Healthcare Hygiene magazine June 2021 June 2021 | Page 38

The FHIR standard — the acronym stands for Fast
Healthcare
Interoperability Resources — focuses on easy implementation , standardizes core healthcare data elements ( known as FHIR resources ) such as patients , admissions , diagnostic reports , and medications , and combines features of prior HL7 versions , such as data format standards , with web service technologies , namely APIs , that have gained wide , crossindustry use .
Outcome measures are nothing without the infrastructure to power the data collection and reporting . During his Decennial Day presentation , Pollock pointed to a schematic showing a series of steps beginning with the acquisition of the medication administration data at the bedside where there are implementations that extract and load those data into a clinical document architecture that is delivered to NHSN where the data are available via a web-based interface to NHSN users for analysis , visualization , and reporting purposes . “ The fact that we are able to use this electronic technology has a lot to do with the advances that have been made in healthcare IT over the years ,” he said .
The transformation of processes made possible by healthcare IT is significant , Pollock said , noting that medication administration has moved from peel-away labels to barcode scans ; laboratory results have moved from paper printouts to electronic laboratory reporting ; and medical records and databases have evolved from paper-based to electronic systems , paving the way for improved surveillance systems .
That said , there are limitations with EHRs , Pollock emphasized , observing that electronic health records ( EHRs ) have not served practitioners well , pointing to Abraham Verghese ’ s article in The New York Times Magazine from 2018 that physicians ’ daily progress notes “ have become bloated and cut-and-paste monsters .”
Pollock noted , “ There is a real limitation in the way that this technology is being used that limits the availability and accuracy — the small data if you will — of the EHR for clinical and subsequent reuse for surveillance purposes . So , there is a lot of work to be done at the level of the data itself . We need these data for action , but we need action to make the data actionable . As a result of these limitations , efforts to introduce , revise and extend HAI and AUR measures must content with the limitations of healthcare IT and the way it is being used , but there are other issues , too . Some of this relates to the very way that the measures themselves are specified . For example , the NHSN ’ s current CLABSI criteria were introduced in the 1980s ; it ’ s actually quite a complicated set of steps to identify and confirm a CLABSI . One of the important steps is ruling out other infections – so , identifying the fact that the infection is not secondary to another site such as a urinary tract infection or pneumonia – this takes a great deal of analysis of the data that are available . It ’ s very hard to translate that into a computable , automatable steps , so one of the ways that we can address that is by recognizing that CLABSIs are part of a larger group of infections called hospital-onset bacteremia – that , along with Clostridioides difficile ( C . diff .) identified from a diagnostic laboratory test and concurrent antimicrobial treatment , and late-onset sepsis and meningitis in neonates present opportunities for automation of microbiology results and antimicrobial use data for surveillance and quality measurement purposes .”
Pollock reported that there is work underway at NHSN to develop the hospital-onset bacteremia , C . diff and late-onset sepsis and meningitis-in-neonates measures for submission to the National Quality Forum and for implementation in NHSN reporting . “ In the coming months , we will be able to describe more completely what the specifications are for these measures , but the intent is to use both the microbiology results as well as the AU data together in conjunction with each other with the treatment providing indication of certain types of microbiology result settings that the practitioners have deemed this an infection ,” he explained . “ The combination of data types , which we know are available in structured , automatable form , is a very important part of our path forward with NHSN and a vision for the future for additional HAI measures .”
Just as the Affordable Care Act was impactful , the 21st Century Cures Act — signed into law on Dec . 13 , 2016 — also provides an important impetus for data automation and interoperable healthcare IT systems . “ While the Act was primarily designed to accelerate development and access to new drugs , there are several important provisions , including those aimed at achieving widespread interoperability among health IT systems ,” Pollock said . “ These provisions include requiring health IT suppliers to make all data elements of a patient ’ s record available without special effort via Application Programming Interfaces ( APIs ). Federal rules require use of the Health Level Seven ( HL7 ) Fast Healthcare Interoperability Resources ( FHIR ) standard for data elements made accessible via APIs . So , over the course of several years , we will see federal regulations going into effect that are going to incentivize and accelerate the opportunity for data automation as pertaining to surveillance and quality measures .”
The FHIR standard — the acronym stands for Fast Healthcare Interoperability Resources — focuses on easy implementation , standardizes core healthcare data elements ( known as FHIR resources ) such as patients , admissions , diagnostic reports , and medications , and combines features of prior HL7 versions , such as data format standards , with web service technologies , namely APIs , that have gained wide , cross-industry use .
“ The FHIR standard is going to be widely implemented and used for a variety of purposes , including the processing of claims , as well as clinical data communications ,” Pollock said . “ We are intending to follow the FHIR path where EHR systems data automation is integrally important for NHSN surveillance . EHRs will update when patients are admitted to the hospital and go through an episode of care . The FHIR resources and those updates will be moved onto a FHIR server , which includes elements at the patient level that can be extracted and used . Initially , our intention is as a data push in which the EHR delivers FHIR resource bundles – HAI and AUR numerator , denominator , line-level patient data — to NHSN . So , here is an automatable process that reuses data
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