Patient-Centered Big Data Drives Future Outcomes Research

An evolution is under way in the field of outcomes research, according to experts presenting at the American Heart Association Scientific Sessions. A study that is based on claims or registry data has substantial limitations because the analyses are based on information that was not gathered for the purpose of that study, according to Denise Bonds, MD, MPH, medical officer, National Heart, Lung, and Blood Institute, who spoke during the session “Outcomes Research 2.0: New Challenges and New Opportunities.” Future outcomes research will involve more deliberate data collection for a specific purpose across larger populations.

Dr Bonds said that the trend is to use new data, big data, and patient-powered data. “We need to look at collecting data that are specifically for that purpose,” she stated.

As an example, Dr Bonds mentioned the Heart Healthy Study, which is available for anyone who wants to sign up. Participants are asked to complete surveys and submit health records and other personal information every 6 months over 10 years. The data are collected online or through smartphones. She said research is also being conducted based on information entered on patient-centered social media websites such as PatientsLikeMe.

Dr Bonds also mentioned the National Institutes of Health (NIH) Collaboratory, which is working to improve the way clinical trials are conducted through the creation of a new infrastructure for collaborative research. The NIH is creating several “pragmatic” projects to address large public health issues. “[The NIH is] looking at ways to conduct pragmatic healthcare trials in a lower-cost way,” she said. “I think this is what the future of outcomes research will look like.”

She acknowledged that there are many potential issues with relying on big data that increasingly rely on patient-reported outcomes. However, researchers can also incorporate clinical outcomes, such as hospitalizations, from electronic medical records. “You can include as part of your enrollment your ability to track electronic medical records.” The increased use of integrated health systems, many of which have patient portals, should also add to the robustness of the data.

In another presentation, Catarina Kiefe, PhD, MD, principal investigator, Department of Quantitative Health Sciences, University of Massachusetts Medical School, provided preliminary findings from her research in acute coronary syndrome (ACS) patients as an example of how outcomes research is evolving.

She began by saying that the term “personalized care,” really means “to deliver data-driven excellent care and give patients choices.” She emphasized that care should not only be evidence-based, but also should reflect patient preferences. “There are not many data out there that do that,” she said.

Her team assembled a cohort of 2300 patients in 7 hospitals in 3 states and followed them for 2 years. The data were based on 60-minute computer-assisted interviews conducted in the hospital at the time of the index hospitalization for ACS. Follow-up interviews via telephone were conducted at 1, 3, 6, and 12 months. Medical records were reviewed for the index hospitalization and rate of readmissions. Also incorporated were claims data and geographic information systems data for up to 2 years of follow-up.

Researchers on her team sought to better understand transitions in care from the inpatient to the outpatient setting and the factors associated with readmissions.

Rather than “risk scores,” investigators are looking to develop “action scores.” These scores are designed to help patients understand what is modifiable and what makes them feel better regarding their cardiovascular health, she said. Eventually, the action scores can be used to help patients make important decisions on how to best manage their outcomes. “The outcomes variables are going to be patient-reported quality of life in addition to the clinical ones,” she said.

Ms Kiefe presented preliminary results for the cohort in Massachusetts. Data showed that those who were versus those who were not readmitted at 30 days reported higher rates of baseline depression (7.4% vs 2.3%), anxiety (13.2% vs 8.1%), and stress (42.3% vs 36.6%). By comparison, readmissions were only slightly associated with a history of percutaneous coronary intervention or a history of atrial fibrillation. Readmissions were also associated with a lower likelihood of having undergone coronary artery bypass graft at baseline, she said.

She told attendees that the findings suggest that “Psychosocial factors may be stronger predictors of readmissions than clinical factors.”

She also noted that there are concerns with the payment pressures currently in place to reduce readmissions.

“We think a certain amount of readmissions probably are necessary, and we are actually even worried that the tremendous pressures not to readmit may result in some damage to patients,” she told attendees.

Another preliminary study finding was related to adherence, which she said improved initially but then declined. “We are finding, very interestingly, that adherence to medications, in particular to cardiovascular medications, improves at 1 month after hospitalization for ACS, then further down the line goes back to the bedrock 50% everybody has been talking about for 30 years.”

She noted that research can benefit from blending patient-reported data and traditional methods of collecting clinical data. “We are using methods and ideas from both epidemiological cohort studies and outcomes research to ask questions that are really very patient oriented.”