Across Vendors
4.1 Data collection
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48 Chapter 4: Research methodology – Multi-methods research
A multi-methods design involves the completion of research, either qualitative or quantitative on their own, then used together to form essential components of one research project (Bryne and Humble, 2007). Qualitative research methods are mostly defined as techniques associated with the gathering, analysis, interpretation and presentation of narrative information (Teddlie and Tashakkori, 2009). In this study, qualitative research is deem as a more informative form of research method since the presence of a variety of stakeholders will require a more in-depth interpretation of patterns, relationships and phenomenon. With its multi-dimensional views necessary to be collated from different perspectives in terms of healthcare, policies and underlying needs, a more complex qualitative research model has to be adopted. Multi-methods research simply mean the combination of more than one type of research methodology for a more thorough understanding of research topic (Clark, 2010). Researchers will typically collect multiple forms of data rather than rely on a single data source, and then all data will be reviewed, make sense and organized into categories or themes that cut across all the data sources (Creswell, 2009). In this case, with a range of roles from different stakeholders in the healthcare system, it is necessary to adopt more than one research methodologies to achieve a more comprehensive model of a possible health service cloud computing system targeting at aging population issues.
4.1 Data collection
Two methods of research are employed in this study, namely intensive interviews and archival documents collation. Intensive interviews were conducted with personnel from government agencies responsible for the healthcare system of Singapore, medical providers such as doctors and nurses and potential users who are indeed potential support group for elderly care. Questions were focused mainly on the present methods of medical records handling, concerns and needs of stakeholders in the healthcare system with regards to scope
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49 performed in health maintenance and views on aging population issues from a personal and overall perspective. Main interview questions can be found in Appendix 1. Further follow-up questions were asked during the interview process to elicit participants‟ responses in more in-depth manner. Interview responses were then transcribed and analyzed. Face-to-face, telephone and email internet interviews are done in this method.
Other than interviews, other data sources such as archival documents in terms of (i)ministerial speeches by the related ministries regarding healthcare policies and initiatives (Ministry of Health, Singapore), (ii) reports on healthcare policies and (iii) newspaper articles on healthcare and eldercare initiatives, were also done to help reveal concepts pertaining to the effective and meaningful use of a health system when tapping on cloud computing technology. Table 2 indicates the pool of data that are obtained from different sets of stakeholders:
Table 2: List of intensive interview stakeholders and archival documents
Stakeholders Retrieval of data from:
Governing Agency (i) Interviews of 2 personnel (A and B) from Ministry of Health(MOH).
(ii) 10 ministerial reports and speeches on aging population and healthcare policies and initiatives.
- Article 1: Speech by Permanent Secretary on Agency of Integrated Care.
- Article 2: Ministerial Speech by Minister of Health on healthy Singaporeans.
- Article 3: Speech by Senior Permanent Secretary.
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50 - Article 4: Ministerial Speech by Minister of Health on polyclinics going paperless.
- Article 5: Speech by Permanent Secretary on tackling challenges in healthcare.
- Article 6: Ministerial Speech by Minister of Health on healthcare reforms.
- Article 7: News Report on Healthcare policies reforms in elderly care.
- Article 8: News Report on integration of healthcare.
- Article 9: Report on elderly care.
- Article 10: Report on elderly care policies.
Professional Medical Providers Interviews of 5 medical professionals (3 doctors, 2 nurses)
- Doctor A and C from public hospitals - Doctor B from private hospital - Nurse A and B from public hospitals
Singaporeans 10 potential Singaporean users ( A to G who
are potential caregivers for their parents, and H to J who are elderly aged above 65 with some form of chronic illness)
- Singaporean A: 32 years old - Singaporean B: 36 years old - Singaporean C: 40 years old - Singaporean D: 39 years old - Singaporean E: 55 years old - Singaporean F: 63 years old - Singaporean G: 46 years old - Singaporean H: 66 years old
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51 - Singaporean I: 70 years old
- Singaporean J: 68 years old
4.2 Triangulation
„Triangulation refers to the combinations and comparisons of multiple data sources, data collection and analysis procedures, research methods, investigators, and inferences that occur at the end of the study‟ (Teddlie and Tashakkori, 2009, p.27). More specifically, in this study, the use of data triangulation, which involved the use of a variety of data sources in a study, is used to understand the inter-relationships between the various stakeholders in the healthcare system of Singapore. This triangulation design compare results, validate, interpret and corroborate the findings based on the findings from the different qualitative findings, thereby having a valid, well-substantiated conclusion about a single phenomenon (Creswell and Clark, 2007).
From the two main types of data collection methods employed, namely intensive interviews and archival documents collation, collation is done via ATLAS.ti software, which allows specific coding of key ideas and themes in each set of data, then formed into links which thereby evolved the theory which consists of criteria necessary for the creation of a more efficient health service cloud computing system that focuses on the aging population issues of the Singapore society. Identification of categories for collection of data through open coding with the assistance of ATLAS.ti software are done from each set of data to identify the variety of concepts raised from the data, and collating them into numerous specific categories.
Open coding, which involves the defragmentation of text and pulling out relevant concepts into various components, is the initial process which then leads on to the more advanced axial coding process (Strauss & Corbin, 1998). Theorizing process takes place with the integration and refining of theory such that theoretical saturation is reached and is known as selective coding (Strauss & Corbin, 1998). In this study, concepts in the collated data were first
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52 identified in a large range with the aim of answering the research questions in this study during the initial open coding process. Subsequently, axial coding was done by drawing links and relationships built between the various concepts identify and thereafter categorized into evidences which support the key concepts.
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53 Chapter 5: Results
With the collation and analysis of the data from the two type of research methods, namely through intensive interviews and archival documents collation from relevant sources, key concepts which are regarded as the elements necessary for proper functioning of a health service cloud computing system to enable active aging are analysed through the use of ATLAS.ti qualitative coding program.
The inter-relationships between the various concepts are coded and categorised and the key element which ensures that the system is able to perform its desired outcomes is the idea of having it as an enabler such that collaborations between the stakeholders are possible. Data are qualitatively analyzed from the datasets comprising of intensive interviews and archival documents of ministerial speeches and publications and newspaper articles through triangulation of findings from the various categories and sources. 6 main categories are identified through the coding process using ATLAS.ti, which allows datasets to be analyzed and categorized. They are: (i) primary care, (ii) familial support, (iii) awareness in health maintenance and transparency in information, (iv) improved efficiency and accuracy in healthcare with seamless transfer of care and (v) intermediate care and (vi) collaboration between stakeholders. This categorization is important when dealing with the large amounts of data which may consist of different concepts. The categorized raw data of the datasets in terms of intensive interviews and archival documents collated via ATLAS.ti can be found in Appendix 2. These 6 categories of concepts above is a depiction of the key issues which should be looked into in the context of the aging population in the Singaporean context, which hence addresses research question 1 of this study.