#CitiusTech

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5 things about AI you may have missed today: Tech giants to combat AI content in polls, Nokia turns to AI, and more

AI roundup: As elections are nearing in various parts of the world, tech giants such as Adobe, Google, Meta, Microsoft, OpenAI, TikTok and others have joined hands to battle AI-generated images during this crucial period. On the other hand, Nokia announced a new AI-powered tool for industrial workers which generates messages such as warnings or information. Know what’s happening in the world of…

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Rajan Kohli, CEO of CitiusTech - Interview Series

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Rajan Kohli, CEO of CitiusTech – Interview Series

New Post has been published on https://thedigitalinsider.com/rajan-kohli-ceo-of-citiustech-interview-series/

Rajan Kohli, CEO of CitiusTech – Interview Series

Rajan Kohli is the Chief Executive Officer of CitiusTech and is responsible for the strategic direction of the company and further CitiusTech’s mission of accelerating healthcare technology innovation and driving long-term value for clients. Rajan is a highly accomplished technology services industry executive with experience across digital transformation, application and engineering services.

Prior to CitiusTech, Rajan has spent over 27 years at Wipro and most recently was the president of Wipro’s iDEAS (Integrated Digital, Engineering and Application Services) business. He led a global business line with revenues of USD 6 billion and committed to helping clients across the world accelerate their transformation and shift how they build and deliver digital products, services and experiences.

CitiusTech is a leading provider of consulting and digital technology to healthcare and life sciences companies. As strategic partners to the world’s leading payer, provider, MedTech, and life sciences companies, CitiusTech drives innovation, business transformation, and industry-wide convergence. They play a deep and meaningful role in accelerating digital innovation, driving sustainable value, and helping improve outcomes across the healthcare ecosystem.

What are the key elements required to successfully implement digital transformation strategies in healthcare and life sciences organizations?

The healthcare industry has struggled in its embrace of digital solutions, with successful digital transformation journeys sporadically occurring over the years. But with technology ready to fuel a paradigm-altering leap in patient care, it’s time for the industry to push past these challenges.

Digital Transformation has the potential to positively impact healthcare across all specialties. For example, specialty drug manufacturers juggle multiple demands springing from various stakeholders and the ecosystem to meet their constantly growing demand. Navigating this intricate network of stakeholders and the ecosystem does not come easy, and many of them look to leverage patient support hub services that offload these responsibilities from the drug manufacturers to manage these responsibilities and optimize client-drug performance. However, with patient hub services facing challenges regarding scalability and efficiency due to escalating volumes, many specialty drug manufacturers must embrace digital transformation strategies to streamline operations and bolster overall efficiency.

Implementing digital transformation in healthcare and life sciences requires a three – prong multifaceted approach.

Leadership commitment is essential to drive and sustain these initiatives, ensuring that there is a top-down endorsement and alignment with strategic goals. This means not only creating a clear vision and roadmap outlining specific objectives and milestones, but also investing in technology and innovative solutions.

Robust data management is another critical element. Establishing strong information governance frameworks ensures data quality, security and regulatory compliance. This includes defining data standards, policies and processes for data management, as well as leveraging advanced analytics and big data technologies to extract actionable insights from health data.

Interoperability is crucial for digital transformation, necessitating the adoption of industry standards like HL7, FHIR and DICOM to facilitate seamless data exchange between different systems and platforms. Utilizing integration platforms and middleware solutions can bridge disparate systems, ensuring smooth data flow and communication across the organization. By embracing interoperability fully, organizations will be able to drive more efficient, effective and patient-centric healthcare delivery.

But at the end of the day, digital transformations start and end with the patient. Healthcare organizations can automate as many processes as they would like, but if they don’t change the experience or the value that the patient receives, it will be especially difficult to find success. A patient-centric approach with the implementation of digital health solutions that enhance patient engagement, improve access to care and enable personalized treatment plans are essential.

How is generative AI currently being used to enhance healthcare treatments and improve patient outcomes?

Generative (Gen) AI offers transformative benefits across the healthcare ecosystem. For healthcare, an industry in which many of the pervasive challenges can be attributed to ineffective human-machine interactions, Gen AI has the power to bridge that gap and truly democratize healthcare.

