Results Summary

What was the project about?

Patients with multiple health problems, such as diabetes and heart disease, may benefit from personalized treatment approaches. For example, patients who have both breathing problems and diabetes may need different medicines than patients who have diabetes alone. Researchers can use statistical methods to group patients with specific health problems and figure out how well treatments work for those patients. But current methods don’t always find all the health problems that can affect how treatments work.

In this project, the research team developed a new method to group patients with common health problems. The method, called a visual analytic method, used a computer program and patient data to draw pictures or maps of the patient groups. The method helped the research team figure out the chance of returning to the hospital for patients in each group.

What did the research team do?

The research team used Medicare claims data for patients with COPD, a lung problem that makes it hard to breathe. The team looked at data for 29,016 patients who returned to the hospital within 30 days of discharge. Then they looked at data for 29,016 patients who didn’t return to the hospital within 90 days of discharge. The team matched patients who did and didn’t return to the hospital based on their age, gender, race, and income.

The research team then used the new method to identify and group patients who returned to the hospital, based on their health problems. The method created a picture showing how the groups were similar and different. Then the team used statistical methods to figure out the chance of returning to the hospital for patients in each group. The method also showed a patient’s likelihood of being in a specific group.

Doctors helped the research team develop the methods and review the results.

What were the results?

The method displayed a picture of four groups of patients with COPD based on their most common health problems:

  • Patients with high blood pressure
  • Patients with diabetes with complications, kidney failure, and heart failure
  • Patients with mental health problems and social concerns
  • Patients with organ damage and digestive conditions

The method also identified the chance of returning to the hospital for each group. For example, the patients with diabetes group had an 18 percent chance of returning to the hospital.

What were the limits of the project?

The new method took almost a week for a computer to run. The research team used claims data. Results may have differed if the team used other types of data or selected patients in different ways.

Future studies could test these methods using other types of data such as health records.

How can people use the results?

Researchers could use these methods to identify groups of patients with certain health conditions, and figure out how treatments work for patients in those groups.

Final Research Report

View this project's final research report.

Peer-Review Summary

Peer review of PCORI-funded research helps make sure the report presents complete, balanced, and useful information about the research. It also assesses how the project addressed PCORI’s Methodology Standards. During peer review, experts read a draft report of the research and provide comments about the report. These experts may include a scientist focused on the research topic, a specialist in research methods, a patient or caregiver, and a healthcare professional. These reviewers cannot have conflicts of interest with the study.

The peer reviewers point out where the draft report may need revision. For example, they may suggest ways to improve descriptions of the conduct of the study or to clarify the connection between results and conclusions. Sometimes, awardees revise their draft reports twice or more to address all of the reviewers’ comments. 

Peer reviewers commented and the researchers made changes or provided responses. Those comments and responses included the following:

  • The reviewers found the final research report to be exceptionally clear and well written, with few requested revisions.
  • The reviewers questioned how the researchers chose their control group of patients from the available Medicare data. The reviewers noted that the patients were not eligible to be in the control group if they were readmitted into a hospital within 90 days after hospital discharge, creating a selection bias leading to significant differences between the case and control patients. The researchers explained that they used the same definitions for their comparison groups as the Center for Medicare and Medicaid Services, since the study used the same models for their analyses. The researchers did note in the discussion section that this difference between the comparison groups exaggerated the differences between the case and control groups.

Conflict of Interest Disclosures

Project Information

Suresh K. Bhavnani, PhD
The University of Texas Medical Branch at Galveston
Leveraging Visual Analytics for the Identification of Patient Subgroups: Application to Improving the Prediction of Hospital Readmission in the Elderly

Key Dates

July 2016
May 2021

Study Registration Information


Has Results
Award Type
Health Conditions Health Conditions These are the broad terms we use to categorize our funded research studies; specific diseases or conditions are included within the appropriate larger category. Note: not all of our funded projects focus on a single disease or condition; some touch on multiple diseases or conditions, research methods, or broader health system interventions. Such projects won’t be listed by a primary disease/condition and so won’t appear if you use this filter tool to find them. View Glossary
State State The state where the project originates, or where the primary institution or organization is located. View Glossary
Last updated: March 14, 2024