- Population health management is a healthcare delivery practice that aims to provide high-quality care to all populations by utilizing value-based payment approaches and patient-centered care. A recent study conducted by Healthagen’s Chief Population Health Officer Charles Kennedy, MD, examines how health IT and data analytics integrate with population health management.
The eHealth Initiative study shows the diversity of health IT utilization in population health management. The most popular kinds of health IT infrastructure for population health included EHRs (69%), analytics software (62%), computerized order entry (59%), and patient portals (59%).
Even the less popular forms of health IT had reported high rates of use. For example, care management software had the lowest rate of use, and yet nearly 43 percent of respondents still reported using it. Respondents also reported using disease registries, data warehouses, and clinical decision supports.
That said, health IT is only the third most prominent source of support for population health management. Pre-existing investments were the most popular supports of population health at 54 percent, as well as organization mission statements.
The study also took a closer look at various functions of population health management. Respondents reported using population health to address patients with multiple chronic diseases (65 percent), high readmissions risk (60 percent), who generate high care costs (59 percent), are high utilizers of care (54 percent), and have specific disease and service needs (40 percent).
Additionally, respondents use different measures to analyze their population health management progress. Among the most popular success measures are intermediate outcomes (55 percent), cost savings (54 percent), patient satisfaction (49 percent), healthcare processes (46 percent), and long-term outcomes (39 percent).
Additionally, the survey examined the use of data analytics in population health management. Specifically, it looked at sources of data analytics and how those data are used. The key data sources are clinical data (77%), claims data (62%), administrative and financial data (52%), healthcare research analytics (43%), and registry data (42%). Thirty-two percent of respondents use data from a health information exchange, while 20 percent report analyzing unstructured text.
Resoundingly the most popular use for these analytics was quality reporting and measuring, with nearly 63 percent of respondents using analytics for that purpose most frequently. Other popular uses of analytics include comparing performance across clinicians, identifying gaps in care or preventative services, and identifying outliers in cost and utilization, all with 43 percent of respondents incorporating those practices. Additionally, analytics are most frequently used retrospectively or in real time.
Far fewer respondents report using patient-generated data, with only 23 percent of respondents reporting doing so. Forty-eight percent of respondents report concerns for the quality of patient-generated data while 42 percent are concerned about the added workload to the clinician.
The study also examined key practices for population health management, including patient engagement and care management. Nearly 60 percent of respondents use patient portals for patient engagement, followed by notifications for preventative measures (48%), post-discharge care coaching (44%), e-forms for patient generated data (42%), notifications for gaps in care (38%), patient navigators (34%), and secure messaging (34%).
Care management activities are also fairly popular for at-risk patients or patients with specific, chronic needs. The most popular care management activities include development of care plans (64 percent), multidisciplinary care teams (56%), health/wellness coaching (48%), periodic telephone follow-ups (48%), automatic notifications for providers (39%), and periodic in-person follow-ups (34%). A very small number of respondents reported using secure messaging for care management as well (8.5%).
However, despite the fact that the respondents reported high engagement with population health management practices, they also reported several hindrances. For example, over half of respondents found challenges with interoperability and data integration. Additionally change management, competing IT priorities, and impact on workflow served as challenges with approximately 40 percent of respondents citing each.
Because respondents showed high engagement with population health management and data analytics, researchers state that the importance of those concepts is evident. However, integration of data and its usefulness serve as serious inhibitors. Solutions to these problems include better systems interoperability as well as increased patient engagement with their healthcare and data generation.
This survey garnered nearly 65 responses between September and the start of October 2015. Respondents were a part of health systems/integrated delivery networks (IDNs), independent physician groups, hospitals or academic medical centers, or other types of healthcare organizations. Through their work, respondents had experience with patient-centered medical homes, Medicare/Medicaid accountable care organizations (ACOs), pay for performance programs, commercial ACOs, and bundled payment initiatives.