Healthtech Security
Article | August 31, 2023
Contents
1. Alexa, Are You There?
2. Digital Assistants-Cum-Doctor-Assistants
3. Toward An AI-Friendly Life!
1. Alexa, Are You There?
If Siri, Alexa, Google Now, or Cortana are your friends, you do not need any special introduction for today’s topic! This is because these digital assistants have become part and parcel of our lives; from completing our minimal tasks to helping us solve our problems, they make our day-to-day life simpler and more manageable. Popularly called AI, Artificial Intelligence is the simulation of human intelligence processes by machines. Similarly, Machine Learning, also called ML, is the capability of a machine to imitate intelligent human behavior.
2. Digital Assistants-cum-Doctor Assistants
The unpredictable pandemic years, which took thousands of lives, depict the rise of complexities in the healthcare industry. To deal with such cases in the future tactfully, the healthcare segment needs to be proactive and implement advanced technologies to detect, resolve, and prevent untimely death. Modern technologies such as Artificial Intelligence and Machine Learning help the medical fraternity perform tasks usually done by humans quickly and accurately, saving much time that can be utilized elsewhere.
Let’s take a quick tour of how AI and ML can boost the healthcare industry:
Artificial Intelligence can broadly scan patient databases or consult patients via a chatbot or online support system to understand their symptoms, send data to doctors, and get real-time diagnoses and prescribed medicines.
Machine Learning, a subset of AI, can replace traditional processes with a supervised one, as in, a patient can be treated based on similar symptoms and treatment of other patients. The process requires a quick scanning of the database, which can be time-consuming if done by human effort.
Taking technology by storm, patients suffering from neurological disorders can be treated via Brain-Computer Interfaces (BCI) backed by AI. With the help of this technology, normal bodily functions, such as the ability to move, speak or react, can be restored. It can also assist doctors in treating patients with strokes, locked-in syndrome, etc.The healthcare segment is revolutionizing, as sensitive operations such as heart surgery are being performed with robotic precision and control with AI-based algorithms. For this purpose, precision machine learning processes are being used to train robots and improve accuracy.
AI can also help in digital pathology. Instead of placing separate slides or tissue blocks and observing them manually, pathologists can do it via AI, which can help analyze digital slides using image analysis and machine learning.
3. Toward an AI-friendly Life!
If you never forget to wear a smartwatch, track daily steps, get water intake notifications, eat mindfully, and consistently monitor pulse rates, then you are already AI-friendly! You have successfully incorporated AI into your life and taken the first step towarda healthy life!
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Health Technology, Digital Healthcare
Article | August 16, 2023
Technology in the 21st century is the fuel that drives innovation and ease in almost every industry today. The healthcare sector isn’t far behind. In fact, the medical industry has taken the concept of the Internet of Things and took it to a new level altogether to reimagine the use of medical technology.
Imagine multiple devices like phones, cameras, GPS sensors, and computers interacting with each other through a seamless transfer of data. Now consider wearable medical devices. The exchange of critical medical information through a web of real-time data networks activates near instantaneous responses from doctors, nurses, and medical services. The aim is to anticipate the need for medical attention long before it is needed and remedy the concerns before they reach a critical stage.
That is exactly how the future of the Internet of Medical Things (IoMT) is shaping out to be.
How IoMT is Redefining Everyday Health?
IoMT is a next-generation solution that embeds cutting-edge monitoring and analysis of individual healthcare journeys through medical devices. The smart watch is the most recognizable wearable medical device that is used by millions of people daily to keep tabs on their vitals.
For instance, the Apple Watch series 6 maps blood oxygen levels, sleep patterns, ECG levels, and also reminds the user to wash their hands after returning home.
The market for healthcare IoT products is vast and is constantly expanding. The Tango Belt is a leading example of smart wearable technology that is revolutionizing elderly and disability care. The belt is designed to sense falls and deploy airbags to soften the impact. In addition, it alerts caregivers in the event of a fall. The belt also uses data analytics by collecting mobility data that is then synced to a smartphone app for displaying metrics.