This is especially true with personalized medicine. Developing treatment plans that are personalized to specific patients can be difficult and time consuming if done manually. By leveraging Gen AI, the algorithms analyze genetic data and patient histories to create personalized treatment plans tailored to the individual’s unique genetic makeup and medical history. Once the treatment plans are in place, patient access to AI-powered virtual health assistants is crucial, as patients have 24/7 access to medical advice, symptom checking and appointment scheduling, which improves patient engagement, more effective treatments, and better patient outcomes.

Gen AI is also playing a significant role in accelerating the drug approval and launch process. The pandemic showcased the potential for rapid drug development, driven by AI’s capabilities. Gen AI accelerates the development of new medications by simulating molecular interactions and predicting which compounds are likely to be effective. This significantly reduces the time and cost associated with traditional drug discovery methods. These AI-powered platforms can also generate potential drug candidates and optimize their chemical structures, expediting the process from concept to clinical trials.

Gen AI algorithms are enhancing the accuracy of medical imaging as well, improving image quality and assisting in the detection of anomalies. In doing so, it facilitates early diagnosis and treatment of conditions such as cancer, significantly improving patient outcomes.

Lastly, predictive analytics powered by Gen AI have groundbreaking potential. Predictive Gen AI models analyze vast amounts of health data to predict disease outbreaks, patient readmissions and potential complications, enabling proactive intervention and better management of chronic diseases.

In what ways can generative AI help in reducing mundane tasks for healthcare professionals, thereby allowing them to focus more on patient care and innovation?

Gen AI can significantly reduce the burden of mundane tasks for healthcare professionals such as clinical documentation, scheduling appointments, managing medical records, and processing insurance claims. Healthcare professionals are free to concentrate on patient care and innovation.

For example, healthcare professionals rely heavily on Electronic Medical Records (EMRs) for safer and more consistent healthcare delivery but doing so requires these individuals to constantly navigate between their narrative-based understanding of patient histories and symptoms, and EMRs’ structured data presentation. Gen AI bridges this gap and significantly reduces cognitive overload for healthcare professionals by summarizing patient history and automating manual tasks, freeing up valuable time for more personalized patient care.

Clinical decision support systems leverage AI to provide healthcare professionals with evidence-based recommendations, alerts, and reminders. These systems analyze patient data and medical literature to offer insights that aid in diagnosis and treatment planning, enhancing clinical outcomes and reducing the cognitive load on healthcare providers.

Remote monitoring technologies, powered by AI, continuously track patients’ vital signs and health status, allowing for real-time health assessments without the need for frequent in-person visits. This improves patient convenience and enables early detection of potential health issues, leading to prompt interventions and better management of chronic conditions.

Gen AI augments human potential improving job satisfaction for healthcare professionals, more on innovative care delivery and patient satisfaction.

What measures can be taken to maximize the effectiveness of Gen AI solutions in monitoring quality and ensuring trust in healthcare decisions?

Quality and trust have become critical points of discussion across the healthcare industry amidst the rapid growth of Gen AI. It requires a robust focus on these issues to ensure benefits are realized responsibly. Among the measures that can be taken:

Privacy and Data Security: Ensuring patient privacy is essential, requiring meticulous anonymization of data and stringent cybersecurity measures to prevent unauthorized access and data breaches. Implementing robust encryption protocols and defense mechanisms against adversarial attacks can protect patient data, while clinicians must retain ultimate decision-making authority to safeguard against potential AI errors.

Maintaining Quality and Fairness: Gen AI systems can inadvertently perpetuate biases present in the training data, leading to disparities in healthcare outcomes. Implementing algorithms capable of eliminating bias, and continuously retraining AI systems to detect and mitigate biases is key.

Accountability and Transparency: Accountability in Gen AI-driven decisions involve multiple stakeholders, including developers, healthcare providers, and end users. Transparent, explainable AI models are necessary for informed decision-making. Developers must ensure that AI models are unbiased and secure, while healthcare providers need to understand that they remain accountable for the decisions made using AI recommendations. Implementing robust regulatory frameworks is essential to address liability issues and maintain trust.

