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
Objectives: To determine the extent of agreement between four commonly used definitions of multiple chronic conditions (MCCs) and compare each definition's ability to predict 30-day hospital readmissions.
Design: Retrospective cohort study.
Setting: National Medicare claims data.
Participants: Random sample of Medicare beneficiaries discharged from the hospital from 2005 to 2009 (n = 710,609).
Measurements: Baseline chronic conditions were determined for each participant using four definitions of MCC. The primary outcome was all-cause 30-day hospital readmission. Agreement between MCC definitions was measured, and sensitivities and specificities for each definition's ability to identify patients experiencing a future readmission were calculated. Logistic regression was used to assess the ability of each MCC definition to predict 30-day hospital readmission.
Results: The sample prevalence of hospitalized Medicare beneficiaries with two or more chronic conditions ranged from 18.6% (Johns Hopkins Adjusted Clinical Groups (ACG) Case-Mix System software) to 92.9% (Medicare Chronic Condition Warehouse (CCW)). There was slight to moderate agreement (kappa = 0.03-0.44) between pair-wise combinations of MCC definitions. CCW-defined MCC was the most sensitive (sensitivity 95.4%, specificity 7.4%), and ACG-defined MCC was the most specific (sensitivity 32.7%, specificity 83.2%) predictor of being readmitted. In the fully adjusted model, the risk of readmission was higher for those with chronic condition Special Needs Plan (c-SNP)-defined MCCs (odds ratio (OR) = 1.50, 95% confidence interval (CI) = 1.47-1.52), Charlson Comorbidity Index-defined MCCs (OR = 1.45, 95% CI = 1.42-1.47), ACG-defined MCCs (OR = 1.22, 95% CI = 1.19-1.25), and CCW-defined MCCs (OR = 1.15, 95% CI = 1.11-1.19) than for those without MCCs.
Conclusion: MCC definitions demonstrate poor agreement and should not be used interchangeably. The two definitions with the greatest agreement (CCI, c-SNP) were also the best predictors of 30-day hospital readmissions.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5397355 | PMC |
http://dx.doi.org/10.1111/jgs.14539 | DOI Listing |
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