Steven Horng1,2, Nathaniel R Greenbaum1,2, Larry A Nathanson1,2, James C McClay3, Foster R Goss4, Jeffrey A Nielson5. 1. Division of Clinical Informatics, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, United States. 2. Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, United States. 3. Department of Emergency Medicine, College of Medicine, University of Nebraska Medical Center, Omaha, Nebraska, United States. 4. Department of Emergency Medicine, University of Colorado Hospital, University of Colorado School of Medicine, Aurora, Colorado, United States. 5. Northeastern Ohio Medical University, University Hospitals Samaritan Medical Center, Ashland, Ohio, United States.
Abstract
OBJECTIVE: Numerous attempts have been made to create a standardized "presenting problem" or "chief complaint" list to characterize the nature of an emergency department visit. Previous attempts have failed to gain widespread adoption as they were not freely shareable or did not contain the right level of specificity, structure, and clinical relevance to gain acceptance by the larger emergency medicine community. Using real-world data, we constructed a presenting problem list that addresses these challenges. MATERIALS AND METHODS: We prospectively captured the presenting problems for 180,424 consecutive emergency department patient visits at an urban, academic, Level I trauma center in the Boston metro area. No patients were excluded. We used a consensus process to iteratively derive our system using real-world data. We used the first 70% of consecutive visits to derive our ontology, followed by a 6-month washout period, and the remaining 30% for validation. All concepts were mapped to Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT). RESULTS: Our system consists of a polyhierarchical ontology containing 692 unique concepts, 2,118 synonyms, and 30,613 nonvisible descriptions to correct misspellings and nonstandard terminology. Our ontology successfully captured structured data for 95.9% of visits in our validation data set. DISCUSSION AND CONCLUSION: We present the HierArchical Presenting Problem ontologY (HaPPy). This ontology was empirically derived and then iteratively validated by an expert consensus panel. HaPPy contains 692 presenting problem concepts, each concept being mapped to SNOMED CT. This freely sharable ontology can help to facilitate presenting problem-based quality metrics, research, and patient care. Georg Thieme Verlag KG Stuttgart · New York.
OBJECTIVE: Numerous attempts have been made to create a standardized "presenting problem" or "chief complaint" list to characterize the nature of an emergency department visit. Previous attempts have failed to gain widespread adoption as they were not freely shareable or did not contain the right level of specificity, structure, and clinical relevance to gain acceptance by the larger emergency medicine community. Using real-world data, we constructed a presenting problem list that addresses these challenges. MATERIALS AND METHODS: We prospectively captured the presenting problems for 180,424 consecutive emergency department patient visits at an urban, academic, Level I trauma center in the Boston metro area. No patients were excluded. We used a consensus process to iteratively derive our system using real-world data. We used the first 70% of consecutive visits to derive our ontology, followed by a 6-month washout period, and the remaining 30% for validation. All concepts were mapped to Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT). RESULTS: Our system consists of a polyhierarchical ontology containing 692 unique concepts, 2,118 synonyms, and 30,613 nonvisible descriptions to correct misspellings and nonstandard terminology. Our ontology successfully captured structured data for 95.9% of visits in our validation data set. DISCUSSION AND CONCLUSION: We present the HierArchical Presenting Problem ontologY (HaPPy). This ontology was empirically derived and then iteratively validated by an expert consensus panel. HaPPy contains 692 presenting problem concepts, each concept being mapped to SNOMED CT. This freely sharable ontology can help to facilitate presenting problem-based quality metrics, research, and patient care. Georg Thieme Verlag KG Stuttgart · New York.
Authors: Stewart Babbott; Linda Baier Manwell; Roger Brown; Enid Montague; Eric Williams; Mark Schwartz; Erik Hess; Mark Linzer Journal: J Am Med Inform Assoc Date: 2013-09-04 Impact factor: 4.497
Authors: Jeremiah D Schuur; Renee Y Hsia; Helen Burstin; Michael J Schull; Jesse M Pines Journal: Health Aff (Millwood) Date: 2013-12 Impact factor: 6.301
Authors: Jeffrey P Ferraro; Ye Ye; Per H Gesteland; Peter J Haug; Fuchiang Rich Tsui; Gregory F Cooper; Rudy Van Bree; Thomas Ginter; Andrew J Nowalk; Michael Wagner Journal: Appl Clin Inform Date: 2017-05-31 Impact factor: 2.342
Authors: Richard T Griffey; Jesse M Pines; Heather L Farley; Michael P Phelan; Christopher Beach; Jeremiah D Schuur; Arjun K Venkatesh Journal: Ann Emerg Med Date: 2014-10-16 Impact factor: 5.721
Authors: Julio C Silva; Shital C Shah; Dino P Rumoro; Jamil D Bayram; Marilyn M Hallock; Gillian S Gibbs; Michael J Waddell Journal: Artif Intell Med Date: 2013-11 Impact factor: 5.326
Authors: Rebecca B Morse; Abigail C Bretzin; Silvia P Canelón; Bernadette A D'Alonzo; Andrea L C Schneider; Mary R Boland Journal: Appl Clin Inform Date: 2022-03-09 Impact factor: 2.342
Authors: Marta Fernandes; Rúben Mendes; Susana M Vieira; Francisca Leite; Carlos Palos; Alistair Johnson; Stan Finkelstein; Steven Horng; Leo Anthony Celi Journal: PLoS One Date: 2020-03-03 Impact factor: 3.240
Authors: Ketki K Tendulkar; Brendan Cope; Jianghu Dong; Troy J Plumb; W Scott Campbell; Apar Kishor Ganti Journal: PLoS One Date: 2022-08-17 Impact factor: 3.752