Ethical Frameworks: Developing ethical frameworks for Gen AI is about fostering responsibility without stifling innovation. Healthcare players must proactively align with evolving ethical standards to ensure Gen AI applications are fair, responsible, and patient-focused. A human-in-the-loop approach, combined with responsible AI practices, can help achieve equitable healthcare outcomes while maximizing Gen AI’s potential.

Platform-Based Quality and Trust Frameworks: Building quality and trust frameworks that integrate into existing quality management systems and align with regulatory recommendations is crucial. These frameworks should measure, validate, and monitor GenAI solutions to ensure consistent and trustworthy outcomes.

Earlier this year, we launched the CitiusTech Gen AI Quality and Trust Solution, the first end-to-end solution of its kind in healthcare. The solution can address these requirements by providing comprehensive validation, continuous monitoring and adherence to regulatory standards, guaranteeing the effectiveness and trustworthiness of Gen AI solutions in healthcare.

How can healthcare organizations work to identify and mitigate algorithmic and training data biases to ensure equitable care decisions?

Healthcare organizations must be extremely proactive in their approach. Using diverse and representative datasets during the training phase helps in reducing biases, ensuring that AI models perform well across different population groups. Implementing bias detection tools can help identify and address biases in AI models by analyzing the model’s outputs to detect any disparities in treatment recommendations or predictions.

Regular audits and reviews of AI systems help in identifying and correcting biases. This involves evaluating the system’s performance across various demographic groups and making necessary adjustments. Inclusive design and development, consisting of a diverse group of stakeholders in the design and development of AI solutions, ensures that different perspectives are considered, reducing the likelihood of biases. Lastly, education and training for employees on the potential biases in AI systems and how to address them is crucial in creating awareness and promoting the responsible use of AI.

How can healthcare organizations effectively use data on Social Determinants of Health (SDOH) to improve patient care, and what are the challenges in integrating this data into official diagnostic codes?

Integrating data on SDOH significantly improves patient care, but there are challenges to address. Comprehensive data collection is essential, including information such as socioeconomic status, education and environmental factors. This data provides insights into the social factors that influence patient health.

Data integration and interoperability are crucial for utilizing SDOH data effectively. Integrating this data into electronic health records (EHRs) and ensuring interoperability between different systems allows healthcare providers to have a holistic view of patient health, enabling personalized care plans. For instance, patients from low-income backgrounds or those living in areas with limited access to healthcare services may require additional support to manage chronic conditions. By incorporating SDOH data, healthcare organizations can develop targeted outreach programs, provide resources for transportation to medical appointments, and offer nutritional assistance to those in need.

Population health management is another area where SDOH data plays a critical role. By analyzing SDOH data at a community level, healthcare organizations can identify trends and patterns that inform public health strategies.

However, integrating SDOH data into official diagnostic codes presents an interoperability or standardization issue. is currently no universally accepted framework for coding SDOH data. Ensuring data quality is also difficult, as SDOH data often comes from various sources with differing levels of accuracy and completeness. Collaboration between healthcare organizations, policymakers, and technology vendors to establish standardized practices and ensure comprehensive data integration will be an important step in addressing these hurdles.

What are the main cybersecurity challenges faced by healthcare organizations, and how can they be addressed?

As we’ve seen over the past year, healthcare organizations are extremely vulnerable to cybersecurity threats. Data breaches and ransomware attacks are significant issues, requiring implementing robust encryption, multi-factor authentication and regular security audits to mitigate these threats. Legacy systems and software vulnerabilities are common in healthcare organizations, as many still use outdated systems. Regularly updating and patching software, as well as migrating to modern, secure platforms, is essential.

Insider threats, where employees with access to sensitive data, also pose significant risks. Implementing strict access controls, monitoring user activity, and providing cybersecurity training can play a significant role in preventing these issues. It’s critical to create a dedicated compliance team responsible for conducting regular security audits and risk assessments to identify vulnerabilities and ensure compliance with regulatory requirements such as HIPAA.

Potentially the most important measure is ongoing training and education for IT staff and healthcare professionals to protect against evolving cyber threats. Many of these threats exploit human vulnerabilities, so the more educated staff are about cybersecurity best practices, the more likely human error will be reduced, leading to more secure patient data.

