https://orcid.org/0000-0001-8973-3400
Abstract
Multi-site research studies redefine cohort studies by simultaneously providing a cross-sectional snapshot of patients and monitoring them over time, to evaluate outcomes. However, careful design is crucial to minimize potential biases, such as seasonal variations, that may arise during the study period. Addressing snapshot study challenges requires strategic solutions: implementing multi-stage sampling for representativeness, providing rigorous data collection training, using translation techniques and content validation for cultural and linguistic appropriateness, streamlining ethical approval processes, and applying comprehensive data management for follow-up and missing data. These strategies can optimize the efficacy and ethicality of snapshot studies.
Define the snapshot study design
Understand advantages and limitations of snapshot study design
Understand strategies to minimize potential biases of snapshot study
Understand approaches that promote the methodology of snapshot study
Introduction
Heart failure (HF) is a final common pathway of many cardiovascular conditions and the most common and burdensome non-communicable disease internationally. Due to limitations of knowledge, technology, and resources, cardiovascular disease is the leading cause of death in low- and middle-income countries. In Thailand, ∼1 million people with 100 000 new cases within one year are diagnosed with HF.
Recent trends in globalization and development have led to a rapid epidemiological transition in the region.1 The snapshot study was implemented to explore patients with HF characteristic including demographic clinical status, patients’ experience, and perspective. The snapshot study provided difference methodology than transitional cohort study. For instance, one epidemiologic study of HF that has been conducted in Thailand used retrospective cohort study, some time ago: The Thai ADHERE study conducted by Laothavorn et al. in 20102. The study used the same protocol as the US ADHERE Registry. The aim of this study was to assess the database of hospitalized patients with the diagnosis of HF or acute decompensated HF in Thailand in terms of patient characteristics, clinical presentations, and causes of HF, precipitating causes of HF, hospital course, management, and hospital outcomes.
The Thai ADHERE provided critical information about HF management and outcomes in Thailand. The results of this study are helpful to provide information on practice guideline recommendations, the development of new interventions, and healthcare policy and system planning, in order to support improve the outcomes of patients with HF in Thailand. Thai ADHERE study, however, was not without limitations. Firstly, study settings were limited to only hospitals in the Bangkok metropolitan area and explored only cardiac centres in tertiary and university hospitals, ignoring primary, secondary, and non-cardiac centre hospitals. This may limit the generalizability to national populations. Secondly, the data collection used routinely collected clinical data, obtained from chart audit. Secondary data sources may provide vast amounts of information, but the quantity was not synonymous with the appropriateness of research objectives and the researcher may lack control over data quality.3 Thirdly, the lack of information from the patient's perspective may limit researchers in order to more fully assess and understand the quality of care so patient-reported outcome and patient-reported experience measures are crucial for measuring patient's perception of the healthcare they have received.
In Australia, researchers implemented the NSW Heart Failure Snapshot Study to obtain a representative, ‘real-world’ cross-sectional view of patients with acute HF and their management including demographic characteristics, medical history, clinical findings at presentation, clinical management (including pathology and cardiac investigations), acute treatment, admission and discharge medications, lengths of stay, and outcome of hospitalization (including clinical status at discharge and mortality), information on specific comorbidities, frailty (aging-related syndrome of physiological decline), depression, medication adherence, and performance status.4 Researchers followed patients 30 days after discharge from hospital, which was considered as the critical period of patients with HF after discharge from hospital.5
The objective of this methods corner paper is to discuss snapshot methods emphasizing on the difference of snapshots methodology compared with traditional cohort studies, their benefits and limitations, and some practical insights emphasizing low and middle incomes perspectives.
Overview of the snapshot methodology
Identify the setting and study population
During the research design phase, the investigator first defines a target population based on specific inclusion and exclusion criteria pertinent to the research question. Subsequently, an accessible population is selected, one that is both geographically and temporally convenient.6 Following this, the investigator is tasked with formulating a sampling strategy, ideally using probability sampling, and developing methods to recruit and retain participants. These steps are crucial in ensuring that the sample is representative of the target population.6
For this snapshot study, prospective consecutive recruitment might offer advantages. This method does not necessitate prior enumeration of the population, making it a fitting choice for the selected settings: one super tertiary care facility and four tertiary hospitals. These settings were chosen via purposive sampling, driven by practical and pragmatic limitations such as time, budget, and the availability of research assistants. Prospective consecutive recruitment, which involves enrolling participants in a specific order, has the potential to capture seasonal or temporal changes over a longer recruitment period. However, potential limitations, such as biases and reduced generalizability due to the order of enrollment, should be considered.6 Despite these challenges, this method might present a viable solution for recruiting and maintaining a representative group of participants across different hospital settings and regions. The study settings spanned four regions: Northern, Southern, Central, and Bangkok.
