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Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. DISCLOSURE
  8. References

Obesity is becoming an increasingly prevalent problem among American children. Screening for obesity associated comorbid conditions has been shown to be inconsistent. The current study was undertaken to explore patterns of ordering screening tests among obese pediatric patients. We analyzed electronic medical records (EMR) from 69,901 patients ages 2–18 years between June 1999 and December 2008. Obese children who had documented diagnoses of obesity were identified based on International Classification of Diseases, Ninth Revision codes. Screening rates for glucose, liver, and lipid abnormalities were assessed. Regression analysis was used to examine impact of patient characteristics and temporal trends were analyzed. Of the 9,251 obese diagnosed patients identified, 22% were screened for all three included obesity-related conditions: diabetes, liver, and lipid abnormalities; 52% were screened for glucose abnormalities; 30% for liver abnormalities; and 41% for lipid abnormalities. Increasing BMI and age were associated with increased rates of screening. Females and Hispanic patients were more likely to be screened. The majority of screening was ordered under “basic metabolic panel,” “hepatic function panel,” and “full lipid profile” for each respective condition. The percentages of patients screened generally increased over time, although the percentages screened for diabetes and lipid abnormalities seemed to plateau or decrease after 2004. Even after diagnosis, many obese patients are not receiving recommended laboratory screening tests. Screening increased during the study period, but remains less than ideal. Providers could improve care by more complete laboratory screening in patients diagnosed with obesity.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. DISCLOSURE
  8. References

Overweight and obesity are common problems among American youth. The prevalence of obesity in American youth has increased from near 5% in the 1960s to 17% in 2004 (1). In 2007–2008, 31.7% of children were at or above the 85% for BMI (2). Obesity affects children's health on many levels including increased blood pressure (3), atherosclerosis (4,5), sleep apnea (6), asthma (7), type 2 diabetes (8), constipation (9), and orthopedic complications (10). Rates of death during follow-up of pediatric patients over an average 23-year period has recently been shown to be significantly higher among children in the highest quartile of BMI when compared to children in the lowest BMI quartile (11).

As there are many possible weight-related health conditions that must be considered in the pediatric patient, screening may be complicated. Among the many health conditions associated with obesity, screening for diabetes, liver abnormalities, and dyslipidemia are most commonly addressed in current guidelines. Such screenings are important, as it has been demonstrated that up to 25% of obese children have impaired glucose tolerance and 4% of obese adolescents have silent type 2 diabetes (12). Steatosis identified by ultrasound has been found in 77% of obese Chinese children and elevated alanine aminotransferase has been found in 6.0–11.5% of adolescents (13,14). Also, according to National Health and Nutrition Examination Survey data as many as 42% of obese adolescents have been found to have lipid abnormalities (15).

A 2007 study found that 4% of overweight children had glucose screening and 9% had lipid screening (16). Similarly, in 2005, it was shown that general pediatricians screen for liver abnormalities in only 2% of overweight children (17). Low rates of screening may be attributed to many factors, including perceived futility of intervention, lack of time and reimbursement for pediatric obesity treatment, and perhaps most notably, the void of clear recommendations in the area of screening obese and overweight pediatric patients that existed prior to 2005–2007 (Table 1).

Table 1.  Guidelines for screening for obese and overweight children among selected American organizations
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Recommendations for laboratory screening of children with weight problems have been varied based on the age of onset of screening, the type of screening recommended, and the BMI at which screening should begin. These guidelines are shown in Table 1. In 2007, a revision of the 1998 expert committee recommendations was published with clear guidelines for screening and assessment of overweight and obese pediatric patients (18). According to these guidelines, overweight children with BMI ≥85th percentile but <95th percentile should have lipid panel testing and, if risk factors are present, should also have fasting glucose and aspartate aminotransferase/alanine aminotransferase levels measured every 2 years if age 10 years or older. Risk factors mentioned are parental obesity, family medical history, current lifestyle habits, BMI trajectory, and current cardiovascular risk factors; however, clinicians are encouraged to use their clinical judgment in assessing risk. For those obese children with BMI ≥95th percentile, fasting glucose and aspartate aminotransferase/alanine aminotransferase should be measured every 2 years if age 10 or older, and should have a fasting lipid panel tested once (18).

The current study was undertaken to evaluate the common practices of pediatric providers in the laboratory evaluation of overweight and obese patients over the period of 1999–2008 and to assess how laboratory evaluation has compared to the recommended guidelines over this period.

