China 
Africa 
Explore chapters and articles related to this topic
Emergence of Real World Evidence in Precision Medicine
Published in Shaker A. Mousa, Raj Bawa, Gerald F. Audette, The Road from Nanomedicine to Precision Medicine, 2020
Patient registries are another potentially significant source of RWD. A patient registry systemically collects uniform data from a population with a particular disease or condition, or who are receiving a particular drug or other medical treatment, in order to evaluate outcomes. The FDA considers that the fitness of patient registries for use in generating RWE depends on whether there are adequate processes for gathering follow-up information as needed, to minimize missing or incomplete data and ensure data quality.
Emergence of Real World Evidence in Precision Medicine
Published in Shaker A. Mousa, Raj Bawa, Gerald F. Audette, The Road from Nanomedicine to Precision Medicine, 2019
Patient registries are another potentially significant source of RWD. A patient registry systemically collects uniform data from a population with a particular disease or condition, or who are receiving a particular drug or other medical treatment, in order to evaluate outcomes. The FDA considers that the fitness of patient registries for use in generating RWE depends on whether there are adequate processes for gathering follow-up information as needed, to minimize missing or incomplete data and ensure data quality.
Considerations for developing chronic care system for traumatic brain injury based on comparisons of cancer survivorship and diabetes management care
Published in Ergonomics, 2018
Siobhan M. Heiden, Barrett S. Caldwell
In diabetes care, some health networks used information systems to assist with both population and individual patient health by tracking process outcomes, which included patient metrics such as blood pressure and lipid levels. These data were tracked in registries for diabetes patients within a health network. For example, McCulloch and colleagues used and continuously updated on-line diabetic patient registry data, including prescriptions, laboratory data (glucose levels, HbAlc levels), hospital discharge data (ICD-9 codes), demographic information, vital signs and utilisation (McCulloch et al. 1998). Similarly, Siminerio and colleagues (2004) created a patient registry to collect data about individual patients and patient populations so as to determine the performance and results of the programme. The patient registry included demographics, visits and charges, laboratory results, biometric markers (e.g. hemoglobin Alc, lipid levels and blood pressure), medications, co-morbid conditions and procedures (Siminerio, Zgibor, and Solano 2004). Quarterly reports on lab data were pulled from registries as part of the process outcomes tracking, as well as to disseminate the information to PCPs, which they used to address their at-risk patients (McCulloch et al. 1998; Siminerio, Zgibor, and Solano 2004). However, the researchers did not include information systems in their study with rural clinics (Siminerio, Piatt, and Zgibor 2005), perhaps because there were additional barriers for providers to use them.