HL7 clinical risk alerts engine in hospitalized patients
1. HL7 CLINICAL LABORATORY RISK ENGINE
ALERTS IN HOSPITALIZED PATIENTS
Dr. Humberto F. Mandirola Brieux
HL7 ARGENTINA, HOSPITAL ITALIANO de Buenos Aires,
HOSPITAL BELGRANO
16th International HL7 Interoperability Conference 2016
Genoa, June 13 - 15 2016
Humberto Fernán Mandirola Brieux abcd, Fernando Campos ab,
Diego Kaminker b, Sebastian Guillen c, Fernando La Rosab
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2. •Introduction of the research.
•Background of Alert in hospitalized
patients in Critical Care Unit.
•Results.
•Conclusions
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AGENDA
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3. latitude 34°33'0.54"S
longitude 58°31'32.33"O
This study was conducted in the Belgrano Hospital
It is an acute Hospital of medium level
200 Beds
8 Critical care unit beds
250 Physicians
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4. INTRODUCTION
•Focus on Abnormal Clinical
Laboratory risk values detection.
• An alert software was used.
•Clinical Laboratory risk often goes
unnoticed.
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5. UNDETECTED CLINICAL
LABORATORY RISK PREVALENCE
•Undetected clinical laboratory risk values
is a serious concern.
•The prevalence of undetected clinical
laboratory risk values problems is higher
than believed.
•It’s a serious underestimated problem.
•The prevalence is 30%, out of which
50% goes undiagnosed.
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6. Others underestimates subjects in
Hospitalized patient
•Alert Systems can help in issues like:
•Antibiotic therapy
•Allergies
•Nutrition Aspect
•Drug interactions
•Drug Contraindications
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Not sure how to deal with Undetected
abnormal Lab values?
Don't Bury your head in the Sand..
It seems obvious but it is not
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8. History Project
•Our aim to diminish the
undetected clinical lab risk value
rate.
•Clinical Laboratory risk aspects
assessed by doctors.
•Multidisciplinary approach.
•Creation of an automatic alarm.
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9. THE ALERT ENGINE
•The alert engine was programed in C#.
•We used different standards.
•LOINC to laboratory data.
•ICD10 to medical record data.
•HL7 2.4 to transfer data.
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13. Inclusion & Exclusion Criteria
•This study is a randomized controlled trial, which provides
the most effective way to exclude external influences
between samples.
•We had to exclude eight patients in total, (3 from the
Alert group and 5 from the control group).
•We excluded these patients because some of these
patient’s data were missing, like laboratory results or
clinical data.
•After the exclusion of these patients, the total number of
patients of both groups was 292.
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14. HOW THE ALERT ENGINE WORKS
Mirth Connect
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17. CONCLUSION
•. Results have shown that the clinical
laboratory risk alert we built was of significant
help.
•Detection of clinical laboratory risk increased
by fourteen % in patients controlled with an
alarm system.
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18. DISCUSION
•It is important to avoid
overabundance of alerts.
•Early detection of laboratory risk
plays a fundamental role in
reducing morbidity in patients.
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19. Email me at hmandirola@biocom.com
Thank you
"Be the change you want to see in the world“
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