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Real-World Evidence Generation
Published in Kelly H. Zou, Lobna A. Salem, Amrit Ray, Real-World Evidence in a Patient-Centric Digital Era, 2023
Joseph S. Imperato, Joseph P. Cook, Diana Morgenstern, Kim Gilchrist, Tarek A. Hassan, Jorge Saenz, Danute Ducinskiene
In contrast, observational study is a type of study in which individuals are observed or certain outcomes are measured (National Cancer Instittue, 2022). No attempt is made to affect the outcome (for example, no treatment is given.) As such, observational data are the essence of “real world.” Observational studies are non-experimental in nature, and thus their role and validity has been a controversial topic in the literature (Collins and Bowman 2020). Nonetheless, observation-based studies can suggest important areas for RCTs, hypothesis generation or clarify our understanding of patient experience. They can do so by utilizing various designs including case report or case series, ecologic, cross-sectional (i.e., a prevalence study), case-control and cohort studies (Kumar and Khan 2014).
Special Topics
Published in Douglas D. Gunzler, Adam T. Perzynski, Adam C. Carle, Structural Equation Modeling for Health and Medicine, 2021
Douglas D. Gunzler, Adam T. Perzynski, Adam C. Carle
In many of the applications in this textbook, we have used complex and messy observational data such as data extracted from electronic health records. The data was preprocessed in order to handle some of the messiness. For example, identified data errors were modified or removed. Codes and lab values were evaluated for consistencies and inconsistencies in diagnoses in helping to define study samples. Given a reasonably cleaned data set, a researcher has to be extremely prudent about what questions can be asked and answered with the available data (Box 15.1). Taksler and colleagues have provided a helpful introduction to many of these considerations in their manuscript on the challenges of working with electronic health record data [1].
Field Methods for Patient Ergonomics
Published in Richard J. Holden, Rupa S. Valdez, The Patient Factor, 2021
Researchers could carry out observations physically, shadowing participants for extended periods of time. Technical advances, such as video recordings and wearable cameras, have enabled longer and more unobtrusive observations (see Chapter 12 in this volume). Observational data are exceedingly rich, providing a wealth of information about the environment and work as it is done. A significant barrier for this methodology is participant acceptance of the observational method—whereas some participants might be happier wearing a camera for hours, some others are more comfortable with a shorter duration of a human observer shadowing them. The benefit to the participant should be carefully weighed against the logistics of the observation. The consent of other people who may be observed with the participant, such as family and friends, may also be required before the observation can be undertaken. The presence of a researcher may also trigger the observer effect (McCambridge et al., 2014), wherein participants behave differently compared to normal due to the knowledge that they are being observed.
Pharmacotherapy for stroke prevention in nonvalvular atrial fibrillation: current strategies and future directions
Published in Expert Opinion on Pharmacotherapy, 2022
Antonio Gómez-Outes, M Luisa Suárez-Gea, Alejandro-Isidoro Pérez-Cabeza, Jose Manuel García-Pinilla
Currently there are also many data in real practice, all of which have the limitations inherent to observational data. A meta-analysis of 88 cohort studies evaluated DOACs and VKAs for the prevention of stroke and other thromboembolic events in 3.4 million patients (2.9 million patient-years of follow-up) [24]. The mean age of the patients in the studies was in the range of 57 to 87 years, with a mean CHA2DS2-VASc score between 0.98 and 6.00. The meta-analysis showed results consistent with those obtained in clinical trials regarding stroke (at least similar effectiveness than VKAs), major bleeding and ICH (lower risk with DOACs compared with VKAs in most of the included studies) [24]. Also, overall mortality, with DOACs was at least similar to or better than that reported with warfarin in this and other available meta-analyses in real practice [24–26].
Ethnographic research in healthcare – patients and service users as participants
Published in Disability and Rehabilitation, 2021
The way in which observational data are recorded should be considered. Information can be video, or audio recorded, or the researcher can take field notes. Field notes are the most common form of recording observational data. The participants need to be able to trust the researcher for the relationship to work. This can be done by not keeping the data secret. Costley and Gibbs [37] suggest that “moral trusting” is a good way to care for the participants and promote the researcher’s integrity. This should help to reduce the feeling that the research is a “spy”! The description of events during observation needs to provide the context. If the group interactions and the observation of these occur in one setting, a floor plan of the location is useful to provide context to the reader [14]. This could be a healthcare or a social setting when observing a patient group.
The Rise of Endovascular Mechanical Circulatory Support Use for Cardiogenic Shock and High Risk Coronary Intervention: Considerations and Challenges
Published in Expert Review of Cardiovascular Therapy, 2021
Benjamin Schwartz, Pankaj Jain, Michael Salama, Navin K. Kapur
Two recent developments will undoubtedly aid in the generation of robust, randomized clinical evidence regarding mechanical support devices. The first is the development of the Society for Cardiovascular Angiography and Intervention (SCAI) cardiogenic shock classification system [55]. The rationale underpinning this system is a recognized need to accurately and quickly classify patients for the purposes of prognostication, referral, and rational clinical trial design and interpretation. The system has subsequently been shown in multiple settings to be predictive of clinical outcome [56–58]. Application of the SCAI classification system into randomized trial design will ensure enrollment of patient populations that are both homogeneous and most likely to benefit clinically from mechanical support. The second development is the establishment of large-scale observational registries that incorporate detailed clinical, hemodynamic, and outcomes data [48,56,59]. These observational data will serve to generate the hypotheses that subsequently inform rational design of randomized trials.