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The feasibility and impact of implementing a computer-guided consultation to target health inequality in Asthma

Greater Manchester has a greater prevalence and worse asthma outcomes than the national average. This study aims to evaluate a digital approach to primary care asthma management and in particular the initial impact of implementing Clinical Decision Support System software in the form of a computer-g...

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Autores principales: Chakrabarti, B., Kane, B., Barrow, C., Stonebanks, J., Reed, L., Pearson, M. G., Davies, L., Osborne, M., England, P., Litchfield, D., McKnight, E., Angus, R. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903267/
https://www.ncbi.nlm.nih.gov/pubmed/36750578
http://dx.doi.org/10.1038/s41533-023-00329-8
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author Chakrabarti, B.
Kane, B.
Barrow, C.
Stonebanks, J.
Reed, L.
Pearson, M. G.
Davies, L.
Osborne, M.
England, P.
Litchfield, D.
McKnight, E.
Angus, R. M.
author_facet Chakrabarti, B.
Kane, B.
Barrow, C.
Stonebanks, J.
Reed, L.
Pearson, M. G.
Davies, L.
Osborne, M.
England, P.
Litchfield, D.
McKnight, E.
Angus, R. M.
author_sort Chakrabarti, B.
collection PubMed
description Greater Manchester has a greater prevalence and worse asthma outcomes than the national average. This study aims to evaluate a digital approach to primary care asthma management and in particular the initial impact of implementing Clinical Decision Support System software in the form of a computer-guided consultation (CGC) in the setting of primary care asthma reviews in deprived areas of Greater Manchester. The CGC (LungHealth Ltd) is an intelligent decision support system ensuring accurate guideline-based staging of asthma and assessment of asthma control with the software subsequently prompting guideline-standard management. Patients on asthma registers in Greater Manchester Primary Care Networks were identified and underwent remote review by nursing staff using the CGC linked directly to the GP clinical system. Three-hundred thirty-eight patients (mean age 59 (SD 17) years; 60% Female) were reviewed. The CGC reported the patient’s asthma control to be “Good” in 22%, “Partial” in 6% and “Poor” in 72%. ACT scores were significantly higher in those patients exhibiting “Good” and “Partial” control when compared to those with “Poor” control. The number of steroid courses and hospital admissions in the previous 12 months was significantly lower in those patients exhibiting “Good” and “Partial” control when compared to those with “Poor” control. Nineteen percent were found not to have a personalised asthma management plan during CGC review, which was alerted by the CGC and subsequently, all but 3 patients had this created on review completion (McNemar’s test; p < 0.001). 5% were found not to have been prescribed regular inhaled steroid therapy resulting in the operator being alerted by the CGC in all cases. Overall, 44% underwent alteration in asthma therapy following the CGC review with 82% of these representing treatment escalation. An end-to-end digital service solution is feasible for Asthma within primary care and the utilisation of a CGC when conducting primary care asthma reviews increases implementation of guideline-level management thus addressing healthcare inequality while enabling identification of “high risk” asthma patients and guiding appropriate therapy escalation and de-escalation.
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spelling pubmed-99032672023-02-07 The feasibility and impact of implementing a computer-guided consultation to target health inequality in Asthma Chakrabarti, B. Kane, B. Barrow, C. Stonebanks, J. Reed, L. Pearson, M. G. Davies, L. Osborne, M. England, P. Litchfield, D. McKnight, E. Angus, R. M. NPJ Prim Care Respir Med Article Greater Manchester has a greater prevalence and worse asthma outcomes than the national average. This study aims to evaluate a digital approach to primary care asthma management and in particular the initial impact of implementing Clinical Decision Support System software in the form of a computer-guided consultation (CGC) in the setting of primary care asthma reviews in deprived areas of Greater Manchester. The CGC (LungHealth Ltd) is an intelligent decision support system ensuring accurate guideline-based staging of asthma and assessment of asthma control with the software subsequently prompting guideline-standard management. Patients on asthma registers in Greater Manchester Primary Care Networks were identified and underwent remote review by nursing staff using the CGC linked directly to the GP clinical system. Three-hundred thirty-eight patients (mean age 59 (SD 17) years; 60% Female) were reviewed. The CGC reported the patient’s asthma control to be “Good” in 22%, “Partial” in 6% and “Poor” in 72%. ACT scores were significantly higher in those patients exhibiting “Good” and “Partial” control when compared to those with “Poor” control. The number of steroid courses and hospital admissions in the previous 12 months was significantly lower in those patients exhibiting “Good” and “Partial” control when compared to those with “Poor” control. Nineteen percent were found not to have a personalised asthma management plan during CGC review, which was alerted by the CGC and subsequently, all but 3 patients had this created on review completion (McNemar’s test; p < 0.001). 5% were found not to have been prescribed regular inhaled steroid therapy resulting in the operator being alerted by the CGC in all cases. Overall, 44% underwent alteration in asthma therapy following the CGC review with 82% of these representing treatment escalation. An end-to-end digital service solution is feasible for Asthma within primary care and the utilisation of a CGC when conducting primary care asthma reviews increases implementation of guideline-level management thus addressing healthcare inequality while enabling identification of “high risk” asthma patients and guiding appropriate therapy escalation and de-escalation. Nature Publishing Group UK 2023-02-07 /pmc/articles/PMC9903267/ /pubmed/36750578 http://dx.doi.org/10.1038/s41533-023-00329-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Chakrabarti, B.
Kane, B.
Barrow, C.
Stonebanks, J.
Reed, L.
Pearson, M. G.
Davies, L.
Osborne, M.
England, P.
Litchfield, D.
McKnight, E.
Angus, R. M.
The feasibility and impact of implementing a computer-guided consultation to target health inequality in Asthma
title The feasibility and impact of implementing a computer-guided consultation to target health inequality in Asthma
title_full The feasibility and impact of implementing a computer-guided consultation to target health inequality in Asthma
title_fullStr The feasibility and impact of implementing a computer-guided consultation to target health inequality in Asthma
title_full_unstemmed The feasibility and impact of implementing a computer-guided consultation to target health inequality in Asthma
title_short The feasibility and impact of implementing a computer-guided consultation to target health inequality in Asthma
title_sort feasibility and impact of implementing a computer-guided consultation to target health inequality in asthma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903267/
https://www.ncbi.nlm.nih.gov/pubmed/36750578
http://dx.doi.org/10.1038/s41533-023-00329-8
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