Annabelle N. Brinkerhoff, Jigar Gosalia, Juan J. Qiu, James A. Pawelczyk, David N. Proctor
{"title":"15 代谢综合征的药物使用和生活方式改变转诊中的差异取决于综合征的编码方式:TriNetX 研究","authors":"Annabelle N. Brinkerhoff, Jigar Gosalia, Juan J. Qiu, James A. Pawelczyk, David N. Proctor","doi":"10.1017/cts.2024.36","DOIUrl":null,"url":null,"abstract":"OBJECTIVES/GOALS: ICD-10 coding inconsistencies hinder timely recognition and treatment of metabolic syndrome (MetS), posing a significant risk for cardiometabolic disease progression. This study employed a digital phenotype for MetS and compared odds for medication and lifestyle intervention compared to those coded for MetS. METHODS/STUDY POPULATION: MetS is a cluster of cardiometabolic risk factors that increase risk for numerous adverse clinical outcomes. Patients with MetS were identified through electronic medical records on TriNetX LLC using the standard ICD-10 code or through a digital phenotype, involving grouping codes for the individual components. Percentage of patients with MetS not captured with the standard code was identified. In addition, disparities in blood pressure, glucose, lipid-lowering medication, and lifestyle intervention between the coding schemas were assessed, shedding light on healthcare inequities and informing targeted interventions. Odds ratios (RR) were presented for all outcomes. RESULTS/ANTICIPATED RESULTS: Patient demographics and lab values were similar between the standard code and digital phenotype cohorts. Of the 4.3 million individuals aged 50 to 80 identified as having MetS using the digital phenotype in the TriNetX research network, only 1.78% of participants shared the standard code. Individuals with the digital phenotype for MetS were at lower odds in receiving glucose lowering medication (OR: 2.11, 95% CI: 1.98–2.13, p <0.001) and exercise or nutrition-based intervention advice (OR: 1.76, 95% CI: 1.55–1.96, p <0.001) after controlling for demographics and lab values for each MetS component. DISCUSSION/SIGNIFICANCE: This project utilized TriNetX to create a digital phenotype for MetS, and suggests most patients are not coded for it using the standard ICD-10 system. This is troublesome given those with the standard code are less likely to receive certain interventions.","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"19 1","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"15 Discrepancies in Medication Usage and Lifestyle Modification Referrals in Metabolic Syndrome is Dependent on how the Syndrome is Coded: A TriNetX Study\",\"authors\":\"Annabelle N. Brinkerhoff, Jigar Gosalia, Juan J. Qiu, James A. Pawelczyk, David N. Proctor\",\"doi\":\"10.1017/cts.2024.36\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"OBJECTIVES/GOALS: ICD-10 coding inconsistencies hinder timely recognition and treatment of metabolic syndrome (MetS), posing a significant risk for cardiometabolic disease progression. This study employed a digital phenotype for MetS and compared odds for medication and lifestyle intervention compared to those coded for MetS. METHODS/STUDY POPULATION: MetS is a cluster of cardiometabolic risk factors that increase risk for numerous adverse clinical outcomes. Patients with MetS were identified through electronic medical records on TriNetX LLC using the standard ICD-10 code or through a digital phenotype, involving grouping codes for the individual components. Percentage of patients with MetS not captured with the standard code was identified. In addition, disparities in blood pressure, glucose, lipid-lowering medication, and lifestyle intervention between the coding schemas were assessed, shedding light on healthcare inequities and informing targeted interventions. Odds ratios (RR) were presented for all outcomes. RESULTS/ANTICIPATED RESULTS: Patient demographics and lab values were similar between the standard code and digital phenotype cohorts. Of the 4.3 million individuals aged 50 to 80 identified as having MetS using the digital phenotype in the TriNetX research network, only 1.78% of participants shared the standard code. Individuals with the digital phenotype for MetS were at lower odds in receiving glucose lowering medication (OR: 2.11, 95% CI: 1.98–2.13, p <0.001) and exercise or nutrition-based intervention advice (OR: 1.76, 95% CI: 1.55–1.96, p <0.001) after controlling for demographics and lab values for each MetS component. DISCUSSION/SIGNIFICANCE: This project utilized TriNetX to create a digital phenotype for MetS, and suggests most patients are not coded for it using the standard ICD-10 system. 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15 Discrepancies in Medication Usage and Lifestyle Modification Referrals in Metabolic Syndrome is Dependent on how the Syndrome is Coded: A TriNetX Study
OBJECTIVES/GOALS: ICD-10 coding inconsistencies hinder timely recognition and treatment of metabolic syndrome (MetS), posing a significant risk for cardiometabolic disease progression. This study employed a digital phenotype for MetS and compared odds for medication and lifestyle intervention compared to those coded for MetS. METHODS/STUDY POPULATION: MetS is a cluster of cardiometabolic risk factors that increase risk for numerous adverse clinical outcomes. Patients with MetS were identified through electronic medical records on TriNetX LLC using the standard ICD-10 code or through a digital phenotype, involving grouping codes for the individual components. Percentage of patients with MetS not captured with the standard code was identified. In addition, disparities in blood pressure, glucose, lipid-lowering medication, and lifestyle intervention between the coding schemas were assessed, shedding light on healthcare inequities and informing targeted interventions. Odds ratios (RR) were presented for all outcomes. RESULTS/ANTICIPATED RESULTS: Patient demographics and lab values were similar between the standard code and digital phenotype cohorts. Of the 4.3 million individuals aged 50 to 80 identified as having MetS using the digital phenotype in the TriNetX research network, only 1.78% of participants shared the standard code. Individuals with the digital phenotype for MetS were at lower odds in receiving glucose lowering medication (OR: 2.11, 95% CI: 1.98–2.13, p <0.001) and exercise or nutrition-based intervention advice (OR: 1.76, 95% CI: 1.55–1.96, p <0.001) after controlling for demographics and lab values for each MetS component. DISCUSSION/SIGNIFICANCE: This project utilized TriNetX to create a digital phenotype for MetS, and suggests most patients are not coded for it using the standard ICD-10 system. This is troublesome given those with the standard code are less likely to receive certain interventions.