A 100-patient database that contains in total 100 virtual patients, 372 admissions, and 111,483 lab observations.

description:

The National Patient Care Database (NPCD), located at the Austin Information Technology Center, is part of the National Medical Information Systems (NMIS). The NPCD collects integrated patient care data from all Veterans Health Information Systems and Technology Architecture (VistA) IT systems. Data recorded in the VistA Patient Care Encounter (PCE) package, which captures clinical data resulting from ambulatory care patient encounters is transmitted to the NPCD using the Ambulatory Care Reporting (ACR) Module of the VistA Patient Information Management System (PIMS) package. The Ambulatory Care Reporting Module provides necessary information on patient treatment, what services were rendered to patients, who provided the services, and whether services reported were synchronized with the VA medical center database. Directive 2006-026 (05/05/2006) required the inclusion to patient care data capture requirements the capture of inpatient encounters for patients seen in outpatient clinics and inpatient billable professional services.Additionally, NPCD includes VistA Spinal Cord Dysfunction (SCD) package and Primary Care Management Module (PCMM) data. The SCD central registry in NPCD is used to provide VA-wide review of patient demographics, clinical aspects of injury and disease, and resource utilization involved in providing care to patients. As of October 2010, data for the Spinal Cord Dysfunction is being maintained in the Spinal Cord Injury and Disorders Outcomes (SCIDO) database; current SCD data in NPCD is residual data only. The data load and extraction process for SCD data in NPCD will be discontinued in FY12. The PCMM data in NPCD includes primary care patient to provider assignments and provider utilization data.The NPCD is used by Veterans Health Administration (VHA) program offices for a wide variety of tasks to include research and budget allocation to medical centers.

The National Patient Care Database (NPCD), located at the Austin Information Technology Center, is part of the National Medical Information Systems (NMIS). The NPCD collects integrated patient care data from all Veterans Health Information Systems and Technology Architecture (VistA) IT systems. Data recorded in the VistA Patient Care Encounter (PCE) package, which captures clinical data resulting from ambulatory care patient encounters is transmitted to the NPCD using the Ambulatory Care Reporting (ACR) Module of the VistA Patient Information Management System (PIMS) package. The Ambulatory Care Reporting Module provides necessary information on patient treatment, what services were rendered to patients, who provided the services, and whether services reported were synchronized with the VA medical center database. Directive 2006-026 (05/05/2006) required the inclusion to patient care data capture requirements the capture of inpatient encounters for patients seen in outpatient clinics and inpatient billable professional services.Additionally, NPCD includes VistA Spinal Cord Dysfunction (SCD) package and Primary Care Management Module (PCMM) data. The SCD central registry in NPCD is used to provide VA-wide review of patient demographics, clinical aspects of injury and disease, and resource utilization involved in providing care to patients. As of October 2010, data for the Spinal Cord Dysfunction is being maintained in the Spinal Cord Injury and Disorders Outcomes (SCIDO) database; current SCD data in NPCD is residual data only. The data load and extraction process for SCD data in NPCD will be discontinued in FY12. The PCMM data in NPCD includes primary care patient to provider assignments and provider utilization data.The NPCD is used by Veterans Health Administration (VHA) program offices for a wide variety of tasks to include research and budget allocation to medical centers.

DSH COVID-19 Patient Testing: Last updated -11/07/2024 DSH COVID-19 Patient Data reports on patient positives and testing counts at the facility level for DSH. The table reports on the following data fields: Total patients that tested positive for COVID-19 since 5/16/2020 Patients newly positive for COVID-19 in the last 14 days Patient deaths while patient was positive for COVID-19 since 5/30/2020 Total number of tests administered since 3/23/2020 Table Notes: COVID-19 test results for patients include DSH patients who are tested while receiving treatment at an outside medical facility. Data has been de-identified in accordance with CalHHS Data De-identification Guidelines. Counts between 1-10 are masked with "<11". Includes Patients Under Investigation (PUIs) testing and proactive testing of asymptomatic patients for surveillance of geriatric, medically fragile, and skilled nursing facility units and for patients upon admission, re-admission, or discharge. Includes all individuals who were positive for COVID-19 at time of death, regardless of underlying health conditions or whether the cause of death has been confirmed to be COVID-19 related illness. Metro-Norwalk is additional COVID-19 surge space and technically a branch location that is part of DSH Metropolitan Hospital.

