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
The combination of computing power, connectivity, and big data has been touted as the future of innovation in many fields, including medicine. There has been a groundswell of companies developing tools for improving patient care utilizing healthcare data, but procedural specialties, like surgery, have lagged behind in benefitting from data-based innovations, given the lack of data that is well structured. While many companies are attempting to innovate in the surgical field, some have encountered difficulties around collecting surgical data, given its complex nature. As there is no standardized way in which to interact with healthcare systems to purchase these data, the authors attempt to characterize the various ways in which surgical data are collected and shared. By surveying and conducting interviews with various surgical technology companies, at least 3 different methods to collect surgical data were identified. From this information, the authors conclude that an attempt to outline best practices should be undertaken that benefits all stakeholders.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1177/15533506211003538 | DOI Listing |
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