title: Appointment "no-shows" are an independent predictor of subsequent quality of care and resource utilization outcomes.
abstract: 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.
  
  
  OBJECTIVE
  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.
  
  
  METHODS
  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.
  
  
  METHODS
  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.
  
  
  METHODS
  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.
  
  
  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.
authors.affiliation: Tufts University School of Medicine, Boston, MA, USA. andrewshwang86@gmail.com.
authors.forename: Andrew S
authors.initials: AS
authors.lastname: Hwang
authors.affiliation: Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Atlas
authors.affiliation: Lab of Computer Science, Massachusetts General Hospital, Boston, MA, USA.
authors.forename: Patrick
authors.initials: P
authors.lastname: Cronin
authors.affiliation: Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
authors.forename: Jeffrey M
authors.initials: JM
authors.lastname: Ashburner
authors.affiliation: Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
authors.forename: Sachin J
authors.initials: SJ
authors.lastname: Shah
authors.affiliation: Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
authors.forename: Wei
authors.initials: W
authors.lastname: He
authors.affiliation: Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
authors.forename: Clemens S
authors.initials: CS
authors.lastname: Hong
mesh_terms: D000328:Adult; D000368:Aged; D001071:Appointments and Schedules; D002908:Chronic Disease; D055088:Early Detection of Cancer / Q000592:standards / Q000706:statistics & numerical data; D005260:Female; D005500:Follow-Up Studies; D005544:Forecasting; D006295:Health Resources / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D000067455:No-Show Patients; D011320:Primary Health Care / Q000379:methods / Q000592:standards*; D011787:Quality of Health Care / Q000592:standards*; D016896:Treatment Outcome
keywords: Health disparities; Identification of high-risk patients; No-show; Psychosocial issues in healthcare