Research staff preparation
Research staff preparation is an important aspect of ensuring the quality and validity of research findings to the same standard, and this process may vary depending on the required procedures in each study.7 Especially for the snapshot study that required data collection in multiple settings, the research staff who work at site locations need to be prepared. The preparation process was developed and presented in Table 1.
Research staff preparation for the snapshot study
| Phase | Preparation detail |
|---|---|
| Selecting Research staff | To ensure the ethical conduct of data collection, research staff were required to meet education, experience, and training requirements. Our study required to have a minimum of a master’s degree in nursing, at least 5 years of experience in cardiovascular nursing, and experience in research, such as publishing or presenting at conferences. Research staff were also required to complete a Health Insurance Portability and Accountability Act (HIPAA) training and ethical considerations in research with humans from the Collaborative Institutional Training Initiative (CITI) programme, and be familiar with the study procedures, such as informed consent, confidentiality, data security, and reporting of adverse events. |
| Review of quantitative methods | Research staff were required to have a basic understanding of the quantitative methods used in the study, such as the study design, sampling strategy, data collection instruments, data quality assurance, and data analysis plan, and be able to explain the purpose and objectives of the study to the participants and stakeholders. |
| Pretesting and Fieldwork training | Research staff had to undergo the pretesting for the data collection to ensure the validity, reliability, and cultural appropriateness. Research staff would be evaluated by reviewing 10 medical records and recording the data on the questionnaire. Then, the principal investigator checked for inter-rater agreement, reviewed the results, and provided feedback to the research staff. |
| Ongoing supervision and support | Research staff would receive ongoing supervision and support from the research team and principal investigator throughout the data collection process, such as regular meetings, monitoring, feedback, and troubleshooting. They would be able to report any issues or concerns that may arise during data collection and seek guidance when needed. |
| Phase | Preparation detail |
|---|---|
| Selecting Research staff | To ensure the ethical conduct of data collection, research staff were required to meet education, experience, and training requirements. Our study required to have a minimum of a master’s degree in nursing, at least 5 years of experience in cardiovascular nursing, and experience in research, such as publishing or presenting at conferences. Research staff were also required to complete a Health Insurance Portability and Accountability Act (HIPAA) training and ethical considerations in research with humans from the Collaborative Institutional Training Initiative (CITI) programme, and be familiar with the study procedures, such as informed consent, confidentiality, data security, and reporting of adverse events. |
| Review of quantitative methods | Research staff were required to have a basic understanding of the quantitative methods used in the study, such as the study design, sampling strategy, data collection instruments, data quality assurance, and data analysis plan, and be able to explain the purpose and objectives of the study to the participants and stakeholders. |
| Pretesting and Fieldwork training | Research staff had to undergo the pretesting for the data collection to ensure the validity, reliability, and cultural appropriateness. Research staff would be evaluated by reviewing 10 medical records and recording the data on the questionnaire. Then, the principal investigator checked for inter-rater agreement, reviewed the results, and provided feedback to the research staff. |
| Ongoing supervision and support | Research staff would receive ongoing supervision and support from the research team and principal investigator throughout the data collection process, such as regular meetings, monitoring, feedback, and troubleshooting. They would be able to report any issues or concerns that may arise during data collection and seek guidance when needed. |
Research staff preparation for the snapshot study
| Phase | Preparation detail |
|---|---|
| Selecting Research staff | To ensure the ethical conduct of data collection, research staff were required to meet education, experience, and training requirements. Our study required to have a minimum of a master’s degree in nursing, at least 5 years of experience in cardiovascular nursing, and experience in research, such as publishing or presenting at conferences. Research staff were also required to complete a Health Insurance Portability and Accountability Act (HIPAA) training and ethical considerations in research with humans from the Collaborative Institutional Training Initiative (CITI) programme, and be familiar with the study procedures, such as informed consent, confidentiality, data security, and reporting of adverse events. |
| Review of quantitative methods | Research staff were required to have a basic understanding of the quantitative methods used in the study, such as the study design, sampling strategy, data collection instruments, data quality assurance, and data analysis plan, and be able to explain the purpose and objectives of the study to the participants and stakeholders. |
| Pretesting and Fieldwork training | Research staff had to undergo the pretesting for the data collection to ensure the validity, reliability, and cultural appropriateness. Research staff would be evaluated by reviewing 10 medical records and recording the data on the questionnaire. Then, the principal investigator checked for inter-rater agreement, reviewed the results, and provided feedback to the research staff. |
