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Percent with a Fragility Fracture Filling Prescription for an Osteoporosis Drug within Six Months
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    Region
    (Click a region name
    below to view its profile)
    Percent with a Fragility Fracture Filling Prescription for an Osteoporosis Drug within Six Months
    (Year: 2006-2010; Region Levels: HRR)
    Anchorage, AK na
    Birmingham, AL 17.3%
    Dothan, AL 10.9%
    Huntsville, AL 12.2%
    Mobile, AL 15.3%
    Montgomery, AL 16.0%
    Tuscaloosa, AL na
    Fort Smith, AR 16.2%
    Jonesboro, AR 15.0%
    Little Rock, AR 13.5%
    Springdale, AR 13.7%
    Texarkana, AR 18.7%
    Mesa, AZ 19.0%
    Phoenix, AZ 12.4%
    Sun City, AZ 25.0%
    Tucson, AZ 12.9%
    Alameda County, CA 15.9%
    Bakersfield, CA 11.3%
    Chico, CA 17.2%
    Contra Costa County, CA 14.0%
    Fresno, CA 13.4%
    Los Angeles, CA 18.2%
    Modesto, CA 11.7%
    Napa, CA na
    Orange County, CA 18.2%
    Palm Springs/Rancho Mira, CA na
    Redding, CA 13.3%
    Sacramento, CA 19.8%
    Salinas, CA 15.7%
    San Bernardino, CA 16.8%
    San Diego, CA 15.5%
    San Francisco, CA 16.8%
    San Jose, CA 17.6%
    San Luis Obispo, CA 24.6%
    San Mateo County, CA 13.0%
    Santa Barbara, CA na
    Santa Cruz, CA na
    Santa Rosa, CA na
    Stockton, CA 15.9%
    Ventura, CA 16.7%
    Boulder, CO na
    Colorado Springs, CO 17.9%
    Denver, CO 15.2%
    Fort Collins, CO na
    Grand Junction, CO 22.9%
    Greeley, CO 21.3%
    Pueblo, CO na
    Bridgeport, CT 15.2%
    Hartford, CT 12.8%
    New Haven, CT 9.8%
    Washington, DC 12.4%
    Wilmington, DE 13.2%
    Bradenton, FL 15.5%
    Clearwater, FL 11.8%
    Fort Lauderdale, FL 12.7%
    Fort Myers, FL 15.3%
    Gainesville, FL 14.0%
    Hudson, FL na
    Jacksonville, FL 17.6%
    Lakeland, FL na
    Miami, FL 11.9%
    Ocala, FL 14.8%
    Orlando, FL 15.5%
    Ormond Beach, FL na
    Panama City, FL na
    Pensacola, FL 18.7%
    Sarasota, FL 16.0%
    St. Petersburg, FL 18.2%
    Tallahassee, FL 20.2%
    Tampa, FL 18.1%
    Albany, GA na
    Atlanta, GA 13.2%
    Augusta, GA 15.8%
    Columbus, GA 21.3%
    Macon, GA 12.5%
    Rome, GA na
    Savannah, GA 19.4%
    Honolulu, HI 28.0%
    Cedar Rapids, IA 14.3%
    Davenport, IA 16.1%
    Des Moines, IA 14.6%
    Dubuque, IA na
    Iowa City, IA 13.3%
    Mason City, IA 14.6%
    Sioux City, IA 14.4%
    Waterloo, IA na
    Boise, ID 12.5%
    Idaho Falls, ID na
    Aurora, IL na
    Bloomington, IL na
    Blue Island, IL 12.4%
    Chicago, IL 9.6%
    Elgin, IL 18.2%
    Evanston, IL 14.1%
    Hinsdale, IL 17.2%
    Joliet, IL 13.8%
    Melrose Park, IL 14.1%
    Peoria, IL 9.6%
    Rockford, IL 14.9%
    Springfield, IL 11.5%
    Urbana, IL 14.9%
    Evansville, IN 14.2%
    Fort Wayne, IN 13.8%
    Gary, IN 15.3%
    Indianapolis, IN 17.2%
    Lafayette, IN 24.1%
    Muncie, IN na
    Munster, IN 19.3%
    South Bend, IN 20.6%
    Terre Haute, IN 21.9%
    Topeka, KS 13.8%
    Wichita, KS 16.7%
    Covington, KY 13.1%
    Lexington, KY 11.8%
    Louisville, KY 15.4%
    Owensboro, KY na
    Paducah, KY 13.5%
    Alexandria, LA na
    Baton Rouge, LA 12.2%
    Houma, LA na
    Lafayette, LA 16.4%
    Lake Charles, LA na
