Effective disease management programmes significantly reduce hospital visits, save costs for healthcare insurers, and lower healthcare costs for patients.
Key to the success of such programmes, however, is to identify the people who are most likely to get sick, and then to provide them with the most aggressive and proactive care programme available.
"Data mining and medical informatics can identify early indicators of serious disease, enabling health insurers and medical aid companies to begin meeting patient healthcare needs before they become seriously ill," says Corey Springett, business development manager at SAS Institute. SAS is the market leader in providing a new generation of business intelligence software and services.
SAS data mining, for example, can score and explore healthcare claims data and identify which members are most at risk for a range of serious illnesses - including diabetes, asthma, congestive heart failure and coronary artery disease.
Once these high-risk members are identified, they can be referred to a disease management programme that offers services ranging from simple reminders about taking medication, to coordinated efforts for managing multiple diseases.
The goals are to improve patient care and reduce healthcare costs. When patients with chronic conditions learn to better manage their conditions, the benefits include fewer complications, fewer office visits, shorter and less frequent hospital stays and, ultimately, a better quality of life.
In the US, for example, a mere 1% of insurance customers incurs nearly a quarter of all healthcare costs. According to the US Health Care Financing Administration, however, early identification and subsequent care management can reduce hospitalisation rates by 50% and cut healthcare costs by 35%.
Before using SAS, major US healthcare insurer Trigon relied on a standard review of patient healthcare activities to identify those patients most in need of care. The standard methods used in the past to identify high-risk patients would only find 20% of the people that should have been identified. The percentage was doubled with one application of SAS Enterprise Miner, and has continued to improve ever since.
"Many early indicators of serious conditions might go unnoticed when viewed in isolation," says Springett. "High-risk patients are often identified from frequent admission reports, but this is very reactive, and often too late."
SAS helps identify the most relevant variables, as well as those patients most at risk for developing chronic conditions. It has the ability to construct patterns, enabling health insurers and medical aid companies to get a complete and accurate picture.
It can improve disease management programmes to the extent that they can reduce the number of hospital visits and lower healthcare costs even more significantly. For example, Trigon's disease management programme for high-risk asthma patients has been proven to reduce emergency room visits by 84% and to reduce inpatient admissions by 28%. Likewise, the programme for congestive heart failure has reduced emergency room visits by 38% and inpatient admissions by 43%.
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