Health Technology, AI
Article | July 18, 2023
Embracing the AI Revolution: Transforming Digital Healthcare Software through AI-Enhanced UX Testing
The wave of demographic change sweeping the United States presents an urgent call to action for healthcare providers. According to the US Census Bureau, adults over 65 will account for a quarter of the US population by 2060, signaling a drastic shift in healthcare delivery needs. More than half a million of this demographic will be centenarians, accentuating the need for digital experiences tailored to seniors' unique needs.
Despite the rapid advancement of digital health technologies, research indicates that many senior citizens struggle to adapt. A recent study reported that 40% of adults over 65 believe their telemedicine visit was inferior to traditional in-person care, with a meager 5% finding it superior. The promise of convenience delivered by digital health is often overshadowed by the frustration associated with technical difficulties. An astounding 75% of senior citizens admit they need assistance when using new electronic devices.
Let's consider the patient portal app, a common touchpoint in the digital health journey. Despite its apparent simplicity, seniors find processes like logging in troublesome due to issues like forgotten passwords, technical bugs, or content readability. This scenario underlines the crucial need for comprehensive User Experience (UX) testing to eliminate these barriers and provide a seamless digital health experience.
The Complex Landscape of Healthcare UX Testing
The complexity of UX testing in healthcare has been exacerbated by the interplay of multiple modules, services, platforms, and vendors. Take Electronic Medical Record (EMR) systems, for instance, which undergo frequent updates, each one potentially impacting the system as a whole. Traditional manual testing methodologies are proving to be time-consuming and costly.
Though automation has revolutionized sectors from automotive to finance, the healthcare industry appears to be lagging. A study by the Health Information and Management Systems Society (HIMSS) reveals that a mere 15% of healthcare providers have adopted modern test automation platforms. Meanwhile, a significant 41% still rely on manual testing. As EMR systems grow increasingly complex and customized, this over-reliance on manual testing poses daunting challenges.
The gravity of this issue is amplified by a startling revelation from the HIMSS study - only 6% of healthcare executive leaders express confidence in their organizations' testing practices. In an increasingly digitized healthcare environment, such a low level of assurance raises substantial concerns about patient safety. Although 75% of the surveyed providers have invested in software testing to safeguard their bottom lines, nearly two-thirds confess feeling inadequately resourced in terms of time, money, and talent to meet future testing requirements. As the list of testing demands grows, QA teams are frequently stretched thin, leaving many potential user journey scenarios untested.
The Power of AI in UX Testing for Better Patient Outcomes
AI technologies hold the potential to revolutionize UX testing in healthcare.
The modern healthcare application is a labyrinth of potential user journeys - a typical mobile application model can yield over 9 billion separate scenarios. To effectively navigate this colossal testing landscape, test automation tools employing Machine Learning (ML) algorithms are critical.
By analyzing historical patterns, prioritized cases, and real-user insights, ML algorithms can auto-generate test cases and meticulously scrutinize each user interaction. This approach ensures an optimal digital experience and robust coverage of potential issues.
The HIMSS study also provides a glimmer of hope, revealing that nearly 80% of healthcare providers plan to adopt real-time testing analytics for quality assurance. AI's role becomes pivotal in augmenting the capacity of software testing teams in this scenario.
By leveraging historical patterns and prioritizing test cases, ML-powered testing tools can automate crucial tests across various platforms, devices, and operating systems. This symbiosis of human expertise and AI not only bolsters productivity but enables comprehensive testing coverage within tight time constraints.
The Future of Healthcare Software UX Testing
The path to perfecting a patient’s digital journey is fraught with challenges.
Healthcare organizations venturing into automated software testing or contemplating in-house tool replacement must stay abreast of evolving healthcare testing requirements. This understanding is key when evaluating automation vendors against the backdrop of regulatory standards. Opting for a technology-agnostic solution ensures extensive test coverage, boosts efficiency, and guarantees longevity as technologies advance. Introducing your software QA teams to user-friendly, low/no-code test automation tools can simplify the onboarding process and fosters better collaboration with Dev teams and business testers.
As we stand at the precipice of this transformative period in healthcare, it's clear that the AI revolution holds the key to unlocking the future of digital healthcare UX testing. By harnessing AI's potential, healthcare providers can ensure a user-friendly, seamless digital experience for the fastest-growing demographic, setting new industry standards in the process.
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Health Technology, Digital Healthcare
Article | July 14, 2023
It’s no secret now that healthcare is an in-demand field. Today, business leaders need modern and intelligent decision-making solutions for their customers and clients. They must also focus on the right investment areas and learn the tricks for investing, spending, and setting goals for revenue generation to accelerate business.
With continuous developments in the healthcare sector, integrating AI into processes can help increase ROI. Therefore, if you, like any other business leader, are looking for solutions to empower your services and products in the healthcare domain, this article will help you through AI’s ultimate use cases and churn out a higher ROI.
