Purpose/ Background
The key resource for value creation in ambulatory healthcare is knowledge. Providers of ambulatory care are faced with knowledge-related challenges: Increasingly complex disease patterns and rapid medical innovation overwhelm their capacity to identify, generate, integrate, modify, diffuse and apply relevant knowledge. This results in reduced quality of care.
Nevertheless, knowledge-based value creation has not been widely explored in ambulatory healthcare. Several research gaps explain: There are few publications regarding tools and methods for the management of knowledge resources in this context. Furthermore, the causal links between knowledge and organizational outcomes has not been theorized. A third major gap in the literature is the non-existence of frameworks for measuring knowledge-induced ambulatory healthcare performance.
Against this backdrop, this dissertation attempts to answer the following overarching question: How can knowledge-based value creation be managed and measured in ambulatory healthcare?
Design/ Methodology/ Approach
This cumulative dissertation adopts a mixed-methods approach, i.e., each of the four included publications adopts a methodological approach appropriate to its topic and research question.
The first publication narratively reviews major developments in Intellectual Capital (IC) and Knowledge Management theory. It benchmarks the new industry standard on Knowledge Management Systems (ISO 30401) against the previous literature by means of document analysis. Thereby it summarizes the state of research and practice regarding knowledge-based value creation.
The second publication takes the form of a systematic literature review. In line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, it summarizes the literature on Knowledge Management and performance in ambulatory healthcare. It compiles an overview of Knowledge Management practices which have been studied in the literature. Furthermore, it lists the indicators used to measure the impact of Knowledge Management on ambulatory healthcare performance and assesses their usefulness for further research and practice.
The third publication explores the Knowledge Management-performance relationship by means of qualitative data analysis. Based on interviews with stakeholders from the ambulatory healthcare context, a toolbox of human-centered Knowledge Management methods and technical Knowledge Management tools for ambulatory healthcare is compiled. A conceptual model of the causal links between knowledge and organizational value creation is derived.
The fourth and final publication uses social network analysis to measure Relational Capital in referrer networks of medical specialists in ambulatory settings. Using inferential statistics, it correlates Relational Capital with the economic performance of healthcare providers.
Findings
The first publication shows that the “ISO 30401:2018 Knowledge Management Systems” standard successfully integrates the broad and heterogenous extant literature on Intellectual Capital and Knowledge Management. The standard creates a common language for this research field and provides guidelines for Knowledge Management Systems across geographical, industry and organizational settings. As it is intentionally neutral with regards to concrete Knowledge Management tools and methods, the challenge lies in the implementation of the standard in practice.
The second publication is a systematic literature review on Knowledge Management and its effects on the performance of ambulatory healthcare providers. It reveals that the previous literature is narrowly focused on 6 types of Knowledge Management practices, namely Electronic Health Records, Health Information Systems, Clinical Decision Support Systems, Trainings, Communities of Practice and bundles of firm-specific Knowledge Management initiatives (“multi-faceted interventions”). In previous publications, these tools and methods were mostly studied in relation to healthcare quality, while other outcomes like financial performance, staff engagement and patient satisfaction were neglected.
The third publication, an interview-based conceptual study, paints a different picture than the literature review. Practitioners use a much broader range of Knowledge Management initiatives than those studied in the literature. Specifically, self-learning tools such as apps and podcasts as well as immersive training sessions are used by ambulatory healthcare providers. Also, technical gadgets for speech recognition and automated data processing are used.
Sector stakeholders also relate Knowledge Management initiatives to a much wider set of outcome dimensions than the academic literature. Financial performance, staff engagement and client (patient/ referrer) satisfaction were named as distal outcomes. According to the interviewees in the study, Knowledge Management initiatives have direct causal connections with these outcomes as well as indirect connections mediated by quality and efficiency.
The fourth publication shows that Relational Capital in social-professional networks of medical specialists can be measured by social network metrics (degree, density, relative betweenness centrality, referrer concentration). Furthermore, empirical support for the relationship between the Relational Capital and economic performance of medical specialist offices is provided.
Originality/ Value
In summary, this thesis makes three key contributions to research: Firstly, it provides an overview of human-centered Knowledge Management methods and technical Knowledge Management tools for the ambulatory healthcare context. Secondly, it sheds light on the causal links between knowledge resources and value/performance delivered by ambulatory healthcare providers. Thirdly, it develops a measurement framework for Relational Capital. Finally, it points out a range of research questions worth exploring.:1 Introduction 1
2 Theoretical Premises 5
2.1 Definitions 5
2.1.1 Ambulatory Healthcare 5
2.1.2 Value in Ambulatory Healthcare 9
2.1.3 Knowledge 11
2.1.4 Knowledge Management 12
2.1.5 Intellectual Capital 18
2.2 The Resource-based View of the Firm 21
2.2.1 Historic Development 21
2.2.2 Key Criticisms 24
2.2.3 Applicability of the Resource-based View to Healthcare 24
2.3 Intellectual Capital Theory 27
2.3.1 Historical Development of Intellectual Capital Theory 27
2.3.2 Intellectual Capital Theory in (Ambulatory) Healthcare 37
2.3.3 Criteria for Constructing and Assessing Intellectual Capital Measurement and Management Frameworks 39
2.4 Knowledge Management Theory 41
2.4.1 Development of Knowledge Management Theory 41
2.4.2 Knowledge Management Theory in (Ambulatory) Healthcare 50
2.4.3 Criteria for Constructing and Assessing Knowledge Management and Measurement Frameworks 51
3 Methodology and Data 53
3.1 Thesis: Mixed Methods Approach 53
3.2 Methodology Publication 1: Narrative Review and Document Analysis 55
3.2.1 Methodological Considerations 55
3.2.2 Data and Analyses 56
3.2.3 Trustworthiness 56
3.2.4 Methodological Issues 56
3.3 Methodology Publication 2: Structured Literature Review 57
3.3.1 Methodological Considerations 57
3.3.2 Sampling and Data Collection 58
3.3.3 Trustworthiness 61
3.3.4 Methodological Issues 61
3.4 Methodology Publication 3: Interview-based Qualitative Data Analysis 63
3.4.1 Methodological Considerations 63
3.4.2 Interview Guide Development 63
3.4.3 Sampling and Data Collection 64
3.4.4 Analyses 66
3.4.5 Trustworthiness 67
3.4.6 Methodological Issues 67
3.5 Methodology Publication 4: Social Network Analysis and Inferential Statistics 69
3.5.1 Methodological Considerations 69
3.5.2 Metric Choice 69
3.5.3 Network Construction 73
3.5.4 Regression Methodology 73
3.5.5 Model Specification 76
3.5.6 Database and Software 82
3.5.7 Reliability and Validity 82
3.5.8 Methodological Issues 82
4 Publication 1: The ISO 30401 Knowledge Management Systems Standard – A New Framework for Value Creation and Research? 83
4.1 Abstract 83
4.1.1 Purpose 83
4.1.2 Design/ Methodology/ Approach 83
4.1.3 Findings 83
4.1.4 Originality/ Value 83
4.2 Introduction 84
4.3 Theoretical Background 85
4.3.1 Roots of Knowledge Management Theory 85
4.3.2 Knowledge and Value – the Resource-based View (before 1991) 86
4.3.3 Theory Development in the 1990s 86
4.3.4 Theoretical Diversification and Empirical Testing in the 2000s 88
4.3.5 Consolidation in the 2010s 88
4.3.6 Approaches to the ISO 30401 89
4.4 Structure and Content of the ISO 30401 – Knowledge Management Systems Standard 90
4.4.1 Structure of the ISO 30401 90
4.4.2 Knowledge Management System Requirements According to ISO 30401 90
4.4.3 Features of the Organizational Context Supporting the Knowledge Management System 93
4.4.4 Non-requirement Statements 93
4.5 Looking Back: Benchmarking the ISO 30401 Against the Literature 94
4.5.1 Nature of Knowledge Management 94
4.5.2 Knowledge Management Practices 95
4.5.3 Knowledge Management Enablers 97
4.5.4 Knowledge and Value Creation 99
4.6 Looking Forward: Maximizing Knowledge-based Value Creation 100
4.6.1 Operationalize the ISO 30401 Based on Empirical Evidence 100
4.6.2 Leverage Effects of Standardization on the Organization 101
4.6.3 Consider Market Forces 101
4.7 Conclusions 102
4.7.1 Synthesis of Findings 102
4.7.2 Contribution and Limitations 102
5 Publication 2: Knowledge Management as a Driver of Performance in Ambulatory Healthcare – a Systematic Literature Review Through an Intellectual Capital Lens 104
5.1 Abstract 104
5.1.1 Purpose 104
5.1.2 Design/ Methodology/ Approach 104
5.1.3 Findings 104
5.1.4 Originality/ Value 104
5.2 Introduction 105
5.3 Methods 106
5.3.1 Data Sources and Search Strategy 106
5.3.2 Quality Assessment Strategy 107
5.3.3 Inclusion and Exclusion Criteria 107
5.3.4 Data Extraction Methods 108
5.4 Findings 108
5.4.1 Search Results 108
5.4.2 Types of Knowledge Management Initiatives and Knowledge Management Impact on Intellectual Capital 109
5.4.3 Performance Dimensions, Indicators and Impact 133
5.4.4 Relevance, Validity and Feasibility of Indicators 134
5.5 Discussion 135
5.5.1 What Knowledge Management initiatives have been used by ambulatory healthcare providers and how do they influence Intellectual Capital? 135
5.5.2 How has Knowledge Management-induced performance been operationalized in ambulatory healthcare and what impact of Knowledge Management on performance has been observed? 136
5.5.3 How suitable are the indicators used in the literature for further research on Knowledge Management, Intellectual Capital and performance in ambulatory healthcare settings? 137
5.5.4 Implications for Research 138
5.5.5 Implications for Practice 139
5.5.6 Limitations 139
6 Publication 3: Developing a Conceptual Model for Knowledge Management and Organizational Success in Ambulatory Healthcare 140
6.1 Abstract 140
6.1.1 Purpose 140
6.1.2 Design/ Methodology/ Approach 140
6.1.3 Findings 140
6.1.4 Originality/ value 140
6.2 Introduction 141
6.3 Related Literature 142
6.3.1 Definition: Fluid Nature of Knowledge 142
6.3.2 Definition: Business Process-Oriented Knowledge Management 142
6.3.3 Knowledge Management in Ambulatory Healthcare 143
6.4 Methodology 144
6.4.1 Sample: Two Sets of Semi-structured Interviews 144
6.4.2 Method: Qualitative Content Analysis (“Coding”) 145
6.5 Findings 145
6.5.1 Process-oriented Taxonomy of Knowledge Management Methods and Tools for Ambulatory Healthcare 145
6.5.2 Conceptual Model of Knowledge Management-induced Ambulatory Healthcare Performance 149
6.6 Discussion 154
6.7 Conclusion 156
7 Publication 4: Relational Capital in Referrer Networks of Medical Specialists in Office Settings 158
7.1 Abstract 158
7.1.1 Purpose 158
7.1.2 Design/ Methodology/ Approach 158
7.1.3 Findings 158
7.1.4 Originality 158
7.2 Introduction 159
7.3 Literature-based Hypothesis Development and Variable Selection 161
7.3.1 Dependent Variable: Economic Performance 162
7.3.2 Independent Variables: Network Characteristics 162
7.3.3 Control Variables: Characteristics of the Organization 166
7.4 Methods 167
7.4.1 Data Source 167
7.4.2 Constructing Medical Specialists’ Networks 167
7.4.3 Statistical Analyses 168
7.5 Findings 168
7.5.1 Sample Characteristics and Descriptive Statistics 168
7.5.2 Correlation of Network Characteristics with Practice Performance 170
7.6 Discussion 173
7.7 Conclusion 174
7.7.1 Contributions to the Literature 174
7.7.2 Implications for Practice 174
7.7.3 Limitations 175
7.7.4 Opportunities for Future Research 176
8 Discussion and Conclusion 177
8.1 Summary of the Results of the Thesis 177
8.2 Contributions to Research 178
8.2.1 Topic 1: Management of Knowledge Resources 178
8.2.2 Topic 2: Knowledge and Value Creation 179
8.2.3 Topic 3: Knowledge (Performance) Measurement 180
8.3 Implications for Practice 181
8.4 Limitations 183
8.5 Opportunities for Future Research 183
8.6 Conclusion 185
9 Appendix I: Questionnaire for Publication 3 (Physician Version) 186
10 Appendix II: Code Counts from the Second Interview Cycle (Publication 3) 192
11 Publication bibliography 198
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:85329 |
| Date | 05 June 2023 |
| Creators | Pflugfelder, Nina Sophie |
| Contributors | Pawlowsky, Peter, Edvinsson, Leif, Technische Universität Chemnitz |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 10.1108/JIC-07-2020-0256, 10.1108/JIC-02-2020-0068, 10.1108/JIC-01-2021-0015 |
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