Novel predictive models for metabolic syndrome risk: A "big data" analytic approach

American Journal of Managed Care

Volumn 20, Issue 6, 2014, Pages

  Steinberg, Gregory B ^a   Church, Bruce W ^b   McCall, Carol J ^b   Scott, Adam B ^a   Kalis, Brian P ^c  

^a AETNA   (United States)

^b GNS Healthcare   (United States)

^c Accenture Health and Public Services   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GLUCOSE; HIGH DENSITY LIPOPROTEIN; INSULIN; TRIACYLGLYCEROL;

ADULT; ARTICLE; CARDIOVASCULAR DISEASE; DATA ANALYSIS; DIABETES MELLITUS; GLUCOSE BLOOD LEVEL; HEALTH CARE COST; HEALTH HAZARD; HEALTH INSURANCE; HEALTH RISK ASSESSMENT; HUMAN; INSULIN RESISTANCE; LABORATORY TEST; LIPID BLOOD LEVEL; MEDICAL RECORD; METABOLIC SYNDROME X; MODEL; PHARMACY; PREDICTION; PREVALENCE; PRIORITY JOURNAL; PROBABILITY; RISK ASSESSMENT; RISK FACTOR; WAIST CIRCUMFERENCE; DRUG COST; ECONOMICS; FEMALE; MALE; MEDICATION COMPLIANCE; PROCEDURES; SEX DIFFERENCE; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA;

DRUG COSTS; FEMALE; HEALTH CARE COSTS; HUMANS; MALE; MEDICATION ADHERENCE; METABOLIC SYNDROME X; MODELS, STATISTICAL; RISK ASSESSMENT; RISK FACTORS; SEX FACTORS;

EID: 84903610582     PISSN: 10880224     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (10)

1. Fitch K, Pyenson B, Iwasaki K. Metabolic syndrome and employer sponsored medical benefits: an actuarial analysis. Milliman website. http://publications. milliman.com/research/health-rr/pdfs/metabolic-syndrome- employer-sponsored- RR03-01-06.pdf. Published March 2006.
2. Ervin RB. Prevalence of metabolic syndrome among adults 20 years of age and over, by sex, age, race and ethnicity, and body mass index: United States, 2003-2006. National Health Statistics Report, vol 13. CDC website. http://www.cdc.gov/nchs/data/nhsr/nhsr013.pdf. Published May 5, 2009.
3. Edington DW, Schulz AB. Metabolic syndrome in a workplace: prevalence, co-morbidities, and economic impact. Metab Syndr Relat Disord. 2009;7(5):459-468.
4. Martin BB, Wiley-Exley E, Richards S, Domino M, Carey T, Sleath B. Contrasting measures of adherence with simple drug use, medication switching, and therapeutic duplication. Ann Pharmacother. 2009; 43(1):36-44.
5. Metropolis N, Rosenbluth A, Rosenbluth M, Teller A, Teller E. Equation of state calculations by fast computing machines. J of Chemical Physics. 1953;21(6):1087-1092. http://www.aliquote.org/pub/metropolis-et-al-1953.pdf.
6. Jaynes ET. Probability Theory: The Logic of Science. New York, NY: Cambridge University Press; 2003.
7. McAna J, Crawford A, Novinger B, et al. A predictive model of hospitalization risk among disabled Medicaid enrollees. Am J Manag Care. 2013;19(5):e166-e174.
8. Target big data to gain access to future strategic leaders. Gartner Market Analysis website. http://www.gartner.com/id=2219715. Published October 31, 2012.
9. Heidari Z, Hosseinpanah F, Mehrabi Y, Safarkhani M, Azizi F. Predictive power of the components of metabolic syndrome in its development: a 6.5-year follow-up in the Tehran Lipid and Glucose Study (TLGS). Eur J Clin Nutr. 2010;64(10):1207-1214.
10. Goodpaster BH, DeLany JP, Otto A, Kuller L et al. The effects of aerobic, resistance, and combined exercise on metabolic control, inflammatory markers, adipocytokines, and muscle insulin signaling in patients with type 2 diabetes. Metabolism. 2011;60(9):1244-1252.