Muutke küpsiste eelistusi

E-raamat: Intervention Effectiveness Research: Quality Improvement and Program Evaluation

  • Formaat: EPUB+DRM
  • Ilmumisaeg: 14-Sep-2017
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319612461
Teised raamatud teemal:
  • Formaat - EPUB+DRM
  • Hind: 44,45 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
Intervention Effectiveness Research: Quality Improvement and Program EvaluationSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 14-Sep-2017
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319612461
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

Do interventions improve health outcomes? This volume provides a model and road map to answer clinical questions related to intervention effectiveness research, quality improvement, and program evaluations. It offers clear and simple guidance for all phases of a clinical inquiry projects from planning through dissemination and communication of results and findings. The book emphasizes the value and importance of leveraging existing data to advance research, practice, and quality improvement efforts.

Intervention and Effectiveness Research is a practical guide for organizing and navigating the intersections of research and practice. Structure, process and outcome worksheets for every step are provided together with examples from diverse settings and populations to lead readers through the process of implementing their own projects. The author guides readers through the process of designing, implementing, and evaluating project

s. This book is intended for teachers of DNP and PhD programs in nursing and other disciplines, their students, and healthcare leaders who need to leverage data to demonstrate care quality and outcomes.

Arvustused

This is a unique book, which can be used by students and novices. It can be useful for DNP students as they develop their end-of-program projects and for nurses as they begin to work on quality improvement and program evaluation projects. There is no comparable book in the field. This would be a great addition to the library of teachers and managers to share with their students and nurses. (Michalene A. King, Doody's Book Reviews, November, 2017)

