Modifying practices to assess pandemic-era real-world data
The COVID-19 pandemic and related social distancing orders affected large-scale changes in treatment-seeking behaviour in healthcare such as in-person doctor visits and prescription pickups. These changes will bring to the forefront new factors for researchers to consider when conducting real-world studies.
Health researchers leverage real-world data (RWD) from healthcare interactions such as electronic health records, patient surveys, medical claims, prescription refill activity and elective surgery participation to understand population characteristics, as well as the effects and use of interventions on clinical and economic outcomes.
As researchers reflect upon the impact of COVID-19 on RWD, they will need to evaluate pre-pandemic processes to determine if they are still fit for purpose when studying pandemic- era data and make the necessary changes. Moving forward, the pandemic-spurred pattern changes in healthcare will be a crucial consideration when researchers are drawing conclusions based on RWD.
Key factors impacting RWD from the COVID-19 pandemic era
As the COVID-19 pandemic became the catalyst for social distancing orders, in-person doctor visits trended downwards, and the gravitation to virtual telehealth shifted how individuals and hospital facilities addressed their care options.
Individuals may have refilled prescriptions less frequently. Patients and hospitals delayed or cancelled elective surgeries and annual appointments due to the implications from the pandemic. Many who live in rural areas experienced reduced access or loss of medical care due to lay- offs. These shifts in treatment-seeking and treatment-availability have had an impact on RWD which needs to be considered when observing population health trends and drawing conclusions in the future of real-world studies.
The impact of telehealth diagnosis versus in-person visits diagnosis
Telehealth adoption grew during the pandemic as it became an alternative for many providers to continue patient visits, as in- person visits were notably lower (by roughly 20% to 43%). However, there are differences in telehealth compared to in-person visits, which researchers need to consider. For instance, the desire of some individuals to adhere to routine in-person visits may have prevented them from seeking treatment when only telehealth was available.
There may be differences in treatment and diagnosis for patients who use telehealth given the lack of tools and technology to assess them in person. The hesitancy from some patients and providers to start a new therapy without receiving in-person diagnostics, vitals and labs could have impacted a patient receiving a new treatment and diagnosis versus continuing existing treatment plans overall.
Differences in population access to healthcare
Virtual hospital visits reached an all-time high during the height of the pandemic. Telehealth visits surged in March 2020 compared to the baseline January and February 2020, while in April, the percentage of telehealth visits peaked, comprising 17% of all medical visits. However, several factors may have affected patients’ ability to use it.
Access to virtual cases is often reliant on the possession of at least one connected device, a stable internet connection and an understanding of how to use the technology. Patients in under- represented and vulnerable populations such as older, disabled, those located in rural areas or socioeconomically challenged may have been at a disadvantage in this shift to more virtual care due to access issues.
Shifting prescription preferences during the pandemic
There was a general decrease in prescription fills during the pandemic with the highest drop being 12% in April 2020 when compared to the same week a prior year. Patients began to change their modes and channels of prescriptions, as well as treatment formulations such as self-administered forms of common infusion therapies to avoid in-person visits and prescription pickups.
Additionally, many extended their medication fills to mitigate the need for frequent refills. It is crucial to consider these factors in any real-world analysis to avoid missing key exposures by social distancing measures and lifted restrictions on early and long-term fills by insurers.
Other disruptions impacting patient medication regimens are reduced availability of certain products through pharmacies due to shortages, fear of the pandemic, as well as potential amplification of existing health conditions or potentially misusing over-the-counter drugs that offer temporary relief.
Although some of these shifts in behaviours may be isolated to the pandemic time frame as normal care routines return, others, such as telehealth adoption, may remain heightened compared to pre-pandemic trends.
Researchers who look at historical trends for their real-world research will require workarounds to account for the findings on inpatient trends they observe during this era. These findings will impact the RWE they generate that could be used to gain an understanding of population health as well as support future regulatory submissions.
Evolving real-world research practices for the future
The new patterns in care from the past year have continued to generate RWD. Generating reliable RWE when observing pandemic- era behaviour shifts will take process changes that account for their underlying catalysts. Researchers should take steps to ensure the RWE they produce is reflective of the circumstances of the time.
When looking at the population of interest, researchers should describe the population at different points in time, noting those that correspond to the pandemic. This can help put results in the context of those who are seeking care. Additionally, researchers should account for the time period and type of care received, restricting the data to a certain type of care. Alternatively, the data collected during the pandemic could be handled separately from previous and subsequent years to address the effects of the pandemic on outcomes.
Researchers should also consider potential biases among patient populations due to the differential impact of the pandemic on certain subgroups. This will help researchers pinpoint insights that should not be considered reliable from the time period.
Lastly, the inclusion of added population characteristics into the multivariate analyses (ie, care received, diagnosis or evidence of prior or current COVID-19 infection, geographic location of patients and calendar time), as well as other variables affected by the pandemic and COVID-19 infection, can lead to a more comprehensive analysis.
Drawing conclusions that drive actionable insights
Real-world studies are emerging as a resource for understanding population health as well as new product and label expansions. As the prevalence of these studies increases, there is a need to reevaluate the way researchers look at RWD from the time during the pandemic to maintain their reliability.
The impacts of the pandemic on medical care make it pertinent that researchers think critically when designing real-world studies, as well as analysing and interpreting real-world data from this time period.
These strategic shifts in research practices will be essential to draw conclusions that are reflective of the study period. The steps that researchers take to evolve with COVID-19 and other future widespread health events will support the longevity of real-word research methods even as patient behaviours and patterns change.
Matthew W Reynolds is vice president, Real World Evidence, at IQVIA