eCQM Title

Preventive Care and Screening: Body Mass Index (BMI) Screening and Follow-Up Plan

eCQM Identifier (Measure Authoring Tool) 69 eCQM Version number 8.2.000
NQF Number 0421e GUID 9a031bb8-3d9b-11e1-8634-00237d5bf174
Measurement Period January 1, 20XX through December 31, 20XX
Measure Steward Centers for Medicare & Medicaid Services (CMS)
Measure Developer Quality Insights
Endorsed By National Quality Forum
Percentage of patients aged 18 years and older with a BMI documented during the current encounter or during the previous twelve months AND with a BMI outside of normal parameters, a follow-up plan is documented during the encounter or during the previous twelve months of the current encounter  

Normal Parameters:       Age 18 years and older BMI => 18.5 and < 25 kg/m2
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CPT(R) contained in the Measure specifications is copyright 2007-2018 American Medical Association. LOINC(R) copyright 2004-2018 Regenstrief Institute, Inc. This material contains SNOMED Clinical Terms(R) (SNOMED CT[R]) copyright 2004-2018 International Health Terminology Standards Development Organisation. All Rights Reserved.
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Measure Scoring Proportion
Measure Type Process
Risk Adjustment
Rate Aggregation
BMI Above Normal Parameters

Obesity is a chronic, multifactorial disease with complex psychological, environmental (social and cultural), genetic, physiologic, metabolic and behavioral causes and consequences. The prevalence of overweight and obese people is increasing worldwide at an alarming rate in both developing and developed countries. Environmental and behavioral changes brought about by economic development, modernization and urbanization have been linked to the rise in global obesity. The health consequences are becoming apparent (Fitch, 2013).

Hales et al. (2017), report that the prevalence of obesity among adults and youth in the United States was 39.8% and 18.5% respectively, from 2015-2016. They note that obesity prevalence was higher among adults in the 40-59 age bracket than those in the 20-39 age bracket, for both men and women. Hales et al. (2017) also disaggregated the data according to ethnicity and noted that obesity prevalence was higher among non-Hispanic black and Hispanic adults and youth when compared with other races ethnicities. While obesity prevalence was lower among non-Hispanic Asian men and women, obesity prevalence among men, was comparable between non-Hispanic black and non-Hispanic white men. Obesity prevalence was higher among Hispanic men compared with non-Hispanic black men. While the prevalence among non-Hispanic black and Hispanic women was comparable, the prevalence for both groups was higher than that of non-Hispanic white women. Most notably, Hales et al. (2017), report that the prevalence of obesity in the United States remains higher than the Healthy People 2020 goals of 14.5% among youth and 30.5% among adults.

More than a third of U.S. adults have a body mass index [BMI] >= 30 kg/m2; substantially at increased risk for diabetes and cardiovascular disease (CVD) (Flegal et al., 2012; Ogden et al., 2014). Behavioral weight management treatment has been identified as an effective first-line treatment for obesity with an average initial weight loss of eight to ten percent. This percentage weight loss is associated with a significant risk reduction for diabetes and CVD (Wadden, Butryn & Wilson, 2007). Despite the availability of effective interventions, two-thirds of obese U.S. patients were not offered or referred to weight management treatment during their primary care visit between 2005 and 2006, (Ma et al., 2009). In addition, the rate of weight management counseling in primary care significantly decreased by ten percent (40% to 30%) between 1995-1996 and 2007-2008 (Kraschnewski et al., 2013). This suggests that the availability of evidence based clinical guidelines since 2008 obesity management in primary care remains suboptimal (Fitzpatrick & Stevens, 2017).

BMI continues to be a common and reasonably reliable measurement to identify overweight and obese adults who may be at an increased risk for future morbidity. Although good quality evidence supports obtaining a BMI, it is important to recognize it is not a perfect measurement. BMI is not a direct measure of adiposity and as a consequence it can over or underestimate adiposity. BMI is a derived value that correlates well with total body fat and markers of secondary complications, e.g., hypertension and dyslipidemia (Barlow & the Expert Committee, 2007).

In contrast with waist circumference, BMI and its associated disease and mortality risk appear to vary among ethnic subgroups. Female African American populations appear to have the lowest mortality risk at a BMI of 26.2-28.5 kg/m2 and 27.1-30.2 kg/m2 for women and men, respectively. In contrast, Asian populations may experience lowest mortality rates starting at a BMI of 23 to 24 kg/m2. The correlation between BMI and diabetes risk also varies by ethnicity (LeBlanc et al., 2011, pp. 2-3).    

Screening for BMI and follow-up therefore is critical to closing this gap and contributes to quality goals of population health and cost reduction. However, due to concerns for other underlying conditions (such as bone health) or nutrition related deficiencies providers are cautioned to use clinical judgment and take these into account when considering weight management programs for overweight patients, especially the elderly (National Heart, Lung, and Blood Institute [NHLBI] Obesity Education Initiative, 1998, p. 91).

