Glassdoor gives you an inside look at what it&#x27;s like to work at HealthKart, including salaries, reviews, office photos, and more. This is the HealthKart company profile. All content is posted anonymously by employees working at HealthKart.

Working at HealthKart | Glassdoor

HealthKart | 130,766 followers on LinkedIn. Your partner for good health | HealthKart is a trusted house of brands with MuscleBlaze and HK Vitals being India’s no. 1 sports nutrition and online vitamin brands. HealthKart also offers a comprehensive range of products dedicated to the vegan ...

HealthKart | LinkedIn

HealthKart’s backstory is intriguing due to its association with the online pharmacy unicorn 1mg, previously known as HealthKartPlus. Both were set up by the parent company Bright Lifecare. While Maheshwari ran HealthKart, HealthKartPlus was headed by HealthKart’s Tandon, Gaurav Aggarwal ...

130+ Stores, 1K+ Brands, 40 Cities: How HealthKart Is Addressing ...

HealthKart offers fitness products and services to help consumers achieve their fitness goals. HealthKart also offers a comprehensive range of products dedicated to the vegan community, kids, and women for their wellness and fitness needs. The company started in 2011 and since then HealthKart ...

Healthkart - Crunchbase Company Profile & Funding

HealthKart offers health products online to help customers achieve fitness goals. Know about the Healthkart company, Healthkart founder, funding, revenue, and more.

HealthKart: How is it Offering Authentic Health Products Online?

HealthKart has 5 employees at their 1 location and $47 m in total funding,. See insights on HealthKart including office locations, competitors, revenue, financials, executives, subsidiaries and more at Craft.

HealthKart Company Profile - Office Locations, Competitors, Revenue, ...

HealthKart - Online store for health, sport, and nutritional supplements. Raised a total funding of $224M over 10 rounds from 20 investors. Valued at $370M. Founded by Sameer Maheshwari, Sameer Maheshwari and 1 other in the year 2011. HealthKart has 349 competitors.

HealthKart - Company Profile - Tracxn

The market is flooded with fake supplements or parallel imports that can cause harm to your body.

HealthKart: The platform to buy authentic products | Companies ...

Together, they decided to return to India and start a company in the healthcare space. ... A degree from Stanford or Harvard Business School would automatically win anybody tickets to a lucrative job. And it was no different for Sameer Maheshwari and Prashant Tandon. While the former is a Harvard graduate, the latter got his degree from Stanford. In fact, Maheshwari and Tandon quit their jobs to start, Healthkart...

Healthkart | How it Started

HealthKart is dedicated to providing everything that you will need in your journey towards a fitter you. From whey protein, vitamin c tablet, fat burners, mass gainers, weight gainers to herbal supplements like shatavari churna, to other bodybuilding supplements and nutritional supplements ...

HealthKart - India's #1 Authentic Online Supplement Store

HealthKart

healthkart

Healthcare Tech, Healthcare - October 10, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of The Year” award, featuring the most promising and innovative companies in the Healthcare Tech startup ecosystem. The list, compiled by the HackerNoon team, showcases 30 startups making significant contributions and driving innovation in the Healthcare Tech industry. https://youtu.be/XOpG6B4AKPU?embedable=true Nominations are open - learn more here. You can nominate your company as the Startup of The Year in the Healthcare Tech industry here. The Startups in the Healthcare Tech industry nominated for Startups of The Year 2024 include: QUALITY HEALTHCARE CENTER
Your Cue
GUTolution
LonVi
HealingHand Tech
BioLinker
FoundationDx
Wassor Womanity
Lumena MindGym
Caare Foundation
Dimple Bindra
Mercurial AI
AGPHARM BIOINNOVATIONS LLP
PetPal PH
Secured Health
MedGos
Aicury
Biocell
Kobeesco
BetterSpace
Wuru
VitruvianMD
Glooma
STMPatch
CARÁ Health
Vuala
Forte Biotech - RAPID Aquaculture Diagnostics
Tenang AI
Alithea Bio
Mindcafe India “We are thrilled to recognize the top startups in the Healthcare Tech industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO. “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” Why It Pays Off to Be Nominated Startups of The Year 2024 is a 100% community-driven voting event recognizing startups transforming technology and the world for the better. Starting October 1st, 2024, the internet can nominate and vote for the best ventures in their city and industry. People can nominate their favorite startups until October 31st, and vote once per day per award for who they think should be Startup of The Year up to March 31st, 2025. Winners will be announced in April 2025, after a comprehensive evaluation by the HackerNoon team. Apart from validation from the world's greenest tech publication, all nominees get free interviews relevant to their region and industry. They will also receive curated startup-friendly packages and a free version of their very own Evergreen Tech Company News Page on HackerNoon. In sum, being nominated gives you major credibility as one of the top startups globally and an expert in your industry, meaning even without winning, you still gain tons of exposure. Nominations are open - learn more here. You can nominate your company as the Startup of The Year in the Healthcare Tech industry here. About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. Visit our FAQ page to learn more. Download our design assets here. Check out the Startups of The Year Merch Shop here. HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. Meet our sponsors: Wellfound: Join the #1 global, startup-focused community. At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months, to build and scale your company with one powerful tool. Get your offer now! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Get started for free. Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection, businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Healthcare Tech, Healthcare - October 10, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of The Year” award, featuring the most promising and innovative companies in the Healthcare Tech startup ecosystem. Healthcare Tech, Healthcare - October 10, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of The Year” award, featuring the most promising and innovative companies in the Healthcare Tech startup ecosystem. Healthcare Tech , Healthcare Healthcare Tech - October 10, 2024 - October 10, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “ Startups of The Year ” award, featuring the most promising and innovative companies in the Startups of The Year startup ecosystem. The list, compiled by the HackerNoon team, showcases 30 startups making significant contributions and driving innovation in the Healthcare Tech industry. https://youtu.be/XOpG6B4AKPU?embedable=true https://youtu.be/XOpG6B4AKPU?embedable=true Nominations are open - learn more here. You can nominate your company as the Startup of The Year in the Healthcare Tech industry here. Nominations are open - learn more here . You can nominate your company as the Startup of The Year in the Healthcare Tech industry here . here Startup of The Year in Startup of The Year in the Healthcare Tech industry here here The Startups in the Healthcare Tech industry nominated for Startups of The Year 2024 include: Startups in Startups in Startups in the Healthcare Tech industry the Healthcare Tech industry nominated QUALITY HEALTHCARE CENTER Your Cue GUTolution LonVi HealingHand Tech BioLinker FoundationDx Wassor Womanity Lumena MindGym Caare Foundation Dimple Bindra Mercurial AI AGPHARM BIOINNOVATIONS LLP PetPal PH Secured Health MedGos Aicury Biocell Kobeesco BetterSpace Wuru VitruvianMD Glooma STMPatch CARÁ Health Vuala Forte Biotech - RAPID Aquaculture Diagnostics Tenang AI Alithea Bio Mindcafe India QUALITY HEALTHCARE CENTER Your Cue GUTolution LonVi HealingHand Tech BioLinker FoundationDx Wassor Womanity Lumena MindGym Caare Foundation Dimple Bindra Mercurial AI AGPHARM BIOINNOVATIONS LLP PetPal PH Secured Health MedGos Aicury Biocell Kobeesco BetterSpace Wuru VitruvianMD Glooma STMPatch CARÁ Health Vuala Forte Biotech - RAPID Aquaculture Diagnostics Tenang AI Alithea Bio Mindcafe India “We are thrilled to recognize the top startups in the Healthcare Tech industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO. “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” “We are thrilled to recognize the top startups in the Healthcare Tech industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO. “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” “We are thrilled to recognize the top startups in the Healthcare Tech industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO . “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” David Smooke, HackerNoon Founder & CEO Why It Pays Off to Be Nominated Startups of The Year 2024 is a 100% community-driven voting event recognizing startups transforming technology and the world for the better. Starting October 1st, 2024, the internet can nominate and vote for the best ventures in their city and industry. People can nominate their favorite startups until October 31st , and vote once per day per award for who they think should be Startup of The Year up to March 31st, 2025. Winners will be announced in April 2025, after a comprehensive evaluation by the HackerNoon team. Startups of The Year 2024 nominate their favorite startups until October 31st nominate their favorite startups Apart from validation from the world's greenest tech publication, all nominees get free interviews relevant to their region and industry. They will also receive curated startup-friendly packages and a free version of their very own Evergreen Tech Company News Page on HackerNoon. get free interviews startup-friendly packages startup-friendly packages Evergreen Tech Company News Evergreen Tech Company News In sum, being nominated gives you major credibility as one of the top startups globally and an expert in your industry, meaning even without winning, you still gain tons of exposure. Nominations are open - learn more here. You can nominate your company as the Startup of The Year in the Healthcare Tech industry here. Nominations are open - learn more here . You can nominate your company as the Startup of The Year in the Healthcare Tech industry here . here Startup of The Year in Startup of The Year in the Healthcare Tech industry here here About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. Startups of The Year 2024 Startups of The Year 2024 many stories many stories The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. free interview on HackerNoon Evergreen Tech Company News Evergreen Tech Company News Visit our FAQ page to learn more. FAQ FAQ Download our design assets here . here here Check out the Startups of The Year Merch Shop here . here here HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. startup-friendly packages startup-friendly packages Meet our sponsors: Meet our sponsors: Meet our sponsors: Wellfound: Join the #1 global, startup-focused community . At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Wellfound: Join the #1 global, startup-focused community Join the #1 global, startup-focused community Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months , to build and scale your company with one powerful tool. Get your offer now ! Notion: Try Notion with unlimited AI, FREE for up to 6 months Get your offer now ! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Get started for free . Hubspot: Get started for free Get started for free Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection , businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Bright Data: Bright Data’s scalable web data collection Bright Data’s scalable web data collection Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Algolia: AI end-to-end Search and Discovery Platform AI end-to-end Search and Discovery Platform

Startups of the Year 2024: 5,508 Startups Nominated in the Healthcare Tech Industry

2024 maran qalltawinaka: 5.508 Qalltawinakaw Industria Tecnológica de Salud ukan sutinchata

