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Table 3 Types of data that could be utilised to track AKI (adapted from Deeny et al [38])

From: Establishing a continuum of acute kidney injury – tracing AKI using data source linkage and long-term follow-up: Workgroup Statements from the 15th ADQI Consensus Conference

Data type Definition Characteristics Examples
Administrative data Data collected as part of the routine administration of healthcare, for example reimbursement and contracting. Records of attendances, procedures and diagnoses entered manually into the administration system for a hospital or other healthcare organization and then collated at regional or national level. Little or no patient or clinician review; no data on severity of illness. Hospital episode statistics (England): Clinical coders review patients’ notes, and assign and input codes following discharge. These codes are used within a grouper algorithm to calculate the payment owed to the care provider. Veterans administration databases: Data from health care episodes within the VA system for both in-patient and out-patient treatment.
Clinical data Data collected by healthcare workers to provide diagnosis and treatment as part of clinical care. These data might arise from the patient (for example, reports of symptoms) but are recorded by the clinician. Electronic medical record of patient diagnoses and treatment. Results of laboratory tests. Compared with administrative data, less standardized in terms of the codes used and less likely to be collated at regional and national levels. Electronic medical record: More than 90 % of primary care doctors reported using the Electronic Medical Record (EHR) in Australia, the Netherlands, New Zealand, Norway and the UK in 2012. In the US, the American Recovery and Reinvestment Act and the Health Information Technology for Economic and Clinical Health Act have driven nationwide uptake and usage of electronic health records (EHR).
Patient generated data Data requested by the clinician or healthcare system and reported directly by the patient to monitor patient health, as well as data that the individual decides to record autonomously without the direct involvement of a health care practitioner. Data collected by the patient on clinical metrics (eg, blood pressure), symptoms or patient reported outcomes; also symptoms and treatment recorded by the patient outside the ‘traditional’ healthcare system structures. Examples include telehealth (e.g. for heart failure patients), UK (Renal) PatientView that allows patients to upload blood pressure, weight and glucose measurements (https://www.patientview.org), Patients Like Me an online quantitative personal research platform (http://www.patientslikeme.com), and individual and patient activity on social media.
Machine generated data Data automatically generated by a computer process, sensor etc. to monitor staff or patient behavior passively. Record of individual behavior as generated by interaction with machines. The nature of the data recorded is determined by the technology used and substantial processing is typically required to interpret it Telecare sensors: Telecare aims for remote, passive and automatic monitoring of behavior within the home, for example for frail older people.