based decision support, 171–173 AIDS, trial registries, 146

A

ABEL system, causal reasoning, 75 Adverse drug events (ADEs), hospital-

based decision support, 171–173 AIDS, trial registries, 146

AI/Rheum system, 39 Alerting systems, 163–166

for adverse drug events (ADEs), 171–173

Vanderbilt WizOrder CPOE, 239–241

Antibiotic assistant, 174–175 Artificial intelligence, 38–39 Associations, and ontologies, 81

B

Bayesian systems Bayes’ Rule, 31–33, 108 development of, 108–109 problems of, 74, 76 Belief networks, 76

Biological computing, 60–61 Boolean logic, 26–29, 173–174

C

Caduceus system, 75

CARE computer language, 193 Case-based reasoning, and system

design, 78

CASNET system, 64, 112–113 causal reasoning, 74–75 Causal reasoning

and diagnostic thinking, 106 and system design, 74–75

CD-ROM, patient health information on, 254–255

Certainty factors, 34, 73

CHF Advisor, causal reasoning, 74–

75

Clinical decision support systems (CDSS)

clinical trials of, 140–151 components of, 5, 35 data mining, 44–61

design of. See Design of CDSS systems

effectiveness of, 8–11

ethical and legal issues, 126–138 future view, 12–13

genetic algorithms, 8, 41, 59–60 hospital-based systems, 159–185 implementation issues, 11–12 input of information, 35–37 knowledge-based systems, 4–6, 34–

40

and mathematical theory, 23–34 neural networks, 6–8, 40–41, 52–

53

output of information, 39–40 compared to physician reasoning,

34–35

and Regenstrief Medical Record System (RMRS), 190–211 rule-based versus data mining, 45,

47

selection of system, criteria for, 13–18

usage, limited, 64–65

Index

263

Clinical terminology

capturing for system, 85–86 Desiderata for, 86–87 local, 88–89

vocabulary utilization problem, 86 Clinical trials of CDSS, 140–151

Columbia Registry of Medical Management Trials, 146–147 diversity, pros/cons, 148–149 importance of, 140–142

information intervention categories, 148

information interventions, effective, 149–150

of patient-education interventions, 148, 150–151

quality improvement aspects, 142–143

randomized controlled trials, 144–146 user satisfaction measures, 143–144 vote-counting, 148

Cluster analysis

and data mining, 57–58 hierarchical, example of, 58–59 limitations of, 57–58

CMIT manual, 109

Columbia Registry of Medical Management Trials, 146–147 knowledge engineering of, 147 Common sense reasoning, and system

design, 71, 77–78

Computer-based Physician Order Entry (CPOE)

knowledge repository infrastructure, 183–185

Regenstrief Medical Record System (RMRS), 195–199, 208–209 Vanderbilt University system. See

Vanderbilt WizOrder CPOE Conditional independence, 74 Conditional probability, 30–31, 37 Consumer health information systems.

See Patient-related decision support

Critical Laboratory Alerting System, 162

Critiquing systems, 166–170 Current Procedural Terminology

(CPT), codes, capturing, 85

D

Database management systems (DBMS), 68–69

Data collection, HELP System methods, 176–177

Data entry, design issues, 88–89 Data mining, 44–61

biological computing, 60–61 CDSS use of, 45–47

compared to rule-based systems, 45, 47

defined, 44

directed data mining. See Supervised learning (directed data mining) genetic algorithms, 59–60

goals of, 44

Kolmogorov-Smirnov test, 56–57 receiver operating characteristic

(ROC) graph, 54–56

statistical pattern recognition, 45 systems, examples, 46

undirected learning. See Unsupervised learning Decision-theoretic reasoning, and

system design, 76–77 Decision trees, 50–51, 68 DENDRAL system, 65

Desiderata for Controlled Medical Vocabularies, 86–87

Design of CDSS systems, 64–92 cased-based reasoning, 78 causal reasoning, 74–75

clinical content and utility issues, 84–85

common sense reasoning, 71, 77–78 data entry issues, 86, 88–89 decision-theoretic reasoning, 76–77 default/common sense knowledge, 71 human-computer interaction issues,