What are the key ethical considerations that healthcare organizations must keep in mind when deploying AI solutions, and how can they navigate the pushback against AI implementations in hospitals?

This is one of the most important issues healthcare organizations must address, with a need to consider several ethical aspects and navigate potential pushback. Ensuring patient privacy and confidentiality is paramount, with AI solutions adhering to strict data protection regulations and employing robust security measures. Patients should be informed about the use of AI in their care and provide consent, involving an explanation of how AI will be used and the potential benefits and risks.

Bias and fairness are also crucial considerations. AI systems are designed to avoid biases and ensure equitable treatment for all patients, but as we know issues can arise here if organizations aren’t careful. That makes continuous monitoring and adjustment of these AI models supremely necessary to maintain fairness.

It’s also extremely important to be transparent about the use of AI and accountable for decisions made by AI systems, most notably by providing explanations for AI-driven decisions and establishing mechanisms for oversight.

Following through with all of that is a major step towards addressing concerns and resistance that both healthcare professionals and patients have towards implementation. But it’s also important to provide education around the implementation and benefits of AI, involving stakeholders in the AI implementation process, establishing a commitment towards taking a comprehensive approach centered around building trust, providing clear communication, and ensuring the ethical use of AI.

How can CitiusTech’s solutions help healthcare organizations achieve seamless data integration and interoperability across various platforms and applications?

At CitiusTech, we’re able to power healthcare digital innovation, business transformation and industry-wide convergence for healthcare and life sciences companies across the globe. Our solutions are designed to achieve seamless data integration and interoperability across various platforms and applications. Our advanced integration platforms ensure that disparate systems communicate and share data effectively, facilitating seamless data exchange for a unified view of patient information.

For example, a major blue plan with over million members was looking to move beyond members’ claims data and manual chart chases and leverage clinical data to accelerate care gap closures. Seeking a solution that could utilize the clinical data effectively, they leveraged CitiusTech to seamlessly integrate clinical data from an array of EHRs and data aggregators, bringing $10 million in annual savings.

CitiusTech’s management solutions maintain data quality, security and compliance throughout the integration process to handle the complexities of healthcare data, including the integration and interoperability of diverse data sources and platforms.

The recently launched CitiusTech Gen AI Quality and Trust Solution, an end-to-end solution that further enhances data integration, ensures the reliability, accuracy and trustworthiness of AI-driven insights. The solution provides robust validation, continuous monitoring and adherence to regulatory standards, creating accurate, reliable, and compliant AI-driven data integration and analysis. This enables healthcare organizations to leverage AI effectively for improved decision-making and patient outcomes.

What future trends do you foresee in the integration of AI within healthcare and life sciences, and how is CitiusTech preparing to address these trends?

With the integration of AI within healthcare and life sciences rapidly growing, the increasing use of AI for predictive analytics and personalized medicine, enhancing operational efficiency through automation, and advancing medical imaging and diagnostics will have a significant impact on the industry.

At CitiusTech, we’re staying ahead of these trends by continuously investing in R&D to stay at the forefront of AI advancements. As mentioned, we’ve developed Gen AI solutions such as our quality and trust tool, as well as other AI solutions that leverage the latest technologies to improve patient outcomes and operational efficiency. It is an essential priority to focus on ensuring the ethical and fair use of AI, addressing biases, and maintaining transparency and accountability in AI-driven decisions. It’s a priority for our team to stay updated with the latest AI trends ensuring we have the best resources available to help healthcare organizations navigate the evolving landscape of AI integration.

Thank you for the great interview, readers who wish to learn more should visit CitiusTech.

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Digital Transformation in Healthcare Market Giants Spending Is Going To Boom | HQSoftware, Microsoft, Cognizant, Accenture

Advance Market Analytics published a new research publication on “Global Digital Transformation in Healthcare Market Insights, to 2027” with 232 pages and enriched with self-explained Tables and charts in presentable format. In the study, you will find new evolving Trends, Drivers, Restraints, Opportunities generated by targeting market-associated stakeholders. The growth of the Digital Transformation in Healthcare market was mainly driven by the increasing R&D spending across the world.

