Gaps #87143
Updated by Vasuki Muniratnam 5 months ago
To generate statistics on dominant organisms identified through microbiological testing, such as the most commonly identified pathogens by specimen type, etc. HUMS to provide details relevant to the required report Comment: To clarify/confirm with client on UI placement !clipboard-202508211736-f1oc2.png! Request to clarify with clients on these points below: How should we define "dominant" organisms? Suggestion for the above: By highest number of isolates, specimen type, resistance pattern, location/unit, infection severity or clinical impact. !clipboard-202508221213-mm5el.png! Example Report: Top 5 Dominant Organisms (Urine, August 2025) *MIS REPORT* MIS REPORT Report Name *Report Name:* Dominant Organism Analysis Report *Search Criteria* | Search Criteria Filter | Control | | Facility | Dropdown | | Ward / Unit | Dropdown | | From Collection Date | Date Picker | | To Collection Date | Date Picker | | Specimen Type | Multi-select Dropdown | | Source Type | Multi-select Dropdown | | Bacteria | Organism Name Optional Search | | Show Report | Button | Export Excel Button Export PDF Button Screen Layout: !clipboard-202606031538-zpjj1.png! *Output Grid* Layout -------------------------------------------------------------- Dominant Organism Analysis Report -------------------------------------------------------------- | Facility : [ UCSI Hospital ▼ ] Ward / Unit : [ All Wards ▼ ] Collection Date : [ 01/08/2025 ] To [ 31/08/2025 ] Specimen Type : [ All ▼ ] Source Type : [ All ▼ ] Organism Name : [________________] [Show Report] -------------------------------------------------------------- Output Grid Rank | Organism Name | Specimen Type | Source Type | No. of Isolates | % of Total Isolates | | 1 | Escherichia coli | Urine | Inpatient | 130 | 43% | | 2 | Klebsiella pneumoniae | Urine | Outpatient | 80 | 27% | | 3 | Enterococcus faecalis | Urine | Inpatient | 40 | 13% | | 4 | Proteus mirabilis | Urine | Walk-In | 25 | 8% | | 5 | Pseudomonas aeruginosa | Urine | Referral | 20 | 6% | | Sample output grid image: !clipboard-202606031609-qnelu.png! ... ... ... ... ... ... Sorting *Sorting* Default sorting: No. of Isolates: DECREASING ORDER Isolates DESC Highest isolate count appears first. *Calculation Logic:* 1. Calculation Logic Step 1 : Retrieve all finalized positive microbiology culture results within the selected: i) Collection Date range ii) Ward iii)Specimen Specimen Type iv) Source Type v) Bacteria 2. Step 2 Exclude: Negative cultures No growth cultures Contaminated cultures Pending cultures *Include Include only cultures with identified organisms.* organisms. 3. Step 3 *Isolate Counting Rule*: Apply De-duplication Rule a.) Only finalized positive culture results shall be included in the report. If: Same Patient b.) Each positive culture result shall be counted as one isolate. + c.) If the same patient has multiple positive cultures for the same organism and specimen type on d.) the SAME collection date, it shall be counted as one isolate only. Same Organism e.) If the same patient has positive cultures for the same organism and specimen type on f.) DIFFERENT collection dates, each occurrence shall be counted as a separate isolate. + Same Specimen Type *1.) Same patient + same organism + same specimen type + same collection date = appears within 14 days Count once only once. 2.) Same patient + same organism + same specimen type + different collection date = Count separately* Step 4 Apply Source Type Priority If duplicate found: Priority Source Type 1 Inpatient 2 Outpatient 3 Referral 4 Walk-In Assign isolate to highest priority source type. Step 5 Identify Unique Calculate Number of Isolates *Group by:* Patient + Bacteria + Specimen Type + Collection Date Group by: After unique isolates are identified, generate the report by grouping: Organism Name + Specimen Type + Source Type + Ward Then, Count Isolates records. Sort by, No of isolates, in Decreasing Order. Result: No. of Isolates Step 6 Calculate Percentage Formula: (Organism Isolates ÷ Total Isolates for same specimen type) × 100 Example: Organism Isolates E. coli 130 Klebsiella 80 Enterococcus 40 Proteus 25 Pseudomonas 20 Total 303 E. coli = 130 ÷ 303 × 100 = 43% Recommended Grid Columns Column Rank Organism Name Specimen Type Source Type Ward No. of Isolates % of Total Isolates Adding Ward is important because the client specifically requested ward-level analysis. Without the Ward column, users cannot identify where the organism prevalence originates.