Patient-Generated Health Data Interoperability Through Master Patient Index: The DH-Convener Approach.

Patient-Generated Health Data (PGHD), such as data provided by wearable devices, hold promise to improve health outcomes. However, to improve clinical decision-making, PGHD should be integrated or linked with Electronic Health Records (EHRs). Typically, PGHD data are collected and stored as Personal Health Records (PHRs), outside EHR systems. To address this challenge, we created a conceptual framework for PGHD/EHR interoperability through the Master Patient Index (MPI) and DH-Convener platform. Then, we identified the corresponding Minimum Clinical Data Set (MCDS) of PGHD to be exchanged with EHR. This generic approach can be used as a blueprint in different countries.

An Intelligent Diabetic Patient Tracking System Based on Machine Learning for E-Health Applications.

BACKGROUND: Continuous surveillance helps people with diabetes live better lives. A wide range of technologies, including the Internet of Things (IoT), modern communications, and artificial intelligence (AI), can assist in lowering the expense of health services. Due to numerous communication systems, it is now possible to provide customized and distant healthcare. MAIN PROBLEM: Healthcare data grows daily, making storage and processing challenging. We provide intelligent healthcare structures for smart e-health apps to solve the aforesaid problem. The 5G network must offer advanced healthcare services to meet important requirements like large bandwidth and excellent energy efficacy. METHODOLOGY: This research suggested an intelligent system for diabetic patient tracking based on machine learning (ML). The architectural components comprised smartphones, sensors, and smart devices, to gather body dimensions. Then, the preprocessed data is normalized using the normalization procedure. To extract features, we use linear discriminant analysis (LDA). To establish a diagnosis, the intelligent system conducted data classification utilizing the suggested advanced-spatial-vector-based Random Forest (ASV-RF) in conjunction with particle swarm optimization (PSO). RESULTS: Compared to other techniques, the simulation's outcomes demonstrate that the suggested approach offers greater accuracy.

Using patient flow analysis with real-time patient tracking to optimize radiation oncology consultation visits.

PURPOSE: Clinical efficiency is a key component of the value-based care model and a driver of patient satisfaction. The purpose of this study was to identify and address inefficiencies at a high-volume radiation oncology clinic. METHODS AND MATERIALS: Patient flow analysis (PFA) was used to create process maps and optimize the workflow of consultation visits in a gastrointestinal radiation oncology clinic at a large academic cancer center. Metrics such as cycle times, waiting times, and rooming times were assessed by using a real-time patient status function in the electronic medical record for 556 consults and compared between before vs after implementation of the PFA recommendations. RESULTS: The initial PFA revealed four inefficiencies: (1) protracted rooming time, (2) inefficient communications, (3) duplicated tasks, and (4) ambiguous clinical roles. We analyzed 485 consult-visits before the PFA and 71 after the PFA. The PFA recommendations led to reductions in overall median cycle time by 21% (91 min vs 72 min, p < 0.001), in cumulative waiting times by 64% (45 min vs 16 min; p < 0.001), which included waiting room time (14 min vs 5 min; p < 0.001) and wait for physician (20 min vs. 6 min; p < 0.001). Slightly less than one-quarter (22%) of consult visits before the PFA lasted > 2 h vs. 0% after implementation of the recommendations (p < 0.001). Similarly, the proportion of visits requiring < 1 h was 16% before PFA vs 34% afterward (p < 0.001). CONCLUSIONS: PFA can be used to identify clinical inefficiencies and optimize workflows in radiation oncology consultation clinics, and implementing their findings can significantly improve cycle times and waiting times. Potential downstream effects of these interventions include improved patient experience, decreased staff burnout, financial savings, and opportunities for expanding clinical capacity.

Stereotactic Neurosurgical Robotics With Real-Time Patient Tracking: A Cadaveric Study.

