scholarly journals Cost of peripheral neuropathy in patients receiving treatment for multiple myeloma: a US administrative claims analysis

2019 ◽  
Vol 10 ◽  
pp. 204062071983902 ◽  
Author(s):  
Xue Song ◽  
Kathleen L. Wilson ◽  
Jerry Kagan ◽  
Sumeet Panjabi
Keyword(s):  
Multiple Myeloma ◽  
Peripheral Neuropathy ◽  
Economic Burden ◽  
Proteasome Inhibitors ◽  
International Classification Of Diseases ◽  
Administrative Claims ◽  
Novel Treatments ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Icd 10

Background: Peripheral neuropathy (PN) is a common consequence of multiple myeloma (MM) among those commonly treated with older-generation proteasome inhibitors (PIs). In this study, we evaluated the economic burden attributable to PN among MM patients in real-world practice settings in the US. Methods: Adults diagnosed with MM and first treated (index event) between 1 July 2006 and 28 February 2017 were identified from MarketScan® Commercial and Medicare claim databases. Continuous enrollment for at least 12 months without treatment and PN diagnoses were required pre-index. Patients were followed for at least 3 months until inpatient death or end of data. The International Classification of Diseases, ninth revision, Clinical Modification (ICD-9-CM) and ICD-10-CM diagnosis codes were used to identify PN. Propensity-score matching was applied to match every patient with PN to two MM patients without a PN diagnosis (controls). Healthcare utilization and expenditures per patient per month (PPPM) in the postindex period were estimated. Results: Of 11,851 patients meeting the study criteria, 15.5% had PN. After matching 1387 patients with PN and 2594 controls were identified. Baseline characteristics were well balanced between cohorts; mean follow up was 23–26 months. PPPM total costs were significantly higher by $1509 for patients with PN than controls, driven by higher hospitalization (PN 77.4%, controls 67.2%; p < 0.001) and emergency department rates (PN 67.8%, controls 58.4%; p < 0.001) and more outpatient hospital-based visits PPPM (PN 13.5 ± 14.7, controls 11.5 ± 18.0; p < 0.001). Conclusions: PN is a prevalent MM treatment complication associated with a significant economic burden adding to the complexity and cost of MM treatment. Highly effective novel treatments such as carfilzomib may reduce the overall disease burden.

The prevalence of localised scleroderma in childhood assessed in the administrative claims data from the United States

2018 ◽  
Vol 4 (1) ◽  
pp. 77-78
Author(s):  
Timothy Beukelman ◽  
Fenglong Xie ◽  
Ivan Foeldvari
Keyword(s):  
United States ◽  
Systemic Sclerosis ◽  
Claims Data ◽  
International Classification Of Diseases ◽  
The United States ◽  
Administrative Claims ◽  
Administrative Claims Data ◽  
Diagnosis Codes ◽  
Classification Of Diseases

Juvenile localised scleroderma is believed an orphan autoimmune disease, which occurs 10 times more often than systemic sclerosis in childhood and is believed to have a prevalence of 1 per 100,000 children. To gain data regarding the prevalence of juvenile localised scleroderma, we assessed the administrative claims data in the United States using the International Classification of Diseases, Ninth Revision diagnosis codes. We found an estimated prevalence in each year ranging from 3.2 to 3.6 per 10,000 children. This estimate is significantly higher as found in previous studies.

scholarly journals Validating Use of Electronic Health Data to Identify Patients with Urinary Tract Infections in Outpatient Settings

Antibiotics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 536
Author(s):  
George Germanos ◽  
Patrick Light ◽  
Roger Zoorob ◽  
Jason Salemi ◽  
Fareed Khan ◽  
...  
Keyword(s):  
Urinary Tract ◽  
Urinary Tract Infections ◽  
Chart Review ◽  
International Classification Of Diseases ◽  
Primary Care Settings ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Tract Infections ◽  
Outpatient Settings

Objective: To validate the use of electronic algorithms based on International Classification of Diseases (ICD)-10 codes to identify outpatient visits for urinary tract infections (UTI), one of the most common reasons for antibiotic prescriptions. Methods: ICD-10 symptom codes (e.g., dysuria) alone or in addition to UTI diagnosis codes plus prescription of a UTI-relevant antibiotic were used to identify outpatient UTI visits. Chart review (gold standard) was performed by two reviewers to confirm diagnosis of UTI. The positive predictive value (PPV) that the visit was for UTI (based on chart review) was calculated for three different ICD-10 code algorithms using (1) symptoms only, (2) diagnosis only, or (3) both. Results: Of the 1087 visits analyzed, symptom codes only had the lowest PPV for UTI (PPV = 55.4%; 95%CI: 49.3–61.5%). Diagnosis codes alone resulted in a PPV of 85% (PPV = 84.9%; 95%CI: 81.1–88.2%). The highest PPV was obtained by using both symptom and diagnosis codes together to identify visits with UTI (PPV = 96.3%; 95%CI: 94.5–97.9%). Conclusions: ICD-10 diagnosis codes with or without symptom codes reliably identify UTI visits; symptom codes alone are not reliable. ICD-10 based algorithms are a valid method to study UTIs in primary care settings.

