Guide to Health Informatics (Arnold Publication)

Book title......Page 4
Contents......Page 6
Note......Page 14
Preface......Page 15
Preface to the first edition......Page 17
Acknowledgements......Page 19
Publishers’ acknowledgements......Page 21
Introduction to health informatics......Page 22
PART 1 BASIC CONCEPTS IN INFORMATICS......Page 30
1 Models......Page 32
1.1 Models are abstractions of the real world......Page 33
1.2 Models can be used as templates......Page 36
1.3 The way we model the world influences the way we affect the world......Page 38
Conclusions......Page 39
Discussion points......Page 40
2.1 Information is inferred from data and knowledge......Page 41
2.2 Models are built from symbols......Page 42
2.3 Inferences are drawn when data are interpreted according to a model......Page 43
2.4 Assumptions in a model define the limits to knowledge......Page 45
2.5 Computational models permit the automation of data interpretation......Page 47
Discussion points......Page 49
3.1 A system is a set of interacting components......Page 51
3.2 A system has an internal structure that transforms inputs into outputs for a specific purpose......Page 52
3.3 Information systems contain data and models......Page 58
Discussion points......Page 60
PART 2 INFORMATICS SKILLS......Page 62
4 Communicating......Page 64
4.1 The structure of a message determines how it will be understood......Page 65
4.2 The message that is sent may not be the message that is received......Page 66
4.3 Grice’s conversational maxims provide a set of rules for conducting message exchanges......Page 70
Discussion points......Page 71
5.1 Messages are structured to achieve a specific task using available resources to suit the needs of the receiver......Page 73
5.2 The patient record can have many different structures......Page 78
Discussion points......Page 82
6 Questioning......Page 84
6.1 Clinicians have many gaps and inconsistencies in their clinical knowledge......Page 85
6.2 Well-formed questions seek answers that will have a direct impact on clinical care......Page 88
6.3 Questions to computer knowledge sources are structured according to the rules of logic......Page 89
6.4 Well-formed questions are both accurate and specific......Page 91
Discussion points......Page 94
7.1 Successful searching for knowledge requires well-structured questions to be asked of well-informed agents......Page 95
7.2 Search strategies are optimized to minimize cost and maximize benefit......Page 96
7.3 The set of all possible options forms a search space......Page 97
7.4 Search strategies are designed to find the answer in the fewest possible steps......Page 98
7.5 The answer is evaluated to see if it is well formed, specific, accurate and reliable......Page 106
Discussion points......Page 108
8.1 Problem-solving is reasoning from the facts to create alternatives, and then choosing one alternative......Page 110
8.2 Hypotheses are generated by making inferences from the given data......Page 112
8.3 Decision trees can be used to determine the most likely outcome when there are several alternatives......Page 117
8.4 Heuristic reasoning guides most clinical decisions but is prone to biases and limited by cognitive resources......Page 118
8.5 An individual’s preferences for one outcome over another can be represented mathematically as a utility......Page 122
Conclusions......Page 125
Discussion points......Page 126
PART 3 INFORMATION SYSTEMS IN HEALTHCARE......Page 128
9.1 Information systems are designed to manage activities......Page 130
9.2 There are three distinct information management loops......Page 132
9.3 Formal and informal information systems......Page 134
Discussion points......Page 138
10 The electronic medical record......Page 140
10.1 The EMR is not a simple replacement of the paper record......Page 141
10.2 The paper-based medical record......Page 142
10.3 The EMR......Page 146
Conclusions......Page 151
Discussion points......Page 152
11 Designing and evaluating information systems......Page 153
11.1 Design and evaluation are linked processes......Page 154
11.2 The formative assessment cycle defines clinical needs......Page 157
11.3 Summative evaluations attempt to determine the measurable impact of a system once it is in routine use......Page 158
11.4 Interaction design focuses on the way people interact with technology......Page 159
11.5 Designing for change......Page 163
11.6 Designing the information management cycle......Page 165
Discussion points......Page 168
PART 4 PROTOCOL-BASED SYSTEMS......Page 170
12 Protocols and evidence-based healthcare......Page 172
12.1 Protocols......Page 174
12.2 The structure of protocols......Page 177
12.3 Care pathways......Page 179
12.4 The protocol life cycle......Page 180
12.5 Departures from a protocol help drive protocol refinement......Page 181
12.6 The application of protocols......Page 182
Discussion points......Page 183
13.1 Passive protocol systems......Page 185
13.2 Active protocol systems......Page 187
13.3 Protocol representations and languages......Page 193
Discussion points......Page 198
14 Disseminating and applying protocols......Page 200
14.1 The uptake of clinical guidelines will remain low as long as the costs perceived by clinicians outweigh the benefits......Page 201
14.2 The clinical impact of a guideline is determined both by its efficacy as well as its adoption rate......Page 202
14.3 Strategies for improving the uptake of evidence into practice may alter either actual or perceived costs and benefits......Page 203
Discussion points......Page 207
15.1 Protocol construction and maintenance......Page 209
15.2 The design of protocols......Page 212
15.3 Protocol design principles......Page 214
Discussion points......Page 216
PART 5 LANGUAGE, CODING AND CLASSIFICATION......Page 218
16.1 Language establishes a common ground......Page 220
16.2 Common terms are needed to permit assessment of clinical activities......Page 221
16.3 Terms, codes, groups and hierarchies......Page 222
16.4 Compositional terminologies create complicated concepts from simple terms......Page 225
16.5 Using coding systems......Page 226
Discussion points......Page 229
17 Healthcare terminologies and classification systems......Page 230
17.1 The International Classification of Diseases......Page 231
