IADR Abstract Archives
Dental Dashboards for Improving Safety and Quality of Oral Healthcare
Objectives: Due to the increased adoption of electronic health records, dentists now have the ability to assess both the quantity and quality of oral healthcare provided to patients. The Dental Quality Alliance as well as other organizations have already developed a plethora of Dental Quality Measures (DQM) to assess the quality of oral health care. Effective ways to visualize these measures are needed so dentists can make good decisions. Our goal was to create a prototype dashboard to help dentists and administrators interpret how well diabetics received annual oral evaluations.
Methods: Data were collected retrospectively from the UTHealth School of Dentistry (UTSD) through the BigMouth Data Repository for all diabetic patients seen between 2010-2014. We used an iterative human-centered design process to develop a dashboard using Tableau (v9.0) that depicted the percentage of diabetics receiving oral evaluation by year, gender, race, age, zip-codes, and providers. Zip-codes were geocoded to a per-capita income layered map of USA that depicted the number of diabetics evaluated/non-evaluated that came to UTSD. Options to filter data by different variables were included.
Results: The dashboard showed 31,242 patients who visited UTSD between 2010-2014, of which 8.8% were diabetic. 48-54% of the diabetics received an oral evaluation (Figure 1). There was no clear relationship between per-capita income and receiving oral evaluation (Figure 1). Oral evaluation across age groups ranged from 46-56%; 53% of females were evaluated as opposed to 56% of males; and more patients were evaluated by students than by residents (Figure 2).
Conclusions: Our study demonstrated the feasibility of using an interactive dashboard to help visualize oral health quality data from EHRs. In future work we will expand the dashboard to include other quality measures and data from additional institutions to help dentists and administrators make data-driven decisions directed towards improving quality and safety.
Methods: Data were collected retrospectively from the UTHealth School of Dentistry (UTSD) through the BigMouth Data Repository for all diabetic patients seen between 2010-2014. We used an iterative human-centered design process to develop a dashboard using Tableau (v9.0) that depicted the percentage of diabetics receiving oral evaluation by year, gender, race, age, zip-codes, and providers. Zip-codes were geocoded to a per-capita income layered map of USA that depicted the number of diabetics evaluated/non-evaluated that came to UTSD. Options to filter data by different variables were included.
Results: The dashboard showed 31,242 patients who visited UTSD between 2010-2014, of which 8.8% were diabetic. 48-54% of the diabetics received an oral evaluation (Figure 1). There was no clear relationship between per-capita income and receiving oral evaluation (Figure 1). Oral evaluation across age groups ranged from 46-56%; 53% of females were evaluated as opposed to 56% of males; and more patients were evaluated by students than by residents (Figure 2).
Conclusions: Our study demonstrated the feasibility of using an interactive dashboard to help visualize oral health quality data from EHRs. In future work we will expand the dashboard to include other quality measures and data from additional institutions to help dentists and administrators make data-driven decisions directed towards improving quality and safety.
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