Challenges and Opportunities for Data Reuse Ronald Cornet, PhD Dept. of Medical Informatics Academic Medical Center – University of Amsterdam

Overview  Why Data Reuse  Categories of Data Reuse  Challenges  Opportunities

Data Reuse  Many data are collected in the care process  Many data are needed e.g., for research purposes  Two options:  Dedicated collection of purpose-specific data  Re-using data from the care process

Dedicated Data Collection  Allows for optimally defined data set  But…  May lead to redundant data collection  Can not always be performed (e.g., retrospectively)

Re-using Data from Care Process  Benefits from readily available data  But…  Data may be incomplete  Data may lack detail  Data may be biased  Data may be incomparable

Seeking a balance  Data from the clinical care process often not fit for reuse  Dedicated data collection costly or impossible  Recording “everything” about “everyone” is impossible  How to collect data in the primary care process that can be reused with minimal drawbacks (e.g., bias, detail)?

Example – cost analysis  Cost analysis based on care records  Only recorded care is taken into account for cost analysis  E.g., during a busy night, a severely traumatized patient enters emergency department, receives blood, resuscitation, and dies, is transported to morgue; no record created

Secondary Uses and Re-uses of Data  Protect and enhance public health  Develop security and confidentiality algorithms and test de-identification routines  Conduct research  Create and maintain terminology and representation formalisms

Secondary Uses and Re-uses (II)  Develop and apply decision support for health care providers  Support quality of patient care  Improve patient safety  Manage personal health

Secondary Uses and Re-uses (III)  Educate and credential healthcare providers and assess training activities  Analyze and Manage Finances  Detect fraud and illicit activity  Identify markets and promote sales

Examples  Public health E.g., setting up disease-specific registries  Cardiosurgery  Renal Failure  Intensive Care  Research E.g., development of prognostic models

Examples  Decision support E.g., develop algorithms, rules, and alerts  Quality of patient care  Manage quality and outcomes »More on this tomorrow (Dr. De Keizer)  Manage staffing and resources  Develop and assess quality indicators

Factors influencing Authorization for secondary Use (I)  Identification Status: Patient identifiable, de- identified, anonymized  Consent provided at the time of data collection  Demographic representation, e.g., age, race, gender  Focus on a vulnerable population (e.g., prisoners)  Original collector and aggregator of the data (government, private)

Factors influencing Authorization for secondary Use (II)  Proposed secondary user of the data, e.g., government, academic institution  Funding source for secondary use  Financial compensation to data collector for providing data to a second party  Beneficiary of secondary use, e.g., society, researcher, academic institution  Disclosure of secondary use, e.g., public disclosure of results and/or methods

 ERA-EDTA Registry  Data about patients on End-Stage Renal Failure  Patient data recorded in renal centers  Data from centers to national registries  Data from national registries to ERA-EDTA  ERA-EDTA shares outcomes with USRDS, ANZDATA Data Reuse Case StudyData Re-Re-Reuse Case Study

Challenges

Opportunities  Adjust data to the intended reuse or  Adjust the intended reuse to the data

Conclusion

Round-up  There are many kinds of data reuse

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