Technologies that Empower IoMT
With the diverse tasks that medical devices must perform, applications exist across a wide spectrum, from artificial intelligence to 5G networks to the cloud.
Consider a pacemaker, for instance. Modern pacemakers are embedded with a multitude of technologies that communicate with each other to send critical patient data to physicians. A pacemaker is a bioelectronic implant that is placed in the chest to control the heartbeat. But a smart pacemaker goes a step further. It is equipped with wireless bluetooth technology that communicates with the patient’s wearable medical device. The smart device or phone will then transfer this data to physicians for check-ups and even alert doctors in the case of anomalies.
To Round It Off
IoMT will subsequently power all medical devices and usher in a future where technology forms the backbone of healthcare service delivery. Although wearable medical technology has been around for decades, the development of a streamlined communication channel between them has redefined their use. Smart medical devices are no longer just an aid but a source of vital individual medical data as well as a way to anticipate care and medical attention.
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Health Technology, Digital Healthcare
Article | August 21, 2023
Contents
1. Getting Started with LIMS Software
2. Benefits of Incorporating LIMS Software into Lab Management
3. LIMS Software Classification
4. Selecting the Right LIMS Software: A Comparison of Variants
5. How LIMS Software Revolutionized Laboratory Management
6. Future Scope
1. Getting Started with LIMS Software
Laboratory Information Management System (LIMS) software automates laboratory operations, improves productivity, and ensures the accuracy as well as reliability of laboratory data. It can be implemented in clinical laboratories, research & development labs, and environmental testing labs and tailored to meet specific needs. LIMS software seamlessly integrates with other laboratory systems, such as electronic lab notebooks and scientific data management systems.
LIMS class software enables storing and managing all information in one place, improving day-to-day work. Yet, research reveals that still 40% of industry leaders 'had not embarked on applying digital to research and development or quality control labs'.
(Source: Accenture)
2. Benefits of Incorporating LIMS Software into Lab Management
By implementing LIMS software, laboratories can significantly reduce time spent locating samples and records, entering data, and generating reports.
LIMS software also offers additional advantages when integrated into laboratory management, such as
1. Optimizing: LIMS automates laboratory processes, allowing for a paperless environment and increased productivity. It also ensures accurate test results by preventing the use of outdated instruments.
2. Automating: LIMS facilitates the input of essential sample information, including its source, date, time, and location of the collection as well as processing data.
3. Compliant: LIMS helps labs follow FDA regulations by creating an audit trail that tracks all activities, including record creation, modification, and deletion. It also enables electronic signatures to authenticate key activities and keep data secure and traceable.
4. Collaborative: LIMS streamlines inter-laboratory collaboration through the option to share data access. This allows lab technicians from disparate laboratories to be seamlessly assigned to different projects and obtain the required information without disruption.
5. Security: LIMS systems offer various mechanisms for managing user access, such as an in-built user management system with a unique username and password, integration with LDAP or Active Directory for user authentication, and access through an Identity Server.
3. LIMS Software Classification
Laboratory Information Management System software can be classified based on several criteria, including functionality, deployment model, industry focus, and the laboratory's needs.
Here is a list of critical features that can be considered while classifying LIMS software:
1. Functionality: Different LIMS software may have varying functionality, including sample tracking, data management, instrument integration, quality control, workflow management, and reporting.
2. Deployment Model: LIMS software can be deployed on-premises or in the cloud. On-premises deployment means that the software is installed and run on the laboratory's own servers, while cloud-based deployment means that the software is hosted and maintained by a third-party provider.
3. Industry Focus: LIMS software can be designed for specific industries or applications, such as pharmaceutical research, clinical laboratories, food and beverage testing, environmental testing, and more.
4. Open-Source vs. Proprietary: LIMS software can also be classified as either open-source or proprietary. Open-source software is freely available and can be modified by users, while a company owns proprietary software and requires a license to use it.
5. Scalability: The size of the laboratory and the number of users accessing the LIMS software can also be a factor in classification. Some LIMS software may be more scalable, allowing for easy expansion as the laboratory grows.
