Healthcare
15 columns
100 rows
8 formats

Microbiology Culture and Sensitivity

This dataset provides detailed microbiology culture and sensitivity results, including organism identification, colony counts, antibiotic susceptibility profiles (MIC values and interpretations), resistance patterns, and infection control alerts. It enables robust tracking of antimicrobial resistance trends, supports stewardship initiatives, and facilitates infection control monitoring in healthcare settings.

last updated 2 Nov 2025
by GoMask

The brief that made it

Hospital antimicrobial stewardship and resistance surveillance

Sample rows

preview · 8 of 100 rows · all 15 columns

culture_idstring	specimen_typestring	colony_countinteger	infection_control_alertboolean	antibiotic_namestring	patient_idstring	specimen_collection_datedate	organism_identifiedstring	mic_valuefloat	susceptibility_interpretationstring	resistance_patternstring	report_datedate	laboratory_namestring	ordering_physicianstring	hospital_unitstring
CULT20240001	blood	1200	true	Vancomycin	PAT10001	2024-03-14	Staphylococcus aureus	1	Susceptible	MRSA	2024-03-15	MetroLab Diagnostics	Dr. Emily Carter	ICU
CULT20240002	urine	90000	true	Ciprofloxacin	PAT10002	2024-04-03	Escherichia coli	0.5	Resistant	ESBL	2024-04-04	Saint Mary Lab	Dr. Samuel Lee	Nephrology
CULT20240003	sputum	48000	true	Meropenem	PAT10003	2024-02-20	Klebsiella pneumoniae	8	Resistant	MDR	2024-02-21	Central PathLab	Dr. Rachel Kim	Pulmonology
CULT20240004	wound	23000	false	Imipenem	PAT10004	2024-05-08	Pseudomonas aeruginosa	2	Intermediate	None	2024-05-09	MetroLab Diagnostics	Dr. Olivia Grant	Surgery
CULT20240005	stool	3000	true	Linezolid	PAT10005	2024-01-19	Enterococcus faecalis	0.75	Susceptible	VRE	2024-01-20	HealthFirst Labs	Dr. Adam Foster	Gastroenterology
CULT20240006	urine	64000	false	Ampicillin	PAT10006	2024-02-16	Proteus mirabilis	16	Resistant	None	2024-02-17	Saint Mary Lab	Dr. Henry Wright	Urology
CULT20240007	blood	500	false	Penicillin	PAT10007	2024-03-25	Streptococcus pneumoniae	0.12	Intermediate	None	2024-03-26	Central PathLab	Dr. Karen Yu	Emergency
CULT20240008	wound	200	true	Oxacillin	PAT10008	2024-05-13	Staphylococcus epidermidis	0.5	Resistant	MRSA	2024-05-14	MetroLab Diagnostics	Dr. Emily Carter	Orthopedics
CULT20240009	sputum	800	false	Ceftriaxone	PAT10009	2024-02-09	Haemophilus influenzae	0.25	Susceptible	None	2024-02-10	HealthFirst Labs	Dr. Rachel Kim	Pulmonology
CULT20240010	blood	100	true	Gentamicin	PAT10010	2024-03-11	Escherichia coli	0.5	Susceptible	ESBL	2024-03-12	Saint Mary Lab	Dr. Samuel Lee	ICU
CULT20240011	urine	76000	true	Ceftazidime	PAT10011	2024-01-21	Enterobacter cloacae	32	Resistant	MDR	2024-01-22	Central PathLab	Dr. Henry Wright	Nephrology
CULT20240012	sputum	49500	true	Colistin	PAT10012	2024-03-17	Acinetobacter baumannii	2	Intermediate	XDR	2024-03-18	MetroLab Diagnostics	Dr. Adam Foster	Pulmonology
CULT20240013	wound	3000	false	Clindamycin	PAT10013	2024-04-25	Streptococcus pyogenes	0.25	Susceptible	None	2024-04-26	Saint Mary Lab	Dr. Olivia Grant	Surgery
CULT20240014	stool	12000	false	Cefotaxime	PAT10014	2024-05-10	Salmonella enterica	0.5	Susceptible	None	2024-05-11	HealthFirst Labs	Dr. Karen Yu	Gastroenterology
CULT20240015	urine	100000	true	Nitrofurantoin	PAT10015	2024-03-02	Escherichia coli	32	Resistant	ESBL	2024-03-03	MetroLab Diagnostics	Dr. Emily Carter	Urology
CULT20240016	blood	500	true	Daptomycin	PAT10016	2024-04-29	Staphylococcus aureus	0.5	Susceptible	MRSA	2024-04-30	Central PathLab	Dr. Samuel Lee	ICU
CULT20240017	other	50	false	Fluconazole	PAT10017	2024-05-05	Candida albicans	2	Intermediate	None	2024-05-06	Saint Mary Lab	Dr. Rachel Kim	Oncology
CULT20240018	wound	7000	true	Ceftazidime	PAT10018	2024-02-13	Pseudomonas aeruginosa	8	Resistant	MDR	2024-02-14	HealthFirst Labs	Dr. Adam Foster	Burn Unit
CULT20240019	blood	400	false	Penicillin	PAT10019	2024-04-15	Streptococcus pyogenes	0.06	Susceptible	None	2024-04-16	MetroLab Diagnostics	Dr. Olivia Grant	Emergency
CULT20240020	sputum	32000	true	Imipenem	PAT10020	2024-03-23	Klebsiella pneumoniae	16	Resistant	ESBL	2024-03-24	Saint Mary Lab	Dr. Henry Wright	Pulmonology