Major players profiled in the study are:

Accenture PLC (Ireland), Adobe Systems (United States), Crayon (Norway), CA Technologies (United States), Cognizant (United States), Dell EMC (United States), Google LLC (United States), IBM Corporation (United States), Microsoft Corporation (United States), Oracle Corporation (United States), SAP SE (Germany), TCS (India), Royal Philips (Netherland), GE Healthcare (United States), Honeywell Life Care Solutions (United States), Stanley Healthcare (United States), Waracle (United Kingdom), HQSoftware (Estonia), Qulix Systems (United Kingdom),

Get Exclusive PDF Sample Copy of This Research @ https://www.advancemarketanalytics.com/sample-report/132280-global-digital-transformation-in-healthcare-market#utm_source=DigitalJournalVinay

Scope of the Report of Digital Transformation in Healthcare

Digital transformation in healthcare is the positive impact of technology in healthcare. Here’s why: Telemedicine, artificial intelligence (AI)-enabled medical devices, and block chain electronic health records are just a few concrete examples of digital transformation in healthcare which are completely reshaping how healthcare business interacts with patients, healthcare providers and regulators., how data is shared among providers and how decisions are made about treatment plans and health outcomes. Digital transformation in healthcare not only increased efficiency but also eliminates humans from the processes.

In 2020, -Medidata and Cognizant have entered into a strategic alliance to offer life science clients comprehensive solutions that leverage the market’s leading cloud platform with world-class business and technology services. This provides pharmaceutical, biotech, medical device companies, contract research organizations (CROs), sites and investigators with digital capabilities to facilitate a fast start to clinical trials, simplify operational complexities and drive digital transformation.

On 7 Feb 2020, CitiusTech, a leading provider of healthcare technology services and solutions, announced a partnership with Google Cloud to accelerate digital transformation and cloud adoption across healthcare organizations.

The Global Digital Transformation in Healthcare Market segments and Market Data Break Down are illuminated below:

by Organization Size (Large Enterprises, SMEs), Technology (Artificial Intelligence (AI), Cloud Computing, Big data and Analytics, Internet of Things (IoT), Others), Business Function (Customer Transformation, Workforce Transformation, Operational Transformation, Product Transformation), Component (Software, Hardware, Services), End User (Hospitals and Clinics, Pharmaceutical Companies, Home care Settings, Others)

Market Opportunities:

Rise in Awareness about 3D Printing

Improvements in the Health Care Infrastructure

Payers and Standards Bodies Can Accelerate and Sustain Technological Advancement by Adapting Reimbursement Guidelines

Market Drivers:

Advancements in Healthcare Fuelling the Market Growth

Increase in Demand for Digital Products

Growing Adoption Rate of EHRS and EMRS

COVID-19 Pandemic Has Fueled the Demand of Digital Transformation in Healthcare

Market Trend:

Rising Importance of Big Data in Healthcare Sector

The Growth of Wearable Medical Devices

Electronic Health Records for Medical Data Management

What can be explored with the Digital Transformation in Healthcare Market Study?

Gain Market Understanding

Identify Growth Opportunities

Analyze and Measure the Global Digital Transformation in Healthcare Market by Identifying Investment across various Industry Verticals

Understand the Trends that will drive Future Changes in Digital Transformation in Healthcare

Understand the Competitive Scenarios

Track Right Markets

Identify the Right Verticals

Region Included are: North America, Europe, Asia Pacific, Oceania, South America, Middle East & Africa

Country Level Break-Up: United States, Canada, Mexico, Brazil, Argentina, Colombia, Chile, South Africa, Nigeria, Tunisia, Morocco, Germany, United Kingdom (UK), the Netherlands, Spain, Italy, Belgium, Austria, Turkey, Russia, France, Poland, Israel, United Arab Emirates, Qatar, Saudi Arabia, China, Japan, Taiwan, South Korea, Singapore, India, Australia and New Zealand etc.

