Rising Medical Errors Boost Demand for Hospital Risk Management Solutions

According to the latest market research study published by P&S Intelligence, the hospital risk management market is projected to reach USD 3,482.3 million by 2030, expanding at a CAGR of 13.5%. This surge is largely attributed to the rising frequency of medical errors and the global prevalence of chronic diseases.

Cloud-based risk management solutions accounted for over 80% of market revenue in the past and are anticipated to grow at a rate of 14% in the future. The increasing demand for interoperability across hospitals and companies, enabling seamless data exchange between databases and systems while reducing operating costs, is driving this growth. The adoption of electronic health records (EHRs), e-prescriptions, mHealth, and telehealth is further fueling industry expansion.

Leading market players are strengthening their positions through acquisitions to enhance cloud-based risk management solutions. For instance, in February 2022, IBM Corporation acquired Neudesic LLC to expand its portfolio of hybrid multi-cloud services.

Large hospitals are expected to dominate the market with a 60% share by 2030, driven by the rising number of large hospitals, increased hospital spending, and the growing use of EHRs. In the U.S., over 90% of hospitals are currently in the process of validating EHRs.

Effective hospital risk management is crucial for the smooth functioning of EHR systems, helping to minimize medical errors. Countries like Japan, South Korea, Russia, and Germany lead in hospital bed density, with ratios of 12.8, 12.4, 8.0, and 7.9 beds per 1,000 people, respectively.

North America leads the global hospital risk management market, with a strong presence of industry players in the U.S. The shift from on-premises to cloud-based healthcare IT solutions and the increasing use of data analytics to optimize hospital workflows are key growth drivers. Additionally, the rising number of medical errors contributes to market expansion. For example, approximately 10,000 Americans die each year due to medication errors, costing the U.S. around USD 40 billion annually.

The growing rate of preventable medical errors, surpassing deaths from car accidents, breast cancer, and AIDS, is expected to continue driving demand for hospital risk management solutions.

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Transforming Healthcare with AI-Powered Medical Imaging

AI-based medical imaging is transforming the field of healthcare by assisting physicians in providing more efficient, personalized, and accurate diagnosis and treatment selections.

Thanks to deep learning algorithms, medical imaging equipment now allows doctors to find irregularities and discover disorders with a greater level of speed and accuracy than ever before. This is because of the substantial advancement in diagnosis precision, treatment effectiveness, and the general quality of patient care.

Over the past few years, there has been a rising acceptance of AI in the healthcare sector to enhance diagnostics, patient care, and evaluation of the patient’s medical information. The utilization of AI technology is becoming more prevalent in medical imaging. Artificial Intelligence’s goal is not to substitute radiologists but to assist them in improving the diagnostic procedure.

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Understanding Medical Imaging

Simply, medical imaging refers to different technologies that are employed to observe the human body to diagnose, treat, or monitor medical conditions. It generally encompasses non-invasive picturing methods for medical personnel to recognize injuries and diagnose illnesses or chronic conditions.

The use of AI analysis in medical imaging assists doctors in identifying problem details or areas that might be missed by the human eye. For example, AI-based medical imaging can examine data points in a medical report to recognize a disease from a healthy part as well as signals from noise.

AI-powered medical imaging has been extensively utilized to:

• Recognize complicated patterns in imaging data.
• Identify image modalities at different treatment phases.
• Deliver a quantitative assessment of radiographic traits.
• Find different ailments characteristics that are not noticeable by human eyes.

Major applications of AI-based medical imaging are:

Cardiovascular Disorders

Cardiovascular disorders are generally diagnosed by assessing the patient’s heart structure. Conventionally, chest X-rays are employed first to find possible heart-associated irregularities. For instance, this technique is employed as a screening tool for an enlarged heart or cardiomegaly.

AI-powered medical imaging equipment can assist in identifying left atrial enlargement, therefore classifying a cardiac issue.

Neurological Abnormalities

AI technology has been effective in obtaining appropriate data from brain pictures. This has assisted in diagnosing different brain abnormalities.

AI-based medical imaging is also utilized to effectively diagnose neurological conditions such as amyotrophic lateral sclerosis, or ALS, and assist doctors in planning for lasting care. In addition, artificial intelligence algorithms in medical imaging can ease amyotrophic lateral sclerosis diagnosis by identifying any pictures that demonstrate suspect results.

Cancer Screening

Medical images are extensively utilized in the assessment of cancers such as colon cancer and breast cancer. For example, in breast cancer, tissue microcalcification is hard to classify as either benign or malignant. In this instance, false positives often result in unnecessary treatment, while unnoticed malignancies can delay diagnoses and affect the medical result.

AI-based medical imaging can enhance the precision and accuracy of finding microcalcifications by utilizing quantitative imaging.

In Ending This

With the surging chronic disorders incidence and the rising need for medical services for the elderly populace, the demand for AI-based medical imaging will reach USD 11,921.4 million in 2030.

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Service Demand to Drive Life Science Analytics Growth

The life science analytics market is projected to expand at a CAGR of 9.6%, reaching USD 18,386 million by 2030. Key drivers for this growth include the increasing emphasis on early disease detection through data analysis, helping to understand prescription patterns and optimize treatment approaches throughout a patient’s healthcare journey, while improving operational efficiency.

The demand for services is expected to see the highest growth, fueled by the presence of major multinationals like Accenture, IBM, and Oracle, which provide a comprehensive range of services in consulting, strategy, operations, and technology. These services enable personalized healthcare and enhanced patient outcomes.

For instance, Accenture supports the life sciences industry with offerings in R&D, medical technology, patient services, supply chain management, and cloud computing. These services help reduce costs, streamline operations, and improve engagement between healthcare companies, patients, and payors.

The on-demand analytics segment will grow at a CAGR of 9.7% due to the availability of flexible solutions. These solutions help users tackle complex challenges such as adapting to regulatory changes, incorporating new technologies, reassessing portfolios, and utilizing real-world evidence for data management and analysis.

In addition, corporations are becoming more agile, reducing the time to bring vaccines from development to production. This agility greatly benefits biotech firms that have been working tirelessly to develop vaccines since the pandemic outbreak. The growth of the life science analytics market is further supported by the rapid response of IT companies providing these solutions.

The Asia-Pacific region will experience the fastest growth, with a 9.9% CAGR by 2030. Factors driving this growth include the rising incidence of chronic diseases, expanding life sciences industry, increasing adoption of advanced technologies, and a focus on strengthening their presence in emerging Asian economies. Increased investment, economic growth in India and China, and improved healthcare infrastructure further fuel the market.

Europe ranks as the second-largest market, driven by the development of new analytics applications in life sciences and the rising demand from the pharmaceutical sector. Analytics in life sciences is heavily utilized to assess clinical trial risks, enhance R&D, forecast budgets, and determine pricing strategies.

The rising global prevalence of chronic diseases will continue to drive the demand for life science analytics solutions in the coming years.

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