Leveraging Data Analytics to Optimize Practice Operations

In your day-to-day patient care routines, you can see progress. You complete countless exams and find diagnoses, teach patients to manage their eye conditions, and help them achieve better outcomes. These are all observable and positive, but beyond these assessments, data analytics will help you truly measure and increase success.

Data analytics in eye care allows you to make smarter, faster, and more profitable practice decisions that drive operational excellence, no matter your starting point. Eye care practice management from independent clinics to multi-location networks scales by incorporating real-time data insights into your daily workflow. Calculating these figures can significantly improve the efficiency of eye care practices, patient satisfaction, and your bottom line.

Why Data Analytics Matters in Eye Care Practices

Without quantifiable data, many eye care practices rely on subjective measurements and estimations. This information is still valuable, but it is reactive rather than proactive. With the increasing pressures of value-based care structures, rising patient expectations, and consistently slim financial margins, reactive data is not competitive.

Instead of waiting for problems to solve, data provides real-time insights that offer a competitive advantage in a value-based care environment. Quantifiable information pinpoints specific ways to increase efficiency in an ophthalmology clinic.

You can use this information to find ways to increase efficiency in an optometry clinic and tailor business decisions like:

• Staffing, scheduling, and availability
• Choosing equipment that suits your practice needs
• Emphasizing staff specialties that support patient demographics and common conditions
• Balancing patient throughput with the costs of running your business

Monitor the unmeasurable information, but utilize data analytics to improve patient satisfaction and continue to deliver appropriate care while managing costs effectively.

Key Patient Data Points to Analyze

Deciding how to use data analytics in an ophthalmology practice will depend on your unique needs, but we’ve found these six patient data points apply to almost every provider.

1. Test Volume and Utilization

First, quantify the test volume and the utilization of different offerings. How many visual field, color vision, or pupillometry tests are you performing each day, week, or month? This insight will offer visibility into your operational capability.

Break down the test utilization by provider to help measure specialties and technician utilization. For multi-location practices, compare offerings and utilization rates at different locations, then use that data to refocus your efforts.

Use Case

Suppose you discover that one location is underutilizing its visual field testing equipment, while another is operating at peak capacity. This insight might suggest a need for additional virtual visual field devices or switching from a traditional tabletop perimeter to a more accessible and mobile virtual solution. It can also help justify the investment in additional units to meet demand or shift testing times to better align with patient flow.

2. Patient Throughput and Wait Times

Around half of all healthcare appointments start late. There are numerous reasons why this happens, but understanding how often late or extended appointments occur at your practice can help optimize throughput and reduce wait times. To find this information, you can clock the time from patient check-in to check-out, the time spent with each technician in each room, and of course, the duration of common tests and screenings.  

Use Case

Reduce bottlenecks and improve patient flow by utilizing enhanced scheduling software, staff training, and implementing new processes, such as conducting visual field tests in the waiting room using a virtual headset. This way, you can offset misaligned schedules and stretch appointment timeslots without impacting the quality of patient care.

3. Test Duration and Completion Rates

Every minute matters in a busy clinic, and workflows are often streamlined to their bare essentials. There’s no time to waste, so analyzing how long each vision test takes, how frequently tests are left incomplete, and how often they’re repeated will reveal opportunities for streamlining workflows.

Use Case

Switching from a Humphrey Field Analyzer to Virtual Field saves an average of 2.4 minutes per 24-2 exam. That efficiency gain adds up quickly across dozens of patients. When comparing the efficiency of these visual field testing machines, you may discover some more subjective or less measurable information, such as patient discomfort, anxiety, or technician frustration with outdated equipment.  

4. Patient Demographics and Accessibility Needs

The benefits of real-time analytics in visual field testing align one-to-one with patient care. Your patient base is likely diverse, so understanding the age, mobility limitations, and primary languages can help shape your equipment choices and staff education strategies.

Use Case

Older patients or those with limited mobility may find traditional tabletop perimeters physically difficult (or even impossible) to use. Virtual Field’s headset is a lightweight, portable, and accessible option for a wide range of patients. Over 40 audio language options help reach a broader patient base and can significantly improve patient understanding. Patients who are better accommodated tend to be more satisfied and offer more referrals.

5. Device Performance and Reliability

Unplanned downtime or frequent calibration issues with testing devices can hurt both practice revenue and patient confidence. Track error rates and the frequency of device calibration, as these data points have a direct impact on the quality and quantity of patient care you can provide.

Use Case

Suppose a traditional tabletop perimeter shows a high error rate and requires frequent maintenance. Equipment that breaks down or underperforms cannot sustain a busy eye care practice. Virtual Field analytics are robust and easy to measure, so you can quickly weigh the expenses of lost revenue from failed tests with the cost of an upgrade.

6. Billing and Reimbursement Metrics

Operational efficiency includes more than patient satisfaction and flow. Track reimbursement rates and claims denials, then compare that data to your practice’s documentation and coding practices. You might uncover errors or opportunities to upskill your staff.

Use Case

If your practice is seeing high denial rates for specific tests due to documentation issues, it might be time to retrain your billing team. Better data visibility also helps identify which tests are most profitable. Eye care technologies that improve profitability and are easier to code will help support maximum reimbursement.

Turning Insights into Action

Optometry practice analytics begins with collecting data, but it becomes truly useful only when you act on it. Here are a few ways practices can use their insights to make tangible improvements:

• Restructure scheduling for efficiency if afternoon no-show rates are high.
• Assign staff more efficiently based on real patient volume to balance workloads.
• Personalize the patient experience with accessible by pre-selecting languages or choosing the best test types.
• Forecast revenue and plan resource allocation for smarter equipment purchases and hiring plans.

Visual Field Testing Data Meets Practice Efficiency Strategies

Intuitive insights are valuable, and you have a deep understanding of your patients’ needs. But when practice leaders have access to real-time, actionable insights, they can make fast, informed decisions that increase efficiency in many ways. Ready to see eye care ROI improvement? Contact Virtual Field for a demo or analytics consultation.