Part I Introduction to Intervention Effectiveness Research, Quality Improvement, and Program Evaluation
1 Key Concepts, Definitions, and Frameworks
3(14)
1.1 Introduction
3(1)
1.2 Definitions and Descriptions of Intervention Effectiveness Research, Quality Improvement, and Program Evaluation: What They Have in Common and How They Differ
4(1)
1.2.1 What Is Quality Improvement?
4(1)
1.2.2 What Is Program Evaluation?
5(1)
1.3 How Intervention Effectiveness Research, Quality Improvement Activities, and Program Evaluation Are Similar
5(1)
1.4 How Intervention Effectiveness Research, Quality Improvement, and Outcome Evaluation Are Different
6(3)
1.4.1 Translational Research
6(1)
1.4.2 Quality Improvement (QI)
6(1)
1.4.3 Six Sigma Quality Improvement
7(1)
1.4.4 Health Services Research
7(1)
1.4.5 Big Data in Health Care Research
8(1)
1.4.6 Program Evaluation
8(1)
1.4.7 Implementation Research
9(1)
1.5 Definitions of Similar Sounding Terms and What This Book Does Not Attempt
9(1)
1.5.1 Comparative Effectiveness Research
9(1)
1.5.2 Implementation Science Research
9(1)
1.5.3 Dissemination Science
10(1)
1.6 Frameworks to Support Intervention Effectiveness Research, Quality Improvement Activities, and Program Evaluation
10(7)
1.6.1 Theory
10(2)
1.6.2 Logic Models
12(1)
1.6.3 Theoretical Framework
12(1)
1.6.4 Conceptual Framework
12(1)
References
13(4)
2 Problem-Intervention-Outcome Meta-Model (PIO MM): A Conceptual Meta Model for Intervention Effectiveness Research, Quality Improvement Activities, and Program Evaluation
17(12)
2.1 Introduction to the Problem-Intervention-Outcome Meta-Model (PIO MM)
17(2)
2.2 PIO MM and the CDC Logic Model
19(1)
2.3 PIO MM and the IHI Quality Improvement Model
20(2)
2.4 Using the PIO MM
22(3)
2.5 Operationalizing the PIO MM
25(1)
2.6 PIO MM Relationship to Change Theory
26(1)
2.7 PIO MM Relationship to PICOT
26(3)
References
27(2)
3 Problem-Intervention-Outcome Meta-Model Project Design
29(12)
3.1 Design for Intervention Effectiveness Research, Quality Improvement Activities, and Program Evaluation
29(3)
3.1.1 Observational Design
29(1)
3.1.2 Retrospective Design
30(1)
3.1.3 Prospective Design
31(1)
3.2 Intervention and Measurement Timing
32(1)
3.3 PIO MM and Research Design
32(1)
3.4 Benefits and Challenges of the Single Group Before and After Design
32(2)
3.4.1 Threats to Internal Validity
33(1)
3.4.2 Enhancing Before and After Design Using Comparisons
33(1)
3.4.3 Considerations for Prospective Data Collection
34(1)
3.5 Comparisons Using PIO MM Variables
34(3)
3.5.1 Problem
34(1)
3.5.2 Intervention
34(1)
3.5.3 Interventionist
35(1)
3.5.4 Outcome
36(1)
3.5.5 Population (Individual Characteristics)
36(1)
3.5.6 Setting
36(1)
3.5.7 Time
37(1)
3.6 Mixed Methods: Qualitative Evaluation
37(4)
References
38(3)
4 Tools for Intervention Effectiveness Research, Quality Improvement Activities, and Program Evaluation
41(12)
4.1 Data Sources
41(1)
4.2 Checklists for Obtaining New or Existing Data for Operationalizing the PIO MM
42(2)
4.3 Electronic Health Record Data
44(1)
4.4 Nursing-Specific Data
44(1)
4.5 Omaha System
45(3)
4.5.1 Problem Classification Scheme
46(1)
4.5.2 Intervention Scheme
46(1)
4.5.3 Problem Rating Scale for Outcomes
46(2)
4.6 Analysis Software and Techniques
48(1)
4.7 Power Analysis
48(1)
4.8 Software for Descriptive and Inferential Statistical Methods and for Creating Graphs/Charts
48(1)
4.8.1 Microsoft Excel
48(1)
4.8.2 R
49(1)
4.8.3 SAS
49(1)
4.9 Big Data (Pattern Detection) Methods
49(2)
4.9.1 Clustering
50(1)
4.9.2 Visualization
50(1)
4.10 Team Approach
51(2)
References
51(2)
5 Descriptive Analysis and Interpretation
53(10)
5.1 Introduction
53(1)
5.2 Data Cleaning
53(2)
5.2.1 Screening Phase
54(1)
5.2.2 Diagnostic Phase
54(1)
5.2.3 Treatment Phase
55(1)
5.2.4 Missing Data
55(1)
5.3 Pre-Processing
55(2)
