Cargando…
The quality of vital signs measurements and value preferences in electronic medical records varies by hospital, specialty, and patient demographics
We aimed to assess the frequency of value preferences in recording of vital signs in electronic healthcare records (EHRs) and associated patient and hospital factors. We used EHR data from Oxford University Hospitals, UK, between 01-January-2016 and 30-June-2019 and a maximum likelihood estimator to...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9995491/ https://www.ncbi.nlm.nih.gov/pubmed/36890179 http://dx.doi.org/10.1038/s41598-023-30691-z |
_version_ | 1784902836761395200 |
---|---|
author | Jackson, Niall Woods, Jessica Watkinson, Peter Brent, Andrew Peto, Tim E. A. Walker, A. Sarah Eyre, David W. |
author_facet | Jackson, Niall Woods, Jessica Watkinson, Peter Brent, Andrew Peto, Tim E. A. Walker, A. Sarah Eyre, David W. |
author_sort | Jackson, Niall |
collection | PubMed |
description | We aimed to assess the frequency of value preferences in recording of vital signs in electronic healthcare records (EHRs) and associated patient and hospital factors. We used EHR data from Oxford University Hospitals, UK, between 01-January-2016 and 30-June-2019 and a maximum likelihood estimator to determine the prevalence of value preferences in measurements of systolic and diastolic blood pressure (SBP/DBP), heart rate (HR) (readings ending in zero), respiratory rate (multiples of 2 or 4), and temperature (readings of 36.0 °C). We used multivariable logistic regression to investigate associations between value preferences and patient age, sex, ethnicity, deprivation, comorbidities, calendar time, hour of day, days into admission, hospital, day of week and speciality. In 4,375,654 records from 135,173 patients, there was an excess of temperature readings of 36.0 °C above that expected from the underlying distribution that affected 11.3% (95% CI 10.6–12.1%) of measurements, i.e. these observations were likely inappropriately recorded as 36.0 °C instead of the true value. SBP, DBP and HR were rounded to the nearest 10 in 2.2% (1.4–2.8%) and 2.0% (1.3–5.1%) and 2.4% (1.7–3.1%) of measurements. RR was also more commonly recorded as multiples of 2. BP digit preference and an excess of temperature recordings of 36.0 °C were more common in older and male patients, as length of stay increased, following a previous normal set of vital signs and typically more common in medical vs. surgical specialities. Differences were seen between hospitals, however, digit preference reduced over calendar time. Vital signs may not always be accurately documented, and this may vary by patient groups and hospital settings. Allowances and adjustments may be needed in delivering care to patients and in observational analyses and predictive tools using these factors as outcomes or exposures. |
format | Online Article Text |
id | pubmed-9995491 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-99954912023-03-10 The quality of vital signs measurements and value preferences in electronic medical records varies by hospital, specialty, and patient demographics Jackson, Niall Woods, Jessica Watkinson, Peter Brent, Andrew Peto, Tim E. A. Walker, A. Sarah Eyre, David W. Sci Rep Article We aimed to assess the frequency of value preferences in recording of vital signs in electronic healthcare records (EHRs) and associated patient and hospital factors. We used EHR data from Oxford University Hospitals, UK, between 01-January-2016 and 30-June-2019 and a maximum likelihood estimator to determine the prevalence of value preferences in measurements of systolic and diastolic blood pressure (SBP/DBP), heart rate (HR) (readings ending in zero), respiratory rate (multiples of 2 or 4), and temperature (readings of 36.0 °C). We used multivariable logistic regression to investigate associations between value preferences and patient age, sex, ethnicity, deprivation, comorbidities, calendar time, hour of day, days into admission, hospital, day of week and speciality. In 4,375,654 records from 135,173 patients, there was an excess of temperature readings of 36.0 °C above that expected from the underlying distribution that affected 11.3% (95% CI 10.6–12.1%) of measurements, i.e. these observations were likely inappropriately recorded as 36.0 °C instead of the true value. SBP, DBP and HR were rounded to the nearest 10 in 2.2% (1.4–2.8%) and 2.0% (1.3–5.1%) and 2.4% (1.7–3.1%) of measurements. RR was also more commonly recorded as multiples of 2. BP digit preference and an excess of temperature recordings of 36.0 °C were more common in older and male patients, as length of stay increased, following a previous normal set of vital signs and typically more common in medical vs. surgical specialities. Differences were seen between hospitals, however, digit preference reduced over calendar time. Vital signs may not always be accurately documented, and this may vary by patient groups and hospital settings. Allowances and adjustments may be needed in delivering care to patients and in observational analyses and predictive tools using these factors as outcomes or exposures. Nature Publishing Group UK 2023-03-08 /pmc/articles/PMC9995491/ /pubmed/36890179 http://dx.doi.org/10.1038/s41598-023-30691-z 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Jackson, Niall Woods, Jessica Watkinson, Peter Brent, Andrew Peto, Tim E. A. Walker, A. Sarah Eyre, David W. The quality of vital signs measurements and value preferences in electronic medical records varies by hospital, specialty, and patient demographics |
title | The quality of vital signs measurements and value preferences in electronic medical records varies by hospital, specialty, and patient demographics |
title_full | The quality of vital signs measurements and value preferences in electronic medical records varies by hospital, specialty, and patient demographics |
title_fullStr | The quality of vital signs measurements and value preferences in electronic medical records varies by hospital, specialty, and patient demographics |
title_full_unstemmed | The quality of vital signs measurements and value preferences in electronic medical records varies by hospital, specialty, and patient demographics |
title_short | The quality of vital signs measurements and value preferences in electronic medical records varies by hospital, specialty, and patient demographics |
title_sort | quality of vital signs measurements and value preferences in electronic medical records varies by hospital, specialty, and patient demographics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9995491/ https://www.ncbi.nlm.nih.gov/pubmed/36890179 http://dx.doi.org/10.1038/s41598-023-30691-z |
work_keys_str_mv | AT jacksonniall thequalityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT woodsjessica thequalityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT watkinsonpeter thequalityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT brentandrew thequalityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT petotimea thequalityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT walkerasarah thequalityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT eyredavidw thequalityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT jacksonniall qualityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT woodsjessica qualityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT watkinsonpeter qualityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT brentandrew qualityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT petotimea qualityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT walkerasarah qualityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics AT eyredavidw qualityofvitalsignsmeasurementsandvaluepreferencesinelectronicmedicalrecordsvariesbyhospitalspecialtyandpatientdemographics |