ePrognosis Brings Risk Assessment into Medical Care Planning

By: Erika Kimball, RN

Our health care system is a veritable cornucopia of treatments offering a variety of fixes for what ails you. All medical interventions, however, carry some risk and side effects that can sometimes outweigh proposed benefits. While physicians know which patients are more at risk for adverse outcomes, deciding the appropriate level of medical treatment is a personal and nuanced experience between practitioner and patient. Gerontology experts at UCSF recently launched ePrognosis, a new on-line tool that helps predict health outcomes among the elderly, adding a useful new data set to the medical care planning process. This tool can help practitioners ‘right size’ care, saving health care resources while maximizing patient quality of life.

ePrognosis is an interactive model comparing multiple medical indices that estimate life expectancy in the elderly. Each index is rated on qualities such as accuracy, usability, and efficacy, and presented in a readily navigable on-line tool that is tailored to patient profile. Based on a comprehensive review of literature published in the Journal of the American Medical Association, ePrognosis begins the national conversation on appropriate level of intervention in the elderly. The model is intended for use by medical professionals only and provides merely one data point in a multifactorial care planning process. Given these limitations, the website offers three examples of how incorporating life-expectancy into medical decision making offers better care:  determining the need for particular cancer screenings in elderly patients, evaluating eligibility for hospice care near end of life, and deciding appropriate work up for incidental diagnostic findings in a chronically ill older adult.

The time is right for ePrognosis as American health consumers are more educated than ever, thanks to the wealth of on-line information regarding diagnoses, symptoms, and treatment options. ePrognosis fills a data gap by providing science-based information that assists patients and physicians in deciding whether available treatment is appropriate for their specific needs.

Economically, prudent use of medical resources is key to the viability of our ailing health care system, as one third of health care resources are utilized during the last year of life. Looking at environmental impact, the amount of medical resources used translates directly to the massive ecological footprint created by the health care industry. Furthermore, data shows that scaling back treatment near end of life doesn’t increase overall mortality rates.

Any talk of scaling back health care in the elderly evokes images of frail grandparents lined up around the block outside of the local doctor’s office, waiting for a flu shot and their monthly medications. Understandably, public outcry readily ensues, as witnessed in the feedback section of ePrognosis. However, medical resource intensity at end of life reflects the disproportionate number of our last precious days spent in or near the hospital, getting tests and treatments and needles and hospital food and beige sterile rooms and hospital acquired infections… I could go on. So while scaling back treatment is about wiser use of finite resources, it is primarily about wisely choosing the health resources that will maximize quality of life.

The ultimate goal of medical care is to improve well-being. ePrognosis contributes to this goal by providing ready access to information that better defines the benefits of treatment options, shifting the focus from which medical interventions we can perform to which interventions we should. This is a vital step in bringing medical decision making into the information age, empowering patients to take a more active role in health care planning.

**Erika Kimball is a Registered Nurse and a Sustainable Business Professional dedicated to minimizing the environmental impacts of the health care industry.  She dreams of zero-waste hospitals and quality health care for all. 



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