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Case Study – Methods, Examples and Guide

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A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

• Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
• Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
• Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
• Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
• Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
• Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
• Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

• The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
• The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
• The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
• The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
• The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

• Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
• Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
• Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
• Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

• In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
• Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
• Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
• Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
• Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
• Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

• Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
• Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
• Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
• Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
• Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
• Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Writing a Case Study

What is a case study?

A Case study is: 

• An in-depth research design that primarily uses a qualitative methodology but sometimes​​ includes quantitative methodology.
• Used to examine an identifiable problem confirmed through research.
• Used to investigate an individual, group of people, organization, or event.
• Used to mostly answer "how" and "why" questions.

What are the different types of case studies?

Note: These are the primary case studies. As you continue to research and learn

about case studies you will begin to find a robust list of different types. 

Who are your case study participants?

What is triangulation ? 

Validity and credibility are an essential part of the case study. Therefore, the researcher should include triangulation to ensure trustworthiness while accurately reflecting what the researcher seeks to investigate.

How to write a Case Study?

When developing a case study, there are different ways you could present the information, but remember to include the five parts for your case study.

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The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews

Research question

• Conceptual framework
• Conceptual vs. theoretical framework

Data collection

• Qualitative research methods
• Focus groups
• Observational research

What is a case study?

Applications for case study research, what is a good case study, process of case study design, benefits and limitations of case studies.

• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Case studies

Case studies are essential to qualitative research , offering a lens through which researchers can investigate complex phenomena within their real-life contexts. This chapter explores the concept, purpose, applications, examples, and types of case studies and provides guidance on how to conduct case study research effectively.

Whereas quantitative methods look at phenomena at scale, case study research looks at a concept or phenomenon in considerable detail. While analyzing a single case can help understand one perspective regarding the object of research inquiry, analyzing multiple cases can help obtain a more holistic sense of the topic or issue. Let's provide a basic definition of a case study, then explore its characteristics and role in the qualitative research process.

Definition of a case study

A case study in qualitative research is a strategy of inquiry that involves an in-depth investigation of a phenomenon within its real-world context. It provides researchers with the opportunity to acquire an in-depth understanding of intricate details that might not be as apparent or accessible through other methods of research. The specific case or cases being studied can be a single person, group, or organization – demarcating what constitutes a relevant case worth studying depends on the researcher and their research question .

Among qualitative research methods , a case study relies on multiple sources of evidence, such as documents, artifacts, interviews , or observations , to present a complete and nuanced understanding of the phenomenon under investigation. The objective is to illuminate the readers' understanding of the phenomenon beyond its abstract statistical or theoretical explanations.

Characteristics of case studies

Case studies typically possess a number of distinct characteristics that set them apart from other research methods. These characteristics include a focus on holistic description and explanation, flexibility in the design and data collection methods, reliance on multiple sources of evidence, and emphasis on the context in which the phenomenon occurs.

Furthermore, case studies can often involve a longitudinal examination of the case, meaning they study the case over a period of time. These characteristics allow case studies to yield comprehensive, in-depth, and richly contextualized insights about the phenomenon of interest.

The role of case studies in research

Case studies hold a unique position in the broader landscape of research methods aimed at theory development. They are instrumental when the primary research interest is to gain an intensive, detailed understanding of a phenomenon in its real-life context.

In addition, case studies can serve different purposes within research - they can be used for exploratory, descriptive, or explanatory purposes, depending on the research question and objectives. This flexibility and depth make case studies a valuable tool in the toolkit of qualitative researchers.

Remember, a well-conducted case study can offer a rich, insightful contribution to both academic and practical knowledge through theory development or theory verification, thus enhancing our understanding of complex phenomena in their real-world contexts.

What is the purpose of a case study?

Case study research aims for a more comprehensive understanding of phenomena, requiring various research methods to gather information for qualitative analysis . Ultimately, a case study can allow the researcher to gain insight into a particular object of inquiry and develop a theoretical framework relevant to the research inquiry.

Why use case studies in qualitative research?

Using case studies as a research strategy depends mainly on the nature of the research question and the researcher's access to the data.

Conducting case study research provides a level of detail and contextual richness that other research methods might not offer. They are beneficial when there's a need to understand complex social phenomena within their natural contexts.

The explanatory, exploratory, and descriptive roles of case studies

Case studies can take on various roles depending on the research objectives. They can be exploratory when the research aims to discover new phenomena or define new research questions; they are descriptive when the objective is to depict a phenomenon within its context in a detailed manner; and they can be explanatory if the goal is to understand specific relationships within the studied context. Thus, the versatility of case studies allows researchers to approach their topic from different angles, offering multiple ways to uncover and interpret the data .

The impact of case studies on knowledge development

Case studies play a significant role in knowledge development across various disciplines. Analysis of cases provides an avenue for researchers to explore phenomena within their context based on the collected data.

This can result in the production of rich, practical insights that can be instrumental in both theory-building and practice. Case studies allow researchers to delve into the intricacies and complexities of real-life situations, uncovering insights that might otherwise remain hidden.

Types of case studies

In qualitative research , a case study is not a one-size-fits-all approach. Depending on the nature of the research question and the specific objectives of the study, researchers might choose to use different types of case studies. These types differ in their focus, methodology, and the level of detail they provide about the phenomenon under investigation.

Understanding these types is crucial for selecting the most appropriate approach for your research project and effectively achieving your research goals. Let's briefly look at the main types of case studies.

Exploratory case studies

Exploratory case studies are typically conducted to develop a theory or framework around an understudied phenomenon. They can also serve as a precursor to a larger-scale research project. Exploratory case studies are useful when a researcher wants to identify the key issues or questions which can spur more extensive study or be used to develop propositions for further research. These case studies are characterized by flexibility, allowing researchers to explore various aspects of a phenomenon as they emerge, which can also form the foundation for subsequent studies.

Descriptive case studies

Descriptive case studies aim to provide a complete and accurate representation of a phenomenon or event within its context. These case studies are often based on an established theoretical framework, which guides how data is collected and analyzed. The researcher is concerned with describing the phenomenon in detail, as it occurs naturally, without trying to influence or manipulate it.

