Why analytics is key to success in population health management
Healthcare organizations involved in value-based care are trying to bend the cost curve by aggressively managing high-cost, high-need patients while eliminating waste and inefficiency without sacrificing quality.
To achieve these goals of population health management, these organizations need accurate, timely data and robust analytics that show providers where to place their efforts and how to improve their performance.
At the highest level of population health management, HCOs must use analytics to categorize their populations by health risk or disease burden. This enables them to identify the patients who will generate most of their health costs in the near term.
Organizations must also have data on high-cost areas like emergency department utilization and post-acute-care patterns. Utilization is highly variable in these areas—if the population uses these resources at above-average rates, it is important to understand why.
Overall, the key to controlling costs and improving the quality of care is to analyze data on the entire patient population. By trying to ensure that healthy people get preventive care and that people with moderate chronic diseases keep them in check, HCOs can meaningfully impact overall quality, manage their rosters and materially reduce the total cost of care.
An effective population health solution will automatically identify patient care gaps, using a combination of claims data and clinical data from multiple sources. It also will use automated messaging via phone, email or text to alert patients with care gaps that they need to make appointments to see their providers.
The combination of automated messaging and an effective use of annual wellness visits can motivate many people who would ordinarily not come into the office to see their providers. Aside from helping to fill care gaps, this is important because, under many value-based contracts, patients are not attributed to a provider unless they visit him or her within a particular time period. These patients, who tend to be relatively healthy and low-cost, counterbalance the sicker patients covered under shared-savings and risk contracts.
Alerts based on analyzed data must be presented to providers very thoughtfully. Physicians are busy with patient care and prefer not to deal with data inputs they consider irrelevant. They do appreciate access to information on care gaps and on opportunities for improved coding. But to get providers’ attention, these kinds of prompts must be inserted into the clinical workflow, which requires some kind of EHR integration.
Physicians are also being held accountable for their performance, and they’d like the opportunity to see how they’re doing on quality measures at all times. So a robust population health solution will include a dashboard that enables providers to view their performance. It should also give them the ability to drill down to the individual patient level so they can understand what they need to do to improve.
Finally, neither providers nor HCOs want an array of population health solutions that don’t work together. Analytics software that can only do risk stratification or utilization analysis, or that can’t provide actionable data, won’t cut it. If you add multiple additional programs to the EHR that doctors are already spending too much time on, they won’t use them. Technology needs to enable them with a solution that integrates with their electronic records system and also helps them execute on important components of population health management.