Patient records, medical imaging, clinical trials
Demographics, clinical diagnoses, procedures, risk factors
This dataset provides detailed records of patient hospital episodes, including demographics, clinical diagnoses, procedures, risk factors, and readmission outcomes. Designed to support clinical decision support, resource allocation, and value-based care analytics, it enables robust analysis of factors influencing hospital readmissions and patient outcomes.
Unified, event-level view of patient health by integrating device telemetry
This dataset provides a unified, event-level view of patient health by integrating device telemetry, vital sign measurements, and laboratory results. Each record is timestamped and linked to both patient and device, enabling advanced multimodal AI research, cross-sensor data fusion, and holistic patient state modeling for healthcare analytics and clinical studies.
Heart rate, step counts, sleep stages, activity types, and calories burned
This dataset contains high-frequency, time-stamped health metrics collected from wearable devices, including heart rate, step counts, sleep stages, activity types, and calories burned. It supports multi-user, multi-device scenarios and is ideal for developing personalized wellness algorithms, sleep analysis, and preventative health models. The structure enables granular time-series analytics and integration with broader health informatics systems.
Patient, prescriber, medication, and pharmacy details
This dataset provides comprehensive, anonymized records of pharmacy prescription orders and medication fulfillment events, including patient, prescriber, medication, and pharmacy details. It enables robust analysis of medication adherence patterns and pharmacy workflow efficiency, supporting research, quality improvement, and operational analytics in healthcare settings.
27 cols
Flat-structured view of healthcare insurance claims
This dataset provides a comprehensive, flat-structured view of healthcare insurance claims, tracking each claim's journey from clinical service through submission, adjudication, and payment. It includes detailed fields for patient, provider, payer, financials, service location, and claim status, making it ideal for process mining, compliance auditing, and cross-domain healthcare analytics.
Technical, clinical, and workflow attributes
This dataset provides comprehensive, structured metadata for simulated diagnostic medical images, including technical, clinical, and workflow attributes. It supports machine learning model development for image processing, anomaly detection, and workflow automation, with detailed fields for modality, patient, study, annotation, and device information. The dataset is ideal for benchmarking, model training, and workflow optimization in medical imaging.
Beds, staff, and equipment across departments and shifts
This dataset provides granular, time-stamped records of hospital resource utilization, including beds, staff, and equipment across departments and shifts. It enables detailed analysis and forecasting for operational planning, surge management, and cost optimization, making it ideal for AI-driven resource allocation and healthcare analytics. The dataset supports both real-time monitoring and historical trend analysis for improved hospital efficiency.
Turn-by-turn logs of synthetic conversations between patients
This dataset contains detailed, turn-by-turn logs of synthetic conversations between patients and virtual healthcare assistants, annotated with intent and dialog act labels for each message. It enables benchmarking and development of conversational AI models for healthcare, supporting tasks such as intent classification, dialog management, and entity extraction. The dataset is ideal for researchers and practitioners building or evaluating medical chatbots and virtual health assistants.
Alert types, severity, escalation actions, and resolution steps
This dataset provides detailed records of alerts generated by remote health monitoring devices, including alert types, severity, escalation actions, and resolution steps. It enables comprehensive tracking of patient safety events, device performance, and care team responses, supporting clinical workflows and quality improvement initiatives. The dataset is ideal for real-time monitoring, compliance auditing, and predictive analytics in healthcare environments.
Patient demographics, triage assessments, vital signs, diagnoses
This dataset provides detailed, de-identified records of emergency department visits, including patient demographics, triage assessments, vital signs, diagnoses, procedures, and outcomes. It enables robust analysis of triage algorithms, patient flow, and clinical outcomes, supporting research and quality improvement in emergency medicine.
Both over-the-counter and prescription medications
This dataset provides detailed, line-level records of pharmacy retail purchase events, including both over-the-counter and prescription medications. Each record captures transaction details, customer demographics (where available), product specifics, payment method, and prescription information, enabling comprehensive analysis of purchasing patterns, health trends, and market basket behaviors.
Healthcare patient referral flows
This dataset provides a comprehensive view of healthcare patient referral flows, capturing detailed information on cross-provider referral patterns, delays, outcomes, and leakage events. It enables healthcare organizations to analyze care coordination, identify bottlenecks, and optimize referral processes to improve patient outcomes and reduce network leakage.
22 cols
Detailed event descriptions, severity, outcomes
This dataset provides a comprehensive, structured record of adverse events reported by participants in clinical trials, including detailed event descriptions, severity, outcomes, and relationships to study drugs. It enables robust safety monitoring, regulatory compliance, and in-depth analysis of clinical trial safety data across multiple sites and studies.
