Navigating the Roadblocks: National Patient and Provider Survey on Barriers to Healthcare and Medication Access for Patients with Vasculitis
Bibliographic record
Abstract
Objectives Access to timely diagnosis, specialized care, and medications is critical for managing vasculitis. This study aimed to explore and quantify the barriers to healthcare access faced by patients and healthcare providers. Methods Two quantitative, descriptive surveys were conducted among patients with vasculitis and healthcare providers (HCPs), including rheumatologists, recruited through the Vasculitis Foundation Canada and Canadian Rheumatology Association. The survey assessed experiences related to diagnostic delays, appointment access, and challenges with medication availability. Data collection occurred from September 2022 to June 2023, and responses were analyzed using descriptive statistics. Results The patient survey had an estimated response rate of 72% (n=100, 46% within the ages of 40-64, 80% were female, 88% were White, 82% had a drug coverage plan). The HCP survey had an estimated response rate of 76% (n=31, 94% were rheumatologists). Diagnostic delays were common, with 66% of patients reporting initial misdiagnoses, and 36% consulting 5 or more doctors before receiving an accurate diagnosis. Of those referred to a rheumatologist, 57% waited more than 1 month for an appointment, and 11% waited 3-6 months. Key barriers to timely diagnosis identified by providers included a lack of family physicians (74%), long waitlists (58%), and inappropriate referrals (48%). Forty-four percent of patients reported barriers to accessing or using medications, particularly related to adverse effects, out-of-pocket costs, and limited insurance coverage. Majority of patients (70%) reported their drug plan excluded or limited the use of certain medications. Ninety-three percent of providers reporting barriers such as prior authorization requirements and step therapy protocols. Rituximab was the most frequently cited as difficult to access by patients and providers, with insurance denials and high out-of-pocket costs noted to be barriers to treatment initiation. Conclusion Patients with vasculitis face significant barriers to timely care and medication access, including diagnostic delays, long wait times, and insurance-related challenges. Addressing these barriers requires systemic changes in healthcare delivery, including improved access to rheumatologists and streamlined medication approval processes. These findings highlight the need for targeted interventions to enhance vasculitis care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".