What the 100 rows show

from the 100-row sample

Urine (specimen type) stands out: mean colony_count is 82,800, against 17,963 for the rest.

58%infection_control_alert = true
6,000median colony_count
3susceptibility interpretations
8resistance patterns
8laboratory names
11hospital units

Mean colony_count by specimen_type99 rows

colony_count99 rows, in bands of 20k

Median 6,000, from 50 to 120,000.

antibiotic_name100 rows · top 10 of 31 values

Ciprofloxacin7
Penicillin7
Vancomycin6
Imipenem6
Linezolid6
Meropenem5
Ceftriaxone5
Clindamycin5
Cefotaxime5
Daptomycin5

15 columns by typefrom the column list below

string 10
integer 1
float 1
date 2
boolean 1

Columns

15 columns in four groups

blueprint · 15 columns
column	type	description	example
Text 10 columns
`culture_id`	string	Unique identifier for the microbiology culture test resultunique	CULT20240001
`patient_id`	string	Unique identifier for the patient from whom the specimen was collected	PAT10001
`specimen_type`	string	Type of specimen collected for culture (e.g., blood, urine, sputum)6 values	blood
`organism_identified`	string	Name of the microorganism identified in the culture (e.g., Escherichia coli)	Staphylococcus aureus
`antibiotic_name`	string	Name of the antibiotic tested for susceptibility (e.g., Ciprofloxacin)	Vancomycin
`susceptibility_interpretation`	string	Interpretation of organism's susceptibility to the antibiotic (e.g., Susceptible, Intermediate, Resistant)Susceptible · Intermediate · Resistant	Susceptible
`resistance_pattern`	string	Summary of resistance pattern (e.g., ESBL, MRSA, VRE, MDR, XDR, PDR)8 values · optional	MRSA
`laboratory_name`	string	Name of the laboratory performing the test8 names · optional	MetroLab Diagnostics
`ordering_physician`	string	Name or identifier of the physician who ordered the testoptional	Dr. Emily Carter
`hospital_unit`	string	Hospital unit or ward where the patient was located at the time of specimen collection11 units · optional	ICU
Numbers 2 columns
`colony_count`	integer	Number of colonies detected in the specimen (CFU/mL or other units)0 or more · optional	1200
`mic_value`	float	Minimum inhibitory concentration (MIC) value for the antibiotic against the organism (µg/mL)0 or more · optional	1
Dates and times 2 columns
`specimen_collection_date`	date	Date when the specimen was collected	2024-03-14
`report_date`	date	Date when the culture and sensitivity report was finalized	2024-03-15
True or false 1 column
`infection_control_alert`	boolean	Indicates if an infection control alert was triggered for antimicrobial stewardshipoptional	true

Use it for

A healthcare dashboard
The infection_control_alert rate, colony_count by specimen_type and a breakdown of antibiotic_name. Excel, Power BI or Tableau.
Why do the 20 urine rows have a mean colony_count of 82,800?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Cultures100
CULT202400011200blood
CULT2024000290000urine
CULT2024000423000wound
A software demo
Believable cultures with patient_id, specimen_type and specimen_collection_date to fill a screen in front of a buyer.

This dataset100 rows15 columns

Yours1,000 rows15 columns

blueprint · microbiology-culture-and-sensitivity

Behind this dataset

Same schema. As many rows as you need.

These 100 rows came out of a blueprint — 15 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Culture ID unique per specimen
Specimen source: blood, urine, sputum, wound, CSF, etc.
Organism identification: species level if possible
Colony count or growth level (light, moderate, heavy)
Gram stain results
Antibiotic panel tested
MIC (Minimum Inhibitory Concentration) values
Susceptibility: sensitive, intermediate, resistant

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: microbiology-culture-and-sensitivity

What should your data show?

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Sample rows

What the 100 rows show

Columns

Use it for

A healthcare dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Healthcare

What should your data show?