What’s with AI in Healthcare at Present?
AI’s role in healthcare is evolving and enhancing traditional business operations, particularly marketing. According to a study by IBM, 71% of customers expect real-time communication. Thus, global demand is fueling the rising adoption of AI marketing solutions.
The effects of AI in healthcare are evident. Gartner reports increased marketing efficiency and effectiveness (86%), improved decision-making (71%), better data analysis and new insights (79%). Global AI spending will rise from $450 million in 2019 to over $28 billion by 2024 is not surprising.
Similar and further studies are ongoing on various use cases of AI in healthcare at scale. What are the efficient use cases of AI that will help healthcare businesses boost their ROI? Let’s find out.
How is AI Applied in Healthcare?
The promising applications of AI in healthcare to improve outcomes are very intriguing. While there is still much to achieve in the AI-dependent healthcare business, there is sufficient potential that tech companies are willing to invest in AI-powered tools and solutions.
Let’s examine the potential examples of AI in healthcare to prepare and support business strategies accordingly and foster higher ROI generation.
Predictive Analytics
AI-based predictive analytics impacts a business by automating administrative tasks, predicting sales outcomes for a year, customers’ behavior and making strategies accordingly. According to a Forbes study, AI-based predictive analytics can save businesses $18 billion in tasks, expenses, and pricing.
To understand this, one example of using AI to automate admin tasks is a collaboration between the Cleveland Clinic and IBM. Cleveland Clinic uses IBM’s Watson to mine big data and provides personalized services for customers and clients on marketing deeds.
Some of the practical applications of AI and predictive analytics in healthcare are:
Monitoring market trends to maximize marketing efforts
Organizing datasets
Creating marketing campaigns tailored to each demographic-based client
Mining collective data for future decision-making
Fraud Prevention
AmerisourceBergen Corp detects fraud and misleading business operations through AI. A sales account team conducts audits with AI to detect usual lea and queries to prevent hefty expenses for businesses.
The example explains that implementing AI in your process will help detect any significant fraud attempts inside your business operation. This will help your business save huge expenditures.
Boost Sales
By putting down false leads, AI helps in maximizing sales numbers, resulting in significant ROI generation. For example, AI transforms data into personalized data, which reduces the cost of operations.
Chatbots
Most healthcare businesses leverage chatbots on their websites to engage more and more customers and boost engagement. In this way, businesses tend to gain multiple leads and convert them into clients by providing the best marketing solutions.
Chatbots are fruitful for AI start-ups in healthcare—small businesses can deploy AI to their websites. By doing so, they can save millions in administrative costs and attract numerous leads.
The most prominent examples of AI in healthcare hail from giant tech titans such as IBM, Amazon, and Microsoft. They are assisting healthcare providers with AI to create and deploy digital-human employees.
Segmentation of Marketing Targets
Is your target audience not responding to your marketing campaigns (for example, by not clicking a link, subscribing or unsubscribing to a newsletter, or not registering for a medical event)? If that's the case, how should you go ahead?
Using AI-based tools allows your marketing to easily identify target behaviors and reactions based on the type of marketing actions to be carried out. Analyzing these actions can help segment targets based on your company's marketing objectives.
The most significant development took place in April 2022, when Amazon Alexa became fully HIPAA compliant. It works with health developers and service providers that manage protected information for customers.
AI Leads to Data Modernization
It’s all about the data—not any data!
There’s a precise association between AI and data management, resulting in data modernization. According to a Cognizant research study, healthcare leaders have made significant progress in modernizing their data. In contrast, most upcoming businesses are expecting to do so by 2024.
The maximum acceleration of AI in modernizing data will be seen in the manufacturing and marketing of healthcare products and services, respectively. It is because AI helps to churn data easily. The accessibility of data, in particular, becomes simpler with automation than doing it manually, which generates a massive amount of data. Such effects of AI in healthcare can be one of the prime reasons for the higher ROI of your business in the future.
“There has never been a greater need for skilled analytic talent in health care. Because AI is becoming more strategic, organizations must ensure access to this skill set, either by growing their analytic teams or seeking out experienced partners."
Steve Griffiths, CEO of Optum Enterprise Analytics
AI Expenditure is on the Rise
McKinsey says that by 2025, the use of AI in healthcare will be widespread, resulting in significant expenditure by global healthcare leaders.
AI is a significant concern for healthcare decision-makers, investors, and innovators as customers extensively engage and react to AI-powered services and solutions. AI is constantly bringing improvements to almost all processes, including cost savings, management of services and products, and monitoring of multiple operations. Even small businesses in the healthcare industry are proactively investing in AI applications to match steps with the current wave of innovation in healthcare services.
Accelerate ROI Using AI
AI in healthcare is becoming one of the prime responsible technologies for accelerating ROI. Technology can eradicate multiple business growth challenges. Let’s find out how.