5.3.1 Transforming and Recoding
55(1)
5.3.2 Identification and Labeling of Clusters Within a Sample
56(1)
5.4 Descriptive Statistics
57(6)
5.4.1 Frequency
58(1)
5.4.2 Cross Tabulation (Cross Tab) Matrix
59(1)
5.4.3 Rank
59(1)
5.4.4 Measures of Central Tendency
59(2)
5.4.5 Measures of Distribution
61(1)
References
62(1)
6 Inferential Analysis and Interpretation
63(14)
6.1 About Inferential Statistics
63(3)
6.2 Comparisons and Statistical Significance
66(3)
6.2.1 Comparisons of Sample Characteristics
66(1)
6.2.2 Outcomes as Measured by Before and After Comparison
66(2)
6.2.3 Benchmarking
68(1)
6.2.4 The P-Value in Large Dataset Research
69(1)
6.3 Clinical or Practical Significance
69(1)
6.3.1 Effect Size (Clinical or Practical Significance of Pchange= PTime2-- PTime1)
69(1)
6.3.2 Interpretation of Effect Size (Clinical or Practical Significance)
70(1)
6.4 Associations
70(3)
6.4.1 Correlation
70(2)
6.4.2 Regression
72(1)
6.4.3 Interpretation of Correlations
72(1)
6.4.4 Survival Analysis (PTime1, PTime2, ... PTimeX)
72(1)
6.4.5 Cross Tabs and Chi-Square (x2)
73(1)
6.5 Generalizability
73(4)
References
75(2)
7 Exploratory Data Analysis
77(10)
7.1 The Development of Exploratory Data Analysis
77(1)
7.2 Interpretation of Exploratory Data Analysis
78(1)
7.3 Visualization Techniques
78(9)
7.3.1 Heat Map
78(2)
7.3.2 Line Graph
80(4)
References
84(3)
8 Ethical Considerations
87(12)
8.1 Minimal Risk
87(1)
8.2 Institutional Review
88(4)
8.2.1 Where and How to Access an IRB
88(1)
8.2.2 When a Project May Be Exempt from IRB Review
88(1)
8.2.3 The Special Case of Quality Improvement
89(1)
8.2.4 Minimal Risk and IRB Review
90(1)
8.2.5 The Special Case of Program Evaluation
91(1)
8.3 Informed Consent
92(1)
8.3.1 What Is Informed Consent?
92(1)
8.3.2 Informed Consent Processes in the Context of Existing Data
93(1)
8.4 Data Privacy and Security
93(6)
References
95(4)
Part II Practical Guide for Using the Problem-Intervention-Outcome Meta-Model
9 Use the Worksheets and PIO MM Figure
99(8)
9.1 Review of Part I
99(1)
9.2 Overview of Part II
100(1)
9.2.1 Examples of Projects
100(1)
9.3 Starting the Process
101(6)
9.3.1 Worksheet Review
101(4)
9.3.2 Complete the PIO MM Diagram
105(1)
References
105(2)
10 Know the Literature (Worksheet A)
107(12)
10.1 Preparing to Complete Worksheet A
107(1)
10.2 Step-by Step Instructions for Completing Worksheet A
108(7)
10.2.1 Population of Interest
109(1)
10.2.2 Problem Addressed
110(1)
10.2.3 Measure(s) of Outcome
110(1)
10.2.4 Intervention(s) Used
111(1)
10.2.5 Measures of Intervention
112(1)
10.2.6 Measure of Intervention Fidelity
112(1)
10.2.7 Demographic Characteristics of a Sample
113(1)
10.2.8 Contextual Factors
113(1)
10.2.9 Analysis Methods
114(1)
10.2.10 Comments
115(1)
10.2.11 Complete Reference
115(1)
10.3 Sources of Information for the PIO MM Matrix
115(4)
References
118(1)
11 Define the Problem (Worksheet B)
119(12)
11.1 Preparing to Complete Worksheet B
119(1)
11.2 Step-by Step Instructions for Completing Worksheet B
120(11)
11.2.1 Problem
120(1)
11.2.2 Definition of the Problem
121(1)
11.2.3 Population of Interest
121(1)
11.2.4 Background
121(1)
11.2.5 Problem Measurement Instrument/Scale
122(1)
11.2.6 Anticipated Outcome and Rationale
123(1)
11.2.7 What is Not Known/Gap in Knowledge
123(5)
References
128(3)
12 Describe the Intervention (Worksheet C)
131(12)
12.1 Preparing to Complete Worksheet C
131(1)
12.2 Step-by Step Instructions for Completing Worksheet C
132(11)
12.2.1 Describe the Intervention
132(1)
12.2.2 Expected Effectiveness
132(1)
12.2.3 Theoretical Framework
133(1)
12.2.4 Intervention Content and Essential Core Components
133(1)
12.2.5 Describe Intervention Measurement: Amount, Type, Fidelity, Quality
134(1)
12.2.6 Describe Interventionist Characteristics: Qualifications, Training, Demographics
135(6)
