Analytics is the discovery and communication of meaningful patterns in data and is used in various disciplines to support decision making. Data can come in many forms such as numerical, textual or rules/guidelines, and the analysis can be descriptive or predictive. Ultimately, the goal of analytics is to guide the decision-making process.
Readmission, defined here in the health care context, refers to a patient returning to a hospital post-discharge. The problem of readmission has taken on extra importance given the financial penalties hospitals now receive for higher than expected rates of patient readmission for certain ailments. These penalties come in the form of not receiving full reimbursement from the Center for Medicare & Medicaid Services (CMS) for care a hospital provides to patients who are readmitted. The implicit assumption for levying such penalties is that hospitals are either not properly following up on patients post-discharge or are releasing patients earlier than they should from the hospital. The goal of levying such penalties is to encourage hospitals to look at care over a longer time horizon.
Much of readmission research has looked at innovations that will enhance post-discharge activities such as patient follow-up on health maintenance schedules, medication reconciliation to avoid adverse drug related complications, education of patients in self-management of health, etc. Several hospitals have started to partner with post-discharge caregivers and other intermediaries (e.g., pharmacies and medical homes) in support of these activities.
Analytic approaches have been used to find patterns among readmitted patients to determine appropriate interventions. Admitted patients have also been analyzed to identify high risk patients who are most likely to get readmitted early to allow a more focused approach in discharge planning. However, many of these approaches look at readmission as a problem that needs to be "tactically" addressed to reduce cost to a hospital. While such an approach may enhance patient care in the short run, not fully understanding the reasons for readmission may only lead to care that is "hospital centric" and not "patient centric."
We use a "readmission lens" to look back into the patient care delivery processes both inside and outside the hospital and the interplay of clinical diagnosis and social factors (the environment a patient comes from pre-admission and goes into post-discharge) in order to ensure that continuity of quality care is the key driver of patient centric care.
Research into this complex interaction cannot be done by any single individual or organization. We are seeking collaborators from many research institutions and other institutions interested in the patient care delivery to:
Understand the challenges in delivering care that is sustainable and
Seek opportunities to address care delivery using inter-disciplinary thought and collaborative action.
This website shows our current work in this area and the number of collaborators that are involved in this work. We hope to use this site as a knowledge network to exchange ideas, share research (both on-going and published) and show-case projects.
We encourage others to share their work through this site. You are also welcome to share your comments.
Our vision is to use various analytic approaches to identify opportunities for improving the agility and efficiency with which quality patient care can be delivered in today's constantly evolving health care landscape.
Our goal is to take a strategic view of delivering patient care that is long-term focused.
Several environmental factors (social, demographic, economic, behavioral, ethnic, etc.) contribute to patient admission and/or readmission to a hospital. The delivery care processes both inside and outside the hospital influence the continuity of care available to a patient, and clinical decisions physicians make impact the care a patient receives. The interplay of factors influencing both clinical and social diagnosis (the environment a patient comes from pre-admission and goes into post-discharge) has to be understood if continuity of quality care is to be long-term focused. The Readmission Analytics approach uses
Case studies, prior and on-going research and in-depth interviews to understand the critical care-delivery paths and decisions hospital staff and patients/family make that impact patient care over a longer time horizon, and
Knowledge discovery and innovative implementation strategies to support quality care using rigorous research methodologies (data capture, analysis, evaluation, etc.)