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Preparing for a US National ALS Registry: Lessons from a pilot project in the State of Georgia

AMYOTROPHIC LATERAL SCLEROSIS 2011年第2期12卷 130-135页

作者： Benatar, Michael Wuu, Joanne Usher, Sharon Ward, Kevin Emory Univ Sch Med Dept Neurol Sect Neurostat Atlanta GA 30322 USA Emory Univ Rollins Sch Publ Hlth Dept Epidemiol Atlanta GA 30322 USA

Our objective was to investigate the utility of existing data sources for identifying cases of amyotrophic lateral sclerosis (ALS) and related motor neuron diseases (MND) in the State of Georgia. Data were acquired from Medicare, Medicaid, Veterans Administration, Emory Healthcare, community neurologists, the ALS Association, and mortality records for ALS/MND patients residing in Georgia during 2001--2005. A neurologist used abstracted medical records to verify the diagnosis of ALS/MND. The positive predictive value (PPV) of an icd code for a verified diagnosis of ALS was estimated. Simple ''rules'' were developed to improve PPV. Results showed that a total of 2413 unique potential cases were identified in existing data sources. Medical records of 579 cases were available for review;the diagnosis of ALS (or a related MND) was confirmed in 486 (PPV == 84%) cases. Predictive rules, which permitted classification of similar to 80% of the chart-reviewed population, improved PPV to 96--98%. In conclusion, existing data sources are useful for identifying cases of ALS/MND;most data sources contribute a substantial number of unique cases. Predictive algorithms may permit correct classification of a large proportion of cases without the need for verification based on medical record review.

关键词： Epidemiology neuroepidemiology ALS Registry icd code positive predictive value

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Incidence of major depression diagnoses in the Canadian Armed Forces: longitudinal analysis of clinical and health administrative data

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SOCIAL PSYCHIATRY AND PSYCHIATRIC EPIDEMIOLOGY 2020年第5期55卷 581-588页

作者： Theriault, Francois L. Hawes, R. A. Garber, B. G. Momoli, F. Gardner, W. Zamorski, M. A. Colman, I. Canadian Forces Hlth Serv Grp Dept Natl Def Ottawa ON Canada Univ Ottawa Sch Epidemiol & Publ Hlth Ottawa ON Canada Childrens Hosp Eastern Ontario Res Inst Ottawa ON Canada Univ Ottawa Dept Family Med Ottawa ON Canada Ottawa Hosp Res Inst Ottawa ON Canada

Purpose Major depression is a leading cause of morbidity in military populations. However, due to a lack of longitudinal data, little is known about the rate at which military personnel experience the onset of new episodes of major depression. We used a new source of clinical and administrative data to estimate the incidence of major depression diagnoses in Canadian Armed Forces (CAF) personnel, and to compare incidence rates between demographic and occupational factors. Methods We extracted all data recorded in the electronic medical records of CAF Regular Force personnel, at every primary care and mental health clinical encounter since 2016. Using a 12-month lookback period, we linked data over time, and identified all patients with incident diagnoses of major depression. We then linked clinical data to CAF administrative records, and estimated incidence rates. We used multivariate Poisson regression to compare adjusted incidence rates between demographic and occupational factors. Results From January to December 2017, CAF Regular Force personnel were diagnosed with major depression at a rate of 29.2 new cases per 1000 person-years at risk. Female sex, age 30 years and older, and non-officer ranks were associated with significantly higher incidence rates. Conclusions We completed the largest study to date on diagnoses of major depression in the Canadian military, and have provided the first estimates of incidence rates in CAF personnel. Our results can inform future mental health resource allocation, and ongoing major depression prevention efforts within the Canadian Armed Forces and other military organizations.

