How does research contribute to the discovery of solutions

Next to determining that best solution, Ostheimer states that doing a discovery with a partner will help you identify:. What is the value that is going to be delivered by doing this project so that first of all, you can justify doing this project, and secondly, we can actually measure our success later based upon what the value of the project is going to be?

Once that is understood, the partner can propose the best combination of options to meet those goals. While the basis of the discovery is always the same, the actual questions that are asked vary depending on the business and industry, because no two businesses are exactly the same. The following outlines some general examples of the types of questions we ask during our discovery process and why:.

When the Discovery is complete , the solutions partner should provide you with a Summary of Findings document that not only does as its name says but also includes recommendations for a solution and the reasoning surrounding it. This is where you get to make sure everyone is on the same page. Equally important — you get insight into why this specific solution is being recommended. This is where you find out the value the solution really holds for your company and the differentiating factors for why that solution is the best fit.

The next step is for the solutions partner to do a presentation and demo of the recommended product that is catered to your specific needs. As in life, there are a lot of grey areas, and a discovery is how to make sure you not only receive a handpicked solution recommendation but understand why and agree with the selection.

Next to determining that best solution, Ostheimer states that doing a discovery with a partner will help you identify: What is the value that is going to be delivered by doing this project so that first of all, you can justify doing this project, and secondly, we can actually measure our success later based upon what the value of the project is going to be? What happens during a Discovery?

The following outlines some general examples of the types of questions we ask during our discovery process and why: Metrics questions give us a foundational understanding of your business. For example: How many employees do you have? Many of them consider the perceptions of the impact of RDS on content usage to better understand what students and researchers need and expect while searching for information. They confirmed among many other things that discovery tools actually had an impact on usage in several libraries, and that journal usage at Summon and Primo institutions increased more than it did with other services.

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Microsoft Academic 2. Reaxys: Chemistry Search Engine by Elsevier. Subscribe for free to get unrestricted access to all our resources on research writing and academic publishing including:. We hate spam too. We promise to protect your privacy and never spam you. Organisational arrangements, clinical skills and other more ambiguous elements that were open to interpretation and negotiation were also critical.

In another study examining innovations in acute care and primary care settings in the UK, Ferlie 16 identified the critical role of boundaries between professional groups.

Unlike some prior studies where high levels of professionalisation facilitated adoption of innovations, Ferlie's research found that the varying roles, social boundaries and distinctive cognitive styles of different professional groups can limit the adoption of new technologies. For example, the introduction of an anticoagulation service was slowed by disagreements between cardiologists, primary care physicians, nurses and IT system designers about the appropriate indications for treatment.

The adoption of minimally invasive cardiac surgery for coronary artery bypass graft or valve replacement surgery in 16 US hospitals provides a third example.

Edmondson and colleagues 17 found that successful implementation depended on team learning processes rather than resources, academic status or innovation history. Innovative procedures like minimally invasive cardiac surgery disrupt established work routines. Each of these research projects used case study methods to identify the novel aspects of the process of implementing innovation.

The research teams collected and analysed data from interviews, clinical data and documents. These research projects examined individuals or teams in context; they were embedded multiple case designs. The case study methods used in these three studies offer valuable tools in exploring the effectiveness of quality improvement more broadly. While case study research is a well-established method in organisational research, it appears to be less common in organisational health services research.

Case study research designs involve the collection of qualitative and often quantitative data from various sources to explore one or more organisations or parts of organisations and the characteristics of these contexts. Case studies can inform the development of more robust theory that identifies the links between problem, intervention and outcome.

Robert Yin, in his classic book, 22 notes that case study research is particularly helpful when researchers want to answer questions of how or why things work in real life contexts. Theory generated from cases may help to make sense of the complex relationships that underline healthcare practice and elucidate why efforts to improve care succeed in some circumstances, but not in others.

Based on these observations, researchers develop constructs that abstract the essence of what has been observed, classify or categorise these observations, and identify relationships between them.

Through these activities, researchers develop theories or models which organise the aspects of the world they study.

Second, in a deductive process, researchers test and improve these theories by exploring whether the same correlations exist in different data sets. This hypothesis testing allows the theory to be confirmed or rejected, and it also permits further specification of the theory to define the phenomena more precisely or specify the circumstances under which correlations hold. Where the goal of research is discovery or new explanations, case studies may offer a more powerful research design than experimental methods.

They suggest the appropriateness of different types of data varies depending on the research questions posed, the current state of the literature and the contribution envisaged from the research. Qualitative data, including interviews, observation and document analysis, are most appropriate for research where theory is nascent, and the research questions are exploratory. On the other hand, where theory is mature, survey methods and statistical testing focused on confirmation of hypotheses are more appropriate.

Organisational case studies have been an effective way to build theory in organisational research. Its emphasis on developing constructs, measures and testable theoretical propositions makes inductive case research consistent with the emphasis on testable theory within mainstream deductive research.