NOTE: This dataset is Inactive and is no longer supported. Any historical knowledge regarding meta data or it's creation is no longer available. All known information is proved as part of this data set. The National Cardiac Device Surveillance Program Database supports the Eastern Pacemaker Surveillance Center (EPSC) staff in its function of monitoring some 11,000 Veterans Health Administration (VHA) patients who have implanted pacemakers or cardioverters. The database stores medically useful information about the patients and their pacemaker test results in order to highlight serial changes, which determine whether the pacemaker is still functioning normally, or whether the patient requires further intervention. The EPSC staff performs regular telephonic checkups, in conjunction with less frequent in-hospital clinic checkups, to determine when pacemakers need to be replaced. Patients are scheduled and called by the Pacemaker Surveillance Center, and have their electrocardiogram recorded and analyzed over the phone, using wires attached to their fingers and a VHA-supplied transmitter. Additionally, some patients are monitored via web-based downloads of their device telemetry. The Pacemaker Center also provides in-hospital clinic checkups for local Washington DC VHA pacemaker patients. All information obtained during the checkups is recorded in the EPSC Database. The database also contains records of pacemaker patients being monitored by VHA facilities east of the Mississippi and who are not being monitored directly by their respective VA medical centers. The VHA Department of Medical Services encourages local VHA medical centers to refer their patients for pacemaker follow-up monitoring to either the Eastern Surveillance Center or to the counterpart Western Surveillance Center in San Francisco, whichever is geographically appropriate. However, referral is optional. The database also maintains a registry of all VHA patients, living and deceased, who have had pacemakers implanted at, or who have been monitored by, VHA facilities. The EPSC receives information for the registry directly from the medical centers for patients that it does not monitor, totaling over 80,000 as of 2010.

The Patient Assessment File (PAF) database compiles the results of the Patient Assessment Instrument (PAI) questionnaire filled out for intermediate care Veterans Health Administration (VHA) patients. The PAI is filled out within two weeks of admission. It is also completed semi-annually on April 1st and October 1st for each patient by a registered nurse familiar with the patient. The PAI questions cover medical treatments, conditions, selected diagnoses, activities of daily living, behaviors, some rehabilitation therapies, and chronic respiratory support. The database is managed by the Geriatrics & Extended Care Strategic Health Care Group in the Office of Patient Care Services. It is currently running at the Austin Information Technology Center (AITC) and is stored in flat files. PAF's primary customer is the Allocation Resource Center (ARC) in Braintree MA. The ARC receives the data from AITC and combines it with data from the Patient Treatment File (PTF) which contains more detailed demographic and treatment information. The ARC builds ORACLE tables, assigning RUG II (Resource Utilization Group II) scores and weighted work units reflecting the level and type of care needed. The 16 different weighted work units, ranging from 479 to 1800, are a factor in the resource allocation and budget decisions on long-term care, and are used to measure efficiency. The data is also used in other reports to Central Office, the Veterans Integrated Service Networks, and the facilities. Several other units also use PAF information including the Decision Support System (DSS). Currently, PAF is in the process of being replaced by the Resident Assessment Instrument/Minimum Data Set (RAI/MDS). RAI/MDS uses a much more extensive questionnaire as its source of information. The RAI/MDS provides clinical data and care protocols in addition to the newer RUG III scores, and is required by the Centers for Medicare and Medicaid Service funded hospitals.

