|Year : 2020 | Volume
| Issue : 2 | Page : 103-109
Determining the rate of obesity documentation in a division of general internal medicine at a tertiary care medical center
Salma Iftikhar1, Jithinraj Edakkanambeth Varayil2, Ryan T Hurt3, Matthew S Salerno1, Paul S Mueller1
1 Division of General Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA
2 Division of General Internal Medicine, Mayo Clinic, Rochester, Minnesota; Department of Family Medicine, University of Illinois College of Medicine Rockford, Rockford, Illinois, USA
3 Division of General Internal Medicine; Division of Gastroenterology and Hepatology; Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, Minnesota, USA
|Date of Submission||24-Jan-2020|
|Date of Acceptance||20-Mar-2020|
|Date of Web Publication||29-Jun-2020|
Dr. Salma Iftikhar
Division of General Internal Medicine, Mayo Clinic, 200 First St SW, Rochester, Minnesota 55905
Source of Support: None, Conflict of Interest: None
Background: Obesity is a leading cause of preventable deaths in the United States, likely second only to tobacco-related diseases. However, studies have shown that the formal diagnosis rate is low, at 19.9%. Furthermore, of the patients with a diagnosis of obesity, only 22.6% receive a treatment plan.
Objective: The objective was to determine rates of identification and diagnosis of obesity and referral for counseling in an ambulatory general internal medicine practice.
Design: The electronic health records (EHR)of patients seen and examined for a 6-month period were searched for obesity-related terms (ORTs) which included: obese, overweight, weight-related issues, and elevated body mass index (BMI).
Patients: All patients with a documented BMI of more than 30 kg/m2 who underwent a medical examination in the Division of General Internal Medicine at Mayo Clinic in Rochester, Minnesota, from October 1, 2012, through March 31, 2013, constituted the study population.
Main Measures: Of 7484 patients seen for a medical examination, 2044 (27.3%) had a BMI more than 30 kg/m2. Of these, 946 (46.3%) were female.
Key Results: The mean BMI was 34.8 kg/m2 (range, 30.0–64.4), and the mean age was 60.7 years (range, 18.5–94.6). Only 473 patients (23.1%) had the International Classification of Disease, Ninth Revision (ICD-9), code for diagnosis of obesity: Class 1 in 192 (41%), class 2 in 162 (34%), and class 3 in 119 (25%). Of the remaining 1571 patients with a BMI more than 30 kg/m2 but without the diagnosis of obesity, 748 (47.6%) had ORTs in their medical notes. Those with an obesity diagnosis were more likely to be referred for nutrition counseling than those with ORTs (9.3% vs. 4.4%; P < 0.0006).
Conclusions: Physicians are meaningfully identifying obesity and discussing its health consequences through the use of ORTs, but they are failing to document ICD diagnoses in the medical records.
The following core competencies are addressed in this article: Medical knowledge, Practice-based learning, Systems-based practice.
Keywords: Medical culture, nutrition, obesity, patient education
|How to cite this article:|
Iftikhar S, Varayil JE, Hurt RT, Salerno MS, Mueller PS. Determining the rate of obesity documentation in a division of general internal medicine at a tertiary care medical center. Int J Acad Med 2020;6:103-9
|How to cite this URL:|
Iftikhar S, Varayil JE, Hurt RT, Salerno MS, Mueller PS. Determining the rate of obesity documentation in a division of general internal medicine at a tertiary care medical center. Int J Acad Med [serial online] 2020 [cited 2020 Jul 6];6:103-9. Available from: http://www.ijam-web.org/text.asp?2020/6/2/103/287964
| Introduction|| |
Obesity affects a third of Americans, and its cost is high. As of 2008, the annual estimated cost for obesity was $147 billion in the United States (US) alone.,, Obesity is a leading cause of preventable deaths in the US, likely only second to tobacco-related diseases. It is associated with more than sixty comorbidities, including cardiovascular disease; Type 2 diabetes mellitus; and malignancies such as esophageal, pancreatic, renal, breast, and thyroid.,
The US Preventive Services Task Force recommends that all adults be screened for obesity and those who have a body mass index (BMI) of 30 kg/m2 or more be offered or referred for multicomponent behavioral interventions, including diet and exercise. Despite this recommendation, many physicians do not diagnose obesity or address it when they do. Indeed, most patients with obesity are not given an action plan for weight loss.,
Notably, a study of a primary care internal medicine ambulatory practice showed that once obesity is formally diagnosed (i.e., listed as a diagnosis with an International Classification of Diseases, Ninth Revision [ICD-9] code), physicians are more likely to refer affected patients for behavioral interventions. However, the same study also showed that, among patients with obesity, the formal diagnosis rate was low, at 19.9%. Furthermore, of the patients with a diagnosis of obesity, only 22.6% had a treatment plan. This is important because we could bill for obesity but if we are missing to bill means we are losing on that revenue. By identifying these gaps and making an effort to inform physicians on these opportunities to bill appropriately, we could in fact generate some additional revenue.
