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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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: Common methods of benchmarking clinical performance rarely, if ever, account for admission source and, in particular, the effect of a patient being transferred from one medical center to another. Small biases in comparisons of observed versus expected deaths can substantially affect how high-quality institutions compare with peer hospitals. With the most sophisticated and validated set of case-mix measures available for patients, the intensive care unit is an ideal setting in which to study the effect of a patient's being transferred from another hospital.
Objective: To determine the extent of bias in benchmarking outcomes when performance measures do not account for transfer patients' greater severity of illness.
Design: Prospectively developed cohort study.
Setting: Medical intensive care unit (MICU) at a tertiary care university hospital.
Patients: 4579 consecutive admissions for 4208 patients from 1 January 1994 to 1 April 1998.
Measurements: MICU and hospital lengths of stay, MICU readmission, and hospital mortality rates.
Results: Compared with directly admitted patients, MICU patients transferred from another hospital had significantly higher Acute Physiology Scores at the time of admission and discharge (P = 0.001). Even after full adjustment for case mix and severity of illness, transfer patients had a 38% longer MICU stay (95% CI, 32% to 45%), a 41% longer hospital stay (CI, 34% to 50%), and a 2.2 times greater odds of hospital mortality (CI, 1.7 to 2.8) than directly admitted patients. With identical efficiency and quality, a referral hospital with a 25% MICU transfer rate compared with another with a 0% transfer rate would be penalized by 14 excess deaths per 1000 admissions when a benchmarking program adjusts only for case mix and severity of illness and not for the source of admission.
Conclusions: In a setting with the most thorough diagnostic-based, case-mix adjustment and the most physiologically precise severity-of-illness information, accepting transfer patients can adversely affect efficiency and quality benchmarks. Benchmarking and profiling efforts beyond intensive care units must also recognize and account for this phenomenon; otherwise, referral centers may have an incentive to refuse care for patients who could benefit from being transferred to their facility.
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Source |
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http://dx.doi.org/10.7326/0003-4819-138-11-200306030-00009 | DOI Listing |
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