Assessing the prevalence of juvenile systemic sclerosis in childhood using administrative claims data from the United States

2018 ◽  
Vol 3 (2) ◽  
pp. 189-190 ◽  
Author(s):  
Timothy Beukelman ◽  
Fenglong Xie ◽  
Ivan Foeldvari
Keyword(s):  
United States ◽  
Systemic Sclerosis ◽  
Claims Data ◽  
International Classification Of Diseases ◽  
The United States ◽  
Administrative Claims ◽  
Administrative Claims Data ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Juvenile Systemic Sclerosis

Juvenile systemic sclerosis is a very rare orphan disease. To date, only one publication has estimated the prevalence of juvenile systemic sclerosis using a survey of specialized physicians. We conducted a study of administrative claims data in the United States using the International Classification of Diseases, Ninth Revision diagnosis codes and found a prevalence of approximately 3 per 1,000,000 children. This estimate will inform the planning of prospective studies.

scholarly journals Challenges and remediation for Patient Safety Indicators in the transition to ICD-10-CM

2014 ◽  
Vol 22 (1) ◽  
pp. 19-28 ◽  
Author(s):  
Andrew D Boyd ◽  
Young Min Yang ◽  
Jianrong Li ◽  
Colleen Kenost ◽  
Mike D Burton ◽  
...  
Keyword(s):  
Patient Safety ◽  
Adverse Events ◽  
International Classification Of Diseases ◽  
Healthcare Research ◽  
Coding System ◽  
Patient Safety Indicators ◽  
Safety Reporting ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Icd 10

Abstract Reporting of hospital adverse events relies on Patient Safety Indicators (PSIs) using International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) codes. The US transition to ICD-10-CM in 2015 could result in erroneous comparisons of PSIs. Using the General Equivalent Mappings (GEMs), we compared the accuracy of ICD-9-CM coded PSIs against recommended ICD-10-CM codes from the Centers for Medicaid/Medicare Services (CMS). We further predict their impact in a cohort of 38 644 patients (1 446 581 visits and 399 hospitals). We compared the predicted results to the published PSI related ICD-10-CM diagnosis codes. We provide the first report of substantial hospital safety reporting errors with five direct comparisons from the 23 types of PSIs (transfusion and anesthesia related PSIs). One PSI was excluded from the comparison between code sets due to reorganization, while 15 additional PSIs were inaccurate to a lesser degree due to the complexity of the coding translation. The ICD-10-CM translations proposed by CMS pose impending risks for (1) comparing safety incidents, (2) inflating the number of PSIs, and (3) increasing the variability of calculations attributable to the abundance of coding system translations. Ethical organizations addressing ‘data-, process-, and system-focused’ improvements could be penalized using the new ICD-10-CM Agency for Healthcare Research and Quality PSIs because of apparent increases in PSIs bearing the same PSI identifier and label, yet calculated differently. Here we investigate which PSIs would reliably transition between ICD-9-CM and ICD-10-CM, and those at risk of under-reporting and over-reporting adverse events while the frequency of these adverse events remain unchanged.

scholarly journals Updating and Validating the U.S. Veterans Affairs Frailty Index: Transitioning From ICD-9 to ICD-10

2021 ◽  
Author(s):  
David Cheng ◽  
Clark DuMontier ◽  
Cenk Yildirim ◽  
Brian Charest ◽  
Chelsea E Hawley ◽  
...  
Keyword(s):  
Frailty Index ◽  
International Classification Of Diseases ◽  
Veterans Affairs ◽  
Administrative Claims ◽  
Before And After ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
National Cohort ◽  
The Mean

