Modern primary care is shifting from a reactive model, where providers primarily address immediate illnesses, to a proactive system focused on long-term health management. The patient panel serves as the foundational organizing unit, defining the specific population for whom a primary care provider and their team are professionally responsible. This structure allows practices to move beyond episodic visits to manage the overall health of a defined group of people. Identifying this population allows practices to better allocate resources and implement population health strategies aimed at improving quality of care and patient outcomes.
Defining the Patient Panel
A patient panel is the specific group of patients for whom a primary care provider and their associated care team accept clinical responsibility. This is distinct from a general patient list, as the panel represents an active commitment to manage the health of every individual on it. The process of formally assigning patients to a provider’s panel is called empanelment, which establishes a consistent, long-term relationship between the patient and a specific care team.
Patients are assigned to a panel through a process known as patient attribution. This assignment can happen in several ways, such as a patient explicitly choosing a provider, or through an algorithm based on recent claims data. In value-based payment models, attribution is important because payers use this methodology to determine the specific population for which a provider is held accountable for cost and quality outcomes. Empanelment is an internal practice activity that matches every patient to a care team, while attribution is typically a payer-level activity that assigns accountability to the practice or provider.
Panel Management and Proactive Care
Panel management is the set of processes and tools used by the primary care team to systematically care for the entire population assigned to a specific panel. This involves utilizing electronic health record data and patient registries to identify and address care needs for patients who have not recently scheduled an appointment. The goal is to shift care from a reactive approach—waiting for a patient to present with a problem—to a proactive one focused on prevention and chronic condition maintenance.
This systematic approach allows the team, often including medical assistants and nurses, to run targeted reports and identify patients with specific care gaps. For instance, a panel manager can generate a registry list of patients overdue for a mammogram or diabetic patients who have not had a necessary annual foot exam or A1C test. Staff then conduct outreach by calling or sending reminders to these patients to schedule the needed service.
Panel management also supports chronic disease management by allowing providers to monitor entire populations, such as patients with hypertension or asthma. This enables the practice to ensure that standardized, evidence-based protocols are being followed for every patient with a particular condition. By proactively managing these populations, the care team can intervene before conditions worsen, supporting better health outcomes and reducing the need for costly emergency services. The practice team can also address care gaps during an office visit for an unrelated issue, a process known as in-reach.
Measuring Panel Size and Its Effect on Access
The number of patients on a panel, or the panel size, is a metric that significantly influences both the quality of care and patient access to the practice. An optimal panel size is defined as the number of patients a provider and their care team can effectively manage while meeting the population’s need for timely access and high-quality care. This number is not fixed and must be balanced against the demands of the system, including patient access, quality outcomes, and provider workload.
Calculating panel size is complex and goes beyond a simple count of active patients; it must account for case mix, which refers to the complexity of the patient population based on factors like age, gender, and chronic disease burden. A panel with many patients suffering from multiple chronic conditions, for example, will require a smaller panel size than one consisting mostly of healthy patients. Practices often use modeling studies and established formulas that consider the provider’s available appointment slots and the average number of visits per patient per year to determine an appropriate size.
When panel sizes are too large, it can negatively affect patient experience by increasing waiting times for routine appointments and potentially worsening clinical quality outcomes. Conversely, an optimized panel size, often supported by a team-based care model, improves patient access and continuity of care. Practices may also track panel ratios, such as the number of clinical support staff per provider, as a quality metric to ensure the team has the necessary capacity to manage the panel’s health needs proactively. Many practices aim for a lower panel size than 2,500 patients per physician, adjusting for patient complexity to allow for proper preventive care.