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

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11 Clinical Practice Guidelines: Supporting Decisions, Optimizing Care 157 Center at Yale New Haven Hospital functions as a resident continuity clinic and uses the Centricity (GE Medical Systems, Fairfield, CT) ambulatory electronic health record system. Following a careful parsing of the guidelines, supplemented with input from Pediatric Respiratory Medicine experts, a set of data collection templates and forms that provide guideline-based advice were designed and refined. An example of system operation is: A pediatric patient (Willy Wheeze) with identified chronic asthma comes for an appointment for health maintenance. His mother notes that he recently experienced his first asthma exacerbation that required a trip to the Emergency Room. The primary care pediatrician (Dr. Jones) clicks a button that adds the asthma management forms to the electronic health record health maintenance templates that are presented for the visit. The asthma forms prompt Dr. Jones to ask about the frequency of wheezing, cough, chest tightness, etc. As Dr. Jones records Willy’s mother’ responses, a rule-based template calculates, per the NHLBI guidelines, the severity level of Willy’s asthma. The frequency of Willy’s symptoms indicates his asthma severity is mild persistent. Dr. Jones next inquires about Willy’s level of asthma control, based on answers to questions about missed school and emergency department visits. Results of pulmonary function testing (PFTs) are also recorded. The decision support system, using data from the history and PFTs, indicates that Willy’s control is suboptimal. A third panel of questions prompts questions about asthma triggers and activities the family has put into place to diminish Willy’s exposure. The system summarizes findings and returns that Willy’s asthma is mild persistent and suboptimally controlled. Dr. Jones considers the assessments, considers overriding the suggestions and notes her reasoning in modifying or accepting the assessments. The system recommends a series of appropriate interventions based on the guideline, including rescue and controller medications. The system also notes that inhaler propellants will be changing in the near future and will require modification and refresher training for patients. Dr. Jones selects appropriate medications from a list and gets additional information on options offered by an onscreen “Info-button.” Dr. Jones clicks on her selections, which are automatically added to Willy’s EHR medication list as prescriptions are prepared for electronic transfer to the pharmacy. An individualized asthma action plan according to NHLBI guidelines is automatically prepared and printed to which Dr. Jones can add additional information. References 1. Bosson JL, Labarere J. Determining indications for care common to competing guidelines by using classification tree analysis: application to the prevention of venous thromboembolism in medical inpatients. Med Decis Mak. 2006;26(1):63–75. 2. Burgers JS, Grol R, Klazinga NS, Makela M, Zaat J. Towards evidence-based clinical practice: an international survey of 18 clinical guideline programs. Int J Qual Health Care. 2003;15(1):31–45.
158 R.N. Shiffman 3. Institute of Medicine. Clinical Practice Guidelines: Directions for a New Program. Field MJ, Lohr KN, eds. Washington, DC: National Academy Press. 4. Peleg M, Boxwala AA, Tu S, et al. The InterMed approach to sharable computer-interpretable guidelines: a review. J Am Med Inform Assoc. 2004;11(1):1–10. 5. Shaneyfelt TM M-SM, Rothwangl J. Are guidelines following guidelines? The methodological quality of clinical practice guidelines in the peer-reviewed medical literature. JAMA. 1999;281:1900–1905. 6. Shiffman RN, Shekelle P, Overhage JM, Slutsky J, Grimshaw J, Deshpande AM. Standardized reporting of clinical practice guidelines: a proposal from the Conference on Guideline Standardization. Ann Intern Med. 2003;139(6):493–498. 7. AGREE Collaboration. Development and validation of an international appraisal instrument for assessing the quality of clinical practice guidelines: the AGREE project. Qual Saf Health Care. 2003;12(1):18–23. 8. Shiffman RN, Dixon J, Brandt C, et al. The GuideLine Implementability Appraisal (GLIA): development of an instrument to identify obstacles to guideline implementation. BMC Med Inform Decis Mak. 2005;27(5):23. 9. Cabana MD, Rand CS, Powe NR, et al. Why don’t physicians follow clinical practice guidelines? A framework for improvement. JAMA. 1999;282(15):1458–1465. 10. Grilli R, Magrini N, Penna A, Mura G, Liberati A. Practice guidelines developed by specialty societies: the need for a critical appraisal. Lancet. 2000;355:103–106. 11. Matthews JC, Johnson ML, Koelling TM. The impact of patient-specific quality-of-care report cards on guideline adherence in heart failure. Am Heart J. 2007;154(6):1174–1183. 12. Jimbo M, Nease DE Jr, Ruffin MT 4th, Rana GK. Information technology and cancer prevention. CA Cancer J Clin. 2006;56(1):26–36. 13. Johnson KB, Feldman MJ. Medical informatics and pediatrics. Decision-support systems. Arch Pediatr Adolesc Med. 1995;149(12):1371–1380. 14. O’Brien MA, Rogers S, Jamtvedt G, et al. Educational outreach visits: effects on professional practice and health care outcomes. Cochrane Database Syst Rev. 2007;17;(4):CD000409. 15. Tierney WM, Overhage JM, Takesue BY, et al. Computerizing guidelines to improve care and patient outcomes: the example of heart failure. J Am Med Inform Assoc. 1995;2:316–322. 16. Institute of Medicine.. Setting Priorities for Clinical Practice Guidelines. Field MJ, ed. Washington, DC: National Academy Press; 1995. 17. de Clercq PA, Blom JA, Korsten HH, Hasman A. Approaches for creating computerinterpretable guidelines that facilitate decision support. Artif Intell Med. 2004;31(1):1–27. 18. Svátek V, Ruzicka M. Step-by-step mark-up of medical guideline documents. Int J Med Inform. 2003;70(2–3):329–335. 19. Peleg M, Tu S, Bury J, et al. Comparing computer-interpretable guideline models: a casestudy approach. J Am Med Inform Assoc. 2003;10(1):52–68. 20. 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. 21. OpenClinical. OpenClinical: Knowledge Management for Health Care Website; 2008. Available at: http://www.openclinical.org. Accessed June 5, 2008. 22. Kim S, Haug PJ, Rocha RA, Choi I. Modeling the arden syntax for medical decisions in XML. Int J Med Inform. 2008;77(10):650–656. 23. Musen MA, Tu SW, Das AK, Shahar Y. EON: a component-based approach to automation of protocol-directed therapy. J Am Med Inform Assoc. 1996;3(6):367–388. 24. Terenziani P, Montani S, Bottrighi A, Torchio M, Molino G, Correndo G. The GLARE approach to clinical guidelines: main features. Stud Health Technol Inform. 2004;101:162–166. 25. De Clercq PA, Blom JA, Hasman A, Korsten HH. GASTON: an architecture for the acquisition and execution of clinical guideline-application tasks. Med Inform Internet Med. 2000;25(4):247–263. 26. Patel VL, Allen VG, Arocha JF, Shortliffe EH. Representing clinical guidelines in GLIF: individual and collaborative expertise. J Am Med Inform Assoc. 1998;5(5):467–483.
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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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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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408 J.H. Schneider of this componen
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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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436 G.R. Kim and S.T. Rosenbloom ab
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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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470 G.R. Kim and K.B. Johnson Cente
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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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