DSH COVID-19 Patient Testing: Last updated -02/10/2025

DSH COVID-19 Patient Data reports on patient positives and testing counts at the facility level for DSH. The table reports on the following data fields:

• Total patients that tested positive for COVID-19 since 5/16/2020

• Patients newly positive for COVID-19 in the last 14 days

• Patient deaths while patient was positive for COVID-19 since 5/30/2020

• Total number of tests administered since 3/23/2020

Table Notes:

COVID-19 test results for patients include DSH patients who are tested while receiving treatment at an outside medical facility. Data has been de-identified in accordance with CalHHS Data De-identification Guidelines. Counts between 1-10 are masked with "<11". Includes Patients Under Investigation (PUIs) testing and proactive testing of asymptomatic patients for surveillance of geriatric, medically fragile, and skilled nursing facility units and for patients upon admission, re-admission, or discharge. Includes all individuals who were positive for COVID-19 at time of death, regardless of underlying health conditions or whether the cause of death has been confirmed to be COVID-19 related illness. Metro-Norwalk is additional COVID-19 surge space and technically a branch location that is part of DSH Metropolitan Hospital.

DSH COVID-19 Patient Testing: Last updated -02/10/2025

DSH COVID-19 Patient Data reports on patient positives and testing counts at the facility level for DSH. The table reports on the following data fields:

• Total patients that tested positive for COVID-19 since 5/16/2020

• Patients newly positive for COVID-19 in the last 14 days

• Patient deaths while patient was positive for COVID-19 since 5/30/2020

• Total number of tests administered since 3/23/2020

Table Notes:

COVID-19 test results for patients include DSH patients who are tested while receiving treatment at an outside medical facility. Data has been de-identified in accordance with CalHHS Data De-identification Guidelines. Counts between 1-10 are masked with "<11". Includes Patients Under Investigation (PUIs) testing and proactive testing of asymptomatic patients for surveillance of geriatric, medically fragile, and skilled nursing facility units and for patients upon admission, re-admission, or discharge. Includes all individuals who were positive for COVID-19 at time of death, regardless of underlying health conditions or whether the cause of death has been confirmed to be COVID-19 related illness. Metro-Norwalk is additional COVID-19 surge space and technically a branch location that is part of DSH Metropolitan Hospital.

The National Prosthetics Patient Database (NPPD) established a central database of Prosthetics data recorded at each Veterans Health Administration facility. Its objective was to enable clinical reviews to increase quality, reduce costs, and improve efficiency of the Prosthetics program. Increase the quality of the services to our Veterans by providing a means to develop consistency in services, review prescription and management practices, develop training, monitor Home Medical Equipment, and measure performance improvements. Reduce costs by comparing costs system-wide, identifying common items for consolidated contracting, identifying costs for Medical Cost Care Funds (MCCF) purposes and improving contracting cost benefit. Improve efficiency by validating the data, improving budget management, determining where coding errors occur, providing training, and comparing unique social security numbers for multiple site usage and item issue. The NPPD Menu provides patient information, patient eligibility, Prosthetic treatment, date of provision, cost, vendor, and purchasing agent information. This system tracks average cost data and its usage and provides on both a monthly and quarterly basis detailed and summary reports by station, Veterans Integrated Service Network (VISN) and agency. The NPPD Menu resides in Veterans Health Information Systems and Technology Architecture (VistA) at the medical center level. This data is updated quarterly. Data is rolled up at each facility and transmitted to Hines. The data is then loaded into the Corporate Data Warehouse (CDW) from which data extracts are done. The data is also put into a ProClarity cube and is available to VA local, regional, and national managers online. National managers have the ability to properly monitor, oversee and manage the national program and regional managers are able to effectively manage their respective areas using this tool. The primary purpose of this database is to provide financial and clinical oversight of the Prosthetics program and is used primarily by the Prosthetics and Sensory Aids (PSA) including VISN staff, VISN Prosthetics Representatives, Prosthetics Program Managers and other Prosthetics staff.

Patients Table:

• PatientID: Unique identifier for each patient.
• firstname: First name of the patient.
• lastname: Last name of the patient.
• email: Email address of the patient.

This table stores information about individual patients, including their names and contact details.

Doctors Table:

• DoctorID: Unique identifier for each doctor.
• DoctorName: Full name of the doctor.
• Specialization: Area of medical specialization.
• DoctorContact: Contact details of the doctor.

This table contains details about healthcare providers, including their names, specializations, and contact information.

