SILAM: Integrating Laboratory Information System within the Liguria Region Electronic Health Record

2014 ◽  
pp. 1294-1297
Author(s):  
Alessandro Tagliati ◽  
Valeria Pupella ◽  
Roberta Gazzarata ◽  
Mauro Giacomini
Keyword(s):  
Information System ◽  
Electronic Health Record ◽  
Health Record ◽  
Laboratory Information System ◽  
Electronic Health

scholarly journals Creation and Use of an Electronic Health Record Reporting Database to Improve a Laboratory Test Utilization Program

2018 ◽  
Vol 09 (03) ◽  
pp. 519-527 ◽  
Author(s):  
Danielle Kurant ◽  
Jason Baron ◽  
Genti Strazimiri ◽  
Kent Lewandrowski ◽  
Joseph Rudolf ◽  
...  
Keyword(s):  
Information System ◽  
Laboratory Test ◽  
Electronic Health Record ◽  
Health Care Systems ◽  
Management Program ◽  
Health Record ◽  
Laboratory Information System ◽  
Utilization Management ◽  
Laboratory Utilization ◽  
Electronic Health

Objectives Laboratory-based utilization management programs typically rely primarily on data derived from the laboratory information system to analyze testing volumes for trends and utilization concerns. We wished to examine the ability of an electronic health record (EHR) laboratory orders database to improve a laboratory utilization program. Methods We obtained a daily file from our EHR containing data related to laboratory test ordering. We then used an automated process to import this file into a database to facilitate self-service queries and analysis. Results The EHR laboratory orders database has proven to be an important addition to our utilization management program. We provide three representative examples of how the EHR laboratory orders database has been used to address common utilization issues. We demonstrate that analysis of EHR laboratory orders data has been able to provide unique insights that cannot be obtained by review of laboratory information system data alone. Further, we provide recommendations on key EHR data fields of importance to laboratory utilization efforts. Conclusion We demonstrate that an EHR laboratory orders database may be a useful tool in the monitoring and optimization of laboratory testing. We recommend that health care systems develop and maintain a database of EHR laboratory orders data and integrate this data with their laboratory utilization programs.

scholarly journals The Benefits and Challenges of an Interfaced Electronic Health Record and Laboratory Information System: Effects on Laboratory Processes

2017 ◽  
Vol 141 (3) ◽  
pp. 410-417 ◽  
Author(s):  
Athena K. Petrides ◽  
Ida Bixho ◽  
Ellen M. Goonan ◽  
David W. Bates ◽  
Shimon Shaykevich ◽  
...  
Keyword(s):  
Information System ◽  
Electronic Health Record ◽  
Government Regulation ◽  
Turnaround Time ◽  
Health Record ◽  
Laboratory Information System ◽  
Before And After ◽  
Electronic Health ◽  
Ordered Data ◽  
The Impact

Context.— A recent government regulation incentivizes implementation of an electronic health record (EHR) with computerized order entry and structured results display. Many institutions have also chosen to interface their EHR with their laboratory information system (LIS). Objective.— To determine the impact of an interfaced EHR-LIS on laboratory processes. Design.— We analyzed several different processes before and after implementation of an interfaced EHR-LIS: the turnaround time, the number of stat specimens received, venipunctures per patient per day, preanalytic errors in phlebotomy, the number of add-on tests using a new electronic process, and the number of wrong test codes ordered. Data were gathered through the LIS and/or EHR. Results.— The turnaround time for potassium and hematocrit decreased significantly (P = .047 and P = .004, respectively). The number of stat orders also decreased significantly, from 40% to 7% for potassium and hematocrit, respectively (P < .001 for both). Even though the average number of inpatient venipunctures per day increased from 1.38 to 1.62 (P < .001), the average number of preanalytic errors per month decreased from 2.24 to 0.16 per 1000 specimens (P < .001). Overall there was a 16% increase in add-on tests. The number of wrong test codes ordered was high and it was challenging for providers to correctly order some common tests. Conclusions.— An interfaced EHR-LIS significantly improved within-laboratory turnaround time and decreased stat requests and preanalytic phlebotomy errors. Despite increasing the number of add-on requests, an electronic add-on process increased efficiency and improved provider satisfaction. Laboratories implementing an interfaced EHR-LIS should be cautious of its effects on test ordering and patient venipunctures per day.

scholarly journals Real-Time Intraoperative Consultation Reporting in the Electronic Health Record