Explanatory case studies

Explanatory case studies are focused on explanation - they seek to clarify how or why certain phenomena occur. Often used in complex, real-life situations, they can be particularly valuable in clarifying causal relationships among concepts and understanding the interplay between different factors within a specific context.

Intrinsic, instrumental, and collective case studies

These three categories of case studies focus on the nature and purpose of the study. An intrinsic case study is conducted when a researcher has an inherent interest in the case itself. Instrumental case studies are employed when the case is used to provide insight into a particular issue or phenomenon. A collective case study, on the other hand, involves studying multiple cases simultaneously to investigate some general phenomena.

Each type of case study serves a different purpose and has its own strengths and challenges. The selection of the type should be guided by the research question and objectives, as well as the context and constraints of the research.

The flexibility, depth, and contextual richness offered by case studies make this approach an excellent research method for various fields of study. They enable researchers to investigate real-world phenomena within their specific contexts, capturing nuances that other research methods might miss. Across numerous fields, case studies provide valuable insights into complex issues.

Critical information systems research

Case studies provide a detailed understanding of the role and impact of information systems in different contexts. They offer a platform to explore how information systems are designed, implemented, and used and how they interact with various social, economic, and political factors. Case studies in this field often focus on examining the intricate relationship between technology, organizational processes, and user behavior, helping to uncover insights that can inform better system design and implementation.

Health research

Health research is another field where case studies are highly valuable. They offer a way to explore patient experiences, healthcare delivery processes, and the impact of various interventions in a real-world context.

Case studies can provide a deep understanding of a patient's journey, giving insights into the intricacies of disease progression, treatment effects, and the psychosocial aspects of health and illness.

Asthma research studies

Specifically within medical research, studies on asthma often employ case studies to explore the individual and environmental factors that influence asthma development, management, and outcomes. A case study can provide rich, detailed data about individual patients' experiences, from the triggers and symptoms they experience to the effectiveness of various management strategies. This can be crucial for developing patient-centered asthma care approaches.

Other fields

Apart from the fields mentioned, case studies are also extensively used in business and management research, education research, and political sciences, among many others. They provide an opportunity to delve into the intricacies of real-world situations, allowing for a comprehensive understanding of various phenomena.

Case studies, with their depth and contextual focus, offer unique insights across these varied fields. They allow researchers to illuminate the complexities of real-life situations, contributing to both theory and practice.

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Understanding the key elements of case study design is crucial for conducting rigorous and impactful case study research. A well-structured design guides the researcher through the process, ensuring that the study is methodologically sound and its findings are reliable and valid. The main elements of case study design include the research question , propositions, units of analysis, and the logic linking the data to the propositions.

The research question is the foundation of any research study. A good research question guides the direction of the study and informs the selection of the case, the methods of collecting data, and the analysis techniques. A well-formulated research question in case study research is typically clear, focused, and complex enough to merit further detailed examination of the relevant case(s).

Propositions

Propositions, though not necessary in every case study, provide a direction by stating what we might expect to find in the data collected. They guide how data is collected and analyzed by helping researchers focus on specific aspects of the case. They are particularly important in explanatory case studies, which seek to understand the relationships among concepts within the studied phenomenon.

Units of analysis

The unit of analysis refers to the case, or the main entity or entities that are being analyzed in the study. In case study research, the unit of analysis can be an individual, a group, an organization, a decision, an event, or even a time period. It's crucial to clearly define the unit of analysis, as it shapes the qualitative data analysis process by allowing the researcher to analyze a particular case and synthesize analysis across multiple case studies to draw conclusions.

Argumentation

This refers to the inferential model that allows researchers to draw conclusions from the data. The researcher needs to ensure that there is a clear link between the data, the propositions (if any), and the conclusions drawn. This argumentation is what enables the researcher to make valid and credible inferences about the phenomenon under study.

Understanding and carefully considering these elements in the design phase of a case study can significantly enhance the quality of the research. It can help ensure that the study is methodologically sound and its findings contribute meaningful insights about the case.

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Conducting a case study involves several steps, from defining the research question and selecting the case to collecting and analyzing data . This section outlines these key stages, providing a practical guide on how to conduct case study research.

Defining the research question

The first step in case study research is defining a clear, focused research question. This question should guide the entire research process, from case selection to analysis. It's crucial to ensure that the research question is suitable for a case study approach. Typically, such questions are exploratory or descriptive in nature and focus on understanding a phenomenon within its real-life context.

Selecting and defining the case

The selection of the case should be based on the research question and the objectives of the study. It involves choosing a unique example or a set of examples that provide rich, in-depth data about the phenomenon under investigation. After selecting the case, it's crucial to define it clearly, setting the boundaries of the case, including the time period and the specific context.

Previous research can help guide the case study design. When considering a case study, an example of a case could be taken from previous case study research and used to define cases in a new research inquiry. Considering recently published examples can help understand how to select and define cases effectively.

Developing a detailed case study protocol

A case study protocol outlines the procedures and general rules to be followed during the case study. This includes the data collection methods to be used, the sources of data, and the procedures for analysis. Having a detailed case study protocol ensures consistency and reliability in the study.

The protocol should also consider how to work with the people involved in the research context to grant the research team access to collecting data. As mentioned in previous sections of this guide, establishing rapport is an essential component of qualitative research as it shapes the overall potential for collecting and analyzing data.

Collecting data

Gathering data in case study research often involves multiple sources of evidence, including documents, archival records, interviews, observations, and physical artifacts. This allows for a comprehensive understanding of the case. The process for gathering data should be systematic and carefully documented to ensure the reliability and validity of the study.

Analyzing and interpreting data

The next step is analyzing the data. This involves organizing the data , categorizing it into themes or patterns , and interpreting these patterns to answer the research question. The analysis might also involve comparing the findings with prior research or theoretical propositions.

Writing the case study report

The final step is writing the case study report . This should provide a detailed description of the case, the data, the analysis process, and the findings. The report should be clear, organized, and carefully written to ensure that the reader can understand the case and the conclusions drawn from it.

Each of these steps is crucial in ensuring that the case study research is rigorous, reliable, and provides valuable insights about the case.

