using secondary data in qualitative research

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Qualitative Secondary Research A Step-By-Step Guide

Claire Largan
Theresa Morris - University College Birmingham, UK
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Perfect for those doing dissertations and research projects, it provides an accessible introduction to the theory of secondary research and sets out the advantages and limitations of using this kind of research. Drawing on years of teaching and research experience, the authors

· Offer step-by-step advice on how to use qualitative secondary data · Walk you through each stage of the research process · Provide practical, ethical tools to help you with your project · Show you how to avoid the potential pitfalls of using secondary data.

Clear and easy to understand, this book is a ready-made toolkit for successfully using qualitative secondary data. From beginner level and beyond, this no-nonsense guide takes the confusion and worry out of doing a secondary research project.

See what’s new to this edition by selecting the Features tab on this page. Should you need additional information or have questions regarding the HEOA information provided for this title, including what is new to this edition, please email [email protected] . Please include your name, contact information, and the name of the title for which you would like more information. For information on the HEOA, please go to http://ed.gov/policy/highered/leg/hea08/index.html .

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I recommend this book to students and more experienced researchers who want to conduct qualitative secondary research. It is a timely and accessible guide.

Overall, the authors have written a well thought out, accessible and comprehensive book, which is a welcome addition to a relatively small literature on secondary data and documentary analysis.

I will definitely be using this in my own research, to ensure that I have not forgotten important elements in my research design and analysis, and will be recommending chapter 5 (ethics in qualitative secondary research) as additional reading in the ethics chapter of my forthcoming book aimed at undergraduate student

Concise and coherent text on QSR. Have been searching for a text that is accessible for students that will allow them to reflect on their progress as researchers while also equipping them with a voice to justify their choices. This meets those parameters.

This is an excellent introductory text for a methodology that has become accepted practice and increasingly expected by research funding bodies. Making full use of collected data is an ethical principle and will prepare students well for future practice.

Very good resource for students and graduates alike. Definitely a must-read and should-work-with book :-)

The contents of the book allows students to carry out research with ease, the book has an easy flow and many useful areas for undergraduates to follow and complete any research work

This book should be an essential companion for anyone undertaking a research project. This underrepresented topic area is broken down into comprehensive chapters that provide a practical approach whilst prompting critical reflection also. Highly recommended.

a well-crafted and accessibly-written textbook which willl be very useful to students at several levels

This is an essential and accessible book for all undergraduate and postgraduate students wishing to carry out secondary research. This book offers a step-by-step guide into the processes of qualitative research, whilst allowing readers to develop their own critical thinking skills.

Miss Novlett Mitchell University College Birmingham

This book provides insights about qualititavie research and it is very useful for every dissertation module. I am so glad I had the opportunity to include it in my module

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Find My Rep

Qualitative Secondary Research A Step-By-Step Guide

Claire Largan
Theresa Morris - University College Birmingham, UK
Description

I recommend this book to students and more experienced researchers who want to conduct qualitative secondary research. It is a timely and accessible guide.

Overall, the authors have written a well thought out, accessible and comprehensive book, which is a welcome addition to a relatively small literature on secondary data and documentary analysis.

Very good resource for students and graduates alike. Definitely a must-read and should-work-with book :-)

The contents of the book allows students to carry out research with ease, the book has an easy flow and many useful areas for undergraduates to follow and complete any research work

a well-crafted and accessibly-written textbook which willl be very useful to students at several levels

Miss Novlett Mitchell University College Birmingham

This book provides insights about qualititavie research and it is very useful for every dissertation module. I am so glad I had the opportunity to include it in my module

Preview this book

For instructors.

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14.4: Secondary data analysis

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Matthew DeCarlo
Radford University via Open Social Work Education

Learning Objectives

Define secondary data analysis
List the strengths and limitations of secondary data analysis
Name at least two sources of publicly available quantitative data
Name at least two sources of publicly available qualitative data

One advantage of unobtrusive research is that you may be able to skip the data collection phase altogether. To many, skipping the data collection phase is preferable since it allows the researcher to proceed directly to answering their question through data analysis. When researchers analyze data originally gathered by another person or entity, they engage in secondary data analysis . Researchers gain access to data collected by other researchers, government agencies, and other unique sources by making connections with individuals engaged in primary research or accessing their data via publicly available sources.

Imagine you wanted to study whether race or gender influenced what major people chose at your college. You could do your best to distribute a survey to a representative sample of students, but perhaps a better idea would be to ask your college registrar for this information. Your college already collects this information on all of its students. Wouldn’t it be better to simply ask for access to this information, rather than collecting it yourself? Maybe.

Challenges in secondary data analysis

Some of you may be thinking, “I never gave my college permission to share my information with other researchers.” Depending on the policies of your university, this may or may not be true. In any case, secondary data is usually anonymized or does not contain identifying information. In our example, students’ names, student ID numbers, home towns, and other identifying details would not be shared with a secondary researcher. Instead, just the information on the variables—race, gender, and major—would be shared. Anonymization techniques are not foolproof, and this is a challenge to secondary data analysis. Based on my limited sample of social work classrooms I have taught, there are usually only two or three men in the room. While privacy may not be a big deal for a study about choice of major, imagine if our example study included final grades, income, or whether your parents attended college. If I were a researcher using secondary data, I could probably figure out which data belonged to which men because there are so few men in the major. This is a problem in real-world research, as well. Anonymized data from credit card companies, Netflix, AOL, and online advertising companies have been “unmasked,” allowing researchers to identify nearly all individuals in a data set (Bode, K. 2017; de Montjoy, Radaelli, Singh, & Pentland, 2015) [1]

Another challenge with secondary data stems from the lack of control over the data collection process. Perhaps your university made a mistake on their forms or entered data incorrectly. If this were your data, you would certainly never make such an error. But if it happened, you could correct it right away. With secondary data, you are less able to correct for any errors made by the original source during data collection. More importantly, you may not know these errors exist and reach erroneous conclusions as a result. Researchers using secondary data should evaluate the procedures used to collect the data wherever possible, and data that lacks documentation on procedures should be treated with caution.

Attending to how the original researchers dealt with missing or incomplete data is also important. Researchers may have simply used the mean score for a piece of missing data or excluded them from analysis entirely. The primary researchers made that choice for a reason, and secondary researchers should understand their decision-making process before proceeding with analysis. Finally, secondary researchers must have access to the codebook for quantitative data and coding scheme for qualitative data. A quantitative dataset often contains shorthand for question numbers, variables, and attributes. A qualitative data analysis contains as a coding scheme explaining definitions and relationships for all codes. Without these, the data would be difficult to comprehend for a secondary researcher.

Secondary researchers, particularly those conducting quantitative research, must also ensure that their conceptualization and operationalization of variables matches that of the primary researchers. If your secondary analysis focuses on a variable that was not a major part of the original analysis, you may not have enough information about that variable to conduct a thorough analysis. For example, if you wanted to study whether depression is associated with income for students and you found a dataset that included those variables. If depression was not a focus of the dataset, researchers may only have included a question like, “Have you ever been diagnosed with major depressive disorder?” While answers to this question will give you some information about depression, it will not give you the depth that a scale like Beck’s Depression Inventory or the Hamilton Rating Scale for Depression would or provide information about severity of symptoms like hospitalization or suicide attempts. Without this level of depth, your analysis may lack validity. Even when operationalization for your variables of interest is thorough, researchers may conceptualize variables differently than you do. Perhaps they are interested in whether a person was diagnosed with depression in their life, whereas, you are concerned with current symptoms of depression. For these reasons, reading research reports and other documentation is a requirement for secondary data analysis.