It is important to enhance beneficiary access to all existing providers of Intensive Behavioral Therapy for obesity (IBT) which would result in decreased healthcare costs and lower obesity rates. Dietary counseling performed by a Registered Dietitian Nutritionist (RDN) is more effective than by a primary care clinician. IBT provided by RDNs for 6-12 months shows significant mean weight loss of up to 10% of body weight, maintained over one year’s time (Raynor & Champagne, 2016). 

BMI below Normal Parameters 

On the other end of the body weight spectrum is underweight (BMI <18.5 kg/m2), which is equally detrimental to population health. When compared to normal weight individuals (BMI 18.5-25 kg/m2), underweight individuals have significantly higher death rates with a Hazard Ratio of 2.27 and 95% confidence intervals (CI) = 1.78, 2.90 (Borrell & Lalitha, 2014). 

Poor nutrition or underlying health conditions can result in underweight (Fryar & Ogden, 2012). The National Health and Nutrition Examination Survey (NHANES) results from the 2007-2010 indicate that women are more likely to be underweight than men. Therefore patients should be equally screened for underweight and followed up with nutritional counselling to reduce mortality and morbidity associated with underweight.
Clinical Recommendation Statement
All adults should be screened annually using a BMI measurement. BMI measurements >=25kg/m2 should be used to initiate further evaluation of overweight or obesity after taking into account age, gender, ethnicity, fluid status, and muscularity; therefore, clinical evaluation and judgment must be used when BMI is employed as the anthropometric indicator of excess adiposity, particularly in athletes and those with sarcopenia (Garvey, et al., 2016 AACE/ACE Guidelines, 2016, pp. 12-13) (Grade A).

Overweight and Underweight Categories:
Underweight <18.5; Normal weight 18.5-24.9; Overweight 25-29.9; Obese class I 30-34.9; Obese class II 35-39.9; Obese class III >=40 (Garvey, et al., 2016 AACE/ACE Guidelines, 2016, p. 15).

When evaluating patients for adiposity related disease risk, waist circumference should be measured in all patients with BMI <35 kg/m2 (Garvey, et. al., 2016 AACE/ACE Guidelines, 2016, p. 13) (Grade A).

BMI cutoff point value of >= 23 kg/m2 should be used in the screening and confirmation of excess adiposity in Asian adults (Garvey, et al., 2016 AACE/ACE Guidelines, 2016, p. 13) (Grade B).  

In the United States the waist circumference cutoff points that can be used to indicate increased risk are >=102 cm (>40 inches) for men and >=88 cm (>35 inches) for women (Garvey, et al., 2016 AACE/ACE Guidelines, 2016, p. 13) (Grade A).

Lifestyle/Behavioral Therapy for Overweight and Obesity should include behavioral interventions that enhance adherence to prescriptions for a reduced-calorie meal plan and increased physical activity (behavioral interventions can include: self-monitoring of weight, food intake, and physical activity; clear and reasonable goal-setting; education pertaining to obesity, nutrition, and physical activity; face-to-face and group meetings; stimulus control; systematic approaches for problem solving; stress reduction; cognitive restructuring [i.e., cognitive behavioral therapy], motivational interviewing; behavioral contracting; psychological counseling; and mobilization of social support structures) (Garvey, et al., 2016 AACE/ACE Guidelines, 2016, p. 22) (Grade A).

Behavioral lifestyle intervention should be tailored to a patient's ethnic, cultural, socioeconomic, and educational background (Garvey, et al., 2016 AACE/ACE Guidelines, 2016, p. 22) (Grade B).

USPSTF Clinical Guideline (Grade B Recommendation)
The USPSTF recommends that clinicians offer or refer adults with a body mass index (BMI) of 30 kg/m2 or higher  to intensive, multicomponent behavioral interventions

- Effective intensive behavioral interventions were designed to help participants achieve or maintain a >= 5% weight loss through a combination of dietary changes and increased physical activity
- Most interventions lasted for 1 to 2 years, and the majority had >= 12 sessions in the first year 
- Most behavioral interventions focused on problem solving to identify barriers, self-monitoring of weight, peer support, and relapse prevention
- Interventions also provided tools to support weight loss or weight loss maintenance (e.g., pedometers, food scales, or exercise videos) (USPSTF, 2018a)

The USPSTF recommends screening for abnormal blood glucose levels as part of cardiovascular risk assessment in adults aged 40 to 70 years who are overweight or have obesity. Patients with certain risk factors (family history of diabetes, personal history of gestational diabetes or polycystic ovarian syndrome, or being a member of certain racial/ethnic groups [African American, American Indian or Alaskan Native, Asian American, Hispanic or Latino, or Native Hawaiian or Pacific Islander]) may also be at increased risk of diabetes at a younger age or at a lower BMI and should be considered for screening (USPSTF, 2018b). 