The type, depth, and quality of data in your study can significantly influence the validity and utility of the study. In case study research, data is usually collected from multiple sources to provide a comprehensive and nuanced understanding of the case. This section will outline the various methods of collecting data used in case study research and discuss considerations for ensuring the quality of the data.

Interviews are a common method of gathering data in case study research. They can provide rich, in-depth data about the perspectives, experiences, and interpretations of the individuals involved in the case. Interviews can be structured , semi-structured , or unstructured , depending on the research question and the degree of flexibility needed.

Observations

Observations involve the researcher observing the case in its natural setting, providing first-hand information about the case and its context. Observations can provide data that might not be revealed in interviews or documents, such as non-verbal cues or contextual information.

Documents and artifacts

Documents and archival records provide a valuable source of data in case study research. They can include reports, letters, memos, meeting minutes, email correspondence, and various public and private documents related to the case.

These records can provide historical context, corroborate evidence from other sources, and offer insights into the case that might not be apparent from interviews or observations.

Physical artifacts refer to any physical evidence related to the case, such as tools, products, or physical environments. These artifacts can provide tangible insights into the case, complementing the data gathered from other sources.

Ensuring the quality of data collection

Determining the quality of data in case study research requires careful planning and execution. It's crucial to ensure that the data is reliable, accurate, and relevant to the research question. This involves selecting appropriate methods of collecting data, properly training interviewers or observers, and systematically recording and storing the data. It also includes considering ethical issues related to collecting and handling data, such as obtaining informed consent and ensuring the privacy and confidentiality of the participants.

Data analysis

Analyzing case study research involves making sense of the rich, detailed data to answer the research question. This process can be challenging due to the volume and complexity of case study data. However, a systematic and rigorous approach to analysis can ensure that the findings are credible and meaningful. This section outlines the main steps and considerations in analyzing data in case study research.

Organizing the data

The first step in the analysis is organizing the data. This involves sorting the data into manageable sections, often according to the data source or the theme. This step can also involve transcribing interviews, digitizing physical artifacts, or organizing observational data.

Categorizing and coding the data

Once the data is organized, the next step is to categorize or code the data. This involves identifying common themes, patterns, or concepts in the data and assigning codes to relevant data segments. Coding can be done manually or with the help of software tools, and in either case, qualitative analysis software can greatly facilitate the entire coding process. Coding helps to reduce the data to a set of themes or categories that can be more easily analyzed.

Identifying patterns and themes

After coding the data, the researcher looks for patterns or themes in the coded data. This involves comparing and contrasting the codes and looking for relationships or patterns among them. The identified patterns and themes should help answer the research question.

Interpreting the data

Once patterns and themes have been identified, the next step is to interpret these findings. This involves explaining what the patterns or themes mean in the context of the research question and the case. This interpretation should be grounded in the data, but it can also involve drawing on theoretical concepts or prior research.

Verification of the data

The last step in the analysis is verification. This involves checking the accuracy and consistency of the analysis process and confirming that the findings are supported by the data. This can involve re-checking the original data, checking the consistency of codes, or seeking feedback from research participants or peers.

Like any research method , case study research has its strengths and limitations. Researchers must be aware of these, as they can influence the design, conduct, and interpretation of the study.

Understanding the strengths and limitations of case study research can also guide researchers in deciding whether this approach is suitable for their research question . This section outlines some of the key strengths and limitations of case study research.

Benefits include the following:

• Rich, detailed data: One of the main strengths of case study research is that it can generate rich, detailed data about the case. This can provide a deep understanding of the case and its context, which can be valuable in exploring complex phenomena.
• Flexibility: Case study research is flexible in terms of design , data collection , and analysis . A sufficient degree of flexibility allows the researcher to adapt the study according to the case and the emerging findings.
• Real-world context: Case study research involves studying the case in its real-world context, which can provide valuable insights into the interplay between the case and its context.
• Multiple sources of evidence: Case study research often involves collecting data from multiple sources , which can enhance the robustness and validity of the findings.

On the other hand, researchers should consider the following limitations:

• Generalizability: A common criticism of case study research is that its findings might not be generalizable to other cases due to the specificity and uniqueness of each case.
• Time and resource intensive: Case study research can be time and resource intensive due to the depth of the investigation and the amount of collected data.
• Complexity of analysis: The rich, detailed data generated in case study research can make analyzing the data challenging.
• Subjectivity: Given the nature of case study research, there may be a higher degree of subjectivity in interpreting the data , so researchers need to reflect on this and transparently convey to audiences how the research was conducted.

Being aware of these strengths and limitations can help researchers design and conduct case study research effectively and interpret and report the findings appropriately.

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• Open access
• Published: 27 June 2011

The case study approach

• Sarah Crowe 1 ,
• Kathrin Cresswell 2 ,
• Ann Robertson 2 ,
• Guro Huby 3 ,
• Anthony Avery 1 &
• Aziz Sheikh 2  

BMC Medical Research Methodology volume  11 , Article number:  100 ( 2011 ) Cite this article

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The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

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Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables 1 , 2 , 3 and 4 ) and those of others to illustrate our discussion[ 3 – 7 ].

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables 2 , 3 and 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 – 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables 2 and 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 – 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8 )[ 8 , 18 – 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table 9 )[ 8 ].

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

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Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

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AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

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Case Studies

Case studies are a popular research method in business area. Case studies aim to analyze specific issues within the boundaries of a specific environment, situation or organization.

According to its design, case studies in business research can be divided into three categories: explanatory, descriptive and exploratory.

Explanatory case studies aim to answer ‘how’ or ’why’ questions with little control on behalf of researcher over occurrence of events. This type of case studies focus on phenomena within the contexts of real-life situations. Example: “An investigation into the reasons of the global financial and economic crisis of 2008 – 2010.”

Descriptive case studies aim to analyze the sequence of interpersonal events after a certain amount of time has passed. Studies in business research belonging to this category usually describe culture or sub-culture, and they attempt to discover the key phenomena. Example: “Impact of increasing levels of multiculturalism on marketing practices: A case study of McDonald’s Indonesia.”

Exploratory case studies aim to find answers to the questions of ‘what’ or ‘who’. Exploratory case study data collection method is often accompanied by additional data collection method(s) such as interviews, questionnaires, experiments etc. Example: “A study into differences of leadership practices between private and public sector organizations in Atlanta, USA.”

