Objective data are routinely used by physicians when making recommendations for prescription medications, but when making surgical referrals, the decision process is less well defined. Since differences in hospital quality and performance have been shown to affect surgical outcomes, two recent JAMA articles focused on decision rationale and whether outcomes may be improved with evidence-based decision support for surgical referrals.
In one study, Dr Naik, et al conducted a qualitative analysis of primary care physician (PCP) responses at Penn Medicine (Pennsylvania, United States) to assess how decision-making differs for medication recommendations vs referrals to specific surgeons or hospitals. This study found that PCPs used decision support tools with consideration of patient attributes when making prescription medication recommendations, but relied on professional experiences, subjective information on quality, and convenience (eg, location, in-network advantages) when making surgical referrals. The authors suggest that supporting referral decision-making with valid and reliable data on surgeon and hospital quality may reduce variability and improve surgical outcomes.
Furthermore, in an analysis of patients with colorectal cancer by Dr Finn, et al, data-driven hospital selection for patients with colorectal cancer (n=21,098) in Florida, United States was shown to affect outcomes. The primary outcome was mean change in social welfare, which provides an economic assessment by balancing the simulated mortality benefit associated with data-driven hospital selection with costs of care at alternative hospitals. They found that use of procedure-specific hospital performance in hospital selection was associated with improved outcomes overall. Patient social welfare increased by nearly $2,000 and was associated with decreased in-hospital mortality risk. Estimated costs of care increased but were offset by the value of additional life gained due to avoidance of in-hospital mortality. Black patients experienced higher gains in mean social welfare than White patients and a greater decrease in mortality risk by selecting the highest-performing hospital. The authors estimated a societal savings of approximately $9,765,000 if data-driven hospital selection were implemented for a population of 5,000 surgical patients with colorectal cancer. The study supports use of outcomes data by patients and referring physicians to make informed decisions when selecting a hospital and could be used to transform care and guide policy in cancer surgery.
Referring physicians typically rely on subjective evaluations of clinical skill, reputation, and convenience, rather than using volume or outcomes data to guide their recommendations. Dr Naik, et al suggest that the practice of using decision support tools for medication selection is transferrable to the surgical referral process and, and ultimately may improve surgical outcomes by encouraging physicians to refer to objectively higher-quality surgeons or hospitals. Similarly, Dr Finn, et al, suggested that surgical outcomes data can be used to guide policy in cancer care (including surgical referral guidance) for improved outcomes and reduced disparities. Providing regular updates on hospital outcomes data can help physicians optimize referrals. Likewise, availability of publicly reported information on surgical outcomes data and hospital performance for individual procedures may help patients weigh their potential outcomes against other considerations to make the optimal choice when selecting a hospital for their procedure.
Interventions to promote selection of higher-quality hospitals for surgical referrals may help to improve outcomes and reduce both disparities and costs. Outcomes data provide a reliable evidence base for decision support tools. Considering publicly reported information on surgical outcomes data and hospital performance for individual procedures may help clinicians and patients weigh their potential outcomes to make the optimal choice when selecting a hospital for their procedure.