Engaging Patients to Reduce Readmission Rates
30 day readmission rate is a key hospital quality measure that is now directly tied to reimbursement, and hence reducing readmission is a high priority for hospital executives. Extensive research has indicated that by improving the hospital discharge process, and following up patients after discharge, hospitals could reduce readmission by 40% or more.
Problems with existing solutions
However, the problem with traditional approaches of building nursing call centers is the high cost. It is prohibitively expensive to have nurses call and follow up each discharged patient. Decades of exhaustive research have indicated that there is no reliable way to tell which patients are likely to get readmitted, and hence an expensive blanket follow up of all patients is required.
“Most current readmission risk prediction models perform poorly” – JAMA 2011 review of 7843 papers
“validated risk-standardized statistical model to accurately profile hospitals using readmission rates is unavailable in the published English-language literature” – Arch Intern Med 2008
“neither providers nor a published algorithm were able to accurately predict which patients were at highest risk of readmission” – J Gen Intern Med 2011
The Ringful Health Approach
Discharge, followup, and predict
Our approach to address this problem is based on evidence-based care transition programs, such as the Care Transition Intervention (CTI) and Transition Care Model (TCM). Following those models, we improve the discharge process via the use of our in-patient tablet devices, blanket follow up discharged patients using automated and pervasive technology, and to create risk prediction model based on the automated engagement data. Using the risk prediction, we can then optimize nursing resources to escalate and follow up patients who are most at risk.
Key features
- Pervasive reach via consumer mobile devices
- Works over voice-only phone lines
- Completely automated and customizable workflows
- Never-before-collected patient behavior data
- More accurate readmission risk stratification
- Focus your resource on high-risk patients
- Incorporate any evidence-based medical content
- Integrate with existing case management systems
- Minimal workflow interruption
Improved discharge planning
An iPad (or other tablet device) for bedside in-patient use. The device provides patient education materials, checklists for discharge planning, and medication management tools. It helps prepare the patients for the follow up programs after discharge, and encourages the patient to take part in medication reconciliation.
Automated patient engagement
An automated program to follow up patients with daily questionnaires through mobile phone, email, web, and voice calls. The questionnaires help identify early warning signs of readmission, and are completely customizable based on evidence-based protocols.
Risk stratification and escalation
Based on patient reported outcomes from the questionnaires, we build a new statistical model to stratify risk factors for each patient. High risk patients are identified via the case management console, and escalated for human followup.
St Luke’s
The St Luke’s Episcopal Health System in Houston is adopting our post-discharge patient engagement solution to reduce heart failure readmissions.
Dell Children’s
The Texas Center for Prevention and Treatment of Childhood Obesity at the Dell Children’s Medical Center leverages our solution to follow up patients after their clinic visits to promote healthy life styles and communicate their progress with clinicians.