A participatory model of the paradox of primary care

Abstract

Purpose: The paradox of primary care is the observation that primary care is associated with apparently low levels of evidence-based care for individual diseases, but systems based on primary care have healthier populations, use fewer resources, and have less health inequality. The purpose of this article is to explore, from a complex systems perspective, mechanisms that might account for the effects of primary care beyond disease-specific care.

Methods: In an 8-session, participatory group model-building process, patient, caregiver, and primary care clinician community stakeholders worked with academic investigators to develop and refine an agent-based computer simulation model to test hypotheses about mechanisms by which features of primary care could affect health and health equity.

Results: In the resulting model, patients are at risk for acute illness, acute life-changing illness, chronic illness, and mental illness. Patients have changeable health behaviors and care-seeking tendencies that relate to their living in advantaged or disadvantaged neighborhoods. There are 2 types of care available to patients: primary and specialty. Primary care in the model is less effective than specialty care in treating single diseases, but it has the ability to treat multiple diseases at once. Primary care also can provide disease prevention visits, help patients improve their health behaviors, refer to specialty care, and develop relationships with patients that cause them to lower their threshold for seeking care. In a model run with primary care features turned off, primary care patients have poorer health. In a model run with all primary care features turned on, their conjoint effect leads to better population health for patients who seek primary care, with the primary care effect being particularly pronounced for patients who are disadvantaged and patients with multiple chronic conditions. Primary care leads to more total health care visits that are due to more disease prevention visits, but there are reduced illness visits among people in disadvantaged neighborhoods. Supplemental appendices provide a working version of the model and worksheets that allow readers to run their own experiments that vary model parameters.

Conclusion: This simulation model provides insights into possible mechanisms for the paradox of primary care and shows how participatory group model building can be used to evaluate hypotheses about the behavior of such complex systems as primary health care and population health.

Keywords: decision modeling; economic models; statistical models.

© 2015 Annals of Family Medicine, Inc.

Figures

Figure 1

Diagram of the main mechanisms of the model.

Figure 2

Average health for people receiving primary or special care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows average health of patients (represented by a number between 0 and 1 with 1 being perfect health) in neighborhood A (left) and neighborhood B (right) for experiment 1 (no primary care features turned on), and the bottom row shows the same result for experiment 6 (all primary care features turned on). The black line in each graph shows the average health of specialty care seekers in each neighborhood, and the gray line shows the health of primary care seekers. The x axis is time (in weeks) and the y axis is health.

Figure 2

Average health for people receiving primary or special care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows average health of patients (represented by a number between 0 and 1 with 1 being perfect health) in neighborhood A (left) and neighborhood B (right) for experiment 1 (no primary care features turned on), and the bottom row shows the same result for experiment 6 (all primary care features turned on). The black line in each graph shows the average health of specialty care seekers in each neighborhood, and the gray line shows the health of primary care seekers. The x axis is time (in weeks) and the y axis is health.

Figure 2

Average health for people receiving primary or special care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows average health of patients (represented by a number between 0 and 1 with 1 being perfect health) in neighborhood A (left) and neighborhood B (right) for experiment 1 (no primary care features turned on), and the bottom row shows the same result for experiment 6 (all primary care features turned on). The black line in each graph shows the average health of specialty care seekers in each neighborhood, and the gray line shows the health of primary care seekers. The x axis is time (in weeks) and the y axis is health.

Figure 2

Average health for people receiving primary or special care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows average health of patients (represented by a number between 0 and 1 with 1 being perfect health) in neighborhood A (left) and neighborhood B (right) for experiment 1 (no primary care features turned on), and the bottom row shows the same result for experiment 6 (all primary care features turned on). The black line in each graph shows the average health of specialty care seekers in each neighborhood, and the gray line shows the health of primary care seekers. The x axis is time (in weeks) and the y axis is health.

Figure 3

Average health for people with or more ongoing health conditions, receiving primary or specialty care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows average health of patients (represented by a number between 0 and 1 with 1 being perfect health) with 3 or more nonacute diseases in neighborhood A (left) and neighborhood B (right) for experiment 1 (no primary care features turned on), and the bottom row shows the same result for experiment 6 (all primary care features turned on). The black line in each graph shows the average health for specialty care seekers in each neighborhood, and the gray line shows the health for primary care seekers. On the x axis is time (in weeks). Note that the results are graphed only after the model has run long enough for a sufficient number of patients who have accumulated multiple diseases.