90–92

ignorance, dealing with, 77 knowledge engineering process, 79 logic-based knowledge

representation, 66–67

medical knowledge, application of structure to, 65–66

ontologies, 79–84

possibilistic reasoning, 77

probabilistic reasoning, 76

procedural knowledge representation, 67

reasoning and systems, 71–72 rule-based systems, 72–74 and special data types, 69–71 storage/retrieval problems, 89 structural data representation, 68–69 vocabulary utilization problem, 86 Deterministic reasoning, and diagnostic

thinking, 106–107 Diagnosis

defined, 99–100

and human reasoning, 104–107 steps in, 100–101

Diagnostic decision support systems (DDSS), 99–121

versus CDSS, 170–171

clinical domain selection, 112–113 clinical user, role of, 102–103 defined, 101

development of, 111–112 diagnostic algorithms, 114 evaluations, 115–118 future of, 120–121

interface/vocabulary issues, 118–

119

knowledge-base construction, 113–114

legal/ethical issues, 119–120, 126–138 types of systems, 107–111

user interfaces, 114–115 Diagnostic reasoning, models of,

104–107

Directed data mining. See Supervised learning (directed data mining) Diverse interventions, clinical trial

effects, 148–149 Domain expert, 79 Drug administration

adverse drug event (ADEs) decision support, 171–173

and CDSS, 6

cost savings, 197, 200–201

insurance plan-dependent formulary checking, 202–203

Regenstrief Medical Record System (RMRS), 201–203

DrugInfoNet, 253 DXplain, 110

E

Electronic medical records (EMRs), 5–6, 159

Empowerment, and patient-related decision support, 250

Ethical and legal issues, 119–120, 126–138

on appropriate use and users, 130–131

FDA regulation, 119–120, 135–137 future view, 137–138

liability, 134–135

shared decision-making, 132–133 standards of care, 128–130 Standard View, 127

Evaluations of systems, 115–118 boundary/limitation evaluation, 117 evaluation design, 115–116

formative evaluations, 115

lack of system effect issue, 117–118 successful system criteria in, 116–

117

EXPERT system shell, 109

F

Family Medical Guide (AMA), 254 Food and Drug Administration (FDA)

anti-regulation arguments, 137 and CDSS regulation, 18, 119–120,

135–137

on software as medical device, 135–137

Formative evaluations, 115

Forms, text displays/templates, 204–206 Foundation for Informed Medical

Decision Making (FIMDM), 254 Frame of reference problem, 83

G GALEN

as ontology-based system, 81–82 terminology server, 88

G-CARE, Regenstrief Medical Record System (RMRS), 197–199

Gene expression data analysis, 58–59 Genetic algorithms

and data mining, 59–60

operation and use of, 8, 41, 59–60

pros/cons of, 60

Germwatcher, 29

Greek Oracle model, 102, 110

H

Health on the Net (HON) Foundation, 256

HELP System, 160–180 alerting subsystem, 163–166 clinical data, types used, 162 components of, 161

critiquing subsystem, 166–168 data collection assistance, 176–177 diagnostic decision support

applications, 170–175 subsystem modules, 162 HELP2 System, 179–181

Computer-based Physician Order Entry (CPOE), 181–185 modules of, 179–180 HEME program, 109

Home Medical Advisor Pro

, 255 Hooper decision, 12–13

Horizon Expert Orders. See Vanderbilt WizOrder CPOE

Human-computer interaction design issues, 90–92

Hypothetical-deductive reasoning, 105

I

If-then rules, 45, 47

Ignorance, and system design, 77 Iliad, 110, 255

Inference engine, 5, 35 programming of, 37–39

Regenstrief Medical Record System (RMRS), 207–208

Informal logic systems of CDSS, 34 Intermountain Healthcare (IHC)

decision support, 159–185 for adverse drug events (ADEs),

171–173

alerting systems, 163–166, 171–173 for antibiotic administration, 174–175 assisted data collection techniques,

