Table 1. Comparison of laboratory investigations using the conventional approach and the LAS (Clin...
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Transcript of Table 1. Comparison of laboratory investigations using the conventional approach and the LAS (Clin...
Table 1. Comparison of laboratory investigations using the conventional approach and the LAS (Clin Chem 45:8 1168-1175 (1999)
Conventional LAS
ResultsMean number of tests ordered 32.7 17.8
t-Test for two related samples t = 5.4, P <0.01
Mean number of samples collected 7.5 5.8
t-Test for two related samples t = 3.4, P <0.02
ObservationsMean costs, $ $232 $194
t-Test for two related samples t = 3.3, P <0.05
Turnaround time (mean no. of days) 3.2 1
Diagnostic accuracy 66% 100%
Number of referrals 12 0
Established guidelines: thyroid testing
Mean number of tests ordered 1.7 1.7
Total number of sample collections 12 8
No established guidelines: hepatitis and autoimmune testing
Mean number of tests ordered 6.7 3.3
Total number of sample collections 38 30
Results returned negative
Mean number of tests ordered 4.8 2
Total number of sample collections 14 9
Retrieve Comment
Modify if required
Enter Data
Generate Rule
Search Rule List
Update rule list
Update comment list
RULE EXISTSSearch comment List
NEW RULEEnter new Comment
Search Rule List
Variables UsedTFT application
• Qualitative– Gender
– Clinical details
– Drug therapy
• Quantitative– Age
– Total T4
– TSH
– Free T4
– Free T3
Adult decision rangesTSH (mu/L)
• Decision Range– >=60
– >=20; <60
– >=10; <20
– >5; <10
– >4; <=5
– >=0.4; <4
– >=0.25; <0.4
– <0.25
• Description– Markedly high
– Very High
– High
– Mildly raised
– Near URL
– Normal
– Near LRL
– Below detection limit
Clinical and Drug detailsTFT
• CLINICAL DETAILS– A. Suspected
hyperthyroidism– B. Suspected
hypothyroidism– C.Post Radioiodine therapy
– D. Post thyroid surgery– E. On thyroxine treatment– F. On T3 treatment– G. On Carbimazole
– H. On PTU– Z. Non-specific
• DRUG THERAPY– A. Lithium
– B. Oestrogens
– C. Amiodarone
– D. Beta-blockers
– E. Glucocorticoids
– F. Phenytoin
– G. Carbamazepine
– H. Androgens
– Z. No relevant drugs
Variables UsedProtein electrophoresis
• Quantitative– patients age– serum total protein, albumin, -globulin, paraprotein concentrations
• Semi-quantitative– Visual assessment of albumin, 1,,2,, 1,,,,2,, and concentrations
• Qualitative– patients gender
– Visual inspection of zones and interzones (11 variables), e.g. 1
zone, - interzone findings
Primer knowledge basesTFT application
Name Cases Case TypesN1 44 Euthyroid
N6 44 Euthyroid (post RAI)
N15 143 Suppressed TSH(thyrotoxicosis)
N16 143 High TSH(Hypothyroid)
Etc…TOTAL 1142
Primer knowledge basesprotein electrophoresis
Name Cases Case TypesS1 6 Normal patterns
S2 18 Chronic inflammationpatterns
S3 32 Beat-gamma fusion
S4 34 Altered alb/globulin fractions
Etc…TOTAL 206
Performance evaluation - TFTPercentage of automatically assigned interpretations (AAI) per TFT batch
60
70
80
90
100
Consecutive TFT batches
Perc
enta
ge A
AI*
per
batc
h
TFT application statistics
• Number of variables specified: 8
• Number of options/decision levels: 70
• Number of theoretical data combinations: 20,412,000
• Number of cases entered via primer knowledge bases: 1142
• Number of rules: >2900
• Percentage of automatically assigned interpretations [using the primer knowledge bases]– At the outset: 66%
– After the first 500 patient cases: 70%
– Maximum achieved: 95%
• Number of interpretations rejected: <1%
electrophoresis application statistics
• Number of variables specified: 23 (22 used in rule generation)
• Number of options/decision levels: 183
• Number of theoretical data combinations: 8,800,000,000,000,000,000
• Number of cases entered via primer knowledge bases: 206
• Number of rules: 350
• Percentage of automatically assigned interpretations [using the primer knowledge bases]– At the outset: 78%
– After the first 500 patient cases: 72%
– Maximum achieved: 70-80%
• Number of interpretations rejected: 0
Clinical evaluationTFT application
(27 TFT requests on 15 randomly-selected new referrals to a thyroid clinic were studied; 2 evaluators participated)
Evaluator 1(physician)
Evaluator 2(biochemist)
Do you agree with thethyrometabolic classification in thereport? Complete agreement Partial agreement Complete disagreement
96%4%0%
85%11%4%
Was the interpretation clear in styleand presentation?