| Ongoing supervision and support | Research staff would receive ongoing supervision and support from the research team and principal investigator throughout the data collection process, such as regular meetings, monitoring, feedback, and troubleshooting. They would be able to report any issues or concerns that may arise during data collection and seek guidance when needed. |
| Phase | Preparation detail |
|---|---|
| Selecting Research staff | To ensure the ethical conduct of data collection, research staff were required to meet education, experience, and training requirements. Our study required to have a minimum of a master’s degree in nursing, at least 5 years of experience in cardiovascular nursing, and experience in research, such as publishing or presenting at conferences. Research staff were also required to complete a Health Insurance Portability and Accountability Act (HIPAA) training and ethical considerations in research with humans from the Collaborative Institutional Training Initiative (CITI) programme, and be familiar with the study procedures, such as informed consent, confidentiality, data security, and reporting of adverse events. |
| Review of quantitative methods | Research staff were required to have a basic understanding of the quantitative methods used in the study, such as the study design, sampling strategy, data collection instruments, data quality assurance, and data analysis plan, and be able to explain the purpose and objectives of the study to the participants and stakeholders. |
| Pretesting and Fieldwork training | Research staff had to undergo the pretesting for the data collection to ensure the validity, reliability, and cultural appropriateness. Research staff would be evaluated by reviewing 10 medical records and recording the data on the questionnaire. Then, the principal investigator checked for inter-rater agreement, reviewed the results, and provided feedback to the research staff. |
| Ongoing supervision and support | Research staff would receive ongoing supervision and support from the research team and principal investigator throughout the data collection process, such as regular meetings, monitoring, feedback, and troubleshooting. They would be able to report any issues or concerns that may arise during data collection and seek guidance when needed. |
Consideration of cultural and language of the questionnaire
Cultural differences can influence responses in self-reported measures due to varying interpretations of concepts.8 When adjusting measures for a new population, researchers must ensure conceptual adequacy and equivalence, reevaluate items reliant on cultural assumptions, and affirm psychometric validity, despite the potential for additional time and effort, to guarantee a fair comparison across cultural groups.8 The Snapshot HF questionnaire, originally in English, required translation into Thai to gather data from Thai patients with HF. The back-translation technique was employed,9 involving two bilingual translators—one translating from English to Thai, and the other blindly retranslating from Thai to English. The two versions were compared for congruity between the original and target languages.
Given social and cultural disparities, certain components of the questionnaire were modified. As this study was conducted in Thailand, where ethnic diversity is less pronounced, we excluded factors like ethnicity, language spoken, and country of birth. This decision aligns with the 2015 census data, which show that Thai ethnicity constituted most of the population (90.32%). Moreover, 9.68% of the population in Thailand, associated with ethnic groups in highland areas, represents more than 1.2 million people dispersed and settled across different regions. Most of these people reside in remote and conserved areas, islands, and border areas, experiencing continuous displacement and resettlement.10 Furthermore, our inclusion criteria necessitated that participant be capable of speaking and writing in Thai. Conversely, elements such as marital status, healthcare coverage, religion, educational attainment, income, depression screening tools, and adherence (using a validated adherence questionnaire) were incorporated into the Snapshot HF study questionnaire.
Protection of human participants
Since the snapshot study required a representative sample of the target population to reflect its characteristics and diversity, the researchers need simplified and universally agreed-upon regulations to ensure the rights, dignity, and well-being of participants.11 In this study, researchers ensured the rights of the human participants in terms of three aspects: potential risks, benefits, and data confidentiality. The researcher proceeded according to procedure in requesting approval for the human research of each participating hospital. This process took more than 6 months in Thailand, where each hospital had its own ethics committee to acknowledge the differences in practice and regulation. The study did not pose any risk to the participants; however, it required some of their time and attention. Researchers requested all participants to provide inform consent. During data collection, some patients presented with symptoms exacerbation such as dyspnoea and fatigue, so researchers have to exclude patients from the study. In addition, some of them were not able to complete the questionnaire by themselves so researchers have to read and complete the questionnaire based on patients answer. This data collection process may develop selection and performance bias.
Outcome ascertainment
The nature of variables and precision in measurements crucially impact study outcomes, with standardization and bias reduction tactics bolstering data reliability.8 Using remote platforms, such as web-based questionnaire platforms, wearable electronics monitors, or telehealth, for data collection balances rigorous research with participant convenience and resource management, enhancing study flexibility.8 In this prospective cohort study on 30-day post-discharge hospital readmissions, researchers defined outcomes as readmissions due to HF symptom exacerbation. Researchers ensured outcome completeness through active follow-ups every patient via phone calls at 15 and 30 days post-discharge consecutively, and passive ascertainment using the hospital database system.