The lack of control over the data collection process also hamstrings the research process itself. While some studies are created perfectly, most are refined through pilot testing and feedback before the full study is conducted (Engel & Schutt, 2016). [2] Secondary data analysis does not allow you to engage in this process. For qualitative researchers in particular, this is an important challenge. Qualitative research, particularly from the interpretivist paradigm, uses emergent processes in which research questions, conceptualization of terms, and measures develop and change over the course of the study. Secondary data analysis inhibits this process from taking place because the data are already collected. Because qualitative methods often involve analyzing the context in which data are collected, secondary researchers may not know enough to authentically and accurately represent the original data in a new analysis.

Returning to our example on race, gender, and major once again, let’s assume you are reasonably certain the data do not contain errors and you are comfortable with having no control over the data collection process. Getting access to the data is not as simple as walking into the registrar’s office with a smile. Researchers seeking access to data collected by universities (or hospitals, health insurers, human service agencies, etc.) must have the support of the administration. In some cases, a researcher may only have to demonstrate that they are competent to complete the analysis, share their data analysis plan, and receive ethical approval from an IRB. Administrators of data that are often accessed by researchers, such as Medicaid or Census data, may fall into this category.

Your school administration may not be used to partnering with researchers to analyze their students. In fact, administrators may be quite sensitive to how their school is perceived as a result of your study. If your study found that women or Latinos are excluded from engineering and science degrees, that would reflect poorly on the university and the administration. It may be important for researchers to form a partnership with the agency or university whose data is included in the secondary data analysis. Administrators will trust people who they perceive as competent, reputable, and objective. They must trust you to engage in rigorous and conscientious research. A disreputable researcher may seek to raise their reputation by finding shocking results (real or fake) in your university’s data, while damaging the reputation of the university.

On the other hand, if your secondary data analysis paints the university in a glowing and rosy light, other researchers may be skeptical of your findings. This problem concerned Steven Levitt, an economist who worked with Uber to estimate how much consumers saved by using its service versus traditional taxis. Levitt knew that he would have to partner with Uber in order to gain access to their data but was careful to secure written permission to publish his results, regardless of whether his results were positive or negative for Uber (Huggins, 2016). [3] Researchers using secondary data must be careful to build trust with gatekeepers in administration while not compromising their objectivity through conflicts of interest.

Strengths of secondary data analysis

While the challenges associated with secondary data analysis are important, the strengths of secondary data analysis often outweigh these limitations. Most importantly, secondary data analysis is quicker and cheaper than a traditional study because the data are already collected. Once a researcher gains access to the data, it is simply a matter of analyzing it and writing up the results to complete the project. Data can take a long time to gather and be quite resource-intensive. So, avoiding this step is a significant strength of secondary data analysis. If the primary researchers had access to more resources, they may also be able to engage in data collection that is more rigorous than a secondary researcher could. In this way, outsourcing the data collection to someone with more resources may make your design stronger, not weaker. Finally, secondary researchers ask new questions that the primary researchers may not have considered. In this way, secondary data analysis deepens our understanding of existing data in the field.

Secondary data analysis also provides researchers with access to data that would otherwise be unavailable or unknown to the public. A good example of this is historical research , in which researchers analyze data from primary sources of historical events and proceedings. Netting and O’Connor (2016) [4] were interested in understanding what impact religious organizations had on the development of human services in Richmond, Virginia. Using documents from the Valentine History Center, Virginia Historical Society, and other sources, the researchers were able to discover the origins of social welfare in the city—traveler’s assistance programs in the 1700s. In their study, they also uncovered the important role women played in social welfare agencies, a surprising finding given the historical disenfranchisement of women in American society. Secondary data analysis provides the researcher with the opportunity to answer questions like these without a time machine. Table 14.3 summarizes the strengths and limitations of existing data.

Ultimately, you will have to weigh the strengths and limitations of using secondary data on your own. Engel and Schutt (2016, p. 327) [5] propose six questions to ask before using secondary data:

What were the agency’s or researcher’s goals in collecting the data?
What data were collected, and what were they intended to measure?
When was the information collected?
What methods were used for data collection? Who was responsible for data collection, and what were their qualifications? Are they available to answer questions about the data?
How is the information organized (by date, individual, family, event, etc.)? Are there identifiers used to identify different types of data available?
What is known about the success of the data collection effort? How are missing data indicated and treated? What kind of documentation is available? How consistent are the data with data available from other sources?

Sources of secondary data

Many sources of quantitative data are publicly available. The General Social Survey (GSS), which was discussed in Chapter 11 , is one of the most commonly used sources of publicly available data among quantitative researchers ( http://www.norc.uchicago.edu/GSS+Website ). Data for the GSS have been collected regularly since 1972, thus offering social researchers the opportunity to investigate changes in Americans’ attitudes and beliefs over time. Questions on the GSS cover an extremely broad range of topics, from family life to political and religious beliefs to work experiences.

Other sources of quantitative data include Add Health ( http://www.cpc.unc.edu/projects/addhealth ), a study that was initiated in 1994 to learn about the lives and behaviors of adolescents in the United States, and the Wisconsin Longitudinal Study ( https://www.ssc.wisc.edu/wlsresearch ), a study that has, for over 40 years, surveyed a panel of 10,000 people who graduated from Wisconsin high schools in 1957. Quantitative researchers interested in studying social processes outside of the United States also have many options when it comes to publicly available data sets. Data from the British Household Panel Study ( https://www.iser.essex.ac.uk/bhps ), a longitudinal, representative survey of households in Britain, are freely available to those conducting academic research (private entities are charged for access to the data). The International Social Survey Programme ( http://www.issp.org ) merges the GSS with its counterparts in other countries around the globe. These represent just a few of the many sources of publicly available quantitative data.

Unfortunately for qualitative researchers, far fewer sources of free, publicly available qualitative data exist. This is slowly changing, however, as technical sophistication grows and it becomes easier to digitize and share qualitative data. Despite comparatively fewer sources than for quantitative data, there are still a number of data sources available to qualitative researchers whose interests or resources limit their ability to collect data on their own. The Murray Research Archive Harvard, housed at the Institute for Quantitative Social Science at Harvard University, offers case histories and qualitative interview data ( http://dvn.iq.harvard.edu/dvn/dv/mra ). The Global Feminisms project at the University of Michigan offers interview transcripts and videotaped oral histories focused on feminist activism; women’s movements; and academic women’s studies in China, India, Poland, and the United States. [6] At the University of Connecticut, the Oral History Office provides links to a number of other oral history sites (www.oralhistory.uconn.edu/links.html). Not all the links offer publicly available data, but many do. Finally, the Southern Historical Collection at University of North Carolina–Chapel Hill offers digital versions of many primary documents online such as journals, letters, correspondence, and other papers that document the history and culture of the American South (dc.lib.unc.edu/ead/archivalhome.php?CISOROOT=/ead).

