Researchers create new tool to measure patient uncertainty for predicting hospital readmissions

Apr 23 2018

Patients come back to Emergency Rooms after initial discharge for many reasons, but Jefferson emergency medicine physician Kristin Rising saw a common theme during multiple prior interview-based studies: patients feel uncertain. Uncertain how to manage their symptoms, uncertain which symptoms might be a sign of disease worsening, and uncertain where to go with questions. To help understand, document, and find effective solutions to address this uncertainty, Dr. Rising worked with a team of Jefferson researchers to develop a way to measure patient uncertainty – the "Uncertainty Scale" (U-Scale).

"We don't do a good job of predicting which patients will come back to the emergency department, which means we don't have a good understanding of why patients are coming back and how we could be assisting them in having a safer transition home from the first emergency department visit," said Kristin Rising, MD, Director of Acute Care Transitions and Associate Professor of Emergency Medicine at Jefferson (Philadelphia University + Thomas Jefferson University). "As a field, we've had difficulty finding an approach that consistently works to identify and address individual patient needs. The Uncertainty Scale we developed gives us a tool to help do that." The results were published in the Journal of Health Psychology.

Unlike most survey-based scales that are developed by psychologists and other experts, the Uncertainty Scale was based on direct patient input and listening sessions.

An expert in concept mapping, Marianna LaNoue, PhD, Associate Professor of Family and Community Medicine and the Jefferson College of Population Health, Dr. Rising, and their colleagues Dr. Angela Gerolamo and Dr. Rhea Powell spent two 6-hour days with two groups of about 20 individuals each who had recently been a patient in the Emergency Department. The patients brainstormed ideas about what types of uncertainty people have when they are experiencing symptoms that may result in an emergency department visit, and then worked with the research team to map their ideas into categories. "Our scale is a direct one to one representation of what they said – we didn't add or take anything away. It's their content entirely," said Dr. LaNoue. "As such, this scale is unique in the field."

Some of the major themes or categories that emerged were:

1. Concern over treatment quality, which may lead a patient to return in hopes of a second opinion;
2. Concern about lack of a diagnosis, thus leaving a patient with no satisfying explanation for their symptoms;
3. Lack of clarity regarding self-management, such that patients are unsure how to deal with symptoms at home
4. Lack of self-efficacy, manifesting as patients not knowing where to go for help for certain symptoms
5. Lack of clarity about the decision to seek care, meaning that patients do not know which symptoms are serious enough to warrant seeing a health professional
6. Psychosocial factors, including worries that getting medical care might interfere with home and work commitments, and;
7. General worries and concerns.

"One of the more interesting findings that emerged in this work is that uncertainty about the quality of treatment was potentially associated with a return emergency department visit," said Dr. LaNoue. She explained that this is a novel finding in a field where most predictors of return visits focus on administrative information about patients, such as their insurance status or chronic health conditions.

Dr. Rising is already bringing the idea of the importance of addressing patient struggles related to uncertainty into emergency medicine resident training. Her current work, funded by the Agency for Healthcare Research and Quality, is focused on developing a curriculum to teach residents to have more effective discharge conversations for patients for whom there is diagnostic uncertainty, meaning that testing has not identified a definitive cause of their symptoms. "As emergency physicians, we focus primarily on acute care, fixing the most immediate life threatening problems. Facilitating a safe and effective transition home for patients who do not appear to have a life-threatening problem is also a really critical part of our job that is often overlooked," said Dr. Rising.

This research has also changed the way Dr. Rising delivers news to her patients. She realized that what she considers good news – that tests are normal and a patient's symptoms do not appear to be life threatening – could actually be experienced as very bad news from the patient perspective. "If a patient comes in with a problem and I tell him that testing is normal and I haven't found a cause of his symptoms, it might give momentary relief, but that patient still is no closer to understanding what is causing his distress. It's not all good news, and we have to acknowledge that we have not improved patients' sense of uncertainty about their disease with this news," said Dr. Rising. She now takes time to acknowledge and validate potential patient struggles related to ongoing uncertainty.

The team of researchers plans to continue to refine and validate the U-Scale itself, and plan to use it to test interventions to alleviate different categories of uncertainty.