Neighbour code capacity and reduction in number of code searches

Author(s):  
Vipin Balyan ◽  
Davinder S Saini ◽  
Alok Kumar Singh ◽  
Paras Agarwal ◽  
Pranjal Agarwal
Keyword(s):  
2012 ◽  
Vol 33 (6) ◽  
pp. 581-588 ◽  
Author(s):  
Lisa M. Rosen ◽  
Tao Liu ◽  
Roland C. Merchant

Background.Blood and body fluid exposures are frequently evaluated in emergency departments (EDs). However, efficient and effective methods for estimating their incidence are not yet established.Objective.Evaluate the efficiency and accuracy of estimating statewide ED visits for blood or body fluid exposures using International Classification of Diseases, Ninth Revision (ICD-9), code searches.Design.Secondary analysis of a database of ED visits for blood or body fluid exposure.Setting.EDs of 11 civilian hospitals throughout Rhode Island from January 1, 1995, through June 30, 2001.Patients.Patients presenting to the ED for possible blood or body fluid exposure were included, as determined by prespecified ICD-9 codes.Methods.Positive predictive values (PPVs) were estimated to determine the ability of 10 ICD-9 codes to distinguish ED visits for blood or body fluid exposure from ED visits that were not for blood or body fluid exposure. Recursive partitioning was used to identify an optimal subset of ICD-9 codes for this purpose. Random-effects logistic regression modeling was used to examine variations in ICD-9 coding practices and styles across hospitals. Cluster analysis was used to assess whether the choice of ICD-9 codes was similar across hospitals.Results.The PPV for the original 10 ICD-9 codes was 74.4% (95% confidence interval [CI], 73.2%–75.7%), whereas the recursive partitioning analysis identified a subset of 5 ICD-9 codes with a PPV of 89.9% (95% CI, 88.9%–90.8%) and a misclassification rate of 10.1%. The ability, efficiency, and use of the ICD-9 codes to distinguish types of ED visits varied across hospitals.Conclusions.Although an accurate subset of ICD-9 codes could be identified, variations across hospitals related to hospital coding style, efficiency, and accuracy greatly affected estimates of the number of ED visits for blood or body fluid exposure.


Author(s):  
Jigneshkumar Gondaliya ◽  
Jyoti Divecha

Abstract Crossover designs robust to changes in carryover models are useful in clinical trials where the nature of carryover effects is not known in advance. The designs have been characterized for being optimal and efficient under no carryover-, traditional-, and, self and mixed carryover- models, however, ignoring the number of subjects, which has significant impact on both optimality and administrative convenience. In this article, adding two more practical models, the traditional, and, self and mixed carryover models having carryover effect only for the new or test treatment, a 5M algorithm is presented. The 5M algorithm based computer code searches all possible two treatment crossover designs under the five carryover models and list those which are optimal and /or efficient to all the five carryover models. The resultant exhaustive list consists of optimal and/or efficient crossover designs in two, three, and four periods, having 4 to 20 subjects of which 24 designs are new optimal for one of the established carryover models, and 34 designs are optimal for newly added models.


2018 ◽  
Vol E101.B (12) ◽  
pp. 2380-2387
Author(s):  
Chun-Lin LIN ◽  
Tzu-Hsiang LIN ◽  
Ruey-Yi WEI
Keyword(s):  

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