By Briana Britton and Cole Manship
In 2010, St. Vincent’s Hospital Manhattan, a Greenwich Village beacon that served poets, writers, artists, and the poor and working-class for more than 150 years, shut its doors.
The hospital had treated victims of numerous calamities including the cholera epidemic of 1849, the sinking of the Titanic in 1912, the 9/11 attack, and the Hudson River landing of US Airways Flight 1549 in 2009.
The close of the iconic hospital was the result of increasingly troubled management whose problems were made worse by the economics of the healthcare industry, changes in neighborhood demographics, and the low profit potential in religious work.
Over the past decade, hospital bankruptcy and closures have become an increasingly grim reality in the United States today. In 2013 alone, 11 hospitals filed for bankruptcy and 18 closed their doors altogether. David Houle and Jonathan Fleece, authors of The New Health Age: The Future of Health Care in America, believe as many as one-third of hospitals may reorganize or close by 2020.
When hospitals are in distress, there are often staffing shortages that may reduce quality of care and increase the incidence of hospital-acquired infections. When hospitals close, area residents may lose access to much-needed medical care, resulting in major implications for communities’ patient health. The reasons for hospitals closing are numerous and complex. Contributing factors include administrative mismanagement, declining reimbursements, evolving patient demographics, and fluctuations in local and national economies. Among the major challenges: by the time hospitals realize they are in financial distress and on a course towards bankruptcy and closure, too often there is little that can be done to correct the path.
Concerned by this issue, Alvarez & Marsal, a leading hospital consulting firm, approached HITLAB for help in finding a solution. Together, HITLAB and Alvarez & Marsal developed a predictive algorithm called the Hospital Failure Predictor, which is capable of predicting the likelihood of a hospital closing or filing for bankruptcy over one-year and five-year periods.
The algorithm utilizes local market demographic and public health data from the Census and CDC, combined with quality and financial performance data from hospitals around the country, to determine whether or when a hospital may need to make changes to stay in operation. In a nutshell, the algorithm helps hospital administrators track the pulse of their institution’s financial and operational health.
The Hospital Failure Predictor algorithm gives hospital administrators the opportunity to make critical financial decisions to save a hospital before it’s too late. We are grateful to Alvarez & Marsal for addressing this issue, which we believe will help not only institutional financial health, but also individual patient health.