Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.
ABSTRACT Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define Charlson and Elixhauser comorbidities in administrative data and assess the performance of the resulting algorithms.
ICD-10 coding algorithms were developed by "translation" of the ICD-9-CM codes constituting Deyo's (for Charlson comorbidities) and Elixhauser's coding algorithms and by physicians' assessment of the face-validity of selected ICD-10 codes. The process of carefully developing ICD-10 algorithms also produced modified and enhanced ICD-9-CM coding algorithms for the Charlson and Elixhauser comorbidities. We then used data on in-patients aged 18 years and older in ICD-9-CM and ICD-10 administrative hospital discharge data from a Canadian health region to assess the comorbidity frequencies and mortality prediction achieved by the original ICD-9-CM algorithms, the enhanced ICD-9-CM algorithms, and the new ICD-10 coding algorithms.
Among 56,585 patients in the ICD-9-CM data and 58,805 patients in the ICD-10 data, frequencies of the 17 Charlson comorbidities and the 30 Elixhauser comorbidities remained generally similar across algorithms. The new ICD-10 and enhanced ICD-9-CM coding algorithms either matched or outperformed the original Deyo and Elixhauser ICD-9-CM coding algorithms in predicting in-hospital mortality. The C-statistic was 0.842 for Deyo's ICD-9-CM coding algorithm, 0.860 for the ICD-10 coding algorithm, and 0.859 for the enhanced ICD-9-CM coding algorithm, 0.868 for the original Elixhauser ICD-9-CM coding algorithm, 0.870 for the ICD-10 coding algorithm and 0.878 for the enhanced ICD-9-CM coding algorithm.
These newly developed ICD-10 and ICD-9-CM comorbidity coding algorithms produce similar estimates of comorbidity prevalence in administrative data, and may outperform existing ICD-9-CM coding algorithms.
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ABSTRACT: Objective. Evaluate the prevalence and outcomes of urinary tract infection (UTI) among renal transplant recipients. Methods. A secondary analysis of the Nationwide Inpatient Sample 2009–2011 was conducted. Survey-weighted multivariable regression analyses were used to examine the impact of UTI on transplant complications, total charges, and length of stay. Results. A total of 1,044 renal transplant recipients, representing a population estimate of 49,862, were included in the study. UTI was most common in transplant recipients with hypertension (53%) and prevalence was noted to be 28.2 and 65.9 cases per 1,000 for men and women, respectively. UTI increased the likelihood of transplant complications (182% for men, 169% for women). Total charges were 28% higher among men as compared to 22% among women with UTI. Such infection also increased the length of stay by 87% among men and 74% among women. Discussion. UTI in renal transplant recipients was associated with prolonged length of stay, total charges, and increased odds of transplant complications. Interventions to prevent UTI among such patients should be a priority area for future research and practice.Journal of Transplantation 02/2015; 2015. DOI:10.1155/2015/854640
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ABSTRACT: The population of people with opioid use disorders (OUD) is aging. There has been little research on the effects of aging on mortality rates and causes of death in this group. We aimed to compare mortality in older (≥50 years of age) adults with OUD to that in younger (<50 years) adults with OUD and older adults with no history of OUD. We also examined risk factors for specific causes of death in older adults with OUD. Using data from the Veteran's Health Administration National Patient Care Database (2000-2011), we compared all-cause and cause-specific mortality rates in older adults with OUD to those in younger adults with OUD and older adults without OUD. We then generated a Cox regression model with specific causes of death treated as competing risks. Older adults with OUD were more likely to die from any cause than younger adults with OUD. The drug-related mortality rate did not decline with age. HIV-related and liver-related deaths were higher among older OUD compared to same-age peers without OUD. There were very few clinically important predictors of specific causes of death. Considerable drug-related mortality in people with OUD suggests a need for greater access to overdose prevention and opioid substitution therapy across the lifespan. Elevated risk of liver-related death in older adults may be addressed through antiviral therapy for hepatitis C virus infection. There is an urgent need to explore models of care that address the complex health needs of older adults with OUD. Copyright © 2015. Published by Elsevier Ireland Ltd.Drug and Alcohol Dependence 12/2014; 147. DOI:10.1016/j.drugalcdep.2014.12.019 · 3.28 Impact Factor
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ABSTRACT: To conduct a systematic review of studies reporting on the development or validation of comorbidity indices using administrative health data and compare their ability to predict outcomes related to comorbidity (ie, construct validity).Journal of Clinical Epidemiology 10/2014; 68(1). DOI:10.1016/j.jclinepi.2014.09.010 · 5.48 Impact Factor