But others assert that multiple case studies provide a stronger base for theory building. Replication enables a researcher to perceive the patterns in the cases more easily and to separate out patterns from change occurrences. Different cases can emphasise varying aspects of a phenomenon and enable researchers to develop a fuller theory.

Fitzgerald and Dopson 19 identify four common types of multiple case study designs, each based on a different logic. These include 1 matching or replication designs intended to explore or verify ideas; 2 comparison of differences, including cases selected for their different characteristics; 3 outliers, comparison of extremes to delineate key factors and the shape of a field; and 4 embedded case study designs where multiple units are examined to identify similarities and differences.

Despite growing numbers of studies on quality improvement in healthcare, there is limited growth in a more general theory about improvement. For example, there is a growing view that improvement interventions should be tailored to potential barriers.

Yet, as Bosch notes, 29 in many cases it is difficult to assess whether such tailoring was done based on a priori barrier identification, and explicit use of theory to match the intervention to the identified barriers.

Case studies might contribute useful information to develop relevant theory. More broadly, case study research provides methods to examine organisational processes over time, examining the interplay of interventions with team dynamics or leadership strategy.

For example, studies by Baker 30 and Bate 31 of high-performing healthcare organisations illustrate the challenges of creating, spreading and sustaining effective practice in organisations. Some case study research has followed organisations over extended time periods repeating interviews with key informants eg, Denis' work on strategic change 40 Unlike survey research and RCTs, case study research can analyse the process of implementation and unpack the dynamics of change.

Organisational case studies can include a wide array of data, including interviews, documents, ethnography, survey data and observations. Although the case study is generally viewed as a qualitative method, it may include quantitative data. Other organisational case study research 17 32 40 43 has adopted a similar mix of data sources.

Case study research typically generates large quantities of data, which makes analysis critical, but complex. Moreover, the methods for aggregating data across projects are not well developed. Even within the same research project, different investigators may take the lead in different cases. Were they prospective or retrospective? Were they longitudinal or cross-sectional? How variable were the political and organisational contexts? Synthesis across studies can help to build a more generalisable understanding of organisational strategies to support improvement.

Yet views vary on whether we can synthesise research from multiple case studies undertaken independently. In their review of studies examining efforts to integrate evidence into clinical decision-making in UK healthcare, Dopson and colleagues 32 compared and synthesised their findings reanalysing the original studies to identify themes, recoding their reports and then assessing the outputs generated by the five researchers involved see table 1.

Such tables offer a bird's-eye view of the extent to which common themes inform different case studies, but such summaries are divorced from understanding how these issues are inter-related within each case. Identifying research themes across studies of innovation diffusion Efforts to create such syntheses raise issues about methodological rigour.

For those researchers who adopt a positivist framework, the test of good case studies builds on four criteria used to assess the rigour of field research: internal validity, construct validity, external validity and reliability. Framework for an investigation of the methodological rigour of case studies They found research procedures enhancing external validity in 82 of papers, and procedures supporting reliability in 27 of these papers.

Few papers provided evidence of internal or construct validity. Yin proposes pattern matching; explanation building; addressing rival explanations and using logic models as strategies to address internal validity. Does the evidence support the theory? Have the investigators ruled out rival explanations? Non-positivist researchers employ other methods to ensure the soundness of their findings; for example, see Lincoln and Guba.

An alternative measure of the rigour of case study research focuses on how good the theory is that emerges from this research. Pfeffer 48 suggests that good theory is parsimonious, testable and logically coherent. Good theory should also address critical issues of interest to organisations and interested parties.

Insights from other disciplines and attempts to seek out anomalies in other authors' work that might inform research in different areas are other strategies that may enrich the quality of case study research, improving the theory that results. Despite the need for more robust theory, why are there so few organisational case studies of quality improvement? Some candidate explanations might include: 1 the limited number of organisational scholars working in this area; 2 the dominance of alternative research paradigms that dismiss case study research; 3 difficulties in securing funding; 4 the lack of publication outlets; and 5 the absence of a clear understanding of the relationship of case study research to the development of theory, and the testing of theory using randomised control trials and other methods.

Still, the emergence of several strong research groups in the UK, Canada and the USA, and growing numbers of high-quality publications offer hope. What is missing in quality improvement research is a clear understanding of how case study research could contribute to the broader research enterprise, enriching the qualitative understanding of the complex processes of improving healthcare delivery. Comparative case study research provides useful methods for identifying the factors facilitating and impeding improvement.

Although valuable in their own right, such methods also offer the opportunity to enrich more traditional approaches to assessing interventions, helping to explain why some interventions are unsuccessful, or why they seem to work effectively in some contexts but not in others. Efforts to improve patient safety and quality of care need to take into account the complexities of the systems in which these improvements are being introduced.

Case study methods provide a robust means to guide implementation of effective practices. Competing interests: None. Provenance and peer review: Not commissioned; externally peer reviewed. National Center for Biotechnology Information , U.