Healthcare
18 columns
100 rows
8 formats

Drug Utilization Review (DUR) and Quality Metrics

This dataset provides comprehensive records of drug utilization reviews, capturing findings such as polypharmacy, inappropriate prescribing, Beers Criteria violations, and HEDIS pharmacy measure compliance. It also tracks quality improvement interventions and links each review to patient and prescriber details, enabling robust analysis of medication safety and prescribing practices. Ideal for healthcare quality improvement, regulatory reporting, and clinical research.

last updated 2 Nov 2025
by GoMask

The brief that made it

Monitoring and improving medication safety and prescribing practices

Sample rows

preview · 8 of 100 rows · all 18 columns

review_idstring	hedis_measure_resultstring	num_active_medicationsinteger	inappropriate_prescribing_flagboolean	hedis_measure_idstring	patient_idstring	review_datedate	polypharmacy_flagboolean	beers_criteria_violation_flagboolean	hedis_measure_namestring	quality_intervention_flagboolean	intervention_typestring	intervention_datedate	prescriber_idstring	prescriber_specialtystring	patient_ageinteger	patient_genderstring	notesstring
DUR-1001	compliant	7	false	HM-003	PAT-2001	2023-03-11	true	false	Statin Therapy for Patients with Diabetes	true	medication change	2023-03-13	PRSC-3012	Endocrinology	57	female	Patient started on statin after review.
DUR-1002	blank	2	false	blank	PAT-2002	2022-12-02	false	false	blank	false	blank	blank	PRSC-3055	Family Medicine	33	male	Routine DUR, no issues identified.
DUR-1003	non-compliant	9	true	HM-002	PAT-2003	2023-01-22	true	true	High-Risk Medication in the Elderly	true	deprescribing	2023-01-30	PRSC-3078	Geriatrics	82	female	Beers Criteria violation addressed via deprescribing.
DUR-1004	blank	1	false	blank	PAT-2004	2023-05-15	false	false	blank	false	blank	blank	PRSC-3090	Pediatrics	8	male	Pediatric patient, single medication.
DUR-1005	compliant	6	false	HM-001	PAT-2005	2022-08-19	true	false	Medication Adherence for Hypertension	false	blank	blank	PRSC-3020	Cardiology	66	other	Good adherence, no intervention needed.
DUR-1006	non-compliant	8	true	HM-004	PAT-2006	2023-04-03	true	false	Antipsychotic Use in Children	true	education	2023-04-12	PRSC-3105	Psychiatry	15	female	Prescriber advised regarding guideline violations.
DUR-1007	blank	3	false	blank	PAT-2007	2022-10-27	false	false	blank	false	blank	blank	PRSC-3017	Internal Medicine	48	female	No DUR issues detected.
DUR-1008	non-compliant	11	true	HM-002	PAT-2008	2023-06-10	true	true	High-Risk Medication in the Elderly	true	deprescribing	2023-06-15	PRSC-3078	Geriatrics	79	male	Multiple inappropriate medications identified.
DUR-1009	blank	1	false	blank	PAT-2009	2022-09-08	false	false	blank	false	blank	blank	PRSC-3111	Family Medicine	41	male	Single prescription, review routine.
DUR-1010	non-compliant	5	true	HM-005	PAT-2010	2023-02-24	true	false	Antidepressant Medication Management	true	education	2023-03-03	PRSC-3132	Psychiatry	29	female	Non-adherence addressed through patient education.
DUR-1011	compliant	2	false	HM-001	PAT-2011	2023-07-19	false	false	Medication Adherence for Hypertension	false	blank	blank	PRSC-3155	Cardiology	64	male	Adherence excellent, no intervention.
DUR-1012	blank	10	false	blank	PAT-2012	2022-11-04	true	false	blank	false	blank	blank	PRSC-3167	Rheumatology	56	female	Complex regimen but no violations.
DUR-1013	compliant	2	false	HM-001	PAT-2013	2023-03-28	false	false	Medication Adherence for Hypertension	false	blank	blank	PRSC-3020	Cardiology	65	female	Patient reviewed for hypertension adherence.
DUR-1014	non-compliant	6	true	HM-005	PAT-2014	2023-04-25	true	false	Antidepressant Medication Management	true	medication change	2023-04-27	PRSC-3132	Psychiatry	45	male	Medication regimen adjusted after review.
DUR-1015	blank	0	false	blank	PAT-2015	2022-06-16	false	false	blank	false	blank	blank	PRSC-3188	Family Medicine	22	female	No medications currently active.
DUR-1016	non-compliant	12	true	HM-002	PAT-2016	2023-05-09	true	true	High-Risk Medication in the Elderly	true	deprescribing	2023-05-12	PRSC-3078	Geriatrics	85	female	Deprescribing intervention for Beers violation.
DUR-1017	compliant	1	false	HM-003	PAT-2017	2022-10-14	false	false	Statin Therapy for Patients with Diabetes	false	blank	blank	PRSC-3012	Endocrinology	50	male	Routine diabetes statin therapy review.
DUR-1018	blank	10	false	blank	PAT-2018	2023-06-30	true	false	blank	false	blank	blank	PRSC-3167	Rheumatology	59	female	Multiple medications, all compliant.
DUR-1019	blank	3	false	blank	PAT-2019	2023-01-08	false	false	blank	false	blank	blank	PRSC-3200	Family Medicine	36	female	No DUR issues.
DUR-1020	non-compliant	6	true	HM-004	PAT-2020	2023-02-13	true	false	Antipsychotic Use in Children	true	education	2023-02-18	PRSC-3105	Psychiatry	13	male	Prescriber educated on antipsychotic guidelines.