The purpose of our study was to determine the rate of identification of obesity, either by formal diagnoses or by the use of obesity-related terms (ORTs) within the body of the clinical note and referral for behavioral interventions. We hypothesized that physicians are more likely to identify patients with obesity by using ORTs than to formally diagnose obesity. We also hypothesized that patients with obesity for whom ORTs are used are more likely to be referred for behavioral interventions than patients with obesity for who ORTs are not used.
We hypothesized that physicians are using terms such as obese, overweight, weight-related issues, and elevated BMI in their notes to discuss obesity and from here on, these will be used in the document as ORT.
Hypertension was defined as a blood pressure more than 140/90 mmHg, mentioned as a diagnosis in the Electronic health record (EHR), or taking antihypertensives.
Type 2 diabetes mellitus was defined as a fasting blood glucose level more than 126 mg/dL, a hemoglobin A1c value of 6.5% or more, an oral glucose tolerance value more than 200 mg/dL, Type 2 diabetes mellitus as a diagnosis in the EHR, or taking insulin or a hypoglycemic.
Hypercholesterolemia was defined as a total serum cholesterol level more than 200 mg/dL, triglyceride value more than 200 mg/dL, low-density lipoprotein value more than 130 mg/dL, a diagnosis of hyperlipidemia, or taking a lipid-lowering medication. BMI was calculated as follows: weight in kilograms divided by square of height in meters (kg/m2).
Obesity was defined using the World Health Organization and National Institutes of Health classification system: overweight, BMI of 25 to 29.9 kg/m2; Class 1 obesity, BMI of 30 to 34.9 kg/m2; Class 2 obesity, BMI of 35 to 39.9 kg/m2; and Class 3 obesity, BMI of 40 kg/m2 or more.
ORT were defined as use of any of the following words: obese, overweight, weight-related issues, and elevated body mass index (BMI).
Limitation in physical activity was defined as having any condition or disease such as chronic obstructive pulmonary disease, asthma, using a wheelchair, or any other illness that prevents the patient from making the recommended lifestyle changes.
*Impression Report Plan. This is the section in the General Medical exam note where the physician puts in their impression, differential, reports, and investigations and finally a plan for the patient. This is the last part of the physician's note
| Methods|| |
Settings and patients
After the study was approved by the Mayo Clinic Institutional Review Board, the EHRs for all outpatients with a documented BMI of more than 30 kg/m2 who underwent a medical examination in the Division of General Internal Medicine at Mayo Clinic in Rochester, Minnesota, from October 1, 2012, through March 31, 2013, were retrospectively reviewed.
The following data were abstracted from the EHRs: demographics including age, sex, address, race, height, weight, and BMI; primary diagnosis; reason for the current visit; presence or absence of comorbidities such as smoking, hypertension, Type 2 diabetes mellitus, hyperlipidemia, hypothyroidism, and cancer; medications; obesity management; and physical limitations. Patients were included if they had research authorization on file and had a Class 1 or greater BMI. We determined whether patients had a formal diagnosis of obesity (e.g., ICD-9 code for obesity or obesity listed as a diagnosis in the impression, report, and plan* section of the medical note); whether, in the absence of a formal diagnosis of obesity, ORTs were used in the medical note; and whether patients were educated on weight loss techniques or referred for behavioral interventions. Finally, we determined whether medications or underlying diseases (e.g., cardiac, pulmonary, thyroid, or physical disability) and the amount of time physicians spent with the patients (based on billing codes used) might contribute to obesity.
