Pediatric Informatics: Computer Applications in Child Health (Health ...

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11 Clinical Practice Guidelines: Supporting Decisions, Optimizing Care 159 27. Ciccarese P, Caffi E, Boiocchi L, Quaglini S, Stefanelli M. A guideline management system. Medinfo. 2004;2004:28–32. 28. Hagerty CG, Chang J, Pickens DS, Kulikowski CA, Sonnenberg FA. Semi-automated encoding of guidelines. Medinfo. 2004:1625. 29. Sutton DR, Taylor P, Earle K. Evaluation of PROforma as a language for implementing medical guidelines in a practical context. BMC Med Inform Decis Mak. 2006;6:20. 30. Zynx Health; 2008. Available at: http://www.zynx.com. Accessed June 8, 2008. 31. Shiffman RN, Michel G, Essaihi A, Thornquist E. Bridging the guideline implementation gap: a systematic, document-centered approach to guideline implementation. J Am Med Inform Assoc. 2004;11(5):418–426. 32. Yale University. Guideline Elements Model Website; 2008. Available at: http://gem.med.yale. edu/default.htm. Accessed June 5, 2008. 33. American Academy of Pediatrics. AAP Red Book Online; 2008. Available at: http:// aapredbook.aappublications.org/. Accessed June 5, 2008. 34. American Academy of Pediatrics. AAP Policy Website; 2008. Available at: http:// aappolicy.aappublications.org/. Accessed June 5, 2008. 35. American Academy of Pediatrics. Steering Committee on Quality Improvement and Management Steering Committee on Quality Improvement and Management Website; 2008. Available at: http://www.aap.org/visit/scoqim.htm. Accessed June 5, 2008.
Chapter 12 Diagnostic Decision Support Mitchell J. Feldman Objectives To describe the history and previous work in the field of medical diagnostic decision support, including Bayes’ Law, on which much of this work is based To illustrate three currently available systems, DXplain, GIDEON, and Isabel To consider how diagnostic decision support could be useful in practice 12.1 Introduction In 1763, the Reverend Thomas Bayes published “a method by which we might judge concerning the probability that an event has to happen, in given circumstances, upon supposition that we know nothing concerning it but that, under the same circumstances, it has happened a certain number of times, and failed a certain other number of times.” 1 This is Bayes’ Law, which in 1959, was applied to medical diagnosis 2 to form the basis of diagnostic decision support. 3, 4 Because almost all computer-based medical diagnostic decision support systems (MDDSS) use some application of Bayes’ Law, it is instructive to review basic principles. 12.2 Testing: Sensitivity and Specificity Medical decision making is predicated on an explicit or implicit use of sensitivity, specificity, and prevalence: The sensitivity of a test is the probability that a test for a disease will be positive in a patient with the disease. A highly sensitive test will be positive in most cases in patients with the disease. In a test of low sensitivity, many patients with the disease will test negative. The specificity of a test is the probability that the test will be negative in a patient without the disease. A highly specific test will be negative in most cases C.U. Lehmann et al. (eds.), Pediatric Informatics: Computer Applications 161 in Child Health, Health Informatics, © Springer Science + Business Media, LLC 2009
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Health Informatics (formerly Comput
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Editors Christoph U. Lehmann George
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vi Series Preface changes to both t
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viii Foreword This text will prove
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x Preface financial investment and
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How to Use This book This book is t
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xvi Contents 9 Pediatric Care, Safe
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xviii Contents Part VII A Vision an
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xx Contributors Donna M. D’Alessa
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xxii Contributors Christoph U. Lehm
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xxiv Contributors Mark M. Simonian,
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4 G.R. Kim pharmacy, medical educat
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6 K.B. Johnson and G.R. Kim Deaths
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8 K.B. Johnson and G.R. Kim 2.4.1 I
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10 K.B. Johnson and G.R. Kim 2.4.3
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12 K.B. Johnson and G.R. Kim Educat
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14 K.B. Johnson and G.R. Kim 2.6 Co
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Chapter 3 Core Pediatric Data Kevin
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3 Core Pediatric Data 21 3.3 Pediat
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3 Core Pediatric Data 23 3.6 Pediat
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Chapter 4 Neonatal Care and Data De
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4 Neonatal Care and Data 27 Essenti
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4 Neonatal Care and Data 29 4.3 The
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4 Neonatal Care and Data 31 some ma
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4 Neonatal Care and Data 33 Measure
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4 Neonatal Care and Data 35 4.5.2.4
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4 Neonatal Care and Data 37 4.6.3 I
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4 Neonatal Care and Data 39 4.7.2.2
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4 Neonatal Care and Data 41 Availab
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44 D.M.N. Paperny Tasks related to
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46 D.M.N. Paperny Behavioral risk d
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48 D.M.N. Paperny for outside ancil
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50 D.M.N. Paperny Video reinforceme
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52 D.M.N. Paperny 3. Litzelman DK,
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Chapter 6 Children with Development
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6 Children with Developmental Disor
