1. Evidence Based Nursing (EBN) & Diagnostic Accuracy Rona F. Levin, PhD, RN (New York, USA) Margaret Lunney, PhD, RN (New York, USA) Barbara Krainovich Miller, EdD, RN (New York, USA) Diná Monteiro da Cruz, PhD, RN (Sao Paulo, Brazil) Cibele de Mattos Pimenta, PhD, RN (Sao Paulo, Brazil)

2. Objectives Explain accuracy of diagnosis as the foundation of EBN-M. Lunney Describe an evidenced-based model (PCD) for use by nurses-R. Levin Apply the PCD format to diagnose anxiety- B. K. Miller Apply the PCD format to teach EBN- D. M. da Cruz & C.M. Pimenta

3. Foundation of Evidence-Based PX: Accurate Interpretation of Data Interpretations determine actions Additional data to be collected Subsequent interpretations Possible outcomes to consider Choices of interventions

4. Foundation of Evidence-Based PX: Accurate Interpretation of Data High potential for inaccuracies Human beings are complex and diverse We do not “know” other people (Munhall, 1993) Knowledge of nursing concepts varies Critical thinking abilities vary

5. Foundation of Evidence-Based PX: Accurate Interpretation of Data What is diagnostic accuracy? Accuracy is a rater’s judgment of the degree to which a diagnostic statement matches the cues in a patient situation (Lunney, 1990).

6. Challenge of Achieving Accuracy: Puzzle: What is the Diagnosis?

7. Research Findings Studies: 1966 to present Conclusions: Interpretations vary widely Influencing factors: Diagnostic Tasks Situational contexts Nurse Diagnosticians

8. Diagnostic Tasks Factors studied: Task complexity Amount of data Relevance of data

9. Situational Contexts Factors studied: Time constraints Role in healthcare system Factors still to be studied: Policies Procedures Philosophy and theories

10. Nurse Diagnosticians Factors studied: Education Use of teaching aids Nursing experience Cognitive strategies Cognitive abilities Personality

11. Summary of Research Findings: Positive Influences on Accuracy Education related to nursing diagnoses Knowledge of diagnostic process and concepts Teaching aids for diagnostic reasoning Variety of thinking processes Experience specific to diagnostic task Lesser amounts and complexity of data

12. Conclusions from Knowledge Development Problem: Diagnostic Accuracy varies from high to low. Solution: Use an evidence-based practice approach to facilitate the formulation of accurate diagnoses.

13. Evidence-Based Practice Best Evidence Clinician’s Experience Patient Preference

14. Solving the Puzzle Is it this?Or This?

15. Evidence-Based Practice to Solve the Puzzle Evidence from Literature Which diagnosis are indicated by the cues? What differentiates similar diagnoses? Which of the possible diagnoses is the best match? Clinician perspective Patient perspective

16. EBM Model Asking answerable questions Finding the best evidence Appraising validity of evidence Integrating evidence with clinician expertise and patient preferences Evaluating one’s effectiveness in above steps Sackett, Straus, Richardson, Rosenberg, & Haynes (2000)

17. Asking Answerable Diagnostic Questions in Nursing PCD format P = Patient population C = Comparison cue or cue cluster D = Differential diagnosis developed by Levin, Miller & Lunney (2004)

18. Asking Answerable Diagnostic Questions in Nursing Example of PCD question: In adult critical care patients (population) who exhibit angry outbursts, complaints about treatments that interfere with sleep/rest, and irritable behavior (cue cluster) what are the possible nursing diagnoses to consider (differential diagnosis)?

19. Asking Answerable Diagnostic Questions in Nursing Possible diagnoses to consider sleep pattern disturbance ineffective coping hopelessness powerlessness fear and/or anxiety cognitive impairment other?

20. Asking Answerable Diagnostic Questions in Nursing Based on evidence, what is the strength of the cues in relation to the possible diagnoses? Based on evidence, which of the possible diagnoses represents the best match with the cues? Does the patient validate the clinician’s interpretation?

21. Finding the Evidence Knowledge of possible diagnoses Research evidence associated with specific diagnoses Knowledge of useful data bases Access to data bases and sources

22. Appraising the Evidence Assess validity of the research-based evidence Type of study survey of nurses? Observation of patients? Sample size and selection Applicability to your practice

23. Integrating Evidence With clinician’s expertise knowledge of diagnoses and diagnostic task specialty focus frequency of caring for patients’ with specific responses (cue clusters) knowledge of related interventions

24. Integrating Evidence Patient’s Perspective Uniqueness of individual Context of human response Values and preferences Validation of nurse’s interpretation

25. Evaluating Effectiveness Am I looking for the research evidence about human responses? Am I considering the highly relevant diagnoses associated with observed cue clusters? Am I considering the individual patient and the specific context when applying research-based evidence?