176–177

categories of applications, 163 clinical programs initiative, 181–

182

and Computer-based Physician Order Entry (CPOE), 181–185

critiquing systems, 166–170 HELP System, 160–180 knowledge management tools,

182–183

knowledge repository, 182–183 modules of, 179–180

for nosocomial infections, 173–174 quality of medical reports,

assessment of, 177–179 suggestion systems, 168–170

International Classification of Diseases (ICD), codes, capturing, 84–85 Internet

diagnostic decision support, 253–254

drug information, 252–253 general health references, 252–253 information seeking, scope of, 252 Intuitive reasoning, informal logic

systems of CDSS, 34

J

Jones criteria, sets, 23–26

K

Knowledge Authoring Tool (KAT), 183–184

Knowledge base

construction for DDSS, 113–114 data representation, forms of, 68–69 default/common sense knowledge,

71, 77–78 features of, 5, 39

knowledge engineering, 79 knowledge repository, 182–183 logic-based formats, 66–67 ontologies, 79–84

procedural-based formats, 67 special data types, 69–71 temporal knowledge, 70–71 Knowledge-based systems. See

Knowledge base; Rule-based systems

Knowledge Review Online (KRO), 183

Kolmogorov-Smirnov test, 56–57

L

Lack of system effect issue, 117–118

Leeds system, 64, 74, 103

Legal issues. See Ethical and legal issues

Liability issue, 134–135 Local terminology, 88–89 Locality, 72–73

Logical Observation Identifiers Names and Codes (LOINC), codes, capturing, 85

Logical operations, Boolean logic, 26–29

Logic-based knowledge formats, 66–67 Logistic regression, 51–52, 174, 196

M

Mathematical theory and CDSS, 23–34 Bayes’ Rule, 31–33

Boolean logic, 26–29 versus informal logic, 34 probability, 29–31 set theory, 23–26

Mayo Clinic, Internet, health information, 253–254

McKesson Horizon Clinical system, 6, 216

Medical Gopher, 195–199 Medical HouseCall, 255

Medical reports, quality, assessment of, 177–179

Medicare, medical necessity, Medicare standards support, 203–204 Medication orders. See Drug

administration MEDITEL system, 110 Medline, Boolean logic, 26–30 MedlinePlus, 253

ModifierConcept, GALEN system, 82 MYCIN system, 29, 34, 47, 64, 70, 110,

113–114

certainty factors, 34, 73–74

N

Nearest neighbor (NN) classifier, 53–

54

Negligence, legal issues, 134–135 Neural networks

and data mining, 52–53 features of, 6–8, 40–41, 52–53 pros/cons of, 7–8, 40–41

Nosocomial infections, hospital-based decision support, 173–174

O

Object-oriented database management systems (OODBMS), 69

Ontologies, 79–84 defined, 79 functions of, 80 upper ontology, 80–81 Ontology-based systems

frame of reference problem, 83 GALEN, 81–82

SNOMED CT, 82, 83 standards, lack of, 83–84 UMLS Semantic Network, 81 Order entry

electronic ordering process, 216–217 manual ordering process, 216–217 See also Computer-based Physician

Order Entry (CPOE)

Oxford Perinatal Database, 146, 147

P

Pathfinder system, 65, 76 Patient education, clinical trial of

effects, 150–151

Patient-related decision support, 249–258

CD-ROMs for, 254–255

diagnostic decision support, 253–255 drug information, 252–253

future view, 258

general health references, 252–253 health information system design,

251–252

patient access to, 256–257 and patient preferences, 250–251 and patient self-efficacy, 250 quality of information, patient

evaluation of, 255–256

Pattern recognition, statistical pattern recognition, 45

Pediatric HouseCall, 255

PIP (Present Illness Program), 110 Possibilistic reasoning, and system

design, 77 Postcoordination, 89 Precoordination, 89 Probabilistic reasoning

and diagnostic thinking, 105–106, 108

and system design, 76

Probability theory basic concepts, 29–31 Bayes’ Rule, 31–33

conditional probability, 30–31, 37 a priori probability, 31, 48–49 Problem Knowledge Couplers (PKCs),