6. Integration Capabilities: LIMS software can also be classified based on its ability to integrate with other software or instruments. Some LIMS software may be more flexible and have better integration capabilities than others, allowing for seamless data exchange between different systems.
4. Selecting the Right LIMS Software: A Comparison of Variants
While selecting the most appropriate LIMS variant, the wide range of available options can pose a challenge for laboratory decision-makers. To aid in this selection process, a comprehensive comparative analysis of LIMS variants is presented below:
1. Lab managers can adopt an objective approach for evaluating and comparing different LIMS solutions by creating a grading rubric. This involves designing a table with separate columns for each LIMS vendor and rows listing the desired features as well as functionalities. To provide a more comprehensive evaluation, advanced rubrics may include rating each functionality on a particular LIMS using a scale of 1 to 5.
2. Next, it is crucial to review how LIMS solutions are structured and stored. This includes determining whether the solution is on-premise or cloud-based, either as a platform-as-a-service (PaaS) or software-as-a-service (SaaS). For optimal flexibility in the laboratory's computing structure, choosing a vendor that offers LIMS as a comprehensive solution is advantageous.
3. Data access must be controlled by using unique user IDs and passwords. Furthermore, data security standards such as HIPAA compliance and SSL encryption will likely be mandatory across many laboratory industries. It is thus imperative to carefully consider and ensure the security features of any potential LIMS solution.
4. To assess the level of support that can be expected with a particular LIMS, one effective method is to directly inquire with the software vendor about outages, response time, and plans of action to address any glitches preemptively. Managing expectations around the LIMS requires asking about the frequency of LIMS updates, including how often the platform is updated, how updates are announced and deployed, and the expected duration of any update-related outages.
5. While selecting a LIMS solution, laboratories must establish a target go-live date, especially when implementing the system in response to, or preparation for, an audit. Software vendors should provide a deployment and implementation timeline, which can be used to compare with the laboratory's objectives and goals. This helps to ensure that the LIMS solution is implemented in a timely and efficient manner.
5. How LIMS Software Revolutionized Laboratory Management
LIMS software has fundamentally revolutionized the laboratory management system in several ways. Before the advent of LIMS, laboratory operations were often paper-based and highly manual, leading to inefficiencies, errors, and inconsistencies. However, with the implementation of LIMS, laboratories have become more efficient, accurate, and compliant.
LIMS has also improved laboratory productivity, allowing scientists to focus on higher-value tasks like data analysis and interpretation. It has enabled collaboration between different laboratories, facilitating communication and knowledge sharing between scientists, researchers, and analysts, and is also leading to more significant innovation and progress in the field of science and research.
6. Future Scope
The future scope of Laboratory Information Management System software is promising as it continues to evolve and adapt to the changing needs of laboratory management. Potential developments include integrating emerging technologies such as artificial intelligence, machine learning, and robotics, cloud-based solutions for scalability and accessibility, IoT integration for automation and safety, enhanced data analytics for improved decision-making, and mobile applications for on-the-go access. Moreover, with SaaS LIMS, there are no license costs, minimal installation fees, and no need for in-house servers or databanks, resulting in reduced IT maintenance costs for hardware and software.
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Health Technology, Digital Healthcare
Article | September 8, 2023
Embark on a journey into the frontier of healthcare innovation in this article. Discover how EHR telemedicine and remote patient monitoring serve as catalysts, driving forward a new era in healthcare.
Contents
1. Integration of EHRs in Telemedicine and Remote Patient Monitoring
2. Technical Challenges and Solutions in EHR Integration
3. Financial Analysis: Cost-Benefit Assessment of Integration
4. Data Privacy and Consent in Integrated EHR-Telemedicine Systems
5. Forging Stronger Patient-Clinician Relationships
1. Integration of EHRs in Telemedicine and Remote Patient Monitoring
EHR telemedicine and remote patient monitoring have reshaped healthcare delivery by seamlessly integrating electronic health records, allowing healthcare providers and patients to exchange information effortlessly, regardless of geographical barriers. This synergy empowers healthcare professionals to access patients' comprehensive medical histories in real time, facilitating more informed decision-making during virtual consultations.