2020 ◽  
Vol 154 (3) ◽  
pp. 387-393
Author(s):  
Molly E Klein ◽  
Joseph W Rudolf ◽  
Maryna Tarbunova ◽  
Tanya Jorden ◽  
Susanna R Clark ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Real Time ◽  
Laboratory Medicine ◽  
Clinical Impact ◽  
Final Report ◽  
Health Record ◽  
Laboratory Information System ◽  
Surgical Team ◽  
Operative Note ◽  
Electronic Health

Abstract Objectives We sought to make pathologists’ intraoperative consultation (IOC) results immediately available to the surgical team, other clinicians, and laboratory medicine colleagues to improve communication and decrease postanalytic errors. Methods We created an IOC report in our stand-alone laboratory information system that could be signed out prior to, and independent of, the final report, and transfer immediately to the electronic health record (EHR) as a preliminary diagnosis. We evaluated two metrics: preliminary (IOC) result review in the EHR by clinicians and postanalytic errors. Results We assessed 2,886 IOC orders from the first 22 months after implementation. Clinicians reviewed 1,956 (68%) of the IOC results while in preliminary status, including 1,399 (48%) within the first 24 hours. We evaluated 150 cases preimplementation and 300 cases postimplementation for discrepancies between the pathologist’s IOC result and the IOC result recorded by the surgeon in the operative note. Discrepancies dropped from 12 of 150 preimplementation to 6 of 150 and 7 of 150 in postimplementation years 1 and 2. One of the 25 discrepancies had a major clinical impact. Conclusions Real-time reporting of IOC results to the EHR reliably transmits results immediately to clinical teams. This strategy reduces but does not eliminate postanalytic interpretive errors by clinical teams.

An integrated electronic health record and information system for Australia?

2000 ◽  
Vol 172 (1) ◽  
pp. 25-27 ◽  
Author(s):  
Christopher D Mount ◽  
Christopher W Kelman ◽  
Leonard R Smith ◽  
Robert M Douglas
Keyword(s):  
Information System ◽  
Electronic Health Record ◽  
Health Record ◽  
Electronic Health

scholarly journals Measuring the rate of manual transcription error in outpatient point-of-care testing

2019 ◽  
Vol 26 (3) ◽  
pp. 269-272 ◽  
Author(s):  
James A Mays ◽  
Patrick C Mathias
Keyword(s):  
Information System ◽  
Electronic Health Record ◽  
Laboratory Tests ◽  
Point Of Care ◽  
Health Record ◽  
Laboratory Information System ◽  
Point Of Care Testing ◽  
Ambulatory Clinic ◽  
Transcription Error ◽  
Clinically Significant

Abstract Many point-of-care laboratory tests are manually entered into the electronic health record by ambulatory clinic staff, but the rate of manual transcription error for this testing is poorly characterized. Using a dataset arising from a duplicated workflow that created a set of paired interfaced and manually entered point-of-care glucose measurements, we found that 260 of 6930 (3.7%) manual entries were discrepant from their interfaced result. Thirty-seven of the 260 (14.2%) errors were discrepant by more than 20% and included potentially dangerous mistranscriptions. An additional 37 (14.2%) errors were due to inclusion of non-numeric characters. Staff-entered result flags deviated from the result flag generated in the laboratory information system in 5121 of 6930 (73.9%) pairs. These data demonstrate that clinically significant discrepancies for clinic-entered point of care results occurred at a rate of approximately 5 per 1000 results and they underline the importance of interfacing instruments when feasible.

Electronic Health Record Proposal for Long-Term Preservation

2013 ◽  
pp. 529-548
Author(s):  
Juanjo Bote
Keyword(s):  
Information System ◽  
Electronic Health Record ◽  
Digital Libraries ◽  
Reference Model ◽  
Digital Preservation ◽  
Health Record ◽  
Information Unit ◽  
Term Basis ◽  
Electronic Health

This chapter introduces a model approach to long-term digital preservation of Electronic Health Record (EHR). The long-term digital preservation is an emerging trend in the environment of digital libraries. However, legal or business needs may cause the use of digital preservation strategies in different fields. This is the case of the EHR as part of the information system of a healthcare institution. After a reasonable space of time without activity, an EHR becomes a passive information unit. Consequently, this passive information unit remains safe in a separate information system where the main purpose is digitally preserving this information on a long-term basis. There are two appropriate methodologies, Trustworthy Repository Audit and Certification Criteria (TRAC) and a Reference Model for Open Archival Information System (OAIS). These methodologies can widely be adopted by health care organizations to preserve EHR in the long-term.

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