90–91

Procedural-based knowledge formats, 67

Protégé, 82–83

Q

QMR, 102, 110, 119–120

Quality improvement, and evaluation of systems, 142–143

Quality Screening and Management (QSM), 44–45

R

Randomized controlled trials of CDSS, 144–146

limitations of, 145

units of randomization, 146 Reasoning

case-based, 78 causal, 74–75, 106 certainty factors, 34, 73 common sense, 71, 77–78 decision-theoretic, 76–77 deterministic, 106–107 diagnostic, 104–107 hypothetical-deductive, 105 possibilistic, 77

probabilistic, 76, 105–106, 108 Receiver operating characteristic

(ROC) graph, 54–56

Regenstrief Medical Record System (RMRS), 190–211

Computer-based Physician Order Entry (CPOE), 195–199, 208–209 drug-administration support, 201–203 inference engine, 207–208

information formats for user, 208–209

insurance plan-dependent formulary checking, 202–203

knowledge base of, 206–207 medical necessity, Medicare standards support, 203–204

positive impacts, 200–201, 210–211 reminders, development of, 190–199 studies of, 192–199

text displays/templates, 204–206 Reminders, Regenstrief Medical

Record System (RMRS), 190–199 RESUME system, 70

Retrieval of data, design issues, 89 Rule-based systems

compared to data mining, 45, 47 design of, 72–74

Rule chaining, 28–29 RxList, 253

RxMed, 253

S

Self-efficacy, and patient-related decision support, 250 Set theory

basic concepts, 23–26 set covering, 25–26

Shannon Information Content, 178 SNOMED CT, as ontology-based

system, 82, 83

Software, as medical device, FDA on, 135–137

Standards of care, ethical aspects, 128–130

Standard View, 127

Statistical pattern recognition CDSS systems using, 46 and data mining, 45

Storage of data, design issues, 89 Structured query language (SQL),

69

Suggestion systems, 168–170 Supervised learning (directed data

mining), 47–54 decision trees, 50–51 logistic regression, 51–52 nearest neighbor (NN) classifier,

53–54

neural networks, 52–53 training process, 47–48 Syllogism, 27–28

T

Templates, text displays/templates,

204–206

Temporal knowledge, design issues, 70–71

Terminologies. See Clinical terminology TOPAZ system, 70

Training, CDSS users, 16–17 Truth-maintenance system, 75

U

UMLS Semantic Network, as ontology- based system, 81

Unsupervised learning, 49, 57–59 cluster analysis, 57–58 features of, 49

gene expression data analysis, 58–59 Users

appropriate, ethical aspects, 130–131 human reasoning/system design. See

Reasoning

satisfaction, measurement of, 143–144

training, 16–17

user interfaces, 114–115

V

Vanderbilt WizOrder CPOE, 216–243 active orders, display of, 220–221 decision support approaches,

237–242

education-related links, 238 hospital ward map, 229

implementation, critical points of, 228–237

individual order construction, 234–235

individual order selection, 232–234 initiation of session, 228

modification of orders, 221 order creation, 218–220 order entry interface, 217–218 order/session completion, 235–237 patient selection from ward census,

228–229

pop-up alerts, 239–241 positive impacts, 225–228 session events, 229–232 underlying philosophy, 222–225 verification of orders, 221–222 Vote-counting, clinical efficacy, 148

W

WebMD, 252–253

WizOrder system. See Vanderbilt WizOrder CPOE

X

XML documents, 182–183