17.2 Diagnosis related groups......Page 234
17.3 Read codes......Page 235
17.4 SNOMED......Page 237
17.5 SNOMED Clinical Terms......Page 239
17.6 The Unified Medical Language System (UMLS)......Page 242
17.7 Comparing coding systems is not easy......Page 244
Discussion points......Page 245
18 The trouble with coding......Page 246
18.1 Universal terminological systems are impossible to build......Page 247
18.2 Building and maintaining terminologies is similar to software engineering......Page 251
18.3 Compositional terminologies may be easier to maintain over time despite higher initial building costs......Page 252
18.4 The way forward......Page 255
Discussion points......Page 257
PART 6 COMMUNICATION SYSTEMS IN HEALTHCARE......Page 258
19 Communication system basics......Page 260
19.1 The communication space accounts for the bulk of information transactions in healthcare......Page 261
19.2 A communication system includes people, messages, mediating technologies and organizational structures......Page 262
19.3 Shared time or space defines the basic contexts of communication system use......Page 265
19.4 Communication services......Page 268
Discussion points......Page 271
20.1 Machine communication is governed by a set of layered protocols......Page 273
20.2 Communication channels can be dedicated or shared......Page 275
20.3 Wireline communication systems......Page 278
20.4 Wireless communication systems......Page 281
20.5 HL7 defines standards for the electronic exchange of clinical messages......Page 284
20.6 Computer and communication systems are merging......Page 287
Discussion points......Page 288
21.1 Telemedicine supports clinical care with communication technologies......Page 290
21.2 The evidence for the effectiveness of telemedicine remains weak......Page 291
21.3 Communication needs in healthcare vary widely......Page 296
21.4 Communication and home healthcare......Page 297
21.5 Communication and primary care......Page 299
21.6 Communication and hospitals......Page 302
21.7 Researching clinical communication......Page 305
Discussion points......Page 310
PART 7 THE INTERNET......Page 312
22 The Internet and World Wide Web......Page 314
22.1 The Internet has evolved through four stages......Page 315
22.2 The Internet as a technological phenomenon......Page 316
22.3 The Internet as a social phenomenon......Page 317
22.4 The Internet as a commercial phenomenon......Page 318
22.5 The Internet as an enterprise phenomenon......Page 319
22.6 Communication on the Internet......Page 320
22.7 The World Wide Web......Page 323
22.8 Security on the Internet......Page 328
22.9 Future Web advances......Page 329
Discussion points......Page 331
23 Web health services......Page 332
23.1 The Web can support rapid publication and distribution of clinical information resources......Page 333
23.2 The electronic patient record can be built using Web technologies......Page 335
23.3 The dissemination of peer-reviewed scientific knowledge is enhanced through use of the Web......Page 337
23.4 Online systems can support continuing education and decision-making......Page 338
23.5 Patients may access healthcare information on the Web......Page 340
23.6 Notification systems offer a rapid way of communicating with the clinical community......Page 343
23.7 The Internet has given rise to new types of healthcare service......Page 344
Discussion points......Page 346
24 Information economics and the Internet......Page 348
24.1 Information has a value......Page 349
24.2 Consuming information on the Web is associated with search costs......Page 353
Discussion points......Page 356
PART 8 DECISION SUPPORT SYSTEMS......Page 358
25 Clinical decision support systems......Page 360
25.1 AI can support both the creation and the use of clinical knowledge......Page 361
25.2 Reasoning with clinical knowledge......Page 362
25.3 Machine learning systems can create new clinical knowledge......Page 366
25.4 Clinical decision support systems have repeatedly demonstrated their worth when evaluated......Page 367
Discussion points......Page 372
26 Intelligent systems......Page 374
26.1 Before reasoning about the world, knowledge must be captured and represented......Page 375
26.2 Rule-based expert systems......Page 377
26.3 Belief networks......Page 378
26.4 Neural networks......Page 379
26.6 The choice of reasoning and representation methods should be based on the needs of the task......Page 381
26.7 Intelligent decision support systems have their limits......Page 382
Discussion points......Page 383
27.1 Automated interpretation and control systems can assist in situations with high cognitive loads or varying expertise......Page 384
27.2 Intelligent systems require access to additional data in the EMR before they can perform many complex functions......Page 386
27.3 There are different levels of signal interpretation, each of which requires increasing amounts of clinical knowledge......Page 387
27.5 Use of intelligent monitors can produce new types of error because of automation bias in the user......Page 393
Conclusions......Page 394
Discussion points......Page 395
28 Biosurveillance......Page 396
28.1 Event reporting = detection + recognition + communication......Page 397
28.2 Infectious disease surveillance systems play a key role in bioagent detection......Page 399
28.3 Clinical education alone is unlikely to enhance event detection and recognition......Page 401
28.4 Online evidence retrieval and CDSS can help support education and decision-making......Page 402
28.5 The Web will need to be used in combination with other communication technologies to support biosurveillance......Page 403
Conclusions......Page 406
Discussion points......Page 407
29 Bioinformatics......Page 408
29.1 Genome science is rich in sequence data but poor in functional knowledge......Page 409
29.2 Genome data can allow patient treatments to be highly tailored to the individual......Page 412
29.3 Bioinformatics can answer many questions about the role of genes in human disease, but is limited by our ability to model biological processes......Page 414
29.4 Bioinformatics is made possible by the development of new measurement and analysis technologies......Page 415
Discussion points......Page 424
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