None listed
Conditions
Brief summary
In a previous audit, we retrospectively studied 418,897 batches of tests in 42,701 patients for a total of 2.5 million individual measurements of nine laboratory results (Loekito et al, Common laboratory tests predict imminent death in ward patients, Resuscitation 2013; 84(3):280-285). We identified simple laboratory abnormalities (e.g. high plasma urea, low blood bicarbonate level, low albumin), which either alone, but even more so when clustered together in particular pattern were associated with a higher risk of poor outcome (MET call, ICU admission or death) by the following calendar day. This finding suggested that, using routinely measure laboratory results, we might be able to identify those patients, who are at high risk of such outcomes and that, we might, therefore, be in a position to notify the ward where these patients are located of such increased risk. In this pilot study, we plan to extend our assessment the feasibility of such a notification system following a pilot study approved by the Human Research Ethics Committee in 2011. Specifically, we plan to continuously scan the raw data emerging form the pathology lab computers with focus on the 8th floor wards. Then, using a computerized risk identification system based on our retrospective analysis, we plan to identify patterns of laboratory data that identify patients at high risk of the above adverse outcomes by the next calendar day. Once such identification has been achieved, we plan to send every second notification to a dedicated pager carried by the Medical Emergency Team (MET) registrar, who will then visit the patient, review his/her laboratory results, contact the primary team to inform them of the laboratory concerns and modify treatment (if appropriate and agreed) following such discussion . Such notification will occur electronically by automated messages sent to the pager. The purpose of the pilot study is to assess: 1. How many notifications such a system would generate per day for the 8th floor wards; 2. Whether such a system can reliably deliver such notifications; 3. How many at risk patients are identified by such a system and how many are missed per month; 4. The outcome of patients identified by such a system.
Interventions
Using data from the previous study (Loekito et al, Common laboratory tests predict imminent death in ward patients, Resuscitation, 2013;84(3):280-285) we have identified patterns and tests with given sensitivity and specificity that can be used to identify at risk patients. We plan to obtain raw level data generated by the Pathology Lab computers as they come on stream and, subsequent to their acquisition by the CERNER system, deliver them to a server where they can be analyzed by software desig
Using data from the previous study (Loekito et al, Common laboratory tests predict imminent death in ward patients, Resuscitation, 2013;84(3):280-285) we have identified patterns and tests with given sensitivity and specificity that can be used to identify at risk patients. We plan to obtain raw level data generated by the Pathology Lab computers as they come on stream and, subsequent to their acquisition by the CERNER system, deliver them to a server where they can be analyzed by software designed to identify high-risk patterns. When such a pattern is identified in a patient who is electronically known to be located on the 8th floor, we plan to send an electronic message to a designated pager carried by the Medical Emergency Team (MET) registrar notifying her/him that patient X is at risk. As an example, if a patient was identified to be at risk of a Medical Emergecny Team (MET) call, the message might take this form “MR John Citizen on ward 8N has major laboratory abnormalities”. However, because of workload issues, only one in two alerts will be sent to the MET registrar’s pager (approximately 2 alerts/day). Patient's whose alert is sent to the MET registrar's pager will form the intervention group. The MET registrar will then review the participant at the next earliest opportunity. At the review the MET registrar will assess the patient and assess the patient's pathology data. The MET registrar will then make treatment decisions and contact the patient's primary team and modify treatment (if appropriate and agreed) following such discussion. The duration of the intervention period is 12 months. All data collections on treatment, characteristics and outcomes will be by means of review of scanned medical records after the patient has been discharged.
Sponsors
Austin Health
Study design
Allocation
Randomised controlled trial
Intervention model
Parallel
Primary purpose
Prevention
Masking
Blinded (masking used) (Subject, Caregiver)
Eligibility
Sex/Gender
All
Healthy volunteers
No
Inclusion criteria
All patients admitted to the acute surgical ward of the Austin Hospital.
Exclusion criteria
Nil
Outcome results
None listed