Appointments Table:

• AppointmentID: Unique identifier for each appointment.
• Date: Date of the appointment.
• Time: Time of the appointment.
• PatientID: Foreign key referencing the Patients table, indicating the patient for the appointment.
• DoctorID: Foreign key referencing the Doctors table, indicating the doctor for the appointment.

This table records scheduled appointments, linking patients to doctors.

MedicalProcedure Table:

• ProcedureID: Unique identifier for each medical procedure.
• ProcedureName: Name or description of the medical procedure.
• AppointmentID: Foreign key referencing the Appointments table, indicating the appointment associated with the procedure.

This table stores details about medical procedures associated with specific appointments.

Billing Table:

• InvoiceID: Unique identifier for each billing transaction.
• PatientID: Foreign key referencing the Patients table, indicating the patient for the billing transaction.
• Items: Description of items or services billed.
• Amount: Amount charged for the billing transaction.

This table maintains records of billing transactions, associating them with specific patients.

demo Table:

• ID: Primary key, serves as a unique identifier for each record.
• Name: Name of the entity.
• Hint: Additional information or hint about the entity.

This table appears to be a demonstration or testing table, possibly unrelated to the healthcare management system.

This dataset schema is designed to capture comprehensive information about patients, doctors, appointments, medical procedures, and billing transactions in a healthcare management system. Adjustments can be made based on specific requirements, and additional attributes can be included as needed.

The dataset contains information of 213 cancer patients undergoing clinical or surgical treatment characterized on sociodemographic and clinical data as well as data from the Care Transition Measure (CTM 15-Brazil). Data collection was carried out 7 to 30 days after their discharge from hospital from June to August 2019. Understanding these data can contribute to improving quality of care transitions and avoiding hospital readmissions. To this end, this dataset contains a broad array of variables:

*gender

*age group

*place of residence

*race

*marital status

*schooling

*paid work activity

*type of treatment

*cancer staging

*metastasis

*comorbidities

*main complaint

*continue use medication

*diagnosis

*cancer type

*diagnostic year

*oncology treatment

*first hospitalization

*readmission in the last 30 days

*number of hospitalizations in the last 30 days

*readmission in the last 6 months

*number of hospitalizations in the last 6 months

*readmission in the last year

*number of hospitalizations in the last year

*questions 1-15 from CTM 15-Brazil

The data are presented as a single Excel XLSX file: cancer patient´s care transitions dataset.xlsx.

The analyses of the present dataset have the potential to generate hospital readmission prevention strategies to be implemented by the hospital team. Researchers who are interested in CTs of cancer patients can extensively explore the variables described here.

The project from which these data were extracted was approved by the institution’s research ethics committee (approval n. 3.266.259/2019) at Associação Hospital de Caridade Ijuí, Rio Grande do Sul, Brazil.

About OPCRD

Optimum Patient Care Research Database (OPCRD) is a real-world, longitudinal, research database that provides anonymised data to support scientific, medical, public health and exploratory research. OPCRD is established, funded and maintained by Optimum Patient Care Limited (OPC) – which is a not-for-profit social enterprise that has been providing quality improvement programmes and research support services to general practices across the UK since 2005.

Key Features of OPCRD

OPCRD has been purposefully designed to facilitate real-world data collection and address the growing demand for observational and pragmatic medical research, both in the UK and internationally. Data held in OPCRD is representative of routine clinical care and thus enables the study of ‘real-world’ effectiveness and health care utilisation patterns for chronic health conditions.

OPCRD unique qualities which set it apart from other research data resources: • De-identified electronic medical records of more than 24.9 million patients • OPCRD covers all major UK primary care clinical systems • OPCRD covers approximately 35% of the UK population • One of the biggest primary care research networks in the world, with over 1,175 practices • Linked patient reported outcomes for over 68,000 patients including Covid-19 patient reported data • Linkage to secondary care data sources including Hospital Episode Statistics (HES)

Data Available in OPCRD

OPCRD has received data contributions from over 1,175 practices and currently holds de-identified research ready data for over 24.9 million patients or data subjects. This includes longitudinal primary care patient data and any data relevant to the management of patients in primary care, and thus covers all conditions. The data is derived from both electronic health records (EHR) data and patient reported data from patient questionnaires delivered as part of quality improvement. OPCRD currently holds over 68,000 patient reported questionnaire data on Covid-19, asthma, COPD and rare diseases.

