Oral Health Intervention in Adult Primary Care

Multi-Level Interventions to Reduce Oral Health Disparities Among Adults in Primary Care Settings

This study is a Stage III cRCT to test the efficacy of multi-level interventions at the practice- and provider-level to address low dental utilization (attendance) among Medicaid-enrolled older adults 55 years or older attending non-urgent primary care visits (PCV) in MetroHealth practice settings. Twelve practices will be randomized into two arms: A) Intervention arm will receive the multi-level intervention that includes: 1. Practice-level: EHR changes to include: ask, advise, assess, and connect (AAAC) strategies; 2. Provider-level: Medical staff (MA, nurse): Training in the AAAC process and complete AAAC for enrolled older adults; Clinicians (physician/nurse practitioner): CSM-based education (didactic), skills training (video training with standardized patients), and view completed AAAC in EHR to deliver core oral health (OH) facts to older adults, reinforce importance of dental visits, and document in EHR that OH facts were delivered. B) Control arm will receive, at the provider-level only (clinicians), non-theory-based information about retaining a healthy mouth using the ADA Mouth Healthy Series and deliver standard OH care for patients. Older Adults will be followed at 12 months and 24 months to determine if the participant had any dental attendance.

The primary objective is to test the efficacy of the practice level EHR strategy to ask [OH risk assessment], advise [going to dentist], assess [willingness for referral], and connect [eReferral, resources] together with clinician theory-based education to communicate OH facts versus clinician alone (standard oral health care) in increasing dental attendance in primary care settings.

The secondary objectives are to assess oral hygiene behavior, Geriatric Oral Health Quality of life, biometric measures (BP, serum cholesterol, blood glucose, hbA1c) abstracted from EHR data, potential mediators and moderators to investigate pathways that affect the primary and secondary outcomes, and assess implementation strategies: adoption, reach, fidelity, and maintenance of providers and practices that affect older adult primary and secondary outcomes.

The hypothesis is that medical staff completing the AAAC strategy and clinicians with improved OH knowledge (chronicity, systemic effects) will deliver consistent oral health messaging to older adults at PCVs that will result in increased preventive and restorative dental utilization compared to those providers delivering standard care.

Study Overview

• Status: Recruiting
• Conditions: Periodontal Diseases; Dental Caries; Dry Mouth; Bleeding Gum
• Intervention / Treatment: Behavioral: EHR Changes; Behavioral: Medical Staff EHR Training, Clinician CSM theory-based didactic education and skills training; Behavioral: Standard ADA Oral Health Training

Detailed Description

Study Design:

This study will utilize a multi-level cluster randomized clinical trial design (Phase III) to assess interventions intended to address poor dental utilization among Medicaid-enrolled older adults aged 55 years or older attending non-urgent primary care visits (PCV) in primary care settings. The focus is on addressing factors (determinants) at the three socio-ecological levels: the practice/organization, provider (medical staff (MA, nurse) and clinicians (physician, nurse practitioner), and the older adult. A total of 12 practices will be randomized to 2 arms as follows: Intervention Arm (Arm A) includes practice-level changes in Epic EHR for the provider-level medical staff to deliver the ask, advise, assess, connect (AAAC) strategies to screen, refer, and provide resources for oral health + clinician CSM theory-based training to deliver oral health facts to older adults and acknowledge giving facts in EHR; Control Arm (Arm B) will receive provider-level standard non-theory based oral health training for the clinician and no changes to the EHR system or completion of AAAC by medical staff. Arm B participants will receive standard of care which is to address any oral health issues if brought to the attention of the provider. Each arm will consist of 6 practices (n= 12), = 47 clinicians (n= 95), and 400 older adults (n= 800). Only the 6 practices in Arm A will enroll = 95 medical staff. Older adults will be recruited at the first PCV and then be followed for two consecutive PCVs (for approximately 24 months). Providers will complete the training dependent upon arm (EHR, didactic + skills or standard didactic) prior to enrolling any patient and will participate in the study for a total of 24-36 months duration (includes initial and booster training). Booster training for clinicians will be completed prior to PCV #2. Immediately after randomization of practices, recruitment of older adult participants will be rolled out during a two-year period, i.e. 6 practices with 400 participants in each of the two years.

The primary outcome will be dental attendance (receipt of dental care) assessed through CareSource Medicaid claims data. The dental attendance from Medicaid claims will be validated with a sub-set of clinical data from the dental EHR. Clinical data (i.e. encounter date, tooth level caries, periodontal data) will be abstracted for those patients who requested an eReferral to Metro dental.

