Reassessing the July Effect: 30 Years of Evidence Show No Difference in Outcomes.

Abstract

OBJECTIVE\nTo critically evaluate whether admission at the beginning-versus-end of the academic year is associated with increased risk of major adverse outcomes.\n\n\nSUMMARY BACKGROUND DATA\nThe hypothesis that the arrival of new residents and fellows is associated with increases in adverse patient outcomes has been the subject of numerous research studies since 1989.\n\n\nMETHODS\nWe conducted a systematic review and random-effects meta-analysis of July Effect studies published prior to December 20, 2019, for differences in mortality, major morbidity, and readmission. Given a paucity of studies reporting readmission, we further analyzed 7\u200ayears of data from the Nationwide Readmissions Database to assess for differences in 30-day readmission for US patients admitted to urban teaching-versus-non-teaching hospitals with 3 common medical (acute myocardial infarction, acute ischemic stroke, and pneumonia) and 4 surgical (elective coronary artery bypass graft surgery, elective colectomy, craniotomy, and hip fracture) conditions using risk-adjusted logistic difference-in-difference regression.\n\n\nRESULTS\nA total of 113 studies met inclusion criteria; 92 (81.4%) reported no evidence of a July Effect. Among the remaining studies, results were mixed and commonly pointed toward system-level discrepancies in efficiency. Meta-analyses of mortality (OR[95%CI]: 1.01[0.98-1.05]) and major morbidity (1.01[0.99-1.04]) demonstrated no evidence of a July Effect, no differences between specialties or countries, and no change in the effect over time. A total of 5.98 million patient encounters were assessed for readmission. No evidence of a July Effect on readmission was found for any of the 7 conditions.\n\n\nCONCLUSIONS\nThe preponderance of negative results over the past 30\u200ayears suggests that it may be time to reconsider the need for similarly-themed studies and instead focus on system-level factors to improve hospital efficiency and optimize patient outcomes.