Integrating Technology & Care to Shape a Smarter DSO Future

Brittany Kearney is a seasoned healthcare executive specializing in clinical operations, strategic program development, and leadership in the dental industry. With expertise in compliance, recruitment, and business growth, she has led key programs optimizing workflows, enhancing patient care, and fostering team success.

In an engaging interaction with Global Woman Leader Magazine, Brittany shares her insights on how evolving patient expectations and dental technology advancements are reshaping Dental service Operations’ (DSO) operational efficiencies, the challenges of integrating AI-driven diagnostics, and strategies for maintaining clinical excellence, brand identity, and business sustainability.

How are evolving patient expectations and advancements in dental technology reshaping operational efficiencies in DSOs? What gaps still exist between clinical excellence and business sustainability?

Evolving patient expectations and advancements in dental technology are driving DSOs to enhance operational efficiencies through AI, digital workflows, teledentistry, and centralized data systems. These innovations streamline processes, improve patient engagement, and optimize treatment planning. However, gaps remain between clinical excellence and business sustainability. Challenges include balancing standardization with personalized care, overcoming high technology adoption costs, addressing provider burnout, navigating regulatory complexities, and maintaining financial sustainability without compromising quality. To bridge these gaps, DSOs must integrate technology strategically while prioritizing clinician support, regulatory compliance, and patient-centered care to ensure both operational success and high-quality treatment outcomes.

With the rise of AI-driven diagnostics and remote care models, how should DSOs integrate emerging technologies while ensuring seamless adoption by clinical teams and maintaining high patient trust?

DSOs should integrate AI-driven diagnostics and remote care models by prioritizing clinician training, phased implementation, and transparent patient communication. AI should enhance, not replace, clinical expertise, ensuring providers remain central to care. Educating patients on AI’s benefits while addressing privacy and accuracy concerns fosters trust. Compliance with HIPAA and industry regulations is critical for data security. Continuous performance monitoring and clinician feedback help refine workflows and optimize adoption. By strategically implementing AI with a focus on clinician empowerment, patient transparency, and regulatory adherence, DSOs can leverage emerging technologies while maintaining high-quality care and trust.

What unexpected operational challenges have surfaced as DSOs scale? How can organizations proactively refine clinical frameworks to mitigate inefficiencies before they become systemic?

As DSOs scale, unexpected challenges include inconsistent care quality, provider burnout, technology adoption resistance, and complex regulatory compliance. Operational inefficiencies arise from fragmented workflows, varied state regulations, and the struggle to balance standardization with personalized care. To mitigate these issues, DSOs should implement proactive clinical frameworks by standardizing best practices while allowing flexibility for individualized patient care. Investing in ongoing provider training, AI-driven workflow optimizations, and centralized data management enhances efficiency. Regular audits, clinician feedback loops, and agile adaptation of protocols help identify inefficiencies early. By prioritizing scalable yet adaptable frameworks, DSOs can sustain quality care, improve provider satisfaction, and prevent operational bottlenecks before they become systemic issues.

What proactive measures can DSOs adopt to build a scalable, adaptable compliance infrastructure without stifling innovation?

DSOs can build a scalable, adaptable compliance infrastructure by implementing real-time monitoring systems, centralized compliance management, and AI-driven audit tools to track evolving regulations. Standardizing protocols while allowing flexibility for state-specific laws ensures consistency. Ongoing staff training, internal audits, and cross-functional compliance teams help maintain adherence without disrupting innovation. Leveraging secure cloud-based platforms for patient data ensures HIPAA compliance while enabling technological advancements. Embedding compliance into workflow automation minimizes administrative burdens, allowing providers to focus on care. By fostering a compliance-first culture that aligns with operational goals, DSOs can proactively address regulatory shifts while maintaining agility for continued growth and innovation.

How can DSOs leverage real-time analytics to identify inefficiencies in patient flow, treatment planning, and resource allocation? What barriers exist to widespread adoption of such tools?

DSOs can leverage real-time analytics to optimize patient flow, treatment planning, and resource allocation by using AI-driven dashboards, predictive modeling, and automated reporting. These tools help identify bottlenecks, reduce wait times, and streamline scheduling, improving operational efficiency and patient experience. Analytics also enhance treatment consistency by tracking provider performance and case acceptance rates.

However, barriers to adoption include high implementation costs, data integration challenges across multiple locations, staff resistance to change, and concerns over data security and compliance. To overcome these, DSOs must invest in user-friendly analytics platforms, provide ongoing staff training, and ensure interoperability with existing systems, enabling seamless adoption and long-term efficiency improvements.

As DSOs continue expanding, how can they ensure consistent clinical quality and brand identity across diverse markets while allowing room for localized operational flexibility?

DSOs can ensure consistent clinical quality and brand identity by standardizing treatment protocols, centralized training, and AI-driven quality audits. Real-time analytics and patient feedback loops help maintain care standards.

For localized flexibility, DSOs should empower regional teams to adapt workflows based on market needs, regulations, and demographics. Decentralized leadership and data-driven decision-making balance uniformity with customization.

Clear brand messaging, centralized marketing, and technology-driven support systems unify identity while allowing tailored patient engagement. By aligning core standards with adaptable frameworks, DSOs can scale efficiently without compromising quality or local relevance.