 2920 participants, 59% were females, 37% were ≥ 65 years old, and Hispanic patients were the most represented race/ethnicity group (39%). Percentage-uncontrolled was 25% non-Hispanic Black, 21% Hispanic, and 20% among non-Hispanic White patients. Compared to non-Hispanic White patients with high RPM utilization, patients with no BP transmission had higher odds of uncontrolled BP: White (OR=1.72; 95% CI: 1.07-2.75), Black (OR=2.11; 95% CI: 1.32-3.39), and Other race (OR=2.36; 95% CI: 1.41-3.96). Similar patterns were observed for low clinician interactions and low portal use.
Disparities in RPM utilization and BP outcomes in our study parallel reported inequities in digital technology utilization and uncontrolled BP in the U.S. Future studies should aim to understand how utilization trends among various vulnerable populations influence HTN outcomes. Such findings may help inform efforts aimed at streamlining access and utilization of RPM to reduce utilization disparities and promote better BP control.
Journal Article
A View Beyond HbA1c: Role of Continuous Glucose Monitoring
Hemoglobin A1C (HbA1c) is used as an index of average blood glucose measurement over a period of months and is a mainstay of blood glucose monitoring. This metric is easy to measure and relatively inexpensive to obtain, and it predicts diabetes-related microvascular complications. However, HbA1c provides only an approximate measure of glucose control; it does not address short-term glycemic variability (GV) or hypoglycemic events. Continuous glucose monitoring (CGM) is a tool which helps clinicians and people with diabetes to overcome the limitations of HbA1c in diabetes management. Time spent in the glycemic target range and time spent in hypoglycemia are the main CGM metrics that provide a more personalized approach to diabetes management. Moreover, the glucose management indicator (GMI), which calculates an approximate HbA1c level based on the average CGM-driven glucose level, facilitates individual decision-making when the laboratory-measured HbA1c and estimated HbA1c are discordant. GV, on the other hand, is a measure of swings in blood glucose levels over hours or days and may contribute to diabetes-related complications. In addition, addressing GV is a major challenge during the optimization of glycemia. The degree of GV is associated with the frequency, duration, and severity of the hypoglycemic events. Many factors affect GV in a patient, including lifestyle, diet, the presence of comorbidities, and diabetes therapy. Recent evidence supports the use of some glucose-lowering agents to improve GV, such as the new ultra-long acting insulin analogs, as these agents have a smoother pharmacodynamic profile and improve glycemic control with fewer fluctuations and fewer nocturnal hypoglycemic events. These newer glucose-lowering agents (such as incretin hormones or sodium–glucose cotransporter 2 inhibitors) can also reduce the degree of GV. However, randomized trials are needed to evaluate the effect of GV on important diabetes outcomes. In this review, we discuss the role of HbA1c as a measure of glycemic control and its limitations. We also explore additional glycemic metrics, with a focus on time (duration) in glucose target range, time (duration) in hypoglycemia, GV, GMI, and their correlation with clinical outcomes.
Journal Article
Effectiveness of Remote Patient Monitoring Equipped With an Early Warning System in Tertiary Care Hospital Wards: Retrospective Cohort Study
Monitoring vital signs in hospitalized patients is crucial for evaluating their clinical condition. While early warning scores like the modified early warning score (MEWS) are typically calculated 3 to 4 times daily through spot checks, they might not promptly identify early deterioration. Leveraging technologies that provide continuous monitoring of vital signs, combined with an early warning system, has the potential to identify clinical deterioration sooner. This approach empowers health care providers to intervene promptly and effectively.
This study aimed to assess the impact of a Remote Patient Monitoring System (RPMS) with an automated early warning system (R-EWS) on patient safety in noncritical care at a tertiary hospital. R-EWS performance was compared with a simulated Modified Early Warning System (S-MEWS) and a simulated threshold-based alert system (S-Threshold).
Patient outcomes, including intensive care unit (ICU) transfers due to deterioration and discharges for nondeteriorating cases, were analyzed in Ramaiah Memorial Hospital's general wards with RPMS. Sensitivity, specificity, chi-square test for alert frequency distribution equality, and the average time from the first alert to ICU transfer in the last 24 hours was determined. Alert and patient distribution by tiers and vitals in R-EWS groups were examined.
Analyzing 905 patients, including 38 with deteriorations, R-EWS, S-Threshold, and S-MEWS generated more alerts for deteriorating cases. R-EWS showed high sensitivity (97.37%) and low specificity (23.41%), S-Threshold had perfect sensitivity (100%) but low specificity (0.46%), and S-MEWS demonstrated moderate sensitivity (47.37%) and high specificity (81.31%). The average time from initial alert to clinical deterioration was at least 18 hours for RPMS and S-Threshold in deteriorating participants. R-EWS had increased alert frequency and a higher proportion of critical alerts for deteriorating cases.
This study underscores R-EWS role in early deterioration detection, emphasizing timely interventions for improved patient outcomes. Continuous monitoring enhances patient safety and optimizes care quality.
Journal Article
Feasibility and User Experience of Digital Patient Monitoring for Real-World Patients With Lung or Breast Cancer
Background
Digital patient monitoring (DPM) tools can facilitate early symptom management for patients with cancer through systematic symptom reporting; however, low adherence can be a challenge. We assessed patient/healthcare professional (HCP) use of DPM in routine clinical practice.
Materials and Methods
Patients with locally advanced/metastatic lung cancer or HER2-positive breast cancer received locally approved/reimbursed drugs alongside DPM, with elements tailored by F. Hoffmann-La Roche Ltd, on the Kaiku Health DPM platform. Patient access to the DPM tool was through their own devices (eg, laptops, PCs, smartphones, or tablets), via either a browser or an app on Apple iOS or Android devices. Coprimary endpoints were patient DPM tool adoption (positive threshold: 60%) and week 1-6 adherence to weekly symptom reporting (positive threshold: 70%). Secondary endpoints included experience and clinical impact.
