The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems.

BACKGROUND: Rare diseases (RD) are a diverse collection of more than 7-10,000 different disorders, most of which affect a small number of people per disease. Because of their rarity and fragmentation of patients across thousands of different disorders, the medical needs of RD patients are not well recognized or quantified in healthcare systems (HCS). METHODOLOGY: We performed a pilot IDeaS study, where we attempted to quantify the number of RD patients and the direct medical costs of 14 representative RD within 4 different HCS databases and performed a preliminary analysis of the diagnostic journey for selected RD patients. RESULTS: The overall findings were notable for: (1) RD patients are difficult to quantify in HCS using ICD coding search criteria, which likely results in under-counting and under-estimation of their true impact to HCS; (2) per patient direct medical costs of RD are high, estimated to be around three-fivefold higher than age-matched controls; and (3) preliminary evidence shows that diagnostic journeys are likely prolonged in many patients, and may result in progressive, irreversible, and costly complications of their disease CONCLUSIONS: The results of this small pilot suggest that RD have high medical burdens to patients and HCS, and collectively represent a major impact to the public health. Machine-learning strategies applied to HCS databases and medical records using sentinel disease and patient characteristics may hold promise for faster and more accurate diagnosis for many RD patients and should be explored to help address the high unmet medical needs of RD patients.

Can you hear us now? The impact of health-care utilization by rare disease patients in the United States.

PURPOSE: The vast majority of rare diseases (RDs) are complex, disabling, and life-threatening conditions with a genetic origin. RD patients face significant health challenges and limited treatments, yet the extent of their impact within health care is not well known. One direct method to gauge the disease burden of RDs is their overall cost and utilization within health-care systems. METHODS: The 2016 Healthcare Cost and Utilization Project (HCUP) databases were used to extract health-care utilization data using International Classification of Diseases, Tenth Revision (ICD-10) codes. RESULTS: Of 35.6 million national hospital weighted discharges in the HCUP Nationwide Inpatient Sample, 32% corresponded to RD-associated ICD-10 codes. Total charges were nearly equal between RDs ($768 billion) compared to common conditions (CCs) ($880 billion) (p < 0.0001). These charges were a result of higher charges per discharge and longer length of stay (LOS) for RD patients compared to those with CCs (p < 0.0001). Health-care cost and utilization was similarly higher for RDs with pediatric inpatient stays, readmissions, and emergency visits. CONCLUSION: Pediatric and adult discharges with RDs show substantially higher health-care utilization compared to discharges with CCs diagnoses, accounting for nearly half of the US national bill.

Machine intelligence in healthcare-perspectives on trustworthiness, explainability, usability, and transparency.

Machine Intelligence (MI) is rapidly becoming an important approach across biomedical discovery, clinical research, medical diagnostics/devices, and precision medicine. Such tools can uncover new possibilities for researchers, physicians, and patients, allowing them to make more informed decisions and achieve better outcomes. When deployed in healthcare settings, these approaches have the potential to enhance efficiency and effectiveness of the health research and care ecosystem, and ultimately improve quality of patient care. In response to the increased use of MI in healthcare, and issues associated when applying such approaches to clinical care settings, the National Institutes of Health (NIH) and National Center for Advancing Translational Sciences (NCATS) co-hosted a Machine Intelligence in Healthcare workshop with the National Cancer Institute (NCI) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB) on 12 July 2019. Speakers and attendees included researchers, clinicians and patients/ patient advocates, with representation from industry, academia, and federal agencies. A number of issues were addressed, including: data quality and quantity; access and use of electronic health records (EHRs); transparency and explainability of the system in contrast to the entire clinical workflow; and the impact of bias on system outputs, among other topics. This whitepaper reports on key issues associated with MI specific to applications in the healthcare field, identifies areas of improvement for MI systems in the context of healthcare, and proposes avenues and solutions for these issues, with the aim of surfacing key areas that, if appropriately addressed, could accelerate progress in the field effectively, transparently, and ethically.

A Global Approach to Rare Diseases Research and Orphan Products Development: The International Rare Diseases Research Consortium (IRDiRC).

Rare diseases present unique challenges to researchers due to the global distribution of patients, complexity and low prevalence of each disease, and limited availability of data. They are also overwhelming and costly for patients, their families, communities, and society. As such, global integration of rare diseases research is necessary to accelerate the understanding, diagnosis, and treatment of rare disorders. The International Rare Diseases Research Consortium (IRDiRC) was born out of that need for a coordinated international community. IRDiRC was launched in 2011 to facilitate cooperation and collaboration on a global scale among the many stakeholders active in rare diseases research to stimulate better coordination, and thereby maximize output of rare diseases research efforts around the world. Members include funders, academic researchers, companies, and patient advocacy organizations all of whom share the common goals and principles of IRDiRC. The overarching objectives of the Consortium are to contribute to the development of 200 new therapies and a means to diagnose most rare diseases, by 2020. As IRDiRC approaches the end of its fifth year, these initial objectives have been largely achieved and new partners from across the globe are joining. This presents the Consortium with the exciting opportunity to set new and even more ambitious goals for the next phase with the ultimate goal of improved health through faster and better diagnostic capabilities and novel therapies for people living with rare diseases and conditions throughout the world.