关键词： Depression Military Epidemiology Risk icd code DSM code

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Palliative Care in Myocardial Infarction: Patient Characteristics and Trends of Service Utilization in a National Inpatient Sample

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AMERICAN JOURNAL OF HOSPICE & PALLIATIVE MEDICINE 2019年第8期36卷 722-726页

作者： Abdullah, Abdullah Sayied Salama, Amr Ibrahim, Hisham Eigbire, George Hoefen, Ryan Alweis, Richard Rochester Reg Hlth Unity Hosp Dept Med 1555 Long Pond Rd Rochester NY 14626 USA Univ Iowa Hosp & Clin Dept Cardiol Iowa City IA 52242 USA Rochester Reg Hlth Sands Constellat Heart Inst Rochester NY USA Univ Rochester Sch Med & Dent Dept Med Rochester NY 14642 USA Rochester Inst Technol Sch Hlth Sci Rochester NY 14623 USA

Introduction: Myocardial infarction (MI) remains a leading cause of mortality. Palliative care (PC) has recently expanded in scope to include noncancer-related conditions. There is little data available regarding the use of PC in critical MI patients. Methods: We used discharge data from the National Inpatient Sample for the years 2012 to 2014. We examined discharges with a primary diagnosis of MI. We measured the rate of PC referral, trend in utilization during the study period and possible predictors of PC utilization. Results: Among 1 667 520 discharges of those patients >= 18 years of age and with a primary diagnosis of MI, use of PC was seen in 2.5% of all patients and in 24% of patients who died. In a multivariable logistic regression, we found the presence of cancer, cardiogenic shock, dementia, stroke, hemiplegia, the use of circulatory support, and mechanical ventilation were associated with higher likelihood of PC referral. Palliative care referral increased during the study period, odds ratio of 1.18 per year (95% confidence interval: 1.14-1.21;P value <.001). Palliative care was not associated with prolonged length of stay. Conclusion: Several comorbidities were associated with the use of PC, most notably the use of mechanical ventilation and the presence of metastatic cancer. There was a trend of increasing use of PC during the study period.

关键词： myocardial infarction acute coronary syndrome palliative care end of life National Inpatient Sample icd code

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Automatic icd Coding Based on Multi-granularity Feature Fusion 18th

Automatic ICD Coding Based on Multi-granularity Feature Fusi...

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18th International Symposium on Bioinformatics Research and Applications (ISBRA)

作者： Yu, Ying Duan, Junwen Jiang, Han Wang, Jianxin Cent South Univ Sch Comp Sci & Engn Changsha Peoples R China Cent South Univ Hunan Prov Key Lab Bioinformat Changsha Peoples R China Univ South China Sch Comp Sci Hengyang Peoples R China

ISBN: (纸本)9783031231971;9783031231988

International Classification of Disease (icd) coding is to assign standard codes, which describe the state of a patient, to a clinical note. It is challenging given the complexity and the number of codes. The icd taxonomy is hierarchically organized with several level codes (chapter, category, subcategory and its subdivision). However, most existing studies focus on the prediction of the fine-grained subcategory codes, neglecting the hierarchical relations of icd codes. Those models pay less attention to common features related to sibling subcategories. The common features could be helpful for rare sample prediction and could be captured in the task of coarse-grained code prediction. In this paper, we propose a multi-task learning model, which explicitly trains multiple classifiers for different code levels. Simultaneously, we capture the relations between finer-grained and coarser-grained labels through a reinforcement mechanism. Extensive experiments on an English and a Chinese dataset show that our approach achieves competitive performance compared with baseline models, especially on Macro-F1 results. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Multi-granularity icd code Clinical notes Automatic assignment

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The rising incidence of rotator cuff repairs

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JOURNAL OF SHOULDER AND ELBOW SURGERY 2013年第12期22卷 1628-1632页

作者： Ensor, Kelsey L. Kwon, Young W. DiBeneditto, Michael R. Zuckerman, Joseph D. Rokito, Andrew S. NYU Hosp Joint Dis Dept Orthopaed Surg Div Shoulder & Elbow Surg New York NY 10016 USA