Стартъпи на 2024 г.: 5 508 стартиращи фирми, номинирани в технологичната индустрия на здравеопазването

Startups del año 2024: 5.508 startups nominadas en la industria de tecnología sanitaria

स्टार्टअप्स ऑफ द ईयर 2024: हेल्थकेयर टेक इंडस्ट्री में 5,508 स्टार्टअप नामांकित

Startup Tahun 2024: 5.508 Startup Masuk Nominasi di Industri Teknologi Kesehatan

2024年のスタートアップ・オブ・ザ・イヤー：ヘルスケア・テック業界で5,508社のスタートアップがノミネート

2024 жылдың стартаптары: денсаулық сақтау саласындағы 5 508 стартап ұсынылды

2024년 올해의 스타트업: 헬스케어 기술 산업에 지명된 5,508개 스타트업

स्टार्टअप अफ द इयर २०२४: ५,५०८ स्टार्टअपहरू हेल्थकेयर टेक उद्योगमा मनोनीत

Стартапи године 2024: 5.508 стартапа номинованих у здравственој технолошкој индустрији

Årets startups 2024: 5 508 startups nominerade inom Healthcare Tech Industry

Mga Startup ng Taon 2024: 5,508 Startup na Nominado sa Healthcare Tech Industry

In our world today, artificial intelligence applications and models are becoming more and more important in the healthcare industry, opening up new avenues for individualized treatment. Customized nutrition as a field is one where AI is making waves. It’s majorly used to generate meal plans; these meal plans, in turn, are specific to a person/user’s goals and preferences as well as health concerns. By making nutrition more personalized, it helps in tackling these issues especially seeing that illnesses such as diabetes, obesity, and heart diseases are becoming common. Seeing this and in order to help tackle the issues, I developed an AI-Web Driven tool that helps generate meal plans that are personalized to each customer. With its customized diet, this project — which is presently a Minimum Viable Product (MVP) — illustrates how artificial intelligence (AI) might improve preventive healthcare. I will discuss the potential applications of AI-powered nutrition in this post, as well as how the Virtual Nutritionist may improve both individual and societal health. Why Personalized Nutrition Is Important For a long time, we have known that poor eating and diet habits are directly related to and cause a range of chronic illneses even when nutrition is highly personalized. What works for one person may not work for another, especially if that person is managing specific health conditions. Personalized nutrition acknowledges these differences and, with the help of AI, delivers dietary advice tailored to individual needs. The Virtual Nutritionist generates meal plans based on each user’s health profile, considering factors like dietary restrictions, caloric goals, and personal preferences. Individuals with diabetes, for instance, can be given meal plans low in sugar, and those who want to lose weight might be given recipes low in calories. Offering people tailored guidance like this encourages them to take charge of their health and enhances their long-term well-being. Building the Virtual Nutritionist The Virtual Nutritionist was created with the straightforward goal of enabling everyone to have access to personalized nutrition through AI. Constructed with Django, the application gathers information from users regarding their dietary choices and health objectives, subsequently producing meal plans that fit those requirements. The app has a wide range of possible uses, even if it is currently in MVP development. With time, the artificial intelligence (AI) underlying the app will be able to incorporate new nutritional research and health trends to make recommendations that are increasingly precise. The Potential Impact on Healthcare Public and individual health could be revolutionized by AI-powered nutrition. In order to improve health outcomes, the Virtual Nutritionist could do the following: Chronic Disease Management:
Meal plans are created to control symptoms and enhance quality of life and are beneficial for people with long-term diseases such as diabetes or heart disease. Preventive Healthcare:
The software offers a proactive strategy for preserving health for those in good health. Users may steer clear of common problems like obesity, which frequently serves as a signpost to more significant health issues, by following personalized meal programs. Scalable Solutions for Healthcare Providers:
With the help of AI-driven solutions like the Virtual Nutritionist, medical professionals, dietitians, and nutritionists can provide more patients with individualized guidance without having to spend time laboriously organizing meals by hand. The Future of Personalized Nutrition Looking forward, the Virtual Nutritionist has the potential to integrate with wearable devices like fitness trackers or smartwatches. This would allow the app to adjust meal plans based on real-time data, such as daily activity levels or sleep patterns. Additionally, disease-specific meal plans could be offered for individuals managing specific health concerns, like kidney disease or hypertension. Community engagement features could also be added, enabling users to share success stories, meal plans, or health goals. Such features would foster a sense of community and long-term commitment to healthy eating. A Call for Collaboration The application is an open-source project, and I would love to collaborate with other developers, data scientists, and healthcare professionals to help improve the app. The project is available on GitHub, and I welcome contributions that can expand its features, refine the AI model, or enhance the user experience. With the right contributions, the Virtual Nutritionist can become a more robust tool that not only improves personal health but also contributes to better public health outcomes. Conclusion The application illustrates how applying AI in progressive ways can help revolutionize nutrition, improve the overall healthcare of the users, and even improve preventive healthcare. Creating meal plans based on individual needs allows the users to make proper decisions for their health and well-being. Seeing that healthcare is evolving, and moving towards more proactive measures, artificial Intelligence is going to play a crucial role in helping users manage their health and build a future where personalized health solutions are accessible to everyone. In our world today, artificial intelligence applications and models are becoming more and more important in the healthcare industry, opening up new avenues for individualized treatment. Customized nutrition as a field is one where AI is making waves. It’s majorly used to generate meal plans; these meal plans, in turn, are specific to a person/user’s goals and preferences as well as health concerns. By making nutrition more personalized, it helps in tackling these issues especially seeing that illnesses such as diabetes, obesity, and heart diseases are becoming common. Seeing this and in order to help tackle the issues, I developed an AI-Web Driven tool that helps generate meal plans that are personalized to each customer. With its customized diet, this project — which is presently a Minimum Viable Product (MVP) — illustrates how artificial intelligence (AI) might improve preventive healthcare. I will discuss the potential applications of AI-powered nutrition in this post, as well as how the Virtual Nutritionist may improve both individual and societal health. Why Personalized Nutrition Is Important For a long time, we have known that poor eating and diet habits are directly related to and cause a range of chronic illneses even when nutrition is highly personalized. What works for one person may not work for another, especially if that person is managing specific health conditions. Personalized nutrition acknowledges these differences and, with the help of AI, delivers dietary advice tailored to individual needs. The Virtual Nutritionist generates meal plans based on each user’s health profile, considering factors like dietary restrictions, caloric goals, and personal preferences. Individuals with diabetes, for instance, can be given meal plans low in sugar, and those who want to lose weight might be given recipes low in calories. Offering people tailored guidance like this encourages them to take charge of their health and enhances their long-term well-being. Building the Virtual Nutritionist The Virtual Nutritionist was created with the straightforward goal of enabling everyone to have access to personalized nutrition through AI. Constructed with Django, the application gathers information from users regarding their dietary choices and health objectives, subsequently producing meal plans that fit those requirements. The app has a wide range of possible uses, even if it is currently in MVP development. With time, the artificial intelligence (AI) underlying the app will be able to incorporate new nutritional research and health trends to make recommendations that are increasingly precise. The Potential Impact on Healthcare Public and individual health could be revolutionized by AI-powered nutrition. In order to improve health outcomes, the Virtual Nutritionist could do the following: Chronic Disease Management:
Meal plans are created to control symptoms and enhance quality of life and are beneficial for people with long-term diseases such as diabetes or heart disease. Chronic Disease Management: Meal plans are created to control symptoms and enhance quality of life and are beneficial for people with long-term diseases such as diabetes or heart disease. Chronic Disease Management: Chronic Disease Management: Meal plans are created to control symptoms and enhance quality of life and are beneficial for people with long-term diseases such as diabetes or heart disease. Preventive Healthcare:
The software offers a proactive strategy for preserving health for those in good health. Users may steer clear of common problems like obesity, which frequently serves as a signpost to more significant health issues, by following personalized meal programs. Preventive Healthcare: The software offers a proactive strategy for preserving health for those in good health. Users may steer clear of common problems like obesity, which frequently serves as a signpost to more significant health issues, by following personalized meal programs. Preventive Healthcare: Preventive Healthcare: The software offers a proactive strategy for preserving health for those in good health. Users may steer clear of common problems like obesity, which frequently serves as a signpost to more significant health issues, by following personalized meal programs. Scalable Solutions for Healthcare Providers:
With the help of AI-driven solutions like the Virtual Nutritionist, medical professionals, dietitians, and nutritionists can provide more patients with individualized guidance without having to spend time laboriously organizing meals by hand. Scalable Solutions for Healthcare Providers: With the help of AI-driven solutions like the Virtual Nutritionist, medical professionals, dietitians, and nutritionists can provide more patients with individualized guidance without having to spend time laboriously organizing meals by hand. Scalable Solutions for Healthcare Providers: Scalable Solutions for Healthcare Providers: With the help of AI-driven solutions like the Virtual Nutritionist, medical professionals, dietitians, and nutritionists can provide more patients with individualized guidance without having to spend time laboriously organizing meals by hand. The Future of Personalized Nutrition The Future of Personalized Nutrition Looking forward, the Virtual Nutritionist has the potential to integrate with wearable devices like fitness trackers or smartwatches. This would allow the app to adjust meal plans based on real-time data, such as daily activity levels or sleep patterns. Additionally, disease-specific meal plans could be offered for individuals managing specific health concerns, like kidney disease or hypertension. Community engagement features could also be added, enabling users to share success stories, meal plans, or health goals. Such features would foster a sense of community and long-term commitment to healthy eating. A Call for Collaboration A Call for Collaboration The application is an open-source project, and I would love to collaborate with other developers, data scientists, and healthcare professionals to help improve the app. The project is available on GitHub , and I welcome contributions that can expand its features, refine the AI model, or enhance the user experience. GitHub GitHub With the right contributions, the Virtual Nutritionist can become a more robust tool that not only improves personal health but also contributes to better public health outcomes. Conclusion Conclusion The application illustrates how applying AI in progressive ways can help revolutionize nutrition, improve the overall healthcare of the users, and even improve preventive healthcare. Creating meal plans based on individual needs allows the users to make proper decisions for their health and well-being. Seeing that healthcare is evolving, and moving towards more proactive measures, artificial Intelligence is going to play a crucial role in helping users manage their health and build a future where personalized health solutions are accessible to everyone.