Keep in mind that the resources mentioned here represent just a snapshot of the many sources of publicly available data that can be easily accessed via the web. Table 14.4 summarizes the data sources discussed in this section.

While the public and free sharing of data has become increasingly common over the years, and it is an increasingly common requirement of those who fund research, Harvard researchers recently learned of the potential dangers of making one’s data available to all (Parry, 2011). [7] In 2008, Professor Nicholas Christakis, Jason Kaufman, and colleagues, of Harvard’s Berkman Center for Internet & Society, rolled out the first wave of their data collected from the profiles of 1,700 Facebook users (2008). [8] But shortly thereafter, the researchers were forced to deny public access to the data after it was discovered that subjects could easily be identified with some careful mining of the data set. Perhaps only time and additional experience will tell what the future holds for increased access to data collected by others.

Key Takeaways

The strengths and limitations of secondary data analysis must be considered before a project begins.
Previously collected data sources enable researchers to conduct secondary data analysis.
Anonymized data- data that does not contain identifying information
Historical research-analyzing data from primary sources of historical events and proceedings
Secondary data analysis- analyzing data originally gathered by another person or entity

Image attributions

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Bode, K. (2017, January 26). One more time with feeling: ‘Anonymized’ user data not really anonymous. Techdirt . Retrieved from: https://www.techdirt.com/articles/20170123/08125136548/one-more-time-with-feeling-anonymized-user-data-not-really-anonymous.shtml ; de Montjoye, Y. A., Radaelli, L., & Singh, V. K. (2015). Unique in the shopping mall: On the reidentifiability of credit card metadata. Science , 347 (6221), 536-539. ↵
Engel, R. J. & Schutt, R. K. (2016). The practice of research in social work (4th ed.) . Washington, DC: SAGE Publishing. ↵
Huggins, H. (Producer). (2016, September 7). Why Uber is an economist’s dream [Audio podcast]. Retrieved from: http://freakonomics.com/podcast/uber-economists-dream/ ↵
Netting, F. E., & O’Connor, M. K. (2016). The intersectionality of religion and social welfare: Historical development of Richmond’s nonprofit health and human services. Religions , 7 (1), 13-28. ↵
These data are not free, though they are available at a reasonable price. See the Global Feminisms’ webpage at https://globalfeminisms.umich.edu/contact ↵
Parry, M. (2011, July 10). Harvard researchers accused of breaching students’ privacy. The Chronicle of Higher Education . Retrieved from chronicle.com/article/Harvards-Privacy-Meltdown/128166↵
Berkman Center for Internet & Society. (2008, September 25). Tastes, ties, and time: Facebook data release. Retrieved from cyber.law.harvard.edu/node/4682↵

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Methodology

What is Secondary Research? | Definition, Types, & Examples

What is Secondary Research? | Definition, Types, & Examples

Published on January 20, 2023 by Tegan George . Revised on January 12, 2024.

Secondary research is a research method that uses data that was collected by someone else. In other words, whenever you conduct research using data that already exists, you are conducting secondary research. On the other hand, any type of research that you undertake yourself is called primary research .

Secondary research can be qualitative or quantitative in nature. It often uses data gathered from published peer-reviewed papers, meta-analyses, or government or private sector databases and datasets.

When to use secondary research, types of secondary research, examples of secondary research, advantages and disadvantages of secondary research, other interesting articles, frequently asked questions.

Secondary research is a very common research method, used in lieu of collecting your own primary data. It is often used in research designs or as a way to start your research process if you plan to conduct primary research later on.

Since it is often inexpensive or free to access, secondary research is a low-stakes way to determine if further primary research is needed, as gaps in secondary research are a strong indication that primary research is necessary. For this reason, while secondary research can theoretically be exploratory or explanatory in nature, it is usually explanatory: aiming to explain the causes and consequences of a well-defined problem.

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using secondary data in qualitative research

Secondary research can take many forms, but the most common types are:

Statistical analysis

Literature reviews, case studies, content analysis.

There is ample data available online from a variety of sources, often in the form of datasets. These datasets are often open-source or downloadable at a low cost, and are ideal for conducting statistical analyses such as hypothesis testing or regression analysis .

Credible sources for existing data include:

The government
Government agencies
Non-governmental organizations
Educational institutions
Businesses or consultancies
Libraries or archives
Newspapers, academic journals, or magazines

A literature review is a survey of preexisting scholarly sources on your topic. It provides an overview of current knowledge, allowing you to identify relevant themes, debates, and gaps in the research you analyze. You can later apply these to your own work, or use them as a jumping-off point to conduct primary research of your own.

Structured much like a regular academic paper (with a clear introduction, body, and conclusion), a literature review is a great way to evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

A case study is a detailed study of a specific subject. It is usually qualitative in nature and can focus on a person, group, place, event, organization, or phenomenon. A case study is a great way to utilize existing research to gain concrete, contextual, and in-depth knowledge about your real-world subject.

You can choose to focus on just one complex case, exploring a single subject in great detail, or examine multiple cases if you’d prefer to compare different aspects of your topic. Preexisting interviews , observational studies , or other sources of primary data make for great case studies.

Content analysis is a research method that studies patterns in recorded communication by utilizing existing texts. It can be either quantitative or qualitative in nature, depending on whether you choose to analyze countable or measurable patterns, or more interpretive ones. Content analysis is popular in communication studies, but it is also widely used in historical analysis, anthropology, and psychology to make more semantic qualitative inferences.

Secondary research is a broad research approach that can be pursued any way you’d like. Here are a few examples of different ways you can use secondary research to explore your research topic .

Secondary research is a very common research approach, but has distinct advantages and disadvantages.

Advantages of secondary research

Advantages include:

Secondary data is very easy to source and readily available .
It is also often free or accessible through your educational institution’s library or network, making it much cheaper to conduct than primary research .
As you are relying on research that already exists, conducting secondary research is much less time consuming than primary research. Since your timeline is so much shorter, your research can be ready to publish sooner.
Using data from others allows you to show reproducibility and replicability , bolstering prior research and situating your own work within your field.

Disadvantages of secondary research

Disadvantages include:

Ease of access does not signify credibility . It’s important to be aware that secondary research is not always reliable , and can often be out of date. It’s critical to analyze any data you’re thinking of using prior to getting started, using a method like the CRAAP test .
Secondary research often relies on primary research already conducted. If this original research is biased in any way, those research biases could creep into the secondary results.

Many researchers using the same secondary research to form similar conclusions can also take away from the uniqueness and reliability of your research. Many datasets become “kitchen-sink” models, where too many variables are added in an attempt to draw increasingly niche conclusions from overused data . Data cleansing may be necessary to test the quality of the research.

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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Normal distribution
Degrees of freedom
Null hypothesis
Discourse analysis
Control groups
Mixed methods research
Non-probability sampling
Quantitative research
Inclusion and exclusion criteria

Research bias

Rosenthal effect
Implicit bias
Cognitive bias
Selection bias
Negativity bias
Status quo bias

A systematic review is secondary research because it uses existing research. You don’t collect new data yourself.