Background: Rotator cuff repairs (RCRs) have become increasingly common. Several studies have shown variation in the indications for this procedure. We chose to track the incidence of RCRs in New York State (NYS) from 1995 to 2009. We hypothesized that after the introduction of the Current Procedural Terminology (CPT) code 29827 for arthroscopic RCR, there would be a significant increase in the rate of RCRs performed in NYS. Materials and methods: The NYS Department of Health's Statewide Planning and Research Cooperative System (SPARCS) database was queried for reported RCRs between the years 1995 and 2009. Using the International Classification of Diseases, Ninth Revision, Clinical Modification procedural code 83.63 and CPT codes 23410, 23412, 23420, and 29827, we collected and analyzed data on RCR procedures. Results: A total of 168,780 RCRs were performed in NYS from 1995 to 2009. In 1995, the population incidence of RCRs was 23.5 per 100,000. In comparison, in 2009, the population incidence was 83.1 per 100,000, an increase of 238% (P < .0001). The percentage of individuals aged between 45 and 65 years undergoing RCR increased from 53.0% to 64.2% during this same period. Conclusions: There has been a notable increase in the volume of RCRs performed in NYS. In addition, after the introduction of CPT code 29827 in 2003, the increase in the incidence of RCRs became significantly more pronounced. Published by Elsevier Inc.

关键词： RCR rotator cuff repair incidence SPARCS CPT code icd code New York

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

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RHEUMATOLOGY 2020年第5期59卷 1059-1065页

作者： Zhao, Sizheng Steven Hong, Chuan Cai, Tianrun Xu, Chang Huang, Jie Ermann, Joerg Goodson, Nicola J. Solomon, Daniel H. Cai, Tianxi Liao, Katherine P. Univ Liverpool Inst Ageing & Chron Dis Liverpool Merseyside England Aintree Univ Hosp NHS Fdn Trust Dept Acad Rheumatol Liverpool L9 7AL Merseyside England Brigham & Womens Hosp Div Rheumatol Immunol & Allergy 75 Francis St Boston MA 02115 USA Harvard Med Sch Boston MA 02115 USA Brigham & Womens Hosp Div Pharmacoepidemiol & Pharmacoecon 75 Francis St Boston MA 02115 USA Harvard TH Chan Sch Publ Hlth Boston MA USA

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.

关键词： classification phenotyping electronic health records free-text natural language processing machine learning axial spondyloarthritis ankylosing spondylitis icd code

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Estimation of malnutrition prevalence using administrative data: Not as simple as it seems

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CLINICAL NUTRITION 2015年第6期34卷 1276-1277页

作者： Khalatbari-Soltani, Saman Waeber, Gerard Marques-Vidal, Pedro Univ Lausanne Hosp Inst Social & Prevent Med IUMSP CH-1010 Lausanne Switzerland Lausanne Univ Hosp CHUV Dept Internal Med Internal Med CH-1011 Lausanne Switzerland

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Clinical Nutrition and the German Diagnosis Related Group System

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AKTUELLE ERNAHRUNGSMEDIZIN 2014年第6期39卷 382-391页

作者： Ockenga, J. Hepatol & Emahrungs Med Med Klin Schwerpunkt Gastroenterol Endokrinol 2 Klinikum Bremen Mitte St Jurgen Str 1 D-28177 Bremen Germany

After introducing the German Diagnosis Related Groups as the basis for hospital reimbursement it is important for clinical nutrition to demonstrate not only the medical but also the economic implications. It has been shown that the presence of malnutrition as well obesity is associated with increased allocation of health care resource and, therefore, cost. Although in the actual G-DRG-System it is partially possible to represent the increased cost, there is still a requirement for an improvement. One major step would be to introduce a clear definition and grading for malnutrition in the clinical setting. For obesity such a classification has recently be accepted by using the body mass index. Next to treatment cost and reimbursement it is necessary to introduce quality indicators for nutritional care. By objective measurement of the treatment quality it can be avoided, that cost saving will lead to reduced quality. This article will report on current status in Germany as well as future steps for improvement of cost effectiveness and quality of nutritional care.

