Assessing the accuracy of an inter-institutional automated patient-specific health problem list

<p>Abstract</p> <p>Background</p> <p>Health problem lists are a key component of electronic health records and are instrumental in the development of decision-support systems that encourage best practices and optimal patient safety. Most health problem lists require ini...

Full description

Bibliographic Details
Main Authors: Taylor Laurel, Poissant Lise, Huang Allen, Tamblyn Robyn
Format: Article
Language:English
Published: BMC 2010-02-01
Series:BMC Medical Informatics and Decision Making
Online Access:http://www.biomedcentral.com/1472-6947/10/10
id doaj-49b3cd426cd14ff09e2b32e4e8a5444b
record_format Article
spelling doaj-49b3cd426cd14ff09e2b32e4e8a5444b2020-11-24T23:44:03ZengBMCBMC Medical Informatics and Decision Making1472-69472010-02-011011010.1186/1472-6947-10-10Assessing the accuracy of an inter-institutional automated patient-specific health problem listTaylor LaurelPoissant LiseHuang AllenTamblyn Robyn<p>Abstract</p> <p>Background</p> <p>Health problem lists are a key component of electronic health records and are instrumental in the development of decision-support systems that encourage best practices and optimal patient safety. Most health problem lists require initial clinical information to be entered manually and few integrate information across care providers and institutions. This study assesses the accuracy of a novel approach to create an inter-institutional automated health problem list in a computerized medical record (MOXXI) that integrates three sources of information for an individual patient: diagnostic codes from medical services claims from all treating physicians, therapeutic indications from electronic prescriptions, and single-indication drugs.</p> <p>Methods</p> <p>Data for this study were obtained from 121 general practitioners and all medical services provided for 22,248 of their patients. At the opening of a patient's file, all health problems detected through medical service utilization or single-indication drug use were flagged to the physician in the MOXXI system. Each new arising health problem were presented as 'potential' and physicians were prompted to specify if the health problem was valid (Y) or not (N) or if they preferred to reassess its validity at a later time.</p> <p>Results</p> <p>A total of 263,527 health problems, representing 891 unique problems, were identified for the group of 22,248 patients. Medical services claims contributed to the majority of problems identified (77%), followed by therapeutic indications from electronic prescriptions (14%), and single-indication drugs (9%). Physicians actively chose to assess 41.7% (n = 106,950) of health problems. Overall, 73% of the problems assessed were considered valid; 42% originated from medical service diagnostic codes, 11% from single indication drugs, and 47% from prescription indications. Twelve percent of problems identified through other treating physicians were considered valid compared to 28% identified through study physician claims.</p> <p>Conclusion</p> <p>Automation of an inter-institutional problem list added over half of all validated problems to the health problem list of which 12% were generated by conditions treated by other physicians. Automating the integration of existing information sources provides timely access to accurate and relevant health problem information. It may also accelerate the uptake and use of electronic medical record systems.</p> http://www.biomedcentral.com/1472-6947/10/10
collection DOAJ
language English
format Article
sources DOAJ
author Taylor Laurel
Poissant Lise
Huang Allen
Tamblyn Robyn
spellingShingle Taylor Laurel
Poissant Lise
Huang Allen
Tamblyn Robyn
Assessing the accuracy of an inter-institutional automated patient-specific health problem list
BMC Medical Informatics and Decision Making
author_facet Taylor Laurel
Poissant Lise
Huang Allen
Tamblyn Robyn
author_sort Taylor Laurel
title Assessing the accuracy of an inter-institutional automated patient-specific health problem list
title_short Assessing the accuracy of an inter-institutional automated patient-specific health problem list
title_full Assessing the accuracy of an inter-institutional automated patient-specific health problem list
title_fullStr Assessing the accuracy of an inter-institutional automated patient-specific health problem list
title_full_unstemmed Assessing the accuracy of an inter-institutional automated patient-specific health problem list
title_sort assessing the accuracy of an inter-institutional automated patient-specific health problem list
publisher BMC
series BMC Medical Informatics and Decision Making
issn 1472-6947
publishDate 2010-02-01
description <p>Abstract</p> <p>Background</p> <p>Health problem lists are a key component of electronic health records and are instrumental in the development of decision-support systems that encourage best practices and optimal patient safety. Most health problem lists require initial clinical information to be entered manually and few integrate information across care providers and institutions. This study assesses the accuracy of a novel approach to create an inter-institutional automated health problem list in a computerized medical record (MOXXI) that integrates three sources of information for an individual patient: diagnostic codes from medical services claims from all treating physicians, therapeutic indications from electronic prescriptions, and single-indication drugs.</p> <p>Methods</p> <p>Data for this study were obtained from 121 general practitioners and all medical services provided for 22,248 of their patients. At the opening of a patient's file, all health problems detected through medical service utilization or single-indication drug use were flagged to the physician in the MOXXI system. Each new arising health problem were presented as 'potential' and physicians were prompted to specify if the health problem was valid (Y) or not (N) or if they preferred to reassess its validity at a later time.</p> <p>Results</p> <p>A total of 263,527 health problems, representing 891 unique problems, were identified for the group of 22,248 patients. Medical services claims contributed to the majority of problems identified (77%), followed by therapeutic indications from electronic prescriptions (14%), and single-indication drugs (9%). Physicians actively chose to assess 41.7% (n = 106,950) of health problems. Overall, 73% of the problems assessed were considered valid; 42% originated from medical service diagnostic codes, 11% from single indication drugs, and 47% from prescription indications. Twelve percent of problems identified through other treating physicians were considered valid compared to 28% identified through study physician claims.</p> <p>Conclusion</p> <p>Automation of an inter-institutional problem list added over half of all validated problems to the health problem list of which 12% were generated by conditions treated by other physicians. Automating the integration of existing information sources provides timely access to accurate and relevant health problem information. It may also accelerate the uptake and use of electronic medical record systems.</p>
url http://www.biomedcentral.com/1472-6947/10/10
work_keys_str_mv AT taylorlaurel assessingtheaccuracyofaninterinstitutionalautomatedpatientspecifichealthproblemlist
AT poissantlise assessingtheaccuracyofaninterinstitutionalautomatedpatientspecifichealthproblemlist
AT huangallen assessingtheaccuracyofaninterinstitutionalautomatedpatientspecifichealthproblemlist
AT tamblynrobyn assessingtheaccuracyofaninterinstitutionalautomatedpatientspecifichealthproblemlist
_version_ 1725500265398796288