Abstract Background The Veterans Affairs Frailty Index (VA-FI) is an electronic frailty index developed to measure frailty using administrative claims and electronic health records data in Veterans. An update to ICD-10 coding is needed to enable contemporary measurement of frailty. Method International Classification of Diseases, ninth revision (ICD-9) codes from the original VA-FI were mapped to ICD-10 first using the Centers for Medicaid and Medicare Services (CMS) General Equivalence Mappings. The resulting ICD-10 codes were reviewed by 2 geriatricians. Using a national cohort of Veterans aged 65 years and older, the prevalence of deficits contributing to the VA-FI and associations between the VA-FI and mortality over years 2012–2018 were examined. Results The updated VA-FI-10 includes 6422 codes representing 31 health deficits. Annual cohorts defined on October 1 of each year included 2 266 191 to 2 428 115 Veterans, for which the mean age was 76 years, 97%–98% were male, 78%–79% were White, and the mean VA-FI was 0.20–0.22. The VA-FI-10 deficits showed stability before and after the transition to ICD-10 in 2015, and maintained strong associations with mortality. Patients classified as frail (VA-FI &gt; 0.2) consistently had a hazard of death more than 2 times higher than nonfrail patients (VA-FI ≤ 0.1). Distributions of frailty and associations with mortality varied with and without linkage to CMS data and with different assessment periods for capturing deficits. Conclusions The updated VA-FI-10 maintains content validity, stability, and predictive validity for mortality in a contemporary cohort of Veterans aged 65 years and older, and may be applied to ICD-9 and ICD-10 claims data to measure frailty.

Identifying Clinically Disruptive International Classification of Diseases 10th Revision Clinical Modification Conversions to Mitigate Financial Costs Using an Online Tool

2014 ◽  
Vol 10 (2) ◽  
pp. 97-103 ◽  
Author(s):  
Neeta K. Venepalli ◽  
Yusuf Qamruzzaman ◽  
Jianrong “John” Li ◽  
Yves A. Lussier ◽  
Andrew D. Boyd
Keyword(s):  
Clinical Oncology ◽  
International Classification Of Diseases ◽  
Information Loss ◽  
International Classification ◽  
Online Tool ◽  
Financial Costs ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Icd 10

Complex transitions and diagnosis codes associated with information loss within clinical oncology require additional attention during the transition to ICD-10-CM.

scholarly journals Construction of a Semi-automatic ICD-10 Coding System

2020 ◽  
Author(s):  
Lingling Zhou ◽  
Cheng Cheng ◽  
Dong Ou ◽  
Hao Huang
Keyword(s):  
System Performance ◽  
International Classification Of Diseases ◽  
Coding System ◽  
Daily Work ◽  
Coding Efficiency ◽  
Testing Phase ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Automatic Coding

Abstract Background The International Classification of Diseases, 10th Revision (ICD-10) has been widely used to describe the diagnosis information of patients. Automatic ICD-10 coding is important because manually assigning codes is expensive, time consuming and error prone. Although numerous approaches have been developed to explore automatic coding, few of them have been applied in practice. Our aim is to construct a practical, automatic ICD-10 coding machine to improve coding efficiency and quality in daily work. Methods In this study, we propose the use of regular expressions (regexps) to establish a correspondence between diagnosis codes and diagnosis descriptions in outpatient settings and at admission and discharge. The description models of the regexps were embedded in our upgraded coding system, which queries a diagnosis description and assigns a unique diagnosis code. Like most studies, the precision (P), recall (R), F-measure (F) and overall accuracy (A) were used to evaluate the system performance. Our study had two stages. The datasets were obtained from the diagnosis information on the homepage of the discharge medical record. The testing sets were from October 1, 2017 to April 30, 2018 and from July 1, 2018 to January 31, 2019. Results The values of P were 89.27% and 88.38% in the first testing phase and the second testing phase, respectively, which demonstrate high precision. The automatic ICD-10 coding system completed more than 160,000 codes in 16 months, which reduced the workload of the coders. In addition, a comparison between the amount of time needed for manual coding and automatic coding indicated the effectiveness of the system-the time needed for automatic coding takes nearly 100 times less than manual coding. Conclusions Our automatic coding system is well suited for the coding task. Further studies are warranted to perfect the description models of the regexps and to develop synthetic approaches to improve system performance.

scholarly journals Construction of a Semi-automatic ICD-10 Coding System

2020 ◽  
Author(s):  
Lingling Zhou ◽  
Cheng Cheng ◽  
Dong Ou ◽  
Hao Huang
Keyword(s):  
System Performance ◽  
International Classification Of Diseases ◽  
Coding System ◽  
Daily Work ◽  
Coding Efficiency ◽  
Testing Phase ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Automatic Coding

Abstract Background The International Classification of Diseases, 10th Revision (ICD-10) has been widely used to describe the diagnosis information of patients. Automatic ICD-10 coding is important because manually assigning codes is expensive, time consuming and error prone. Although numerous approaches have been developed to explore automatic coding, few of them have been applied in practice. Our aim is to construct a practical, automatic ICD-10 coding machine to improve coding efficiency and quality in daily work. Methods In this study, we propose the use of regular expressions (regexps) to establish a correspondence between diagnosis codes and diagnosis descriptions in outpatient settings and at admission and discharge. The description models of the regexps were embedded in our upgraded coding system, which queries a diagnosis description and assigns a unique diagnosis code. Like most studies, the precision (P), recall (R), F-measure (F) and overall accuracy (A) were used to evaluate the system performance. Our study had two stages. The datasets were obtained from the diagnosis information on the homepage of the discharge medical record. The testing sets were from October 1, 2017 to April 30, 2018 and from July 1, 2018 to January 31, 2019. Results The values of P were 89.27% and 88.38% in the first testing phase and the second testing phase, respectively, which demonstrate high precision. The automatic ICD-10 coding system completed more than 160,000 codes in 16 months, which reduced the workload of the coders. In addition, a comparison between the amount of time needed for manual coding and automatic coding indicated the effectiveness of the system-the time needed for automatic coding takes nearly 100 times less than manual coding. Conclusions Our automatic coding system is well suited for the coding task. Further studies are warranted to perfect the description models of the regexps and to develop synthetic approaches to improve system performance.

