Literature DB >> 25776581

Appointment "no-shows" are an independent predictor of subsequent quality of care and resource utilization outcomes.

Andrew S Hwang1, Steven J Atlas2, Patrick Cronin3, Jeffrey M Ashburner2, Sachin J Shah2, Wei He2, Clemens S Hong2.   

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.
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.

Entities:  

Keywords:  Health disparities; Identification of high-risk patients; No-show; Psychosocial issues in healthcare

Mesh:

Year:  2015        PMID: 25776581      PMCID: PMC4579240          DOI: 10.1007/s11606-015-3252-3

Source DB:  PubMed          Journal:  J Gen Intern Med        ISSN: 0884-8734            Impact factor:   5.128


  22 in total

1.  Is this "my" patient? Development and validation of a predictive model to link patients to primary care providers.

Authors:  Steven J Atlas; Yuchiao Chang; Thomas A Lasko; Henry C Chueh; Richard W Grant; Michael J Barry
Journal:  J Gen Intern Med       Date:  2006-09       Impact factor: 5.128

2.  A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.

Authors:  M E Charlson; P Pompei; K L Ales; C R MacKenzie
Journal:  J Chronic Dis       Date:  1987

3.  Success of automated algorithmic scheduling in an outpatient setting.

Authors:  Patrick R Cronin; Alexa Boer Kimball
Journal:  Am J Manag Care       Date:  2014-07       Impact factor: 2.229

4.  Impact of peer health coaching on glycemic control in low-income patients with diabetes: a randomized controlled trial.

Authors:  David H Thom; Amireh Ghorob; Danielle Hessler; Diana De Vore; Ellen Chen; Thomas A Bodenheimer
Journal:  Ann Fam Med       Date:  2013 Mar-Apr       Impact factor: 5.166

5.  Trends in complexity of diabetes care in the United States from 1991 to 2000.

Authors:  Richard W Grant; Paul A Pirraglia; James B Meigs; Daniel E Singer
Journal:  Arch Intern Med       Date:  2004-05-24

6.  A culturally tailored navigator program for colorectal cancer screening in a community health center: a randomized, controlled trial.

Authors:  Sanja Percac-Lima; Richard W Grant; Alexander R Green; Jeffrey M Ashburner; Gloria Gamba; Sarah Oo; James M Richter; Steven J Atlas
Journal:  J Gen Intern Med       Date:  2009-02       Impact factor: 5.128

7.  Missing scheduled visits in the outpatient clinic as a marker of short-term admissions and death.

Authors:  María Martínez Colubi; María Jesús Pérez-Elías; Laura Elías; María Pumares; Alfonso Muriel; Ana Moreno Zamora; Jose Luis Casado; Fernando Dronda; Dolores López; Santiago Moreno
Journal:  HIV Clin Trials       Date:  2012 Sep-Oct

8.  Applying a risk-adjustment framework to primary care: can we improve on existing measures?

Authors:  Amy K Rosen; Robert Reid; Anne-Marie Broemeling; Carter C Rakovski
Journal:  Ann Fam Med       Date:  2003 May-Jun       Impact factor: 5.166

9.  Patient complexity: more than comorbidity. the vector model of complexity.

Authors:  Monika M Safford; Jeroan J Allison; Catarina I Kiefe
Journal:  J Gen Intern Med       Date:  2007-12       Impact factor: 5.128

10.  Patient-physician connectedness and quality of primary care.

Authors:  Steven J Atlas; Richard W Grant; Timothy G Ferris; Yuchiao Chang; Michael J Barry
Journal:  Ann Intern Med       Date:  2009-03-03       Impact factor: 25.391

View more
  41 in total

1.  A missed primary care appointment correlates with a subsequent emergency department visit among children with asthma.

Authors:  Colleen Marie McGovern; Margaret Redmond; Kimberly Arcoleo; David R Stukus
Journal:  J Asthma       Date:  2017-03-02       Impact factor: 2.515

2.  Year-End Clinic Handoffs: A National Survey of Academic Internal Medicine Programs.

Authors:  Erica Phillips; Christina Harris; Wei Wei Lee; Amber T Pincavage; Karin Ouchida; Rachel K Miller; Saima Chaudhry; Vineet M Arora
Journal:  J Gen Intern Med       Date:  2017-02-14       Impact factor: 5.128

3.  Application of Machine Learning to Predict Patient No-Shows in an Academic Pediatric Ophthalmology Clinic.

Authors:  Jimmy Chen; Isaac H Goldstein; Wei-Chun Lin; Michael F Chiang; Michelle R Hribar
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

4.  No-Show Patients and the Triple Aim.

Authors:  Martin F Shapiro
Journal:  J Gen Intern Med       Date:  2015-10       Impact factor: 5.128

5.  Health Care Is Failing the Most Vulnerable Patients: Three Underused Solutions.

Authors:  Danielle H Rochlin; Chuan-Mei Lee; Claudia Scheuter; Terry Platchek; Robert M Kaplan; Arnold Milstein
Journal:  Public Health Rep       Date:  2020-09-22       Impact factor: 2.792

6.  Facilitating Visit Attendance with Staff Reminder Calls in a Safety-Net Clinic.

Authors:  Miamoua Vang; Mark Linzer; Rebecca Freese; Katherine Vickery; Nathan D Shippee; Ellen Coffey
Journal:  J Gen Intern Med       Date:  2020-04       Impact factor: 5.128

7.  Patients' missed appointments in academic family practices in Quebec.

Authors:  Jessica Claveau; Marie Authier; Isabel Rodrigues; Maxime Crevier-Tousignant
Journal:  Can Fam Physician       Date:  2020-05       Impact factor: 3.275

8.  Factors associated with patient no-show rates in an academic otolaryngology practice.

Authors:  Caitlin E Fiorillo; Allyson L Hughes; Chen I-Chen; Philip M Westgate; Thomas J Gal; Matthew L Bush; Brett T Comer
Journal:  Laryngoscope       Date:  2017-08-16       Impact factor: 3.325

9.  Defining Team Effort Involved in Patient Care from the Primary Care Physician's Perspective.

Authors:  Andrew S Hwang; Steven J Atlas; Johan Hong; Jeffrey M Ashburner; Adrian H Zai; Richard W Grant; Clemens S Hong
Journal:  J Gen Intern Med       Date:  2016-10-21       Impact factor: 5.128

10.  Targeted Reminder Phone Calls to Patients at High Risk of No-Show for Primary Care Appointment: A Randomized Trial.

Authors:  Sachin J Shah; Patrick Cronin; Clemens S Hong; Andrew S Hwang; Jeffrey M Ashburner; Benjamin I Bearnot; Calvin A Richardson; Blair W Fosburgh; Alexandra B Kimball
Journal:  J Gen Intern Med       Date:  2016-08-08       Impact factor: 5.128

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.