Collect and Use Data for Quality Improvement

Consider hiring or assigning a current staff member to lead the effort to collect and use data. The person you hire or assign to this role should understand how to use data for quality improvement and be familiar with the data already available at your practice. For larger practices or health systems, consider establishing a dedicated data team rather than a single person to distribute responsibility and garner additional perspectives.

Your practice likely collects data on the medical care received by patients, participates in a registry, and/or meets Physician Quality Reporting System (PQRS) requirements. If the data you already collect are sufficient for quality improvement, additional data collection efforts will not be necessary.

During the early stages of integrating behavioral health in your primary care practice, your data needs are likely to be related to the operational and financial aspects of integration. Data can help answer questions such as:

• Can patients be seen by an integrated behavioral health provider within a reasonable timeframe?
• Is there routine screening for behavioral health conditions that can identify patients who need referrals?
• Are there established referral workflow to ensure appropriate referrals to the behavioral health provider(s) for patients who screen positive for mental health issues or substance use?
• Which providers are referring patients to the behavioral health provider(s)?
• Which patients are being referred to the behavioral health provider(s)?
• Are patients in the integrated care target population being seen by a behavioral health provider?

Data from billing and scheduling systems may be adequate to answer many of these questions. If additional data elements must be captured, think about whether they can be collected as part of existing work processes and whether they need to be collected continuously or periodically. Examples of data to collect for integrated behavioral health include:

Operational Systems Data:

• Behavioral Health Referral Rate: Percentage of primary care visits resulting in a behavioral health referral.
• Warm Handoff Rate: Number/percentage of warm handoffs successfully completed.
• Time to First Behavioral Health Appointment: Average wait time from referral to initial behavioral health consultation.
• Behavioral Health Appointment No-Show Rate: Percentage of scheduled behavioral health appointments that are missed.
• Behavioral Health Provider Panel Size/Productivity: Number of patients managed or visits completed per behavioral health provider.
• Co-location Utilization: Percentage of patients seen by a behavioral health provider on the same day as their primary care visit.

Financial and Utilization Data:

• Behavioral Health Billing Codes Utilized: Tracking the frequency and type of integration-specific CPT codes billed.
• Revenue Generated by Behavioral Health Services: Financial income from integrated behavioral health services.
• Total Cost of Care (Pre/Post): Comparing overall healthcare expenditures for patients before and after engaging in integrated behavioral health.
• Emergency Department Utilization: Tracking emergency department visits for behavioral health crises or somatic complaints before and after integrated behavioral health.
• Hospitalization Rates: Changes in inpatient psychiatric or general medical hospitalizations.

Clinical Outcomes & Patient Progress Data:

• Screening Positivity Rates: Percentage of patients screening positive for depression (e.g., PHQ-9 score), anxiety (e.g., GAD-7 score), or substance use (e.g., DAST-10 score).
• Symptom Reduction: Average change in depression, anxiety, or substance use symptom scores over time.
• Functional Improvement: Patient-reported improvements in daily functioning or quality of life (e.g., using PROMIS measures).
• Medication Adherence: For patients on psychiatric medications, tracking adherence rates.
• Chronic Disease Management Outcomes: For patients with comorbid chronic conditions, tracking improvements in medical markers (e.g., A1c for diabetes, blood pressure for hypertension) after BHI.

Patient and Provider Experience:

• Patient Satisfaction: Survey data on patient satisfaction with access to and quality of integrated behavioral health services.
• Provider Satisfaction: Surveys on primary care provider and behavioral health provider satisfaction with teamwork, communication, and support within the integrated model.

Consider the following questions to help inform your data collection plan:

What data do you currently collect?

Take inventory of what data you already collect. You might be collecting more data than you realize, especially if you have an electronic health record (EHR) system, use patient registries, or participate in mandatory reporting.

What data do you want to collect?

After reviewing the data your practice has readily available, look for any gaps or data needs. Consider these questions:

• Do the available data help you identify, track, and manage patients in need of integrated care?
• Do the available data allow you to aggregate information at the practice level for monitoring and improving the quality of integrated care?
• Do the available data help you assess quality of care for patients in your practice?

What data collection tools exist?

The next step is to map your data needs to available tools or other data sources. Data collection tools are available for functions such as these:

• Identifying patients who may benefit from integrated care.
• Monitoring treatment progress.
• Assessing quality of care.

When assessing the outcomes of integrated care, it is important to think broadly and adopt a "balanced scorecard" of measures to help you understand the impact of integration. A balanced scorecard might include:

• Clinical outcome measures.
• General functional measures.
• Measures of financial impact (e.g., total cost of care).
• Patient experience of care.
• Provider and staff experience of care.

If your practice does not collect data on a regular basis, consider small pilot initiatives or Plan-Do-Study-Act (PDSA) cycles before launching into full-scale data collection. By starting small, you can implement a number of consecutive data collection, reporting, and quality improvement cycles, each building on the previous one.

A pilot initiative is a small-scale, short-term project designed to test the feasibility and effectiveness of a new approach, such as integrating behavioral health services or implementing a quality improvement strategy, before wider implementation in a primary care practice or health system. The PDSA cycle is an iterative, four-step process that will allow your practice to learn and adapt as you implement and test new quality improvement strategies. By embedding PDSA cycles within your pilot initiatives, your practice or system can systematically test and refine your data collection and quality improvement efforts before scaling them up.

• Plan: Identify a specific aim for improvement and develop a plan to test a change. This includes defining the objective, making predictions about what will happen, and outlining the steps to carry out the test.
• Do: Implement the plan and collect data to document the changes and their effects.
• Study: Analyze the data and compare the results to your predictions. Reflect on what you learned from the test.
• Act: Based on the study results, decide what to do next. You might adopt the change, adapt it based on your findings, or abandon it and try a different approach in a new PDSA cycle.

Consider these questions when planning for the pilot initiative or PDSA cycle:

What is the purpose of the pilot initiative or PDSA cycle?Each pilot/PDSA cycle might focus on only one of the following aspects:

• Identifying patients in need of integrated care.
• Monitoring patient progress and making needed adjustments to the treatment plan.
• Monitoring patients who have improved.
• Tracking patients who do not adhere to their follow-up appointment schedules.
• Improving patient experience.
• Improving health outcomes.

What metric or indicator will illustrate that this pilot or PDSA cycle "worked"?

• Identify metrics that you are interested in and decide what level of improvement would be considered a success before moving forward with full-scale data collection.
• It may help to use a driver diagram or logic model for specific targeted problems. A mapped out theory of change can help you determine if your pilot efforts are really leading to improved quality, improved health outcomes, and increased cost-effectiveness.

What will be the size of the pilot or PDSA cycle data collection plan?

• How many participants will be included in your pilot? How long will it last?

What will the sample of patients for the pilot or PDSA cycle look like?

• How will you sample patients for the pilot?

If you conduct a pilot or PDSA cycle initiative, pay attention to what works and what doesn't as you transition into full-scale data collection. Make any refinements to the process as needed.

The data you collect can provide invaluable information for quality improvement. For example, you can use data to identify areas for improvement or assess the outcomes of your integrated care initiatives. Remember to continually revisit the Playbook as an upward spiral, gradually approaching the North Star of a seamlessly integrated behavioral health and primary care setting.

Other data considerations include data storage and security. Consider the following questions:

• Are data stored in an existing database, or does your practice need to choose a database platform?
• If you are selecting a database platform, will an off-the-shelf platform suit your needs, or do you need a platform that is custom-designed for your setting?

It is important to gain knowledge of HIPAA requirements and ensure that data are stored and used according to the requirements.