Secondary outcomes from participant questionnaires will be assessed at 24 months post 1st PCV as follows: oral hygiene behavior and oral health quality of life. Biometric measures (i.e. BP, weight, height, hbA1c) will be abstracted from EHR data.

Participants:

Study participants include medical staff (intervention arm), clinicians, and older adult patients from primary care practices within Cuyahoga County. Medical staff must be solely at the participating practice (not floating between practices) and not planning to leave the practice within a year. Clinicians must be solely in the participating practice (not floating between different practices), have a minimum of 2 patient-care days per week, and not planning to leave the practice within a year. Older adult patient participants are those 55 years or older, attending a wellness or a non-urgent PCV, and enrolled in CareSource Medicaid. All participants meeting the eligibility criteria will be enrolled in the study upon signing the consent form.

Procedures:

Pre-PCV #1 Visit:

Providers: Reviews the written/electronic consent form and signs the form. Medical staff (Arm A) attends EHR training and clinician attends OH didactic education and skills training (Arm A) to communicate core OH facts (dental and systemic links, chronicity of dental disease, dental visits) to older adults or clinician (Arm B) attends standard ADA based didactic training. Providers complete administered pre- and post-tests (clinicians only), socio-demographics (before only), and self-efficacy (clinicians only) to providers before and after the training session.

PCV #1 (Baseline):

Providers: Medical staff in Arm A asks oral health questions and provides an eReferral/structured referral. Clinician delivers oral health facts and documents OH in EHR, based on study arm.

Participants (before clinician encounter): Research staff will review inclusion/exclusion criteria, the written/electronic consent form, and patient signs the form. Medical staff then proceed with the AAAC process (Arm A) in EHR and provide an eReferral to Metro dental or structured referral to Medicaid-accepting dentists with resources. In the exam room, participants will complete the following baseline questionnaires: Brief Illness Perception Questionnaire-Revised for Dental Use in Older/Elder Adults (Brief IPQ-RDE) and the Older Adult Questionnaire.

Participants (during clinician encounter): Older adults will receive the core oral health facts from the clinician in Arm A and reinforcement for dental visits. Arm B participants will receive the clinician's standard oral health care. Older adults attending PCVs may have research staff directly observe the encounter to evaluate the clinician's delivery of OH communication for a sample of visits.

Participants (after clinician encounter): Older adults will provide feedback about the OH information given to them during the medical visit with a short exit questionnaire. Older adults will be given the B1: Follow-up Brief IPQ-RDE to be completed and returned.

Participants after PCV #1: Older adults will receive telephone calls and text messages from research staff to remind them to complete and/or return the Follow-up Brief IPQ-RDE if it has not already been returned. Older adults will receive telephone calls and text messages from research staff 8 weeks after the PCV to complete the Dental Attendance Questionnaire.

Before PCV #2:

Providers: Provide OH didactic education booster session for clinicians based on study arm.

PCV #2:

Providers: Same assessments as PCV #1 Participants: Same assessments as PCV #1

PCV #3:

Providers: Same assessments as PCV #1 (no booster training). Participants: Same assessments as PCV #1 except follow-up Brief IPQ-RDE and Dental Attendance Questionnaire.

Analysis Plan:

Primary Statistical Analysis: For the primary outcome of dental attendance (preventive, restorative) by 12 months (similarly for attendance between 12 and 24 months) the investigators will use a generalized estimating equations (GEE) approach with practices as clusters. This approach will be based on a marginal model with a logit link and include as covariates an intervention indicator variable and selected patient baseline variables considered as potential confounders. A corrected standard error, adjusting for the small number of clusters, and a corresponding score test will be used to test for an intervention effect, and 95% confidence intervals for the intervention effect (on an odds ratio scale) will be computed. To assess possible effect modification, interaction terms involving the intervention indicator and each moderator (for example, sociodemographic and social support variables) will be added to the above model and tested. The investigators will consider alternative within-cluster association models, for example, by allowing for a second level of clustering (of providers nested within practices), and through an alternating logistic regression approach (using odds ratios as measures of association among binary outcomes in a cluster or sub cluster). As a supplementary analysis, the investigators will analyze dental attendance in the two time periods (from baseline to 12 months and from 12 to 24 months) via a longitudinal model. Specifically, the investigators will extend the above GEE approach by accounting for clustering of the repeated measures within individual as well as within practice (and possibly provider). The investigators will test for an (assumed common) effect of the intervention on dental attendance each year, as well as test for varying effects over time by adding an intervention by time interaction term to the model. The initial analysis will assume that missing data are missing completely at random (MCAR).