The Future of Healthcare: How AI Is Revolutionizing Personalized Nutrition

We are all aware that AI is a hot button topic at the moment. It is something that’s attributed to just about everything, from deep fakes to stand up comedy, but how can AI help change the healthcare system in America? I recently sat down with Ramya Ganti, a tech expert in the healthcare space and the CEO of BabySteps, a women’s health startup. She has years of experience in expanding access to healthcare across the country, and offers insights into the field. Her work experience is vast, starting in a teaching hospital at Vanderbilt, and then expanding into AI and health tech fields with Thoughtful AI and Fortune 500 company BCG. She believes in creating a more efficient healthcare system that passes the savings along to the patients. Decluttering the system, and creating less confusion are at the core of Ganti’s beliefs and she was very thorough in her analysis of the United States healthcare system. Below is my best summation of what she said and how AI will help to build a stronger healthcare system that will ultimately benefit the people that matter the most: patients. What Is the Big Issue? “It all starts with an understanding of one of the biggest issues facing the healthcare system, and that issue has always been lack of efficiency,” said Ganti. “There are so many tasks that take up the time of doctors and hospital administrators that can be streamlined by the use of advanced technology such as AI.” Let’s begin by looking at a few examples she laid out for me. AI will help to speed up finding out what the diagnosis is for each patient, as well as accelerate drug development. Off to a good start already, but also it helps to streamline clinical trials, which leads to a more efficient delivery system. It can even help to automate the biggest system cloggers, administrative tasks, which in her words, “reduces the burden on healthcare providers allowing them to focus more on patient care.” Patient care is key, let’s face it. These efficiencies are welcomed on both sides, as it reduces the cost for the healthcare providers, allowing the trickle down effect of making healthcare more affordable for the patients. So what does the efficiency actually look like? Increasing Efficiency According to a Citigroup report, there will be a 25 to 30 percent reduction in administrative costs, thanks to an increase in automation of administrative tasks. AI-powered image analysis can help speed up disease detection by up to 90 percent, which leads to accelerated diagnosis leading to faster response times to medical issues. It helps nurses, too. A 30 percent offload in administrative tasks helps allow nurses to focus more on patient care and less on paperwork, according to Accenture research. Healthcare is one field where the use of AI increases the person-to-person contact. It does so by more accurately matching patients with doctors. Ganti believes heavily in the use of AI chatbots to help give research-backed answers 24/7. She says “I’m excited to see the significant impact this innovation will have.” For decades, the thought of not talking with another human being was looked down upon, but the innovation surrounding AI chatbots allows for a more efficient solution. Ganti sees a number of positive effects these chatbots are having. For example, they offer round the clock access to information, which reduces the unnecessary trips to the emergency room. Allowing patients to input their symptoms and get a preliminary assessment allows them to learn the severity of their illness, and whether a doctor's visit is required, saving money, especially for self-pay patients. And that’s not all, AI chatbots can also help with appointment scheduling once again helping to reduce administrative duties in the office. Now we know how AI is currently helping but what’s next? We are on the cusp of improving the healthcare system beyond what we had ever imagined. The next step in AI involves a deeper level of integration and personalization, and it's a major step with massive benefits for both patients and hospitals. AI can truly help with all levels of personal care. “We can see AI systems put into place that continuously analyze patient data to detect early warning signs of deterioration, as well as helping support clinicians in managing chronic conditions such as diabetes and cancer,” said Ganti. But it goes even beyond that. Operations efficiency, something that has lagged with overburdened hospitals, will improve. Predicting patient volume, resource allocation and even supply chain management, are all tasks more suited for an AI program. Ganti circles back to one of the biggest issues that hospitals face: “AI will aid with administrative duties through Robotic Process Automation, freeing up the staff for more patient care,” she said. “More time spent with patients is a fundamental benefit of integrating AI into hospitals.” Looking into the future, AI can help through augmenting intelligence. This will empower healthcare professionals and help to enhance their capabilities. It will go a step further, Ganti believes, by “ensuring AI systems are designed to complement human expertise and workflow.” Finally, getting to the heart of one of the major issues that has plagued the American healthcare system, is the wait times at doctor’s offices and hospitals. There is nothing worse than knowing you are having a health problem, but having to wait for something to be done about it. So, where does that leave the American healthcare system? We’re on the precipice of a new era, says Ganti, one driven by data analytics and a higher emphasis given to human interaction. In Ganti’s own words” “The future of healthcare will be marked by more precise, data-driven decision-making and significant financial savings,” she said. “Embracing these innovations today will pave the way for a more efficient, cost-effective healthcare system tomorrow.” We are all aware that AI is a hot button topic at the moment. It is something that’s attributed to just about everything, from deep fakes to stand up comedy, but how can AI help change the healthcare system in America? I recently sat down with Ramya Ganti, a tech expert in the healthcare space and the CEO of BabySteps, a women’s health startup. She has years of experience in expanding access to healthcare across the country, and offers insights into the field. Her work experience is vast, starting in a teaching hospital at Vanderbilt, and then expanding into AI and health tech fields with Thoughtful AI and Fortune 500 company BCG. She believes in creating a more efficient healthcare system that passes the savings along to the patients. Decluttering the system, and creating less confusion are at the core of Ganti’s beliefs and she was very thorough in her analysis of the United States healthcare system. Below is my best summation of what she said and how AI will help to build a stronger healthcare system that will ultimately benefit the people that matter the most: patients. What Is the Big Issue? What Is the Big Issue? “It all starts with an understanding of one of the biggest issues facing the healthcare system, and that issue has always been lack of efficiency,” said Ganti. “There are so many tasks that take up the time of doctors and hospital administrators that can be streamlined by the use of advanced technology such as AI.” Let’s begin by looking at a few examples she laid out for me. AI will help to speed up finding out what the diagnosis is for each patient, as well as accelerate drug development. Off to a good start already, but also it helps to streamline clinical trials, which leads to a more efficient delivery system. It can even help to automate the biggest system cloggers, administrative tasks, which in her words, “reduces the burden on healthcare providers allowing them to focus more on patient care.” Patient care is key, let’s face it. These efficiencies are welcomed on both sides, as it reduces the cost for the healthcare providers, allowing the trickle down effect of making healthcare more affordable for the patients. So what does the efficiency actually look like? Increasing Efficiency Increasing Efficiency According to a Citigroup report , there will be a 25 to 30 percent reduction in administrative costs, thanks to an increase in automation of administrative tasks. a Citigroup report a Citigroup report AI-powered image analysis can help speed up disease detection by up to 90 percent, which leads to accelerated diagnosis leading to faster response times to medical issues. It helps nurses, too. A 30 percent offload in administrative tasks helps allow nurses to focus more on patient care and less on paperwork, according to Accenture research . Accenture research Accenture research Healthcare is one field where the use of AI increases the person-to-person contact. It does so by more accurately matching patients with doctors. Ganti believes heavily in the use of AI chatbots to help give research-backed answers 24/7. She says “I’m excited to see the significant impact this innovation will have.” For decades, the thought of not talking with another human being was looked down upon, but the innovation surrounding AI chatbots allows for a more efficient solution. Ganti sees a number of positive effects these chatbots are having. For example, they offer round the clock access to information, which reduces the unnecessary trips to the emergency room. Allowing patients to input their symptoms and get a preliminary assessment allows them to learn the severity of their illness, and whether a doctor's visit is required, saving money, especially for self-pay patients. And that’s not all, AI chatbots can also help with appointment scheduling once again helping to reduce administrative duties in the office. Now we know how AI is currently helping but what’s next? We are on the cusp of improving the healthcare system beyond what we had ever imagined. The next step in AI involves a deeper level of integration and personalization, and it's a major step with massive benefits for both patients and hospitals. AI can truly help with all levels of personal care. “We can see AI systems put into place that continuously analyze patient data to detect early warning signs of deterioration, as well as helping support clinicians in managing chronic conditions such as diabetes and cancer,” said Ganti. But it goes even beyond that. But it goes even beyond that. Operations efficiency, something that has lagged with overburdened hospitals, will improve. Predicting patient volume, resource allocation and even supply chain management, are all tasks more suited for an AI program. Ganti circles back to one of the biggest issues that hospitals face: “AI will aid with administrative duties through Robotic Process Automation, freeing up the staff for more patient care,” she said. “More time spent with patients is a fundamental benefit of integrating AI into hospitals.” Looking into the future, AI can help through augmenting intelligence. This will empower healthcare professionals and help to enhance their capabilities. It will go a step further, Ganti believes, by “ensuring AI systems are designed to complement human expertise and workflow.” Finally, getting to the heart of one of the major issues that has plagued the American healthcare system, is the wait times at doctor’s offices and hospitals. There is nothing worse than knowing you are having a health problem, but having to wait for something to be done about it. So, where does that leave the American healthcare system? So, where does that leave the American healthcare system? We’re on the precipice of a new era, says Ganti, one driven by data analytics and a higher emphasis given to human interaction. In Ganti’s own words” “The future of healthcare will be marked by more precise, data-driven decision-making and significant financial savings,” she said. “Embracing these innovations today will pave the way for a more efficient, cost-effective healthcare system tomorrow.”

