Factors Associated With Nonattendance at Scheduled Outpatient Appointments in a University General Hospital (AU1)

March 19, 2015 updated by: Diego Hernan Giunta, MD, Hospital Italiano de Buenos Aires
Our objectives were to estimate the prevalence of nonattendance at outpatient offices, to identify the characteristics of appointments for which nonattendance was more likely to occur, and to generate a predictive model that could be applied to each appointment to estimate the probability of nonattendance.

Study Overview

Detailed Description

Nonattendance at scheduled appointments at outpatient clinics is a common problem in general medical practice, representing a significant cost to the health care system, and resulting in disruption of daily work planning.Nonattendance at medical appointments has consequences not only for doctors (as it requires a greater use of resources and time), but also for patients, because there may be deterioration in the quality of care, and dissatisfaction associated with delays in obtaining a new appointment.

Previous studies have reported that nonattendance at scheduled appointments is most frequently associated with those patients attending follow-up appointments, generally those assigned to another professional, those with appointments on Fridays, and those with appointments assigned 1 - 2 weeks in advance. Nonattendance was also associated with younger patient age, greater psychological problems, and lower socioeconomic status.Furthermore, in patients with chronic diseases, the nonattendance rate was also reported to be lower. Clinical patient characteristics can be important predictors of nonattendance, but they required high quality electronic health records to predict nonattendance accurately In the United States and Europe, the nonattendance rate is estimated to be between 6.5%-55%; there is little evidence regarding nonattendance in Latin America. Many studies have described the prevalence and impact of nonattendance at scheduled medical appointments, and possible strategies to decrease the nonattendance rate. However, few studies have utilized the characteristics associated with nonattendance for building predictive models, which might better identify those patients who may not attend a scheduled appointment

Study Type

Observational

Enrollment (Actual)

10000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Buenos Aires
      • Capital Federal, Buenos Aires, Argentina, C1199ABD
        • Hospital Italiano de Buenos Aires

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

We included all requested appointments (random consecutive sampling) between 2012 and 2013 (24 month). The sample was randomized to allocate a generation cohort (two-thirds of the sample) and a validation cohort (one third of the sample).

Description

Inclusion Criteria:

  • Over 17 years.
  • Adults who attended, did not attend and cancelled a scheduled appointment at the Outpatient care system at the Italian Hospital of Buenos Aires (HIBA)

Exclusion Criteria:

  • The refusal to register or to the informed consent process.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Retrospective Cohort
Adult patients who had scheduled an appointment for outpatient primary care. Patients were divided into two groups, including those who attended their scheduled appointment and those who missed it.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Prevalence of non attendance, attendance and cancellation
Time Frame: Cohort study of 24 month
Characterize, describe and compare the clinical and administrative characteristics of outpatients who didn't attend, attended and cancelled an appointment in internal medicine/primary health care, clinical subspecialties and surgical specialties.
Cohort study of 24 month

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Clinical and administrative characteristics
Time Frame: Cohort study of 24 month
Characterize, describe and compare the clinical and administrative characteristics of outpatients who didn't attend, attended and cancelled an appointment in internal medicine/primary health care, clinical subspecialties and surgical specialties.
Cohort study of 24 month

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start

May 1, 2014

Primary Completion (Actual)

September 1, 2014

Study Completion (Actual)

December 1, 2014

Study Registration Dates

First Submitted

April 6, 2014

First Submitted That Met QC Criteria

April 6, 2014

First Posted (Estimate)

April 9, 2014

Study Record Updates

Last Update Posted (Estimate)

March 24, 2015

Last Update Submitted That Met QC Criteria

March 19, 2015

Last Verified

March 1, 2015

More Information

Terms related to this study

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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