scholarly journals Development and validation of a structured query language implementation of the Elixhauser comorbidity index

2017 ◽  
Vol 24 (4) ◽  
pp. 845-850 ◽  
Author(s):  
Richard H Epstein ◽  
Franklin Dexter
Keyword(s):  
Query Language ◽  
Diagnosis Related Groups ◽  
International Classification Of Diseases ◽  
Diagnosis Codes ◽  
Structured Query Language ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Related Group ◽  
Comorbidity Index ◽  
Development And Validation

Abstract Objective: Comorbidity adjustment is often performed during outcomes and health care resource utilization research. Our goal was to develop an efficient algorithm in structured query language (SQL) to determine the Elixhauser comorbidity index. Materials and Methods: We wrote an SQL algorithm to calculate the Elixhauser comorbidities from Diagnosis Related Group and International Classification of Diseases (ICD) codes. Validation was by comparison to expected comorbidities from combinations of these codes and to the 2013 Nationwide Readmissions Database (NRD). Results: The SQL algorithm matched perfectly with expected comorbidities for all combinations of ICD-9 or ICD-10, and Diagnosis Related Groups. Of 13 585 859 evaluable NRD records, the algorithm matched 100% of the listed comorbidities. Processing time was ∼0.05 ms/record. Discussion: The SQL Elixhauser code was efficient and computationally identical to the SAS algorithm used for the NRD. Conclusions: This algorithm may be useful where preprocessing of large datasets in a relational database environment and comorbidity determination is desired before statistical analysis. A validated SQL procedure to calculate Elixhauser comorbidities and the van Walraven index from ICD-9 or ICD-10 discharge diagnosis codes has been published.

Symptoms in Blastomycosis, Coccidioidomycosis, and Histoplasmosis Versus Other Respiratory Illnesses in Commercially Insured Adult Outpatients—United States, 2016–2017

2020 ◽  
Author(s):  
Kaitlin Benedict ◽  
Miwako Kobayashi ◽  
Shikha Garg ◽  
Tom Chiller ◽  
Brendan R Jackson
Keyword(s):  
Respiratory Infections ◽  
Healthcare Providers ◽  
International Classification Of Diseases ◽  
Community Acquired Pneumonia ◽  
Fungal Diseases ◽  
Respiratory Illnesses ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Icd 10

Abstract Background Blastomycosis, coccidioidomycosis, and histoplasmosis cause various symptoms and syndromes, which may present similarly to other infections such as bacterial or viral community-acquired pneumonia, influenza, and tuberculosis. Methods We used the IBM MarketScan Research Databases to identify adult outpatients with International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM), diagnosis codes during 2016–2017 for blastomycosis, coccidioidomycosis, histoplasmosis, pneumonia (viral, bacterial, Streptococcus pneumoniae, and unspecified pneumonia), influenza; tuberculosis, and other lower and upper respiratory infections. We compared symptoms on and in the 90 days before diagnosis between patients with these diagnosis codes. Results Fever was less common in blastomycosis (2.6%), histoplasmosis (5.3%), and coccidioidomycosis (9.4%) than in patients with influenza (18.5%) or pneumonia (12.6–16.3%). Fungal diseases resembled bacterial, viral, and unspecified pneumonias for many pulmonary symptoms. However, cough was more common with coccidioidomycosis (31.4%) and less common with histoplasmosis (14.0%) and blastomycosis (13.1%) versus influenza (20.2%). Although less frequent, solitary pulmonary nodule (5.2–14.4%), enlarged lymph nodes (3.7–9.0%), hyperhidrosis (&lt;2%), and erythema nodosum (&lt;2%) were particularly suggestive of fungal diseases. Conclusions Despite limitations inherent in administrative coding, this analysis of symptom codes across disease types suggests that fungal diseases may be difficult to clinically distinguish from other causes of pneumonia except when certain uncommon symptoms are present. Healthcare providers caring for patients with pneumonia, especially if nonresponsive to conventional treatment, should consider fungal diseases as possible etiologies.

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