Farhan Ullah1, David C Kaelber2. 1. Center for Internal Medicine and Pediatrics, Center for Clinical Informatics Research and Education, The MetroHealth System (F Ullah, DC Kaelber), Cleveland, Ohio. Electronic address: dr.farhanullah1@gmail.com. 2. Center for Internal Medicine and Pediatrics, Center for Clinical Informatics Research and Education, The MetroHealth System (F Ullah, DC Kaelber), Cleveland, Ohio; Departments of Internal Medicine, Pediatrics, and Population and Quantitative Health Sciences, Case Western Reserve University (DC Kaelber), Cleveland, Ohio.
Abstract
OBJECTIVE: We used de-identified clinical data from multiple health care systems using different electronic health records (EHRs) to 1) quantify the prevalence of common pediatric chronic diseases, 2) investigate patent characteristics associated with common pediatric chronic diseases, and 3) compare the results of our methodology to determine chronic disease prevalence with traditional approaches. METHODS: We used a HIPAA-compliant and de-identified web application (Explorys; IBM Watson Health Explorys Inc.) to identify patients 17 years old or younger from multiple health care systems in the US who were seen in primary care clinics between 2016-2018 to determine the most common chronic conditions in this age group. The prevalence of chronic conditions was compared between different age groups, genders, races/ethnicities, and insurance; odds ratios and confidence intervals were calculated and reported. RESULTS: The top 6 chronic conditions identified by prevalence were: obesity/overweight (36.7%), eczema (15.8%), asthma (12.7%), food allergies (4.7%), attention deficit-hyperactivity disorder (4.09%) and hypertension (4.07%). Chronic conditions were generally more prevalent among relatively older pediatric patients, males, and African-American and multiracial groups. CONCLUSIONS: Approximately 40% of children and adolescents have at least one chronic disease. Obesity/overweight, eczema, and asthma are the most common chronic diseases of childhood, in the US, among those seeking care in health care systems with EHRs. The work compiled herein demonstrates that aggregated, standardized, normalized and de-identified population-level EHR data can provide both sufficient insight and statistical power to calculate the prevalence of chronic diseases and the odds ratio of various risk factors.
OBJECTIVE: We used de-identified clinical data from multiple health care systems using different electronic health records (EHRs) to 1) quantify the prevalence of common pediatric chronic diseases, 2) investigate patent characteristics associated with common pediatric chronic diseases, and 3) compare the results of our methodology to determine chronic disease prevalence with traditional approaches. METHODS: We used a HIPAA-compliant and de-identified web application (Explorys; IBM Watson Health Explorys Inc.) to identify patients 17 years old or younger from multiple health care systems in the US who were seen in primary care clinics between 2016-2018 to determine the most common chronic conditions in this age group. The prevalence of chronic conditions was compared between different age groups, genders, races/ethnicities, and insurance; odds ratios and confidence intervals were calculated and reported. RESULTS: The top 6 chronic conditions identified by prevalence were: obesity/overweight (36.7%), eczema (15.8%), asthma (12.7%), food allergies (4.7%), attention deficit-hyperactivity disorder (4.09%) and hypertension (4.07%). Chronic conditions were generally more prevalent among relatively older pediatric patients, males, and African-American and multiracial groups. CONCLUSIONS: Approximately 40% of children and adolescents have at least one chronic disease. Obesity/overweight, eczema, and asthma are the most common chronic diseases of childhood, in the US, among those seeking care in health care systems with EHRs. The work compiled herein demonstrates that aggregated, standardized, normalized and de-identified population-level EHR data can provide both sufficient insight and statistical power to calculate the prevalence of chronic diseases and the odds ratio of various risk factors.
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