Methods and Procedures

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. DISCLOSURE
  8. References

Study design and data collection

This was a retrospective cohort study of patients ages 2 through 18 with at least one outpatient visit including a recorded height and weight between June 1999 and December 2008 within the MetroHealth System, a large tertiary academic health-care system in northeast Ohio (N = 69,901 patients with 314,184 visits).

The MetroHealth System has used the EpicCare (Epic Systems Corporation, Madison, Wisconsin) electronic medical record (EMR) in outpatient clinics since 1999. We used information gathered at visits including age, race/ethnicity, sex, weight, and height. Race was recorded by asking patients what race/ethnicity they identify themselves with. Height and weight measurements were taken by nurses or medically trained assistants using standardized clinical procedures and medical scales/stadiometers. Recorded heights ≤30.5 cm or ≥243.4 cm were considered to be entered erroneously. Similarly, weights ≤1.5 kg or ≥300 kg were not included. Similar criteria have been used previously and eliminated <1% of visits from our initial cohort (19).

Age- and sex-specific percentiles for BMI were determined using the most recent growth charts from the Centers for Disease Control and Prevention (20). Obesity was defined as a BMI ≥30 kg/m2 or the 95th percentile. We only examined laboratory screening for obese children (6) (as opposed to overweight children) as guidelines have been more consistent for this group. Among obese children, those with documented diagnoses were identified based on International Classification of Diseases, Ninth Revision codes entered for past medical history, visit diagnoses, and problem lists for all patient visits. International Classification of Diseases, Ninth Revision codes included were obesity, not otherwise specified (278.00); morbid obesity (278.01); dysmetabolic syndrome (277.7); overweight (278.02); and weight gain, abnormal (783.1). For this analysis, we focused only on obese patients with documented diagnoses based on these codes, because in this group we could accurately assess providers' compliance with obesity-related guidelines after these patients were correctly identified as being obese.

Laboratory screening tests were identified within orders entered in the EMR. Within the MetroHealth System all orders for outpatient visits are entered in the EMR—paper orders are not used. Orders were searched for any order that may have been used to screen patients for diabetes, liver abnormalities, and dyslipidemias. For diabetes screening, orders included were “fingerstick/glucose,” “glucose,” “glucose tolerance test, 2-h,” “glucose, 2-h postparandial,” “glucose, fasting,” “glucose, fingerstick in office,” “insulin,” “glucose, whole blood,” “basic metabolic panel,” and “hemoglobin A1C.” Screening for liver abnormalities included “hepatic function panel,” “alanine aminotransferase,” and “aspartate aminotransferase.” For dyslipidemia screening, “cholesterol,” “full lipid profile,” “HDL,” “LDL cholesterol, direct,” and “triglycerides” were used. Although some of these would not be the most clearly recommended tests for initial screening, they were all included in order to provide the most comprehensive record of screening for obesity-related conditions. We focused on orders rather than laboratory results, as ordering is under the control of providers, while whether the lab is actually drawn is reliant on factors that may be outside of the providers' control. This study was approved by the MetroHealth System institutional review board.

Statistical analysis

Based on the above definitions, we first calculated the percentages of patients who received each of the three types of laboratory screening. A patient was considered to be screened for diabetes, liver abnormalities, and dyslipidemia if relevant orders (discussed above) were entered at any point during the study period. The percentage of patients who received screening for all three obesity-related conditions was also calculated. Children aged 10 or older were also considered as a subset of the larger cohort, as the most recent guidelines specify screening for all obese patients in this age category as opposed to only those with risk factors (18).

Multiple logistic regression models were used to compute odds ratios and 95% confidence intervals for associations between patient characteristics and screening for all three obesity-associated conditions among diagnosed patients. Factors in the multivariate models included BMI and height percentiles, age, gender, ethnicity, and number of visits in which the patient was obese. For factors that changed over the study period (e.g., age), information from the first obese visit was used. To examine temporal trends, the percentages of diagnosed patients who were screened for obesity-related conditions within each year from 1999 to 2008 were calculated. For these calculations, only previously unscreened patients with a visit during the specified year were used. Generalized estimating equations for logistic regression with the autoregressive correlation structure were used to examine the association between year and screening, adjusting for demographic changes in the population over time and accounting for repeated visits by the same patient (21). Year was modeled as a continuous variable to examine the significance of trends in screening over the entire study period, from 1999 to 2008. In addition, in secondary analyses, indicator variables were used to compare rates of screening for individual years to one another.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. DISCLOSURE
  8. References

