A retrospective study from the National Institutes of Health (NIH) suggests that healthcare costs for people with rare diseases have been underestimated, possibly being three to five times higher than for people without rare diseases.
This study provides evidence for the potential effect rare diseases can have on public health and health systems, and suggests that the medical costs of patients may be comparable to those of cancer and heart failure.
“There needs to be greater public awareness of the large and growing medical footprint of rare diseases in society,” Anne Pariser, MD, director of the National Center for Advancing Translational Sciences (NCATS) at the NIH Office of Rare Diseases Research and author principal of the study, said in a press release.
âOnly about 10% of rare diseases have therapy approved by the FDA for their treatment. The findings underscore an urgent need for further research, earlier and more precise diagnostics and interventions for these disorders, âadded Pariser.
The study, “The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and health systems,Was published in the Orphanet Journal of Rare Diseases.
The researchers looked at the medical costs of people diagnosed with 14 representative rare diseases, compared to patients of the same age diagnosed with non-rare diseases (a control group). Its main objectives were to estimate the prevalence of these diseases in four different health system databases (HCS), including the Eversana HCS and NCATS database, and to identify the estimate of the average direct cost per disease. .
The 14 rare diseases selected represent a range of disorders that differ in their prevalence, organ systems affected, age of onset, clinical course and availability of approved treatment.
Disease prevalence was calculated using International Classification of Diseases (ICD) codes for rare diseases, and disease percentages by comparing those with rare diseases to the entire HCS database.
The results showed that the percentages of illnesses were quite variable between different HCSs, and for many illnesses, the NCATS analysis appeared to show higher percentages of patients with rare diseases, compared to the Eversana database.
According to the team, these results can be explained in part by the different populations represented by each database.
“Many RD [rare diseases]R & Ds, particularly genetically-derived, are known to cluster within certain populations and variable results may simply show clustering of populations in certain geographic areas or HCS, âthe researchers wrote.
In addition, they noted that some rare disease patients may have limited mobility and / or an inability to work, forcing reliance on public insurance programs for access to health care, which may help explain the higher percentages in the NCATS database.
Turning to estimates of average direct costs per disease, using the NCATS and Eversana databases and then comparing them to age-matched controls without rare disease, the researchers found that average rare disease costs were 1.5 to 23.9 times the costs for patients with non-rare diseases.
Note that the direct medical costs were estimated by averaging the cost per patient per disease, and the total direct costs were estimated by adding the average cost per patient over the period.
National Eversana HCS database estimates from 2006 to 2020 per patient per year ranged from $ 8,812 to $ 140,044 for rare disease patients versus $ 5,862 for the control group. (This database includes both public and private health insurance coverage.)
NCATS estimates, calculated primarily using a Medicaid database for the state of Florida from 2007 to 2012, ranged from $ 4,859 to $ 18,994 for rare disease patients versus $ 2,211 for the control group. (Medicaid is a government sponsored insurance program in the United States)
In both databases, the cost per patient per year was higher for patients with a rare disease than for those with a non-rare disease, being “about three [to] five times higher than controls of the same age, âthe researchers wrote.
When the team crudely extrapolated the average cost estimates for the roughly 25 million people with a rare disease in the United States, the total annual direct medical costs for rare diseases were in the order of 400. billions of dollars a year, “making the financial burden similar to other costly diseases, such as cancer and heart failure, and exceeding that of Alzheimer’s disease,” they wrote.
Nonetheless, when the researchers calculated the total costs per rare disease over the time period analyzed – by multiplying the number of patients with that particular disease (or control disease) by the average disease costs – a higher average cost for patients with non-rare diseases that any individual rare disease per year has been observed.
“The reasons why the total costs per disease are generally lower [versus] the control is probably due to the small number of patients per disease, despite the high average costs PP [per patient] for DR [rare disease]The researchers wrote.
To better understand the diagnostic journey of patients with a rare disease, the team reviewed records documenting key medical events, diagnosis, and treatment of four people with one of two conditions, Batten disease ( MB) and cystic fibrosis (CF). These diseases were selected because they have disease-modifying therapies, allowing an evaluation of the clinical course of patients before and after treatment.
A long journey to a definitive diagnosis after the first clinical presentation was apparent, which could lead to “progressive, irreversible and costly complications of their disease,” the researchers wrote.
Interestingly, the team noted that rare disease patients often share a consistent group of symptoms (such as infections or seizures) and characteristics (such as persistent and progressive early signs) that could be used, thanks to to machine learning techniques, to establish disease patterns that could potentially enable faster diagnosis and earlier treatment.
âUltimately, to improve the lives of people with rare diseasesâ¦ we need to find innovative ways, including new technologies, to help shorten the long diagnostic odysseys that so many patients and families go through and make more treatments available more quickly, âsaid Joni L. Rutter. , PhD, Acting Director of NCATS and study co-author.
Overall, the researchers concluded that rare diseases “have a high medical burden on patients and CHS, and collectively represent a major impact on public health.”
They suggested that âmachine learning strategies applied to HCS databases and medical records using sentinel diseases and patient characteristics may hold promise for faster and more accurate diagnosis for many patients with DR and should be explored to help meet the unmet medical needs of DR patients. “