Download
evidence based nursing ebn diagnostic accuracy n.
Skip this Video
Loading SlideShow in 5 Seconds..
Evidence Based Nursing (EBN) & Diagnostic Accuracy PowerPoint Presentation
Download Presentation
Evidence Based Nursing (EBN) & Diagnostic Accuracy

Evidence Based Nursing (EBN) & Diagnostic Accuracy

154 Views Download Presentation
Download Presentation

Evidence Based Nursing (EBN) & Diagnostic Accuracy

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

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

  14. Solving the Puzzle

  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. COMPARE D-Differential NDxs Definition Defining Characteristics Related Factors P-Population: Pre-Op Pt’s C-Cues: Presenting Objective & Subjective Data DERIVE Evidence-based NDx: Pre-Op Anxiety 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 Accuracy Inaccuracy Principles of Evidence Based Practice

  34. Evidence-Based Nursing • 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* • “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. Asking answerable questions • Searching evidence • Appraising evidence Case Study • PCD format* • P = Patient population • C = Comparison • D = Differential diagnosis *Developed by Levin, Miller & Lunney (2004)

  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-PopulationSearching the Evidence

  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-PopulationAppraising 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-PopulationAppraising 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?