Abstract:
BACKGROUND:Real-world data on the benefit/risk profile of medicines is needed, particularly in patients who are ineligible for randomised controlled trials conducted for registration purposes. This paper describes the methodology and source data verification which enables the conduct of pre-licensing clinical trials of COPD and asthma in the community using the electronic medical record (EMR), NorthWest EHealth linked database (NWEH-LDB) and alert systems. METHODS:Dual verification of extracts into NWEH-LDB was performed using two independent data sources (Salford Integrated Record [SIR] and Apollo database) from one primary care practice in Salford (N = 3504). A feasibility study was conducted to test the reliability of the NWEH-LDB to support longitudinal data analysis and pragmatic clinical trials in asthma and COPD. This involved a retrospective extraction of data from all registered practices in Salford to identify a cohort of patients with a diagnosis of asthma (aged ≥18) and/or COPD (aged ≥40) and ≥2 prescriptions for inhaled bronchodilators during 2008. Health care resource utilisation (HRU) outcomes during 2009 were assessed. Exacerbations were defined as: prescription for oral corticosteroids (OCS) in asthma and prescription of OCS or antibiotics in COPD; and/or hospitalisation for a respiratory cause. RESULTS:Dual verification demonstrated consistency between SIR and Apollo data sources: 3453 (98.6%) patients were common to both systems; 99.9% of prescription records were matched and of 29,830 diagnosis records, one record was missing from Apollo and 272 (0.9%) from SIR. Identified COPD patients were also highly concordant (Kappa coefficient = 0.98). A total of 7981 asthma patients and 4478 COPD patients were identified within the NWEH-LDB. Cohort analyses enumerated the most commonly prescribed respiratory medication classes to be: inhaled corticosteroids (ICS) (42%) and ICS plus long-acting β2-agonist (LABA) (40%) in asthma; ICS plus LABA (55%) and long-acting muscarinic antagonists (36%) in COPD. During 2009 HRU was greater in the COPD versus asthma cohorts, and exacerbation rates in 2009 were higher in patients who had ≥2 exacerbations versus ≤1 exacerbation in 2008 for both asthma (137.5 vs. 20.3 per 100 person-years, respectively) and COPD (144.6 vs. 41.0, respectively). CONCLUSION:Apollo and SIR data extracts into NWEH-LDB showed a high level of concordance for asthma and COPD patients. Longitudinal data analysis characterized the COPD and asthma populations in Salford including medications prescribed and health care utilisation outcomes suitable for clinical trial planning.
journal_name
BMC Med Inform Decis Makjournal_title
BMC medical informatics and decision makingauthors
Elkhenini HF,Davis KJ,Stein ND,New JP,Delderfield MR,Gibson M,Vestbo J,Woodcock A,Bakerly NDdoi
10.1186/s12911-015-0132-zsubject
Has Abstractpub_date
2015-02-07 00:00:00pages
8issn
1472-6947pii
10.1186/s12911-015-0132-zjournal_volume
15pub_type
杂志文章abstract:BACKGROUND:Electronic medical records (EMRs) contain a variety of valuable medical concepts and relations. The ability to recognize relations between medical concepts described in EMRs enables the automatic processing of clinical texts, resulting in an improved quality of health-related data analysis. Driven by the 201...
journal_title:BMC medical informatics and decision making
pub_type: 杂志文章
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更新日期:2019-04-09 00:00:00
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journal_title:BMC medical informatics and decision making
pub_type: 杂志文章
doi:10.1186/1472-6947-6-13
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abstract:BACKGROUND:In recent years, a significant change has taken place in the health care delivery systems due to the availability of smartphones and mobile software applications. The use of mobile technology can help to reduce a number of barriers for mental health care such as providers' workload, lack of qualified personn...
journal_title:BMC medical informatics and decision making
pub_type: 杂志文章
doi:10.1186/s12911-021-01386-0
更新日期:2021-01-19 00:00:00
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journal_title:BMC medical informatics and decision making
pub_type: 杂志文章,评审
doi:10.1186/s12911-017-0415-7
更新日期:2017-02-23 00:00:00
abstract:BACKGROUND:The District Health Information Software-2 (DHIS2) is widely used by countries for national-level aggregate reporting of health-data. To best leverage DHIS2 data for decision-making, countries need to ensure that data within their systems are of the highest quality. Comprehensive, systematic, and transparent...
journal_title:BMC medical informatics and decision making
pub_type: 杂志文章
doi:10.1186/s12911-020-01315-7
更新日期:2020-11-13 00:00:00
abstract:BACKGROUND:Health numeracy is an important factor in how well people make decisions based on medical risk information. However, in many countries, including Japan, numeracy studies have been limited. METHODS:To fill this gap, we evaluated health numeracy levels in a sample of Japanese adults by translating two well-kn...
journal_title:BMC medical informatics and decision making
pub_type: 杂志文章
doi:10.1186/1472-6947-12-104
更新日期:2012-09-11 00:00:00
abstract:BACKGROUND:The chronic kidney disease (CKD) is a worldwide critical problem, especially in developing countries. CKD patients usually begin their treatment in advanced stages, which requires dialysis and kidney transplantation, and consequently, affects mortality rates. This issue is faced by a mobile health (mHealth) ...
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journal_title:BMC medical informatics and decision making
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更新日期:2011-06-21 00:00:00
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pub_type: 杂志文章,随机对照试验
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更新日期:2013-08-15 00:00:00
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journal_title:BMC medical informatics and decision making
pub_type: 杂志文章,多中心研究
doi:10.1186/s12911-014-0101-y
更新日期:2014-11-25 00:00:00
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doi:10.1186/1472-6947-14-98
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journal_title:BMC medical informatics and decision making
pub_type: 杂志文章,meta分析
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更新日期:2015-03-21 00:00:00
abstract::In this editorial, we first summarize the 2018 International Conference on Intelligent Biology and Medicine (ICIBM 2018) that was held on June 10-12, 2018 in Los Angeles, California, USA, and then briefly introduce the six research articles included in this supplement issue. At ICIBM 2018, a special theme of Medical I...
journal_title:BMC medical informatics and decision making
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更新日期:2019-01-31 00:00:00