‘Waiting for’ and ‘waiting in’ public and private hospitals: a qualitative study of patient trust in South Australia
Notice bibliographique
Résumé
BACKGROUND: Waiting times for hospital appointments, treatment and/or surgery have become a major political and health service problem, leading to national maximum waiting times and policies to reduce waiting times. Quantitative studies have documented waiting times for various types of surgery and longer waiting times in public vs private hospitals. However, very little qualitative research has explored patient experiences of waiting, how this compares between public and private hospitals, and the implications for trust in hospitals and healthcare professionals. The aim of this paper is to provide a deep understanding of the impact of waiting times on patient trust in public and private hospitals. METHODS: A qualitative study in South Australia, including 36 in-depth interviews (18 from public and 18 from private hospitals). Data collection occurred in 2012-13, and data were analysed using pre-coding, followed by conceptual and theoretical categorisation. RESULTS: Participants differentiated between experiences of 'waiting for' (e.g. for specialist appointments and surgery) and 'waiting in' (e.g. in emergency departments and outpatient clinics) public and private hospitals. Whilst 'waiting for' public hospitals was longer than private hospitals, this was often justified and accepted by public patients (e.g. due to reduced government funding), therefore it did not lead to distrust of public hospitals. Private patients had shorter 'waiting for' hospital services, increasing their trust in private hospitals and distrust of public hospitals. Public patients also recounted many experiences of longer 'waiting in' public hospitals, leading to frustration and anxiety, although they rarely blamed or distrusted the doctors or nurses, instead blaming an underfunded system and over-worked staff. Doctors and nurses were seen to be doing their best, and therefore trustworthy. CONCLUSION: Although public patients experienced longer 'waiting for' and 'waiting in' public hospitals, it did not lead to widespread distrust in public hospitals or healthcare professionals. Private patients recounted largely positive stories of reduced 'waiting for' and 'waiting in' private hospitals, and generally distrusted public hospitals. The continuing trust by public patients in the face of negative experiences may be understood as a form of exchange trust norm, in which institutional trust is based on base-level expectations of consistency and minimum standards of care and safety. The institutional trust by private patients may be understood as a form of communal trust norm, whereby trust is based on the additional and higher-level expectations of flexibility, reduced waiting and more time with healthcare professionals.
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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 | 0,012 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,011 | 0,011 |
| Communication savante | 0,005 | 0,006 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».