With the healthcare landscape changing from fee-for-service to fee-for-value models, healthcare provider systems (hospitals, clinics, independent physician associations, etc.) are now more than ever under pressure to effectively manage the health and cost outcomes of their given populations. Under such models, providers are not only providing healthcare service to the patients, but also sharing in the financial risk and reward of patient costs. To effectively become a value-based organization, providers today are actively adopting a process broadly termed as population health. The Population Health process usually starts with identifying key segments of a population that face certain risks of adverse health outcomes and thereby high cost – a step known as risk stratification. Once risk is stratified, appropriate patient intervention programs are employed to improve access to health, targeted encounters with providers, and continuous monitoring of patient risk leading to lower emergency room visits, better clinical outcomes (such as properly managed blood glucose levels for diabetics) and lower financial cost.
There are many proven methods of risk-stratification to assign patients to low, medium, or high-risk groups. For example, the Adjusted Clinical Groups method examines patient diagnoses and the Elder Risk Assessment method assigns risk based on patient demographics. In today’s market, we observe many proprietary methods of risk stratification developed by various provider systems. The variables used in risk stratification can be classified into the following categories:
- Clinical: Data from electronic medical records (EMRs), patient vitals, laboratory data, etc.
- Administrative: Usually consists of patient claims that track diagnosis and procedures already conducted.
- Socio-Economic: Patients’ social situations, family and friend support systems, language preference, community involvement, the degree of influence out of pocket expenses could have on the patient’s well-being, etc.
- Lifestyle: Health and activity tracking devices such as Fitbit, Apple Watch, etc., which carry critical daily lifestyle data about a patient.
While the above categories play a large role in risk stratification, a new dimension known as Spatial Access can significantly lend leverage to the provider systems in affecting patient outcomes. For some patients, the overall risk may increase significantly due to their spatial, geographical, and transportation access to medical and wellness resources. Spatial access refers to patients’ geographic proximity and ease of mobility to resources such as hospitals, primary care physician offices, primary and specialty care clinics, nurses, etc. The geographic arrangement of patient and provider resources can play a significant role in healthcare utilization. For example, patients living in areas with fewer healthcare resources— regions often termed as ‘doctor deserts’ — have been linked with higher rates of preventable ER visits that are notorious for raising healthcare costs without necessarily improving healthcare outcomes. Using geographical and spatial analysis to supplement existing risk stratification techniques can help providers with an untapped method of assessing risk and generating better ROI in the long run.
To incorporate Spatial Access analysis into risk stratification, providers must:
- Gather patient and patients’ social network geographic information
Most EMR systems already contain patient address information but often lack information about the patients’ social network. The following types of data should be collected and refreshed on an annual basis:
- Distance to closest primary care clinic, both straight line and network distance
- Distance to closest primary care provider, both straight line and network distance
- Spatial density of medical resources in a given area, especially primary care services
- Access to vehicle transportation, either on own or through family member
- Proximity to public transportation
- Conduct “Spatial Access” risk stratification
Using a geographic information system (GIS), assign relative risk to each patient based on each of the components listed above and then create a composite risk based on all of the attributes.
- Represent population risk stratification visually via mapping
Examine which areas of a provider’s service areas are prone to having individuals with high-risk; look for clusters of high or low-risk patients in doctor deserts. Viewing individual or aggregate risk through mapping would offer analysts and decision makers a comprehensive view of what types of risk are occurring in their service area.
- Strategize how to implement interventions based on locations of high-risk patients
If clusters of high-risk patients exist in a certain area, begin to strategize about what kinds of interventions may alleviate the problem. Interventions may include the placement of new primary or specialty care clinics. Since creating new clinics can be challenging, increased use of mobile provider teams can be an alternate solution. Lastly, a combination of telemedicine and mobile medicine should be assessed for the right mix of care for doctor deserts and lack of physical clinics.
Understanding the spatial context of patient demand vs. provider supply of healthcare service is an important component for accountable care organizations to conduct accurate risk stratification. Moreover, incorporating GIS into healthcare service analyses improves decision-making capabilities for evaluating, planning, and implementing strategic initiatives. By taking advantage of the analytic capabilities of GIS and spatial access risk stratification, healthcare service providers are better equipped to understand their patient population more comprehensively to thrive in the new value-based world.