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Research Letter |

A Multivariate Analysis of Dermatology Missed Appointment Predictors FREE

Patrick R. Cronin, MA1,2; Leah DeCoste, BA3,4; Alexa Boer Kimball, MD, MPH5
[+] Author Affiliations
1Practice Improvement Division, Massachusetts General Hospital, Boston
2now with Lab of Computer Science, Massachusetts General Hospital, Boston
3College of the Holy Cross, Worcester, Massachusetts
4now with University of Massachusetts Medical School, Worcester
5Department of Dermatology, Massachusetts General Hospital and Harvard Medical School, Boston
JAMA Dermatol. 2013;149(12):1435-1437. doi:10.1001/jamadermatol.2013.5771.
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Published online

Dermatology appointment nonattendance rates range from 17% to 31%,13 and patients who miss appointments without prior notification (no-shows and same-day cancellations) disrupt schedules, decrease access for others, resulting in underutilization of resources and thereby increasing cost, and interrupt continuity of medical care.1,4 Therefore, we set out to determine if easily attainable variables from scheduling data could be used to predict patients likely to miss dermatology appointments.

This study was conducted in the department of medical dermatology at the Massachusetts General Hospital under the approval of the Partners institutional review board. The department employs 30 physicians, rendering approximately 59 000 visits annually. It uses the IDX scheduling system and Televox for automated reminder calls 3 days prior to visit. Patients, at that time, were not charged for missing appointments.

The outcome measure, missed appointments, was the failure to arrive without notifying the practice before the appointment date.

Data were collected for 47 348 medical dermatology appointments from August 2010 through July 2011, representing 80% of appointments. The number of previously missed medical dermatology appointments was collected from September 2008 through July 2011. New and follow-up appointments (routine and urgent) for weekday appointments were included. Appointments on days with heavy snowfall or outside the standard session (ie, 8:00 am–12:00 pm and 1:00-5:00 pm Monday-Friday) were excluded.

The following variables were identified through literature searches and input from department leadership: appointment type, weekday, appointment hour, wait days (number of days between scheduling and appointment date), language, age, insurance type, sex, and number of previously missed medical dermatology appointments. Insurance type was divided into commercial insurance with a copy, plans with coinsurance, Medicare, Medicaid, free care, and self-insured.

Data were extracted using Standard Query Language (SQL) and were analyzed using SAS software (version 9.2). Univariate regression tests were performed on all variables, and a multivariate logistic regression was performed on statistically significant variables (P < .05).

The final cohort had 41 893 records with 7812 missed appointments (18.6%). Forty-one percent of patients who missed appointments did arrive at a future appointment within 1 year.

Through univariate analyses (Table), all variables were statistically significant (P < .05). All variables were included in a multivariate logistic regression, and weekday, wait days (Figure), language, age group, insurance type, and number of previously missed appointments remained statistically significant (P < .05), whereas appointment type (P = .30), sex (P = .27), and appointment hour (P = .54) did not.

Table Graphic Jump LocationTable.  Univariate and Multivariate Factors Associated With Missed Appointments
Place holder to copy figure label and caption
Figure.
Missed Appointment Rate by Wait Days
Graphic Jump Location

This study isolates key factors that identify patients who are likely to miss appointments, which most practices should be able to easily obtain. In this era of cost containment, maximizing clinic efficiency will become increasingly important, and missed appointments are an obvious source of waste.

One of the novel aspects of this work is that it allows a practice to use the findings from both the univariate and multivariate analysis. Any significant univariate variable may be useful as a single filter, whereas the multivariate model allows a practice to determine which combinations would be redundant. We also validate findings that have been anecdotally observed: the day of the week matters (since practices are usually closed over the weekend, Monday is particularly vulnerable), and a track record of missed appointments is also predictive. Our analysis is consistent with literature1,3 showing that missed appointment rates increase the longer patients wait for appointments (Table), likely because it increases the chances of forgetting or neglecting to cancel an appointment when plans change. Age is a predictive factor, with younger patients and the very old (>90 years) most likely to miss appointments. Finally, we show that patients with coinsurance, which was virtually nonexistent before 2005 and now affects approximately 19% of the population,5 are 20% more likely to miss appointments than those who have a copay (Table), presumably owing to the greater potential financial burden.