26. Evidence-Based Nursing Diagnosis: Anxiety NANDA Nursing Diagnoses: Definitions & Classification 2003-2004 Refined based on research submitted to DRC 1973, 1982, 1998

27. Refinement: Nursing Research Validation Studies Whitley (1994, 1992, 1989) Levin, Krainovich-Miller et al. (1989)\ Krainovich (1988) Fadden, Fehring & Kendel-Rossi (1987) Lopez & Risey (1986) Jones & Jakob (1984) Jones & Jakob (1981) Haag & Adamski (1978) Graham & Conley (1971)

28. NDx Normal Anxiety Nursing Research Clinical & Content Validation Studies Interdisciplinary Case Studies & Research Findings

29. Differential Diagnoses Anxiety Fear Ineffective Coping Disturbed Thought Processes

30. Diagnostic Reasoning Process Definition Defining Characteristics Related Factors

31. P-Population: Pre-Op Pt’s C-Cues: Presenting Objective & Subjective Data D-Differential NDxs Definition Defining Characteristics Related Factors Evidence-based NDx: Pre-Op Anxiety COMPARE DERIVE PCD

32. Patient Perspective Critical to Diagnostic Accuracy Compare to Clinician Perspective Results: NDx statement that best fits the patient’s cues in context

33. Interpreting Human Responses is a Complex Task Principles of Evidence Based Practice Inaccuracy Accuracy

34. Evidence-Based Nursing. Patient Preference Best Evidence Clinician’s experience Asking Answerable Questions Finding the Best Evidence Appraising Validity of Evidence Integrating Evidence (clinician/patient) Evaluating Effectiveness Sackett et al (2000) Applied to diagnosis, interventions (treatments), and outcomes

35. Case Study “Cases are stories with a message. They are not simply narratives for entertainment. They are stories to educate.” “... the role of students and instructor vary as will the case material itself.” (Herreid CF, 2004)

36. Case Study “Case methods or studies provide a process of participatory learning that facilitates active and reflective learning and results in the development of critical thinking and effective problem-solving skills. This develops self-directed lifelong learners.” (Tomey AM,2003)

37. Case Study A Patient in Respiratory Critical Care* A Patient in Respiratory Critical Care* “ Mrs. H, 70 years old, was admitted to a respiratory medical unit because she presented with increasing shortness of breath over....” (Handout p.1) * Perry, K. A patient in respiratory critical care. In: Lunney M. (2002). Critical thinking & nursing diagnosis (pp. 74-75, 140-142). Philadelphia: NANDA International.

38. Case Study Objective: Participants will apply the PCD format to interpret patient data Directions: Use groups of 5 to 7 Assign leader & recorder - Leader: Help group to stay focused; conduct discussions in a nurturing environment - Recorder: Document relevant aspects of the discussion and report group conclusions

39. Case Study Directions Read the text carefully (Handout p.1) Imagine you are the nurse of the patient Task- state NDxs that best explain the patient’s situation Apply the PCD format* to ask answerable questions to make accurate NDXs * developed by Levin, Miller & Lunney (2004)

40. Case Study PCD format * P = Patient population C = Comparison D = Differential diagnosis * Developed by Levin, Miller & Lunney (2004) Asking answerable questions Searching evidence Appraising evidence

41. P-Population Asking Answerable Questions What are the most common nursing diagnoses (NDxs) in the population that this patient represents (critical care patients)? Searching the Evidence CINAHL Medline

42. P-Population Searching the Evidence Subject SearchCINAHLMEDLINE S1: Nursing Diagnosis 25371661 S2: Critical Care 25747252 S3: Intensive Care -6371 S4: Critically Ill Patient / Critical Illness 20544825 S5: S1 and S2 464 S6: S1 and S3 -15 S7: S1 and S4 / Limit: research 10 / 34 / NA

43. P-Population Searching the Evidence CINAHL Wang LT, Lee C. (2002) Asencio JMM. (1997) [Spanish] Roberts BL et al. (1996) Logan J; Jenny J. (1991)

44. P-Population Searching the Evidence MEDLINE Gordon M, Hiltunen E. (1995) Wieseke A et al. (1994) Pasini DA et al. (1996) [Portuguese] Alorda C et al. (1996) [Spanish]

45. P-Population Appraising the Validity of Evidence Question: What are the most common nursing diagnoses (NDxs) in the population that this patient represents (critical care patients)?

