13 Clinical informatics to direct community echocardiography: an electronic healthcare record pilot. (4th June 2021)
- Record Type:
- Journal Article
- Title:
- 13 Clinical informatics to direct community echocardiography: an electronic healthcare record pilot. (4th June 2021)
- Main Title:
- 13 Clinical informatics to direct community echocardiography: an electronic healthcare record pilot
- Authors:
- Mbonye, Kamatamu Amanda
Yazdi, Alireza
Cashin, Shane
Ahluwalia, Nikhil
Laskar, Nabila
Bhattacharyya, Sanjeev
Hayward, Carl
Lloyd, Guy
Joshi, Abhishek - Abstract:
- Abstract : Background: Delayed diagnosis of valvular heart disease carries a poor prognosis, and early identification is desirable. We undertook a retrospective analysis of echocardiographic and electronic health care record data from the largest single cardiovascular service in the UK, to identify the burden of acute presentations with previously undiagnosed valvular heart disease and to determine the geographical and demographic distribution. Methods and Results: Automated text mining analysis was retrospectively applied to all echocardiographic examinations performed between 2015 and 2019 at Bart's Health NHS trust, identifying 2043 reports containing text or numerical data indicating severe valvular lesions. Demographic and clinical data was integrated with the echocardiographic dataset, identifying the postcode and GP practices for with the highest proportion of patients with severe valvular disease that were diagnosed during acute inpatient admissions. 376 individuals had severe valvular lesions identified during acute admission, of which 269 (72%) had no previously documented echocardiogram. A cluster of 11 GP practices (9%, 11 of 117 practices) were identified as having a higher proportion of diagnoses of severe valvular disease on acute admissions [ figure 1 ]. These 11 were plotted geographically, alongside correlating postcodes, to identify geographical hotspots [ figure 2 ]. Analyses were undertaken using Matlab, R and ggplot2. Conclusions: A geographical clusterAbstract : Background: Delayed diagnosis of valvular heart disease carries a poor prognosis, and early identification is desirable. We undertook a retrospective analysis of echocardiographic and electronic health care record data from the largest single cardiovascular service in the UK, to identify the burden of acute presentations with previously undiagnosed valvular heart disease and to determine the geographical and demographic distribution. Methods and Results: Automated text mining analysis was retrospectively applied to all echocardiographic examinations performed between 2015 and 2019 at Bart's Health NHS trust, identifying 2043 reports containing text or numerical data indicating severe valvular lesions. Demographic and clinical data was integrated with the echocardiographic dataset, identifying the postcode and GP practices for with the highest proportion of patients with severe valvular disease that were diagnosed during acute inpatient admissions. 376 individuals had severe valvular lesions identified during acute admission, of which 269 (72%) had no previously documented echocardiogram. A cluster of 11 GP practices (9%, 11 of 117 practices) were identified as having a higher proportion of diagnoses of severe valvular disease on acute admissions [ figure 1 ]. These 11 were plotted geographically, alongside correlating postcodes, to identify geographical hotspots [ figure 2 ]. Analyses were undertaken using Matlab, R and ggplot2. Conclusions: A geographical cluster of GP practices, centred around a single hospital, had a higher proportion of patients diagnosed with severe valvular disease during acute admissions without a previous echocardiogram. Outreach echocardiography provision in these regions could potentially identify patients with valvular disease before acute decompensation. Further work should focus on improving methodology to identify cases and investigating risk factors that predispose to diagnosis of severe valvular disease in extremis. Conflict of Interest: none … (more)
- Is Part Of:
- Heart. Volume 107(2021)Supplement 1
- Journal:
- Heart
- Issue:
- Volume 107(2021)Supplement 1
- Issue Display:
- Volume 107, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 107
- Issue:
- 1
- Issue Sort Value:
- 2021-0107-0001-0000
- Page Start:
- A10
- Page End:
- A11
- Publication Date:
- 2021-06-04
- Subjects:
- Echocardiography -- Clinical Informatics -- Valves
Heart -- Diseases -- Treatment -- Periodicals
Cardiology -- Periodicals
616.12 - Journal URLs:
- http://www.bmj.com/archive ↗
http://heart.bmj.com ↗
http://www.heartjnl.com ↗ - DOI:
- 10.1136/heartjnl-2021-BCS.13 ↗
- Languages:
- English
- ISSNs:
- 1355-6037
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25293.xml