81% 96%
Were any references in theinterpretation to the followingitems appropriate? Specific thyroid diagnoses [5] Interfering conditions/drugs [4] Further tests on the sample [1] Followup recommendations [16] Treatment recommendations [2]
Actual no. of‘No’ answers
04000
Actual no. of‘No’ answers
10110
Clinical evaluationElectrophoresis application
(115 questionnaires circulated, 64 returned, 56% response)
Question Answer - YES Answer - NO
1. Did you require aninterpretation? 79% 21%
2. Was the interpretation helpful?95% 5%
3. Did the interpretation confirm anexisting or suspected diagnosis? 24% 76%
4. Did the interpretation lead to anew diagnosis not previouslysuspected?
0% 100%
5. Did you perform furtherinvestigations on the basis of theinterpretation?
14% 86%
Clinical evaluationElectrophoresis application
(115 questionnaires circulated, 64 returned, 56% response)
Question Answer - YES Answer - NO
1. Did you require aninterpretation? 79% 21%
2. Was the interpretation helpful?95% 5%
3. Did the interpretation confirm anexisting or suspected diagnosis? 24% 76%
4. Did the interpretation lead to anew diagnosis not previouslysuspected?
0% 100%
5. Did you perform furtherinvestigations on the basis of theinterpretation?
14% 86%
Performance evaluationElectrophoresis application
0
20
40
60
80%
AA
I pe
r ba
tch
of 1
00
case
s
100 200 300 400 500
Total Number of reports entered
Without primerWith primer
Performance evaluationElectrophoresis application
(to demonstrate knowledge acquisition)
0
20
40
60
80%
AA
I pe
r ba
tch
of 1
00
case
s
100 200 300 400 500
Total Number of reports entered
All reportslabelled reports
Cooperativity
DATA
KBS
Diagnostic outcomeInterpretation
Cooperativity
KBS-1Comment
Diagnostic outcome (1) KBS-i
IntegratingComment
KBS-2Comment
Diagnostic outcome (2)
KBS-4Comment
Diagnostic outcome (4)
KBS-3Comment
Diagnostic outcome (3)
CooperativityOrgan-related profiles
• Renal profile – Na, K, Urea, Creatinine
• Bone profile– Ca, Alb, Corr Ca, Phosphate, AlkPhos
• Liver profile– Bili, Alb, T Protein, AST, Alk Phos, GGT
• Cardiac profile
• Lipid profile
CooperativityDecision Levels
120 mmol/L
110 mmol/L
140 mmol/L
130 mmol/L
160 mmol/L
150 mmol/LPlasmaSodium Concentration
Rule Elements
R Tr
L Tl
B Tb
C Tc
i Clin TiSexAge
Diagnostic outcomes CommentsRules and rule elements
Integrating rule and its elements
CooperativityPrimer knowledge bases
Universe KBS (Primers are subsets)
PRIMER
RenalKBS
PRIMER
BoneKBS
PRIMER
LiverKBS
PRIMER
Cardiac/LipidKBS
Selected Diagnostic Outcomes
• Renal profile– prerenal impairment
– Renal impairment
– hyponatraemia
– hypokalaemia
– hypernatraemia
– hyperkalaemia
– etc
• Bone profile– osteomalacia pattern
– renal osteomalacia
– primary hyperparathyroidism
– etc
Profile interpretations
• Renal– Na 133 [Low]
– K 5.8 [Raised]
– Urea 30.5 [raised]
– Creatinine 400 [Raised]
• Interpretation– Renal impairment with
hyperkalaemia and mild hyponatraemia
• Diagnostic outcome– renal impairment
• Bone– Ca 1.94 Corr Ca 2.04 [Low]
– Alb 35 [Normal]
– Phosphate 1.88 [High]
– Alk Phos 450 [High]
• Interpretation– Hypocalcaemia, raised
phosphate and Alk Phos: osteomalacia pattern
• Diagnostic outcome– osteomalacia pattern
Cooperative KBS output
• Renal KBS comment– Renal impairment with hyperkalaemia and mild hyponatraemia.