To account for missing data, the investigators will conduct sensitivity analyses in which responses are imputed under conservative assumptions. Additionally, sensitivity analysis will be conducted for those without a dental home vs. those with a dental home at the start of the study. For the longitudinal analysis, the MCAR assumption will be assessed by modeling missingness of the dental attendance outcome, and testing whether missingness in the second year is related to dental attendance in the first year. If a violation of MCAR is found, alternative approaches (such as use of a GLIMMIX model) will be considered. This model will use a logit link, include the same covariates as above, and incorporate random effects for practices, as well as second-level random effects for individuals in the longitudinal model.

Secondary Statistical Analysis: Secondary outcomes (OH related quality of life, oral hygiene behavior, biometric measures collected at all three PCVs) will be analyzed using a GEE/marginal model approach similarly to that described for dental utilization, but using the appropriate link function depending on the variable; for e.g., an identity link (linear model) may be appropriate for continuous outcomes such as the quality of life measure and biometric measures. Log transformations will be considered for the sake of improving approximations to a normal distribution.

Data Management:

The research staff or older adult will enter answers either electronically or on paper and the research staff will review the questionnaires after completed and prior to the older adult leaving the PCV. The older adult will have a copy of the questionnaire to reference during the surveys as needed. Each paper form and questionnaire will be entered by one individual and verified by a different person.

All study forms and questionnaires collected on paper will be double-checked and kept secure at all times. Further, study forms will be entered into the database and checked for inconsistencies and range and assessed for missing data. Any inconsistencies, outliers, or missing data observed will be compared to the paper document and appropriate corrective actions carried out. REDCap's native data resolution workflow will be used to document and fix any data anomalies. The Data Manager will also respond to data queries generated by the PI, Study Coordinator, or other research staff.

Following collection of all data from the project, additional data processing will be required by the Data Manager, e.g., longitudinal coding of medical illness and dental claims data, creation of psychosocial scale scores. Following PI concurrence, the database will be locked.

Data for this study will include: (1) oral health screening questions, (2) study questionnaires: older adults, provider, medical staff, and practice, (3) abstracted medical and Dentrix dental data, (4) abstracted Medicaid dental claims data, (5) data from observation of providers and medical staff, and (6) EHR audit data. Form revisions should be minimal; however, should they occur, changes will be submitted to the Data Manager for updating and dissemination to research staff.

Quality control is primarily conducted at the study team level through internal processes of data review/data monitoring using periodic custom reports. The Data Manger will run regular validation reports to detect data anomalies and will work with the research staff to resolve any data anomalies that arise during data entry. REDCap's native data resolution workflow will be used to document and fix any data anomalies. The Data Manager will also respond to data queries generated by the PI, Study Coordinator, or other research staff.

• Study Type: Interventional
• Enrollment (Estimated): 929
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Suchitra Nelson, PhD; Phone Number: 216-368-3469; Email: sxn15@case.edu

Study Locations

• United States
  • Ohio
    • Cleveland, Ohio, United States, 44106
      • Recruiting
      • Case Western Reserve University
      • Principal Investigator: Suchitra Nelson, PhD
      • Contact: Suchitra Nelson; Email: suchitra.nelson@case.edu
      • Contact: David Kaelber; Email: dkaelber@metrohealth.org
      • Sub-Investigator: David Kaelber, MD, PhD, MPH

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

Practices:

• Use Epic EHR
• Have older adults covered by Medicaid
• Located within 60 miles of the CWRU research offices

Provider (medical staff or clinician):

Medical staff (MA, nurse):

• Do not float between practices
• Plan not to leave practice within a year
• Provide a signed and dated consent form

Clinicians (Physician, NP):

• Have a minimum of 2 patient-care days per week
• Do not float between practices
• Plan not to leave practice within a year
• Provide signed and dated consent form

Older Adult/Patient Participant:

• Enrolled in CareSource Medicaid Plan
• Female or male aged 55 years or older
• Attending non-urgent primary care visits (PCV) at enrolled site
• Provide signed and dated informed consent form
• Planning to stay in the immediate area for the next year
• Enrolled in the Adult Wellness Registry

Exclusion Criteria:

• The presence of any serious medical health condition (such as dementia or other cognitive disorder not allowing them to participate) where the clinician indicates they should not participate.
• The presence of any serious mental health disorders such as schizophrenia where the clinician indicates they should not participate.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Prevention
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Double

