eADSTdataset.pdf

We convened a multidisciplinary team inclusive of physicians from the divisions of Community Pediatrics and Pediatric Pulmonology and formed a working group called Asthma Best Practice Initiative (ABPI). The team reviewed current guidelines and discussed practical considerations of a community-based clinical practice. The team developed a blue print algorithm for the eADST based on NHLBI and GINA guidelines, with main focus areas of Asthma History, Risks, Initial Asthma Severity and Asthma Control, that guides the HCP to the appropriate severity classification and subsequent therapeutic step and follow up recommendations based on NHLBI guidelines. The tool integrates algorithms from multiple age groups, each of which has a separate diagnostic and management algorithm.During subsequent patient visits, the tool auto-populates with the previously recorded most recent asthma severity classification as well as risk factors. After updating current impairment, interim history and risks, the tool guides the HCP to decide current level of control, update severity classification and therapeutic step if indicated, and provide guidance for recommended appropriate treatment.The health system’s EMR Informatics team was engaged, and together the clinical and informatics team developed and revised the eADST within the capacity and limitations of the health systems existing platform. The final product was reviewed and approved for by the health systems Pediatric EMR Committee. Prior to launch of the eADST, primary care providers in the three clinics served by Division of Community Pediatrics received a one-hour training on best-practice guidelines for asthma management, as well as the use of the electronic asthma decision support tool (eADST). Providers also received a follow up e-mail correspondence reinforcing the educational and training materials.We defined asthma classification precision by grouping of asthma related ICD-10 codes grouped as either “non-precise" or “precise" classification for the purposes of evaluation. Non-precise diagnosis codes included: Unspecified Asthma (J45.909), Unspecified Asthma Exacerbation (J45.901)and Other Asthma(J45.998). Precise diagnosis codes included: Mild Intermittent Asthma(J45.20), Mild Intermittent Asthma with Acute Exacerbation(J45.21), Mild Persistent Asthma(J45.30), Mild Persistent Asthma with Acute Exacerbation(J45.31), Moderate Persistent Asthma(J45.40), Moderate Persistent Asthma with Acute Exacerbation(J45.42), and Exercise Induced Asthma(J45.990).The eADST was launched in June 2018 simultaneously at three clinics in the Division of Community Pediatrics. We reviewed outcomes from the 12 months prior to eADST and training (07/2017-06/2018) and 12 months after launch (07/2018-06/2019) of the intervention. Statistical analysis was performed using the Chi squared test. A p-value of less than 0.05 was considered statistically significant. This study was approved by the Institutional Review Board of MedStar Georgetown University Hospital.