[DO= renal impairment]
• Bone KBS comment– hypocalcaemia, raised phosphate and Alk Phos. DO =
osteomalacia pattern.
• Integrating KBS comment– These results are consistent with renal failure and associated renal
osteodystrophy
Decision Support SystemsSupport for Health Care Professionals
Alarm/Alert SystemsAlertA significant but mild trend in a variable, or theachievement of a specified level by the variable.
Univariate Alerts: based on a single variableMultivariate Alerts: based on multiple variables
AlarmA marked trend in single variable, or the achievementof a critical specified level by the variable, and/or thepresence of several (multiple) alerts or multivariatealerts.
Univariate Alarms: based on a single variableMultivariate Alarms: based on multiplesvariables
Alarm/Alert Systems
Methods
Alarms/alerts based on Critical Values
Alerts/alarms based on Critical Trends Mathematical/Statistical methods Biodynamic Models KBS/Temporal reasoning systems
Knowledge-based (intelligent) alerts/alarms Cooperative systems
Alarm/Alert Systems
Univariate AlertsBased onSignificantValues
If Sodium_Concentration <125 mmol/lThenSet Alert [Sodium_Concentration] ON;End;
Based onSignificantTrends
If Potassium_Trend >0.1 mmol/l/hrThenSet Alert [K_Trend] ONEnd;
Alarm/Alert SystemsMultivariate Alerts
Based onSignificantValues
If Sodium<125and Water_Balance > 1000mland Urea NOT RAISEDThen Set Alert [Dilution_Hyponatraemia] ONEnd;
Based onSignificantTrends
If Potassium_Trend >0.1 mmol/l/hrand K_Infusion > 5 mmol/hrand Potassium_Concentration>4.5 mmol/lThen
Set Alert [Hyperkalaemia_ trend] ONEnd;
Knowledge-based alerts
If Sodium<125 mmol/land Urine Osmolality > 350 mosm/kgand cvp NORMALand Urea NOT RAISEDand Euthyroid/EuAdrenaland CARBAMAZEPINE TherapyThen Set Alerts [SIADH]; [CBZ effect] ONEnd;
Alarm/Alert SystemsCalibration
Alarms, when triggered, should lead to an immediate change inpatient care.
Alarms which do not lead to a change in patient care (false alarms)should be suppressed on subsequent occasions, or converted to analert status.
Suppression could also be achieved by knowledge-based revision ofthe Trigger Thresholds.
Repeated alarms may be ignored.
Alarms need to be responsive to the clinical context
Alarms should draw attention to new or strange findings.
Alarm/Alert Systems
Univariate AlarmsBased on SignificantValues
If Sodium_Concentration <120 mmol/l ThenSet Alarm [Hyponatraemia] ON;
End;
Based on SignificantTrends
If Potassium_Trend >0.5 mmol/l/hr ThenSet Alarm [K_Trend] ON
End;
Alarm/Alert SystemsMultivariate Alarms
Based on SignificantValues
If Sodium<120and Water_Balance > 1000mland Urea NOT RAISEDThen Set Alarm [Dilution_Hyponatraemia] ONEnd;
Based on SignificantTrends
If Potassium_Trend >0.5 mmol/l/hrand K_Infusion > 5 mmol/hrand Potassium_Concentration>5.0 mmol/lThen
Set Alarm [Hyperkalaemia_ trend] ONEnd;
Knowledge-basedalarms
If Sodium<115and Alert [SIADH] ONand Alert [Sodium_Trend] POSITIVEand Alert [Hyponatraemia] ONThen Suppress Alarm [Hyponatraemia]End;
Alarm/Alert SystemsVariables specified in the Alarms/Alerts System.