What the 100 rows show

from the 100-row sample

Non-compliant (hedis measure result) stands out: 28 of its 29 rows have inappropriate_prescribing_flag = true, against 0 of 33 for the rest.

28%inappropriate_prescribing_flag = true
4.5median num_active_medications
3intervention types
4patient genders
12prescriber specialties
53median patient_age

Inappropriate prescribing flag rate by hedis_measure_resultinappropriate_prescribing_flag = true

Non-compliant (hedis measure result)'s mean num_active_medications is 8.4, against 4.7 for compliant.

num_active_medications100 rows, in bands of 2

Median 4.5, from 0 to 13.

hedis_measure_id62 rows with a value · 38 left blank

HM-0018
HM-0057
HM-0036
HM-0026
HM-0043
HEDIS-CPM-043
HEDIS-ADR-013
HEDIS-PDC-053
HEDIS-PDC-013
HEDIS-PDC-023

18 columns by typefrom the column list below

string 10
integer 2
date 2
boolean 4

Columns

18 columns in four groups

blueprint · 18 columns
column	type	description	example
Text 10 columns
`review_id`	string	Unique identifier for each drug utilization review recordunique	DUR-1001
`patient_id`	string	Unique identifier for the patient whose drug regimen is being reviewed	PAT-2001
`hedis_measure_id`	string	Identifier for the HEDIS pharmacy measure evaluated during the reviewoptional	HM-003
`hedis_measure_name`	string	Name of the HEDIS pharmacy measure evaluatedoptional	Statin Therapy for Patien…
`hedis_measure_result`	string	Result of the HEDIS measure evaluation (e.g., compliant, non-compliant, not applicable)compliant · non-compliant · not applicable · optional	compliant
`intervention_type`	string	Type of quality improvement intervention recommended or implemented (e.g., medication change, education, deprescribing)3 types · optional	medication change
`prescriber_id`	string	Unique identifier for the prescriber responsible for the patient's medication regimen	PRSC-3012
`prescriber_specialty`	string	Medical specialty of the prescriber12 specialties · optional	Endocrinology
`patient_gender`	string	Gender of the patientmale · female · other · unknown · optional	female
`notes`	string	Additional notes or comments from the reviewer regarding findings and recommendationsoptional	No DUR issues detected.
Numbers 2 columns
`num_active_medications`	integer	Number of active medications prescribed to the patient at the time of review0 or more	7
`patient_age`	integer	Age of the patient at the time of review0 to 120	57
Dates and times 2 columns
`review_date`	date	Date when the drug utilization review was conducted	2023-03-11
`intervention_date`	date	Date when the quality improvement intervention was implementedoptional	2023-03-13
True or false 4 columns
`polypharmacy_flag`	boolean	Indicates if polypharmacy (use of multiple medications) was identified	true
`inappropriate_prescribing_flag`	boolean	Indicates if inappropriate prescribing was detected according to clinical guidelines	false
`beers_criteria_violation_flag`	boolean	Indicates if any Beers Criteria violations were found for elderly patients	false
`quality_intervention_flag`	boolean	Indicates if a quality improvement intervention was recommended or implemented	true

Use it for

A healthcare dashboard
The inappropriate_prescribing_flag rate, num_active_medications by hedis_measure_result and a breakdown of hedis_measure_id. Excel, Power BI or Tableau.
Why do 28 of 100 rows have inappropriate_prescribing_flag = true?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Reviews100
DUR-10017compliant
DUR-10039non-comp…
DUR-10068non-comp…
A software demo
Believable reviews with patient_id, review_date and polypharmacy_flag to fill a screen in front of a buyer.

This dataset100 rows18 columns

Yours1,000 rows18 columns

blueprint · drug-utilization-review-dur-and-quality-metrics

Behind this dataset

Same schema. As many rows as you need.

These 100 rows came out of a blueprint — 18 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

DUR ID unique per review
Review type: prospective, concurrent, retrospective
Polypharmacy: typically 5+ medications, or 10+ for geriatrics
Beers Criteria: potentially inappropriate medications in elderly
High-risk medication use: anticholinergics, sedatives, NSAIDs in elderly
Duplicate therapy across classes
Drug-disease contraindications
HEDIS pharmacy measures: statin use in diabetes, beta-blocker post-MI, ACE-I in CHF

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

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: drug-utilization-review-dur-and-quality-metrics

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?