Session timing, wait times, patient engagement actions, device usage
This dataset provides detailed, anonymized metrics from virtual healthcare sessions, including session timing, wait times, patient engagement actions, device usage, connection quality, and post-session feedback. It enables robust analysis of telehealth utilization, patient experience, and operational efficiency, supporting quality improvement and research in digital health delivery.
15 cols
Ratings on staff, communication, cleanliness, and outcomes
This dataset aggregates detailed, standardized patient satisfaction and outcome survey responses from hospitals and healthcare facilities, including ratings on staff, communication, cleanliness, and outcomes, along with patient demographics and visit details. It enables robust benchmarking, quality improvement, and predictive analytics for healthcare providers and researchers.
Demographics, diagnoses, clinical parameters, medications
This dataset provides a comprehensive registry of chronic disease patients, including demographics, diagnoses, clinical parameters, medications, and risk stratification metrics. It is designed to support advanced analytics, care management workflows, and risk prediction models for population health management and clinical decision support.
Beds, staff, ventilators, and PPE, to support capacity planning
This dataset provides daily, hospital-level forecasts of resource utilization, including beds, staff, ventilators, and PPE, to support capacity planning and emergency response. Each record details projected needs and availability for specific resource types, along with confidence intervals and model metadata, enabling healthcare administrators and policymakers to anticipate surges and allocate resources efficiently.
Severity, duration, medication usage, and demographic information
This dataset provides detailed, time-stamped records of patient-reported symptoms, including severity, duration, medication usage, and demographic information. It enables comprehensive tracking of disease progression and supports advanced analytics and AI-based diagnostic research in healthcare. The structure is optimized for longitudinal studies and integration with clinical systems.
Timestamped logs of patient adherence to prescribed medication regimens
This dataset provides detailed, timestamped logs of patient adherence to prescribed medication regimens, capturing scheduled and actual intake times, adherence status, and reasons for nonadherence. It enables healthcare providers to monitor compliance, identify patterns of missed doses, and design targeted interventions to improve patient outcomes and reduce hospital readmissions.
Demographics, clinical encounters, vital signs, laboratory results
This dataset provides comprehensive, longitudinal synthetic patient records simulating chronic disease progression, including demographics, clinical encounters, vital signs, laboratory results, medications, and outcomes. Designed for safe AI/ML experimentation, it enables time-series modeling, predictive analytics, and healthcare research without patient privacy risks.
Heart rate, blood pressure, respiratory rate, blood oxygen saturation
This dataset provides high-frequency, multi-sensor vital sign measurements from synthetic wearable devices, including heart rate, blood pressure, respiratory rate, blood oxygen saturation, and skin temperature. Each record is timestamped and linked to a user and device, with contextual information such as activity type, sensor status, and geolocation, making it ideal for time-series analysis, anomaly detection, and digital health research.
16 cols
Ratings on satisfaction, communication, technical quality
This dataset contains detailed, structured feedback from synthetic telemedicine consultations, including ratings on satisfaction, communication, technical quality, and free-text comments. It captures patient demographics, consultation context, and device usage, making it ideal for analyzing patient experience, modeling satisfaction drivers, and optimizing telemedicine services.
Patient and operator interactions with connected medical devices
This dataset provides detailed, synthetic logs of patient and operator interactions with connected medical devices, capturing device, user, compliance, and anomaly information. It enables comprehensive analysis of device usage patterns, operator behavior, procedural compliance, and early detection of anomalies or errors in clinical settings. The dataset is valuable for improving device usability, supporting regulatory audits, and enhancing patient safety.
Patient demographics, structured symptoms, vital signs, and triage outcomes
This dataset provides detailed records of emergency department triage decisions, including patient demographics, structured symptoms, vital signs, and triage outcomes. It enables urgent care optimization, patient flow modeling, and clinical research into triage patterns and outcomes. The comprehensive structure supports both operational analytics and advanced predictive modeling.
Code systems found in the sample rows of all 222 healthcare datasets.
Generated Real code
One sentence in. A dataset with that pattern out.
| age | primary_dx | discharge_date | readmit_30d |
|---|---|---|---|
| 81 | I50.9 | 2024-03-14 | yes |
| 52 | E11.9 | 2024-03-14 | no |
| 77 | J44.1 | — | yes |
| 64 | N18.3 | 2024-03-15 | no |
A pattern you asked for Everything else