关键词： diagnosis related groups economics cost effectiveness nutrition dietitian health care quality icd code

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Automated icd coding for primary diagnosis via clinically interpretable machine learning

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INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS 2021年 153卷 104543-104543页

作者： Diao, Xiaolin Huo, Yanni Zhao, Shuai Yuan, Jing Cui, Meng Wang, Yuxin Lian, Xiaodan Zhao, Wei Chinese Acad Med Sci & Peking Union Med Coll Fuwai Hosp Dept Informat Ctr Beijing 100037 Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Fuwai Hosp Natl Ctr Cardiovasc Dis Dept Informat Ctr Beijing 100037 Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Fuwai Hosp Med Record Dept Beijing 100037 Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Fuwai Hosp Natl Ctr Cardiovasc Dis Beijing 100037 Peoples R China

Background: Computer-assisted clinical coding (CAC) based on automated coding algorithms has been expected to improve the International Classification of Disease, tenth version (icd-10) coding quality and productivity, whereas studies oriented to primary diagnosis auto-coding are limited in the Chinese context. Objective: This study aims at developing a machine learning (ML) model for automated primary diagnosis icd-10 coding. Methods: A total of 71,709 admissions in Fuwai hospital were included to carry out this study, corresponding to 168 primary diagnosis icd-10 codes. Based on clinical implications, two feature engineering methods were used to process discharge diagnosis and procedure texts into sequential features and sequential grouping features respectively by which two kinds of models were built and compared. One baseline model using one-hot encoding features was considered. Light Gradient Boosting Machine (LightGBM) was adopted as the classifier, and grid search and cross-validation were used to select the optimal hyperparameters. SHapley Additive exPlanations (SHAP) values were applied to give the interpretability of models. Results: Our best prediction model was developed based on sequential grouping features. It showed good performance in the test phase with accuracy and macro-averaged F1 (Macro-F1) of 95.2% and 88.3% respectively. The comparison of the models demonstrated the effectiveness of the sequential information and the grouping strategy in boosting model performance (P-value < 0.01). Subgroup analysis of the best model on each individual code manifested that 91.1% of the codes achieved the F1 over 70.0%. Conclusions: Our model has been demonstrated its effectiveness for automated primary diagnosis coding in the Chinese context and its results are interpretable. Hence, it has the potential to assist clinical coders to improve coding efficiency and quality in Chinese inpatient settings.

关键词： icd code Primary diagnosis Machine learning Computer-assisted coding

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Estimation of the incidence of pleural mesothelioma according to death certificates in France

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AMERICAN JOURNAL OF INDUSTRIAL MEDICINE 2002年第3期42卷 188-199页

作者： Iwatsubo, Y Matrat, M Michel, E Boutin, C Galateau-Salle, F Jougla, E Bignon, J Pairon, JC Brochard, P Fac Med INSERM E99 09 F-94010 Creteil France Univ Paris Inst Med Travail F-75252 Paris France CHI Creteil Creteil France Ctr Epidemiol Causes Med Deces INSERM CepiDc Le Vesinet France Hop Conception Marseille France Coll Natl Francais Anatomopathologistes Specialis Grp C MESOPATH Caen France Univ Bordeaux 2 F-33076 Bordeaux France

Background The number of cases of pleural mesothelioma in France has varied substantially according to methods of assessment. Materials and Methods We collected information from certifying physicians about 316 subjects who died between 1 July 1992 and 30 June 1993 in three regions of France with a cause of death coded as icd-9 category 163. The icd codes selected as the cause of death for 178 deaths between 1 January 1987 and 31 December 1992 histologically confirmed and diagnosed as pleural mesothelioma by an expert committee were examined. Finally, we used this information to estimate the number of deaths from pleural. mesothelioma in France in 1992. Results In Part I, 45% (men: 54%;women: 28%) of the cases coded as icd-9 section 163 were definitely or probably mesothelioma;18% (men: 16%;women: 21%) possibly mesothelioma;and 37% (men: 30%;women: 51%) other tumors, primarily adenocarcinoma metastases. In Part II, 74% of the confirmed pleural mesotheliomas were coded in category 163 (men: 75%;women: 70%). Extrapolation nationwide indicated that 902 deaths were coded as icd-9 163 in 1992: 521 cases involved definite or probable mesothelioma and 724 definite, probable, and possible cases. Conclusions The analysis of this sample suggests that estimating the number of mesothelioma cases from the cause-of-death statistics may overestimate their incidence, but that death certificates appeared to report the diagnosis of histologically confirmed mesothelioma accurately. (C) 2002 Wiley-Liss, Inc.

关键词： pleural mesothelioma death certificates histology icd code

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