How Artificial Intelligence Will Actually Change The Healthcare System in America

Artificial Intelligence (AI) in healthcare has long captured our imagination, fueled by portrayals in movies and TV shows where robotic surgeons and virtual assistants are the norm. But beyond science fiction, AI has profoundly impacted real-world healthcare. As it has evolved over the years, AI has transformed from an ambitious idea into a powerful tool, reshaping how we deliver care. The Three Waves of AI in Healthcare​ The journey of AI in healthcare can be categorized into three distinct waves: 1. The First Wave: Foundations and Early Exploration​ The first wave emerged in the aftermath of World War II with the introduction of Machine Learning and the coining of the term "Artificial Intelligence." During this period, foundational concepts like the Turing Test were developed, laying the groundwork for future advancements. While the early stages of AI were exploratory, they set the stage for what was to come. Colossus was the world's first electronic programmable computer, at Bletchley Park in Bedfordshire. Bletchley Park Trust/Science & Society Picture Library via Chris Monk 2. The Second Wave: Expert Systems and Rule-Based AI​ The second wave, spanning the 1980s, was marked by the development of expert systems such as MYCIN and DXPlain. These systems aimed to mimic human decision-making using large sets of rules to provide medical recommendations. However, their potential was limited by the complexity of managing thousands of interacting rules and the constraints of the data available at the time, which primarily came from textbooks and human experts. DXPlain, one of the pioneering expert systems in healthcare, aimed to emulate human decision-making. 3. The Third Wave: AI Renaissance & ChatGPT​ The third and current wave of AI began in the 2010s, characterized by the introduction of deep learning and neural networks. This era has been driven by the availability of large datasets, advances in computing power (especially GPUs), and innovative architectures like transformers which gave AI the ability to understand bodies of text as a whole versus just sequences of words. The "Attention is All You Need" paper introduced the transformer architecture, revolutionizing natural language processing. The release of models like GPT-3 and ChatGPT has revolutionized natural language processing and catalyzed the development of AI-driven applications in healthcare, enabling conversational agents, predictive analytics, and personalized care. These same technologies are now being deployed to assist clinicians through prepopulating notes, automating repetitive tasks, and providing decision support. Imaging, pathology, and radiology are some of the fields where AI is making significant inroads, helping to reduce the time and cost of diagnosis while improving accuracy. For example, AI can now analyze medical images with remarkable precision, often outperforming human experts in specific tasks like detecting diabetic retinopathy or analyzing radiology scans. They are also capable of operating in the background to find opportunistic diagnoses that may have been missed by human eyes. This concept is often overlooked and will become more important as costs continue to come down. via Avicenna.AI a leading medical imaging AI company One of the most exciting developments is AI’s ability to integrate multimodal data—combining text, images, biosensor data, and even genomic information to provide a more comprehensive understanding of a patient’s condition. This capability allows AI to go beyond simple image recognition and contribute to the overall diagnostic process, taking into account the patient’s medical history and up to date data. The Da Vinci Surgical System is a prime example of how AI is transforming surgery (from their website) While fully autonomous surgery may still be a decade away, the integration of AI into the surgical process is already enhancing precision and outcomes. The da Vinci Surgical System, which combines robotic surgery with AI, is a prime example of how technology is pushing the boundaries of what’s possible. AI in Outreach and Care Delivery​ At CareLaunch, we recognize the transformative power of AI and are integrating advanced AI capabilities into our CRM platform to support healthcare providers. AI is a strong fit for our mission to streamline patient communication, optimize workflows, and provide actionable insights. For instance, our AI-powered features can predict patient needs based on their historical data, enabling proactive outreach through our CRM. This is particularly valuable in managing chronic conditions, where timely interventions can prevent complications and improve quality of life. At the core of any AI or healthcare based initiative is a strong data foundation. The CareLaunch platform leverages HL7 FHIR standards to ensure that data is interoperable and secure. This also allows for the integration of AI models and other third-party tools to enhance the platform’s capabilities. Our CRM system takes the guesswork out of patient communication by automating outreach campaigns with data-driven precision. Whether it's reminding patients about upcoming appointments, sending post-visit follow-ups, or launching preventive care initiatives, CareLaunch ensures that every message is sent at the right time to the right patient. This automation reduces administrative burden on healthcare providers, allowing them to focus more on patient care while ensuring that no critical communication is overlooked. The Mayo Clinic's use of AI in diagnostics offers a real-world example of how AI-driven insights can lead to better patient care—a vision we share and strive to achieve with our platform. At CareLaunch, we’re redefining what’s possible in healthcare outreach and patient relationship management. Our AI-driven CRM platform is designed to help you deliver personalized care, streamline communications, and ultimately improve patient outcomes. Ready to see how CareLaunch can transform your practice? Schedule a demo today and discover how our innovative solutions can help you connect with your patients in more meaningful ways. For more insights into how CareLaunch is leveraging AI to transform healthcare, visit our blog or explore our platform to see how we can help you enhance patient care and operational efficiency. Artificial Intelligence (AI) in healthcare has long captured our imagination, fueled by portrayals in movies and TV shows where robotic surgeons and virtual assistants are the norm. But beyond science fiction, AI has profoundly impacted real-world healthcare. As it has evolved over the years, AI has transformed from an ambitious idea into a powerful tool, reshaping how we deliver care. The Three Waves of AI in Healthcare ​ ​ The journey of AI in healthcare can be categorized into three distinct waves: 1. The First Wave: Foundations and Early Exploration ​ The First Wave: Foundations and Early Exploration ​ The first wave emerged in the aftermath of World War II with the introduction of Machine Learning and the coining of the term "Artificial Intelligence." During this period, foundational concepts like the Turing Test were developed, laying the groundwork for future advancements. While the early stages of AI were exploratory, they set the stage for what was to come. Turing Test Colossus was the world's first electronic programmable computer, at Bletchley Park in Bedfordshire. Bletchley Park Trust/Science & Society Picture Library via Chris Monk Colossus was the world's first electronic programmable computer, at Bletchley Park in Bedfordshire. Bletchley Park Trust/Science & Society Picture Library via Chris Monk Chris Monk 2. The Second Wave: Expert Systems and Rule-Based AI ​ The Second Wave: Expert Systems and Rule-Based AI ​ The second wave, spanning the 1980s, was marked by the development of expert systems such as MYCIN and DXPlain . These systems aimed to mimic human decision-making using large sets of rules to provide medical recommendations. However, their potential was limited by the complexity of managing thousands of interacting rules and the constraints of the data available at the time, which primarily came from textbooks and human experts. MYCIN DXPlain DXPlain, one of the pioneering expert systems in healthcare, aimed to emulate human decision-making. DXPlain, one of the pioneering expert systems in healthcare, aimed to emulate human decision-making. 3. The Third Wave: AI Renaissance & ChatGPT ​ The Third Wave: AI Renaissance & ChatGPT ​ The third and current wave of AI began in the 2010s, characterized by the introduction of deep learning and neural networks. This era has been driven by the availability of large datasets, advances in computing power (especially GPUs), and innovative architectures like transformers which gave AI the ability to understand bodies of text as a whole versus just sequences of words. transformers The "Attention is All You Need" paper introduced the transformer architecture, revolutionizing natural language processing. The "Attention is All You Need" paper introduced the transformer architecture, revolutionizing natural language processing. The release of models like GPT-3 and ChatGPT has revolutionized natural language processing and catalyzed the development of AI-driven applications in healthcare, enabling conversational agents, predictive analytics, and personalized care. These same technologies are now being deployed to assist clinicians through prepopulating notes, automating repetitive tasks, and providing decision support. GPT-3 ChatGPT Imaging, pathology, and radiology are some of the fields where AI is making significant inroads, helping to reduce the time and cost of diagnosis while improving accuracy. For example, AI can now analyze medical images with remarkable precision, often outperforming human experts in specific tasks like detecting diabetic retinopathy or analyzing radiology scans. They are also capable of operating in the background to find opportunistic diagnoses that may have been missed by human eyes. This concept is often overlooked and will become more important as costs continue to come down. via Avicenna.AI a leading medical imaging AI company via Avicenna.AI a leading medical imaging AI company Avicenna.AI One of the most exciting developments is AI’s ability to integrate multimodal data—combining text, images, biosensor data, and even genomic information to provide a more comprehensive understanding of a patient’s condition. This capability allows AI to go beyond simple image recognition and contribute to the overall diagnostic process, taking into account the patient’s medical history and up to date data. The Da Vinci Surgical System is a prime example of how AI is transforming surgery (from their website) The Da Vinci Surgical System is a prime example of how AI is transforming surgery (from their website ) their website While fully autonomous surgery may still be a decade away, the integration of AI into the surgical process is already enhancing precision and outcomes. The da Vinci Surgical System , which combines robotic surgery with AI, is a prime example of how technology is pushing the boundaries of what’s possible. da Vinci Surgical System AI in Outreach and Care Delivery ​ ​ At CareLaunch, we recognize the transformative power of AI and are integrating advanced AI capabilities into our CRM platform to support healthcare providers. AI is a strong fit for our mission to streamline patient communication, optimize workflows, and provide actionable insights. For instance, our AI-powered features can predict patient needs based on their historical data, enabling proactive outreach through our CRM. This is particularly valuable in managing chronic conditions, where timely interventions can prevent complications and improve quality of life. At the core of any AI or healthcare based initiative is a strong data foundation. The CareLaunch platform leverages HL7 FHIR standards to ensure that data is interoperable and secure. This also allows for the integration of AI models and other third-party tools to enhance the platform’s capabilities. Our CRM system takes the guesswork out of patient communication by automating outreach campaigns with data-driven precision. Whether it's reminding patients about upcoming appointments, sending post-visit follow-ups, or launching preventive care initiatives, CareLaunch ensures that every message is sent at the right time to the right patient. This automation reduces administrative burden on healthcare providers, allowing them to focus more on patient care while ensuring that no critical communication is overlooked. The Mayo Clinic's use of AI in diagnostics offers a real-world example of how AI-driven insights can lead to better patient care—a vision we share and strive to achieve with our platform. Mayo Clinic's use of AI in diagnostics At CareLaunch, we’re redefining what’s possible in healthcare outreach and patient relationship management. Our AI-driven CRM platform is designed to help you deliver personalized care, streamline communications, and ultimately improve patient outcomes. Ready to see how CareLaunch can transform your practice? Schedule a demo today and discover how our innovative solutions can help you connect with your patients in more meaningful ways. Schedule a demo For more insights into how CareLaunch is leveraging AI to transform healthcare, visit our blog or explore our platform to see how we can help you enhance patient care and operational efficiency. our blog our platform

