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Ten Most Expensive Diseases

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The Ten Most Expensive Diseases

The list of the 10 most expensive diseases includes:

  1. Heart conditions $76 billion
  2. Trauma disorders $72 billion
  3. Cancer $70 billion
  4. Mental disorders, including depression $56.0 billion
  5. Asthma and chronic obstructive pulmonary disease $54 billion
  6. High blood pressure $42 billion
  7. Type 2 diabetes $34 billion
  8. Osteoarthritis and other joint diseases $34 billion
  9. Back problems $32 billion
  10. Normal childbirth $32 billion

How Are They Affected

  1. Cardiovascular Disease (Heart Conditions) can best be impacted by treating
    • Diabetes mellitus
    • Hypertension
    • Hypercholesterolemia
    • Obesity
    • Smoking
    • Chronic Kidney Disease
  2. Trauma Disorders is best treated by Seat Belt Usage
  3. Cancer - the physical exams are cancer screening tests as are
    • prostate checks
    • pap and pelvic
    • breast checks
    • mammogram
    • colonoscopy after the age of 50. Early detection is the most critical element.
  4. Asthma - COPD
  5. Heart Failure - Heart Failure accounts for 15% of the Cardiovascular Disease total. Aggressive outpatient management is key.
  6. Osteoarthritis and Back pain are best affected by controlling weight.

Recommended Reporting measures

Because we are trying to affect the most prevalent and most expensive diseases, these conditions will be most likely the ones that will be required:

Measure #1: Hemoglobin A1c Poor Control in Type 1 or 2 Diabetes Mellitus Patient data (age and diagnosis) can be pulled from existing tables. A1c greater than 9.0% result can be pulled from procedure_results table that is addressed in Lab Results Display MU. Measure #64: Asthma Assessment Build an assessment form similar to the one found here: Add a clinical alert to inform the providers to do the evaluation.

Measure #110: Influenza Vaccination for Patients _ 50 Years Old The data can be pulled from procedure_order table using age filter.

Measure #112: Screening Mammography The data can be pulled from procedure_result table. The provider is required to sign off the result and put a review date on it.

Measure #115: Advising Smokers to Quit The data can be pulled from clinical_alerts table. This is already a part of Clinical Decision Support MU. For any current smokers, an alert will be created. The provider will respond to the alert and offers smoking cessation health plan to the patient. Both response and advice are tracked. Two G codes must be documented (G8455: Current tobacco smoker AND G8402: Tobacco (smoke) use cessation intervention, counseling).

  1. Diabetes mellitus
    • A1c
  2. Hypertension
    • Systolic BP
    • Diastolic BP
    • Mean Arterial pressure = (2*SysBP + DiasBP)/3
  3. Hypercholesterolemia
    • Total cholesterol
    • Triglycerides
    • HDL cholesterol
    • LDL Cholesterol
    • Non-HDL Cholesterol (Total cholesterol - HDL Cholesterol)
  4. Obesity
    • Height
    • Weight
    • BMI
  5. Smoking
    • Cessation counseling
  6. Chronic Kidney Disease
    • Creatinine clearance - algorithm based on
      • age
      • sex (women multiply by 0.8)
      • weight
      • race (African Americans multiply by 1.2)
      • last creatinine
  7. Seat Belt Usage
  8. Cancer -
    • General physical exam
      • Male prostate checks
    • Female
      • pap and pelvic
      • breast checks
      • mammogram
    • Colonoscopy after the age of 50
  9. Asthma - COPD
  10. Heart Failure
    • Most recent Ejection Fraction
    • ACE inhibitor usage ( or ARB)
    • Beta blocker usage


Samuel T. Bowen, MD