Success Story
Can Less Care Mean Better Care?
National Data Stream
How reflecting low-value of care can have a high impact on hospitalized patients and lead to smarter medicine
The concept of low-value care refers to clinical practices that add little to no benefit for patients; they can also cause harm or unnecessary costs. For example: elderly hospitalized patients often experience stress and anxiety. To help them sleep, they are sometimes prescribed benzodiazepines, which should only be used under particular indications. As a result, the risk of falls is increased. Another example involves taking the temperature or blood pressure at night, and thus disrupting the patient’s sleep, while this might not be absolutely needed and/or better scheduling could help avoid it.
Smarter Medicine
In Switzerland, the “Smarter Medicine” initiative from 2016 began publishing recommendations for reducing low-value care practices. “Our project LUCID, with Marie Méan from the CHUV, aims at evaluating the impact of these recommendations,” says Guillaume Obozinski, deputy director of the Swiss Data Science Center.
The strategy is simple yet ambitious: by creating a national data stream designed for research purposes that aggregates standardized data of consenting patients from five university hospitals across Switzerland, the team can study whether clinical practices have changed over time. “Essentially, you have to translate clinical practices into quantifiable indicators in a precise manner,” Obozinski explains. There are significant challenges posed by different semantics used in the hospitals and in data standardization. “We have to perform consistency checks on the converted data to ensure for example that all measurements are truly comparable.” This part of the work, though less glamorous than developing advanced analytics, is fundamental for building a reliable national registry for researchers.
The current dataset comprises nearly 300,000 hospital stays. This large volume of data is both an asset and a challenge. It offers a rich resource for assessing trends and identifying the impact of new guidelines over time. But the sheer volume requires rigorous quality control to detect errors or inconsistencies in data entry or due to data extractions. Another challenge lies in the close coordination required between the data management and the clinical research team to make datasets securely accessible to researchers—all while ensuring the system remains user-friendly, legally compliant, and ethically sound.
Data transfers are encrypted
Given the sensitive nature of health data, security is a major concern, and very strict measures are put in place on the BioMed IT infrastructure managed by SPHN. For example, all data transfers are encrypted, and strict access protocols ensure that only authorized personnel can access the information. In addition, all data are pseudonymized to ensure that patient confidentiality is preserved at every stage.
“PHRT organized a number of events that allowed various stakeholders to come together, increased awareness about ongoing projects, and fostered exchanges in the research community”, says Obozinski. With the end of PHRT funding, sustainability of NDS remains a major challenge.
The goal of this NDS project (www.LUCID-nds.ch) is not only to evaluate low-value care practices but also to establish a sustainable registry that can serve as the backbone for future research initiatives in the field of quality of care.
Dr. Guillaume Obozinski
