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Filename: drivers/Session_files_driver.php
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Filename: Session/Session.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Filename: helpers/my_audit_helper.php
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Filename: controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
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Objectives: To measure geographic variations in treatment costs for specific conditions, explore the consistency of these patterns across conditions, and examine how service mix and population health factors are associated with condition-specific and total area costs.
Data Sources: Medicare claims for 1.5 million elderly beneficiaries from 60 community tracking study (CTS) sites who received services from 5,500 CTS Physician Survey respondents during 2004-2006.
Study Design: Episodes of care for 10 costly and common conditions were formed using Episode Treatment Group grouper software. Episode and total annual costs were calculated, adjusted for price, patient demographics, and comorbidities. We correlated episode costs across sites and examined whether episode service mix and patient health were associated with condition-specific and total per-beneficiary costs.
Principal Findings: Adjusted episode costs varied from 34 to 68 percent between the most and least expensive site quintiles. Area mean costs were only weakly correlated across conditions. Hospitalization rates, surgery rates, and specialist involvement were associated with site episode costs, but local population health indicators were most related to site total per-beneficiary costs.
Conclusions: Population health appears to drive local per-beneficiary Medicare costs, whereas local practice patterns likely influence condition-specific episode costs. Reforms should be flexible to address local conditions and practice patterns.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3922465 | PMC |
http://dx.doi.org/10.1111/1475-6773.12087 | DOI Listing |
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