Healthcare costs for people with rare diseases have been underestimated, study finds
New retrospective study of medical and insurance records indicates The costs of healthcare for people with a rare disease have been underestimated and are three to five times higher than the costs for people without a rare disease. The study, led by the National Institutes of Health’s National Center for Advancing Translational Sciences (NCATS), provides new evidence of the potential impact of rare diseases on public health, suggesting that nationwide medical costs for people with rare diseases are comparable to those with cancer and heart failure. The results of the study were published on October 21 in the Orphanet Journal of Rare Diseases.
The public needs to be made more aware of the large and growing medical footprint of rare diseases in society. Only about 10% of rare diseases have therapy approved by the FDA for their treatment. The findings underscore an urgent need for more research, and earlier and more precise diagnoses and interventions for these disorders. ”
Most of the approximately 7,000 to 10,000 known rare diseases disproportionately affect children, adolescents and young adults. Individually, most rare diseases can affect only a few hundred to a few thousand people worldwide. However, rare diseases are collectively common, affecting an estimated 25 to 30 million people in the United States. Many of these conditions have a genetic cause, are serious or life threatening, and are difficult to diagnose and treat.
The pilot study was a collaborative effort between NCATS; Eversana Life Sciences, Chicago; Oregon University of Health and Sciences, Portland; Sanford Health, Sioux Falls, South Dakota; and a health insurer in Australia. Pariser and his colleagues analyzed patient diagnostic information in medical records and billing codes. They used the International Classification of Diseases (ICD) codes, which denote disease diagnosis and other methods, to determine people with rare diseases and their direct medical costs for 14 rare diseases in four health systems per compared to patients with non-rare diseases of a similar age.
The pilot study aimed to test the feasibility of this approach in analyzing data on the prevalence and costs of rare diseases. The 14 rare diseases represented a diverse set of disorders that differed in prevalence, organ systems affected, age of onset, clinical course, and availability of approved treatment or specific ICD code. Examples of selected rare diseases include sickle cell anemia, muscular dystrophy and eosinophilic esophagitis.
The analysis showed large variations in the prevalence of rare diseases across different health systems, which the researchers attributed in part to geographic differences, as well as the use of public insurance versus insurance. private, which may include a different representation of patient groups. In addition, certain genetic diseases may occur more frequently in certain populations, depending on the demographic makeup of a region.
The team determined approximate medical costs by examining health system data from NCATS and Eversana. In all cases, the cost per patient per year (PPPY) for patients with a rare disease exceeded the costs for patients with non-rare diseases of the same age. According to the Eversana Health System Database, which included estimates from commercial and insurance payers spanning nearly 15 years, PPPY costs ranged from $ 8,812 to $ 140,044 for rare disease patients, up from 5 $ 862 for those without a rare disease. NCATS data, which relied primarily on estimates from Florida Medicaid information over five years, showed PPPY costs ranging from $ 4,859 to $ 18,994 for rare disease patients versus $ 2,211 for those without. rare sickness.
The team reported that extrapolating the estimated average costs for the roughly 25 to 30 million people with rare diseases in the United States would result in total annual direct medical costs of around $ 400 billion, which is similar to the annual direct medical costs for cancer, heart failure and Alzheimer’s disease.
The researchers also used patient medical records to trace the diagnostic journey of four people with a rare disease, including two people with some form of Batten’s disease, an inherited neurological disorder, and two others with cystic fibrosis. an inherited disease that seriously affects the lungs. The âmapsâ of the journey provided detailed descriptions of direct medical costs, such as hospitalizations and procedures associated with these illnesses, and provided information on the clinical management of patients before and after diagnosis of the illness.
The researchers noted that analysis of medical records revealed that patients with rare diseases often share a consistent group of symptoms (eg, seizures, infections, and developmental delay) and characteristics, which could help clinicians. make diagnoses faster and start treatment earlier. Since many people are diagnosed with a rare disease at a young age and most rare diseases are serious conditions, patients with rare diseases are likely to spend more time in the hospital and incur greater medical expenses in their lifetime than those who do not.
Such similarities among rare disease patients could point to the potential use of machine learning techniques on healthcare system databases to improve diagnoses, said Joni L. Rutter, Ph.D., director by interim NCATS, co-author of the study.
The research team is also interested in determining whether the methodologies used to explore the prevalence and associated costs for a small set of rare diseases could be adapted to thousands of other known rare diseases.
âUltimately, to improve the lives of people with rare diseases,â said Rutter, âwe need to find innovative ways, including new technologies, to help shorten the long diagnostic odysseys experienced by many patients and families and make more treatments available more quickly. “
Tisdale, A., et al. (2021) The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and health systems. Orphanet Journal of Rare Diseases. doi.org/10.1186/s13023-021-02061-3.