From: Real-world data for precision public health of noncommunicable diseases: a scoping review
Authors (Year) | Country | Application | Target noncommunicable diseases/s | Types of RWD | RWD | Traditional data | Refresh frequency | Aggregation of RWD | Analytics | Implementation |
---|---|---|---|---|---|---|---|---|---|---|
Glidewell et al. (2018) [30] | USA | - | Congenital Heart Disease | 1. Clinical, Medication & Family Hx 2. Claims/Billing | 1. EHR, birth and death files; SPARCS health information system 2. Medicaid, claims database | CHD registry | Static (cross-sectional) | Static records linked across data sources using Fine-Grained Records Integration and Linkage Tool and SAS. Microsoft Access database hosted standardised, aggregate data | Nil reported | Deidentified and deduplicated surveillance dataset transferred to CDC for review |
Guilbert et al. (2012) [31] | USA | - | Asthma, T2DM (use cases) | Clinical, Medication & Family Hx | EHR | Census (social, economic and behavioural conditions) | Static (cross-sectional) | Built PHIN AVR Web Portal data system to aggregate EHR and community-level data | Geospatial—geocoding, spatial regression Descriptive—prevalence Inferential—multivariate analyses, data mining | Demographic, clinic, community disease summary reports |
Ji et al. (2017) [32] | USA | Social InfoButtons | MS, Fibromyalgia, MDD, GAD, CFS, ALS, Parkinson's, Epilepsy, SAD, Panic Disorder (top ten conditions) | Social media | Twitter, SMN | CDC, PubMed, WebMD, MedHelp | Static (cross-sectional) | Data sources integrated via semantic web technology—links terms from different sources that describe the same concept | Geospatial—geocoding Descriptive—disease prevalence, social discussion, topic prevalence, associations, recommendations Temporal—treatment comparison over time | Platform 'Social InfoButtons'—government an end-user for disease surveillance and to increase awareness of social health trends |
Li et al. (2020) [35] | China | NCDCMS | T2DM, IHD, cerebrovascular disease, malignant and benign neoplasms of the central nervous system | Clinical, Medications & Family Hx | EHR | Electronic clinical history database | Real-time (1 day) | Stepwise, bidirectional 3-level public health data exchange Uniform data standards required to connect HIS with NCDCMS | Geospatial—mapping | Implemented in 5 cities in Zhejiang Province |
Lix et al. (2018) [33] | Canada | CCDSS | T2DM, HT, Mental illness, COPD, Asthma, IHD, AMI, HF, Osteoporosis, Parkinson's, MS, Stroke, Epilepsy, Dementia, Osteoarthritis | Claims/ billing | Health insurance registration, physician billing claims | Hospital discharge abstracts (via administrative dataset) and prescription drug records | Static (cross-sectional) | Provinces/territories generate aggregate data from PHAC data request. Data are reconciled based on uniform definitions | Descriptive—disease incidence, prevalence, mortality (bar and line charts) Geospatial—mapping across provinces and territories | Implemented by PHAC. CCDSS data produced in publications, disease reports and interactive open data resources |
Shaban-Nejad et al. (2017) [34] | Canada | PopHR | Arthritis, Asthma, Cancer, CKF, COPD, CHF, Mental illness, Obesity, IHD, MS, Parkinson's, T2DM | 1. Clinical, Medication & Family HX 2. Claims/Billing 3. Environmental | 1. Public health insurance provider 2. Public health insurance provider 3. Retail transactions | Census and Surveys | Near real-time (2-weeks to 1-year) | Aggregated and individual-level data Server-client architecture: (1) Data processing (2) Data integration (3) Semantics | Geospatial—mapping Descriptive—bar charts, data tables, time series, scatter plots (w/ stratification) Temporal—time series, prevalence changes Comparative—intervention impact, multiple queries | Test users—public health and health service agencies Software verification, rapid feedback, usability testing Pilot implementation to support public health planning and health system management |