The Evolution of AI in Healthcare: From Ambitious Beginnings to What's Next

Surveys show that most healthcare stakeholders consider investments in insights and analytics as a priority funding nowadays. They point out that their organizations are increasingly betting on unified business intelligence (BI) solutions that help implement predictive analytics. Building such a data-driven approach in healthcare propels this domain forward, as 94% of respondents believe. They emphasized the top advantage doctors and patients can leverage from implementing healthcare BI tools and data analytics: a more personalized treatment path. Now, we do see progress in this market. For instance, the Deloitte survey found that customers are more satisfied with how fast and easy they can share their data via wearables than they were a few years ago. Nevertheless, transforming these data into valuable insights is still a perennial challenge from clinicians’ perspective, let alone acting on it promptly. I would say that data is one of the most underutilized assets in healthcare now. Storing Data Does Not Mean Benefiting From Them Many healthcare organizations lack dedicated teams or analytical tools to interpret this volume of data. Clinicians complain about being overloaded by a huge number of irrelevant records. So, only well-implemented electronic health records (EHR) systems with built-in analytical software, served by professionals, can quickly extract information with decision-making potential. Despite focusing on a data-driven approach in the majority of interviewed organizations, only 16% define themselves as mature players in this race. They can gather and analyze data from various sources and leverage findings. The rest of the healthcare institutions are struggling with different chain links of this process. Working with healthcare solutions suppliers, I see how often their customers demand customized software with advanced BI tools to not only react urgently but also use its forecast capabilities. Inhibitory Factors While the mentioned statistics show the healthcare sector has an optimistic view of using BI and DA solutions, some roadblocks stop capitalizing on this opportunity. Forty-three percent of interviewees listed disparate or incompatible systems as a top handicap healthcare organizations deal with. The bottom line is that such organizations need a solution to connect all these data storage, parse the information, and visualize ready-to-use findings. Preparing this infrastructure is a multi-step process that demands resources. It is not just about the investments. As I highlighted before, healthcare stakeholders are ready to adopt these technologies. I would say they know about this trend and would like to jump on this opportunity, but subconsciously, such projects may seem like a burden with an uncertain return on investment (ROI) still for many managers. How to Overcome Limitations In fact, healthcare management wants to know how the new technology aligns with the KPIs and helps boost performance. For example, medical organizations are waiting for more engagement from patients and a higher number of positive reviews, cost optimization, scaling, and better security. From a doctor's perspective, automating some paperwork and decreasing diagnosis time matter. A B2B vendor that provides a SaaS EHR solution would like to compete with major players and increase its market share, gain a new round of investments, meet tight deadlines and high investor expectations, or ultimately, enter new markets and even go for an IPO. In the U.S., there is a noticeable trend toward burnout and dissatisfaction among clients and doctors. Recently, the U.S. healthcare system faced its largest cyber attack. Gartner warned about such concerns last year. Such serious problems in the healthcare domain uncover big opportunities for health tech players, especially with SaaS products. The medical system needs new qualitative solutions to revolutionize its operations or thoroughly modernize the exciting ones. All you need is to show your clients how an EHR solution with BI tools will address their specific problems or help them achieve their goals. The second most common limitation I often observe in such projects is the scope of work and time frames, which is overwhelming for many stakeholders. As a micro-changing approach mature adopter, we recommend an incremental legacy modernization of your EHR system (of course, into your decision-making assistant and a business driver). How It Works In Practice We have had a client who offers EHR as a SaaS solution. Initially, they used this system for internal purposes. Later, they saw the growing demand for such software and decided to get their share of the pie. The organization faced many limitations. Their old system wasn’t scalable enough and couldn’t cope with increased users and data. Additionally, the owners were afraid of security concerns, data leaks, and damaging their reputations. The main challenge was to isolate customers’ data from each other in one environment. As a solution, we created a cloud multi-tenant architecture when different clinics’ records are operated absolutely independently. Also, cloud migration enables the client to scale the resources according to their actual use. For instance, seasonal influenza outbreaks cause higher patient activities and increased requests. The system adjusts resource consumption for such cases and scales them down after the peak periods. Moreover, the solution can predict such events. The system transforms historical data and information extracted in real-time from various databases into conclusions. Then, it automatically visualizes them on BI monitoring panels and notifies decision-makers. Hence, healthcare organizations can prepare their personnel and infrastructure in advance. A clear business strategy based on the modernized solution helped our client gain investments and government program support. By relying on our step-by-step upgrading approach, they overcame the main limitations. In Conclusion When we talk about adopting BI and data analysis in healthcare, it goes not only about technical or funding limitations. The key inhibitor we have to cope with is switching managers' business mindset and encouraging the new corporate culture. It is not enough just to have innovative tools. They won’t revolutionize your performance if they don’t have organizational leaders' support. While many companies are still implementing technologies for technologies, the most successful market players see their purposes and reach them. Also published here. Surveys show that most healthcare stakeholders consider investments in insights and analytics as a priority funding nowadays. They point out that their organizations are increasingly betting on unified business intelligence (BI) solutions that help implement predictive analytics. consider Building such a data-driven approach in healthcare propels this domain forward, as 94% of respondents believe. They emphasized the top advantage doctors and patients can leverage from implementing healthcare BI tools and data analytics : a more personalized treatment path. data analytics Now, we do see progress in this market. For instance, the Deloitte survey found that customers are more satisfied with how fast and easy they can share their data via wearables than they were a few years ago. Nevertheless, transforming these data into valuable insights is still a perennial challenge from clinicians’ perspective, let alone acting on it promptly. I would say that data is one of the most underutilized assets in healthcare now. Storing Data Does Not Mean Benefiting From Them Many healthcare organizations lack dedicated teams or analytical tools to interpret this volume of data. Clinicians complain about being overloaded by a huge number of irrelevant records. So, only well-implemented electronic health records (EHR) systems with built-in analytical software, served by professionals, can quickly extract information with decision-making potential. Despite focusing on a data-driven approach in the majority of interviewed organizations, only 16% define themselves as mature players in this race. They can gather and analyze data from various sources and leverage findings. The rest of the healthcare institutions are struggling with different chain links of this process. Working with healthcare solutions suppliers, I see how often their customers demand customized software with advanced BI tools to not only react urgently but also use its forecast capabilities. Inhibitory Factors While the mentioned statistics show the healthcare sector has an optimistic view of using BI and DA solutions, some roadblocks stop capitalizing on this opportunity. Forty-three percent of interviewees listed disparate or incompatible systems as a top handicap healthcare organizations deal with. The bottom line is that such organizations need a solution to connect all these data storage, parse the information, and visualize ready-to-use findings. Preparing this infrastructure is a multi-step process that demands resources. It is not just about the investments. As I highlighted before, healthcare stakeholders are ready to adopt these technologies. I would say they know about this trend and would like to jump on this opportunity, but subconsciously, such projects may seem like a burden with an uncertain return on investment (ROI) still for many managers. How to Overcome Limitations In fact, healthcare management wants to know how the new technology aligns with the KPIs and helps boost performance. For example, medical organizations are waiting for more engagement from patients and a higher number of positive reviews, cost optimization, scaling, and better security. From a doctor's perspective, automating some paperwork and decreasing diagnosis time matter. A B2B vendor that provides a SaaS EHR solution would like to compete with major players and increase its market share, gain a new round of investments, meet tight deadlines and high investor expectations, or ultimately, enter new markets and even go for an IPO. In the U.S., there is a noticeable trend toward burnout and dissatisfaction among clients and doctors. Recently, the U.S. healthcare system faced its largest cyber attack. Gartner warned about such concerns last year. faced warned Such serious problems in the healthcare domain uncover big opportunities for health tech players, especially with SaaS products. The medical system needs new qualitative solutions to revolutionize its operations or thoroughly modernize the exciting ones. All you need is to show your clients how an EHR solution with BI tools will address their specific problems or help them achieve their goals. The second most common limitation I often observe in such projects is the scope of work and time frames, which is overwhelming for many stakeholders. As a micro-changing approach mature adopter, we recommend an incremental legacy modernization of your EHR system (of course, into your decision-making assistant and a business driver). incremental legacy modernization How It Works In Practice We have had a client who offers EHR as a SaaS solution. Initially, they used this system for internal purposes. Later, they saw the growing demand for such software and decided to get their share of the pie. The organization faced many limitations. Their old system wasn’t scalable enough and couldn’t cope with increased users and data. Additionally, the owners were afraid of security concerns, data leaks, and damaging their reputations. The main challenge was to isolate customers’ data from each other in one environment. As a solution, we created a cloud multi-tenant architecture when different clinics’ records are operated absolutely independently. Also, cloud migration enables the client to scale the resources according to their actual use. For instance, seasonal influenza outbreaks cause higher patient activities and increased requests. The system adjusts resource consumption for such cases and scales them down after the peak periods. Moreover, the solution can predict such events. The system transforms historical data and information extracted in real-time from various databases into conclusions. Then, it automatically visualizes them on BI monitoring panels and notifies decision-makers. Hence, healthcare organizations can prepare their personnel and infrastructure in advance. A clear business strategy based on the modernized solution helped our client gain investments and government program support. By relying on our step-by-step upgrading approach, they overcame the main limitations. In Conclusion When we talk about adopting BI and data analysis in healthcare, it goes not only about technical or funding limitations. The key inhibitor we have to cope with is switching managers' business mindset and encouraging the new corporate culture. It is not enough just to have innovative tools. They won’t revolutionize your performance if they don’t have organizational leaders' support. business mindset While many companies are still implementing technologies for technologies, the most successful market players see their purposes and reach them. Also published here . here here

Business Intelligence Is So Important For Development In Healthcare: Here's Why

Corporate Downfalls: Why Healthcare Is Losing The Battle Against Ransomware Attacks

