Medicare End-of-Life Policies Should Reflect Variations in Cancer Patient Populations
Looking beyond general statistics can lead to better design of policies related to end-of-life care among oncology patients, researchers say.
Nuances among patient populations are not reflected in Medicare policies regarding cancer patients’ end-of-life care, finds a new study led by Harvard Medical School researchers and published in the July issue of Health Affairs.
Currently, Medicare policies on cancer patients’ end-of-life care are based on general statistics like average survival time and treatment costs. The study found that the dominant end-of-life care settings for patients with lung cancer—home, inpatient facility, hospice, or intensive care—showed variations in survival time, expenses, number of hospitalizations, and length of palliative care.
“Medicare policies for cancer care ought to be designed with diversity in mind. There is no average patient,” study senior investigator Laura Hatfield, an associate professor of health care policy at Harvard Medical School, says in a news release.
Survival Times Differ
To identify care patterns, investigators analyzed Medicare claims from 1995 to 2009 for more than 14,000 patients with extensive stage small-cell lung cancer, and compared the time patients spent in each care setting from diagnosis to death relative to patients’ overall survival time.
For example, while the average survival time for patients with small-cell lung cancer is eight to 12 months, many patients have much shorter life expectancies. Patients who spent most of their time in inpatient and ICU settings had an average survival time of one month, and patients in the hospice group had a survival time of around four months. Patients who spent the most time at home had an average survival time of 10 months.
The researchers’ model classifies patients with the same diagnosis into smaller groups with similar characteristics, which the authors hope can be used to inform tailored healthcare coverage options and provide better individualized care.
The authors say that their findings do not indicate that healthcare settings necessarily played a role in different survival times. Rather, the purpose of classifying patients in subgroups was to give policymakers better information about variation in patients’ outcomes and healthcare needs
“If a patient has only one month to live, then policies should ensure that their care includes more rapid decision making and advanced care planning,” Hatfield said.