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: Spine surgery and its corresponding costs have increased in recent years and are variable across geographic regions. Discretionary care is the component of spending variation that is independent of illness severity, age, and regional pricing. It is unknown whether greater discretionary care is associated with improved safety for patients undergoing spine surgery, as we would expect from value-based health care.
Methods: We conducted an analysis of 5 spine surgery cohorts based on Medicare claims from 2013 to 2017. Patients were grouped into quintiles based on the Dartmouth Atlas End-of-Life Inpatient Care Index (EOL), reflecting regional spending variation attributed to discretionary care. Multivariable regression examined the association between discretionary care and safety measures while controlling for age, sex, race, comorbidity, and hospital features.
Results: We observed a threefold to fourfold variation in 90-day episode-of-care cost across regions, depending on the cohort. Spine-specific spending was correlated with EOL quintile, confirming that spending variation is due more to discretionary care than it is to pricing, age, or illness severity. Greater spending across EOL quintiles was not associated with improved safety, and, in fact, was associated with poorer safety in some cohorts. For example, all-cause readmission was greater in the high-spending EOL quintile relative to the low-spending EOL quintile among the "fusion, except cervical" cohort (14.2% vs. 13.1%; OR = 1.10; 95% CI = 1.05 to 1.20), the "complex fusion" cohort (28.0% vs. 25.4%; OR = 1.15; 95% CI = 1.01 to 1.30), and the "cervical fusion" cohort (15.0% vs. 13.6%; OR = 1.12; 95% CI = 1.05 to 1.20).
Conclusions: Wide variation in spending was not explained by differences in illness severity, age, or pricing, and increased discretionary care did not enhance safety. These findings point to inefficient use of health-care resources, a potential focus of reform.
Level Of Evidence: Economic and Decision Analysis Level IV. See Instructions for Authors for a complete description of levels of evidence.
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Source |
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http://dx.doi.org/10.2106/JBJS.21.00389 | DOI Listing |
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