Test* Type** Categories***
Renal Sub-system:Sodium (mmol/l) QN 20Potassium (mmol/l) QN 20Urea (mmol/l) QN 20Creatinine (mol/l) QN 20Bicarbonate (mmol/l) QN 20Chloride (mmol/l) QN 5Glucose (mmol/l) QN 8
Acid-Base Sub-system:Arterial blood pH QN 5Arterial blood pCO2 QN 5Arterial blood pO2 QN 9
Haemodynamic Sub-system:Central venous pressure (mmHg) QN 4Cardiac failure index QL 2Oedema index QL 2Temperature index QL 3Pulse rate QN 5Blood pressure index QL 3Weight change QN 5Urine Output QN 6Sodium balance (mmol/day) QN 6Sodium output (mmol/day) QN 5Potassium balance (mmol/day) QN 4Potassium output (mmol/day) QN 4Nitrogen balance (g/day) QN 6Nitrogen output (g/day) QN 5Water balance (litres/day) QN 6
Footnote: *All laboratory tests are plasma concentrations or activities unless stated otherwise. **Each test is classified asquantitative (QN) or qualitative (QL). ***The number of decision levels specified is given for quantitative variables and thenumber of options specified for qualitative variables.
Alarm/Alert SystemsVariables specified in the Alarms/Alerts System.
Test* Type** Categories***
Critical Care Chemistry Sub-system:Bilirubin (mol/l) QN 15Blood prothrombin time QN 5Albumin (g/l) QN 14Total protein (g/l) QN 13Aspartate aminotransferase (u/l) QN 15Amylase (u/l) QN 5Calcium (mmol/l) QN 20Phosphate (mmol/l) QN 19Creatine kinase (u/l) QN 15Alkaline phosphatase (u/l) QN 17Alanine aminotransferase (u/l) QN 15Gamma-glutamyl transferase (u/l) QN 15Urate (mmol/l) QN 4Triglyceride (mmol/l) QN 18Blood haemoglobin concentration QN 8Blood white cell count QN 7Magnesium (mmol/l) QN 6
Variables considered at the Integrating System level:Renal Diagnostic Outcome QL Coded entries 000-099Acid-Base Diagnostic Outcome QL Coded entries 000-099Haemodynamic Diagnostic Outcome QL Coded entries 000-099Critical Care Chemistry Diagnostic Outcome QL Coded entries 000-099
Variables available to all participating systems:Age QN Adult, ChildSex QL M, FClinical information QL Coded entries A-Z
Footnote: *All laboratory tests are plasma concentrations or activities unless stated otherwise. **Each test is classified asquantitative (QN) or qualitative (QL). ***The number of decision levels specified is given for quantitative variables and thenumber of options specified for qualitative variables.
Alarm/Alert SystemsExample of output of the alarms/alerts System.
60 year old male with pyrexia (39Celsius)
PlasmaSodium 152 mmol/l[135-145]Potassium 3.9 mmol/l[3.5-5.0]Urea 4.5 mmol/l[3.0-7.0]Creatinine 98 mol/l [60-100]
Diagnostic OutcomesRenal DSS: Univariate Alert: Moderate hypernatraemia.Acid-Base DSS: No Results.Haemodynamic DSS: Univariate Alert: Pyrexia
Critical Care Chemistry DSS: No Results.
Integrating InterpretationIntegrating KBS: Multivariate Alert: Dehydration in a pyrexial
patient.
Decision Support SystemsSupport for Health Care Professionals
• Microbiology Applications– Computerised infectious disease monitor (Evans, 1986). Computer-
generated alarms were produced for (1) all patients with hospital-acquired infections; (2) patients on antibiotics to which they were not susceptible; (3) who could be receiving less expensive antibiotics; (4) who were receiving prophylactic antibiotcis for too long. Use of the system saved time for hospital infection control staff, and improved antibiotic use.
– MRSA monitor (Safran, Scherrer 1994). Infection control nurses were provided daily with computer-generated lab alerts giving details of MRSA+ together with re-admission alerts giving details of new admissions previously known to be colonised with MRSA. System saved time for ICNs and helped as a preventive warning.
Decision Support SystemsSupport for Health Care Professionals
• Histopathology/Cytopathology applications– PAPNET Cervical Screening Neural Network– Telepathology
Decision Support SystemsSupport for Health Care Professionals
• Haematology applications– Diamond and Nguyen/Coulter Electronics.
Various DSS applications for use with Coulter systems, flow cytometry, classification of haematological malignancies etc.
EQA Applications
• EQA Toolkit