Advantages of case study method include data collection and analysis within the context of phenomenon, integration of qualitative and quantitative data in data analysis, and the ability to capture complexities of real-life situations so that the phenomenon can be studied in greater levels of depth. Case studies do have certain disadvantages that may include lack of rigor, challenges associated with data analysis and very little basis for generalizations of findings and conclusions.

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Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating, and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyse the case.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

Prevent plagiarism, run a free check.

Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

However, you can also choose a more common or representative case to exemplify a particular category, experience, or phenomenon.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data .

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

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• Published: 26 April 2024

Clinician and staff experiences with frustrated patients during an electronic health record transition: a qualitative case study

• Sherry L. Ball 1 ,
• Bo Kim 2 , 3 ,
• Sarah L. Cutrona 4 , 5 ,
• Brianne K. Molloy-Paolillo 4 ,
• Ellen Ahlness 6 ,
• Megan Moldestad 6 ,
• George Sayre 6 , 7 &
• Seppo T. Rinne 2 , 8  

BMC Health Services Research volume  24 , Article number:  535 ( 2024 ) Cite this article

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Metrics details

Electronic health record (EHR) transitions are known to be highly disruptive, can drastically impact clinician and staff experiences, and may influence patients’ experiences using the electronic patient portal. Clinicians and staff can gain insights into patient experiences and be influenced by what they see and hear from patients. Through the lens of an emergency preparedness framework, we examined clinician and staff reactions to and perceptions of their patients’ experiences with the portal during an EHR transition at the Department of Veterans Affairs (VA).

This qualitative case study was situated within a larger multi-methods evaluation of the EHR transition. We conducted a total of 122 interviews with 30 clinicians and staff across disciplines at the initial VA EHR transition site before, immediately after, and up to 12 months after go-live (September 2020-November 2021). Interview transcripts were coded using a priori and emergent codes. The coded text segments relevant to patient experience and clinician interactions with patients were extracted and analyzed to identify themes. For each theme, recommendations were defined based on each stage of an emergency preparedness framework (mitigate, prepare, respond, recover).

In post-go-live interviews participants expressed concerns about the reliability of communicating with their patients via secure messaging within the new EHR portal. Participants felt ill-equipped to field patients’ questions and frustrations navigating the new portal. Participants learned that patients experienced difficulties learning to use and accessing the portal; when unsuccessful, some had difficulties obtaining medication refills via the portal and used the call center as an alternative. However, long telephone wait times provoked patients to walk into the clinic for care, often frustrated and without an appointment. Patients needing increased in-person attention heightened participants’ daily workload and their concern for patients’ well-being. Recommendations for each theme fit within a stage of the emergency preparedness framework.

Conclusions

Application of an emergency preparedness framework to EHR transitions could help address the concerns raised by the participants, (1) mitigating disruptions by identifying at-risk patients before the transition, (2) preparing end-users by disseminating patient-centered informational resources, (3) responding by building capacity for disrupted services, and (4) recovering by monitoring integrity of the new portal function.

Peer Review reports

Electronic health record (EHR) transitions present significant challenges for healthcare clinicians and staff. These transitions require adjustments in care delivery and may threaten care quality and value. It is critical that healthcare organizations undergoing these changes learn from others who have undergone similar transitions [ 1 , 2 ]. However, the current literature lacks adequate guidance on navigating EHR transitions, especially as they relate to how clinicians and staff interact with patients [ 3 ].

Embedded within EHRs, patient portals facilitate complete, accurate, timely, and unambiguous exchange of information between patients and healthcare workers [ 4 , 5 ]. These portals have become indispensable for completing routine out-of-office-visit tasks, such as medication refills, communicating laboratory results, and addressing patient questions [ 6 ]. In 2003, the VA launched their version of a patient portal, myHealtheVet [ 7 ] and by 2017 69% of Veterans enrolled in healthcare at the VA had registered to access the patient portal [ 8 ]. Similar to other electronic portals, this system allows Veterans to review test results, see upcoming appointments, and communicate privately and securely with their healthcare providers.

EHR transitions can introduce disruptions to patient portal communication that may compromise portal reliability, impacting patient and clinician satisfaction, patients’ active involvement in self-management, and ultimately health outcomes [ 9 ]. During an EHR transition, patients can expect reductions in access to care even when clinician capacity and IT support are increased. Patients will likely need for more assistance navigating the patient portal including and using the portal to communicate with their providers [ 10 ]. Staff must be prepared and understand how the changes in the EHR will affect patients and safeguards must be in place to monitor systems for potential risks to patient safety. Building the capacity to respond to emerging system glitches and identified changes must be included in any transition plan. Although portal disruptions are likely to occur when a new EHR is implemented, we know little about how these disruptions impact healthcare workers’ interactions and care delivery to patients [ 11 , 12 ].

Due to an urgency to raise awareness and promote resolution of these patient portal issues,, we utilized existing data from the first EHR transition site for the Department of Veterans Affairs (VA)’s enterprise-wide transition. We focused on end users’ responses to the question “How Veterans were affected by the transition?”. We used qualitative methods to begin to understand how provider and patient interactions were affected during and by the EHR transition. We explored the impact of the EHR transition on patients through healthcare workers’ vicarious and direct experiences with patients. Due to the high level of disruption in care delivery we draw on insights from an emergency preparedness framework [ 13 ] to generate a set of recommendations to improve healthcare workers’ experiences during EHR transitions. The emergency preparedness framework includes 4 phases of an iterative cycle that include: (1) building capacity to mitigate issues, (2) preparing for the inevitable onset of issues, (3) responding to issues as they emerge, and (4) strategies to recover from any damage incurred.

In early 2020, the VA embarked on an EHR transition from a homegrown, legacy EHR system, developed by VA clinicians and used since the 1990s, to a new commercial system by the Oracle-Cerner Corporation. The primary objectives of this transition were to standardize care and improve interoperability between VA Medical Centers nationwide and the Department of Defense (DoD). Spanning over a decade, this transition plan is scheduled to roll out to all VA medical centers and outpatient clinics.