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

Sources in this article

We strongly encourage students to use sources in their work. You can cite our article (APA Style) or take a deep dive into the articles below.

George, T. (2024, January 12). What is Secondary Research? | Definition, Types, & Examples. Scribbr. Retrieved April 2, 2024, from https://www.scribbr.com/methodology/secondary-research/

Largan, C., & Morris, T. M. (2019). Qualitative Secondary Research: A Step-By-Step Guide (1st ed.). SAGE Publications Ltd.

Peloquin, D., DiMaio, M., Bierer, B., & Barnes, M. (2020). Disruptive and avoidable: GDPR challenges to secondary research uses of data. European Journal of Human Genetics , 28 (6), 697–705. https://doi.org/10.1038/s41431-020-0596-x

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Qualitative Secondary Analysis: A Case Exemplar

PMID: 29254902
PMCID: PMC5911239
DOI: 10.1016/j.pedhc.2017.09.007

Qualitative secondary analysis (QSA) is the use of qualitative data that was collected by someone else or was collected to answer a different research question. Secondary analysis of qualitative data provides an opportunity to maximize data utility, particularly with difficult-to-reach patient populations. However, qualitative secondary analysis methods require careful consideration and explicit description to best understand, contextualize, and evaluate the research results. In this article, we describe methodologic considerations using a case exemplar to illustrate challenges specific to qualitative secondary analysis and strategies to overcome them.

Keywords: Critical illness; ICU; qualitative research; secondary analysis.

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Secondary Data Analysis: Ethical Issues and Challenges

Research does not always involve collection of data from the participants. There is huge amount of data that is being collected through the routine management information system and other surveys or research activities. The existing data can be analyzed to generate new hypothesis or answer critical research questions. This saves lots of time, money and other resources. Also data from large sample surveys may be of higher quality and representative of the population. It avoids repetition of research & wastage of resources by detailed exploration of existing research data and also ensures that sensitive topics or hard to reach populations are not over researched ( 1 ). However, there are certain ethical issues pertaining to secondary data analysis which should be taken care of before handling such data.

Secondary data analysis

Secondary analysis refers to the use of existing research data to find answer to a question that was different from the original work ( 2 ). Secondary data can be large scale surveys or data collected as part of personal research. Although there is general agreement about sharing the results of large scale surveys, but little agreement exists about the second. While the fundamental ethical issues related to secondary use of research data remain the same, they have become more pressing with the advent of new technologies. Data sharing, compiling and storage have become much faster and easier. At the same time, there are fresh concerns about data confidentiality and security.

Issues in Secondary data analysis

Concerns about secondary use of data mostly revolve around potential harm to individual subjects and issue of return for consent. Secondary data vary in terms of the amount of identifying information in it. If the data has no identifying information or is completely devoid of such information or is appropriately coded so that the researcher does not have access to the codes, then it does not require a full review by the ethical board. The board just needs to confirm that the data is actually anonymous. However, if the data contains identifying information on participants or information that could be linked to identify participants, a complete review of the proposal will then be made by the board. The researcher will then have to explain why is it unavoidable to have identifying information to answer the research question and must also indicate how participants’ privacy and the confidentiality of the data will be protected. If the above said concerns are satisfactorily addressed, the researcher can then request for a waiver of consent.

If the data is freely available on the Internet, books or other public forum, permission for further use and analysis is implied. However, the ownership of the original data must be acknowledged. If the research is part of another research project and the data is not freely available, except to the original research team, explicit, written permission for the use of the data must be obtained from the research team and included in the application for ethical clearance.

However, there are certain other issues pertaining to the data that is procured for secondary analysis. The data obtained should be adequate, relevant but not excessive. In secondary data analysis, the original data was not collected to answer the present research question. Thus the data should be evaluated for certain criteria such as the methodology of data collection, accuracy, period of data collection, purpose for which it was collected and the content of the data. It shall be kept for no longer than is necessary for that purpose. It must be kept safe from unauthorized access, accidental loss or destruction. Data in the form of hardcopies should be kept in safe locked cabinets whereas softcopies should be kept as encrypted files in computers. It is the responsibility of the researcher conducting the secondary analysis to ensure that further analysis of the data conducted is appropriate. In some cases there is provision for analysis of secondary data in the original consent form with the condition that the secondary study is approved by the ethics review committee. According to the British Sociological Association’s Statement of Ethical Practice (2004) the researchers must inform participants regarding the use of data and obtain consent for the future use of the material as well. However it also says that consent is not a once-and-for-all event, but is subject to renegotiation over time ( 3 ). It appears that there are no guidelines about the specific conditions that require further consent.

Issues in Secondary analysis of Qualitative data

In qualitative research, the culture of data archiving is absent ( 4 ). Also, there is a concern that data archiving exposes subject’s personal views. However, the best practice is to plan anonymisation at the time of initial transcription. Use of pseudonyms or replacements can protect subject’s identity. A log of all replacements, aggregations or removals should be made and stored separately from the anonymised data files. But because of the circumstances, under which qualitative data is produced, their reinterpretation at some later date can be challenging and raises further ethical concerns.

There is a need for formulating specific guidelines regarding re-use of data, data protection and anonymisation and issues of consent in secondary data analysis.

Acknowledgements

The authors declare that there is no conflict of interest.

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Open access
Published: 05 April 2024

Barriers and facilitators to guideline for the management of pediatric off-label use of drugs in China: a qualitative descriptive study

Min Meng 1 , 2 , 3 , 4 na1 ,
Jiale Hu 5 na1 ,
Xiao Liu 6 ,
Min Tian 4 ,
Wenjuan Lei 4 ,
Enmei Liu 2 , 3 ,
Zhu Han 7 ,
Qiu Li 2 , 3 , 8 &
Yaolong Chen 1 , 2 , 3 , 9 , 10 , 11

BMC Health Services Research volume 24 , Article number: 435 ( 2024 ) Cite this article

Metrics details

Despite being a global public health concern, there is a research gap in analyzing implementation strategies for managing off-label drug use in children. This study aims to understand professional health managers’ perspectives on implementing the Guideline in hospitals and determine the Guideline’s implementation facilitators and barriers.

Pediatric directors, pharmacy directors, and medical department directors from secondary and tertiary hospitals across the country were recruited for online interviews. The interviews were performed between June 27 and August 25, 2022. The Consolidated Framework for Implementation Research (CFIR) was adopted for data collection, data analysis, and findings interpretation to implement interventions across healthcare settings.

Individual interviews were conducted with 28 healthcare professionals from all over the Chinese mainland. Key stakeholders in implementing the Guideline for the Management of Pediatric Off-Label Use of Drugs in China (2021) were interviewed to identify 57 influencing factors, including 27 facilitators, 29 barriers, and one neutral factor, based on the CFIR framework. The study revealed the complexity of the factors influencing managing children’s off-label medication use. A lack of policy incentives was the key obstacle in external settings. The communication barrier between pharmacists and physicians was the most critical internal barrier.

To our knowledge, this study significantly reduces the implementation gap in managing children’s off-label drug use. We provided a reference for the standardized management of children’s off-label use of drugs.