Our study is limited because it was conducted at a single location with 30 physicians. Although only dermatology appointments are demonstrated in this manuscript, we have found similar results in other departments in our institution.

In conclusion, targeted interventions at patients likely to miss appointments could decrease the negative financial impact while limiting the expense and possible annoyance of reminding others unnecessarily. Patients who are younger, have been waiting a long time, or have less comprehensive insurance seem to be most likely to benefit from reminders.6

Accepted for Publication: May 23, 2013.

Corresponding Author: Alexa Boer Kimball, MD, MPH, Department of Dermatology, Massachusetts General Hospital, Harvard Medical School, 50 Staniford Street, Suite 240, Boston, MA 02114 (harvardskinstudies@partners.org).

Published Online: September 30, 2013. doi:10.1001/jamadermatol.2013.5771.

Author Contributions: Mr Cronin had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: All authors.

Acquisition of data: Cronin, Kimball.

Analysis and interpretation of data: All authors.

Drafting of the manuscript: Cronin, DeCoste.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Cronin.

Administrative, technical, or material support: Cronin.

Study supervision: Kimball.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by Massachusetts General Physicians Organization Funds.

Role of the Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Information: The project was performed as part of ongoing practice improvement efforts at the Massachusetts General Physicians Organization.

Canizares  MJ, Penneys  NS.  The incidence of nonattendance at an urgent care dermatology clinic. J Am Acad Dermatol. 2002;46(3):457-459.
PubMed   |  Link to Article
Penneys  NS, Glaser  DA.  The incidence of cancellation and nonattendance at a dermatology clinic. J Am Acad Dermatol. 1999;40(5, pt 1):714-718.
PubMed   |  Link to Article
Cohen  AD, Dreiher  J, Vardy  DA, Weitzman  D.  Nonattendance in a dermatology clinic: a large sample analysis. J Eur Acad Dermatol Venereol. 2008;22(10):1178-1183.
PubMed   |  Link to Article
Sequist  TD.  Ensuring equal access to specialty care. N Engl J Med. 2011;364(23):2258-2259.
PubMed   |  Link to Article
Employer Health Benefits: 2012 Summary of Findings. The Henry J. Kaiser Family Foundation Headquarters. January 17, 2013. http://ehbs.kff.org/pdf/2012/8346.pdf. Accessed May 15, 2013.
Hasvold  PE, Wootton  R.  Use of telephone and SMS reminders to improve attendance at hospital appointments: a systematic review. J Telemed Telecare. 2011;17(7):358-364.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure.
Missed Appointment Rate by Wait Days
Graphic Jump Location

Tables

Table Graphic Jump LocationTable.  Univariate and Multivariate Factors Associated With Missed Appointments

References

Canizares  MJ, Penneys  NS.  The incidence of nonattendance at an urgent care dermatology clinic. J Am Acad Dermatol. 2002;46(3):457-459.
PubMed   |  Link to Article
Penneys  NS, Glaser  DA.  The incidence of cancellation and nonattendance at a dermatology clinic. J Am Acad Dermatol. 1999;40(5, pt 1):714-718.
PubMed   |  Link to Article
Cohen  AD, Dreiher  J, Vardy  DA, Weitzman  D.  Nonattendance in a dermatology clinic: a large sample analysis. J Eur Acad Dermatol Venereol. 2008;22(10):1178-1183.
PubMed   |  Link to Article
Sequist  TD.  Ensuring equal access to specialty care. N Engl J Med. 2011;364(23):2258-2259.
PubMed   |  Link to Article
Employer Health Benefits: 2012 Summary of Findings. The Henry J. Kaiser Family Foundation Headquarters. January 17, 2013. http://ehbs.kff.org/pdf/2012/8346.pdf. Accessed May 15, 2013.
Hasvold  PE, Wootton  R.  Use of telephone and SMS reminders to improve attendance at hospital appointments: a systematic review. J Telemed Telecare. 2011;17(7):358-364.
PubMed   |  Link to Article

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