The healthcare information technology (IT) market is expected to witness market growth at a rate of 16.17% in the forecast period of 2021 to 2028 and is expected to reach USD 34.3 billion by 2028. Data Bridge Market Research report on healthcare information technology (IT) market provides analysis and insights regarding the various factors expected to be prevalent throughout the forecast period while providing their impacts on the market’s growth. The rise in the aviation sector is escalating the growth of healthcare information technology (IT) market.
The North America Healthcare Information Technology (IT) Market Market Scope and Size
On the basis of product and services, the healthcare information technology (IT) market is segmented into healthcare provider solutions, healthcare payer solutions, and HCIT outsourcing services. Healthcare provider solutions are further sub-segmented into clinical solutions and non-clinical solutions. Clinical solutions are divided into PACS and VNA, e-prescribing system, computerized physician order entry, clinical decision support system (CDSS), electronic health record (EHR), specialty information management systems, patient engagement solutions, radiology information systems (RIS), radiation dose management solutions, medical image analysis systems, care management systems, mheath solutions, patient registry software, laboratory information systems, infection surveillance solutions, telemedicine, population health management solutions, HCIT integration systems, and practice management systems. Non-clinical solutions are divided into healthcare workforce management solutions, medical document management solutions, healthcare asset management solutions, pharmacy information systems, healthcare analytics, revenue cycle management solutions, healthcare information exchanges, medication management solutions, supply chain management solutions, healthcare interoperability solutions, customer relationship management solutions,
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Key Players North America Healthcare Information Technology (IT) Market Market
· The major players covered in the healthcare information technology (IT) market report are Allscripts Healthcare, LLC, Epic Systems Corporation, McKesson Corporation, Cerner Corporation, Siemens Healthcare GmbH, Carestream Health, Agfa-Gevaert Group, athenahealth, Inc., eClinicalWorks, GENERAL ELECTRIC, GREENWAY HEALTH, LLC., Infor, Koninklijke Philips N.V., NXGN Management, LLC, Oracle, Siilo, BigHealth, Vida Health, SWORD Health, NOVIGENIX SA, Lantum, BD, Bioaxis, Ada Health GmbH, among other. DBMR analysts understand competitive strengths and provide competitive analysis for each competitor separately.
MAJOR TOC OF THE REPORT
v Chapter One: Introduction
v Chapter Two: North America Healthcare Information Technology (IT) Market Market Segmentation
v Chapter Three: North America Healthcare Information Technology (IT) Market Market Overview
v Chapter Four: Executive Summary
v Chapter Five: Premium Insights
v Chapter Six: Global North America Healthcare Information Technology (IT) Market Market by Product & Procedure type
Get TOC Details: @ https://www.databridgemarketresearch.com/toc/?dbmr=north-america-healthcare-it-market
Key Report Highlights
Comprehensive pricing analysis based on different product types and regional segments
Market size data in terms of revenue and sales volume
Deep insights about regulatory and investment scenarios of the global North America Healthcare Information Technology (IT) Market Market
Analysis of market effect factors and their impact on the forecast and outlook of the global North America Healthcare Information Technology (IT) Market Market
The detailed assessment of the vendor landscape and leading companies to help understand the level of competition in the global North America Healthcare Information Technology (IT) Market Market
The exhaustive analysis of various trends of the Global North America Healthcare Information Technology (IT) Market Market to help identify market developments
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Machine learning could become a new weapon in the fight against Medicare fraud.Machine learning can be a useful tool in detecting Medicare fraud, according to a new study that can recover anywhere from $ 19 billion to $ 65 billion lost in fraud each year.Researchers at Florida Atlantic University’s College of Engineering and Computer Science recently published the world’s first study using Medicare Big data, machine learning, and advanced analytics to automate fraud detection.
They tested six different machine learners on balanced and unbalanced data sets and eventually found that the RF100 Random Forest algorithm would be most effective in detecting potential cases of fraud.
They found that unbalanced data sets are more than balanced data sets when scanning for fraud.There are many implications in determining what fraud is and what is not, such as clerical error,” says Richard A. Bowder, senior author and Ph.D.“Our goal is to allow machine learners to know all this data and flag anything suspicious.
Then we can alert researchers and auditors, who should focus on 50 cases instead of 500 cases or more.”In the study, Bowder and colleagues examined Medicare data, covering 37 million cases from 2012 to 2015, for incidents such as patient abuse, neglect, and billing for medical services.
The team has reduced the data set to 3.7 million cases, which is still a challenge for human researchers charged with pinpointing Medicare fraud.The authors used the National Provider Identifier — a government-issued ID number for health care providers to compare fraud labels with Medicare Part data, which includes provider details, payment and charge information, policy codes, all policies, and medical specifications.When researchers compared NPI with Medicare data, they flagged fraudulent providers in a separate database.“If we can accurately assess the physician’s uniqueness based on our statistical analyses, then we can detect exceptional physician behaviors and flag as much fraud as possible for further investigation,” said Tagi M. Khoshgofthar, Ph.D., co-author, and professor at the school.So, if a cardiologist is wrongly labeled a neurologist, it is a sign of deception.However, the data set remains a challenge.
A small number of fraudulent providers and a large number of onboard providers have made data imbalance that can fool machine practitioners.
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