| Group 1 - Architect |
| (i) Focus on the current demographics using standardized metadata of CIHI, hospitalization, and readmission |
| for BC and VIHA. |
| (ii) CIHI requests hospitals to submit data based on set data collection targets and standards. Much of the used |
| collected data is from DAD and some ADT; therefore, combining the 2 databases to form NoSQL database |
| is representative. |
| (iii) ADT is location, medical service and inpatient to discharge, so we can add those columns while diagnosis |
| and procedure are separate and can add those to the patient encounter even though they are separate. |
| (iv) Requested by and regulated by CIHI all metadata associations can be based on the encounter and MRN at |
| hospital level with PHN as a primary key. |
| (v) It is the most important system that holds the patient’s non-clinical information. These are based at the |
| patient encounter level and are represented by columns and rows in existing database for our NoSQL. |
| (vi) ADT is collected when patient is still in the hospital, but DAD data is recorded after patient leaves the |
| healthcare facility. Combining ADT and DAD is already done at the hospital level and can have representation |
| of hospital system via non-relational database. |
| (vii) DAD contain the clinical information that is collected ADT is the location, date and time of the visit, and |
| patient personal information. Data elements for data are based on profiles at the metadata level. And |
| there is a data dictionary that we can simulate. |
| (viii) Patients are identified using their PHN, MRN and encounter number. Encounter level queries are important |
| as well as hospital level patients’ metadata that is possible to represent encounters as rows in database. |
| Group 2 - Reporting |
| (i) Produce standard reports hourly, daily, weekly, monthly, and yearly with no errors for reporting, the |
| metadata are supposed to be standardized at the enterprise architecture. Dependencies in the data can be |
| simulated with the correct metadata. |
| (ii) ADT is implemented from vendor and source of truth and automated, DAD is abstraction and utilizes |
| source; therefore, the 2 databases are already linked. Combining ADT and DAD is possible and representative |
| of hospital system while supporting clinical reporting and benchmarking our simulations. |
| (iii) Significant relevance to reporting to CIHI can show similar queries in simulation. |
| (iv) Standardized reporting is available to show similar queries in simulation. |
| (v) Primary keys are important for data integrity and no errors while linking encounter to patient. Database |
| keys need to be represented. |
| (vi) Encounter level data important to standard reporting and data integrity. Simulation patient encounters |
| at hospital level to represent clinical reporting. |
| (vii) Key stores important to index data because foundation of system is based on patient encounter. Need to |
| utilize technologies to create key stores and unique indexes of the encounters to query the data. |
| (viii) Important queries need to incorporate as proof of concept with certain fields from hospital systems: |
| (a) Frequency of Diagnosis (Dx) Code with LOS, Frequency of Diagnosis (Dx) Code with LOS, Diagnosis |
| Code with Discharge date and Discharge time, Diagnosis Code with Unit Transfer Occurrence, Diagnosis |
| Code with Location building, Location Unit, Location Room, Location Bed, Discharge Disposition, |
| Diagnosis Code with Encounter Type and LOS, Diagnosis Code with Medical Services and LOS, Highest LOS |
| for MRNs with Admit date, Frequency (or number) of Admit category with Discharge_Date, |
| Provider Service with Diagnosis codes. |
| (ix) Combining the columns, we need to be able to perform these basic calculations: |
| (a) [Discharge time/date] – [Admission time/date] = length of stay (LOS) [Current date] – [Birth date] = Age |
| (b) [Left Emergency Department (ED) date/time] – [Admission to ED date/time] = Wait time in ED |
| (c) Intervention start date/time = needs to be between [Admission time/date] and [Discharge time/date] |
| (d) (Intervention) Episode Duration = Should be less than LOS |
| (e) Transfer In/Out Date = Should be between [Admission time/date] and [Discharge time/date] |
| (f) Days in Unit = should be less than or equal to LOS. |
| Group 3 - Data Warehouse |
| (i) Like key stores, we need dependencies in our database to be representative of existing system relevant to the |
| hospital operations. |
| (ii) Certain data elements with standardized metadata are necessary for the data to be accurate. The process |
| needs to generate same metadata with accurate dependencies. |
| (iii) Integration is not necessary for system to work but only to query the data ad hoc or correctly, and currently |
| no real time or streaming data. Integration depends on patient healthcare numbers from system at |
| each encounter and linkage between ADT and DAD via indexed rows. |
| (iv) Medical Services is not currently utilized in clinical reporting because it is not DAD abstracted, but could be |
| utilized in data warehouse. The reason is due to CIHI’s data standards can integrate medical services and other |
| metadata from ADT with direct linkage to metadata from DAD. |
| (v) Transfers are important to ADT and flow of patients in the system as their encounters progress and change. |
| We can use transfers and locations in the database as simulated metadata of known profiles from hospital. |
| (vi) Combining columns against encounter rows is already implemented at the hospital level; therefore, ADT and |
| DAD combination is relevant and simulation valuable. |
| (vii) Groupings allow building and construct of database to add columns progressively based on the encounter. |
| (viii) Diagnosis is important because it is health outcome of hospital. Groupings important as performance |
| metrics. Simulating queries based on encounters. |
