The size of the Healthcare Data Industry market was valued at USD XX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 16.20% during the forecast period. Data in healthcare signifies all the information that is created or gathered in the healthcare industry. These include patient records, electronic health records, genomic data, health insurance claims, medical images, and all other clinical trial data. All this stands at the back of modern healthcare and could support many critical applications. First and foremost, health data improves patient care. Pattern analysis for patient records is simplified by health care providers in ensuring accurate disease diagnosis and application of personalized treatment plans. Medical field images, such as X-rays and MRIs, are helpful in finding abnormalities and useful in surgical methods. Genomic data insights comprise susceptibility from a genetic view point, which therefore enables coming up with a customised treatment plan for diseases such as cancer. Then, the health information data is very crucial in conducting research and developing new medical knowledge. Researchers analyze epidemiology of diseases by adopting massive datasets, manufacture new drugs and treatments, and analyze effectiveness of health care programs by such datasets. For instance, the medical trials dataset helps in the development of evidence about the safety and efficiency of new treatment options. The health insurance claims dataset can help assess healthcare utilization patterns so as to identify areas in need of improvement. Therefore, health care data also enables administrative and operational functions of health care organizations. EHRs allow easy maintenance of the patient data, enable sound communications among healthcare providers, and minimize errors. Apart from this, analytics on health insurance claims are performed to make possible billing and reimbursement services to ensure the payment of the healthcare provider in the right amount of their rendered service. Further, analytics data could be used for optimization of resource utilization, in identifying potential cost savings, and making health care organizations efficient as a whole. Healthcare information is one of those precious assets that propel innovation, promote better patient outcomes, and support the coherent functioning of the healthcare system. Therefore, improving the quality and efficiency in which care delivery is offered can be achieved through the effective use of healthcare information by healthcare providers, researchers, and administrators for a better state of health among individuals and communities. Recent developments include: March 2022: Microsoft launched Azure Health Data Services in the United States. It is a platform as a service (PAAS) offering designed exclusively to support protected health information (PHI) in the cloud., March 2022: The government of Thailand launched a big data portal for healthcare facilities. The National Reforms Committee on Public Health recently joined hands with 12 government agencies to improve the quality of healthcare services by implementing digital technologies.. Key drivers for this market are: Increase in Demand for Analytics Solutions for Population Health Management, Rise in Need for Business Intelligence to Optimize Health Administration and Strategy; Surge in Adoption of Big Data in the Healthcare Industry. Potential restraints include: Security Concerns Related to Sensitive Patients Medical Data, High Cost of Implementation and Deployment. Notable trends are: Cloud Segment is Expected to Register a High Growth Rate Over the Forecast Period.

Leiden University’s study aims to demonstrate the added value of advanced bibliometrics analyses in the context of science policy, beyond its conventional uses in research evaluation. The analyses takes into consideration the example of cancer research to illustrate the potential of bibliometric data to reveal information beyond counting publications and citations, and specifically to gain insights into the dynamics of a research field or organisation, its structure and its different ways in which research is connected to societal processes. The bibliometric analyses have been conducted using the RISIS CWTS publication Dataset. The power of advanced bibliometrics is its capacity to analyse and contextualize a research group, a university, a discipline, regions, countries or group of countries. Thus, the study encourages science policy analysists to make use of advanced scientometric techniques to support decision making. In addition, it will show how bibliometrics can support benchmarking of countries and types of cancer across a variety of properties – not only number of publications and citations, but also the extent to which these publications are mentioned in social media, are cited in patents, are produced in local hospitals, in local languages (non-English), in collaboration with industry, etc. In the area of cancer research, this multidimensional perspective could help science policy analysts to identify specific research areas which might be candidates to be funded and/or to better understand and reflect on how the cancer mission evolves across Europe.