Deprivation, demography and missed scheduled appointments at an NHS primary dental care and training service

West, Amelia; Stones, Tara; Wanyonyi, Kristina

doi:10.1038/s41415-020-1197-3

Cited by 12 publications

(18 citation statements)

References 22 publications

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“…No significant difference in FTA was found between males and females. This finding was consistent with previous studies 1,5 ; however, in some studies, FTA was higher in males due to prioritizing work commitments over health‐related appointments 19,20 . Those with gender listed as “unstated” had significantly higher FTA rates (13.8%) compared to males and females (6.4% and 6.7%, respectively).…”

Section: Discussionsupporting

confidence: 90%

Impact of demographics and appointment characteristics on patient attendance in a university dental clinic

White

Butler-Howell

Nadon-Hoysted

et al. 2020

Journal of Dental Education

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Introduction Failed patient attendance in a university dental clinic is detrimental to the student learning experience, the university as a business, and to members of the public awaiting urgent dental treatment. Purpose This study aimed to identify the demographic, appointment characteristics, and time‐related factors associated with patient attendance in a university dental clinic from 2015 to 2019. Methods A 5‐year retrospective analysis was conducted in 2020 on data extracted from the Griffith University Dental Clinic patient management system. Following data cleaning and categorization, the dataset was downloaded into SPSS for statistical analysis. Frequencies, odds ratio, and chi squared were used to determine the demographic and time‐related factors of patients who had completed, cancelled, and failed to attend (FTA) appointments. Results A total of 23.4% of appointments were cancelled, and 6.6% were FTA. Demographics associated with cancellations include females, adults aged 25 to 44, and private paying patients. FTA were higher in young adults aged 19 to 24, low to mid‐range socioeconomic status (SES) and those eligible for publicly funded dental treatment. Mondays and Fridays experienced the greatest number of FTA and cancellations, respectively. Emergency appointments had the greatest attendance rates and endodontic procedures the lowest. Conclusion The loss of clinical teaching hours, resources, and revenue necessitates the implementation of targeted strategies to minimize cancellations and FTA based on demographic and appointment characteristics that may render individual as high risk for failed attendance.

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Section: Discussionsupporting

confidence: 90%

Impact of demographics and appointment characteristics on patient attendance in a university dental clinic

White

Butler-Howell

Nadon-Hoysted

et al. 2020

Journal of Dental Education

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“…The aims of the investigation were to evaluate patient demographic data such as age, gender, and zip codes of predoctoral clinics at TUSDM, and compare lead response time between no‐show and checked‐in appointments. Examining missed or no‐show appointments has not been widely researched, specifically in a dental setting, but has been shown to be a contributing factor for maintenance of continued access of care 7 …”

Section: Discussionmentioning

confidence: 99%

“…Students lose their experience to have face‐to‐face interaction with patients. The loss for the patients is that the wait time for the new patient exam is longer for other patients who need the appointment to prevent advancement of oral diseases 7 . Additionally, there is financial loss for the university based on underuse of the chairs.…”

Section: Discussionmentioning

confidence: 99%

“…This impacts other patients’ access to oral healthcare. By identifying the no‐show appointments, schools, and teaching clinics can study the reasons behind the missed sessions and improve operational efficiency, decrease financial loss, and look for ways to further dental access to patients who need assistance in acquiring oral health care 7,9 …”

Section: Discussionmentioning

confidence: 99%

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Exploratory analysis to enhance operational efficiency of new patient screenings

Kim

Patel

et al. 2020

Journal of Dental Education

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Objective The aims of this study were to 1) evaluate patient demographic data for new patient exams (NPE) and 2) analyze lead response time for checked‐in and no‐show appointments in predoctoral clinics in a dental school. Methods The data for the study were collected from the predoctoral clinics at Tufts University School of Dental Medicine (TUSDM) for patients with NPE appointments with American Dental Association's (ADA) diagnostic code of D100. A total of 26,826 appointments and 24,419 unique patients were reviewed from January 1, 2015 to December 31, 2019. Patient demographic variables such as age, gender, zip codes, and lead response time were analyzed. Results From 26,826 total number of appointments, 10,454 appointments were categorized as no‐show appointments (38.97%). In the no‐show appointments, the sex distribution was 59.93% female and 40.07% male, and in checked‐in category, the sex distribution was 53.75% female and 46.25% male. As the lead response time increased over 5 days, the no‐show rate increased to 49.79%. Approximately 55% of the entire NPE was from Greater Boston area. Conclusion The association between lead time and no‐show rate was shown that when lead time was reduced, no‐show rate decreased. By identifying the no‐show appointments and lead time, schools and clinics can improve operational efficiency, reduce financial loss, and maintain continuation of care by supporting patients who need access to care and creating secondary automated recall system to maximize communication and chair use.

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“…One of the sentences in the Kirton et al paper which jumped out at me was that patients did not always understand the differences between emergency and non-emergency appointment systems. 1 In turn this made me make a connection with the cultural differences which are highlighted in the paper by West et al 2 on the social status and demography of patients who missed scheduled appointments. Analysis of routinely collected electronic primary dental care records from individual, representative patients revealed patterns that predicted missed appointments.…”

mentioning

confidence: 91%

The appointed time

Hancocks

2020

Br Dent J

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Deprivation, demography and missed scheduled appointments at an NHS primary dental care and training service

Cited by 12 publications

References 22 publications

Impact of demographics and appointment characteristics on patient attendance in a university dental clinic

Impact of demographics and appointment characteristics on patient attendance in a university dental clinic

Exploratory analysis to enhance operational efficiency of new patient screenings

The appointed time

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