Have Any Questions Regarding Global Digital Transformation in Healthcare Market Report, Ask Our Experts@ https://www.advancemarketanalytics.com/enquiry-before-buy/132280-global-digital-transformation-in-healthcare-market#utm_source=DigitalJournalVinay

Strategic Points Covered in Table of Content of Global Digital Transformation in Healthcare Market:

Chapter 1: Introduction, market driving force product Objective of Study and Research Scope the Digital Transformation in Healthcare market

Chapter 2: Exclusive Summary – the basic information of the Digital Transformation in Healthcare Market.

Chapter 3: Displaying the Market Dynamics- Drivers, Trends and Challenges & Opportunities of the Digital Transformation in Healthcare

Chapter 4: Presenting the Digital Transformation in Healthcare Market Factor Analysis, Porters Five Forces, Supply/Value Chain, PESTEL analysis, Market Entropy, Patent/Trademark Analysis.

Chapter 5: Displaying the by Type, End User and Region/Country 2016-2021

Chapter 6: Evaluating the leading manufacturers of the Digital Transformation in Healthcare market which consists of its Competitive Landscape, Peer Group Analysis, BCG Matrix & Company Profile

Chapter 7: To evaluate the market by segments, by countries and by Manufacturers/Company with revenue share and sales by key countries in these various regions (2022-2027)

Chapter 8 & 9: Displaying the Appendix, Methodology and Data Source

Finally, Digital Transformation in Healthcare Market is a valuable source of guidance for individuals and companies.

Read Detailed Index of full Research Study at @ https://www.advancemarketanalytics.com/buy-now?format=1&report=132280#utm_source=DigitalJournalVinay

Contact Us:

Craig Francis (PR & Marketing Manager)

AMA Research & Media LLP

Unit No. 429, Parsonage Road Edison, NJ

New Jersey USA – 08837

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CMS 21st Century Cures IPA Rule & its Impact on State Health Agencies - CitiusTech CMS 21st Century Cures IPA Rule & its Impact on State Health Agencies

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NCQA’s Future of HEDIS® – How to align your health plan to follow this direction - CitiusTech

Our assessment  identifying 7 key areas of impact and that will drive the preparedness required for health plans in near term

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eClinicalWorks is hiring Fresher & Experienced software testers Follow Fresher & Experience Jobs - ReferIndia for more hiring updates #software #hiring #fresher #eclinical #jobs #experience #tcs #mnc #citiustech #capgemini #hiringfreshers #freshers #jobalert #fresherjobs (at Gujrat) https://www.instagram.com/p/CWcXYWWKEw0/?utm_medium=tumblr

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CitiusTech 2021 Hiring Freshers as Trainee

CitiusTech 2021 Hiring Freshers as Trainee Software Engineer CitiusTech 2021 Hiring Freshers as Trainee Software Engineer at Mumbai Job Title: Trainee Software Engineer Pass-out Year: 2020 / 2021 Location: Mumbai Experience: Freshers

CitiusTech Recruitment Drive for 2021 Fresher CitiusTech 2021 Hiring Freshers as Trainee Software Engineer at Mumbai About Company: CitiusTech is a specialist provider of healthcare technology and consulting enabled business solutions, with strong presence across the payer, provider, MedTech and life sciences markets. As a strategic partner to some of the world’s largest healthcare organizations,…

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A Pen Can Either Make Or Break A Future. Have A Great Weekend. #Pens #Stationery #CitiusTech #OneStopSolution #OneStopShop #OfficeSupplies #OfficeProducts #KanfaSupply #CorporateGifting #CorporateSupplies #ITProducts #Weekend #Mumbai #India 🖊🤝🌞

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Healthcare Analytics Market

Healthcare Analytics Market is valued at USD 29.54 Billion in 2021 and expected to reach USD 162.69 Billion by 2028 with a CAGR of 27.6% over the forecast period. 

Global Healthcare Analytics Market: Global Size, Trends, Competitive, Historical & Forecast Analysis, 2022-2028- Increasing adoption of big data in healthcare organizations, rising popularity of personalized medicine, and growing adoption of healthcare analytics are some of the major factors driving the growth of the Global Healthcare Analytics Market. 

