Evidence Based Nursing (EBN)

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 raters 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
Clinicians Experience
Best Evidence
Patient Preference
14
Solving the Puzzle

Is it this? Or 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 ones 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 clinicians
  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 clinicians 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

• Patients Perspective
• Uniqueness of individual
• Context of human response
• Values and preferences
• Validation of nurses 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 Pts 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
  patients 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 patients
  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)
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
Subject Search CINAHL MEDLINE
S1 Nursing Diagnosis 2537 1661
S2 Critical Care 2574 7252
S3 Intensive Care - 6371
S4 Critically Ill Patient / Critical Illness 2054 4825
S5 S1 and S2 4 64
S6 S1 and S3 - 15
S7 S1 and S4 / Limit research 10 / 3 4 / 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-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?

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
C-ComparisonSearching the Evidence
Subject Search CINAHL MEDLINE
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)
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-ComparisonAppraising Validity of the Evidence

• Validation studies
• Design
• Clinical? Control group (with x without the NDx)?
• Content validation by experts?
• Sample
• Similar to the patients population?
• Sampling methods?

57
C-ComparisonAppraising 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-ComparisonAppraising 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 Internationals Classification

Literature data base will be the same selected
for COMPARISON
60
D-Differential DiagnosisAppraising 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
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