Nutritional safety for the elderly should be considered when recommending weight reduction. "A clinical decision to forego obesity treatment in older adults should be guided by an evaluation of the potential benefits of weight reduction for day-to-day functioning and reduction of the risk of future cardiovascular events, as well as the patient's motivation for weight reduction. Care must be taken to ensure that any weight reduction program minimizes the likelihood of adverse effects on bone health or other aspects of nutritional status" (NHLBI Obesity Education Initiative, 1998, p. 91) (Evidence Category D). In addition, weight reduction prescriptions in older persons should be accompanied by proper nutritional counseling and regular body weight monitoring (NHLBI Obesity Education Initiative, 1998, p. 91).

The possibility that a standard approach to weight loss will work differently in diverse patient populations must be considered when setting expectations about treatment outcomes (NHLBI Obesity Education Initiative, 1998, p. 97) (Evidence Category B).
Improvement Notation
Higher score indicates better quality
Barlow, S. E., & the Expert Committee. (2007). Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: Summary report. Pediatrics, 120(Suppl. 4), S164-S192.
Borrell, L. N., & Samuel, L. (2014). Body mass index categories and mortality risk in U.S. adults: The effect of overweight and obesity on advancing death. American Journal of Public Health, 104(3), 512-519.
Centers for Disease Control and Prevention (CDC). (2012). National Health and Nutrition Examination Survey (NHANES). Prevalence of underweight among adults aged 20 and over:
United States, 1960–1962 Through 2011–2012. Retrieved from
Diehr, P., O’Meara, E. S., Fitzpatrick A., et al. (2008). Weight, mortality, years of healthy life, and active life expectancy in older adults. Journal of the American Geriatrics Society, 56(1), 76-83.
Donini, L. M., Savina, C., Gennaro, E., et al. (2012). A systematic review of the literature concerning the relationship between obesity and mortality in the elderly. The Journal of Nutrition, Health & Aging, 16(1), 89-98.
Flegal, K. M., Carroll, M. D., Kit, B. K., & Ogden, C. L. (2012). Prevalence of obesity and trends in the distribution of body mass index among U. S. adults, 1999-2010. JAMA, 307(5), 491-497.
Fitch, A., Everling, L., Fox, C., et al. (2013, May). Prevention and management of obesity for adults. Bloomington, MN: Institute for Clinical Systems Improvement. 
Fitzpatrick, S. L., & Stevens, V. J. (2017, June 1). Adult obesity management in primary care, 2008-2013. Preventive Medicine, 99, 128-133. Retrieved from
Fryar, C. D., & Ogden, C. L. (2012). Prevalence of underweight among adults aged 20 and over: United States, 1960-1962 through 2007-2010. Hyattsville, MD: NCHS, Division of Health and Nutrition Examination Surveys. Retrieved from
Garvey, W. T., Mechanick, J. I., Brett, E. M., et al. (2016, January 1). American Association of Clinical Endocrinologists and American College of Endocrinology comprehensive clinical practice guidelines for medical care of patients with obesity. Endocrine Practice, 22(Suppl. 3), pp. 1-203.
Hales, C. M., Carroll, M. D., Fryar, C. D., et al. (2017, October). Prevalence of obesity among adults and youth: United States, 2015-2016. NCHS Data Brief No. 288. Retrieved from
Holme, I., & Tonstad, S. (2015). Survival in elderly men in relation to midlife and current BMI. Age and Ageing, 44(3), 434-439. 
LeBlanc, E., O’Connor, E., Whitlock, E. P., et al. (2011). Screening for and management of obesity and overweight in adults (Evidence Report No. 89; AHRQ Publication No. 11-05159-EF-1). Rockville, MD: Agency for Healthcare Research and Quality. 
Kraschnewski, J. L., Sciamanna, C. N, Stuckey, H. L., et al. (2013, February). A silent response to the obesity epidemic: Decline in US physician weight counseling, 51 (2). Retrieved from
NHLBI Obesity Education Initiative. (1998). Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults (Report No. 98-4083). Bethesda, MD: NHLBI.
Ogden CL, Carroll MD, Fryar CD, Flegal KM. Prevalence of obesity among adults and youth: United States, 2011–2014. NCHS data brief, no 219. Hyattsville, MD: National Center for Health Statistics. 2015. Retrieved from
Raynor, H. A., & Champagne, C. M. (2016). Position of the Academy of Nutrition and Dietetics: Interventions for the treatment of overweight and obesity in adults. Journal of the Academy of Nutrition and Dietetics, 116(1), 129-147.
U.S. Preventive Services Task Force. (2018 a). Behavioral weight loss interventions to prevent obesity-related morbidity and mortality in adults: U.S. Preventive Services Task Force recommendation statement. JAMA, 320(11), 1163–1171. doi:10.1001/jama.2018.13022
U.S. Preventive Services Task Force. (2018b). Final recommendation statement: Weight loss to prevent obesity-related morbidity and mortality in adults: Behavioral interventions. Retrieved from
Wadden, T. A, Butryn, M. L., Wilson, C. (2007). Lifestyle modification for the management of obesity, 132 (6), 2226-2238.
BMI- Body mass index (BMI) is a number calculated using the Quetelet index: weight divided by height squared (W/H2) and is commonly used to classify weight categories. BMI can be calculated using:

