Have you heard the phrase, “What you measure improves”? It’s a simple concept to understand but a challenge for some organizations to put into practice. Dental Service Organizations (DSOs) have been grappling with this issue for years. Despite significant advocacy and investment in better data practices, our industry still lags behind others in making good data a reality.
The Challenge of Dental Data
Gathering dental data and putting it to use within a DSO can be daunting. Whether it’s selecting a practice management system (PMS), ensuring secure and compliant data collection, or maintaining data quality from the outset, there are several key decisions to navigate when building a comprehensive data strategy.
Anyone attempting to build a functional data warehouse must consider the following:
1. Reporting – Start with the End in Mind
What do you want to accomplish? What do you need to measure? Think beyond KPIs—consider your overall vision for the company. You are building a framework that will provide insight into the financial and operational health of your DSO, helping leadership make better decisions and achieve their objectives. Take the time to define your goals, and the necessary KPIs, dashboards, and reports will follow.
Consider your audience. The finance team will require profit and loss statements with detailed expense breakdowns. The operations team will need key ratios used daily in practice management. Good data design incorporates all these requirements and builds an underlying framework that provides each team with the necessary insights. By understanding your objectives upfront, you lay the foundation for a successful data warehouse.
2. Create a Model for Good Data at the Point of Entry
We often repeat the phrase, “Garbage in, garbage out” (GIGO), but how many of us take steps to prevent it? For DSOs, this means developing training and workflows that ensure proper data entry at the practice level. A data warehouse is only as good as the consistency of its inputs—this is a fundamental requirement. Unfortunately, no amount of coding can compensate for poor data entry. As stewards of data integrity, we must collaborate with operations teams to provide clear guidelines for practice managers.
There are two common areas where poor data entry undermines data quality:
- Consistent Provider ID Usage – Each provider (doctor, hygienist, etc.) must have a single, unique provider ID. When office managers create multiple IDs for the same provider, it becomes difficult to track production and collections accurately. Ensure all relevant production is tied to the correct, single provider ID. Then tie ALL relevant production to the correct, single provider ID.
- Monthly Reconciliation of Explanation of Benefits (EOBs) – Not only is this a legal requirement, but it’s also a best practice for maintaining clean financial data. Office managers should reconcile EOBs regularly to keep patient and insurance balances accurate. Failing to do so leads to inflated accounts receivable (A/R), which negatively impacts reporting and decision-making.
3. Practice Management Systems (PMS)
There are many PMS options available, and even more opinions about them. These systems fall into two main categories: On-Premise and Cloud-Based.
- On-Premise PMS – This setup requires purchasing and maintaining a physical server at the practice location. Data collection involves installing an agent (software) that periodically copies the local database and pushes it to a centralized online service. To optimize storage and bandwidth, these agents typically perform delta updates, capturing only the data that has changed (e.g., newly scheduled patients, completed procedures, and payments received).
- Cloud-Based PMS – Cloud systems store data online and can be accessed as a service. Instead of an agent, data is collected through an Application Programming Interface (API), which connects the PMS to the data warehouse. API connections allow for full database copies or delta updates, similar to on-premise setups.
Regardless of whether data is gathered via an agent or an API, it can be consolidated into a single data warehouse for all practice locations.
4. HIPAA Compliance and Security
All data within a PMS is considered Protected Health Information (PHI)—or more specifically, Electronic PHI (ePHI). This means that all data stored in a DSO’s data warehouse is subject to HIPAA regulations. IT professionals have a fiduciary responsibility to ensure that ePHI is handled securely.To comply with HIPAA, all data transfers must be:
- Encrypted to prevent unauthorized access.
- Protected by Multi-Factor Authentication (MFA/2FA) for added security.
- Safeguarded with cybersecurity measures such as firewalls, managed switches, and anti-virus software with real-time monitoring and auto-remediation.
Additionally, a lesser-known but equally important HIPAA provision requires that all PHI and ePHI remain within the borders of the United States. If you are setting up a data warehouse, ensure your provider keeps all PHI data stored in U.S.-based data centers.
Final Thoughts
A well-structured data strategy is crucial for the success of a DSO. Reliable data enables better decision-making, but good data doesn’t happen by accident—it requires intentional design, time, commitment, and resources. There are no shortcuts. However, when a team aligns behind a shared data vision, a DSO can build a powerful, differentiating advantage.By keeping the end in mind and consistently applying these best practices, your DSO can achieve long-term data success.
Andy Taylor is the Head of IT for Dentive, LLC. With over 25 years of experience leading successful teams and developing scalable processes, he brings a wealth of business and technical expertise. His measured approach to strategy and intelligent design has helped private, PE-backed, and publicly traded companies implement meaningful, high-impact solutions.