46. P-Population Appraising the Validity of Evidence Prevalence studies (cross-sectional) Population & Sample Is the population similar to the population of the case study patient? How was the sample drawn?

47. P-Population Appraising the Validity of Evidence Prevalence studies (cross-sectional) Data collection Cover different domains? Who were the diagnosticians? How was accuracy of NDxs assured? Results Valid and reliable? Applicable to this case study?

48. C-Comparison Asking Answerable Questions Which data are cues to possible NDxs (human responses)? Which data are highly relevant to explain the human responses?

49. C-Comparison Asking Answerable Questions Which data are cues to possible NDxs (human responses)? -  participation in care -  use of the call bell -  interest in providers’ actions -  sleep -  communication with daughter (who used to read Bible to her) - What else?

50. C-Comparison Asking Answerable Questions Which NDx (human response) best explains the current situation? Relevant data –  participation in care –  use of the call bell –  interest in providers’ actions –  sleep –  communication with daughter (who used to read Bible to her) Possible Explanations Fear? Powerlessness? Hopelessness? Spiritual Distress? What else?

51. C-Comparison Asking Answerable Questions Based on evidence, what is the strength of the cues in relation to possible diagnoses? Searching Evidence CINAHL Medline NANDA International

52. Subject SearchCINAHLMEDLINE S1: Fear (* and Validation Studies) 1202 (*15)4736 (*0) S2: Hopelessness (* and Validation Studies) 175 (*0)(*0) S3: Hope (*and Validation Studies) 870(*12)(*0) S4: Powerlessness (* and Validation Studies) 251 (*3)(*0) S5: Spiritual distress NANDA (*and Validation Studies) 25 (*7)(*0) S6: Validation Studies 4340(*0) C-Comparison Searching the Evidence

53. C-Comparison Searching the Evidence CINAHL  Fear Whitley GG. (1997)  Powerlessness Bufe GM & Abdul-Hamid M. (1995)  Hopelessness Beyea SC & Peters DD. (1987)  Spiritual Distress Twibell RS et al. (1996) Hensley LD. (1994)

54. C-Comparison Searching the Evidence Nursing Diagnosis Classification (NANDA International, Handout, p.2)  Fear  Powerlessness  Hopelessness  Spiritual Distress

55. C-Comparison Appraising Validity of the Evidence Question: Based on evidence, what is the strength of the cues in relation to possible NDxs?

56. C-Comparison Appraising Validity of the Evidence Validation studies Design -Clinical? Control group (with x without the NDx)? -Content validation by experts? Sample -Similar to the patient’s population? -Sampling methods?

57. C-Comparison Appraising Validity of the Evidence Validation studies Data collection Instruments Wide search for defining characteristics? Based on operational definitions of the defining characteristics? Validity and reliability? Results Valid and reliable? Applicable to the patient?

58. C-Comparison Appraising Validity of the Evidence Concept analysis/development studies Purpose -Identification? -Development? -Clarification? Method -Consistent ? Results -Valid and reliable ? -Applicable to the patient?

59. D-Differential Diagnosis Asking Answerable Questions Which of the possible NDxs represent the best match with the cues? Searching Evidence CINAHL Medline NANDA International’s Classification Literature data base will be the same selected for COMPARISON

60. D-Differential Diagnosis Appraising Validity of the Evidence Validation studies Design -Compare nursing diagnoses? -Clinical? Control group (with x without the ND)? -Content validation by experts? Sample, Data collection, and Results -Apply the same criteria of Comparison

61. Summary What are the most commom NDxs in this situation? Based on evidence, what is the strength of the cues in relation to the possible diagnoses? Which of the possible NDxs represent the best match with the cues? Answerable Question Searching Evidence Appraising Evidence Epidemiological studies Criteria of validity applied to epidemiological studies Validation studies comparing nursing diagnosis Validation studies Concept analysis / development studies Criteria of validity applied to nursing diagnosis validation studies Criteria of validity applied to nursing diagnosis validation studies

62. Challenges Clinical research-based literature Epidemiological studies Validation studies Criteria to appraise evidence Data base frameworks Measurement tools for specific NDxs Skills for searching evidence Accessibility of data bases

63. Conclusion The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn and relearn. Alvin Toffler