Move over, Dr. House. There's a new medical genius in town, and it doesn't even have a stethoscope. Spike, a Silicon Valley startup that focuses on data technology and artificial intelligence (AI), just landed $3.5 million in seed funding. Its mission? To give healthcare AI, which is set to reach $148 billion by 2029, the brainpower it needs. The oversubscribed investment was co-led by Practica Capital and TheVentureCity, and a who's who of tech investors joined the party, including CEAS Investments, Plug & Play Ventures, Geek Ventures, and Axel Springer Porsche (APX). Spike is ready to supercharge product development, expand into new markets, and cement its status as a medical director in the AI health technology field. So, what's Spike's secret remedy? Its B2B solution allows developers to add AI superpowers to their healthcare apps. Spike aims to cut development time and costs to a fraction of what they used to be and connect to the data collected by hundreds of medical, wearable, and IoT devices. Think of Spike's API as a health data buffet, offering insights from over 300 sources – from your trusty Fitbit to high-tech medical devices. It's the fuel that powers Spike's AI algorithms to deliver personalized healthcare solutions smarter than a med school grad (well, almost). "Advancements in retrieval-augmented generation AI mean that LLMs are no longer taking a 'best guess,' but are now able to seek out specialized context, producing outputs that are much more accurate and considerably less prone to hallucinations," Povilas Gudzius, CEO and co-founder of Spike, said. "By incorporating this technology on top of Spike's high-quality health data API, we're enabling our clients to easily leverage these tools and improve the health of millions of end users." Spike vs. the Goliaths, with a RAG, not a Stone Sure, Google, Amazon, and Microsoft have their AI health data solutions. But let's be honest: They're like old-school doctors who still use pagers. Spike is the young, energetic upstart shaking things up. Google Cloud Healthcare API provides access to healthcare data and offers AI and machine learning tools for building healthcare applications. Amazon HealthLake is a HIPAA-eligible service that helps healthcare organizations store, transform, query, and analyze health data. And Microsoft Azure API for FHIR enables the exchange of healthcare data using the FHIR standard and offers AI tools for building healthcare applications. So while the megaliths in the room are busy managing massive cloud infrastructures, Spike is laser-focused on healthcare. They're not just aggregating data; they're curating it, ensuring it's top-notch and tailor-made for the unique needs of the medical world. And Spike uses retrieval-augmented generation (RAG), a technique for enhancing the accuracy and reliability of generative AI models with facts fetched from external sources. RAG helps AI models avoid embarrassing "hallucination" moments by cross-checking their answers with real-world facts. Think of it as a reality check for AI, ensuring its answers are as accurate as a doctor's diagnosis. This makes AI more reliable, less prone to making things up, and ultimately, much more useful in the healthcare world. "We are utilizing health expertise networks and curated in specialized context databases in RAG AI infrastructure," Gudzius said. "RAG AI allows us to incorporate these problem-specific sources effectively and makes the LLM responses more grounded. The design of the RAG AI infrastructure and domain-expert curated medical content allows us to further innovate in developing the 'Trustworthy Health AI.'" All of this technology doesn't mean Spike can scrimp on security and privacy. Like the Big 3, it has to make strong commitments to regulatory protection, especially with searches for AI in healthcare being orders of magnitude higher than searches for AI safety. "Spike takes data security and privacy very seriously, so our infrastructure products follow strict GDRP, HIPAA, and CCPA regulatory guidelines," Gudzius said. "From the technical perspective, we are also adopting specific techniques to prioritize data privacy. For example, we have built our data access layers that provide limited control to the LLM agent while handling data acquisition logic and complying with regulatory requirements. As the quality and volume of individuals' health data grows, there's a huge need to develop and innovate regulatory-compliant techniques for private health data-to-LLM interactions like that." The Future of Healthcare: Spike's Prescription This $3.5 million isn't just pocket change; it's the catalyst for Spike's grand vision. They're not just building AI tools but trustworthy AI tools that are as reliable as your favorite family doctor (but hopefully with a better bedside manner). They're expanding their reach to include everything from electronic health records to genomics data. "We believe in a future where health data volume will grow exponentially driven by the improvements in sensor hardware," Gudzius said. "These sensors include optical, electrical, and electromechanical sensors from wearables, IoT devices, and other sources like EHRs and lab tests. We are well positioned to capture this potential because our team has extensive experience working with data acquisition and a scientific background in Health AI. Our edge is ensuring we provide the capabilities of these emerging non-diagnostic technologies to our clients in a safe and regulatory compliant way." Spike imagines a future where AI isn't just a buzzword; it's an integral part of healthcare, improving patient care and making those dreaded doctor's visits a little less dreadful. A version of this article was originally published on Dataconomy and is republished with permission. Move over, Dr. House. There's a new medical genius in town, and it doesn't even have a stethoscope. Spike , a Silicon Valley startup that focuses on data technology and artificial intelligence (AI), just landed $3.5 million in seed funding. Its mission? To give healthcare AI, which is set to reach $148 billion by 2029 , the brainpower it needs. Spike set to reach $148 billion by 2029 The oversubscribed investment was co-led by Practica Capital and TheVentureCity, and a who's who of tech investors joined the party, including CEAS Investments, Plug & Play Ventures, Geek Ventures, and Axel Springer Porsche (APX). Spike is ready to supercharge product development, expand into new markets, and cement its status as a medical director in the AI health technology field. So, what's Spike's secret remedy? Its B2B solution allows developers to add AI superpowers to their healthcare apps. Spike aims to cut development time and costs to a fraction of what they used to be and connect to the data collected by hundreds of medical, wearable, and IoT devices. Think of Spike's API as a health data buffet, offering insights from over 300 sources – from your trusty Fitbit to high-tech medical devices. It's the fuel that powers Spike's AI algorithms to deliver personalized healthcare solutions smarter than a med school grad (well, almost). "Advancements in retrieval-augmented generation AI mean that LLMs are no longer taking a 'best guess,' but are now able to seek out specialized context, producing outputs that are much more accurate and considerably less prone to hallucinations," Povilas Gudzius, CEO and co-founder of Spike, said. "By incorporating this technology on top of Spike's high-quality health data API, we're enabling our clients to easily leverage these tools and improve the health of millions of end users." Spike vs. the Goliaths, with a RAG, not a Stone Spike vs. the Goliaths, with a RAG, not a Stone Sure, Google, Amazon, and Microsoft have their AI health data solutions. But let's be honest: They're like old-school doctors who still use pagers. Spike is the young, energetic upstart shaking things up. Google Cloud Healthcare API provides access to healthcare data and offers AI and machine learning tools for building healthcare applications. Amazon HealthLake is a HIPAA-eligible service that helps healthcare organizations store, transform, query, and analyze health data. And Microsoft Azure API for FHIR enables the exchange of healthcare data using the FHIR standard and offers AI tools for building healthcare applications. So while the megaliths in the room are busy managing massive cloud infrastructures, Spike is laser-focused on healthcare. They're not just aggregating data; they're curating it, ensuring it's top-notch and tailor-made for the unique needs of the medical world. And Spike uses retrieval-augmented generation (RAG), a technique for enhancing the accuracy and reliability of generative AI models with facts fetched from external sources. RAG helps AI models avoid embarrassing "hallucination" moments by cross-checking their answers with real-world facts. Think of it as a reality check for AI, ensuring its answers are as accurate as a doctor's diagnosis. This makes AI more reliable, less prone to making things up, and ultimately, much more useful in the healthcare world. "We are utilizing health expertise networks and curated in specialized context databases in RAG AI infrastructure," Gudzius said. "RAG AI allows us to incorporate these problem-specific sources effectively and makes the LLM responses more grounded. The design of the RAG AI infrastructure and domain-expert curated medical content allows us to further innovate in developing the 'Trustworthy Health AI.'" All of this technology doesn't mean Spike can scrimp on security and privacy. Like the Big 3, it has to make strong commitments to regulatory protection, especially with searches for AI in healthcare being orders of magnitude higher than searches for AI safety . searches for AI in healthcare being orders of magnitude higher than searches for AI safety "Spike takes data security and privacy very seriously, so our infrastructure products follow strict GDRP, HIPAA, and CCPA regulatory guidelines," Gudzius said. "From the technical perspective, we are also adopting specific techniques to prioritize data privacy. For example, we have built our data access layers that provide limited control to the LLM agent while handling data acquisition logic and complying with regulatory requirements. As the quality and volume of individuals' health data grows, there's a huge need to develop and innovate regulatory-compliant techniques for private health data-to-LLM interactions like that." The Future of Healthcare: Spike's Prescription The Future of Healthcare: Spike's Prescription This $3.5 million isn't just pocket change; it's the catalyst for Spike's grand vision. They're not just building AI tools but trustworthy AI tools that are as reliable as your favorite family doctor (but hopefully with a better bedside manner). They're expanding their reach to include everything from electronic health records to genomics data. "We believe in a future where health data volume will grow exponentially driven by the improvements in sensor hardware," Gudzius said. "These sensors include optical, electrical, and electromechanical sensors from wearables, IoT devices, and other sources like EHRs and lab tests. We are well positioned to capture this potential because our team has extensive experience working with data acquisition and a scientific background in Health AI. Our edge is ensuring we provide the capabilities of these emerging non-diagnostic technologies to our clients in a safe and regulatory compliant way." Spike imagines a future where AI isn't just a buzzword; it's an integral part of healthcare, improving patient care and making those dreaded doctor's visits a little less dreadful. A version of this article was originally published on Dataconomy and is republished with permission. A version of this article was originally published on Dataconomy and is republished with permission. published on Dataconomy

