Before it can be used for analytics, healthcare’s big data has to come from somewhere. Wearable devices, mHealth apps, and remote sensors are increasingly becoming the source of patient-generated health data (PGHD) that can aid in chronic disease management and population health, even as providers continue to struggle with accepting and synthesizing this information within the EHR.
But healthcare organizations that successfully meet the challenges of patient-generated health data are seeing a return on their investment, claims a new survey from Accenture. Seventy-three percent of organizations that have adopted personalization technologies have seen positive financial resultsfrom the decision so far.
Physicians are also cautiously optimistic about integrating wearables into their treatment plans. Despite the results of a recent MedPanel survey, which indicated that only 15 percent of providers discuss wearables with their patients, eighty-five percent of physicians participating in the Accenture poll say that the use of wearable health devices improves patient engagement by keeping users on track with daily management of their conditions.
Patients, too, are eagerly embracing wearables and mHealth technologies as they drive the rapid growth of the Internet of Things. Seventy-six percent say that the use of these personal devices has the potential to improve their health. Fifty-four percent of patients say that monitoring their vitals and other statistics is one of the primary reasons they use any type of smartphone apps.
“We’re entering an era of personalized healthcare where patients expect to have a meaningful and convenient individual health experience, both virtually and in-person,” says Kaveh Safavi JD, MD, who leads Accenture’s health business. “The advent of real-time patient data, smarter technologies and individualized services will help health providers break from their traditional business models and provide outcome-focused services for individuals.”
Patient-generated health data has the potential to become a major asset for healthcare organizations, especially those that embrace the idea that big data analytics is quickly becoming a core competency they can no longer avoid.
More than 40 percent of health executives responding to the survey said that the volume of data generated and stored by their organization has grown more than fifty percent in just one year. Eighty three percent of executives think that the industry’s massive data growth spurt will require providers to develop the ability to manage intelligent machines over the next three years.
A similar number believe that they will soon have to spend just as much time training machines to perform big data analytics as they spend on training their human staff members to deliver high-quality care.
Organizations are investing in a variety of machine learning techniques to develop and refine their big data analytics capabilities, the survey found. Fifty-nine percent are using rule-based algorithms to build their systems’ intellects, while 45 percent are focused on predictive analytics to turn raw data into actionable insights.
“As the digital revolution gains momentum, doctors and clinicians will use machines to augment human labor, personalize care and manage more complex tasks,” predicts Safavi. “The digital revolution is also creating a data goldmine that can spark medical breakthroughs and improve individualized treatment plans.”
Wearables have already found a niche in the realms of chronic disease management and medical research, but many mHealth applications are still searching for a way to add meaning and effectiveness to patient care.
With a new framework for behavioral health providers, the non-profit Centerstone Research Institutesuggests that mHealth apps running on a patient’s omnipresent smartphone could help patients maintain steady progress with their treatment by bridging the gap between the difficulties of daily life and their scheduled visits with a healthcare professional.
“More than 90 percent of Americans own a cell phone and 64 percent own smartphones,” said Tom Doub, PhD, CEO of Centerstone Research Institute. “Our goal is to capitalize on these widely available technologies to help make healthcare more convenient, accessible and effective for both clinicians and patients.”
mHealth apps have suffered from image problems thanks to thousands of free, low-quality programs with little clinical relevance that have flooded the market since smartphones made their debut. Understanding how to use mHealth to collect meaningful and effective patient-generated health data has been a challenge that CRI is hoping to address with its appImpact guide for behavioral health providers.
“There are heaps of health-related apps available on the market. Some are great, but others aren’t,” Doub said. “appImpact helps providers cut through the clutter to use the best tool in the right program to effectively treat patients. These technologies are changing the behavioral healthcare landscape, and CRI’s framework and best practices help providers stay on the leading edge of mHealth solutions.”
The guide proposes that mHealth apps could have the most impact on two populations of patients: adolescents at risk for mental health issues and Medicaid “superusers” who incur high expenses from preventable emergency department visits and frequent utilization of services.
Patient-generated health data from mHealth apps can alert providers to potential crisis events, encourage patients to adhere to treatment plans, bolster connections to care coordinators or physicians, and collect passively generated data on symptoms or vitals through the app itself or an associated wearable device.
While mHealth apps and wearables have the potential to improve care coordination and chronic disease management, they will also vastly increase the amount of data flowing into a healthcare organization’s EHR or data warehouse. Providers must proactively address this upcoming avalanche of information if they wish to turn patient-generated health data into an asset that can produce ameasurable financial return.
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