Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: To be successful, cost control efforts must target Medicaid Managed Care (MMC) beneficiaries likely to incur high costs. The critical question is how to identify potential high cost beneficiaries with simple, reproducible, transparent, auditable criteria. Our objective in this analysis was to evaluate whether the total burden of comorbidity, assessed by the Charlson comorbidity index, could identify MMC beneficiaries who incurred high health care costs.
Methods: The MetroPlus MMC claims database was use to analyze six months of claims data from 07/07-12/07; the analysis focused on the total amount paid. Age, gender, Charlson comorbidity score, serious mental illness and pregnancy were analyzed as predictors of total costs.
Results: We evaluated the cost profile of 4,614 beneficiaries enrolled at MetroPlus, an MMC plan. As hypothesized, the comorbidity index was a key correlate of total costs (p < .01). Yearly costs were more related to the total burden of comorbidity than any specific comorbid disease. For adults, in addition to comorbidity (p < .01) both serious mental illness (p < .01) and pregnancy (p < .01) were also related to total costs, while age, drug addiction and gender were not. The model with age, gender, comorbidity, serious mental illness, pregnancy and addiction explained 20% of the variance in total costs. In children, comorbidity (p < .01), serious mental illness (p < .01), addiction (p < .03) and pregnancy (p < .01) were associated with log cost; the model with those variables explained 6% of the variance in costs.
Conclusions: Comorbidity can be used to identify MMC beneficiaries most likely to have high costs.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4289361 | PMC |
http://dx.doi.org/10.1186/1472-6963-14-461 | DOI Listing |
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