Data management
Similarly, to a regular database, snapshot study may face missing or incomplete data due to various reasons, including (i) incorrect or missing data values because of data entry errors, (ii) inconsistent value-naming conventions because of entry formats, and (iii) incomplete information because data are not captured or available. Snapshot studies often involve multiple sites that may have different data formats, standards, or definitions. For example, different hospitals may use different diagnostic codes for the same condition. It could pose some challenges in data aggregation and analysis. Therefore, data management for snapshot studies should include methods for harmonizing and standardizing the data across different sources to ensure data consistency and comparability.12
In addition, since snapshot studies are carried out across different sites in a short period of time, handling missing or incomplete data is crucial to eliminate data errors and inconsistencies and solve the object identity problem. After the data collecting process, the researcher team implemented the data cleaning process before analysing the data. In this study, we had missing in some variables but less than 15% so we used complete-case analysis technique, which only includes the participants with complete data on all waves in the analysis, thereby potentially reducing the precision of the estimates of exposure–outcome associations.13 Utilizing the secure web application for snapshot study would be ideal for creating and managing online surveys and databases for multi-site study. However, our study did not have access to such a tool. Instead, Microsoft Excel was used to store and manage data for each setting separately. Then, the data were merged and analysed using the Statistical Package for the Social Sciences version 25 (IBM Corp., Armonk, NY, USA).
Step-by-step approach—a ‘snapshot’
What is a snapshot research design?
A snapshot study is a cross-sectional view of patients and follows the patients for a certain period of time for the outcome of interest. This design is different from traditional cohort study because it provides more of a real-world view of the population of interest and can be helpful to describe a clinical cohort. For instance, researchers could explore the perception of patients related to the condition or experience that they received during hospitalization. However, researchers have to develop a strong methodology to minimize bias throughout the study design, data collection, and data analysis process (Central illustration).
In study population and setting phase, researchers have to ensure the representativeness of study population and setting. Researchers should clearly define target, source, and study population and identify the inclusion and exclusion criteria. Then, researchers should understand a variety of study settings that may influence the outcome of interest. Our study may introduce the selection bias; however, we tried to cover all regions and different levels of hospitals in Thailand. Then, researchers have to prepare researcher staff in each setting to ensure the quality of data collection process especially reliability and minimize bias. The research staff preparation process can be found in Table 1.
The countries that do not use English as the first language have to ensure the availability of questionnaire being translated to the local language. In case, the questionnaire is not available, the researchers have to use a standard technique for translating. For instance, a back-translation technique where two bilingual translators were selected: one translating from original to local language, the other blindly translating local to original language. The two translators should be fluent in both original and local language, and had experienced related to research topic. Moreover, the questionnaire that contains a cultural sensitivity content requires the researchers to evaluate the content validity to examine the validity on local population.
Several hospitals have their Institutional Review Board and request researchers to separately submit and get approval from individual setting. This multi-site HF snapshot study took 6 months to complete the approval from Institutional Review Board because each hospital had its own ethics committee to acknowledge the differences in practice and regulation. This process could be faster if researchers could locate the proxy person to support and prepare the proposal before submitting to the Institutional Review Board.
Finally, prospective cohort study may have incomplete data issue, so researchers have to use several methods to promote outcome ascertainment, both active and passive. The active ascertainment is directly contacting the participants such as making a call or sending mail or email, while passive ascertainment is indirectly contacting the participants such as using the hospital record or electronic health record. Moreover, researchers have to recheck and clean data before analysing. Then, researcher should also prepare to deal with missing data.
Limitation
Despite the vast benefit of a snapshot, its limitation needs to be considered. Firstly, the snapshot study is sensitive to changes in the population over time. For example, if a study measures the prevalence of the disease in one population, it may not reflect the true disease burden and not include the prevalence that happens after the time of study. This is also relevant for diseases influenced by seasonal variations, such as chronic HF. According to Inglis et al. (2008)14, chronic HF-related morbidity and mortality vary across seasons, with higher rates in winter than in summer. This suggests that relative changes in temperature may affect the health outcomes of HF patients. Therefore, snapshot study may not fully capture the dynamic nature of health outcomes and were biased due to seasonal variation and potential triggers. Additionally, due to its cross-sectional design, the snapshot study may not establish causal relationships or infer directionality between variables, still capturing the data’s fluctuation over a short time. Another limitation of the snapshot study is the limited ability to generalize to other populations or settings as it is conducted in a specific region or country and may not account for the heterogeneity of populations and validity over time.
Conclusion
A multi-site research study provides a new perspective of the cohort study in capturing a cross-sectional view of patients and follows the patients for some period of time. This study may have bias around seasonal variation/timing of the ‘snapshot’. Therefore, researchers should carefully develop a strong study design to minimize the bias that could occur during the study.
Author contributions
Thitipong Tankumpuan and Patricia M. Davidson (Conceptualization), Thitipong Tankumpuan, Suratsawadee Kruahong, and Chitchanok Benjasirisan (Writing—original draft), and Patricia M. Davidson (Writing—review & editing).
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Data availability
All data are incorporated into the article.
References
Author notes
Conflict of interest: none declared.
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