References
141(2)
13 Define the Outcome (Worksheet D)
143(12)
13.1 Preparing to Complete Worksheet D
143(1)
13.2 Step-by-Step Instructions for Completing Worksheet D
144(11)
References
152(3)
14 Plan the Analysis (Worksheet E)
155(12)
14.1 Preparing to Complete Worksheet E
155(5)
14.1.1 Step
1. Review Project Statements
156(2)
14.1.2 Step
2. Select Statements That Are Most Applicable to the Project and Discipline
158(1)
14.1.3 Step
3. Review Design Options
158(1)
14.1.4 Step
4. State the Design
158(1)
14.1.5 Step
5. Review Variables
159(1)
14.1.6 Step
6. Plan for Creating New Variables
159(1)
14.2 Step-by-Step Instructions for Completing Worksheet E
160(7)
14.2.1 Exploratory Data Analysis
160(1)
14.2.2 Sample
160(1)
14.2.3 Intervention
161(1)
14.2.4 Outcome
162(1)
14.2.5 Relationships Among Variables
163(1)
References
164(3)
15 Interpret the Results (Worksheet F)
167(12)
15.1 Preparing to Complete Worksheet F
167(1)
15.2 Results Statements and Presentation
168(7)
15.2.1 Presenting the Results
168(1)
15.2.2 Description of Sample Characteristics
168(2)
15.2.3 Description of Interventions
170(1)
15.2.4 Description of Outcomes
171(2)
15.2.5 Description of Benchmark Attainment
173(1)
15.2.6 Correlations Between Interventions and Outcomes
174(1)
15.3 Results Interpretation
175(4)
15.3.1 Theoretical Framework-Related Interpretation
176(1)
15.3.2 Temporality-Related Interpretation
176(1)
15.3.3 Give Alternative Explanations for the Findings
177(1)
References
178(1)
16 Disseminate the Findings
179(26)
16.1 Why Dissemination Matters
179(1)
16.2 Getting the Most Benefit from This
Chapter
180(1)
16.3 Iterative Interpretation and Explication of the Overall Story
180(4)
16.4 Drafting the Abstract: Summarize the Story in Brief
184(1)
16.5 Develop and Display Results
185(2)
16.6 Adding Meaningful Interpretation to the Results
187(6)
16.7 Limitations
193(1)
16.8 The Methods Section
194(1)
16.9 The Purpose Statement
195(1)
16.10 Background to Set the Stage for the Purpose
195(2)
16.11 The Gap in Knowledge
197(1)
16.12 Title, Abstract, and Conclusion
198(1)
16.13 Rewrite the Abstract
199(1)
16.14 Write the Conclusions Section
199(2)
16.15 Polishing Tips
201(1)
16.16 Styles and Author Guidelines
201(4)
References
202(3)
17 Synthesis, Next Steps, and Epilogue
205
17.1 Planning Next Steps
205(2)
17.2 Questions to Inspire Next Steps
207(1)
17.3 Building Evidence on Evidence
208
References
209
Karen A. Monsen, PhD, RN, FAAN, is an award-winning scholar and expert nurse informatician.  She is co-director of the University of Minnesota Center for Nursing Informatics, Director of the Omaha System Partnership, affiliate faculty in the Institute for Health Informatics, and faculty in the Center for Spirituality and Healing. Dr. Monsen specializes in data management for intervention effectiveness research, quality improvement, and outcome evaluation in nursing and health care. 

Based on her years of public health experience and her insights from exploring big data methods with existing datasets, Dr. Monsen celebrates the power of shared understanding enabled by the use of standardized data. At the cross roads of research and practice, she champions intervention effectiveness research through three major initiatives: The Omaha System Community of Practice, The Omaha System Partnership for Knowledge Discovery and Health Care Quality; and The Omaha

System Guidelines. These initiatives are face-to-face and Internet forums for research and quality improvement projects world-wide.  Dr. Monsen is the author of over 70 published studies that have advanced the design, development and evaluation of clinical practice for diverse problems, programs, and populations.
Lisainfo e-raamatute kohta Lisainfo e-raamatute kohta
Püsilink: https://www.kriso.ee/db/97833196124616e.html
Märksõnad: