Entrepreneurship in Healthcare

Ralf Wilden, Massimo Garbuio, Federica Angeli, Daniele Mascia

• Publisher: Routledge
• Year: 2018
• ISBN:
  9781351655255
• Edition: 1
• Topic: Commerce
• Subtopic: Activité entrepreneuriale

Entrepreneurship in the Healthcare sector has received increased attention over the last two decades, both in terms of scholarly research and number of innovative enterprises. Entrepreneurial activities and innovations have emerged from and will continue to be driven by several actors along the healthcare value chain but especially from non-traditional healthcare players. In this new volume, we present the reader with several critical issues in healthcare entrepreneurship and innovation, covering a comprehensive set of research topics. We bring together the latest academic research and management practice, with contributions by authors from entrepreneurship, medical sciences, and management, who provide in depth and practical insights into designing and managing entrepreneurship in healthcare. Upon providing a systematic review of the research field, we discuss several important macro-, meso-, and micro-level issues in healthcare entrepreneurship, such as opportunity identification, the entrepreneurial ecosystem including accelerators, the benefits of open innovation for the sector, and social entrepreneurship in healthcare.

These topics open up avenues for nurturing entrepreneurship in healthcare through both education and policy. Building on this trend, the book is organized around levels of analysis and specifies which cross-disciplinary efforts are needed to advance understanding of how entrepreneurs discover opportunities and start viable and innovative businesses.

Healthcare Entrepreneurship will be of interest scholars of health care and entrepreneurs alike, but also managers of innovative health care enterprises as well as policy makers in the health sector.

1
Entrepreneurship in Healthcare

Past Contributions and Future Opportunities

Massimo Garbuio and Ralf Wilden

Introduction

The number of startups listed on the New York Stock Exchange that are active in healthcare-related industries has grown significantly, such that they now comprise the largest number of company listings in the New York Stock Exchange in 2014. In September 2015, the New York Times counted over 165,000 smartphone applications available in the US to help people stay healthy or monitor medical conditions.¹ Innovation in healthcare is expected to be significantly fueled by new entrants and entrepreneurs using digital technologies, “Internet of Things” applications, and/or low-cost business models to solve problems more cheaply and effectively (Teece, 2010; Christensen, 1997). It has been highlighted that starting a business may be the most valuable lesson for medical students (Ryu, 2017). Similarly, it has been claimed that anesthesiologists could become the next leaders in innovative medical entrepreneurism (Kwon et al., 2017).

Despite its promise, entrepreneurship in the healthcare context faces several unique barriers (Phillips and Garman, 2006). First, because the majority of healthcare revenue (which is primarily generated from third parties, such as governments and insurance providers) is directly linked to specific provided services, healthcare organizations have little room to use their revenues for other activities (Robinson, 2001), such as building up risk capital to allocate to entrepreneurial activities (Phillips and Garman, 2006). Second, the hierarchical structure of healthcare organizations and competition for scarce resources often discourages collaboration between organizations with similar capabilities. Finally, the high degree of professional autonomy of healthcare professionals and their discomfort with risk taking given the traditional scope of their work hinders entrepreneurship.

A better understanding of the unique context and challenges that the healthcare sector provides will help to advance entrepreneurship research in general. For example, digitalization and the large availability of mobile devices in both advanced and developing economies allow for new business models, often driven by entrepreneurs previously not active in healthcare. Further, the Internet of Things, and wearable devices more specifically, permit us to monitor health conditions and address them in new ways, even remotely. Finally, pay per product is being replaced with pay-per-usage and subscription models, and even free models, as when income is generated by advertising or cross-selling to other market segments. As these examples suggest, it is becoming easier for healthcare entrepreneurs to reach large numbers of people.

Most of the entrepreneurship research using a healthcare context has been published in healthcare and medical journals, with little reference to management theories and journals. That is of some concern, given the wealth of knowledge that entrepreneurship and management literature have developed over the years. We aim to contribute to the current debate with two key contributions. First, we explore the research progress that has been made in the area of healthcare entrepreneurship. To do so, using text mining, we conduct systematic content analysis of the abstracts 909 articles published in relevant health and management journals. More precisely, we explore the dominant content themes of existing research, as well as changes in these content themes over time. Second, to improve our understanding of research in healthcare entrepreneurship, we suggest themes that can be leveraged to shape future research endeavors and foster collaborations across fields (Ireland and Webb, 2007). Indeed, to increase the chances of discovering valuable opportunities and starting viable businesses in healthcare, much of the work from entrepreneurship and management more broadly can be leveraged further. We do so by presenting our research directions in a multi-level framework, distinguishing among macro-, meso-, and microlevel research, as established in entrepreneurship research. We provide key themes for each and suggest entrepreneurship, management, innovation, and marketing theories that may help guide further research.

Methodology

To examine the impact of entrepreneurship in healthcare research and develop a framework for future theory building and testing, we conduct a systematic review of published articles in the area of entrepreneurship in healthcare (Tranfield et al., 2003). We validate the extrapolation of relevant themes and concepts through textual analysis using the Leximancer software. To conduct a systematic literature review, we primarily drew on Tranfield et al. (2003) and Macpherson and Jones (2010), in addition to Lee (2009), Rashman et al. (2009), and Wang and Chugh (2014). We followed a systematic approach to increase the validity of our findings by providing a clear set of steps that can be replicated. Given that our sample spans multiple disciplines, from entrepreneurship to management to medical care, we followed Lee (2009), Rashman et al. (2009), and Wang and Chugh (2014) in considering systematic reviews as a “guiding tool” that allows us to shape the review according to our research focus and objectives rather than as a methodology with rigid rules.

Data Collection

Using Scopus, one of the most comprehensive research platforms available (Zupic and Čater, 2015), we looked for articles that explicitly included the terms “entrep*” AND “healthcare” OR “health care” in their titles, keywords, and/or abstracts.² We focused our search on only journal articles published in English. Thus, we did not include other published outputs, such as in book chapters and conference proceedings. Books (similar to working papers and book chapters) do not undergo as rigorous editorial review process as journals, and including these sources may impact the quality of the data and results.

The comprehensive search resulted in 1,289 articles (909 available abstracts), out of which 145 articles were published in journals classified in as belonging to business, management, accounting, economics, finance, or econometrics, and 912 articles were published in journals related to medicine, nursing, or health professions. We focus our analysis on these two broad categories of academic research, and include all articles for which abstracts were available (135 abstracts in the former and 671 articles in the latter category).

Analysis Method

To provide a detailed analysis of core publications in entrepreneurship in healthcare, we analyze the manuscripts using unstructured ontological discovery. We therefore shift the level of analysis to the words used by the authors instead of investigating authors and their citation patterns. The result is a systematic, unbiased, and content-driven review of the literature (Biesenthal and Wilden, 2014). We apply the textual data-mining software Leximancer 4.0, a valuable tool for narrative inquiry of a research field (Sowa, 2000; Stubbs, 1996). This text mining tool has been used in previous literature reviews in areas such as open innovation (Randhawa et al., 2016), dynamic capabilities (Wilden et al., 2016), and service-dominant logic (Wilden et al., 2017). The assumption underlying this type of analysis is that co-occuring words reflect categories (i.e., concepts) that carry specific meanings and that words are defined by the context within which they occur. Leximancer differs from manual coding of words, as it bootstraps an expanded list of related terms that signify a concept from the text data. This machine-based identification of concepts exhibits close agreement with expert judgment (Campbell et al., 2011; Rooney, 2005; Wilden et al., 2017). It is therefore appropriate for sophisticated exploratory research due to its high reliability and reproducibility of concept extractions and thematic grouping.

A Bayesian learning algorithm underlies Leximancer to identify: (i) the most frequently used concepts within the text data, and (ii) the relationships between these identified concepts. Thus, Leximancer first systematically uncovers key concepts within the healthcare entrepreneurship paradigm by using a small number of seed words from the text (thematic analysis). To do so, the software generates a thesaurus of words that are closely related to a concept to define its content. Identified concepts are more than just keywords; they represent collections of words that carry related meaning (Campbell et al., 2011). Second, Leximancer reveals how concepts are linked based on the frequency and co-occurrence of words within their contexts (semantic analysis). The result is an investigation of concepts (i.e., common text elements) and themes (i.e., groupings of uncovered concepts) (Mathies and Burford, 2011).

