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1 | | -comorbidities_icd10 |
| 1 | +comorbidities.icd10 |
2 | 2 | =================== |
3 | 3 |
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4 | | -Comorbidities calculator for R using ICD-9 and ICD-10 based scores |
| 4 | +Comorbidities calculator for R using ICD-9 and ICD-10 based scores. Currently only icd-9 codes are implemented and tested. |
| 5 | + |
| 6 | +Methods to categorize ICD-9-CM codes into sensible disease categories have |
| 7 | +been developed and published by numerous authors. Two of the most widely |
| 8 | +used such methods are the Deyo adaptation of Charlson index and the |
| 9 | +Elixhauser index. This package has functions to categorize comorbidites |
| 10 | +into the Deyo-Charlson index, the original Elixhauser index of 30 |
| 11 | +comorbidities, and the AHRQ comorbidity index (an update to the original |
| 12 | +Elixhauser method). |
| 13 | + |
| 14 | +This package consists of 3 functions: deyo, elixhauser, and ahrq. |
| 15 | +The functions are very similar in that they each take as input a data frame |
| 16 | +structured such that each row contains a list of ICD-9-CM codes (e.g. |
| 17 | +discharge or admission diagnoses) attributed to a single patient. The |
| 18 | +function goes from row to row comparing the ICD-9-CM codes a patient has |
| 19 | +with the particular comorbidity index that function represents. If a |
| 20 | +patient has a diagnosis (as indicated by ICD-9-CM code) that is one of the |
| 21 | +diagnoses in the paritcular index chosen, then the patient is considered to |
| 22 | +have this diagnosis. Regardless of how many different ICD-9-CM codes a |
| 23 | +patient has corresponding to a particular comorbidity category, a |
| 24 | +comorbidity is only counted once. |
| 25 | + |
| 26 | +The value returned consists of a vector and one or two data frames. The |
| 27 | +vector is the total comorbidity count, or in the case of the deyo() |
| 28 | +function, the total Charlson score. The functions elixhauser() and ahrq() |
| 29 | +return one data frame. Each row in the data frame is devoted to a |
| 30 | +particular patient, and each column is a diagnosis. The data frame codes a |
| 31 | +0 if the patient does not have that diagnosis and 1 if the patient does have |
| 32 | +that diagnosis. The deyo() function returns a second data frame, which codes |
| 33 | +the point value of that particular diagnosis in the Charlson score rather |
| 34 | +than a 1. |
| 35 | + |
| 36 | +This package is a work upon Paul Gerrards original comorbidities package. |
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