    Metairie, LA na
    Monroe, LA 22.4%
    New Orleans, LA na
    Shreveport, LA 18.3%
    Slidell, LA na
    Boston, MA 12.0%
    Springfield, MA 16.3%
    Worcester, MA na
    Baltimore, MD 12.7%
    Salisbury, MD 12.9%
    Takoma Park, MD 16.5%
    Bangor, ME 8.9%
    Portland, ME 10.6%
    Ann Arbor, MI 17.4%
    Dearborn, MI na
    Detroit, MI 9.4%
    Flint, MI na
    Grand Rapids, MI 15.1%
    Kalamazoo, MI 15.2%
    Lansing, MI 20.2%
    Marquette, MI na
    Muskegon, MI na
    Petoskey, MI na
    Pontiac, MI na
    Royal Oak, MI 16.7%
    Saginaw, MI 12.6%
    St. Joseph, MI na
    Traverse City, MI na
    Duluth, MN na
    Minneapolis, MN 12.5%
    Rochester, MN 15.0%
    St. Cloud, MN na
    St. Paul, MN 9.6%
    Cape Girardeau, MO 16.2%
    Columbia, MO 13.4%
    Joplin, MO 17.2%
    Kansas City, MO 14.5%
    Springfield, MO 13.4%
    St. Louis, MO 13.5%
    Gulfport, MS na
    Hattiesburg, MS 13.8%
    Jackson, MS 15.0%
    Meridian, MS na
    Oxford, MS na
    Tupelo, MS 15.1%
    Billings, MT 12.6%
    Great Falls, MT 26.2%
    Missoula, MT 17.5%
    Durham, NC 13.9%
    Greenville, NC 13.9%
    Hickory, NC 15.6%
    Raleigh, NC 13.6%
    Wilmington, NC 16.0%
    Winston-Salem, NC 13.7%
    Lincoln, NE 12.2%
    Omaha, NE 15.0%
    Lebanon, NH 10.1%
    Manchester, NH 15.9%
    Camden, NJ 12.0%
    Hackensack, NJ 11.4%
    Morristown, NJ 12.9%
    New Brunswick, NJ 10.2%
    Newark, NJ 6.8%
    Paterson, NJ na
    Ridgewood, NJ 17.0%
    Albuquerque, NM 15.2%
    Las Vegas, NV 15.6%
    Reno, NV 17.7%
    Albany, NY 14.0%
    Binghamton, NY 17.9%
    Bronx, NY 15.6%
    Buffalo, NY 18.3%
    East Long Island, NY 16.0%
    Elmira, NY na
    Manhattan, NY 15.1%
    Rochester, NY 9.9%
    Syracuse, NY 15.3%
    White Plains, NY 12.1%
    National Average 14.3%
    90th Percentile 19.3%
    50th Percentile 14.5%
    10th Percentile 11.2%
        • DENOMINATOR DEFINITION:
        • Patients were included in the fragility fracture cohort if they (1) experienced a fracture of the hip, distal forearm or humerus between 5/1/2006 and 12/31/2009, (2) were continuously enrolled in fee-for-service Medicare Parts A and B for at least 36 months preceding the index fracture and at least 12 months following the fracture, (3) were alive and continuously enrolled in and used (one or more fill record) a stand-alone Medicare Part D plan for at least 6 months following the fracture, (4) did not have an identically-defined fragility fracture in the 36 months preceding the index fracture, (5) were predominantly community dwelling (not hospitalized for more than 90 days and had no prescriptions filled by a long-term care pharmacy type) in the first 6 months following index fracture, (6) had no cancer diagnosis (other than non-melanoma skin cancer), hospice enrollment, or managed Medicare enrollment at any time in claims records analyzed.

        • NUMERATOR DEFINITION:
        • All medication use measures were based on Part D event fill records for the time frame specific to each cohort’s observation. The Lexi-Data Basic database (Lexicomp) was used to obtain the drug name, dose, brand or generic status, and active ingredient according to the National Drug Code (NDC).




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