IBM (US), SAS Institute Inc. (US), Optum, Inc. (US) are Leading Players in the Healthcare Analytics Market
Northbrook, IL 60062 — (SBWIRE) — 03/01/2023 — The healthcare analytics industry is expected to experience significant growth in the near future. The increasing demand for data-driven solutions in healthcare, the growing demand for digital health solutions, and the use of cloud-based analytics platforms are some of the factors driving this growth. Additionally, the emergence of artificial intelligence (AI) and machine learning (ML) technologies are creating new opportunities for healthcare providers to gain insights into patient health and improve care quality. In the near future, healthcare analytics will become more sophisticated and predictive, as these technologies become more widely adopted. Moreover, healthcare analytics is expected to be used to identify high-risk patients, predict health outcomes, and provide early detection and prevention services. As the industry matures, it is likely that healthcare analytics will become increasingly important in providing personalized and tailored patient care.
Healthcare Analytics market in terms of revenue was estimated to be worth $27.4 billion in 2022 and is poised to reach $85.9 billion by 2027, growing at a CAGR of 6.9% from 2022 to 2027 according to a latest report published by MarketsandMarkets™. Healthcare analytics is the efficient use of data and related business insights built through statistical, quantitative, predictive, comparative, cognitive, and other emerging applied analytical models. Increasing venture capital investments, big data in healthcare and government initiatives to increase EHR adoption are driving the market growth. However, high costs of healthcare analytics software and services and rising data security concerns are likely to restrain the market growth in the coming years.
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Prominent Players of Healthcare Analytics Market:
The prominent players in healthcare analytics market include IBM (US), SAS Institute Inc. (US), Optum, Inc. (US), Cerner Corporation (US), Allscripts Healthcare, LLC (US), Cotiviti, Inc. (US), CitiusTech Inc (US), Health Catalyst (US), CVS Health (US), Inovalon (US), McKesson Corporation (US), MedeAnalytics, Inc. (US), Oracle (US), ExlService Holdings, Inc. (US), Gainwell (US), Wipro (US), Flatiron (US), Apixio (US), Enlitic, Inc. (US), Komodo Health, Inc. (US), HealthEC, LLC, Sema4 OpCo, Inc. (US), Evidation Health, Inc. (US), Insilico Medicine (US), Exscientia (UK), Aetion, Inc.(US), and Premier (US). and Among Others
Notable Healthcare Analytics mergers and acquisitions for 2021 – 2022 include:
– UnitedHealth Group’s acquisition of Change Healthcare for $8 billion
– IBM’s acquisition of Truven Health Analytics for $2.6 billion
– McKesson Corporation’s acquisition of MedAssets for $2.8 billion
– Optum’s acquisition of Humedica for an undisclosed amount
– Allscripts’ acquisition of Enterprise Health Solutions for $185 million
– Cerner Corporation’s acquisition of Siemens Health Services for $1.3 billion
– The Advisory Board Company’s acquisition of Evolent Health for $1.3 billion
– GE Healthcare’s acquisition of Predixion Software for an undisclosed amount
– HCA Healthcare’s acquisition of RCCH HealthCare Partners for $1.8 billion
– Athenahealth’s acquisition of Vericred for an undisclosed amount
Growth Drivers of Healthcare Analytics Market from Macro to Micro:
– Increasing usage of Electronic Medical Records: The increasing use of electronic medical records (EMRs) is driving the growth of healthcare analytics market. EMRs help in the storage and retrieval of patient records in an organized manner, which makes the data more accessible to medical practitioners and healthcare organizations for decision making.
– Growing need for cost containment in healthcare: The rising cost of healthcare is a major concern for healthcare organizations and governments all over the world. Healthcare analytics helps in identifying cost-saving opportunities and improving operational efficiency. This is expected to drive the growth of healthcare analytics market.
– Need for better patient outcomes: Healthcare analytics provides insights into patient outcomes, which helps healthcare organizations in understanding the effectiveness of the treatment and taking corrective actions if required. This is expected to be a major driver of healthcare analytics market.
– Government support: Governments of various countries are taking initiatives to promote the adoption of healthcare analytics. For example, the US government has launched the Precision Medicine Initiative to improve patient outcomes and reduce healthcare costs. This is expected to boost the growth of healthcare analytics market.
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Hypothetic Challenges of Healthcare Analytics Market in Near Future:
– Increasing cost of healthcare analytics solutions: Increasing cost of healthcare analytics solutions due to rising demand and increasing complexity of data sets, may pose a challenge for the healthcare analytics market in the near future.
– Security and privacy concerns: Security and privacy concerns related to the utilization of healthcare analytics solutions may limit the growth of the healthcare analytics market in the near future.
– Lack of skilled professionals: Lack of skilled professionals to effectively utilize healthcare analytics solutions may hamper the growth of the healthcare analytics market in the near future.
– Regulatory hurdles: Regulatory hurdles related to healthcare analytics solutions may restrict the growth of the healthcare analytics market in the near future.
– Data integration issues: Data integration issues, such as incompatibility of data sets, may also impede the growth of the healthcare analytics market in the near future.
Top 3 Use Cases of Healthcare Analytics Market:
– Population Health Management: Population health management is a healthcare analytics solution that enables healthcare organizations to analyze health data from disparate sources to gain insights into population health trends. This helps healthcare organizations better manage the health of their patient population, identify gaps in care, and develop targeted interventions to improve outcomes.
– Clinical Decision Support: Clinical decision support systems are healthcare analytics solutions that use data-driven insights to help healthcare providers make better decisions about patient care. By leveraging predictive analytics and machine learning, these systems can provide clinicians with real-time recommendations based on the patient’s history, current condition, and other factors.
– Fraud Detection and Prevention: Healthcare analytics can be used to detect and prevent fraud in the healthcare industry. By leveraging predictive analytics and machine learning, healthcare organizations can detect suspicious activity, identify patterns of fraudulent behavior, and take action to prevent fraud. This helps keep healthcare costs down and ensure that patient data is secure.
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