Primary Care Referrals for Suspected Hematologic Malignancies: Incidence, Factors Affecting Choice of Specialist, and Flow of Referral Information.
Notice bibliographique
Résumé
Abstract Abstract 3830 Background: Although the primary care physician (PCP) is often the first point of contact for patients with suspected hematologic malignancy, little is known about hematologic referrals from primary care, including their frequency, the factors that affect choice of specialist, and the quality of information exchanged. Methods: In April 2010, we administered a 34-item questionnaire to a random sample of 190 physicians in the state of Massachusetts identified as PCPs (family practice, general practice, or internal medicine) in the American Medical Association's physician file. PCPs were given the opportunity to complete the survey via post or Internet. An additional mailing was sent to non-respondents, followed by at least two attempts at telephone contact. Physicians were asked for the approximate number of patients seen in the past year with suspected hematologic malignancy, the frequency of formal specialty referral, and informal “curbside” referral. PCPs were also queried about the factors that influence their choice of specialist, and about the information exchange with the specialist; these measures were then analyzed by self-reported PCP characteristics using chi-square statistics. Results: As of August, 2010, 118 physicians had responded (response rate = 62.1%). 67.8% identified themselves as internists, and 61.9% were male. The median reported patient panel size during the prior 12 months was 1800; median percentage of patients ≥ 65 years was 30.0%; median percentage of patients in managed care was 55.0%; and median year of graduation from residency, 1996. PCPs were evenly distributed with respect to academic affiliation (from no affiliation to full-time faculty). The median number (IQR) of patients in the prior 12 months who were suspected of having hematologic malignancy was 5 (3, 10). Among suspected hematologic malignancies, the median number formally referred to a specialist (hematologist or surgeon) was 5 (3, 10), and the median number who received informal “curbside” consult was 0 (0, 0.5). Respondents rated the importance of several factors in their choice of specialist (1 = not important at all to 5 = extremely important). Those factors rated ≥ 3 included reputation of specialist/facility (94.9%), patient's preference for site of care (92.4%), distance of site from patient's home (89.8%), specialist's affiliation with a cancer center (88.1%), practice's affiliation with specialist (82.2%), personal relationship with specialist (79.7%), patient's ability to pay (67.0%), and availability of clinical trials at the referral site (63.6%). The following table summarizes responses to questions about flow of referral information and follow-up: Conclusions: Consultation for suspected hematologic malignancy from PCPs is relatively infrequent, tends to manifest through formal referral as opposed to informal discussion, and is most often affected by specialist reputation and patient preference for site of care. Only about half of our respondents reported providing the specialist with a referral letter or email, which may result in poor quality of referral information. Alternately, a high number reported giving a copy of abnormal test results to their patients to bring to the specialist, which may ameliorate this issue and reflect an ongoing evolution in the patient/provider partnership. Moreover, fairly often, patients have not been to see the specialist upon follow-up with their PCP. This finding seems to reflect patient cancellations rather than a failure in physician systems, suggesting that increases in patient education and personalized follow-up may be the best approach to ensure completion of timely hematologic referrals. Disclosures: No relevant conflicts of interest to declare.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».