During the spring of 2020, when pandemic restrictions kept most people in the US at home, the use of telehealth rose to about 51%.
[Source: Elation Health]
Moreover, it enhances the accuracy of remote patient monitoring by providing up-to-date data, enabling timely interventions and improving overall healthcare outcomes. Integrating EHR telemedicine systems enhances efficiency and ensures that patient care remains at the forefront of modern healthcare, transcending traditional physical boundaries.
2. Technical Challenges and Solutions in EHR Integration
Navigating telehealth EHR integration and remote patient monitoring solutions uncovers a range of technical challenges, each with its own set of potential remedies. These include interoperability issues, which can be mitigated by adopting standardized data formats like HL7 FHIR. EHR interoperability solutions may involve using data exchange protocols such as HL7's Consolidated Clinical Document Architecture (C-CDA) or developing custom APIs to facilitate seamless data exchange between EHRs and telemedicine platforms. Additionally, the imperative need for data security and privacy is achieved through robust encryption and adherence to regulations like HIPAA or GDPR. Data integration challenges arising from varying EHR data storage methods can be resolved using middleware or integration platforms. Investing in telecom infrastructure and developing offline-capable telemedicine apps can address limited connectivity in remote areas. Ensuring real-time data access involves optimizing EHR databases and creating low-latency systems. Other challenges encompass integrating data from medical devices, ensuring data accuracy, scalability, user-friendly interfaces, regulatory compliance, and cost management strategies.
3. Financial Analysis: Cost-Benefit Assessment of Integration
When contemplating the integration of EHR telemedicine and remote patient monitoring systems, conducting a comprehensive cost-benefit analysis is crucial. This assessment covers financial aspects, including initial implementation costs (software development, hardware upgrades, training, and data migration), ongoing operational expenses (maintenance and data storage), and potential efficiency gains (streamlined workflows and improved data accessibility). It also evaluates the impact on patient outcomes, satisfaction, and financial benefits of enhanced healthcare quality, reduced readmissions, and increased patient engagement. Healthcare organizations can estimate cost savings in remote patient monitoring and explore expanding telemedicine services to underserved populations to make informed financial decisions.
Additionally, this analysis considers long-term financial viability and alignment with organizational goals, including regulatory compliance costs, risk assessment, scalability considerations, and the competitive advantages of integrated telemedicine services. By calculating ROI and assessing potential risks, healthcare entities can develop risk mitigation strategies, ensuring that EHR integration in telemedicine and remote patient monitoring enhances healthcare delivery and aligns with the organization's financial sustainability and long-term success.
4. Data Privacy and Consent in Integrated EHR-Telemedicine Systems
Data privacy and obtaining informed consent are paramount in integrated EHR and telemedicine systems. Patients should provide explicit consent, understanding the data collected and its intended use, with strict encryption protocols safeguarding data during transmission. Access controls and data minimization practices restrict unauthorized access, while patient portals enable individuals to manage their data-sharing preferences and revoke consent if needed. Compliance with regulations such as HIPAA or GDPR is crucial, as is maintaining comprehensive audit trails to track data access. Training, awareness, and robust incident response plans fortify data privacy efforts, fostering trust and transparency in these integrated systems where healthcare organizations and patients share responsibility for secure data handling.
5. Forging Stronger Patient-Clinician Relationships
Integrating EHR telemedicine and remote monitoring systems goes beyond mere efficiency and accessibility objectives. It serves as a catalyst for nurturing more substantial and meaningful patient-clinician relationships. This fusion of technology and healthcare has the capacity to bridge physical distances, allowing clinicians to truly understand and engage with their patients on a deeper level. Patients, armed with increased access to their health data, become more active participants in their healthcare, while clinicians, with their comprehensive information, can offer more personalized and informed guidance. The potential of EHR telemedicine reaches far beyond the digital screen; it empowers both patients and clinicians to collaborate in pursuit of improved health outcomes, ushering in a new era of patient-centric care grounded in trust, communication, and shared knowledge.
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