The Europe Healthcare Analytics Market is projected to register a CAGR of 19% over the forecast period.
The COVID–19 has a slightly positive impact on the healthcare analytics market, which has been majorly attributed to the current focus of the pharmaceutical and biotech companies on developing a therapeutic drug or vaccine for COVID–19. Some companies are also conducting clinical trials for their specific drug components. Analytics, which plays a major role in clinical trials and dealing with the huge database, is found to be useful in the current situation of the COVID – 19 global outbreak.
With the increasing data records in the healthcare sector, the adoption of advanced analytics is increasing to provide data-driven insights at a faster rate, which are the primary factors driving the studied market. Reduced cost of care and prediction of possible emergency services drive the market. With digitized healthcare records, patient patterns and histories can be identified more efficiently. Predictive analytics can isolate patients that may be at risk of crises from chronic health problems, giving physicians an opportunity to provide corrective plans that decrease emergency visits, thus, further reducing the overall cost of resources. With the advent of digital devices such as IoT and applications that are increasingly becoming part of the healthcare system in Europe, various government initiatives to support and incentivize the use of technological solutions in healthcare further boost the demand for data analytics. For instance, in November 2019, Digital Supply Law was proposed in the federal parliament in Germany, which enables doctors to prescribe apps to their patients, which can be reimbursed by German statutory health insurance.
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Apart from this, the use of connected devices that generate huge amounts of data is expected to increase significantly; this raw data can be analyzed to make better enterprise decisions. According to European Telecommunications Network Operators(ETNO), the number of IoT active connections in healthcare in the EU during 2019 stood at 2.79 million and expected to reach 10.34 million by 2025. Such growth further strengthens the demand for data analytics and tools to gain data-driven insights into the industry.
Moreover, a surge in the adoption of e-health services in European Union in recent years is also expected to boost the growth of the studied market. According to a study by the European Commission in 2018, about 96% of the doctors in the region used electronic health records. Countries such as Estonia, Denmark, Finland, Spain, Sweden, and the UK are amongst the highest adopters of e-health, and it is routinely used among doctors in these countries. Over 80% of the doctors in the region are using e-health functionalities such as problem list/diagnoses (86%), lab test results (86%), basic medical parameters (85%), medical history (84%), symptoms (81%), clinical notes (80%), ordered tests (80%). Such data can be used by the institutes to analyze further and optimize their operations to reduce redundant activities.
Further, with the outbreak of Covid-19 various hospitals and healthcare enterprises are increasing their focus on the adoption of analytics as part of their operations. Patients and doctors are rapidly adopting telemedicine and other digital tools to deliver care. According to Tech Nation’s Data Commons, the United Kingdom has more than 100 healthtech startups with the potential to become USD 1 billion business, and the UK government announced to provide a fund of GBP 1.25 billion, which includes a GBP 500 million investment fund for high-growth companies.
Key Market Trends
Clinical Data Analytics to Witness Significant Growth Over the Forecast Period
A growing number of healthcare institutes and enterprises are looking to adopt clinical analytics as part of their operations to offer preventive care by effectively monitoring patient data and individual attention to increasing the effectiveness and efficiency of their services.
Clinical data analytics is assured to become an essential tool that makes use of real-time medical data health (by eHealth) through predictive analytics to generate insights into data, make decisions, predict outcomes, and decrease costs by enabling early interventions for potential clinical complications. Clinical data analytics is helping healthcare providers in analyzing their data and initiating a shift from fee-for-service reimbursements to value-based purchasing, accountable care organizations, and value-based insurance design (VBID).
The adoption of predictive analytics in better diagnosing the patient results in reducing the customer cost and increasing customer satisfaction. According to a study by the Society of Actuaries in 2019, predictive data analytics amongst healthcare enterprises resulted in a 39% reduced cost and a 42% increase in patient satisfaction.
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Hospitals in Italy mostly have their own Computerized physician order entry(CPOE), electronic medical record(EMR), and Radio-frequency identification(RFID) track & trace platform fully operating in the country. The hospital information systems and EMRs in the Lombardy region is one of the largest investment provided by the government in Italy.
Further, researchers of the Politecnico Di Milano’s Digital Innovation in Healthcare Observatory monitors the evolution of digital healthcare in Italy year over year. In 2019, they quantified the economic resources used in Italy to build digital support to government healthcare, with around total expense summing up to EUR 1.39 billion. This provides a significant contribution to the healthcare analytics market.
Moreover, a significant share of expenditure is related to patient care, and diagnosis and analytics offer to optimize the process. According to a study by MedTech Europe in 2018, about 76.6% of the healthcare expenditure in Europe is related to inpatient and outpatient care.
The increasing adoption of digital patient records as electronic medical records in the region is seeing a surge that helps organizations offer better care and analysis of patients’ various conditions. Thus, various patients of hypertension, cardiovascular disease, and other chronic illness patient’s data can be better analyzed.
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