Peer Review reports

Introduction

Off-label drug use in pediatrics is a global public health issue [ 1 ], particularly in China [ 2 , 3 ]. According to a systematic review, pediatric off-label medicine prescription rates ranged from 22.7% to 51.2% in outpatient settings and 40.48% to 78.96% in hospitalized children in China [ 4 ]. However, there are numerous unreasonable examples of off-label drug use in children, posing significant risks to children’s safety [ 5 , 6 ]. As a result, the Guideline for the Management of Pediatric Off-label Use of Drugs in China (i.e., the Guideline) was developed in 2021 by the Chinese Society of Pediatric Clinical Pharmacology, the Chinese Medical Association, and the National Clinical Research Center for Child Health and Disorders (Children’s Hospital of Chongqing Medical University), in collaboration with the Chinese GRADE Center [ 7 ].

However, translating evidence from clinical practice guidelines (i.e., CPG) into practice, also known as implementation [ 8 , 9 ], is a complex process influenced by various factors such as political and social, the health organizational system, the CPG context, healthcare professionals, and patients [ 10 ]. For example, only about half of Chinese healthcare professionals follow the recommendations and understand the clinical practice guidelines, which range from 3 to 86% [ 9 ].

To enhance guideline adherence among healthcare professionals, it is necessary to identify the facilitators and barriers to guideline implementation [ 11 ]. In addition, theory-based guideline implementation research can assist implementers in avoiding potential pitfalls that may hinder their effectiveness [ 12 ]. Consequently, identifying factors that influence the implementation of recommendations, that is, implementation barriers and facilitators [ 10 ], is essential for the early clinical translation of guidelines to implement strategies tailored to anticipated barriers [ 13 ] and to optimize the implementation of interventions [ 14 ].

Off-label use of drugs in children is a complex aspect of clinical practice [ 15 ]. Only a small number of studies have demonstrated that the following are obstacles to the management of pediatric off-label use in China: lack of time to offer sources of information and evidence of off-label use, no available expert panel on off-label use, no adverse drug reaction monitoring system, no database of off-label drugs, no ethics council or pharmacy administration committee, difficulties in gaining written agreement from parents or guardians, and absence of a unified regulatory framework [ 16 , 17 , 18 ]. In addition, doctors’ awareness prescription of off-label drugs [ 19 , 20 , 21 , 22 ], their fear of legal repercussions [ 23 ], and they are less of informing parents about off-label drugs [ 21 , 24 ] were obstacles to managing children’s off-label drug use. However, none of the present research is theoretically based on guideline implementation studies and hence may lack systematicity in identifying factors influencing off-label drug use management in children. In addition, implementation strategies for managing pediatric off-label drug use are understudied.

Implementation strategies tailed based on the implementation contextual factors can promote adherence among healthcare professionals [ 25 ]. The Consolidated Framework for Implementation Research (CFIR), a well-known implementation science framework, has been extensively used as a framework in recent research on strategies for implementing guidelines, and it has successfully identified the influencing factors for guidelines’ implementation [ 26 , 27 , 28 , 29 , 30 , 31 ].Therefore, this study used CFIR for guiding data collection, data analysis, and findings interpretation to implement interventions across healthcare settings and aimed to understand professional health managers’ perspectives on implementing the Guideline in hospitals and determine the Guideline’s implementation facilitators and barriers. Also, the suggestions for implementing the Guideline were created by mapping the identified barriers to the Expert Recommendations for Implementing Change (ERIC) and selecting the appropriate strategies for implementation [ 26 , 32 ].

Research design

A qualitative descriptive study design was used in this study to understand professional health managers’ perceived barriers and facilitators to implementing the Guideline in hospitals [ 33 ]. In the previous study, 896 healthcare professionals from mainland China were invited to complete a questionnaire to rate the urgency and difficulty of implementing each of the 21 recommendations in the Guideline, ranking the recommendations according to combined scores, and selecting the top five of them (See Table 1 ).

Setting and sample

The study was conducted collaboratively by the Clinical Pharmacology Group of the Pediatric Society of the Chinese Medical Association and the National Clinical Research Center for Child Health (Children’s Hospital of Chongqing Medical University). Pediatric directors, pharmacy directors, and medical department directors from secondary and tertiary hospitals across the country were recruited voluntarily through the members’ units for online interviews via Tencent Meeting ( https://meeting.tencent.com ).

Reading available studies and performing some initial research helped create an interview framework [ 16 , 17 , 34 , 35 , 36 ]. Before the formal interviews started, a pharmacy director was recruited to participate in the pretest, and the interview plan was modified to consider the pretest results. The formal interviews were performed between June 27 and August 25, 2022, and participants were recruited using the convenience sampling approach. All the professionals with at least one year of management experience in pediatric off-label drug use were included. All experts invited to present were encouraged to participate and were given comprehensive information on the study via WeChat. They were instructed to read the Guideline in detail and ask the guideline developers to explain any questions accordingly [ 7 ]. Detailed interview times and locations were negotiated after signing an electronic informed consent. The sample size for this investigation was determined based on data coding, data saturation, and study feasibility [ 37 ].

Data collection

A semi-structured interview outline was created, with all questions revolving around the CFIR. The conversation will focus on potential contributing elements and obstacles to the Guideline’s implementation (See Supplementary Material 2 ). The CFIR framework and pre-interview were used to determine the validity of a structured interview in this qualitative research.

Data collection and analysis were repeated to discover new insights from early interviews that would guide later interviews and data collection [ 33 ]. We used Tencent Conferences ( https://meeting.tencent.com ) for audio recording and Xunfeitingjian Software ( https://www.iflyrec.com/ ) for transcriptions. Each interview was recorded with a particular interviewer label and then transcribed verbatim. All interviewees had the chance to examine the interview recordings to increase credibility and reliability.

Data analysis

The facilitators and barriers of the Guideline were investigated explicitly in the qualitative content analysis of expert interview data [ 38 ]. Both inductive and deductive methods were used to identify facilitators, barriers, and neutral factors [ 39 ]. A neutral influence has no positive or negative consequences or both positive and negative consequences but is overall neutral [ 40 ]. Meaningful text units, such as sentences, paragraphs, and words, were inductively extracted into coding and then subjected to CFIR framework analysis. These codes were then classified into subcategories and generic categories for further evaluation [ 41 ]. Information extraction and coding in Chinese were carried out independently by two researchers (MM and LX), and any discrepancies were resolved through discussion. The final findings were translated into English and further discussed by the research team to enable researcher triangulation and to reach a consensus on the results [ 42 ].

Role of the funding sources

The funder provided support for expert consultation fees and research publication costs. The study’s design and execution were not influenced by the research funding.

Characteristics of participants

Individual interviews were conducted with 28 healthcare professionals. The interviews ranged from 21 to 56 min. Half of the participants had a bachelor’s degree, and 60.7% were male. Among the participants, pediatric directors, pharmacy directors, and medical department director were ten, nine, and nine, correspondingly. About 40% of participants had more than 20 years of experience, 27 were in senior positions, and one was in an intermediate position. There were 15 from tertiary hospitals and 13 from secondary hospitals, respectively. Twenty of the professionals interviewed were dissatisfied with the current management of off-label drug use in children. Participants came from all across the Chinese mainland (see Table 2 ).

