Browsing by Author "Willis, Lisa"

Now showing 1 - 4 of 4
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    Comparing gingivitis diagnoses by bleeding on probing (BOP) exclusively versus BOP combined with visual signs using large electronic dental records
    (Springer, 2023-10-10) Patel, Jay S.; Shin, Daniel; Willis, Lisa; Zai, Ahad; Kumar, Krishna; Thyvalikakath, Thankam P.; Cariology, Operative Dentistry and Dental Public Health, School of Dentistry
    The major significance of the 2018 gingivitis classification criteria is utilizing a simple, objective, and reliable clinical sign, bleeding on probing score (BOP%), to diagnose gingivitis. However, studies report variations in gingivitis diagnoses with the potential to under- or over-estimating disease occurrence. This study determined the agreement between gingivitis diagnoses generated using the 2018 criteria (BOP%) versus diagnoses using BOP% and other gingival visual assessments. We conducted a retrospective study of 28,908 patients' electronic dental records (EDR) from January-2009 to December-2014, at the Indiana University School of Dentistry. Computational and natural language processing (NLP) approaches were developed to diagnose gingivitis cases from BOP% and retrieve diagnoses from clinical notes. Subsequently, we determined the agreement between BOP%-generated diagnoses and clinician-recorded diagnoses. A thirty-four percent agreement was present between BOP%-generated diagnoses and clinician-recorded diagnoses for disease status (no gingivitis/gingivitis) and a 9% agreement for the disease extent (localized/generalized gingivitis). The computational program and NLP performed excellently with 99.5% and 98% f-1 measures, respectively. Sixty-six percent of patients diagnosed with gingivitis were reclassified as having healthy gingiva based on the 2018 diagnostic classification. The results indicate potential challenges with clinicians adopting the new diagnostic criterion as they transition to using the BOP% alone and not considering the visual signs of inflammation. Periodic training and calibration could facilitate clinicians' and researchers' adoption of the 2018 diagnostic system. The informatics approaches developed could be utilized to automate diagnostic findings from EDR charting and clinical notes.
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    Developing Automated Computer Algorithms to Track Periodontal Disease Change from Longitudinal Electronic Dental Records
    (MDPI, 2023-03-08) Patel, Jay S.; Kumar, Krishna; Zai, Ahad; Shin, Daniel; Willis, Lisa; Thyvalikakath, Thankam P.
    Objective: To develop two automated computer algorithms to extract information from clinical notes, and to generate three cohorts of patients (disease improvement, disease progression, and no disease change) to track periodontal disease (PD) change over time using longitudinal electronic dental records (EDR). Methods: We conducted a retrospective study of 28,908 patients who received a comprehensive oral evaluation between 1 January 2009, and 31 December 2014, at Indiana University School of Dentistry (IUSD) clinics. We utilized various Python libraries, such as Pandas, TensorFlow, and PyTorch, and a natural language tool kit to develop and test computer algorithms. We tested the performance through a manual review process by generating a confusion matrix. We calculated precision, recall, sensitivity, specificity, and accuracy to evaluate the performances of the algorithms. Finally, we evaluated the density of longitudinal EDR data for the following follow-up times: (1) None; (2) Up to 5 years; (3) > 5 and ≤ 10 years; and (4) >10 and ≤ 15 years. Results: Thirty-four percent (n = 9954) of the study cohort had up to five years of follow-up visits, with an average of 2.78 visits with periodontal charting information. For clinician-documented diagnoses from clinical notes, 42% of patients (n = 5562) had at least two PD diagnoses to determine their disease change. In this cohort, with clinician-documented diagnoses, 72% percent of patients (n = 3919) did not have a disease status change between their first and last visits, 669 (13%) patients’ disease status progressed, and 589 (11%) patients’ disease improved. Conclusions: This study demonstrated the feasibility of utilizing longitudinal EDR data to track disease changes over 15 years during the observation study period. We provided detailed steps and computer algorithms to clean and preprocess the EDR data and generated three cohorts of patients. This information can now be utilized for studying clinical courses using artificial intelligence and machine learning methods.
