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How Accurate Are Patients At Diagnosing The Cause Of Their Knee Pain With The Help Of A Web-based Symptom Checker?

OBJECTIVES: Researching medical information is the third most popular activity online, and there are a variety of web-based symptom checker programs available to the patient. A recent study has demonstrated that a web-based program can generate an accurate differential diagnosis in 89% of ambulatory...

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Autores principales: Bisson, Leslie J., Komm, Jorden, Bernas, Geoffrey A., Marzo, John M., Rauh, Michael A., Browning, William M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4901722/
http://dx.doi.org/10.1177/2325967115S00150
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author Bisson, Leslie J.
Komm, Jorden
Bernas, Geoffrey A.
Marzo, John M.
Rauh, Michael A.
Browning, William M.
author_facet Bisson, Leslie J.
Komm, Jorden
Bernas, Geoffrey A.
Marzo, John M.
Rauh, Michael A.
Browning, William M.
author_sort Bisson, Leslie J.
collection PubMed
description OBJECTIVES: Researching medical information is the third most popular activity online, and there are a variety of web-based symptom checker programs available to the patient. A recent study has demonstrated that a web-based program can generate an accurate differential diagnosis in 89% of ambulatory patients with knee pain based on a history entered by the patient. Despite the regularity of online symptom checking, the authors are not aware of any study that has evaluated a patient's ability to self-diagnose the cause of their knee pain based on the results of a diagnostic program. The purpose of this study was to determine the ability of a patient to select his or her own diagnosis after being supplied with a differential diagnosis generated by a web-based program for the patient's knee pain. METHODS: A web-based program was created to collect a knee pain history and generate a differential diagnosis for ambulatory patients with knee pain. The diagnoses generated by the program were linked to informative content which was immediately available to the patient in order to allow them to learn more about each diagnosis. Prior to coming to their office appointment, the patient was given the link for the program. They entered their history into the program which then generated a list of most likely causes for the patient's knee pain based on their history. The program has the capability of generating 21 common knee diagnoses. After exploring the informative content, the patient selected which diagnosis or diagnoses they believed were the most likely cause of their pain. Despite the program generating a limited list, the patient had the ability to select from all 21 diagnoses capable of being generated by the program when selecting the diagnosis(es) they believed was the cause of their knee pain. Within days of completing the program, each patient was examined by a board-certified orthopaedic surgeon. The physician was blinded to the differential diagnosis generated by the program as well as the diagnosis(es) selected by the patient. A third party was responsible for comparing the diagnosis(es) generated by the program with that selected by the patient as well as the final diagnosis(es) determined by the physician. The diagnosis(es) provided by the physician were considered the correct diagnosis for the patient. The level of matching between the patient selected diagnosis and the physician's diagnosis determined the ability of the patient to correctly diagnose the cause of their knee pain. RESULTS: Ninety-two males and 108 females, with an average age of 49 years (19-76) were analyzed for this study. Two hundred twenty-seven patients were excluded from analysis because they did not complete the entire program, 10 patients were excluded because they were under 18 years of age and 6 patients were excluded because they had a diagnosis other than one capable of being generated by the program. Patients selected an average of 2 diagnoses (1-9). The program generated an average of 6.6 diagnoses (2-13) per patient and each patient had an average of 1.8 physician diagnoses (1-4). The patient selected diagnosis matched the physician's diagnosis 58% of the time. CONCLUSION: Patients are able to diagnose the cause of their knee pain 58% of the time based on information provided by a web-based symptom checker program.
