A scoring system based on patient demographics, overall health and severity of acute illness at time of admission to a hospital seems to accurately estimate a patient's risk of dying within a year of hospitalization, a new study suggests.
The survey is based on the hospital patient one-year mortality risk model — HOMR — a model internally validated in a 2014 study by lead researcher Carl van Walraven, MD, of the University of Ottawa in Ontario, Canada. The new research, published in the Canadian Medical Association Journal, provides external validation for the predictive accuracy of the model.
The researchers used routinely collected administrative data such as age, chronic medical conditions and previous visits to the ER within the past year from nonpsychiatric admissions of more than 1 million adult patients to hospitals in Ontario, Canada, Alberta, Canada and Boston in order to calculate their individual HOMR scores.
After crunching the numbers, researchers reported the HOMR score was strongly and significantly associated with risk of death in all populations. They concluded that the HOMR model can be used for risk adjustment in analyses of health administrative data to predict long-term survival for hospital patients.
Although there is potential for the metric to be applied in comparing quality of care between hospitals, or for it to be used as an objective tool for determining course of treatment based on a patient's likelihood of mortality within a certain time frame, the tool would need a bit of tweaking before being used in that context, Dr. van Walraven said.
"My hunch is, this could be developed to use on the front lines, in routine practice," Dr. van Walraven said.