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    Learning experience about the use of the ICDAS by dental students in the clinic
    (2024) Alfawaz, Ibrahim; Soto Rojas, Armando E.; Al Dehailan, Laila A.; Willis, Lisa
    Background: The International Caries Detection and Assessment System (ICDAS), established in 2002, is a method to detect and assess the severity of dental caries. It provides scores ranging from 0 (sound tooth) to 6 (extensive cavitation). This system enhances the accuracy of caries diagnosis and assists in conducting research related to public health. Objective: This study aims to explore the knowledge and learning experience of ICDAS in the third-year (D3) and fourth-year (D4) students at Indiana University School of Dentistry (IUSD), evaluate how well they can utilize it, and determine whether they use the ICDAS in clinics. Material and Methods: A questionnaire to assess knowledge and use of ICDAS in the clinic was developed by the student investigator and committee members. The initial questionnaire underwent pilot testing, received feedback from faculty and alums, and was evaluated by the Center for Survey Research. Institutional Review Board (IRB) was obtained. The questionnaire included open-ended and Likert scale questions to assess students' attitudes, knowledge, perceptions, and potential behavioral modifications regarding the ICDAS. The questionnaire was anonymously distributed through Qualtrics and designed to ensure all responses were obtained, specifically targeting D3 and D4 dental students. The responses were gathered and subjected to statistical analysis. Results: 75 Out of 229 dental students (32% of D3 and D4) responded to the survey. This group had 40% D3 and 60% D4 respondents. D4 students were more confident in identifying ICDAS 1 lesions (p=0.041). Students with prior experience were less likely to correctly identify an ICDAS 3 (p=0.034). Additionally, they were less likely to accurately identify an ICDAS 4 (p=0.010). 93% of students stated that ICDAS scores affected treatment. Four ICDAS scoring systems were also discussed with students. About 90% of students indicated that ICDAS caries stages helped them choose preventive or restorative treatments to enhance minimally invasive dentistry. Over 90% of students disagreed with negative statements such as difficulty understanding, learning, having too many scores, and being inadequate for the clinical setting. Conclusion: Third and fourth-year dental students in IUSD exhibit positive learning experiences in their continuing clinical practice with ICDAS and demonstrate adequate knowledge of ICDAS.
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    Longevity of dental restorations in Sjogren's disease patients using electronic dental and health record data
    (Springer Nature, 2024-02-07) Gomez, Grace Gomez Felix; Wang, Mei; Siddiqui, Zasim A.; Gonzalez, Theresa; Capin, Oriana R.; Willis, Lisa; Boyd, LaKeisha; Eckert, George J.; Zero, Domenick T.; Thyvalikakath, Thankam Paul; Dental Public Health and Dental Informatics, School of Dentistry
    Background: Decreased salivary secretion is not only a risk factor for carious lesions in Sjögren's disease (SD) but also an indicator of deterioration of teeth with every restorative replacement. This study determined the longevity of direct dental restorations placed in patients with SD using matched electronic dental record (EDR) and electronic health record (EHR) data. Methods: We conducted a retrospective cohort study using EDR and EHR data of Indiana University School of Dentistry patients who have a SD diagnosis in their EHR. Treatment history of patients during 15 years with SD (cases) and their matched controls with at least one direct dental restoration were retrieved from the EDR. Descriptive statistics summarized the study population characteristics. Cox regression models with random effects analyzed differences between cases and controls for time to direct restoration failure. Further the model explored the effect of covariates such as age, sex, race, dental insurance, medical insurance, medical diagnosis, medication use, preventive dental visits per year, and the number of tooth surfaces on time to restoration failure. Results: At least one completed direct restoration was present for 102 cases and 42 controls resulting in a cohort of 144 patients' EDR and EHR data. The cases were distributed as 21 positives, 57 negatives, and 24 uncertain cases based on clinical findings. The average age was 56, about 93% were females, 54% were White, 74% had no dental insurance, 61% had public medical insurance, < 1 preventive dental visit per year, 94% used medications and 93% had a medical diagnosis that potentially causes dry mouth within the overall study cohort. About 529 direct dental restorations were present in cases with SD and 140 restorations in corresponding controls. Hazard ratios of 2.99 (1.48-6.03; p = 0.002) and 3.30 (1.49-7.31, p-value: 0.003) showed significantly decreased time to restoration failure among cases and positive for SD cases compared to controls, respectively. Except for the number of tooth surfaces, no other covariates had a significant influence on the survival time. Conclusion: Considering the rapid failure of dental restorations, appropriate post-treatment assessment, management, and evaluation should be implemented while planning restorative dental procedures among cases with SD. Since survival time is decreased with an increase in the number of surfaces, guidelines for restorative procedures should be formulated specifically for patients with SD.