Continuous data were presented as median and interquartile range, and categorical data were presented as counts and percentages. Kruskal–Wallis and c2 statistical tests for differences between groups were used, as appropriate. For all statistical tests, P < 0.05 was considered statistically significant. Additionally, graphic displays of the data were produced to further investigate distributions by groups of interest. All analyses and graphics were produced with SAS version 9.4 (SAS Institute, Inc).
| Results|| |
Of 7484 patients who had a medical examination, 2044 (27.3%) had a BMI more than 30 kg/m2. Of these, 946 (46.3%) were female. The mean BMI was 34.8 kg/m2 (range, 30.0–64.4), and the mean age was 60.7 years (range, 18.5–94.6). The mean time spent with a provider was 40.1 min and was equal in both patients with a diagnosis and those with ORTs. However, on an average, 5 more minutes was spent with female patients than male patients in both groups. Only 473 patients (23.1%) had the ICD-9 code for diagnosis of obesity: Class 1 in 192 (41%), Class 2 in 162 (34%), and Class 3 in 119 (25%) [Table 1]. Of the remaining 1571 patients with a BMI more than 30 kg/m2 but without the diagnosis of obesity, 748 (47.6%) had ORTs in their medical notes. Patients who had ORTs were older (mean age, 60.6 years) than those with obesity diagnosis (57.6 years) (P < 0.0001) [Table 2]. Women were more likely than men to have the diagnosis. Those with ORTs had a lower mean BMI than those with diagnosis (35 vs. 37.3 kg/m2, P < 0.0001) [Table 2]. The rate of diagnosis increased as the BMI increased [Figure 1]. Those with diagnosis were more likely to be referred to nutrition and behavioral education (9.3% vs. 4.4%; P ≤ 0.0006) [Table 2] and [Figure 2]. Female patients with diagnosis were more likely to be referred for nutrition and behavioral education than those with ORTs [Table 3] and [Table 4]. Provider time increased with increasing BMI.
|Table 1: Baseline characteristics of 2044 patients with a body mass index >30 kg/m2|
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|Table 2: Comparison of patients with diagnosis of obesity and patients with obesity-related terms in their medical notes|
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|Figure 1: Relationship between obesity diagnosis and body mass index. (a) Rate of obesity diagnosis increases when body mass index increases between 30 and 50 kg/m2. (b) ORT indicates obesity-related term. The horizontal line in the middle of each box indicates the median, and the top and bottom borders of the box mark the 75th and 25th percentiles (respectively), and the whiskers above and below the box mark the minimum and maximum points within 2.0 interquartile range of the median, respectively. The points beyond the whiskers are outliers|
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|Figure 2: Frequency of nutrition and behavioral education in patients with obesity-related terms (ORTs) in their medical notes and patients with diagnosis of obesity|
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|Table 3: Comparisons for patients with obesity-related terms in their medical notes, by sex and overall|
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|Table 4: Comparisons for patients with diagnosis of obesity, by sex and overall|
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| Discussion|| |
To our knowledge, this is the first study to show that physicians often use ORTs to discuss the impact of being overweight during their interactions with patients. Unfortunately, they are not documenting or billing for obesity and overweight appropriately. However, we found that the ORT use rate was almost 50% (47.6%). The sensitivity surrounding labeling patients as obese, especially if a good rapport has not been established, may be an inhibiting factor and a reason why physicians are not explicitly listing the term obesity as the diagnosis. Many investigators suggest that the word obesity may be offensive. In addition, another Mayo Clinic study found that many patients inaccurately perceive their BMI and the accuracy decreases with increased BMI. Clinicians who discuss weight loss strategies with their patients have a direct impact on motivating them to make lifestyle modifications. Most physicians have received little training for discussing weight issues and have not been educated about the effects of genetics and medications on weight gain. This lack of training may be another reason physicians are not documenting obesity as a diagnosis but using ORTs instead. In addition, the physicians may feel uncomfortable using the term obese and may not want to offend the patient, hence avoid putting it under diagnosis but do include it in their discussion. Our study confirms that female patients receive longer consultation time and are more likely to receive a diagnosis of obesity than male patients and that patients with a higher class of BMI are more likely to be given a diagnosis of obesity.
Our study population was similar to that of Bardia et al. Although nutrition counseling was ordered once obesity was diagnosed, both studies found that referrals for appropriate interventions are lacking. Only 98 of the 2044 patients in this study were referred for nutrition counseling. Unlike previous studies, our study did not find a difference in the diagnosis of other comorbidities, including hypertension, Type 2 diabetes mellitus, cancer, thyroid disease, or physical disability among obesity diagnosis and those with ORT.
