P006 DISCORDANCE OF COMMUNICATION PRIORITIES BETWEEN HEALTHCARE PROFESSIONALS AND PATIENTS WITH ULCERATIVE COLITIS: RESULTS OF A GLOBAL ULCERATIVE COLITIS NARRATIVE SURVEY
Bibliographic record
Abstract
The Ulcerative Colitis (UC) Narrative is a global survey of patients (pts) and gastroenterology physicians (GIs) aimed at identifying the impact of the disease and comparing and contrasting perceptions of UC burden and management approaches. We describe the prioritization of topics for discussion at routine appointments from pt and GI perspectives, and examine the potential impact of any discordance. Data are presented from 2100 pts and 1254 GIs in Australia, Canada, Finland, France, Germany, Italy, Japan, Spain, the UK, and the USA. Surveys were conducted online and by phone by The Harris Poll between August 2017 and February 2018. Eligible adult pts with UC (confirmed by endoscopy) were those who had visited a GI in the previous 12 months and had ever received prescription medication for UC. Self-reported medication history was used as a proxy for disease severity, with pts with moderate to severe UC defined as pts who had ever taken immunosuppressants, tumor necrosis factor inhibitors, other biologics, or corticosteroids for >4 of the past 12 months. Pts who had only ever taken 5-aminosalicylates or had a colectomy were excluded. Eligible GIs were those who saw ≥10 UC pts each month (≥5 in Japan), of whom ≥10% were taking a biologic and did not practice in a long-term care facility or hospice. Data are presented from all respondents who consented and completed the survey. Pts were a mean age of 40.8 years (standard deviation [SD] 12.4), 53% were male, and 82% had moderate to severe UC, with 67% considering their UC to be controlled with few to no symptoms. Survey responses showed some overlap between pts and GIs in their priorities for discussion at routine appointments. The top priorities selected for pts were discussions on ‘ability to manage symptoms’ (32%), ‘symptoms/problems experienced since last visit’ (29%), ‘how to control inflammation’ (29%), and ‘cancer risk’ (24%), while GIs’ highest priorities for discussion included ‘symptoms since last visit’ (53%), ‘ability to manage symptoms’ (40%), and ‘side effects of current treatment’ (40%). The greatest discordance between pt and GI prioritization was observed for cancer risk (24% vs 11%), fatigue management (16% vs 5%), emotional impact (13% vs 7%), and new medications (21% vs 15%). Both pts (63%) and GIs (79%) wish they had more time at appointments. Symptom control is a high priority for discussion among pts with UC and GIs, but other topics such as cancer risk, fatigue management, emotional impact, and new medications were viewed as less of a priority for GIs than for pts. GIs need to be mindful of those topics of greatest concern to the pt, and identify ways to discuss topics important to both parties, since shortage of appointment time is a barrier to communication.
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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 | 0.008 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".