Spike Aims to Give Healthcare AI a Brain Boost and Outsmart the Tech Giants

With an alarming 46 percent statistical concern about access to treatment in the healthcare system around the world, AI is seeking to democratize and simplify the process of diagnosis and patient treatment. With companies like Google, GE Healthcare, Siemens Healthineers, and many other leading AI startups, these AI dreams are achieving more feasibility. However, how will AI’s health solution be future-proof if privacy concerns and data breaches are still lurking? Overview of AI advancements GE Healthcare has been able to develop a technology that assists with ultra-sound imaging, and high-level accurate scans like PET, MRI, and CT. it is also in the U.S. Food and Drug Administration-approved AI medical devices having 58 out of 692 entries. Siemens Healthineers claims to have more than 80 AI-based healthcare solutions with 40 hardware devices approved lately. The focus of this company is the algorithmic mechanism that automates the post-processing of images and helps radiologists handle heavy workflows and routine tasks. According to an article on VKTR by Neil Savage, “it includes modules for chest CT, which can highlight lung nodules and estimate tumor burden; brain MR, which divides the brain into different segments and makes volumetric measurements” A host of other startups are promising in harnessing the potential of the intelligent models in addressing the human problems with the current healthcare system. Can we trust AI with our healthcare data? AI by default makes decisions and recommendations based on the data it has been trained with and all forms have an underlying principle of large datasets in finding patterns. This leads us to our first question on how the benefits be balanced with the disadvantages in utilizing people’s healthcare data for training and decisions. The concerns are in two categories. The first concern is the privacy of the data used to train these models, second is the model’s response based on the input of the patient’s data in the working process—or decision-making process of the model. AI’s advancements in the healthcare venture have received ovations with its impressive abilities ranging from medical evaluations, automation, chest x-rays, smart wearables, medical diagnosis, imaging processing, and robotic surgery—which has been touted as a hypothetical possibility with recent innovations and on a higher level rather than the current level with tiny incisions. In Health IT security’s words, “Artificial intelligence (AI) in healthcare has the potential to revolutionize clinical research and care delivery. AI can be used to sift through massive databases and may have applications in mental healthcare and cancer detection.” Over time, the medical profession has prioritized the oath of secrecy in the medical process of diagnosis, treatments, and prescriptions. However, a data-oriented system solving the measure of traditional problems while maintaining the status quo remains a vital cornerstone to the utility of this innovation. Definitive Healthcare has identified about 80 percent of health data breaches due to hacking or IT incidents. Therefore, there’s still a lot to be addressed when fears abound about the possibility of weaponized models, poisoning, and other sort of invasive possibilities on the technology that was originally meant to assist and automate tasks. This compounds the problems and leaves gaps as the healthcare AI application accelerates at an unprecedented pace. Several approaches may mitigate problems and tie up the loose ends which will be detailed in succeeding paragraphs. Looking forward: The turning point and AI promises A technical approach such as anonymizing, encryption, and creating privacy-oriented algorithms in storing and retrieval of health care data. An example is blockchain technology detailed in this paper by the NLM. A second way can be developing legal frameworks in protecting the medical records of individuals and according to Valentin Kuzmenco, in an article on Hyperight, “We need robust legal frameworks to safeguard our privacy in the digital age. Stringent data protection laws like GDPR and CCPA offer a starting point,… protecting our data from unauthorized access and misuse, regardless of geographical borders.” There’s a longtime perpetual concern of big tech with people’s data and their collateral cost of internet surfing, and recommendation algorithms. Patients can be educated on best privacy practices, and providing consent forms—because not all forms of medical data may be deemed private Thirdly, there is ongoing research in addressing the underlying concerns and a continual progression will address technological challenges with data privacy and automative algorithms. Being on the lookout while supervising automation for progressive steps will go a long way. In conclusion, the impact of AI in the healthcare industry is promising and has lots of potential to mitigate current and future healthcare problems and automate tasks to lower costs and democratize healthcare. However, best security practices, compliance regulatory frameworks, and continual research would enhance a futuristic possibility with innovations and advancements. With an alarming 46 percent statistical concern about access to treatment in the healthcare system around the world, AI is seeking to democratize and simplify the process of diagnosis and patient treatment. With companies like Google , GE Healthcare , Siemens Healthineers , and many other leading AI startups, these AI dreams are achieving more feasibility. 46 percent statistical concern Google GE Healthcare Siemens Healthineers However, how will AI’s health solution be future-proof if privacy concerns and data breaches are still lurking? Overview of AI advancements Overview of AI advancements GE Healthcare has been able to develop a technology that assists with ultra-sound imaging, and high-level accurate scans like PET, MRI, and CT. it is also in the U.S. Food and Drug Administration-approved AI medical devices having 58 out of 692 entries. GE Healthcare Siemens Healthineers claims to have more than 80 AI-based healthcare solutions with 40 hardware devices approved lately. The focus of this company is the algorithmic mechanism that automates the post-processing of images and helps radiologists handle heavy workflows and routine tasks. Siemens Healthineers According to an article on VKTR by Neil Savage, “it includes modules for chest CT, which can highlight lung nodules and estimate tumor burden; brain MR, which divides the brain into different segments and makes volumetric measurements” VKTR A host of other startups are promising in harnessing the potential of the intelligent models in addressing the human problems with the current healthcare system. host of other startups Can we trust AI with our healthcare data? Can we trust AI with our healthcare data? AI by default makes decisions and recommendations based on the data it has been trained with and all forms have an underlying principle of large datasets in finding patterns. This leads us to our first question on how the benefits be balanced with the disadvantages in utilizing people’s healthcare data for training and decisions. The concerns are in two categories. The first concern is the privacy of the data used to train these models, second is the model’s response based on the input of the patient’s data in the working process—or decision-making process of the model. AI’s advancements in the healthcare venture have received ovations with its impressive abilities ranging from medical evaluations, automation, chest x-rays, smart wearables, medical diagnosis, imaging processing, and robotic surgery—which has been touted as a hypothetical possibility with recent innovations and on a higher level rather than the current level with tiny incisions. In Health IT security’s words, “Artificial intelligence (AI) in healthcare has the potential to revolutionize clinical research and care delivery. AI can be used to sift through massive databases and may have applications in mental healthcare and cancer detection.” Over time, the medical profession has prioritized the oath of secrecy in the medical process of diagnosis, treatments, and prescriptions. However, a data-oriented system solving the measure of traditional problems while maintaining the status quo remains a vital cornerstone to the utility of this innovation. Definitive Healthcare has identified about 80 percent of health data breaches due to hacking or IT incidents. Therefore, there’s still a lot to be addressed when fears abound about the possibility of weaponized models, poisoning, and other sort of invasive possibilities on the technology that was originally meant to assist and automate tasks. Definitive identified invasive This compounds the problems and leaves gaps as the healthcare AI application accelerates at an unprecedented pace. Several approaches may mitigate problems and tie up the loose ends which will be detailed in succeeding paragraphs. Looking forward: The turning point and AI promises Looking forward: The turning point and AI promises A technical approach such as anonymizing, encryption, and creating privacy-oriented algorithms in storing and retrieval of health care data. An example is blockchain technology detailed in this paper by the NLM. paper A second way can be developing legal frameworks in protecting the medical records of individuals and according to Valentin Kuzmenco, in an article on Hyperight, “We need robust legal frameworks to safeguard our privacy in the digital age. Stringent data protection laws like GDPR and CCPA offer a starting point,… protecting our data from unauthorized access and misuse, regardless of geographical borders.” GDPR and CCPA There’s a longtime perpetual concern of big tech with people’s data and their collateral cost of internet surfing, and recommendation algorithms. Patients can be educated on best privacy practices, and providing consent forms—because not all forms of medical data may be deemed private Thirdly, there is ongoing research in addressing the underlying concerns and a continual progression will address technological challenges with data privacy and automative algorithms. Being on the lookout while supervising automation for progressive steps will go a long way. In conclusion, the impact of AI in the healthcare industry is promising and has lots of potential to mitigate current and future healthcare problems and automate tasks to lower costs and democratize healthcare. However, best security practices, compliance regulatory frameworks, and continual research would enhance a futuristic possibility with innovations and advancements.

As Healthcare AI Advances, How Do we Balance the Benefits With Privacy Concerns?

Revolutionizing Healthcare: Andy Schoonover's Playbook for Disrupting Entrenched Industries

বিপ্লবী স্বাস্থ্যসেবা: প্রবেশ করা শিল্পগুলিকে ব্যাহত করার জন্য অ্যান্ডি শুনোভারের প্লেবুক

Revolutionierung des Gesundheitswesens: Andy Schoonovers Strategie zur Umwälzung etablierter Branchen

Revolucionando la atención médica: el manual de Andy Schoonover para revolucionar industrias arraigadas

Révolutionner les soins de santé : le manuel d'Andy Schoonover pour perturber les industries bien établies

स्वास्थ्य सेवा में क्रांति: स्थापित उद्योगों में बदलाव के लिए एंडी स्कूनओवर की कार्यपुस्तिका

ヘルスケアの革命: 定着した業界を変革するためのアンディ・シューノーバーの戦略

의료 혁신: 고착화된 산업을 혁신하기 위한 Andy Schoonover의 플레이북

Revolucionando a saúde: o manual de Andy Schoonover para desestabilizar indústrias entrincheiradas

Революция в здравоохранении: книга Энди Шуновера по разрушению устоявшихся отраслей

Sağlık Hizmetinde Devrim Yaratmak: Andy Schoonover'ın Yerleşik Endüstrileri Yıkmaya Yönelik Başucu Kitabı

Cách mạng hóa hoạt động chăm sóc sức khỏe: Sách hướng dẫn cách phá vỡ các ngành công nghiệp cố thủ của Andy Schoonover