Results
At data cutoff (June 9, 2022), adoption was 85% and adherence was 76%. Customer satisfaction and effort scores for patients were 76% and 82%, respectively, and 83% and 79% for HCPs. Patients spent approximately 10 minutes using the DPM tool and completed approximately 1.0 symptom questionnaires per week (completion time 1-4 minutes). HCPs spent approximately 1-3 minutes a week using the tool per patient. Median time to HCP review for alerted versus non-alerted symptom questionnaires was 19.6 versus 21.5 hours. Most patients and HCPs felt that the DPM tool covered/mostly covered symptoms experienced (71% and 75%), was educational (65% and 92%), and improved patient-HCP conversations (70% and 83%) and cancer care (51% and 71%).
Conclusion
The DPM tool demonstrated positive adoption, adherence, and user experience for patients with lung/breast cancer, suggesting that DPM tools may benefit clinical cancer care.
Digital patient monitoring tools can facilitate early symptom monitoring and management for cancer through systematic symptom reporting; however, low adherence can be a challenge. This study assessed patient and healthcare professional use of such tools in routine clinical practice.
Journal Article
Use of Cellular-Enabled Remote Patient Monitoring Device for Hypertension Management in Pregnant Women: A Feasibility Study
IntroductionHypertension affects 5–10% of pregnancies in the United States. Chronic hypertension during pregnancy can have a significant impact on maternal and neonatal outcomes, especially in rural populations. Pregnancies complicated by hypertension are currently managed through frequent clinic visits or extended hospital stays. Cellular-enabled remote patient monitoring devices provide an alternative treatment method for women in rural areas.Research AimThis study aimed to measure the feasibility of and patient satisfaction with using an integrated model of cellular-enabled remote patient monitoring devices for blood pressure supported by a 24/7 nurse call center.MethodsIn a mixed methods pilot study, twelve women with chronic hypertension during pregnancy were given cellular-enabled BodyTrace™ blood pressure cuffs and weight scales. Participants’ blood pressures were continuously monitored by a nurse call center. Participants completed a survey and a brief semi-structured interview after two weeks.ResultsParticipants scored low on stress and anxiety with mean scores of 5.45 (SD = 3.56) and 8.09 (SD 3.62), respectively. Participants scored high on behavioral intention, system usability, and perceived benefits with mean scores of 8.73 (SD = 2.53), 75.91 (SD = 23.70), and 19.64 (SD = 5.92), respectively. Participants perceived benefits to using the device, including increased monitoring by health professionals, increased self-awareness, decreased number of clinic visits, and convenience of use. Perceived disadvantages included higher readings when compared to clinical readings.DiscussionCellular-enabled remote patient monitoring devices for blood pressure are a valuable tool for managing treatment of pregnancies complicated by hypertension.
Journal Article
A new trauma severity scoring system adapted to wearable monitoring: A pilot study
Wearable technologies represent a strong development axis for various medical applications and these devices are increasingly used in daily life as illustrated by smart watches’ popularisation. Combined with new data processing methods, it constitutes a promising opportunity for telemonitoring, triage in mass casualty situations, or early diagnosis after a traffic or sport accident. An approach to processing the physiological data is to develop severity scoring systems to quantify the critical level of an individual’s health status. However, the existing severity scores require a human evaluation. A first version of a severity scoring system adapted to continuous and real-time wearable monitoring is proposed in this article. The focus is made on three physiological parameters straightforwardly measurable with wrist-wearables: heart rate, respiratory rate, and SpO 2 , which may be enough to characterise continuously hemodynamic and respiratory status. Intermediate score functions corresponding to each physiological parameter have been established using a sigmoid model. The boundary conditions have been defined based on a survey conducted among 54 health professionals. An adapted function has also been developed to merge the three intermediate scores into a global score. The scores are associated with a triage tricolour code: green for a low-priority casualty, orange for a delayable one, red for an urgent one. Preliminary confrontation of the new severity scoring system with real data has been carried out using a database of 84 subjects admitted to the intensive care unit. Colour classification by the new scoring system was compared with independent physicians’ direct evaluation as a reference. The prediction success rate values 74% over the entire database. Two examples of continuous monitoring over time are also given. The new score has turned out to be consistent, and may be easily upgraded with the integration of additional vital signs monitoring or medical information.
Journal Article
Invasive and Non-Invasive Remote Patient Monitoring Devices for Heart Failure: A Comparative Review of Technical Maturity and Clinical Readiness
Heart failure (HF) represents a growing public health concern, driven by rising prevalence and the challenge of frequent, costly (re-)hospitalizations from decompensation. To address these, HF management has progressed towards incorporating devices for remote patient monitoring (RPM), with most being focused on identifying decompensation and providing timely, tailored pharmacological interventions. To date, the pool of devices has enlarged substantially, forming a spectrum of invasive and non-invasive options whose clinical adoption potential is yet to be determined. This review summarizes existing devices for RPM in HF care, with a major focus on technical characteristics and potential clinical efficacy. To unify the two traditionally separated groups, we re-classify the sampled devices in a single taxonomical dimension, the physical location of the sensing element(s), and objectively assess their current development state using the Medical Device Readiness Level, a metric that merges technical and clinical perspectives. Furthermore, we outline additional evaluative metrics within two complementary dimensions, focused on process efficiency and patient outcomes, ultimately offering a structured framework to evaluate clinical adoption.
Journal Article