Approvals and Governance

OPCRD has NHS research ethics committee (REC) approval to provide anonymised data for scientific and medical research since 2010, with its most recent approval in 2020 (NHS HRA REC ref: 20/EM/0148). OPCRD is governed by the Anonymised Data Ethics and Protocols Transparency committee (ADEPT). All research conducted using anonymised data from OPCRD must gain prior approval from ADEPT. Proceeds from OPCRD data access fees and detailed feasibility assessments are re-invested into OPC services for the continued free provision of patient quality improvement programmes for contributing practices and patients.

For more information on OPCRD please visit: https://opcrd.co.uk/

Overview: The goal of the project was to develop a unique database linking chronic disease clinical data from an electronic medical record (EMR) of a large academic healthcare system to multi-payer claims data. The longitudinal relational database can be used to study clinical effectiveness of many diagnostic and treatment interventions. The population of patients used consisted of those patients who were attributed to the University of Michigan Health System (UMHS) as continuing care patients, who are also in adjudicated and validated chronic disease registries. Data Access: These data are not available from ICPSR. The data are restricted to use by the principal investigator and cannot be shared.

This dataset contains State data of several home health agency quality measures for Home Health Agencies. This survey is designed to measure the experiences of people receiving home health care from Medicare-certified home health agencies. The Home Health Care Consumer Assessment of Healthcare Providers and Systems (HHCAHPS) is conducted for home health agencies by approved HHCAHPS Survey vendors.

THIS RESOURCE IS NO LONGER IN SERVICE, documented on Septemeber 02, 2014. Through a collaborative effort with experts in doctor-elderly patient interaction who participated in the development of ADEPT, a database of approximately 435 audio and video tapes of visits of patients age 65 and older (n=46) to their primary physician was established for testing ADEPT and for access by medical educators and researchers. Data associated with each tape include reason for visit, physician characteristics (age, race, gender), patient characteristics (age, race, gender), companion characteristics (age, race, gender), and length of doctor-patient relationship. Through a collaborative effort with experts in doctor-elderly patient interaction who participated in the development of ADEPT, a database of approximately 435 audio and video tapes of visits of patients age 65 and older (n=46) to their primary physician was established for testing ADEPT and for access by medical educators and researchers. Data associated with each tape include reason for visit, physician characteristics (age, race, gender), patient characteristics (age, race, gender), companion characteristics (age, race, gender), and length of doctor-patient relationship. Patient visits to their primary physician were videotaped at four sites: an academic medical center in the Midwest, an academic medical center in the Southwest, a suburban managed care medical group, and an urban group of physicians in independent practice. Repeat visits between the same doctor and patient were taped for 19 patients resulting in 48 tapes of multiple visits. Patients were recruited in the waiting room for a convenience sample. Before the visit, patients provided demographic data and completed a global satisfaction form. Following the visit, patients completed the SF-36, and the ABIM for patient satisfaction. Two weeks following the visit, patients were contacted by telephone and asked about their understanding, compliance and their utilization of health services over the past year. At twelve months, patients were contacted by telephone for administration of the SF-36, the global satisfaction form, and the utilization of health services survey. Data Availability: Archived at the Saint Louis University School of Medicine Library. Interested researchers and medical educators should contact the PI, Mary Ann Cook, JVCRadiology (at) sbcglobal.net * Dates of Study: 1998-2001 * Study Features: Longitudinal, Anthropometric Measures * Sample Size: 46

Abstract

A UK Primary Care Database

Documentation

IMRD, incorporating THIN, a Cegedim Database in electronic form, and otherwise, is a longitudinal patient database. Primary care practices in the UK are recruited by Cegedim to participate in the data collection scheme. The data collection software removes practice, practitioner and patient identifiers at source, retaining information on patient’s, (1) the physical health or condition of that patient, (2) the mental health or condition of that patient, (3) the diagnosis of the condition of that patient, (4) the care or treatment given to that patient, and (5) other information which is to an extent derived, directly or indirectly, from such information.

