With the amount of data exceeding 187 petabytes by 2015, soaring trend of social media and increasing use of technology further adding to the data generation ensures that the need for predictive analytics in healthcare will be the competitive advantage of the organizations. Furthermore, with services becoming more customized and specific to a consumer, the demand of effectively predicting the pattern to take decisions while strategizing and implementing the process efficiently will provide an edge over the competition. Accurate implementation of predictive analytics will lead to the creation of more precise and detailed profiling of the patient resulting in better service experience as well as prediction of potential diseases leading to the prevention, thereby increasing value to the customer. Since around 2% of genetic structure tends to be different for every person, prediction of the type of dosage, projection of vulnerability data via Electronic Health Record (EHR) will further help in creating a personalized profile close to perfection. Thus, predictive analytics is the branch that uses data mining, statistical techniques, machine learning and predictive modeling to determine likely trends in future using descriptive data.
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The primary market driver for Healthcare Predictive Analytics is the surfacing of personalized and evidence-based medicine. It helps in managing inherited disorders through prediction of molecular pathology, accurate diagnosis and assessing phenotypic correlations. This information results in efficient personal healthcare. Another factor increasing the need for predictive analysis in the healthcare industry is the efficiency enhancement of the processes currently followed. This can be done by reducing unnecessary cost, thereby, curtailing overall costs of current systems. As mentioned earlier, another driver for the market is the exponential expansion of data via various tools which will require appropriate usage of predictive analytics. Advancements in this field will also give rise to better systems which will reduce the penalties due to the failure of controlling adverse conditions. However, the area is a new application of technology, availability of labor with required skill set is lacking, which might hinder the growth of the market. Furthermore, the high initial costs associated with usage of the technologies required for implementing predictive analytics is another major inhibitor for the market. Additionally, the integrity of data and safety associated with it may also negatively impact the market as it might make healthcare industries refrain from sharing data with analytics firm.
The Healthcare Predictive Analytics Market can be segmented via application, component, mode of deployment, geography and end user. By application, the market is segmented into Clinical Data Analytics, Financial Data Analytics, Administrative Data Analytics and Research Data Analytics. Segmentation by component gives software, hardware, and services. By mode of deployment, the market is categorized as On-Premise, Web-Based and Cloud-Based. Regarding geography, North America, Europe, Asia-Pacific and, Middle East and Africa gives the segmentation of the market. The market is classified as hospitals, physicians, clinics, government organizations and research institutions, via end-user segmentation.
Currently, North America (majorly U.S.) is the leader because of implementation of EHR and GPS enabled systems. Europe has second largest share while Asia-Pacific market is expected to increase at a relatively higher rate. In MEA, Saudi Arabia and South Africa are key markets.
IBM, Cerner, Oracle, McKesson Corporation, Optum Inc., Verisk Analytics, TruvenHealthAnalytics are some of the major market players.
Report ContentsRegional AnalysisReport Highlights
Market Drivers, Restraints and Opportunities
Market Size & Forecast 2016 to 2022
Supply & Demand Value Chain
Market - Current Trends
Competition & Major Companies
Technology and R&D Status
Porters Five Force Analysis
Strategic and Critical Success Factor Analysis of Key Players
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