Health care analytics
Health care analytics is a product category used in the marketing of business software and consulting services. It makes extensive use of data, statistical and qualitative analysis, explanatory and predictive modeling.[1]
Contents
Theory
"Predictive vs. Explanatory Modeling in IS Research", and patient health information to drive medical decision making.[vague] The breadth of digital data available through point-of-care encounters, medical claims, pharmacy claims, lab values, HRAs, genetic markers, and biometrics has resulted in an increase in the capabilities of traditional analytical tools. This data is combined with medical guidelines and patient profiles to reveal contraindicated care, gaps in care, and opportunities for cost savings. John-David Lovelock, Research VP at Gartner, called health care analytics 'the first step in improving the overall efficiency of hospitals.'[2]
Real-time Health Care Analytics
Currently the most prevalent application for real-time health care analytics is within Clinical Decision Support (CDS) software. These programs analyze clinical information at the point of care and support health providers as they make prescriptive decisions. These real-time systems are “active knowledge systems, which use two or more items of patient data to generate case-specific advice.”[3]
Health care analytics is the key for health issue measurements.
Batch Health Care Analytics
Batch health care analytics is a technical application in which retrospectively evaluates population data sets (i.e. records of patients in a large medical system, or claims data from an insured population). These evaluations can be used to supplement disease management or population health management efforts.
Opportunities for the secondary use of routinely collected data for research purposes have increased enormously in recent years due to the wide uptake and advances in technology; for example, electronic health records (EHR). The continued expansion of large databases of patient records, often linked to other sources of data, has greatly enhanced the possibilities for using these records for health services and clinical research. [4]
A benefit of batch health care analytics is its use of "predictive modeling across multiple clinical conditions.[5] This process can identify undiagnosed conditions for patients within an insurer's patient population, or suggest interventions to prevent conditions from developing.
References
- ↑ Galit Schmueli and Otto Koppius
- ↑ http://wistechnology.com/articles/4599/
- ↑ "Decision support systems." 26 July 2005. 17 Feb. 2009 http://www.openclinical.org/dss.html
- ↑ Exploiting the potential of large databases of electronic health records for research using rapid search algorithms and an intuitive query interface http://jamia.bmj.com/content/early/2013/11/22/amiajnl-2013-001847.full
- ↑ Howe, Rufus, and Christopher Spence. Population health management: Healthways' PopWorks. HCT Project 2004-07-17, volume 2, chapter 5, pages 291-297. Retrieved 2008-10-12.