In this manuscript, we present data from the Mann-Grandstaff VA Medical Center in Spokane, WA, VA’s first EHR transition site. The study uses qualitative methods with clinician and staff interviews as part of a larger multi-method evaluation of the EHR transition. Our overarching goal is to identify and share recommendations to improve VA’s EHR transition efforts; rather than be guided by a theoretical framework our study design including the interview guides [ 14 , 15 ] were based primarily on what was being experienced. An experienced team of ten qualitative methodologists and analysts conducted the study.

This evaluation was designated as non-research/quality improvement work by the VA Bedford Healthcare System Institutional Review Board deeming it exempt from needing an informed consent. Study materials, including interview guides with verbal consent procedures, were reviewed and approved by labor unions and by the VA Bedford Healthcare System Institutional Review Board; all methods were carried out in accordance with local and national VA guidelines and regulations.

Interview guides and an outline of the data collection plans were reviewed and approved by relevant national unions before beginning recruitment.

Recruitment

Recruitment began in July 2020, before the first site implemented the new EHR. Prior to collecting data, we met with site leadership to get buy-in and support for the study, understand local context, determine how the site was approaching the transition, and to obtain the names of clinicians and staff for potential interviews. All potential participants were invited by email to participate in a one-hour voluntary interview conducted on Microsoft Teams® about their experiences with this transition; we used snowball sampling during interviews to expand the pool of interviewees. Verbal permission for audio recording of interviews was obtained immediately prior to the interview. Interview participants were informed that they could skip any questions, pause or stop the recording, and stop the interview at any time and were invited to ask questions before beginning the interview.

Most participants were interviewed at multiple timepoints; these included pre-implementation interviews, brief check-ins, and post-implementation interviews (Table  1 ). At the end of the pre-implementation interview, participants were invited to participate in 3–4 additional, shorter (15–20 min), check-in interviews where information about any changes in the transition process, context, or experience could be discussed. Most initial interviewees, in addition to three new participants, participated in post-implementation interviews (35–60 min; approximately 2–3 months and 10–12 months after the implementation) to reflect on the entire transition process.

Data collection

Experienced qualitative interviewers included PhD trained qualitative methodologist and masters level qualitative analysts (JB, SB, AC, EK, MM, GS) conducted individual interviews with clinicians and staff, aligning to a semi-structured interview guide with follow-up probes using the participant’s words to elicit rich responses grounded in the data [ 16 ]. The guide was designed to inform ongoing efforts to improve the rollout of the new EHR. Six main categories were covered in our interview guides, including (1) attitudes toward the new software, (2) information communicated about the transition, (3) training and education, (4) resources, (5) prior experience with EHRs, and (6) prior experiences with EHR transitions. After piloting the interview guide with a clinician, initial interviews were completed between September and October 2020 and averaged  ∼  45 min in duration. Two-month and one-year post-implementation interview guides included an additional question, “Has the Cerner transition affected Vets?”; data presented here largely draw from responses to this question. Check-ins (October 2020– December 2020) took  ∼  15 min; two-month post-implementation interviews (December 2020– January 2021) and one-year post-implementation interviews (October 2020 - November 2021) took  ∼  45 min. Audio recordings of all interviews were professionally transcribed. To ensure consistency and relationship building, participants were scheduled with the same interviewer for the initial and subsequent interviews whenever feasible (i.e., check-ins and post-implementation interviews). Immediately following each interview, interviewers completed a debrief form where highlights and general reflections were noted.

Throughout the data collection process, interviewers met weekly with the entire qualitative team and the project principal investigators to discuss the recruitment process, interview guide development, and reflections on data collection. To provide timely feedback to leadership within the VA, a matrix analysis [ 17 ] was conducted concurrently with data collection using the following domains: training, roles, barriers, and facilitators. Based on these domains, the team developed categories and subcategories, which formed the foundation of an extensive codebook.

Data analysis

All interviewers also coded the data. We used inductive and deductive content analysis [ 18 ]. Interview transcripts were coded in ATLAS.ti qualitative data analysis software (version 9). A priori codes and categories (based on the overall larger project aims and interview guide questions) and emergent codes and categories were developed to capture concepts that did not fit existing codes or categories [ 18 ]. Codes related to patient experience and clinician interactions with patients were extracted and analyzed using qualitative content analysis to identify themes [ 18 ]. Themes were organized according to their fit within the discrete stages of an emergency preparedness framework to generate recommendations for future rollout. In total, we examined data from 111 interviews with 24 VA clinicians and staff (excluding the initial 11 stakeholder meetings (from the 122 total interviews) that were primarily for stakeholder engagement). We focused on participants’ responses related to their experiences interacting with patients during the EHR transition.

Exemplar quotes primarily came from participants’ responses to the question, “Has the Cerner transition affected Vets?” and addressed issues stemming from use of the patient portal. This included both clinicians’ direct experiences with the portal and indirect experiences when they heard from patients about disruptions when using the portal. We identified four themes related to clinicians’ and staff members’ reported experiences: (1) stress associated with the unreliability of routine portal functions and inaccurate migrated information; (2) concern about patients’ ability to learn to use a new portal (especially older patients and special populations); (3) frustration with apparent inadequate dissemination of patient informational materials along with their own lack of time and resources to educate patients on use of the new portal; and (4) burden of additional tasks on top of their daily workload when patients needed increased in-person attention due to issues with the portal.

Stress associated with the unreliability of routine portal functions and inaccurate migrated information

One participant described the portal changes as, “It’s our biggest stress, it’s the patients’ biggest stress… the vets are definitely frustrated; the clinicians are; so I would hope that would mean that behind the scenes somebody is working on it” (P5, check-in).

Participants expressed significant frustration when they encountered veterans who were suddenly unable to communicate with them using routine secure messaging. These experiences left them wondering whether messages sent to patients were received.

Those that use our secure messaging, which has now changed to My VA Health, or whatever it’s called, [have] difficulty navigating that. Some are able to get in and send the message. When we reply to them, they may or may not get the reply. Which I’ve actually asked one of our patients, ‘Did you get the reply that we took care of this?’ And he was like, ‘No, I did not (P11, 2-months post)

Participants learned that some patients were unable to send secure messages to their care team because the portal contained inaccurate or outdated appointment and primary site information.