Enhanced Performance
As previously stated, use cases of AI in healthcare can relieve stress on employees. This would allow them to devote their time to more value-added marketing activities to churn more ROI.
Emphasize Cost-Effectiveness
Most of the businesses associated with healthcare are concerned about the costs involved. With AI, they now develop policies to spend less on non-essential activities and necessitate profit-oriented actions.
"We believe in the potential of AI to deliver insights and operational efficiencies that unlock better health-care performance."
Robert Musslewhite, CEO at OptumInsight
Frequently Asked Questions
How is AI used in healthcare?
AI in healthcare automates and predicts processes by analyzing data throughout. It is used to predict potential customers, improve business management workflows, and manufacture medical products.
How does AI drive growth in the healthcare industry?
AI drives business growth by improving the ability to understand better day-to-day customer patterns and needs based on services and products.
How is AI changing the Healthcare industry?
AI applications in healthcare have demonstrated their potential to improve analytics and data management and assist service providers in making timely medical decisions.
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Health Technology, Digital Healthcare
Article | September 7, 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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Health Technology
Article | September 28, 2022
Introduction
Healthcare supply chains are highly regulated, high-margin domains with stringent quality criteria, such as the demand for cold-chain storage and shipping. In addition, due to a lack of adequate understanding of the complicated rules governing healthcare products and services, medical aid providers are encountering inefficiencies while outsourcing capabilities to logistics service providers (LSPs).
In today's value-based care paradigm, healthcare leaders are tasked with improving patient outcomes while decreasing costs. With surging globalization, the growing cross-border nature of several medical products, and rising complexities in healthcare logistics, the need for building a robust supply chain is rapidly increasing across the healthcare industry.
Key Ways to Enhance Healthcare Supply Chain
A resilient supply chain plays a vital role in managing supplies, procuring resources, and shipping medical goods, among others, which assists in improving patient outcomes, enhancing service efficiency, and declining costs. Healthcare organizations are aiming to strengthen their supply chain to enjoy these benefits such as increased reimbursement, improved quality control, reduced inventory and overhead costs, and better collaboration with suppliers.
Here are some of the key ways to assist medical aid providers in building a strong healthcare supply chain
Develop effective inventory management
Manufacturers frequently encounter difficulties with timely inventory movement through their supply chains. Revenue is lost, and profit margins are harmed when products expire because they are not used adequately. This is why it is crucial to effectively manage the inventory process.
Hence, healthcare executives should deploy a high-quality equipment management system and increase collaboration between organizations, suppliers, and manufacturers to assist them in controlling inventory levels and effective inventory management.
Use technology and analytics to make operations run smoother
When it comes to supply chain management automation, the healthcare sector continues to lag behind other sectors. This is true for both the enterprise resource planning (ERP) functions and data analytics use for making decisions about forecasting and product choice.
Healthcare executives should make use of efficient technologies, such as solid analytics, in order to successfully improve a supply chain. Implementing data analytics and automation tools can assist in making healthcare supply chain management more efficient and effortless.
Widen and strengthen the supplier base
One of the most effective ways to build a robust healthcare supply chain is by increasing the number of suppliers and enhancing supplier base management.
Manufacturers and purchasers should abandon using single-or limited-source supply chains for raw materials and finished goods. This will assist healthcare companies in expanding their network of raw material suppliers and helps in careful consideration of which suppliers to use for procuring which resources.
Improve order accuracy and order cycle times to lower costs
Healthcare providers sometimes encounter a large number of errors during the ordering process. When incorrect products are ordered, the facilities face losses in revenue and are sometimes unable to deliver specific services due to the unavailability of products they need. Errors in placing orders can also result in medication errors. This can lead to a decrease in patient outcomes and negatively impact the company’s revenue growth.
To reduce the frequency of errors, these providers should deploy a computerized provider entry system. This will help improve order accuracy, increase supply chain efficiencies, and shorten turnaround times in healthcare ordering processes.
Consistently track and calibrate performance
Regardless of the size of the healthcare facility, it is of great importance for medical aid providers to carefully track and calibrate their performance frequently or on a specified timeline. This enables clinically integrated supply chains in healthcare to use key performance indicators (KPIs) to compare outcomes in terms of cost and quality and make decisions about products.
What’s Next?
The rising integration of novel disruptive technologies such as data analytics, the internet of things, artificial intelligence, and blockchain into healthcare supply chain management software is facilitating smooth operations, transparency, growth, and security across the life-science industry.
With a growing need for enhancing supply chains, healthcare providers are focusing on deploying advanced supply chain management solutions, such as healthcare logistics software, to strengthen their supply chains. As the trend continues to grow, the sales of healthcare supply chain management software and services are anticipated to rise from the US$2.2 billion registered in 2020 to US$3.3 billion by 2025.
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