Among the 69,901 eligible patients, 18,232 (26.0%) were found to be obese for at least one visit during the study period, and 9,251 of these obese patients (50.7%) had a documented diagnosis. These obese patients with documented obesity diagnoses had a total of 47,180 visits during study period (mean number of visits per patient = 5.1). Well child visits (based on CPT codes) consist of 60.1% of the visits. Visits to pediatric specialists based on coding for clinic location accounted for 10.5% of the visits. Obstetrics and gynecology accounted for another 1.0% of visits, and nutritionists accounted for another 1.0% of visits. The majority of the rest of the visit were to general pediatric providers for non-well child care visits. Patient demographic characteristics are shown in Table 2.

Table 2.  Demographic information of study patients
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Among obese diagnosed patients, 2,042 (22.1%) were screened for all three areas: diabetes, liver abnormalities, and dyslipidemias. Of obese patients who were diagnosed, 4,803 (51.9%) were screened for diabetes, 2,726 (29.5%) were screened for liver function abnormalities, and 3,780 (40.9%) were screened for dyslipidemia during the study period. Among obese patients aged 10 or older (N = 6,625), 3,968 (59.9%) had screening for diabetes, 2,330 (35.2%) had screening for abnormal liver function, and 3,324 (50.1%) had screening for dyslipidemia.

Multiple logistic regression analyses among the obese diagnosed patients demonstrated that males were less likely than females to be screened for all three obesity-related conditions (Table 3). Hispanic patients were more likely to be screened than non-Hispanic, nonwhite patients (who were predominantly African-American). Increasing BMI and increasing age were associated with increased rates of screening (odds ratios 1.05 and 1.07 for each increased percentile and year of age, respectively). The number of visits per study year in which the patient qualified as obese and the height of the patients did not affect screening rates. Logistic regression analyses for the associations of patient characteristics with each individual screening test also were performed and generally produced similar results (Table 3).

Table 3.  Multivariate OR (95% CI) for associations of patient characteristics with screening for obesity-related conditions among diagnosed obese patients
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Of the orders that qualified for screening for diabetes among diagnosed obese patients, 41.4% were “basic metabolic panel.” Of the orders that qualified for screening for liver abnormalities among obese patients, 80.5% were “hepatic function panel,” and of the orders that qualified for screening for dyslipidemia, 59.6% were “full lipid profile.” See Table 4 for complete list of the percentages of various screening tests ordered.

Table 4.  Tests ordered for diabetes screening, liver abnormalities, and lipid abnormalities
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There was a statistically significant increase in screening for all three obesity-related conditions over the entire study period (P < 0.001), although the percentages of patients who were screened seemed to plateau or decrease slightly later in the study period (Figure 1). Diabetes screening increased during the study period from 7.2% in 1999 to a peak of 22.3% in 2004; after 2004, however, diabetes screening decreased to 15.6% in 2008, which was statistically significant (P = 0.001 for 2004 vs. 2008). Liver screening increased from 2.4% of patients in 1999 to 13.1% in 2007 and then decreased to 10.9% in 2008, which also was a statistically significant decline (P = 0.001 for 2007 vs. 2008). Screening for dyslipidemia increased from 12.0% in 1999 to a peak of 19.0% in 2004, then decreased significantly to 15.6% in 2008 (P = 0.001 for 2004 vs. 2008).

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Figure 1. Screening for obesity-associated conditions by year among diagnosed obese patients. Obesity is defined as a BMI ≥95th percentile. Screening for obesity-related conditions extracted from order sets for glucose testing, liver function screening, and lipid screening as described in the text.

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. DISCLOSURE
  8. References

The current study was undertaken to explore patterns of screening for obesity-related complications among obese pediatric patients who have been diagnosed. After an obese child is diagnosed with obesity, diagnosis should be followed by an assessment for obesity-related conditions that may require treatment or further intervention. Previous studies have demonstrated that children who are overweight and obese are often not diagnosed (22). In addition, it has been shown that screening among overweight and obese children and adolescents may not take place the majority of the time. A study in 2005 demonstrated that only 2–23% of obese or overweight children had documented screening for fatty liver disease (17). Similarly, 8–34% of such children were screened for high cholesterol or glucose abnormalities (17). Our study confirms this low level of screening among obese patients in a larger cohort. Because our study focuses on whether or not a test was ordered, as opposed to whether or not a test result was received, it helps to isolate the pediatric provider as the primary link in the low screening rates We demonstrated that over 75% of patients are not screened for all three obesity-related conditions. To our knowledge, this is the first study to explore the temporal ordering patterns of physicians and to explore the specific tests being ordered to screen for these three obesity-related conditions.