I’ve heard people say that the appointments aren’t accurate in there… veterans who have said, ‘yeah, it shows I’m registered,’ and when they go into the new messaging system, it says they are part of a VA that they haven’t gone to in years, and that’s the only area they can message to, they can’t message to the [site] VA, even though that’s where they’ve actively being seen for a while now. (P20, 2-months post)

After the EHR transition, participants noted that obtaining medications through the portal, which was once a routine task, became unreliable. They expressed concern around patients’ ability to obtain their medications through the portal, primarily due to challenges with portal usability and incomplete migration of medication lists from the former to the new EHR.

I think it’s been negative, unfortunately. I try to stay optimistic when I talk to [patients], but they all seem to be all having continued difficulty with their medications, trying to properly reorder and get medications seems to still be a real hassle for them. (P17, one-year post) …the medications, their med list just didn’t transfer over into that list [preventing their ability to refill their medications]. (P13, 2-months post)

Concern about patients’ ability to learn to use a new portal

Clinicians and staff expressed concerns around veterans’ ability to access, learn, and navigate a new portal system. Clinicians noted that even veterans who were adept at using the prior electronic portal or other technologies also faced difficulties using the new portal.

They can’t figure out [the new portal], 99% of them that used to use our [old] portal, the electronic secure messaging or emailing between the team, they just can’t use [the new one]. It’s not functioning. (P13, one-year post) Apparently, there’s a link they have to click on to make the new format work for them, and that’s been confusing for them. But I still am having a lot of them tell me, I had somebody recently, who’s very tech savvy, and he couldn’t figure it out, just how to message us. I know they’re still really struggling with that. (P5, 2-months post) And it does seem like the My Vet [my VA Health, new portal], that used to be MyHealtheVet [prior portal], logging on and getting onto that still remains really challenging for a large number of veterans. Like they’re still just unable to do it. So, I do think that, I mean I want to say that there’s positive things, but really, I struggle (P17, one-year post)

Participants recognized difficulties with the new system and expressed empathy for the veterans struggling to access the portal.

I think that a lot of us, individually, that work here, I think we have more compassion for our veterans, because they’re coming in and they can’t even get onto their portal website. (P24, one-year post)

Participants acknowledged that learning a new system may be especially difficult for older veterans or those with less technology experience.

But, you know, veterans, the general population of them are older, in general. So, their technologic skills are limited, and they got used to a system and now they have to change to a new one. (P13, 2-months post) So, for our more elderly veterans who barely turn on the computer, they’re not getting to this new portal. (P8, check in) And you know, I do keep in mind that this is a group of people who aren’t always technologically advanced, so small things, when it’s not normal to them, stymie them.(P13, one-year post)

Concerns were heightened for veterans who were more dependent on the portal as a key element in their care due to specific challenges. One participant pointed out that there may be populations of patients with special circumstances who depend more heavily on the prior portal, MyHealtheVet.

I have veterans from [specific region], that’s the way they communicate. Hearing impaired people can’t hear on the phone, the robocall thing, it doesn’t work, so they use MyHealtheVet. Well, if that goes away, how is that being communicated to the veteran? Ok? (P18, Check-in)

Frustration with inadequate dissemination of information to veterans about EHR transition and use of new portal

Participants were concerned about poor information dissemination to patients about how to access the new portal. During medical encounters, participants often heard from patients about their frustrations accessing the new portal. Participants noted that they could only give their patients a phone number to call for help using the new system but otherwise lacked the knowledge and the time to help them resolve new portal issues. Some clinicians specifically mentioned feeling ill-equipped to handle their patients’ needs for assistance with the new portal. These experiences exacerbated clinician stress during the transition.

Our veterans were using the MyHealtheVet messaging portal, and when our new system went up, it transitioned to My VA Health, but that wasn’t really communicated to the veterans very well. So, what happened was they would go into their MyHealtheVet like they had been doing for all of these years, to go in and request their medications, and when they pulled it up it’d show that they were assigned to a clinician in [a different state], that they have no active medications. Everything was just messed up. And they didn’t know why because there was no alert or notification that things would be changing. (P8, check in) I field all-day frustration from the veterans. And I love my job, I’m not leaving here even as frustrated as I am, because I’m here for them, not to, I’m here to serve the veterans and I have to advocate for them, and I know it will get better, it can’t stay like this. But I constantly field their frustrations.… So, I give them the 1-800 number to a Cerner help desk that helps with that, and I’ve had multiple [instances of] feedback that it didn’t help. (P13, one-year post) And [the patients are] frequently asking me things about their medication [within the portal], when, you know, I can’t help them with that. So, I have to send them back up to the front desk to try to figure out their medications. (P17, one-year post)

Veteran frustration and the burden of additional tasks due to issues with the portal

Clinicians reported that veterans expressed frustration with alternatives to the portal, including long call center wait times. Some veterans chose to walk into the clinic without an appointment rather than wait on the phone. Clinicians noted an increase in walk-ins by frustrated veterans, which placed added workload on clinics that were not staffed to handle the increase in walk-ins.

It’s been kind of clunky also with trying to get that [new portal] transitioned. And then that’s created more walk-ins here, because one, the vets get frustrated with the phone part of it, and then MyHealtheVet (prior portal) not [working], so they end up walking [into the clinic without an appointment]. (P19, check-in) In terms of messages, they can’t necessarily find the clinician they want to message. We had a veteran who came in recently who wanted to talk to their Rheumatologist, and it’s like, yeah, I typed in their name, and nothing came up. So, they have to try calling or coming in. (P20, 2-months post)

In summary, participants described the new patient portal as a source of stress for both themselves and their patients.

In addition to their own direct experience using a new EHR to communicate with their patients, clinicians and staff can be affected by perceptions of their patients’ experiences during an EHR transition [ 19 ]. At this first VA site to transition to the new EHR, clinicians and staff shared their concerns about their patients’ experiences using the portal. They were particularly troubled by unreliability of the secure messaging system and challenges patients faced learning to use the new system without proper instruction. Moreover, clinicians were alarmed to hear about patients having to make in-person visits– especially unplanned (i.e., walk in) ones– due to challenges with the new portal. Each of these issues needs to be addressed to ensure veteran satisfaction. However, the only solution participants could offer to frustrated patients was the telephone number to the help desk, leaving them with no clear knowledge of a solution strategy or a timeline for resolution of the issues.

