Identification of validated case definitions for medical conditions used in primary care electronic medical record databases: a systematic review

McBrien, Kerry; Souri, Sepideh; Symonds, Nicola E; Rouhi, Azin; Lethebe, Brendan Cord; Williamson, Tyler; Garies, Stephanie; Birtwhistle, Richard; Quan, Hude; Fabreau, Gabriel; Ronksley, Paul E.

doi:10.1093/jamia/ocy094

Cited by 44 publications

(39 citation statements)

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“…38 The use of electronic health records for epidemiological research largely relies upon the accuracy of documenting by the healthcare professionals contributing to the dataset. A limitation of using such records is that no study has validated the Read codes relating to childhood maltreatment and mental ill health in UK primary care, 41 however, work has been done to try and improve maltreatment-related coding in primary care. 26 We selected the Read codes relating to outcomes with the assistance of individuals trained in psychiatry, and to mitigate any misclassification risk, we also conducted the analysis pertaining to prescription data which is coded accurately.…”

Section: Discussionmentioning

confidence: 99%

The burden of mental ill health associated with childhood maltreatment in the UK, using The Health Improvement Network database: a population-based retrospective cohort study

Chandan

Thomas

Gokhale

et al. 2019

The Lancet Psychiatry

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Section: Discussionmentioning

confidence: 99%

The burden of mental ill health associated with childhood maltreatment in the UK, using The Health Improvement Network database: a population-based retrospective cohort study

Chandan

Thomas

Gokhale

et al. 2019

The Lancet Psychiatry

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“…Few reviews [ 9 - 12 ] have been published on developing EMR case definitions or phenotyping algorithms for selected chronic conditions, but none specifically cover all of the Charlson comorbidities. Furthermore, these articles narrowed their scope to specific perspectives [ 10 ] or specific settings (eg, inpatient or primary care only) [ 9 , 11 ]. These reviews report few studies utilizing natural language processing (NLP) or machine learning (ML), which emphasizes the importance of data science techniques (eg, deep learning) in the present health research.…”

Section: Introductionmentioning

confidence: 99%

Electronic Medical Record–Based Case Phenotyping for the Charlson Conditions: Scoping Review

Lee¹,

Doktorchik²,

Martin³

et al. 2021

JMIR Med Inform

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Background Electronic medical records (EMRs) contain large amounts of rich clinical information. Developing EMR-based case definitions, also known as EMR phenotyping, is an active area of research that has implications for epidemiology, clinical care, and health services research. Objective This review aims to describe and assess the present landscape of EMR-based case phenotyping for the Charlson conditions. Methods A scoping review of EMR-based algorithms for defining the Charlson comorbidity index conditions was completed. This study covered articles published between January 2000 and April 2020, both inclusive. Embase (Excerpta Medica database) and MEDLINE (Medical Literature Analysis and Retrieval System Online) were searched using keywords developed in the following 3 domains: terms related to EMR, terms related to case finding, and disease-specific terms. The manuscript follows the Preferred Reporting Items for Systematic reviews and Meta-analyses extension for Scoping Reviews (PRISMA) guidelines. Results A total of 274 articles representing 299 algorithms were assessed and summarized. Most studies were undertaken in the United States (181/299, 60.5%), followed by the United Kingdom (42/299, 14.0%) and Canada (15/299, 5.0%). These algorithms were mostly developed either in primary care (103/299, 34.4%) or inpatient (168/299, 56.2%) settings. Diabetes, congestive heart failure, myocardial infarction, and rheumatology had the highest number of developed algorithms. Data-driven and clinical rule–based approaches have been identified. EMR-based phenotype and algorithm development reflect the data access allowed by respective health systems, and algorithms vary in their performance. Conclusions Recognizing similarities and differences in health systems, data collection strategies, extraction, data release protocols, and existing clinical pathways is critical to algorithm development strategies. Several strategies to assist with phenotype-based case definitions have been proposed.

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“…The use of UK primary care records for epidemiological research relies upon the accuracy of documenting by the healthcare professionals contributing to the dataset. A limitation of the study is the exposure and outcome Read codes have not yet been validated against clinical notes (McBrien et al., 2018). Previous work conducted using the THIN database exploring the incidence and prevalence of domestic abuse in a primary care cohort suggests that substantial under‐recording when compared to self‐reported national survey estimates (Chandan, 2020; Chandan, Gokhale, et al., 2020; Chandan, Taylor, et al., 2020; Jeyaraman & Chandan, 2020; Office For National Statistics, 2016).…”

Section: Discussionmentioning

confidence: 99%

The association between exposure to domestic abuse in women and the development of syndromes indicating central nervous system sensitization: A retrospective cohort study using UK primary care records

Chandan

Keerthy

Gokhale

et al. 2021

European Journal of Pain

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Background Domestic abuse is a global public health issue. The association between the development of central sensitivity syndromes (CSS) and previous exposure to domestic abuse has been poorly understood particularly within European populations. Methods A retrospective cohort study using the ‘The Health Improvement Network,’ (UK primary care medical records) between 1st January 1995–31st December 2018. 22,604 adult women exposed to domestic abuse were age matched to 44,671 unexposed women. The average age at cohort entry was 36 years and the median follow‐up was 2.5 years. The outcomes of interest were the development of a variety of syndromes which demonstrate central nervous system sensitization. Fibromyalgia, chronic fatigue syndrome and temporomandibular joint disorder outcomes have been reported previously. Outcomes were adjusted for the presence of mental ill health. Results During the study period, women exposed to domestic abuse experienced an increased risk of developing chronic lower back pain (adjusted incidence rate ratio [aIRR] 2.28; 95% CI 1.85–2.80), chronic headaches (aIRR 3.15; 95% CI 1.07–9.23), irritable bowel syndrome (aIRR 1.41; 95% CI 1.25–1.60) and restless legs syndrome (aIRR 1.89; 95% CI 1.44–2.48). However, no positive association was seen with the development of interstitial cystitis (aIRR 0.52; 95% CI 0.14–1.93), vulvodynia (aIRR 0.42; 95% CI 0.14–1.25) and myofascial pain syndrome (aIRR 1.01; 95% CI 0.28–3.61). Conclusion This study demonstrates the need to consider a past history of domestic abuse in patients presenting with CSS; and also consider preventative approaches in mitigating the risk of developing CSS following exposure to domestic abuse. Significance Domestic abuse is a global public health issue, with a poorly understood relationship with the development of complex pain syndromes. Using a large UK primary care database, we were able to conduct the first global cohort study to explore this further. We found a strong pain morbidity burden associated with domestic abuse, suggesting the need for urgent public health intervention to not only prevent domestic abuse but also the associated negative pain consequences.

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Identification of validated case definitions for medical conditions used in primary care electronic medical record databases: a systematic review

Abstract: PROSPERO CRD42016040020 (submitted June 8, 2016, and last revised June 14, 2016).

Cited by 44 publications

References 50 publications

The burden of mental ill health associated with childhood maltreatment in the UK, using The Health Improvement Network database: a population-based retrospective cohort study

The burden of mental ill health associated with childhood maltreatment in the UK, using The Health Improvement Network database: a population-based retrospective cohort study

Electronic Medical Record–Based Case Phenotyping for the Charlson Conditions: Scoping Review

The association between exposure to domestic abuse in women and the development of syndromes indicating central nervous system sensitization: A retrospective cohort study using UK primary care records

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