Identified influencing factors

According to the findings of the interviews, there are 57 factors influencing the implementation of the Guideline in China, including 27 facilitators, 29 barriers, and one neutral factor. These contributing factors were spread throughout 29 constructs in the four CFIR domains studied for the guidelines (see Table 3 and Supplementary Material 1 ). The most influential factors were found in the internal setting, and the fewest influences were found in the intervention characteristics, which was 24 and ten, respectively. Following the CFIR framework, including intervention characteristics, external setting, internal setting and individual characteristics, we will present the following descriptions of all influential factors.

Intervention characteristics

In seven of the eight constructs in the CFIR domain of intervention characteristics, three facilitators and seven barriers were identified (see Table 3 and Supplementary Material 1 ). Many experts supported the implementation of the Guideline and praised the quality and strength of the evidence in terms of facilitators. The Guideline’s key relative strengths were the Guideline developed by a pediatric specialty hospital, which was in charge of developing pharmaceuticals for pediatrics, including national interdisciplinary specialists with more impact. It is more advantageous than comparable existing guidelines in China.

The barriers included a lack of practicality, unnecessary clinical practice, a need for context-specific adaptation, poor trialability in non-children’s hospitals, poor feasibility in primary hospitals, some complicated recommendations, and a need for some cost. The participant said, “With or without this guideline, it has little impact on clinical practice; it is just an additional option to consider.” which showed the Guideline is not particularly meaningful. The absence of emergency response capacity, the shortage of pediatricians, and the inability to accurately estimate adverse drug reactions are the key barriers to implementation in primary care facilities. The adaptations to the guidelines that are required to fit the implementing setting include suiting the primary level, renaming off-label drug use to expanded drug use, managing pediatric population subgroups differently (neonates, infants, children, and adolescents), improving process management, and simplifying clinical practice. The management of off-label use of drugs should be implemented for all patients while managing the pediatric population, according to the broad view of non-children’s hospital managers who believe that the pediatric population is too small. Costs that need to be considered include the cost of purchasing, maintaining, and updating the database, the cost of recruiting assessment experts, the cost of legislation, training, and dissemination, as well as the time clinicians must spend managing off-label drugs.

External setting

In the four constructs of the external setting, a total of 12 influencing factors were included, with five facilitating factors, six barrier factors, and one neutral factor (see Table 3 and Supplementary Material 1 ). In terms of facilitating factors, the Guideline can meet children’s treatment needs, pharmaceutical companies participate in and promote clinical trials, the Physicians Law of the People’s Republic of China encourages the management of off-label drug use in children, the occurrence of off-label drug use disputes in children raises concerns in this area, and unique improvement campaigns. Neutral influences include the Guangdong Pharmaceutical Society, the Shandong Pharmaceutical Society, and similar guidelines from other countries.

The barriers included a lack of patient understanding, pharmaceutical industry off-label promotion, too many choices, non-reimbursement by health insurance, risk of legal conflicts, and a lack of administrative or policy promotion. Although clinicians may have some authority, they will still have to deal with the problem and risk of off-label use of drugs because patients frequently lack comprehension of their use. " Well-known professionals collect a variety of evidence and then inform the patient of any potential adverse effects,, the parents will claim, ‘I signed the informed permission, but I do not know the medicine and saw the instructions did not include this use. You are a doctor, and you know whether to use it.' if the accident occurs.” In China, the health insurance reimbursement system has a direct impact on clinicians’ treatment behavior, and “there is a big problem with not being reimbursed for any medications that are used off-label. " In addition, the possibility of legal disputes arising from the off-label use of medications in children worries many doctors. A participant said,” After all, there is no particular legislation, and while the Physician Law specifies that off-label drug use is subject to standards and guidelines, there are still risks in practice. " Furthermore, the lack of administrative or policy impetus for the guideline is an essential barrier, “Regarding the current context of hospital medication use in China, the power of professionals is constantly pushed by the force of administration or policy. “

Internal setting

The 14 structures of the internal setting in CFIR contained the most influencing elements, with 15 facilitators and nine barriers (see Table 3 and Supplementary Material 1 ). The facilitators included graded management, a dedicated person to drive, the addition of prescription review rules, promotion by societies or associations, promotion by medical associations, cultural alignment with the hospital, high urgency, fitting firmly with the hospital’s management, availability of punishments, alignment with hospital management goals, a better learning environment, proper off-label drug coverage by the hospital, a team of off-label drug management, a database, and clinical pharmacists’ support of off-label drug use. Off-label drugs are not reimbursed by Medicare but are covered by some hospitals. " The hospital will pay for reasonable off-label drugs that are approved by the hospital but are not paid for by health insurance.” Furthermore, many hospitals are prepared to implement off-label management in children, and interview experts believe that clinical pharmacist support can help manage the off-label use of drugs. A participant said, “Our clinical pharmacists are our most important resource for explaining off-label drug use. The combination of clinicians and clinical pharmacists coming together to assess the safety and efficacy of the drugs is particularly good.”

The barriers included the low priority of pediatrics in non-children’s hospitals, the unfavorable social environment, the conflict between clinicians and patients, the lack of communication between pharmacists and clinicians, a lack of priority in comparison to other daily work, a lack of personal gain, low-level physician compliance, complex management procedures, a lack of attention from hospital leadership, and a lack of specialized training. According to many experts, managing pediatric off-label drug use does not prioritize daily work since it is only a small component of rational medication management or daily diagnosis and treatment. A participant said, " Off-label drugs for children are just a minor part of clinical treatment. In the arduous clinical work, I must always prioritize the patient, making off-label drugs impossible to focus on”. Additionally, especially in primary hospitals, there is a lack of specialized training in using off-label medications in children.

Individual characteristics

In the four constructs of the individual characteristics, a total of 11 influencing factors were included, with four facilitating factors and seven barrier factors (see Table 3 and Supplementary Material 1 ). The facilitators included an alignment with personal beliefs, physician confidence, a willingness to promote, and a high degree of professional restraint and self-defense of pediatric doctors. The transmission and promotion of guidelines with coworkers, classmates, and some network contacts were mentioned by experts as methods. Furthermore, some interviewers considered pediatricians more self-aware and disciplined than adult physicians.

The barriers included a lack of understanding of the Benefit and Risk Assessment framework, low titles, a lack of passion and innovation on the part of pharmacists, a wide range of technical competence, a few physicians’ poor ethical principles, an ignorance of physicians’ management of off-label use drugs, and a physicians’ empiricism with drug use. Recommendation 4.1’s benefit and risk assessment framework confused many medical professionals. They offered some solutions, such as “I hope to use it as a quantitative adjustment of a scale,” “make it a scoring system,” “make its voice recognizable,” or “make it as intelligent standard operating procedures.” The more considerable barriers are physicians’ empirical use of drugs and a lack of awareness about off-label drug management. “Clinically, there isn’t a clear line between right and wrong, and I think that after the recommendations are put into place, there will be a lot of resistance to changing doctors’ habits if they need to.”