Metric Units:  BMI = Weight (kg) / (Height (m) x Height (m))    
English Units: BMI = Weight (lbs.) / (Height (in) x Height (in)) x 703

Follow-Up Plan - Proposed outline of treatment to be conducted as a result of a BMI out of normal parameters. A follow-up plan may include, but is not limited to: documentation of education, referral (for example a Registered Dietitian Nutritionist (RDN), occupational therapist, physical therapist, primary care provider, exercise physiologist, mental health professional, or surgeon) for lifestyle/behavioral therapy, pharmacological interventions, dietary supplements, exercise counseling and/or nutrition counseling
*  There is no diagnosis associated with this measure.
*  This measure is to be reported a minimum of once per reporting period for patients seen during the reporting period. 
*  This measure may be reported by eligible professionals who perform the quality actions described in the measure based on the services provided at the time of the qualifying visit and the measure-specific denominator coding. 

BMI Measurement Guidance:
*  Height and Weight - An eligible professional or their staff is required to measure both height and weight. Both height and weight must be measured within twelve months of the current encounter and may be obtained from separate encounters.  Self-reported values cannot be used.
*  The BMI may be documented in the medical record of the provider or in outside medical records obtained by the provider. 
*  If the most recent documented BMI is outside of normal parameters, then a follow-up plan is documented during the encounter or during the previous twelve months of the current encounter. 
* If more than one BMI is reported during the measurement period, the most recent BMI will be used to determine if the performance has been met.
* Review the exclusions and exceptions criteria to determine those patients that BMI measurement may not be appropriate or necessary. 

Follow-Up Plan Guidance: 

 * The documented follow-up plan must be based on the most recent documented BMI, outside of normal parameters, example: "Patient referred to nutrition counseling for BMI above or below normal parameters."

(See Definitions for examples of follow-up plan treatments).

Variation has been noted in studies exploring optimal BMI ranges for the elderly (see Donini et al., [2012]; Holme & Tonstad [2015]; Diehr et al. [2008]). Notably however, all these studies have arrived at ranges that differ from the standard range for ages 18 and older, which is >=18.5 and < 25 kg/m2. For instance, both Donini et al. (2012) and Holme and Tonstad (2015) reported findings that suggest that higher BMI (higher than the upper end of 25kg/m2) in the elderly may be beneficial. Similarly, worse outcomes have been associated with being underweight (at a threshold higher than 18.5 kg/m2) at age 65 (Diehr et al. 2008). Because of optimal BMI range variation recommendations from these studies, no specific optimal BMI range for the elderly is used. However, it may be appropriate to exempt certain patients from a follow-up plan by applying the exception criteria. Review the following to apply the Medical Reason exception criteria: 
The Medical Reason exception could include, but is not limited to, the following patients as deemed appropriate by the health care provider: 
* Elderly patients (65 or older) for whom weight reduction/weight gain would complicate other underlying health conditions such as the following examples:
    * Illness or physical disability
    * Mental illness, dementia, confusion
    * Nutritional deficiency such as Vitamin/mineral deficiency 
* Patients in an urgent or emergent medical situation where time is of the essence and to delay treatment would jeopardize the patient's health status
Transmission Format
Initial Population
All patients 18 and older on the date of the encounter with at least one eligible encounter during the measurement period
Equals Initial Population
Denominator Exclusions
Patients who are pregnant 
Patients receiving palliative or hospice care
Patients who refuse measurement of height and/or weight
Patients with a documented BMI during the encounter or during the previous twelve months, AND when the BMI is outside of normal parameters, a follow-up plan is documented during the encounter or during the previous twelve months of the current encounter
Numerator Exclusions
Not Applicable
Denominator Exceptions
Patients with a documented Medical Reason

Patients in an urgent or emergent medical situation where time is of the essence and to delay treatment would jeopardize the patient's health status
Supplemental Data Elements
For every patient evaluated by this measure also identify payer, race, ethnicity and sex

Table of Contents

Population Criteria




Data Criteria (QDM Data Elements)

Supplemental Data Elements

Risk Adjustment Variables

Measure Set