Quantitative evaluation of two-way referral policies based on PMC index model.

Abstract

Objective: Perfect policy system support is the key to effective work, and policy evaluation can provide theoretical basis for policy revision. This study aims to quantitatively evaluate the two-way referral policy in China and thus improve the policy system of two-way referral.

Methods: This research focuses on 14 two-way referral policies published from 2007 to 2021. Basing on the focus of the two-way referral policy identified by text-mining methods, we constructed a PMC index model containing 9 primary and 43 secondary variables to conduct a quantitative evaluation of the two-way referral policy.

Results: All document types are work notices. The two-way referral policy issued by relevant departments have gradually increased since 2015.The average PMC index of the 14 documents was 5.84, and the policy with the highest PMC index score was the policy P14 issued by Jiangsu province. There are 6 excellent policies, 8 good policies, and no qualified grade policy. The difference in PMC index scores mainly shows the three dimensions of policy clarity, policy content and policy coverage.

Conclusions: This study indicates that the quality of two-way referral policy is generally good, which reveals the factors affecting the policy operability and contributes to expand the research perspective of two-way referral policy evaluation.We also analyzed the advantages and disadvantages of the existing policy of two-way referral through policy evaluation, and provided guidance for subsequent policy revisions.