Literature DB >> 10647759

Physician practice variation in assignment of return interval.

K B DeSalvo1, B E Bowdish, A S Alper, D M Grossman, W W Merrill.   

Abstract

BACKGROUND: Recent shifts in reimbursement toward capitation makes appointment availability a significant resource and stimulates us to understand primary care physician (hereafter referred to as "provider") behavior concerning appointment assignment. The results of prior studies suggest significant provider variability in this area.
OBJECTIVE: To examine the influences on assigning patient revisit intervals in the ambulatory setting.
METHODS: Survey regarding general care issues of hypothetical diabetic and hypertensive patients seen in an ambulatory setting was given to 62 providers in the Internal Medicine Program at the Tulane University Internal Medicine Residency Program and outpatient clinics, New Orleans, La. Measurements evaluated included survey responses for demographics (sex, year of birth, year of graduation from medical school, and level of training) and practice style (decision to change therapy, order tests, and recommended return appointment interval in weeks) variables.
RESULTS: The response rate was 89% (56 providers). Most respondents were men (n = 39). Wide variation was noted in assignment of reappointment interval with mean return intervals for the scenarios ranging from 2.2 to 20.5 weeks. Significant influences on provider practice included patient stability (P<.001), the decision to change therapy (P = .001), and the decision to order tests (P = .001). All correlated with an earlier return appointment. Some providers exhibited test-ordering tendencies across scenarios. Sex was a significant provider independent variable and was not influenced by other study variables. Female providers assigned earlier reappointment intervals for their patients.
CONCLUSIONS: Wide variation exists among practitioners with similar training background and practice setting. As expected, patient stability was a major determinant of assigned return interval. Test-ordering behaviors may consume appointments inappropriately and may be a productive area for efforts to reduce provider variability. The influence of the provider's sex on scheduling follow-up appointments warrants further investigation.

Entities:  

Mesh:

Year:  2000        PMID: 10647759     DOI: 10.1001/archinte.160.2.205

Source DB:  PubMed          Journal:  Arch Intern Med        ISSN: 0003-9926


  9 in total

1.  Revisit frequency and its association with quality of care among diabetic patients: Translating Research Into Action for Diabetes (TRIAD).

Authors:  Keiko Asao; Laura N McEwen; Jesse C Crosson; Beth Waitzfelder; William H Herman
Journal:  J Diabetes Complications       Date:  2014-06-19       Impact factor: 2.852

2.  Encounter frequency and blood pressure in hypertensive patients with diabetes mellitus.

Authors:  Alexander Turchin; Saveli I Goldberg; Maria Shubina; Jonathan S Einbinder; Paul R Conlin
Journal:  Hypertension       Date:  2010-05-24       Impact factor: 10.190

3.  Predictors of provider-patient visit frequency during hemodialysis.

Authors:  Yelena Slinin; Haifeng Guo; Suying Li; Jiannong Liu; Benjamin Morgan; Kristine Ensrud; David T Gilbertson; Allan J Collins; Areef Ishani
Journal:  Am J Nephrol       Date:  2013-07-17       Impact factor: 3.754

4.  Rethinking the frequency of between-visit monitoring for patients with diabetes.

Authors:  John D Piette; James E Aikens; Ann M Rosland; Jeremy B Sussman
Journal:  Med Care       Date:  2014-06       Impact factor: 2.983

5.  A general method for identifying excess revisit rates: the case of hypertension.

Authors:  Norman Frohlich; Marilyn Cree; K C Carriere
Journal:  Healthc Policy       Date:  2008-02

6.  Visit frequency and hypertension.

Authors:  Richard Guthmann; Nancy Davis; Matthew Brown; Jose Elizondo
Journal:  J Clin Hypertens (Greenwich)       Date:  2005-06       Impact factor: 3.738

7.  Maximizing the value of mobile health monitoring by avoiding redundant patient reports: prediction of depression-related symptoms and adherence problems in automated health assessment services.

Authors:  John D Piette; Jeremy B Sussman; Paul N Pfeiffer; Maria J Silveira; Satinder Singh; Mariel S Lavieri
Journal:  J Med Internet Res       Date:  2013-07-05       Impact factor: 5.428

8.  Patient-Centered Pain Care Using Artificial Intelligence and Mobile Health Tools: Protocol for a Randomized Study Funded by the US Department of Veterans Affairs Health Services Research and Development Program.

Authors:  John D Piette; Sarah L Krein; Dana Striplin; Nicolle Marinec; Robert D Kerns; Karen B Farris; Satinder Singh; Lawrence An; Alicia A Heapy
Journal:  JMIR Res Protoc       Date:  2016-04-07

9.  Variation in Follow-Up Visit Practices Across Clinicians and Conditions: Findings From a University Cardiology Practice.

Authors:  Caterina Yuan Liu; Ralph Gonzales
Journal:  Health Serv Res Manag Epidemiol       Date:  2015-12-09
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.