Role differences

Conflicting views exist among experts on the interaction between clinical pharmacists and physicians. A pharmacist said, “The most challenging component of communicating with clinicians is clinical department chiefs, in particular. Some medical professionals will collect books, manuals, guidelines, and other information to prove their point to you. We must explain that any use not listed in the drug manual is considered off-label, but it may not be irrational. Additionally, you must carefully and exhaustively offer evidence when introducing each form of an off-label drug one at a time. With the medical department, communication is still quite simple.” In contrast, doctors contended that “prescriptions are frequently evaluated by the hospital’s pharmacy department, for example, in the case of incorrect dosage. Then a deduction is required, and much work and time must be spent on fighting and appealing each time.” Clinicians expect pharmacists to devote their time and energy as the driving force behind the off-label use of drugs for children, even though the varied feedback from the roles for communication may be related to the various goals of the different roles for managing off-label drugs for children. A participant said, “Pharmacy is expected by medical departments to offer a catalog or to advance scientific management, but their primary goal is self-preservation and minimizing dangers to clinicians during treatment. Clinicians are also extremely hopeful that pharmacies will become more clinically friendly through constant appeal and standardization, some actions to support the development of a reliable system, and a social environment. However, clinicians might not invest much time or effort in this area.”

Conflicting influential factors

Some interview experts viewed clinical pharmacists as facilitators, but some believed that they made managing children’s off-label drug use more difficult. “It is appropriate for clinical pharmacists to direct the clinical use of medications because they are more knowledgeable about drug toxicology and adverse effects. But the current situation of over-centralization of clinical pharmacist rights and restriction of clinical use of medications to clinicians, as well as the lack of personal competence of clinical pharmacists, may hinder the rational clinical use of medications, including off-label use in children,” one medical director stated.

Many experts regarded the Law on Doctors of the People's Republic of China as a facilitating factor, but some experts still think there are legal concerns involved in putting the Guidelines into practice. An expert said, “The Physicians’ Law contains 67 items, including four on the use of off-label drugs, which is considerable progress for the management of off-label use of drugs. However, there is no targeted legislation. Clinicians are at higher risk of experiencing adverse side effects from using off-label drugs.” The experts regard the guidelines’ implementation as urgent but not a priority. An interviewer said, “As a result of our current inadequate drug supply and the urgent demand for pediatric medications, experts stressed the urgent necessity to address the issue of off-label prescriptions for children.” However, according to experts, it is not given the highest priority for implementation, primarily due to the busy and complex clinical work and the concern about off-label use of drugs making up a tiny portion of daily work. Additionally, managing children’s off-label drug use is also not a standard component of hospital assessments, and medical staff typically puts the hospital’s assessment requirement first.

According to our knowledge, this is the first study conducted by Chinese guideline developers to tailor the implementation strategy of the guidelines. Key stakeholders in the implementation of the Guideline for the management of pediatric off-label use of drugs in China (2021) were interviewed to identify 57 influencing factors, including 27 facilitators, 29 barriers, and one neutral factor, based on the implementation science CFIR framework and using one-on-one expert in-depth interviews. Based on mapping the critical barriers to the CFIR-ERIC [ 26 , 32 ], recommendations for implementation strategies were made, such as tailoring strategies, encouraging adaptability, inquiring of national health administrations to promote recommendations, and establishing networks for communication between clinicians and pharmacists. The study revealed the complexity of the factors influencing managing children’s off-label medication use. We will update the Guideline to address the lack of patient awareness, and a lack of policy incentives (non-reimbursement by health insurance and a lack of administrative or policy promotion) were the key obstacles in external settings. The communication barriers between pharmacists and physicians were found to be the most critical internal barriers. Regarding individual characteristics, the main barriers were pharmacists’ varying technical competence and physicians’ empiricism with medication use. Additionally, this study discovered that even though the PRC Physicians Law’s enforcement helped implement and promote the Guideline, it still needs to relieve the issue of legal dangers for medical staff completely. The difference in the barriers to implementing the Guideline for different roles of medical staff is the communication barrier between pharmacists and physicians.

According to this qualitative study, the Guideline was viewed as having less applicability for primary hospitals by many experts. The findings were consistent with a 2017 study on managing children’s off-label drug use, which also found a significant difference between the management of children’s off-label drug use in secondary and tertiary hospitals [ 17 ]. In China, each hospital grade has a unique set of medical duties, and the higher the grade, the greater the capacity for treatment [ 43 , 44 ]. As map CFIR-ERIC suggests, we should tailor strategies [ 26 , 32 ]. It is advised that guideline developers should take into account the creation of implementation strategies for various hospital grades [ 14 ]. Additionally, many experts feel that the Benefit and Risk Assessment Framework in recommendation 4.1 is difficult to comprehend and would like to quantify and improve the framework’s operability to help physicians make speedy and accurate decision-making. Intelligent assisted decision-making technologies have been created globally and deployed in clinical practice [ 45 , 46 , 47 ]. Artificial intelligence-based and scientifically sound assisted decision-making systems for children’s off-label drug use to have some shortcomings [ 45 ]. As map CFIR-ERIC suggests, we should promote adaptability and suggest researchers should develop a more practical framework for monitoring the use of off-label drugs in children or a scientifically validated off-label medication-assisted decision-making system to make it easy to follow [ 26 , 32 ].

As our findings show, in China, the lack of policy incentives and Medicare not covering off-label medicine costs are severe barriers to managing off-label drug use in children [ 48 , 49 ], Belgium [ 50 ], the Czech Republic [ 51 ], Germany [ 52 ], Italy [ 53 ], Switzerland [ 53 ], the United States [ 54 , 55 ], Slovakia [ 55 ], Greece [ 5 ], and Poland [ 56 ], were currently capable of paying for certain off-label drugs by general health insurance. As a result, it is proposed that China’s health insurance department consider establishing a national essential specified reimbursement catalog for off-label drugs based on the relevant experience of the countries mentioned above. Also, we find that a lack of administrative & policy promotion is a barrier. Policies are the most influential drivers of medical practice improvement in China. For example, the Chinese Special Rectification Activity on Clinical Antibiotic Use (CSRA), launched in 2011, has been implemented by hospitals and promoted by policy. Numerous studies have demonstrated its rapid and long-term implementation effect [ 57 , 58 , 59 ]. Alter incentive/allowance structures, involve executive boards, and build a coalition were mapped by CFIR-ERIC [ 26 , 32 ]; consequently, the national health administration is called upon to promote implementing off-label drug use management in children.