We propose applying emergency preparedness actions to future EHR rollouts: mitigate, prepare, respond, and recover (Fig.  1 ) [ 13 ]. By applying these actions, patient portal disruptions may be alleviated and patients’ communication with their clinicians and access to care can be maintained. For example, issues stemming from a disruption in the portal may be mitigated by first identifying and understanding which patients typically use the portal and how they use it. Sites can use this information to prepare for the transition by disseminating instructional materials to staff and patients on how to access the new portal, targeting the most common and critical portal uses. Sites can respond to any expected and emerging portal disruptions by increasing access to alternative mechanisms for tasks disrupted by and typically completed within the portal. After the transition, recovery can begin by testing and demonstrating the accuracy and reliability of functions in the new portal. These actions directly address reported clinician concerns and can help maintain patient-clinician communication, and access to care.

The emergency preparedness framework was applied. This framework includes 4 actions: (1) mitigate, (2) prepare, (3) respond, and (4) recover. These actions can be repeated. Recommendations for how each action (1–4) can be applied to a portal transition are included in each blue quadrant of the circle

Sites could mitigate issues by first understanding which patients will be most affected by the transition, such as those who rely heavily on secure messaging. Reliable use of secure messaging within the VA facilitates positive patient-clinician relationships by providing a mechanism for efficient between-visit communication [ 20 , 21 , 22 , 23 ]. During the EHR transition, clinicians and staff became concerned about the well-being of patients from whom they weren’t receiving messages and those who depended on the portal to complete certain tasks. Since secure messaging is often initiated by patients to clinicians [ 23 ], clinicians will likely be unaware that messages are being missed. Understanding how and which patients currently use the portal and anticipating potential portal needs is a first step toward mitigating potential issues.

Despite efforts to inform Veterans of the EHR transition and patient portal [ 24 ] including information sent to a Veteran by email, direct mail, postings on VA websites, and a town hall, our findings agree with those of Fix and colleagues [ 10 ] and suggest that many Veterans were unprepared for the transition. Our findings suggest that end users heard that more is needed to improve the dissemination of knowledge about the transition and how to navigate the new patient portal to both VA employees and the patients they serve.

Preparations for the transition should prioritize providing VA clinicians and staff with updated information and resources on how to access and use the new portal [ 25 ]. VA clinicians deliver quality care to veterans and many VA employees are proud to serve the nation’s veterans and willing to go the extra mile to support their patients’ needs [ 26 ]. In this study, participants expressed feeling unprepared to assist or even respond to their patients’ questions and concerns about using the new portal. This unpreparedness contributed to increased clinician and staff stress, as they felt ill-equipped to help their patients with portal issues. Such experiences can negatively affect the patient-clinician relationship. Preparing clinicians and patients about an upcoming transition, including technical support for clinicians and patients, may help minimize these potential issues [ 10 , 27 ]. Specialized training about an impending transition, along with detailed instructions on how to gain access to the new system, and a dedicated portal helpline may be necessary to help patients better navigate the transition [ 23 , 28 ].

In addition to a dedicated helpline, our recommendations include responding to potential changes in needed veteran services during the transition. In our study, participants observed more veteran walk-ins due to challenges with the patient portal. Health systems need to anticipate and address this demand by expanding access to in-person services and fortifying other communication channels. For example, sites could use nurses to staff a walk-in clinic to handle increases in walk-in traffic and increase call center capacity to handle increases in telephone calls [ 29 ]. Increased use of walk-in clinics have received heightened attention as a promising strategy for meeting healthcare demands during the COVID-19 pandemic [ 30 ] and can potentially be adapted for meeting care-related needs during an EHR transition. These strategies can fill a gap in communication between clinicians and their patients while patients are learning to access and navigate a new electronic portal.

Finally, there is a need for a recovery mechanism to restore confidence in the reliability of the EHR and the well-being of clinicians and staff. Healthcare workers are experiencing unprecedented levels of stress [ 31 ]. A plan must be in place to improve and monitor the accuracy of data migrated, populated, and processed within the new system [ 2 ]. Knowing that portal function is monitored could help ease clinician and staff concerns and mitigate stress related to the transition.

Limitations

This study has several limitations. First, data collection relied on voluntary participation, which may introduce self-selection response bias. Second, this work was completed at one VA medical center that was the first site in the larger enterprise-wide transition, and experiences at other VAs or healthcare systems might differ substantially. Third, we did not interview veterans and relied entirely on secondhand accounts of patient experiences with the patient portal. Future research should include interviews with veterans during the transition and compare veteran and VA employee experiences.

Despite a current delay in the deployment of the new EHR at additional VA medical centers, findings from this study offer timely lessons that can ensure clinicians and staff are equipped to navigate challenges during the transition. The strategies presented in this paper could help maintain patient-clinician communication and improve veteran experience. Guided by the emergency preparedness framework, recommended strategies to address issues presented here include alerting those patients most affected by the EHR transition, being prepared to address patients’ concerns, increasing staffing for the help desk and walk-in care clinics, and monitoring the accuracy and reliability of the portal to provide assurance to healthcare workers that patients’ needs are being met. These strategies can inform change management at other VA medical centers that will soon undergo EHR transition and may have implications for other healthcare systems undergoing patient portal changes. Further work is needed to directly examine the perspectives of veterans using the portals, as well as the perspectives of both staff and patients in the growing number of healthcare systems beyond VA that are preparing for an EHR-to-EHR transition.

Data availability

Deidentified data analyzed for this study are available from the corresponding author on reasonable request.

Abbreviations

Electronic health record

Department of Veterans Affairs

VA Medical Centers

Department of Defense

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Acknowledgments

We acknowledge and thank members of the EMPIRIC Evaluation qualitative and supporting team for their contributions to this work including Ellen Ahlness, PhD, Julian Brunner, PhD, Adena Cohen-Bearak, MPH, M.Ed, Leah Cubanski, BA, Christine Firestone, Bo Kim, PhD, Megan Moldestad, MS, and Rachel Smith. We greatly appreciate the staff at the Mann-Grandstaff VA Medical Center and associated community-based outpatient clinics for generously sharing of their time and experiences participating in this study during this challenging time.