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spelling pubmed-49017222016-06-10 How Accurate Are Patients At Diagnosing The Cause Of Their Knee Pain With The Help Of A Web-based Symptom Checker? Bisson, Leslie J. Komm, Jorden Bernas, Geoffrey A. Marzo, John M. Rauh, Michael A. Browning, William M. Orthop J Sports Med Article OBJECTIVES: Researching medical information is the third most popular activity online, and there are a variety of web-based symptom checker programs available to the patient. A recent study has demonstrated that a web-based program can generate an accurate differential diagnosis in 89% of ambulatory patients with knee pain based on a history entered by the patient. Despite the regularity of online symptom checking, the authors are not aware of any study that has evaluated a patient's ability to self-diagnose the cause of their knee pain based on the results of a diagnostic program. The purpose of this study was to determine the ability of a patient to select his or her own diagnosis after being supplied with a differential diagnosis generated by a web-based program for the patient's knee pain. METHODS: A web-based program was created to collect a knee pain history and generate a differential diagnosis for ambulatory patients with knee pain. The diagnoses generated by the program were linked to informative content which was immediately available to the patient in order to allow them to learn more about each diagnosis. Prior to coming to their office appointment, the patient was given the link for the program. They entered their history into the program which then generated a list of most likely causes for the patient's knee pain based on their history. The program has the capability of generating 21 common knee diagnoses. After exploring the informative content, the patient selected which diagnosis or diagnoses they believed were the most likely cause of their pain. Despite the program generating a limited list, the patient had the ability to select from all 21 diagnoses capable of being generated by the program when selecting the diagnosis(es) they believed was the cause of their knee pain. Within days of completing the program, each patient was examined by a board-certified orthopaedic surgeon. The physician was blinded to the differential diagnosis generated by the program as well as the diagnosis(es) selected by the patient. A third party was responsible for comparing the diagnosis(es) generated by the program with that selected by the patient as well as the final diagnosis(es) determined by the physician. The diagnosis(es) provided by the physician were considered the correct diagnosis for the patient. The level of matching between the patient selected diagnosis and the physician's diagnosis determined the ability of the patient to correctly diagnose the cause of their knee pain. RESULTS: Ninety-two males and 108 females, with an average age of 49 years (19-76) were analyzed for this study. Two hundred twenty-seven patients were excluded from analysis because they did not complete the entire program, 10 patients were excluded because they were under 18 years of age and 6 patients were excluded because they had a diagnosis other than one capable of being generated by the program. Patients selected an average of 2 diagnoses (1-9). The program generated an average of 6.6 diagnoses (2-13) per patient and each patient had an average of 1.8 physician diagnoses (1-4). The patient selected diagnosis matched the physician's diagnosis 58% of the time. CONCLUSION: Patients are able to diagnose the cause of their knee pain 58% of the time based on information provided by a web-based symptom checker program. SAGE Publications 2015-07-17 /pmc/articles/PMC4901722/ http://dx.doi.org/10.1177/2325967115S00150 Text en © The Author(s) 2015 http://creativecommons.org/licenses/by-nc-nd/3.0/ This open-access article is published and distributed under the Creative Commons Attribution - NonCommercial - No Derivatives License (http://creativecommons.org/licenses/by-nc-nd/3.0/), which permits the noncommercial use, distribution, and reproduction of the article in any medium, provided the original author and source are credited. You may not alter, transform, or build upon this article without the permission of the Author(s). For reprints and permission queries, please visit SAGE’s Web site at http://www.sagepub.com/journalsPermissions.nav.
spellingShingle Article
Bisson, Leslie J.
Komm, Jorden
Bernas, Geoffrey A.
Marzo, John M.
Rauh, Michael A.
Browning, William M.
How Accurate Are Patients At Diagnosing The Cause Of Their Knee Pain With The Help Of A Web-based Symptom Checker?
title How Accurate Are Patients At Diagnosing The Cause Of Their Knee Pain With The Help Of A Web-based Symptom Checker?
title_full How Accurate Are Patients At Diagnosing The Cause Of Their Knee Pain With The Help Of A Web-based Symptom Checker?
title_fullStr How Accurate Are Patients At Diagnosing The Cause Of Their Knee Pain With The Help Of A Web-based Symptom Checker?
title_full_unstemmed How Accurate Are Patients At Diagnosing The Cause Of Their Knee Pain With The Help Of A Web-based Symptom Checker?
title_short How Accurate Are Patients At Diagnosing The Cause Of Their Knee Pain With The Help Of A Web-based Symptom Checker?
title_sort how accurate are patients at diagnosing the cause of their knee pain with the help of a web-based symptom checker?
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4901722/
http://dx.doi.org/10.1177/2325967115S00150
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