医疗保健革命：安迪·斯库诺弗颠覆根深蒂固行业的策略

The rise of electronic health records and the growing use of data analytics in healthcare have made data governance a key focus area for improving healthcare services to be safer, more efficient, and better tailored to individual patient needs. The stakes are high, as a single breach in healthcare data can jeopardize patient confidentiality and weaken trust in the entire healthcare system. Astra Security reports that 51% of healthcare organizations have seen an uptick in data breaches since 2019, with hospitals facing increasing amounts of breaches over the last 12 years. Data governance is important not just for security but for ensuring data quality, integrity, and accessibility – all critical for informed decision-making in healthcare. The HIPAA (Health Insurance Portability and Accountability Act) Journal revealed that a whopping 133 million records were exposed or mishandled in 2023 alone, underscoring the need for proper data governance. Healthcare data leaders like Nithin Narayan Koranchirath are rising to the challenge by championing proper data governance strategies in the healthcare industry. Nithin’s belief is that more awareness of the essential role data governance plays in healthcare will lead to increased adoption by the industry. Managing Data in Healthcare Data governance is not a box to tick and then be forgotten about; it is a strategic necessity in the healthcare industry. With the increasing amount of Electronic Health Records (EHRs) and medical research data, healthcare institutions must guarantee that data remains precise, accessible, and secure. With inconsistencies in data across different EHR systems, there are more administrative tasks and potential risks to patient well-being than ever before. The challenges for healthcare providers in handling data are maintaining privacy and security standards, complying with regulations, managing data sources effectively, and ensuring seamless communication between different systems. Establishing a data governance program can enhance the delivery of healthcare services, foster innovation and research, improve decision-making in healthcare, and ensure compliance with laws like HIPAA and GDPR (General Data Protection Regulation). An Authority on Healthcare Data Management Nithin Narayan Koranchirath, a professional in healthcare data management, stresses the significance of data governance. He has years of expertise overseeing various healthcare data systems, and emphasizes that "efficient data management goes beyond compliance, it aims at enhancing outcomes and streamlining healthcare services." Data governance might appear as a subject typically reserved exclusively for IT experts, but its impact extends to everyone involved in the healthcare network. At its core, data governance entails managing data from the collection phase to its end use in patient care or research. Nithin’s pivotal moment came when leading the Data and Analytics platform at his current organization, one of the United States’s largest healthcare providers, where he witnessed the transformative impact of data-driven insights. "This role allowed me to witness firsthand the power of data-driven insights in revolutionizing data analytics delivery and administration," Nithin reflects, solidifying his commitment to analytics and data-driven decision-making. Grasping proper data governance practices empowers healthcare professionals with the knowledge to make informed decisions. This fundamental understanding reduces the chances of mistakes that could jeopardize safety. For patients, it offers reassurance that their personal data is handled with care and confidentiality. Additionally, implementing data governance measures such as utilizing Enterprise Master Patient Indexes (EMPI) can significantly enhance healthcare quality by providing an overview of patient records. Implementing a Data Governance Framework Tailored for Healthcare Healthcare professionals frequently encounter obstacles with data, such as difficulty accessing and safeguarding data, disorganized and isolated data sets, limited resource availability, and insufficient staff collaboration and training. Overcoming these challenges involves defining roles for adopting security measures, selecting a data management solution, allocating resources for data experts, and educating staff on effective data management practices. When assessing options for data governance solutions, healthcare institutions should take into account several factors, including integration with existing systems, compliance with requirements, scalability, and ease of use. Platforms like Big Data, AWS, and Snowflake offer data governance capabilities for overseeing data governance processes while effectively addressing security concerns and regulatory demands. Nithin’s work in implementing a comprehensive data governance framework at his organization via Big Data, AWS, and Snowflake underscores the practical benefits of such knowledge. "The implementation of robust data governance practices enabled us to achieve greater compliance with regulatory requirements and mitigate risks associated with data management," he explains. For healthcare professionals, this translates to better decision-making capabilities, and for patients, it means the assurance of data privacy and security. AWS and Snowflake are cloud-based data management solutions that align seamlessly with the needs of the healthcare industry. It offers functionalities like data discovery, traceability, and search capabilities to help organizations streamline their approach to data governance while simultaneously enhancing security and compliance measures efficiently. At the end of the day, leaders such as C-suite executives and IT managers ultimately bear responsibility for ensuring data governance practices are followed in an organization. However, every individual working within the healthcare sector plays a role in its success. Effective leadership should ensure that all staff members know the importance of data governance, while data experts should have a grasp on how data impacts staff operations. Future Outlook for Data Governance in Healthcare In an era defined by numerous technological advancements in healthcare, the importance of data governance is only set to grow. As we look towards the future, data governance in healthcare is poised to become a cornerstone of the United States healthcare system, playing a pivotal role in shaping economic outcomes. The U.S. healthcare sector, one of the largest contributors to the national economy, faces rising costs, inefficiencies, and demands for improved patient outcomes and privacy. Nithin’s hard work in solving these issues will have lasting positive effects not only on the healthcare industry but on the tech sector and the U.S. economy at large. Additionally, with the standardization of data practices, interoperability across different healthcare systems can be improved. This improvement facilitates better coordination of care, especially for chronic disease management, which is a significant expenditure for the U.S. economy. Data governance addresses these challenges by enhancing the quality, accessibility, and security of healthcare data. The path toward establishing effective data governance within healthcare is challenging but critical. As Nithin Narayan Koranchirath says himself, "Data governance is the backbone of a trustworthy healthcare system." By ensuring the integrity, accessibility, and security of healthcare data, the U.S. can improve its healthcare outcomes, reduce costs, and foster innovation, thereby enhancing its economic stability and growth. This story was distributed by Jon Stojan Media under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author The rise of electronic health records and the growing use of data analytics in healthcare have made data governance a key focus area for improving healthcare services to be safer, more efficient, and better tailored to individual patient needs. The stakes are high, as a single breach in healthcare data can jeopardize patient confidentiality and weaken trust in the entire healthcare system. Astra Security reports that 51% of healthcare organizations have seen an uptick in data breaches since 2019, with hospitals facing increasing amounts of breaches over the last 12 years. Data governance is important not just for security but for ensuring data quality, integrity, and accessibility – all critical for informed decision-making in healthcare. The HIPAA (Health Insurance Portability and Accountability Act) Journal revealed that a whopping 133 million records were exposed or mishandled in 2023 alone, underscoring the need for proper data governance. 51% of healthcare organizations 51% of healthcare organizations 133 million records 133 million records Healthcare data leaders like Nithin Narayan Koranchirath are rising to the challenge by championing proper data governance strategies in the healthcare industry. Nithin’s belief is that more awareness of the essential role data governance plays in healthcare will lead to increased adoption by the industry. Managing Data in Healthcare Managing Data in Healthcare Data governance is not a box to tick and then be forgotten about; it is a strategic necessity in the healthcare industry. With the increasing amount of Electronic Health Records (EHRs) and medical research data, healthcare institutions must guarantee that data remains precise, accessible, and secure. With inconsistencies in data across different EHR systems, there are more administrative tasks and potential risks to patient well-being than ever before. The challenges for healthcare providers in handling data are maintaining privacy and security standards, complying with regulations, managing data sources effectively, and ensuring seamless communication between different systems. Establishing a data governance program can enhance the delivery of healthcare services, foster innovation and research, improve decision-making in healthcare, and ensure compliance with laws like HIPAA and GDPR (General Data Protection Regulation). An Authority on Healthcare Data Management An Authority on Healthcare Data Management Nithin Narayan Koranchirath, a professional in healthcare data management, stresses the significance of data governance. He has years of expertise overseeing various healthcare data systems, and emphasizes that "efficient data management goes beyond compliance, it aims at enhancing outcomes and streamlining healthcare services." Data governance might appear as a subject typically reserved exclusively for IT experts, but its impact extends to everyone involved in the healthcare network. At its core, data governance entails managing data from the collection phase to its end use in patient care or research. Nithin’s pivotal moment came when leading the Data and Analytics platform at his current organization, one of the United States’s largest healthcare providers, where he witnessed the transformative impact of data-driven insights. "This role allowed me to witness firsthand the power of data-driven insights in revolutionizing data analytics delivery and administration," Nithin reflects, solidifying his commitment to analytics and data-driven decision-making. Grasping proper data governance practices empowers healthcare professionals with the knowledge to make informed decisions. This fundamental understanding reduces the chances of mistakes that could jeopardize safety. For patients, it offers reassurance that their personal data is handled with care and confidentiality. Additionally, implementing data governance measures such as utilizing Enterprise Master Patient Indexes (EMPI) can significantly enhance healthcare quality by providing an overview of patient records. Implementing a Data Governance Framework Tailored for Healthcare Implementing a Data Governance Framework Tailored for Healthcare Healthcare professionals frequently encounter obstacles with data, such as difficulty accessing and safeguarding data, disorganized and isolated data sets, limited resource availability, and insufficient staff collaboration and training. Overcoming these challenges involves defining roles for adopting security measures, selecting a data management solution, allocating resources for data experts, and educating staff on effective data management practices. When assessing options for data governance solutions, healthcare institutions should take into account several factors, including integration with existing systems, compliance with requirements, scalability, and ease of use. Platforms like Big Data, AWS, and Snowflake offer data governance capabilities for overseeing data governance processes while effectively addressing security concerns and regulatory demands. offer data governance capabilities offer data governance capabilities Nithin’s work in implementing a comprehensive data governance framework at his organization via Big Data, AWS, and Snowflake underscores the practical benefits of such knowledge. "The implementation of robust data governance practices enabled us to achieve greater compliance with regulatory requirements and mitigate risks associated with data management," he explains. For healthcare professionals, this translates to better decision-making capabilities, and for patients, it means the assurance of data privacy and security. AWS and Snowflake are cloud-based data management solutions that align seamlessly with the needs of the healthcare industry. It offers functionalities like data discovery, traceability, and search capabilities to help organizations streamline their approach to data governance while simultaneously enhancing security and compliance measures efficiently. At the end of the day, leaders such as C-suite executives and IT managers ultimately bear responsibility for ensuring data governance practices are followed in an organization. However, every individual working within the healthcare sector plays a role in its success. Effective leadership should ensure that all staff members know the importance of data governance, while data experts should have a grasp on how data impacts staff operations. Future Outlook for Data Governance in Healthcare Future Outlook for Data Governance in Healthcare In an era defined by numerous technological advancements in healthcare, the importance of data governance is only set to grow. As we look towards the future, data governance in healthcare is poised to become a cornerstone of the United States healthcare system, playing a pivotal role in shaping economic outcomes. The U.S. healthcare sector, one of the largest contributors to the national economy, faces rising costs, inefficiencies, and demands for improved patient outcomes and privacy. Nithin’s hard work in solving these issues will have lasting positive effects not only on the healthcare industry but on the tech sector and the U.S. economy at large. Additionally, with the standardization of data practices, interoperability across different healthcare systems can be improved. This improvement facilitates better coordination of care, especially for chronic disease management, which is a significant expenditure for the U.S. economy. Data governance addresses these challenges by enhancing the quality, accessibility, and security of healthcare data. The path toward establishing effective data governance within healthcare is challenging but critical. As Nithin Narayan Koranchirath says himself, "Data governance is the backbone of a trustworthy healthcare system." By ensuring the integrity, accessibility, and security of healthcare data, the U.S. can improve its healthcare outcomes, reduce costs, and foster innovation, thereby enhancing its economic stability and growth. This story was distributed by Jon Stojan Media under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author This story was distributed by Jon Stojan Media under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author This story was distributed by Jon Stojan Media under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author https://business.hackernoon.com/brand-as-author

Stories, News & Mentions about HEALTHKART

Healthkart’s Stories on HackerNoon

Healthkart's News & Mentions