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
Introduction: In Germany, Emergency Medical Services (EMS) were involved in a total of 7.3 million emergency cases in 2016/2017. Information on prehospital care is stored in several secondary data sources, yet combined analysis of these data at the level of individual patients or EMS cases happens rarely. Research is needed on which methods and variables are suitable for the linkage of these data sources.
Methods: We linked EMS records from five Bavarian emergency service districts to health claims data belonging to ten statutory health insurers (data from 2016). Two linkage approaches at the level of individual patient's EMS case/reimbursement case were demonstrated. First, a deterministic linkage was conducted based on the patient's unique identifying health insurance number. The second linkage was probabilistic. As linkage variables, it comprised the only partially available health insurance number plus several non-unique key variables, the latter being a patient's health insurance provider, sex, year of birth and distance travelled. In order to verify the deterministic and the probabilistic linkages' quality, rates of accordance of several variables present in both data sources were calculated.
Results: The starting point for our data linkage were 106,371 EMS records (independent of certain health insurance companies) and 432,693 EMS services reimbursed by health insurers (independent of specific EMS providers). 4,327 EMS records could be linked to health claims data - out of 5,921 EMS records that coded a health insurance company contributing claims data to Inno_RD. With a probabilistic linkage, it was possible to increase this number to a total of 5,379 linked EMS records. All checks carried out indicated a high linkage quality for both the deterministic and the probabilistic approach.
Conclusion: A linkage of EMS records with health claims data is possible. In Inno_RD, a probabilistic approach has proven a valuable alternative to deterministic linkage via health insurance number since EMS records can be linked meaningfully even if the health insurance number is unavailable or where a minority of non-unique key variables show non-accordance or missing values.
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Source |
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http://dx.doi.org/10.1055/a-1630-7398 | DOI Listing |
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