Optimal cancer care entails coordination among multiple providers and continued follow-up and surveillance over time. The patient-centered care brings opportunities to improve the delivery of cancer care. The adoption of patient-centered oncology care (PCOC) is in its infancy. Evidence synthesis on the model’s effectiveness is scant.
This is the first systemic review and meta-analysis on associations of PCOC with cancer patients’ adverse health care utilization, cost, patient satisfaction, and quality of care.
Our study was guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) framework. Quality appraisal was performed using Downs and Black’s quality checklist. Study-level effect sizes of adverse health care utilization were computed using Cohen’s d and summarized using forest plots. Funnel plots were constructed to examine publication bias.
Of 334 studies that were reviewed, 10 met eligibility criteria and were included into the final analysis. Many included studies implemented almost all six of patient-centered care core attributes, plus three additional attributes that specifically addressed cancer patients’ needs, including triage pathways, standardized and evidence-based symptom management, as well as support patient navigation. PCOC patients had lower utilization of inpatient care (standardized means difference [SMD] = −0.027, p = .049). Overall positive effect of PCOC on emergency department use was small and not significant (SMD = −0.023, p = .103). With regard to cost and quality of care, our narrative summaries showed an overall positive direction, though we found limitations in individual study quality that precluded a meta-analysis.
The results showed that it is possible to utilize patient-centered model to support best practice of cancer care. Early evidence shows that the PCOC model has potential to improve health care utilization, cost, and quality of care, but limited numbers of included articles and heterogeneity of those studies implied that more rigorous research is expected to further investigate the model’s effects.