Principles for Safe Implementation of ICD Codes for Human Trafficking

2021 ◽  
Vol 49 (2) ◽  
pp. 285-289 ◽  
Author(s):  
Jordan Greenbaum ◽  
Ashley Garrett ◽  
Katherine Chon ◽  
Matthew Bishop ◽  
Jordan Luke ◽  
...  
Keyword(s):  
Mental Health ◽  
Electronic Health Records ◽  
Human Trafficking ◽  
Health Consequences ◽  
Health Records ◽  
Adverse Health ◽  
Icd Codes ◽  
Electronic Health

AbstractHuman trafficking is associated with a variety of adverse health and mental health consequences, which should be accurately addressed and documented in electronic health records.

scholarly journals Incorporating natural language processing to improve classification of axial spondyloarthritis using electronic health records

Rheumatology ◽  
2019 ◽  
Vol 59 (5) ◽  
pp. 1059-1065 ◽  
Author(s):  
Sizheng Steven Zhao ◽  
Chuan Hong ◽  
Tianrun Cai ◽  
Chang Xu ◽  
Jie Huang ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Free Text ◽  
Text Data ◽  
Health Records ◽  
Disease Concepts ◽  
Icd Codes ◽  
Electronic Health

Abstract Objectives To develop classification algorithms that accurately identify axial SpA (axSpA) patients in electronic health records, and compare the performance of algorithms incorporating free-text data against approaches using only International Classification of Diseases (ICD) codes. Methods An enriched cohort of 7853 eligible patients was created from electronic health records of two large hospitals using automated searches (⩾1 ICD codes combined with simple text searches). Key disease concepts from free-text data were extracted using NLP and combined with ICD codes to develop algorithms. We created both supervised regression-based algorithms—on a training set of 127 axSpA cases and 423 non-cases—and unsupervised algorithms to identify patients with high probability of having axSpA from the enriched cohort. Their performance was compared against classifications using ICD codes only. Results NLP extracted four disease concepts of high predictive value: ankylosing spondylitis, sacroiliitis, HLA-B27 and spondylitis. The unsupervised algorithm, incorporating both the NLP concept and ICD code for AS, identified the greatest number of patients. By setting the probability threshold to attain 80% positive predictive value, it identified 1509 axSpA patients (mean age 53 years, 71% male). Sensitivity was 0.78, specificity 0.94 and area under the curve 0.93. The two supervised algorithms performed similarly but identified fewer patients. All three outperformed traditional approaches using ICD codes alone (area under the curve 0.80–0.87). Conclusion Algorithms incorporating free-text data can accurately identify axSpA patients in electronic health records. Large cohorts identified using these novel methods offer exciting opportunities for future clinical research.

scholarly journals Maximizing the use of social and behavioural information from secondary care mental health electronic health records

2020 ◽  
Vol 107 ◽  
pp. 103429
Author(s):  
S.M. Goodday ◽  
A. Kormilitzin ◽  
N. Vaci ◽  
Q. Liu ◽  
A. Cipriani ◽  
...  
Keyword(s):  
Mental Health ◽  
Electronic Health Records ◽  
Secondary Care ◽  
Health Records ◽  
Electronic Health

scholarly journals Evaluation of Smoking Status Identification Using Electronic Health Records and Open-Text Information in a Large Mental Health Case Register

PLoS ONE ◽  
2013 ◽  
Vol 8 (9) ◽  
pp. e74262 ◽  
Author(s):  
Chia-Yi Wu ◽  
Chin-Kuo Chang ◽  
Debbie Robson ◽  
Richard Jackson ◽  
Shaw-Ji Chen ◽  
...  
Keyword(s):  
Mental Health ◽  
Electronic Health Records ◽  
Smoking Status ◽  
Health Records ◽  
Case Register ◽  
Text Information ◽  
Electronic Health

scholarly journals Mining Electronic Health Records Data: Domestic Violence and Adverse Health Effects

2016 ◽  
Vol 32 (1) ◽  
pp. 79-87 ◽  
Author(s):  
Gunnur Karakurt ◽  
Vishal Patel ◽  
Kathleen Whiting ◽  
Mehmet Koyutürk
Keyword(s):  
Domestic Violence ◽  
Electronic Health Records ◽  
Health Effects ◽  
Health Records ◽  
Adverse Health Effects ◽  
Adverse Health ◽  
Electronic Health

scholarly journals Neutrophil-lymphocyte ratio across psychiatric diagnoses: An electronic health record investigation

2020 ◽  
Author(s):  
Aimee Brinn ◽  
James M Stone
Keyword(s):  
Mental Health ◽  
Electronic Health Records ◽  
National Health ◽  
Psychiatric Patients ◽  
Secondary Outcome ◽  
Health Records ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Mental Health Diagnoses ◽  
Electronic Health

AbstractObjectivesThe main objective of this study was to compare neutrophil-lymphocyte ratio, a marker of systemic inflammation, between patients diagnosed with ICD-10 psychiatric disorders and control participants.DesignA cross-sectional methodology was employed to retrospectively analyse electronic health records and records derived from a national health survey.SettingA secondary mental health care service consisting of four boroughs in South London.ParticipantsA diverse sample of 13,888 psychiatric patients extracted from South London and Maudsley electronic health records database and 3,920 control participants extracted from National Health and Nutrition Survey (2015-2016) were included in the study.Primary and secondary outcome measuresPrimary: NLR levels in patients with mental health diagnoses, NLR between patients with different mental health diagnoses. Secondary: Relationship of NLR to length of hospitalisation and to mortality.ResultsNLR was elevated compared to controls in patients with diagnoses including dementia, alcohol dependence, schizophrenia, bipolar affective disorder, depression, non-phobic anxiety disorders, and mild mental retardation (p < 0.05). NLR also correlated with age, antipsychotic use and hypnotic use. NLR was found to be higher in individuals of “White” ethnicity and lower in individuals of “Black” ethnicity. Elevated NLR was associated with increased mortality (β = 0.103, p = 2.9e-08) but not with hospital admissions or face-to-face contacts.ConclusionsElevated NLR may reflect a transdiagnostic pathological process occurring in a subpopulation of psychiatric patients. NLR may be useful to identify and stratify patients who could benefit from adjunctive anti-inflammatory treatment.Article SummaryStrengths and limitations of this studyLargest study to date of cross-diagnostic neutrophil-lymphocyte measurements in a psychiatric population.Sample is representative of diverse adult psychiatric patients in South London.Systematic differences between patients and controls reduce the validity of these comparisons.This study was retrospective and thus, confounding measures such as body mass index, smoking status and diet were unavailable.

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