Overview:
Princeton Health Affiliated Physicians (PHAP) is a multi-specialty, hospital-owned practice with a main faculty practice and several satellite locations. In order to enable providers working across the organization to plan for continuous quality improvement and complex care management, the practice embarked on a project to integrate a population health software tool into their EHR and other data systems. The resulting population health reports can also help providers to assess their patients’ data related to preventive health, chronic disease, and behavioral health management; and to intervene with individual, high-risk patients.
Management of high-risk patients presents a challenge to any primary care organization. To intervene with at-risk patients, organizations require timely, actionable data. Such data also helps organizations to monitor medical costs, such as pharmaceuticals and diagnostic tests.
PHAP has grappled with these issues since joining the Comprehensive Primary Care Initiative in 2012, The Initiative uses metrics such as cancer screening, blood pressure monitoring, and diabetes care. The organization felt stymied in taking action to improve chronic care management. They were unable to act proactively without ready access to information on patients’ health, medical services, and claims data. The practice also lacked the analytic capabilities to generate the visuals and data that reveal the patterns and individuals at risk.
Previously, PHAP compiled population health data in a laborious manual process using a pivot table in the EHR to identify people with different conditions and separate them into risk categories. After losing this feature with an EHR upgrade in 2013, the organization worked with Lightbeam Health Solutions to use their population health software.
The organization wanted to create a seamless, readily-accessible, and efficient means for providers to monitor their performance and their patients’ needs in an easy-to-use dashboard with the goal of proactively to manage patients at the point of care rather than waiting for claims and other data.
Outcome:
In 2014, the practice sought a population health software vendor that already had a relationship with their EHR vendor, e-MDs. The software allows the practice to use a sophisticated Johns Hopkins LCG algorithm that analyzes patient care patterns, medications, other social factors, insurance, and other data to divide patients into risk categories. This analysis also allows the providers to drill down and identify gaps of care for specific patients, and to assign those individuals to care managers. As a result, the providers can better transition high-risk patients in danger of complications or high service utilization to complex care management.
The practice began by confirming the feasibility and validity of the process by establishing the data exchange and validating the data extraction. They then tested integration of EHR data with data from other platforms and from CMS.
Next, the practice validated that the data were representative of data from the original sources, and that the reports generated by the system accurately reflected the current state both in terms of importing the correct data, and in terms of interpreting that data.
After the integration was complete, the practice began to develop an understanding of the application and the power of its dashboards and reports. This process began at the executive and analytics levels of the organization, and then was opened to providers who received basic training on using the tools. The vendor provides remote training sessions to demonstrate the tool to providers and support them as they learn the system.
The vendor also provides training for care managers to help them keep track of high-risk individuals identified by the system due to the status of their care, their communication with the care manager, or data about gaps in their treatment.. The care managers also learn how to use the software to create care plans for individual patients.
The practice finds it easy and efficient to run population health reports, and shares information with the organization, clinics, and providers on a monthly and quarterly basis.
This process is still ongoing. The practice began implementation with its outpatient practice in January 2015, and is currently completing a training effort with their internists. The practice plans to launch organization-wide in the near future.
Lessons Learned:
A practice seeking to integrate a tool like this does not have to reinvent the wheel. To find a solution, the Director of Practice Innovation, Dr. Tobe Fisch, first investigated what peers were doing. As part of that process, she joined a user support group that formed a partnership with their EHR vendor, e-MDs.
The practice has early indications that the new software should have little impact on providers’ workflow and, instead, will simplify their ability to deliver good care to those most in need of it. Beyond that, providers see two direct benefits. First, this process will facilitate their ability to demonstrate the quality care that they provide. Second, this process will enable physicians and the practice to maximize the work of care managers into their efforts to reach and serve high-risk patients.
The organization expects that some providers may be resistant to learning a new technology and that some will have a greater learning curve using the software. One sticking point is that the new tool requires a separate log in, so providers may be dismayed by the lack of integration with their other systems.
Next-Steps/Future Vision:
The organization is in the middle of deploying this process to their providers, so the ultimate impact on patients is unknown. The practice expects that these data will help them improve care by identifying patients who currently fall through the cracks. They also expect it to shed light on what services patients are using and why, and what they can do better to meet patient needs effectively and appropriately.
The data generated by the population health software is already helping the practice to monitor their effectiveness in providing quality care and taking corrective action. The practice has already used these data on an organizational level to see where demand for certain health care services was higher than the staffing provided, and to take action to increase available service. In the future, PHAP will assess whether they are performing better on gaps in care through better quality metrics showing patients are getting the care they need (e.g., better controlled blood pressure, improved cholesterol levels, cancer screening, decrease in unneeded expenditures).
Although PHAP launched this project to help its providers, patients may be able to use the tool in the future for self-care via a module for patient engagement where they can upload their health data (e.g., weight, blood pressure, blood sugars) into the system.