Top tech needs for value-minded executives
As health information technology (HIT) proliferates at breakneck speed, it still falls short in several areas critical to the realization and advancement of value-based care.
Here are the top opportunities for technology to provide meaningful improvements in patient outcomes and cost of care reduction:
1. More advanced patient-facing HIT.
Sometimes described as information prescribing, more sophisticated HIT tools can identify patient’s information gaps and target information to particular moments in care. These systems can conduct patient outreach to support a pharmaceutical manufacturer’s patient support program or reinforce the provider’s care plan. This self-management content can be customized to a patient’s specific needs and delivered in a way that is understandable, actionable and meaningful. One interesting approach being tested is the University of Southern California’s Virtual Care Clinic (VCC) launched in January of this year. The VCC is a digital healthcare model that incorporates a variety of technologies, including mobile apps, wearable sensors, data collection and analytics to allow patients anywhere to access medical care. The VCC’s aspiration: to deliver “[a] continuous model of healthcare that is focused on the patient and is on-demand. That means continuous diagnostics with wireless sensors and fully leveraging the sensors and coprocessors in the phone to provide context to the healthcare data.”
2. Patient in-home monitoring.
Monitoring patient behavior when it comes to issues such as medication nonadherence, a $100 to $300 billion source of wasted healthcare spending, needs significant improvement.
Most healthcare happens outside the four walls of a clinic or hospital, yet most providers have no mechanism for integrating observations of daily living into the care management process. Most of the useful medication management issues—medication adherence, socioeconomic and lifestyle data—remains just outside the provider’s view. Access to this type of patient information is needed to help providers better engage their patients in their treatment regimens. However this data largely remains locked in silos.
New “patient engagement” apps pop up almost every week. Many are helpful, but a consistent, caring human being is still essential to improving patient compliance to medication regimens and health outcomes. We know this because of the work of our patient care coordinators. These healthcare professionals build trusting relationships with our patients through learning about lifestyle preferences and barriers to adherence, such as side effects and prior authorization challenges, that would go unidentified and unresolved if not for this direct human-to-human intervention. In a study of HIV patients on highly active antiretroviral therapy (HAART), our medication management protocols, including consistent direct outreach by our patient care coordinators, improved the number of patients at least 95% adherent to HAART by 69%. Those patients exhibited lower overall healthcare costs of $3,000 per patient per year.
In a separate study at the University of Alabama Birmingham, researchers examined a cohort of approximately 650 HIV-infected patients who were enrolled with Curant Health for enhanced pharmacy services, including dedicated care teams and patient education. At the end of the study period, there was a statistically significant increase in the proportion of patients with a suppressed HIV viral load, from 73% to 88%.
3. Better data analytics.
EHRs could be used to capture the data necessary for advanced analytics. An effective automated analytics algorithm could be employed to identify high-risk patients and high risk behaviors. To meet the goals of an outcomes-based contract between pharmaceutical manufacturers and payers for example, providers ideally would be notified when the system detects high-risk behavior that leads to medication noncompliance before the noncompliance actually occurs. Of course all analytics are only valuable if the information they provide is acted upon in a clinically meaningful way in a timely manner.
Patient self-perceived data could be meaningful, relatively easy data to add to risk algorithms. A recent study published in the International Journal of General Medicine analyzed whether self-reported quality of life or other health behaviors captured in an EHR-linked biobank can predict future risk of hospitalization. Compared to study participants with excellent self-perceived health, those reporting poor/fair health had higher risk of hospitalization, and self-reported alcohol use was inversely associated with hospitalization. Capturing data of this type could further strengthen the analytics underpinnings of outcomes-based contracts.