Evidence map›Paper›PMID 29136649›Full record

ArticlePloS one2017

Discordance between 'actual' and 'scheduled' check-in times at a heart failure clinic.

Eiran Z Gorodeski, Emer Joyce, Benjamin T Gandesbery, Eugene H Blackstone, David O Taylor, W H Wilson Tang, Randall C Starling, Rory Hachamovitch

Abstract readComparative Study
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. A Machine Learning-Based Approach for Predicting Patient Punctuality in Ambulatory Care Centers.International journal of environmental research and public health · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Eiran Z GorodeskiSection of Heart Failure and Cardiac Transplantation, Tomsich Family Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio, United States of America.ORCID http://orcid.org/0000-0003-3756-8831
Emer JoyceSection of Heart Failure and Cardiac Transplantation, Tomsich Family Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio, United States of America.
Benjamin T GandesberyCase Western Reserve University School of Medicine, Cleveland, Ohio, United States of America.
Eugene H BlackstoneDepartment of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, United States of America.
David O TaylorSection of Heart Failure and Cardiac Transplantation, Tomsich Family Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio, United States of America.
W H Wilson TangSection of Heart Failure and Cardiac Transplantation, Tomsich Family Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio, United States of America.
Randall C StarlingSection of Heart Failure and Cardiac Transplantation, Tomsich Family Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio, United States of America.
Rory HachamovitchSection of Cardiovascular Imaging, Tomsich Family Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionA 2015 Institute Of Medicine statement "Transforming Health Care Scheduling and Access: Getting to Now", has increased concerns regarding patient wait times. Although waiting times have been widely studied, little attention has been paid to the role of patient arrival times as a component of this phenomenon. To this end, we investigated patterns of patient arrival at scheduled ambulatory heart failure (HF) clinic appointments and studied its predictors. We hypothesized that patients are more likely to arrive later than scheduled, with progressively later arrivals later in the day. METHODS AND

resultsUsing a business intelligence database we identified 6,194 unique patients that visited the Cleveland Clinic Main Campus HF clinic between January, 2015 and January, 2017. This clinic served both as a tertiary referral center and a community HF clinic. Transplant and left ventricular assist device (LVAD) visits were excluded. Punctuality was defined as the difference between 'actual' and 'scheduled' check-in times, whereby negative values (i.e., early punctuality) were patients who checked-in early. Contrary to our hypothesis, we found that patients checked-in late only a minority of the time (38% of visits). Additionally, examining punctuality by appointment hour slot we found that patients scheduled after 8AM had progressively earlier check-in times as the day progressed (P < .001 for trend). In both a Random Forest-Regression framework and linear regression models the most important risk-adjusted predictors of early punctuality were: later in the day appointment hour slot, patient having previously been to the hospital, age in the early 70s, and white race.

conclusionsPatients attending a mixed population ambulatory HF clinic check-in earlier than scheduled times, with progressive discrepant intervals throughout the day. This finding may have significant implications for provider utilization and resource planning in order to maximize clinic efficiency. The impact of elective early arrival on patient's perceived wait times requires further study.

Indexed as

Ambulatory Care FacilitiesAppointments and SchedulesHeart FailureHumansTime Factors

Identifiers

PMID29136649
PMCPMC5685632

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.