Showing posts with label second. Show all posts
Showing posts with label second. Show all posts
30 Second Sprints Several Times A Week Could Prevent Diabetes
Tuesday, May 6, 2014
If youre having difficulty keeping your resolution to exercise 30 minutes a day, 5-days-a-week, then youre going to like this study.Researches put young men through some very brief, but strenuous, workouts and found their sensitivity to insulin (and so their blood sugar levels) improved:
Extremely Short Duration High Intensity Interval Training Substantially Improves Insulin Action In Young Healthy Males, BMC Endocrine Disorders, January 2009
A total of 16 men, average age 21, underwent 6 sessions of exercise over 14 days.
A session of exercise consisted of:
- 30 seconds of cycling as fast as possible
- 4 minutes of rest
- The above repeated 4 to 6 times
Compared to before training (baseline):
- Postprandial glucose levels declined 12% (measured by AUC: Area Under the Curve)
- Postprandial insulin levels declined 37% (AUC)
- Postprandial free fatty acid levels declined 26% (AUC)
- Insulin sensitivity improved 23% (measured by Cederholm index)
- Aerobic cycling performance improved 6%
"The efficacy of a high intensity exercise protocol, involving only ~250 kcal of work each week, to substantially improve insulin action in young sedentary subjects is remarkable. This novel time-efficient training paradigm can be used as a strategy to reduce metabolic risk factors in young and middle aged sedentary populations who otherwise would not adhere to time consuming traditional aerobic exercise regimes."
Predictive Modeling The Second Most Important Ingredient for Provider Accountability
Thursday, February 27, 2014
![]() |
| When accountability fails |
While its one thing for health care providers to be "accountable" for costs, its another for them to actually make money at it. The Disease Management Care Blog is continuously amazed at how many physicians and administrators believe that dollops of "primary care," "prevention" and "wellness" will empty hospital beds and cause insurance money to appear like the morning dew on a windshield of a physician specialists BMW.
Believe that and the DMCB has an ORD-SFO United Airlines upgrade "departure management card" it would like to sell you.
If the DMCB could do only one thing to reduce costs within one fiscal year for a health care system , it wouldnt be PCPs, wellness or prevention. Instead, it would place one vastly overpaid case manager in every emergency room in the network. His or her job would be to find alternative levels of care for persons that dont really need to be in the hospital and begin discharge planning for those who do.
The second thing the DMCB would do is implement predictive modeling. Thats why its immodestly tooting its horn and suggesting research like this is so important. In this web first publication, Chris Hollenbeak, Mark Chirumbole, Benjamin Novinger, Frank Din and your humble DMCB examined the baseline demographic data and medical conditions that can predict the likelihood of a future high cost hospitalization within a Medicaid population. Armed with knowing which of its patients are at risk ahead of time is a critical level of intelligence for any newly "accountable" hospital, clinic, IPA, PHO or IDN. By reaching out to high risk individuals prior to any crisis, physicians and administrators can engage these patients in outpatient settings and keep them away from the emergency room.
The good news is that the art and science of predictive modeling is within reach of most data bases, desk-top computers, statistical software packages and trained analysts. The bad news is that interpreting and executing on that information remains a daunting challenge.
Health systems like HealthCare Partners is a good example of how it can work well. As this "accountability" movement in health care evolves, the DMCB will undoubtedly learn about other good examples.
The systems that rely on vague notions about primary care, fail to understand the role of case management and ignore the business case for predictive modeling will form the bad examples.
Labels:
accountability,
for,
important,
ingredient,
modeling,
most,
predictive,
provider,
second,
the
Subscribe to:
Posts (Atom)