Although the Law on Doctors of the People's Republic of China was a reasonable basis for off-label use, physicians and hospitals face potential legal risks in practice, according to our research, which may be because of its implementation challenges [ 59 ]. According to Chinese Physicians Law, “in special cases where effective therapies are not yet available, a physician may, after obtaining the patient’s explicit informed consent, use a drug that is not stated in the drug’s instructions but has evidence to support its use,” which indicates that there are two conditions for using drugs off-label. First, obtain the patient’s informed consent. Second, there is evidence supported. Clinical challenges exist in obtaining informed permission from parents of children, primarily because of their lack of comprehension of the concept of off-label use of drugs [ 19 , 60 ] and an increased risk of adverse reaction [ 60 ], which is further worsened by the crisis in doctor-patient trust crisis [ 61 ]. Additionally, the current inaccessibility of evidence, mainly because of the shortage of locally evidence-based data for pediatrics [ 62 , 63 ], the shortage of evidence-based specialists [ 64 ], and the ignorance of “evidence-based medicine” and its critical databases among doctors both domestically and internationally [ 65 ]. As a result, the following two suggestions are recommended: On the one hand, information sharing and disease-specific education [ 66 ] can help doctors and patients communicate more effectively. The Guideline’s developers should create patient and public versions of the Guidelines [ 67 , 68 ] to “translate” the rationale and recommendations into a format that patients and the general public can understand and use, as well as to assist parents of children in understanding the meaning and necessity of off-label drugs in a friendly manner. Parents will have a better grasp of why off-label drug use is necessary. On the other hand, the authors of the recommendations should invite evidence-based specialists to regularly update the “list of common types of pediatric off-label use of drugs, evidence levels, and recommendations” in Recommendation 1.2, making it easy for clinicians to access the evidence-based information regarding the use of drugs off-label in children.

Clinical pharmacists actively contribute to managing off-label drugs in children, as the experts indicated in their interviews [ 69 , 70 , 71 , 72 ]. However, the study identified communication barriers between pharmacists and physicians, which is consistent with the findings [ 73 ]. On the one hand, the idea of the doctor as a leader is ingrained in the medical profession. The power gap between doctors and pharmacists makes doctors seem unapproachable to pharmacists [ 74 , 75 ]. On the other, most clinical pharmacists in China originally trained as ordinary pharmacists and went on to finish a year of continuing clinical pharmacy education [ 76 , 77 ]. A need for more clarity of duty and role conflict among clinical pharmacists is frequently the result of shorter training programs and quick duty transitions [ 76 ]. The wide range mainly demonstrates this in clinical pharmacist competence [ 78 ], which has caused physicians to need more faith in their expertise [ 73 ]. In order to improve the communication effectiveness of pediatric off-label use of drug management, it is suggested to investigate appropriate communication strategies and establish networks for communication between doctors and pharmacists according to the CFIR-ERIC map [ 26 , 32 ]. For instance, physician-pharmacist-patient communication has become more effective and satisfying thanks to the situation-background-assessment-recommendation (SBAR) standardized communication model [ 79 , 80 ].

To our knowledge, this study significantly reduces the implementation gap in managing children’s off-label drug use. We systematically identified and analyzed the “Guideline for the Management of Pediatric Off-Label Use of Drugs in China” implementation challenges using the CFIR framework and gave suggestions for implementing the Guideline. In this study, we investigated the perspectives of healthcare professionals in various hospital roles on the management of children’s off-label drug use. We provided a reference for the standardized management of children’s off-label use of drugs.

Limitations

The study also has some limitations. Firstly, only the key stakeholders in the Guideline—the head of pediatrics, the head of the pharmacy, and the medical department director were included in the study, whichmeans that not all influencing factors were identified. Still, since all participants have rich experience in the field and experience managing off-label drug use in children, we believe they are more representative. Second, quotations with codes were translated into English from the expert interviews and data analysis done in Chinese. Although no researchers of the international collaborative team had read the original transcripts, a consensus was reached through an iterative process and triangulation to ensure the objectivity of the data collection and analysis.

Implications for further research and clinical practice

Planning the implementation of guidelines, including a good fit between implementation strategies, relevant interventions, and contexts, is more complicated and demanding [ 81 ]. The findings of this study indicate that future complex interventions for the Guideline will be necessary because of several influencing factors. It is advised that future intervention studies be designed using the new framework for complex interventions, which includes intervention development or identification, feasibility, assessment, and implementation [ 82 ]. Partnership, target population-centered, evidence, and theory-based, implementation-based, efficiency-based, stepped or phased, intervention-specific, and combination are currently recommended intervention development and design methodologies [ 83 ]. Combining the Chinese implementation settings will be possible concerning numerous implementation strategies, such as workflow and regulation optimization, assessment tool development, resource input, or multidisciplinary collaboration [ 84 ]. Consequently, complex interventions may be established to encourage the implementation of guidelines at various levels of the hospital setting. In addition, appropriate process evaluation methods should be adopted to comprehend and better understand the causal mechanisms and contextual factors associated with outcome change [ 85 , 86 ].

Despite being a global public health concern, there is a research gap in analyzing implementation strategies for managing off-label drug use in children. In the future, the Guideline will be updated based on facilitators and barriers, and interventions will be created in various settings to advance guidelines’ implementation by guideline developers. Additionally, the findings in this study are regarded as a baseline for comparison with the barriers and facilitators evaluated during and after implementing an intervention to improve the use of off-label drug management strategies.

Data availability

To preserve the anonymity of interviewees, the transcribed interviews are not available for sharing. The remaining data generated or analysed during this study are included in this published article and its supplementary information file.

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Acknowledgements

Thanks to Professor Fei Yin of Xiangya Hospital Central South University for his help in recruiting experts for the interviews.

This research was funded by the Chevidence Lab Child & Adolescent Health of Chongqing Medical University’s Children’s Hospital’s Key Project in 2022 (LY03007).

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Min Meng and Jiale Hu contribute equally.

Authors and Affiliations

Chevidence Lab of Child & Adolescent Health, Children’s Hospital of Chongqing Medical University, Chongqing, China

Min Meng & Yaolong Chen

National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children’s Hospital of Chongqing Medical University, Chongqing, China

Min Meng, Enmei Liu, Qiu Li & Yaolong Chen

Chongqing Key Laboratory of Pediatrics, Chongqing, China

Department of Pharmacy, Gansu Provincial Hospital, Lanzhou, China

Min Meng, Min Tian & Wenjuan Lei

Department of Nurse Anesthesia, Virginia Commonwealth University, Richmond, USA

School of Public Health, Lanzhou University, Lanzhou, China

College of Pharmacy, Gansu University of Chinese Medicine, Lanzhou, China

Department of Nephrology, Children’s Hospital of Chongqing Medical University, Chongqing, China

Research Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences(2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, China

Yaolong Chen

WHO Collaborating Centre for Guideline Implementation and Knowledge Translation, Lanzhou, China

Lanzhou University GRADE Center, Lanzhou, China

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MM and JH are joint first authors. YC and QL designed the study. MM organized all expert interviews with the help of JH and requested experts to examine the interview recordings. XL and MM extracted information and coded in Chinese.WL and XL analyzed the data. MT and ZH translated interview. MM and JH drafted the manuscript. YC and QL revised the article. All authors have read and approved the final manuscript.

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Correspondence to Qiu Li or Yaolong Chen .

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This study was approved by the Research Ethics Committees at Gansu Provincial People’s Hospital (approval number: 2022 − 152). All participants signed the informed consent form. All interviews were conducted anonymously, and all transcripts and other records were kept private. Participants were informed that they could start, refuse, or withdraw from the study without negative consequences.The study was performed in accordance with the Declaration of Helsinki.

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Meng, M., Hu, J., Liu, X. et al. Barriers and facilitators to guideline for the management of pediatric off-label use of drugs in China: a qualitative descriptive study. BMC Health Serv Res 24 , 435 (2024). https://doi.org/10.1186/s12913-024-10860-0

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