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Arm A: EHR Changes, EHR Training, and CSM theory-based Oral Health Training; AAAC EHR Changes, Medical staff EHR Training, Clinician CSM theory based education and skills training	Behavioral: EHR Changes; Practice-Level: Changes to the Epic EHR system will include the AAAC process to ask 5 oral health questions, advise for dental attendance, assess the type of referral, and connect with referral and resources; Behavioral: Medical Staff EHR Training, Clinician CSM theory-based didactic education and skills training; Provider-Level: Medical staff to complete EHR training and then deliver the ask, advise, assess, connect (AAAC) strategies to screen, refer, and provide resources for oral health. Clinician will receive Common-Sense Model of Self- Regulation (CSM) and Social Cognitive Theory based education and skills training for the physician/nurse practitioner to communicate core OH facts to the patient and provide reinforcement of the importance of dental visits to overall health. Clinicians will also document the encounter in EHR.
Active Comparator: Arm B: Control Arm with Standard ADA Oral Health Training; ADA-based education for clinicians only	Behavioral: Standard ADA Oral Health Training; Provider-Level: Clinician only: Clinicians will receive standard American Dental Association (ADA) based oral health hygiene training (brushing, flossing, fluoridated water, cleaning dentures) and asked to follow their current oral health care with their patients. The usual care currently is to address oral health issues if the patient complains or has a question. The clinicians will not have skills training nor visual resources for the patient encounter.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Dental Attendance	Receipt of dental care as number of visits through Medicaid Claims data (Current Dental Terminology (CDT) codes for preventive or restorative procedures in the past 12 months).	Data will be abstracted from Medicaid Claims data from baseline PCV #1 to 24 month exit visit (PCV #3)
Dental visits	Receipt of preventive and restorative dental care as number of visits through dental EHR data	Data will be abstracted from dental EHR from baseline PCV#1 to 24 month exit visit (PCV #3)

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change in oral hygiene	Frequency of tooth brushing	Assessed as change between baseline primary care visit (PCV #1) and 24 month follow-up exit visit (PCV#3)
Change in Oral Health Quality of Life	Total numeric score on Geriatric Oral Health Quality of Life 12-item questionnaire. Scale is a Likert-scale. Total scores range from 12 as the lowest to 60 being the highest score. Higher scores indicate a higher Oral Health Quality of Life.	Assessed as change between baseline primary care visit (PCV #1) and 24 month follow-up exit visit (PCV#3)
Change in Biometric Measures-Blood Pressure	Systolic and diastolic blood pressure in mmHg	Data will be abstracted from Epic EHR to assess changes from baseline primary care visit (PCV #1) and 24 month follow-up exit visit (PCV #3)
Change in Biometric Measures-BMI	Weight (lbs) and height (inches) will be converted to kg and meters to calculate BMI in kg/m^2	Data will be abstracted from Epic EHR to assess BMI changes from baseline primary care visit (PCV #1) and 24 month follow-up exit visit (PCV #3)
Change in Biometric Measures -blood glucose	Blood glucose in mg/dl	Data will be abstracted from Epic EHR to assess changes from baseline primary care visit (PCV #1) and 24 month follow-up exit visit (PCV #3)
Change in Biometric Measures -serum cholesterol	Serum cholesterol in mg/dl	Data will be abstracted from Epic EHR to assess changes from baseline primary care visit (PCV #1) and 24 month follow-up exit visit (PCV #3)
Change in Biometric Measures -Hemoglobin A1C	HbA1c as a percent (%)	Data will be abstracted from Epic EHR to assess changes from baseline primary care visit (PCV #1) and 24 month follow-up exit visit (PCV #3)

Collaborators and Investigators

• Sponsor: Case Western Reserve University
• Collaborators: National Institute of Dental and Craniofacial Research (NIDCR)
• Investigators: Principal Investigator: Suchitra Nelson, PhD, Case Western Reserve University

Study record dates

Study Major Dates

• Study Start (Actual): September 25, 2024
• Primary Completion (Estimated): October 30, 2028
• Study Completion (Estimated): October 30, 2028

Study Registration Dates

• First Submitted: August 7, 2024
• First Submitted That Met QC Criteria: August 12, 2024
• First Posted (Actual): August 15, 2024

Study Record Updates

• Last Update Posted (Estimated): October 15, 2025
• Last Update Submitted That Met QC Criteria: October 13, 2025
• Last Verified: October 1, 2025

More Information

Terms related to this study

• Keywords: Primary Care; Older Adults; Oral Health; Common Sense Model of Self-Regulation; EHR Modifications (Oral Health Questions and Referral)
• Additional Relevant MeSH Terms: Mouth Diseases; Stomatognathic Diseases; Pathologic Processes; Tooth Diseases; Hemorrhage; Gingival Diseases; Salivary Gland Diseases; Tooth Demineralization; Oral Hemorrhage; Pathological Conditions, Signs and Symptoms; Periodontal Diseases; Dental Caries; Gingival Hemorrhage; Xerostomia
• Other Study ID Numbers: STUDY00000602; 4UH3DE030856-03 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No