BACKGROUND: Robotic neurosurgery may improve the accuracy, speed, and availability of stereotactic procedures. We recently developed a computer vision and artificial intelligence-driven frameless stereotaxy for nonimmobilized patients, creating an opportunity to develop accurate and rapidly deployable robots for bedside cranial intervention. OBJECTIVE: To validate a portable stereotactic surgical robot capable of frameless registration, real-time tracking, and accurate bedside catheter placement. METHODS: Four human cadavers were used to evaluate the robot's ability to maintain low surface registration and targeting error for 72 intracranial targets during head motion, ie, without rigid cranial fixation. Twenty-four intracranial catheters were placed robotically at predetermined targets. Placement accuracy was verified by computed tomography imaging. RESULTS: Robotic tracking of the moving cadaver heads occurred with a program runtime of 0.111 ± 0.013 seconds, and the movement command latency was only 0.002 ± 0.003 seconds. For surface error tracking, the robot sustained a 0.588 ± 0.105 mm registration accuracy during dynamic head motions (velocity of 6.647 ± 2.360 cm/s). For the 24 robotic-assisted intracranial catheter placements, the target registration error was 0.848 ± 0.590 mm, providing a user error of 0.339 ± 0.179 mm. CONCLUSION: Robotic-assisted stereotactic procedures on mobile subjects were feasible with this robot and computer vision image guidance technology. Frameless robotic neurosurgery potentiates surgery on nonimmobilized and awake patients both in the operating room and at the bedside. It can affect the field through improving the safety and ability to perform procedures such as ventriculostomy, stereo electroencephalography, biopsy, and potentially other novel procedures. If we envision catheter misplacement as a "never event," robotics can facilitate that reality.

Patient tracking during treatment of children with cancer in India - An exploratory study.

BACKGROUND: Abandonment of treatment, a major cause of treatment failure in low- and middle-income countries like India, is particularly high during the diagnostic and initial phase of treatment. Tracking of patients during this risk period may reduce treatment abandonment rates and increase quality of care. AIM: The primary aim was to pilot the use and check the acceptability of a tool for tracking children with cancer in New Delhi during the initial part of their treatment. Secondary aim was to estimate abandonment rates among these patients. METHODS: This prospective study was carried out in two centers of North India in New Delhi and enrolled children less than 18 years diagnosed with cancer at these centers and who had registered with Cankids for social support. Parent support group (PSG) workers maintained contact with the child's family at least once a week for the first 12 weeks. Details of each contact and subsequent action were recorded in a customized book (called "You are not alone" or YANA Book). Descriptive analysis of these contacts was done in Microsoft Excel and presented in frequencies and percentages. The five-point Likert scale was used to check the acceptability of the tool among the PSG workers. RESULTS: Seven PSG workers enrolled and tracked 81 patients (73% male with a median age of 6 years). During the 12-week study period, 986 contacts were attempted and three (3.7%) patients had abandoned their treatment. All PSG workers strongly agreed that the YANA book was simple to understand and use, decreased their workload, and helped provide better assistance to patients. CONCLUSION: The tool for patient tracking was well accepted by the PSG workers and considered easy to use. We now plan to implement our model as a routine service at all the partnering hospitals in India.

Implementing a Patient Tracking System in a Large EMS System.

Objective: Accurate tracking of patients poses a significant challenge to prehospital and hospital emergency medical providers in planned and unplanned events. Previous reports on patient tracking systems are limited primarily to descriptive reports of post incident reviews or simulated exercises. Our objective is to report our experience with implementing a patient barcode tracking system during various planned events within a large urban EMS system.Methods: In 2018, representatives from the Chicago Department of Public Health, Chicago Fire Department EMS, private EMS agencies, and 27 hospitals in the Chicago EMS System were trained on the use of a web-based patient tracking system using barcoded triage tags and wristbands to monitor triage category and hospital destination during an event. The tracking system was used on two planned operational days and three pre-planned mass gathering events. The primary outcome was the percent of patients initially scanned by EMS that were scanned by the hospital. Descriptive statistics were collected. Barriers to patient tracking system use were identified.Results: Each event was reviewed for the number of patients assigned a barcode identifier and scanned by EMS that were then scanned by the hospital. In the first planned operational day, 57% (359/622) of patients initially scanned by EMS were scanned by the hospital. In the second planned operational day, 88% (355/402) of EMS scanned patients were scanned by the hospital and 37% (133/355) were assigned a final disposition. At three city mass gathering events, there were 79% (50/63), 95% (190/199), and 82% (46/56) of EMS scanned patients also scanned by hospitals. Logistical and technological challenges were documented.Conclusions: Use of a web-based system with barcode identifiers successfully tracked patients from prehospital to hospital during planned operational days and mass gathering events. Percent of scanned patients increased after the first operational day and remained consistent in subsequent events. Limitations to the patient tracking system included logistical and technological barriers. Similar patient tracking systems may be implemented to assist with event management in other EMS systems.