The “EHRM Partnership Integrating Rapid Cycle Evaluation to Improve Cerner Implementation (EMPIRIC)” (PEC 20–168) work was supported by funding from the US Department of Veterans Affairs, Veterans Health Administration, Health Services Research & Development Quality Enhancement Research Initiative (QUERI) (PEC 20–168). The findings and conclusions in this article are those of the authors and do not necessarily reflect the views of the Veterans Health Administration, Veterans Affairs, or any participating health agency or funder.

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Sherry L. Ball

Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA

Bo Kim & Seppo T. Rinne

Department of Psychiatry, Harvard Medical School, Boston, MA, USA

Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, USA

Sarah L. Cutrona & Brianne K. Molloy-Paolillo

Division of Health Informatics & Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA

Sarah L. Cutrona

Seattle-Denver Center of Innovation for Veteran-Centered and Value-Driven Care, VHA Puget Sound Health Care System, Seattle, WA, USA

Ellen Ahlness, Megan Moldestad & George Sayre

University of Washington School of Public Health, Seattle, WA, USA

George Sayre

Geisel School of Medicine at Dartmouth, Hannover, NH, USA

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Contributions

S.R. designed the larger study. G.S. was the qualitative methodologist who led the qualitative team. S.B., E.A., and M.M. created the interview guides and completed the interviews; Data analysis, data interpretation, and the initial manuscript draft were completed by S.B. and B.K. S.C. and B.M. worked with the qualitative team to finalize the analysis and edit and finalize the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Sherry L. Ball .

Ethics declarations

Ethics approval and consent to participate.

This evaluation was designated as non-research/quality improvement by the VA Bedford Healthcare System Institutional Review Board. All methods were carried out in accordance with local and national VA guidelines and regulations for quality improvement activities. This study included virtual interviews with participants via MS Teams. Employees volunteered to participate in interviews and verbal consent was obtained to record interviews. Study materials, including interview guides with verbal consent procedures, were reviewed and approved by labor unions and determined as non-research by the VA Bedford Healthcare System Institutional Review Board.

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Not applicable.

The findings and conclusions in this paper are those of the authors and do not necessarily represent the official position of the Department of Veterans Affairs.

Prior presentations

Ball S, Kim B, Moldestad M, Molloy-Paolillo B, Cubanski L, Cutrona S, Sayre G, and Rinne S. (2022, June). Electronic Health Record Transition: Providers’ Experiences with Frustrated Patients. Poster presentation at the 2022 AcademyHealth Annual Research Meeting. June 2022.

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The authors declare no competing interests.

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Ball, S.L., Kim, B., Cutrona, S.L. et al. Clinician and staff experiences with frustrated patients during an electronic health record transition: a qualitative case study. BMC Health Serv Res 24 , 535 (2024). https://doi.org/10.1186/s12913-024-10974-5

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Received : 29 August 2023

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Published : 26 April 2024

DOI : https://doi.org/10.1186/s12913-024-10974-5

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Quantum challenge to be solved one mile underground

by Chalmers University of Technology

Radiation from space is a challenge for quantum computers as their computation time becomes limited by cosmic rays. Researchers from Chalmers University of Technology, Sweden, and University of Waterloo in Canada are now going deep underground in the search for a solution to this problem—in a two-kilometer-deep mine.

A recently discovered cause of errors in quantum computers is cosmic radiation. Highly charged particles from space disturb the sensitive qubits and cause them to lose their quantum state, as well as the ability to continue a calculation. But now quantum researchers from Sweden and Canada will join forces to find a solution to the problem—in the world's deepest located clean room, two kilometers underground.

"We are super excited about this project because it addresses the very important question of how cosmic radiation affects qubits and quantum processors. Gaining access to this underground facility is crucial to understanding how the effects of cosmic radiation can be mitigated," says Per Delsing, Professor of Quantum Technology at Chalmers University of Technology, Sweden, and Director of the Wallenberg Center for Quantum Technology.

Canadian Shield protects against cosmic rays

The unique research project is carried out in collaboration between researchers from Chalmers University of Technology, the Institute for Quantum Computing (IQC) at the University of Waterloo, and SNOLAB near Sudbury, Ontario, Canada.

In the study, superconducting qubits manufactured at Chalmers University of Technology will first be tested above ground in both Sweden and Canada. Next, the same qubits will be tested far below the Canadian ground so that differences between the two environments may be studied. With the help of the two-kilometer-thick "ground shield" that surrounds the world's deepest clean room located in the Vales Creighton mine in Ontario, the researchers may shut out cosmic rays or radioactivity that otherwise would have "knocked out" the qubits above ground.

"SNOLAB maintains the lowest muon flux in the world and has advanced cryogenics testing capabilities, making it an ideal place to conduct valuable research on quantum technologies," says Jeter Hall, Director of research at SNOLAB and Adjunct Professor at Laurentian University in Canada.

May solve error correction challenge

For the impact of quantum computers to be realized in society, quantum researchers first need to solve the issue of error correction. While classical computers use systems that can correct the errors that occur and provide reliable results, there are no current systems powerful enough to correct the significantly more complex errors that occur in quantum computers.

The error correction methods used on quantum computers today assume that each error caused by cosmic rays occurs independently of each other. This is an incorrect assessment, since these kinds of errors, on the contrary, usually correlate with each other. Current error correction methods cannot correct correlating errors, which means that multiple qubits can lose their quantum state at the same time. By increasing the understanding of the qubit processes, the researchers now want to find methods to reduce the number of correlated errors.

"With this project, we hope to start understanding what's going on with the qubit decoherence in relation to cosmic rays , and then start understanding how the radiation affects the qubits in more controlled ways," says Dr. Chris Wilson, Professor at the University of Waterloo and active at the Institute for Quantum Computing in Ontario.

The project is carried out in collaboration between Chalmers University of Technology, the Institute for Quantum Computing (IQC) at the University of Waterloo, Ontario, Canada, and SNOLAB near Sudbury, Ontario, Canada.

Provided by Chalmers University of Technology

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