Data provided by: IQVIA

Section 2

Section 3

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 28,2025. The Stroke Patient Recovery Research Database (SPReD) initiative creates the infrastructure needed for the collection of a wide range of data related to stroke risk factors and to stroke recovery. It also promotes the analysis and management of large brain and vessel images. A major goal is to create a comprehensive electronic database Stroke Patient Recovery Research Database or SPReD and populate it with patient data, including demographic, biomarker, genetic and proteomic data and imaging data. SPReD will enable us to combine descriptions of our stroke patients from multiple projects that are geographically distributed. We will do this in a uniform fashion in order to enhance our ability to document rates of recovery; to study the effects of vascular risk factors and inflammatory biomarkers; and to use these data to improve their physical and cognitive recovery through innovative intervention programs. This comprehensive database will provide an integrated repository of data with which our researchers will investigate and test original ideas, ultimately leading to knowledge that can be applied clinically to benefit stroke survivors.

Aim: The purpose of obtaining the required data is to obtain a source of information on the health status of the population. At the same time, the National Register of Hospitalized Patients provides data for a qualitative and quantitative assessment of the activities of individual inpatient facilities and their departments.

Data from the NRHOSP are an important tool for managing the health sector and determining the concept and implementation of the state's health policy, which is needed to define the optimal network of inpatient medical facilities. The resulting information from the NRHOSP is transferred to the database of the World Health Organization (WHO) and other international organizations according to contractual obligations.

Statistical unit of inquiry: The statistical unit is the completed stay of a hospitalized patient in the department.

Every completed hospitalization of a patient (native or foreigner) in one inpatient department of an inpatient care provider, regardless of the method of admission and termination (discharge, transfer, death) becomes a mandatory report.

Cases of one-day care (one-day surgery) are also reported to NRHOSP. One-day care is health care, the provision of which requires the patient to stay in bed for a period of less than 24 hours, taking into account the nature and duration of the medical services provided. When providing one-day care, continuous availability of acute inpatient intensive care must be ensured ( Section 8, Act No. 372/2011 Coll. , on health services).

Newly, in accordance with decree 373/2016 Coll. cases of hospitalization not completed by the end of the monitored year are also compulsorily reported to the NRHOSP, by the end of January of the following year at the latest. These cases must be marked with the termination method "hospitalization continues" with a termination date of 12/31 of the monitored year.

MIMIC-III is a large, freely-available database comprising deidentified health-related data associated with over forty thousand patients who stayed in critical care units of the Beth Israel Deaconess Medical Center between 2001 and 2012. The database includes information such as demographics, vital sign measurements made at the bedside (~1 data point per hour), laboratory test results, procedures, medications, caregiver notes, imaging reports, and mortality (including post-hospital discharge).MIMIC supports a diverse range of analytic studies spanning epidemiology, clinical decision-rule improvement, and electronic tool development. It is notable for three factors: it is freely available to researchers worldwide; it encompasses a diverse and very large population of ICU patients; and it contains highly granular data, including vital signs, laboratory results, and medications.

Retrospectively collected medical data has the opportunity to improve patient care through knowledge discovery and algorithm development. Broad reuse of medical data is desirable for the greatest public good, but data sharing must be done in a manner which protects patient privacy. Here we present Medical Information Mart for Intensive Care (MIMIC)-IV, a large deidentified dataset of patients admitted to the emergency department or an intensive care unit at the Beth Israel Deaconess Medical Center in Boston, MA. MIMIC-IV contains data for over 65,000 patients admitted to an ICU and over 200,000 patients admitted to the emergency department. MIMIC-IV incorporates contemporary data and adopts a modular approach to data organization, highlighting data provenance and facilitating both individual and combined use of disparate data sources. MIMIC-IV is intended to carry on the success of MIMIC-III and support a broad set of applications within healthcare.

This database contains a physiologically realistic virtual patient database (VPD), representing the human arterial system, for the primary purpose of studying the affects of arterial disease on haemodynamics.