The results of this thematic and semantic analysis are represented in “maps of meaning.” The black dots represent identified concepts; the relationships between concepts are then identified and aggregated into themes.³ The color of the circles (brighter circles are more important) and their size (which indicates how many concepts have been clustered to form a given theme) indicate the importance of the themes. The distance between concepts on these “maps of meaning” indicate how closely the concepts are related. Hence, concepts that are weakly related semantically will be mapped far apart from each other and vice versa (Campbell et al., 2011; Rooney, 2005). Summing up, Leximancer aids researchers in interpreting and visualizing the structure of complex text data.

State of Entrepreneurship in Healthcare Research

Publication Statistics

In a first analysis step, we analyzed the publication trends. To do so, we analyzed all 909 available abstracts included in our sample, not restricting the list of journals to any specific research area. Figure 1.1 shows that the number of publications has steadily increased.

As summarized in Figure 1.1, research on entrepreneurship in the healthcare sector has attracted growing interest over the past 40 years. Furthermore, our analysis reveals that entrepreneurship in healthcare research is beginning to reach a broad audience, indicating interest within multiple domains. More specifically, the majority of our sample articles were published in medical and nursing journals rather than in entrepreneurship or management journals. In fact, only six articles were published in leading management or strategy journals, such as: Research Policy (two articles), R&D Management (one), Journal of Business Venturing (two), Journal of Business Ethics (three), and Harvard Business Review (four). In fact, medicine, nursing, or health professions journals correspond to 71% of our total entrepreneurship in healthcare research sample, and business, management, accounting, economics, finance, or econometrics articles for 11%, revealing that the impact of former three fields has been more significant than that of other disciplines. Overall, our review suggests that entrepreneurship in healthcare research has yet to reach a broad audience in management as well as marketing. However, we notice a promising trend toward increased research in this area.

Figure 1.1 Publications Per Year

Textual Analysis Findings

In the following sections, we conduct a text-mining-based content analysis of the identified article abstracts to systematically decipher key concepts and themes. To conduct the analysis, all text data was used as input into the analysis, and concept seeds were created through the software—the equivalent of assuming a “diffuse prior” of theoretical concepts. Patterns that arose between concepts were identified and aggregated into themes. We illustrated the relationship between concepts and themes through concept maps. We structured our textual analysis in two steps. First, we analyzed all article abstracts published in medical journals and in management-related journals separately. Second, we compared the findings of these two sets of articles.

In the “maps of meaning” discussed and presented hereafter, circles represent themes derived from the articles, and relevant concepts are located within each theme. The importance of themes is shown by the color and size of the circles, with darker and bigger circles being more important. The distance between concepts on the map indicates how closely related they are; that is, concepts that are only weakly semantically linked will appear far apart on the concept map (Campbell et al., 2011; Rooney, 2005).

Healthcare and Medical Journals Sample

We began by analyzing the available abstracts of the 671 articles published in medicine, nursing, or health professions journals (Figure 1.2).

Figure 1.2 Themes and Concepts Based on Medical Journals Abstracts

Existing healthcare research has highlighted the importance of innovation as well as systems. For example, Shaw (1993) investigated the role of entrepreneurs’ networks to foster innovation and found that consultant clinicians and physicians play an important role in new product development processes and marketing of innovative products. For example, research has investigated the use of six sigma, a set of techniques and tools for process improvement, in healthcare services and research and development (R&D) processes (Rehn and Abetti, 2013). Furthermore, Janssen and Moors (2013) have investigated the role of entrepreneurial strategies in developing sustainable innovations for the structural change of healthcare systems.

The themes policy and entrepreneurs (comprising concepts such as community, public, and government) appear in close proximity on the map. In particular, previous macro-level research has investigated the role of public policies and go...

Table of contents

• Cover
• Title
• Copyright
• Contents
• Authors’ Biographies
• Preface
• 1 Entrepreneurship in Healthcare: Past Contributions and Future Opportunities
• PART 1 Macro-Level Topics in Healthcare Entrepreneurship
• PART 2 Meso-Level Topics in Healthcare Entrepreneurship
• PART 3 Micro-Level Topics in Healthcare Entrepreneurship
• Index