In 2011, the Centers for Medicare and Medicaid Services announced reimbursement for intensive behavioral counseling of patients with obesity by primary care consultants., However, unless obesity is identified and diagnosed, efforts to educate patients and formulate a treatment plan are not possible. Because obesity is not being billed, there is revenue lost. Perhaps, if obesity were a billable preventive diagnosis, it could be incorporated and charged for as a preventive service. In addition, a template could be built for incorporation into the medical note that automatically triggers referral to services based on obesity class. For example, a patient with Class 1 obesity would receive a brochure with resources and referral to a nutritionist, one with Class 2, in addition, would be referred to an exercise specialist, and one with Class 3, additionally, would be referred to an endocrinologist for bariatrics discussion and resources. Clearly, physicians spend more time with female patients, and thus the likelihood of discussion and documentation of obesity is higher. This finding is challenging to fully analyze. More time may be spent because the patient has other complex issues, is difficult to communicate with, or is resistant to discussion about weight. Perhaps, having a licensed practical nurse or nurse practitioner provide education regarding weight in all patients with Class 2 or greater obesity would be a revenue-generating option if this can be billed as a separate visit, and this will also save the physician's time to discuss the important health concerns that the patient came for. The physician still will need documentation of initial discussion and referral for further education.
Some investigators have suggested that health-care professionals emphasize a patient's overall health and not only weight and BMI. Patient-centered communication strategies, such as motivational interviewing, have been associated with patient adherence and positive outcomes. The continuum of care can also be ensured by providing adequate referral resources for behavioral change counseling., Accordingly, efforts to address obesity with patients should be increased.
Our study has some limitations. Primary diagnosis and medication were not factors in the analysis because they each have too many variables and each variable does not have enough samples to attain statistical power. Future work can include the primary diagnosis and medication to improve the statistical power and perhaps seek additional factors contributing to obesity. Because our institution is a tertiary care center, our patients may have challenging conditions. Furthermore, in the Division of General Internal Medicine, they are usually seen for a one-time visit with or without a brief follow-up visit, mostly to focus on the medical issue for which attention was sought. Therefore, follow-up with the patient and the primary care provider regarding ongoing weight management will be essential. Information obtained may give insight into the impact of obesity counseling. Future population-based studies are required to further assess how to best manage the obesity epidemic. Clearly, physicians need more training regarding billing, need to feel comfortable with discussing the patients weight-related health issues in a clear way, need to document this in their notes, and need to be well aware of their institutional resources for weight loss. A short phone call reminder from the nurse regarding update on the patient's ongoing diet and exercise program and how those efforts are going also will be beneficial to keep the motivation up.
| Conclusions|| |
Higher BMI directly correlates with the diagnosis of obesity. Physicians are meaningfully identifying obesity and discussing its effect on health through the use of ORTs, but they are failing to adequately document the ICD-9 diagnosis in the medical records; thus, revenue is possibly being lost. In addition, they are not making a considerable effort at nutrition and behavioral counseling, probably because of lack of time or they are discussing more complex health-related issues given the fact that ours is a tertiary care center. Female patients had longer visits, were more likely to have diagnosis, and had relatively increased referral for nutrition counseling. The rate of referrals for nutrition and behavioral counseling was still very low overall in that only 98 of 2044 patients received referrals.
MSS was involved in data collection and JEV was involved in the initial study design. SI, RTH, and PSM were involved with all the aspects of design, data collection, and writing the manuscript.
We thank Saeed Mehrabi, Ph.D, for statistical support.
This study was presented as a poster at the Dubai International Healthcare Summit, Dubai, United Arab Emirates, October 18–20, 2016.
Financial support and sponsorship
Funding for abstraction, statistical support, and data analysis was obtained from the Division of General Internal Medicine through the Healthy Weight Initiative, Mayo Clinic, Rochester, Minnesota.
Conflicts of interest
There are no conflicts of interest.
Ethical conduct of research
We received IRB approval for this study. All the assigned participants had a consent on file. Patient identity was not disclosed. Any data collected was confidential, without identifying features. All linking identifiers will be destroyed after the publication of this article. Applicable EQUATOR Network guidelines (https://www.equator-network.org/) were followed.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4]