Background: Identifying individuals at high risk for suboptimal outcomes is an important goal of healthcare delivery systems. Appointment no-shows may be an important risk predictor.
Objectives: To test the hypothesis that patients with a high propensity to "no-show" for appointments will have worse clinical and acute care utilization outcomes compared to patients with a lower propensity.
Design: We calculated the no-show propensity factor (NSPF) for patients of a large academic primary care network using 5 years of outpatient appointment data. NSPF corrects for patients with fewer appointments to avoid over-weighting of no-show visits in such patients. We divided patients into three NSPF risk groups and evaluated the association between NSPF and clinical and acute care utilization outcomes after adjusting for baseline patient characteristics.
Participants: A total of 140,947 patients who visited a network practice from January 1, 2007, through December 31, 2009, and were either connected to a primary care physician or to a primary care practice, based on a previously validated algorithm.
Main measures: Outcomes of interest were incomplete colorectal, cervical, and breast cancer screening, and above-goal hemoglobin A1c (HbA1c) and low-density lipoprotein (LDL) levels at 1-year follow-up, and hospitalizations and emergency department visits in the subsequent 3 years.
Key results: Compared to patients in the low NSPF group, patients in the high NSPF group (n=14,081) were significantly more likely to have incomplete preventive cancer screening (aOR 2.41 [2.19-.66] for colorectal, aOR 1.85 [1.65-.08] for cervical, aOR 2.93 [2.62-3.28] for breast cancer), above-goal chronic disease control measures (aOR 2.64 [2.22-3.14] for HbA1c, aOR 1.39 [1.15-1.67] for LDL], and increased rates of acute care utilization (aRR 1.37 [1.31-1.44] for hospitalization, aRR 1.39 [1.35-1.43] for emergency department visits).
Conclusions: NSPF is an independent predictor of suboptimal primary care outcomes and acute care utilization. NSPF may play an important role in helping healthcare systems identify high-risk patients.
Keywords: Health disparities; Identification of high-risk patients; No-show; Psychosocial issues in healthcare.