Telehealth Implementation in Federally Qualified Health Centers During the COVID-19 Pandemic: Changes to Care Provision
Bibliographic record
Abstract
Background During the COVID-19 pandemic, federally qualified health centers (FQHCs) experienced rapid telehealth adoption, which drastically shifted how FQHCs delivered care to underserved patients. While studies indicate clinicians and patients would like to continue to use telehealth after the pandemic, questions remain about telehealth care quality, and there are opportunities for improvement in FQHCs. Objective The aim of this paper is to explore changes to care provision that occurred in FQHCs between 2020 and 2021 and identify opportunities to address challenges and maximize benefits as virtual care evolves. Methods A total of 15 semistructured interviews were conducted with clinic personnel (leaders, physicians, and staff) at 2 FQHCs in Northern California, between December 2020 and April 2021, to examine telehealth adoption and use of 2 synchronous modalities (audio-video and audio-only or phone) during the pandemic. Results Physicians and staff reported several positive changes as a result of using telehealth, including increases in patient reach, reductions in no-show rates, and an improved ability to discuss specific medications that patients generally have nearby for reference at home. Other changes occurring during telehealth use had mixed or negative impacts on care provision. For example, the elimination of body language cues, a reduction in the amount of information exchanged, and a reported reduced ability to develop and foster interpersonal connections affected the patient-physician relationship. Respondents also described distractions that were present in some virtual appointments, such as background noise, interruptions, or when patients were multitasking (ie, cooking and cleaning). Modifications to clinic workflow and care processes were reported as well, including the need to triage appointment types (in person vs virtual), and to conduct previsit intake interviews by phone. Clinics developed work-arounds for addressing social and nonmedical needs, such as mailing or emailing resources or pamphlets to patients or providing referrals and support by phone. Respondents also described additional considerations or processes to address newfound privacy needs of telehealth, including confirming whether patients were in a private space during the visit, switching from video to phone visits to increase privacy if necessary, and requesting follow-up from physicians if the patient was unable to share pertinent information due to a lack of privacy during a virtual appointment. Conclusions Telehealth implementation in FQHCs required modifications to care processes and impacted the patient-physician relationship. These findings highlight unique challenges and opportunities for disseminating and sustaining telehealth in settings that deliver care to safety net populations. Guidelines and evidence-based practices are needed to improve telehealth use in FQHCs, including strategies to increase information exchange during virtual appointments and support interpersonal connections between patients and physicians. The following are also needed: best practices for how clinics can most effectively triage virtual appointments; protocols to further mitigate privacy issues and decrease distractions during telehealth appointments; and identifying when telehealth can best supplement in-person care to improve patient outcomes and clinic efficiency. Conflicts of Interest None declared.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".