Cargando…

The internal validation of weight and weight change coding using weight measurement data within the UK primary care Electronic Health Record

PURPOSE: To use recorded weight values to internally validate weight status and weight change coding in the primary care Electronic Health Record (EHR). PATIENTS AND METHODS: We included adult patients with weight-related Read codes recorded in the UK’s Clinical Practice Research Datalink EHR betwee...

Descripción completa

Detalles Bibliográficos
Autores principales: Nicholson, Brian D, Aveyard, Paul, Hamilton, Willie, Bankhead, Clare R, Koshiaris, Constantinos, Stevens, Sarah, Hobbs, Frederick DR, Perera, Rafael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6354686/
https://www.ncbi.nlm.nih.gov/pubmed/30774449
http://dx.doi.org/10.2147/CLEP.S189989
_version_ 1783391218168758272
author Nicholson, Brian D
Aveyard, Paul
Hamilton, Willie
Bankhead, Clare R
Koshiaris, Constantinos
Stevens, Sarah
Hobbs, Frederick DR
Perera, Rafael
author_facet Nicholson, Brian D
Aveyard, Paul
Hamilton, Willie
Bankhead, Clare R
Koshiaris, Constantinos
Stevens, Sarah
Hobbs, Frederick DR
Perera, Rafael
author_sort Nicholson, Brian D
collection PubMed
description PURPOSE: To use recorded weight values to internally validate weight status and weight change coding in the primary care Electronic Health Record (EHR). PATIENTS AND METHODS: We included adult patients with weight-related Read codes recorded in the UK’s Clinical Practice Research Datalink EHR between 2000 and 2017. Weight status codes were compared to weight values recorded on the same day and positive predictive values (PPVs) were calculated for commonly used codes. Weight change codes were validated using three methods: the percentage (%) difference in kilograms at the time of the code and 1) the previous weight measurement, 2) the weight predicted using linear regression, and 3) the historic mean weight. Weight change codes were validated if estimates were consistent across two out of three methods. RESULTS: A total of 8,108,481 weight codes were recorded in 1,000,002 patients’ EHR. Twice as many were recorded in females (n=5,208,593, 64%). The mean body mass index for “overweight” codes ranged from 31.9 kg/m(2) to 46.9 kg/m(2) and from 17.4 kg/m(2) to 19.2 kg/m(2) for “underweight” codes. PPVs for the most commonly used weight status codes ranged from 81.3% (80%–82.5%) to 99.3% (99.2%–99.4%). Across the estimation methods, and using only validated weight change codes, mean weight loss ranged from – 5.2% (SD 5.8%) to −7.9% (SD 7.3%) and mean weight gain from 4.2 % (SD 5.5%) to 7.9 % (SD 8.2%). The previous and predicted weight methods were most consistent. CONCLUSION: We have developed an internationally applicable methodology to internally validate weight-related EHR coding by using available weight measurement data. We demonstrate the UK Read codes that can be confidently used to classify weight status and weight change in the absence of weight values. We provide the first evidence from primary care that a Read code for unexpected weight loss represents a mean loss of ≥ 5 % in a 6-month period, which was broadly consistent across age groups and gender.
format Online
Article
Text
id pubmed-6354686
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Dove Medical Press
record_format MEDLINE/PubMed
spelling pubmed-63546862019-02-15 The internal validation of weight and weight change coding using weight measurement data within the UK primary care Electronic Health Record Nicholson, Brian D Aveyard, Paul Hamilton, Willie Bankhead, Clare R Koshiaris, Constantinos Stevens, Sarah Hobbs, Frederick DR Perera, Rafael Clin Epidemiol Original Research PURPOSE: To use recorded weight values to internally validate weight status and weight change coding in the primary care Electronic Health Record (EHR). PATIENTS AND METHODS: We included adult patients with weight-related Read codes recorded in the UK’s Clinical Practice Research Datalink EHR between 2000 and 2017. Weight status codes were compared to weight values recorded on the same day and positive predictive values (PPVs) were calculated for commonly used codes. Weight change codes were validated using three methods: the percentage (%) difference in kilograms at the time of the code and 1) the previous weight measurement, 2) the weight predicted using linear regression, and 3) the historic mean weight. Weight change codes were validated if estimates were consistent across two out of three methods. RESULTS: A total of 8,108,481 weight codes were recorded in 1,000,002 patients’ EHR. Twice as many were recorded in females (n=5,208,593, 64%). The mean body mass index for “overweight” codes ranged from 31.9 kg/m(2) to 46.9 kg/m(2) and from 17.4 kg/m(2) to 19.2 kg/m(2) for “underweight” codes. PPVs for the most commonly used weight status codes ranged from 81.3% (80%–82.5%) to 99.3% (99.2%–99.4%). Across the estimation methods, and using only validated weight change codes, mean weight loss ranged from – 5.2% (SD 5.8%) to −7.9% (SD 7.3%) and mean weight gain from 4.2 % (SD 5.5%) to 7.9 % (SD 8.2%). The previous and predicted weight methods were most consistent. CONCLUSION: We have developed an internationally applicable methodology to internally validate weight-related EHR coding by using available weight measurement data. We demonstrate the UK Read codes that can be confidently used to classify weight status and weight change in the absence of weight values. We provide the first evidence from primary care that a Read code for unexpected weight loss represents a mean loss of ≥ 5 % in a 6-month period, which was broadly consistent across age groups and gender. Dove Medical Press 2019-01-25 /pmc/articles/PMC6354686/ /pubmed/30774449 http://dx.doi.org/10.2147/CLEP.S189989 Text en © 2019 Nicholson et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Nicholson, Brian D
Aveyard, Paul
Hamilton, Willie
Bankhead, Clare R
Koshiaris, Constantinos
Stevens, Sarah
Hobbs, Frederick DR
Perera, Rafael
The internal validation of weight and weight change coding using weight measurement data within the UK primary care Electronic Health Record
title The internal validation of weight and weight change coding using weight measurement data within the UK primary care Electronic Health Record
title_full The internal validation of weight and weight change coding using weight measurement data within the UK primary care Electronic Health Record
title_fullStr The internal validation of weight and weight change coding using weight measurement data within the UK primary care Electronic Health Record
title_full_unstemmed The internal validation of weight and weight change coding using weight measurement data within the UK primary care Electronic Health Record
title_short The internal validation of weight and weight change coding using weight measurement data within the UK primary care Electronic Health Record
title_sort internal validation of weight and weight change coding using weight measurement data within the uk primary care electronic health record
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6354686/
https://www.ncbi.nlm.nih.gov/pubmed/30774449
http://dx.doi.org/10.2147/CLEP.S189989
work_keys_str_mv AT nicholsonbriand theinternalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT aveyardpaul theinternalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT hamiltonwillie theinternalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT bankheadclarer theinternalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT koshiarisconstantinos theinternalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT stevenssarah theinternalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT hobbsfrederickdr theinternalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT pererarafael theinternalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT nicholsonbriand internalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT aveyardpaul internalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT hamiltonwillie internalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT bankheadclarer internalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT koshiarisconstantinos internalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT stevenssarah internalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT hobbsfrederickdr internalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord
AT pererarafael internalvalidationofweightandweightchangecodingusingweightmeasurementdatawithintheukprimarycareelectronichealthrecord