The applications of healthcare analytics ranges from basic reporting and dashboard creation to high-end predictive and prescriptive analytics. The availability of advanced analytics for modeling, simulation, and forecasting allows both the life sciences and healthcare industries to focus on researching and delivering more effective strategies for preventing, managing, and curing health-related issues. With the health reforms focusing more on proactive healthcare, along with the potential aggregation of a cross-industry longitudinal health information database, the demand and desire for analytics-driven healthcare is growing. With a comprehensive healthcare data set, advanced analytics can be shared in near real-time and applied to better understand individuals, conditions, and treatments both in terms of specific comparisons and long-term perspectives with the help of electronic health records.
According to a new market research report published by iHealthcareAnalyst, Inc., Electronic Health Records Market – Global EHR Softwares Analysis and Forecast 2016-2020, the global electronic health records market was valued at USD 12,445 Million in 2013 and is estimated to reach USD 22,235 Million in 2020, expanding at a CAGR of 6.0% from 2015 to 2020.
The healthcare informatics can be leveraged to achieve many qualitative as well as quantitative goals:
- Improving health care quality
- Reducing health care costs
- Early detection, prevention, and management of chronic diseases
- Ensuring secure and protected patient health information
- Informing medical decisions at the time or place of care
- Improving coordination among hospitals, labs, physicians, payers and patients
- Facilitating rapid response to public health emergencies
- Facilitating health and clinical research
- Promoting a more effective marketplace
- Improving efforts to reduce health disparities
Personalized Medicine (including genomics and phenotype evaluation)
Personalized medicine involves the analytics of evaluating the specific treatment options available for specific characteristics and the effectiveness of treatments relevant to a specific situation.
Evaluation of providers along a number of potential dimensions, such as adherence to guidelines, qualitative improvements for various conditions, breadth of treatment options, and success rates for procedures.
Evaluation and analysis of a disease or condition based on the characteristics of the patient’s condition or the target itself. Evaluation of a particular treatment, drug, or compound for any unexpected new indications as a result of the use of the treatment alone or in combination with other treatments or drugs.
Evaluation and analysis of patients including their risks, conditions, and care plan strategy, treatment adoption and adherence likelihood.
Clinical Trial Management
Recruitment: Analytics that allow for both real-time recruitment of patients into clinical trials based on specific characteristics of an ideal participant as well as analytics that evaluate an available patient population to proactively identify potential clinical trial participants based on an ideal participant profile.
Simulation: Analytics evaluating a comprehensive longitudinal health information database for simulating clinical trials using cohorts selected from the aggregated population based on specific participant characteristics.
Surveillance: Evaluation of marketed drugs to compare safety and efficacy results with those collected during the drug development process.