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Table 1. Comparison of laboratory investigations using the conventional approach and the LAS (Clin Chem 45:8 1168-1175 (1999) ConventionalLAS Results Mean.

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Presentation on theme: "Table 1. Comparison of laboratory investigations using the conventional approach and the LAS (Clin Chem 45:8 1168-1175 (1999) ConventionalLAS Results Mean."— Presentation transcript:

1 Table 1. Comparison of laboratory investigations using the conventional approach and the LAS (Clin Chem 45: (1999) ConventionalLAS Results Mean number of tests ordered t-Test for two related samplest = 5.4, P <0.01 Mean number of samples collected t-Test for two related samplest = 3.4, P <0.02 Observations Mean costs, $$232$194 t-Test for two related samplest = 3.3, P <0.05 Turnaround time (mean no. of days)3.21 Diagnostic accuracy66%100% Number of referrals120 Established guidelines: thyroid testing Mean number of tests ordered Total number of sample collections128 No established guidelines: hepatitis and autoimmune testing Mean number of tests ordered Total number of sample collections3830 Results returned negative Mean number of tests ordered4.82 Total number of sample collections149

2 Retrieve CommentModify if required Enter Data Generate RuleSearch Rule List Update rule listUpdate comment list RULE EXISTS Search comment List NEW RULE Enter new Comment Search Rule List

3 Variables Used TFT application Qualitative –Gender –Clinical details –Drug therapy Quantitative –Age –Total T4 –TSH –Free T4 –Free T3

4 Adult decision ranges TSH (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

5 Clinical and Drug details TFT 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

6 Variables Used Protein 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

7 Primer knowledge bases TFT application

8 Primer knowledge bases protein electrophoresis

9 Performance evaluation - TFT Percentage of automatically assigned interpretations (AAI) per TFT batch

10 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%

11 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

12 Clinical evaluation TFT application (27 TFT requests on 15 randomly-selected new referrals to a thyroid clinic were studied; 2 evaluators participated)

13 Clinical evaluation Electrophoresis application (115 questionnaires circulated, 64 returned, 56% response)

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15 Performance evaluation Electrophoresis application

16 Performance evaluation Electrophoresis application (to demonstrate knowledge acquisition)

17 Cooperativity DATA KBS Diagnostic outcomeInterpretation

18 Cooperativity KBS-1 Comment Diagnostic outcome (1) KBS-i Integrating Comment KBS-2 Comment Diagnostic outcome (2) KBS-4 Comment Diagnostic outcome (4) KBS-3 Comment Diagnostic outcome (3)

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20 Cooperativity Organ-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

21 Cooperativity Decision Levels 120 mmol/L 110 mmol/L 140 mmol/L 130 mmol/L 160 mmol/L 150 mmol/L Plasma Sodium Concentration

22 Rule Elements R Tr L Tl B Tb C Tc i Clin Ti SexAge Diagnostic outcomesComments Rules and rule elements Integrating rule and its elements

23 Cooperativity Primer knowledge bases Universe KBS (Primers are subsets) PRIMER Renal KBS PRIMER Bone KBS PRIMER Liver KBS PRIMER Cardiac/ Lipid KBS

24 Selected Diagnostic Outcomes Renal profile –prerenal impairment –Renal impairment –hyponatraemia –hypokalaemia –hypernatraemia –hyperkalaemia –etc Bone profile –osteomalacia pattern –renal osteomalacia –primary hyperparathyroidism –etc

25 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

26 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

27 Decision Support Systems Support for Health Care Professionals

28 Alarm/Alert Systems

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38 Decision Support Systems Support 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.

39 Decision Support Systems Support for Health Care Professionals Histopathology/Cytopathology applications –PAPNET Cervical Screening Neural Network –Telepathology

40 Decision Support Systems Support 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.

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42 EQA Applications EQA Toolkit

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