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Chapter 7 Pediatric Emergency and P
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7 Pediatric Emergency and Pediatric
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84 W.H. Drummond et al. A recovery
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86 W.H. Drummond et al. 8.2.2 Forma
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88 W.H. Drummond et al. 8.2.2.1 Sys
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92 W.H. Drummond et al. noise overl
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94 W.H. Drummond et al. needs requi
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96 W.H. Drummond et al. Children’
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98 W.H. Drummond et al. After the P
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100 W.H. Drummond et al. Table 8.2
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102 W.H. Drummond et al. Table 8.3
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104 W.H. Drummond et al. when to su
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15 Pediatric Care Coordination: The
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Chapter 16 Prioritizing Pediatric I
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16 Prioritizing Pediatric Investmen
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Chapter 17 Aligning Pediatric Ambul
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17 Aligning Pediatric Ambulatory Ne
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258 G.R. Kim and C.U. Lehmann Elect
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260 G.R. Kim and C.U. Lehmann 18.2.
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262 G.R. Kim and C.U. Lehmann There
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264 G.R. Kim and C.U. Lehmann 13. C
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266 K.B. Johnson and C.G.M. Weigle
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280 C. Sable et al. computer for la
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282 C. Sable et al. Table 20.3 Tele
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284 C. Sable et al. without increas
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286 C. Sable et al. Fig. 20.1b Wash
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288 C. Sable et al. prior to case d
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290 C. Sable et al. presence of con
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292 C. Sable et al. 17. Sable C, Ro
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294 A.E. Zuckerman and G.R. Kim 21.
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296 A.E. Zuckerman and G.R. Kim �
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Chapter 22 Privacy Issues David M.N
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22 Privacy Issues 305 22.3 Pediatri
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22 Privacy Issues 307 patient must
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22 Privacy Issues 309 and receipt o
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Chapter 23 Electronic Mail in Pedia
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23 Electronic Mail in Pediatric Pra
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Chapter 24 Information Management b
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24 Information Management by Patien
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Chapter 25 Overview of Pediatric In
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25 Overview of Pediatric Inpatient
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Chapter 26 Prescribing/Ordering: Co
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26 Prescribing/Ordering: Computeriz
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346 S.H. Mitchell et al. 27.2.1 Med
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348 S.H. Mitchell et al. context of
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350 S.H. Mitchell et al. 27.3.3.1 C
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352 S.H. Mitchell et al. challenges
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354 S.H. Mitchell et al. work round
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Chapter 28 Medication Administratio
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28 Medication Administration and In
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Chapter 29 Understanding and Preven
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29 Understanding and Preventing Err
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386 D.C. Stockwell and A.D. Slonim
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400 J.H. Schneider a number of prob
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402 J.H. Schneider on governance, u
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404 J.H. Schneider 31.6.1 Data Rele
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406 J.H. Schneider Understanding op
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410 J.H. Schneider Table 31.1 (cont
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412 J.H. Schneider References 1. Am
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Chapter 32 Developing Pediatric Dat
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32 Developing Pediatric Data Standa
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430 G.R. Kim and S.T. Rosenbloom Co
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432 G.R. Kim and S.T. Rosenbloom No
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434 G.R. Kim and S.T. Rosenbloom pr
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Chapter 34 Pediatric Research and I
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34 Pediatric Research and Informati
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Chapter 35 The Moving Picture of Pe
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35 The Moving Picture of Pediatric
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472 G.R. Kim and K.B. Johnson 36.4
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Index A 2006 AAP recommendations on
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Index 477 psychological data, 45 se
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Index 479 High frequency flow inter
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Index 481 O Online Mendelian Inheri
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Index 483 Standards development org
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