The use of patient-reported outcome measures to improve patient-related outcomes – a systematic review
Notice bibliographique
Résumé
BACKGROUND: Patient-reported outcome measures (PROMs) provide invaluable information on patients' health outcomes and can be used to improve patient-related outcomes at the individual, organizational and policy levels. This systematic review aimed to a) identify contemporary applications and synthesize all evidence on the use of PROMs in these contexts and b) to determine characteristics of interventions associated with increased effectiveness. METHODS: Five databases were searched for studies providing quantitative evidence of the impact of PROM interventions. Any study design was permitted. An overall benefit (worsening) in outcome was defined as a statistically significant improvement (deterioration) in either a PROM, patient-reported experience measure or clinical outcome. Study quality was assessed using the Effective Public Healthcare Panacea Project's Quality Assessment Tool for Quantitative Studies. A narrative synthesis was conducted. RESULTS: Seventy-six studies of the 11,121 articles identified met the inclusion criteria. At the individual level, 10 (43%) of 23 studies that fed back PROMs to the patient or healthcare provider showed an improvement in outcome. This percentage increased in studies which used PROMs to monitor disease symptoms and linked these to care-pathways: 17 (68%) of 25 studies using this mechanism showed an improvement. Ten (71%) of 14 studies using PROMs to screen for disease found a benefit. The monitoring and screening approach was most effective using PROMs covering cancer-related, depression and gastro-intestinal symptoms. Three studies found that the mere collection of PROMs resulted in improved outcomes. Another three studies used PROMs in decision aids and found improved decision quality. At the organizational/policy level, none of the 4 studies that used PROMs for benchmarking found a benefit. The three studies that used PROMs for in-depth performance analyses and 1 study in a plan-do-study-act (PDCA) cycle found an improvement in outcome. Studies employing disease-specific PROMs tended to observe improved outcomes more often. There are concerns regarding the validity of findings, as studies varied from weak to moderate quality. CONCLUSIONS: The use of PROMs at the individual level has matured considerably. Monitoring/screening applications seem promising particularly for diseases for which treatment algorithms rely on the experienced symptom burden by patients. Organizational/policy-level application is in its infancy, and performance evaluation via in-depth analyses and PDCA-cycles may be useful. The findings of this review may aid stakeholders in the development and implementation of PROM-interventions which truly impact patient outcomes.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,011 | 0,002 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».