Orders for each of the tests increased throughout the study period, although screening for diabetes and dyslipidemia seemed to plateau or decrease after 2004. This finding is consistent with results from a previous study in this population, which indicated that diagnosis rates of obesity may have plateaued or decreased following 2005 (22). These data may indicate that there is a need for provider education, more extensive clinical decision support in the EMR, and more active strategies for both the identification of obese children and the screening of obese children following their identification.

Rates of screening were minimally increased for patients who were older and had a higher BMI. These patients are most at risk of remaining obese into adulthood (23) and are therefore most at risk for obesity-conditions at some point in life. The increased screening among this older group may imply that providers do recognize the need for screening in patients who are at the highest risk of comorbid conditions. Female and Hispanic children are more likely to be screened, perhaps because they are at increased risk of complications of obesity such as diabetes (24). Interestingly, the number of obese visits does not increase the chances of screening. This perhaps implies that if a provider is familiar with the screening guidelines, the patient is screened regardless of the number of visits; however, if the provider is unfamiliar with the guidelines or does not agree with them, patients are not screened despite multiple visits.

There are many reasons why children who are obese may not be screened for obesity-related conditions, including the provider not recognizing that the child is obese and not knowing the current guidelines for obese patients or not recognizing the increased risk of comorbid conditions. We have presented data concerning only diagnosed patients, eliminating the possibility that obese patients are not identified and therefore not screened because of lack of recognition of the underlying diagnosis. Lack of knowledge of current guidelines likely contributes to underscreening, as guidelines have varied throughout the study period, beginning with vague recommendations in 1998 to more complete guidelines published in 2005 and 2007 (18,25,26,27). Interestingly, however, screening does not seem to increase following the release of such guidelines. While it is possible that these publications may have a delayed effect, we do not demonstrate increasing screening rates conforming to the release of clear guidelines.

Therefore, one of the primary issues may be the need to better publicize new guidelines. Additionally, even if providers are familiar with the guidelines, screening may be insufficient among obese patients if there is perceived futility among providers of discussing and identifying weight problems in children and adolescents. Providers may see obesity as less important than other conditions, and 77% feel that treating obesity can be “very frustrating” (21). Such treatment is historically not well reimbursed, furthering possible lack of emphasis by many providers. Lastly, providers may feel that screening of all obese children over the age of 10 years is low yield and not cost effective. They may be identifying higher risk patients and screening only those individuals. Guidelines for universal screening of obese children over 10 years of age may therefore lead to lower screening compliance rates while those of highest risks are still being screened.

Limitations of our study include the fact that our population represents a single center, and, while our sample size is large, our population may not be representative of other regions. Other limitations include the reliance on EMR data. Order data from the EMR, however, is guaranteed to be complete as there is no other means of ordering laboratory tests within the MetroHealth System outpatient facilities. We also used International Classification of Diseases, Ninth Revision codes for identifying diagnosed patients. The clinical question that we wished to answer, however, was whether screening for obesity-related conditions occurred among diagnosed obese patients. Therefore, while some patients who were recognized and diagnosed without entering International Classification of Diseases, Ninth Revision codes may not have been included in the analysis, we are assured that all those included were recognized as obese by at least one provider. Several patient factors such as lifestyle habits, insurance status, and family history were not included in the analysis. We have previously investigated the family history documentation within both the designated section of the EMR and also within the text notation sections and have found it to be incomplete and not clinically useful for identification and management of childhood obesity (28). Therefore, family history was not included in this analysis. Lastly, many of the orders included in the analysis may be ordered for reasons other than for work up of obesity, particularly basic metabolic panels and hepatic function panels. If these were ordered for other reasons, this would only serve to overestimate the laboratory screening done for obesity-related conditions and so screening rates would actually be lower then the relatively low rates reported.

Diagnosis of obesity among children and adolescents has been shown to be incomplete. In the current study, we have demonstrated that even among patients who are diagnosed with obesity, the majority of patients still may not have screening tests ordered for obesity-related conditions, based on recommended guidelines. Other means of improving diagnosis and screening should be investigated and considered.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. DISCLOSURE
  8. References
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