Healthcare Analytics Market Key Players 

IBM

Optum

Cerner

SAS Institute

Allscripts

McKesson

MedeAnalytics

Oracle

Inovalon

Health Catalyst

SCIO Health Analytics

Cotiviti

CitiusTech

Wipro

VitreosHealth

others

Global Healthcare Analytics Market Segmentation:- 

By Type

Cognitive Analytics  

Descriptive Analytics  

Prescriptive Analytics 

Predictive Analytics 

By Component

 Services  

Software 

Hardware 

By Deployment Model

On-demand  

On-premise 

By Application

Operation & Administrative Analytics  

Clinical Analytics  

Population Health 

Financial Analytics 

By End-User

Healthcare Payers  

Life Science Companies

 News- 

PINC AI Launched INsights, an Enhanced Technology Offering for Customized, On-Demand Healthcare Analytics 

On January 19th, 2022; PINC AI, Premier, Inc's technology and services platform, launched INsights, an enhanced self-service healthcare solution for creating customized, on-demand analytics. INsights are a vendor-agnostic analytics platform that accesses PINC AI's pure, standardized and risk-adjusted healthcare data, including all U.S. Covers more than 45 percent of hospital inpatient discharges. INsights users leverage pre-developed analytics developed by PINC AI, as well as conduct customized data queries and visualizations using PINC AI or their own data sources. 

Amazon Launched Service for Big Data Analytics in Healthcare 

On December 10th, 2020; Amazon Web Services (AWS) announced Amazon HealthLake, a HIPAA-eligible service that aims to support interoperability standards and further drive the use of big data analytics in healthcare. Amazon HealthLake aimed to collect an organization’s complete data across different siloes and varying formats into a centralized data lake, automatically standardizing the data using machine learning techniques. The service allows organizations to store, tag, index, standardize, query, and apply machine learning techniques to analyze data in the cloud. 

By Region Analysis

North America

U.S.

Canada

Europe

Germany

France

U.K.

Italy

Spain

Netherland

Turkey

Switzerland

Belgium

Rest of Europe

Asia-Pacific

China

South Korea

Japan

India

Australia

Philippines

Singapore

Malaysia

Thailand

Indonesia

Rest Of APAC

Latin America

Brazil

Mexico

Colombia

Argentina

Peru

Rest of South America

Middle East and Africa

Saudi Arabia

UAE

Egypt

South Africa

Rest Of MEA

Key Benefits of Global Healthcare Analytics Market Report–

  Global Healthcare Analytics Market report covers     in-depth historical and forecast analysis 

Global Healthcare Analytics Market research report     provides detail information about Market Introduction, Market Summary,     Global market Revenue (Revenue USD), Market Drivers, Market Restraints,     Market Opportunities, Competitive Analysis, Regional and Country Level. 

Global Healthcare Analytics Market report helps to     identify opportunities in marketplace.

Global Healthcare Analytics Market report covers     extensive analysis of emerging trends and competitive landscape. 

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BITS Pilani to Upskill Professionals in Data Science, Analytics, Collaborates With CitiusTech

BITS Pilani to Upskill Professionals in Data Science, Analytics, Collaborates With CitiusTech

The Birla Institute of Technology and Science (BITS) Pilani’s Work Integrated Learning Programmes (WILP) division has collaborated with CitiusTech, a healthcare provider and a consulting solutions to teach students about emerging technologies such as data science and analytics technologies. The programme is for the working professional, the firm said and is for the CitrusTech’s employees. With…

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“Healthcare Analytics Market” report provides a detailed analysis of global market size, regional and country-level market size, segmentation, market growth, market share, and competitive landscape.

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CRM Systems for Health Plans - CitiusTech

Salesforce introduced the health cloud in 2016 specifically for the healthcare and life-science industry to help stakeholders across the clinical value chain drive digital transformation on a secure and customizable platform. This enables healthcare organizations to build strong relationships with customers and drive collaboration.

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Job Opening

ETL/SQL testing || Exp: 5-7 years Company: Citiustech healthcare Location: Mumbai/Bengaluru/Pune/ Chennai/hyderabad/Gurgaon Notice period: Immediate to 30 days would be preferred For reference kindly WhatsApp 8884144165 ThanksVishal Goyal