Figure 3

Average health for people with or more ongoing health conditions, receiving primary or specialty care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows average health of patients (represented by a number between 0 and 1 with 1 being perfect health) with 3 or more nonacute diseases in neighborhood A (left) and neighborhood B (right) for experiment 1 (no primary care features turned on), and the bottom row shows the same result for experiment 6 (all primary care features turned on). The black line in each graph shows the average health for specialty care seekers in each neighborhood, and the gray line shows the health for primary care seekers. On the x axis is time (in weeks). Note that the results are graphed only after the model has run long enough for a sufficient number of patients who have accumulated multiple diseases.

Figure 3

Average health for people with or more ongoing health conditions, receiving primary or specialty care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows average health of patients (represented by a number between 0 and 1 with 1 being perfect health) with 3 or more nonacute diseases in neighborhood A (left) and neighborhood B (right) for experiment 1 (no primary care features turned on), and the bottom row shows the same result for experiment 6 (all primary care features turned on). The black line in each graph shows the average health for specialty care seekers in each neighborhood, and the gray line shows the health for primary care seekers. On the x axis is time (in weeks). Note that the results are graphed only after the model has run long enough for a sufficient number of patients who have accumulated multiple diseases.

Figure 3

Average health for people with or more ongoing health conditions, receiving primary or specialty care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows average health of patients (represented by a number between 0 and 1 with 1 being perfect health) with 3 or more nonacute diseases in neighborhood A (left) and neighborhood B (right) for experiment 1 (no primary care features turned on), and the bottom row shows the same result for experiment 6 (all primary care features turned on). The black line in each graph shows the average health for specialty care seekers in each neighborhood, and the gray line shows the health for primary care seekers. On the x axis is time (in weeks). Note that the results are graphed only after the model has run long enough for a sufficient number of patients who have accumulated multiple diseases.

Figure 4

Average number of visits for people receiving primary or specialty care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows average number of clinician visits for patients in neighborhood A (left) and neighborhood B (right) for experiment 1 (no primary care features turned on), and the bottom row shows the same result for experiment 6 (all primary care features turned on). The black line in each graph shows the average clinician visits for specialty care seekers in each neighborhood, and the gray line shows the average clinician visits for primary care seekers. On the x axis is time (in weeks).

Figure 4

Average number of visits for people receiving primary or specialty care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows average number of clinician visits for patients in neighborhood A (left) and neighborhood B (right) for experiment 1 (no primary care features turned on), and the bottom row shows the same result for experiment 6 (all primary care features turned on). The black line in each graph shows the average clinician visits for specialty care seekers in each neighborhood, and the gray line shows the average clinician visits for primary care seekers. On the x axis is time (in weeks).

Figure 4

Average number of visits for people receiving primary or specialty care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows average number of clinician visits for patients in neighborhood A (left) and neighborhood B (right) for experiment 1 (no primary care features turned on), and the bottom row shows the same result for experiment 6 (all primary care features turned on). The black line in each graph shows the average clinician visits for specialty care seekers in each neighborhood, and the gray line shows the average clinician visits for primary care seekers. On the x axis is time (in weeks).

Figure 4

Average number of visits for people receiving primary or specialty care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows average number of clinician visits for patients in neighborhood A (left) and neighborhood B (right) for experiment 1 (no primary care features turned on), and the bottom row shows the same result for experiment 6 (all primary care features turned on). The black line in each graph shows the average clinician visits for specialty care seekers in each neighborhood, and the gray line shows the average clinician visits for primary care seekers. On the x axis is time (in weeks).

Figure 5

Average number of sick visits for people receiving primary or specialty care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows the average number of sick visits for patients in neighborhood A (left) and neighborhood B (right) from experiment 1. The bottom row shows the same results for experiment 6. In each graph, the black line tracks the average sick visits for specialty patients, and the gray line tracks this number for primary care patients.

Figure 5

Average number of sick visits for people receiving primary or specialty care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows the average number of sick visits for patients in neighborhood A (left) and neighborhood B (right) from experiment 1. The bottom row shows the same results for experiment 6. In each graph, the black line tracks the average sick visits for specialty patients, and the gray line tracks this number for primary care patients.

Figure 5

Average number of sick visits for people receiving primary or specialty care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows the average number of sick visits for patients in neighborhood A (left) and neighborhood B (right) from experiment 1. The bottom row shows the same results for experiment 6. In each graph, the black line tracks the average sick visits for specialty patients, and the gray line tracks this number for primary care patients.

Figure 5

Average number of sick visits for people receiving primary or specialty care in 2 neighborhoods. PC = primary care; SC = specialty care. The top row shows the average number of sick visits for patients in neighborhood A (left) and neighborhood B (right) from experiment 1. The bottom row shows the same results for experiment 6. In each graph, the black line tracks the average sick visits for specialty patients, and the gray line tracks this number for primary care patients.