|Submitted By: Joel Andress / Centers for Medicare and Medicaid Services (CMS) Center for Clinical Standards and Quality (CCSQ)|
|Data Element Information|
|Use Case Description(s)|
|Use Case Description||Encounter information is used extensively by hospitals, clinicians and providers submitting data for quality measurement. This patient level encounter information provides context for when, why and what type of healthcare encounters occurred which may have led to conditions diagnosed, procedures performed, or medications prescribed. It is used in quality measurement to define a population for measurement based on time of encounter occurrence, and encounter reason, or the location within a hospital an encounter occurred.
It is also critical context for clinicians interpreting transferred information. For example, contextualizing an eGFR measure during an acute care hospitalization excludes it from use in categorizing a patient’s stage of chronic kidney disease. For quality assessment, the context of encounters is the cornerstone of attribution and accountability for performance.
|Estimated number of stakeholders capturing, accessing using or exchanging||More than 4,000 hospitals and 1 million providers are currently capturing, accessing and exchanging this encounter level information. This information is currently electronically submitted by providers and hospitals, or their Health IT firms/EHR vendors, to CMS for quality measurement.|
|Link to use case project page||https://ecqi.healthit.gov/ecqms|
|Use Case Description||Data exchange of encounter information is also critical for clinical care. Clinicians need to be aware of recent healthcare encounters, including the type of encounter, the reason for the visit, how recent that encounter was (date/time) and discharge disposition and diagnosis in order to provide relevant and quality care for the patient thereafter.
Currently, this type of encounter information is exchanged as part of care coordination and admission/discharge/transfer notifications as part of ONC interoperability standards.
|Estimated number of stakeholders capturing, accessing using or exchanging||All healthcare providers using certified electronic health record technology (CEHRT) should be capturing, accessing, using and exchanging these encounter data elements.|
|Link to use case project page||https://www.healthit.gov/isa/section-ii-contentstructure-standards-and-implementation-specifications|
|Use Case Description||Actively monitoring diseases, making decisions about public health threats, identifying trends in healthcare services utilization and other public health matters depend on accessible and accurate data. EHRs are a data source that can provide timely and relevant data beyond its use by health care providers. EHR data, if made more available for public health professionals and researchers, can lead to more rapid disease detection, tracking, and treatment and innovation in healthcare delivery.
A patient's encounter with a provider of medical services, ranging from an ambulatory office visit with the patient's primary care provider, to a sudden, acute injury necessitating a trip to an Emergency Department to an admission to and subsequent discharge from a hospital for surgery is a fundamental organizing principle across the healthcare industry. The encounter class of data elements is widely used in EHRs and other systems for clinical care, payment purposes and operational efficiency. Beginning with the encounter status, often used as a trigger for clinical workflow, through classifying, numerically identifying and assigning a date and time to the encounter, to identifying the patient and provider subjects of the encounter as well as their roles form the structure of the encounter these encounter elements have varied clinical and administrative uses. The chief complaint, reason for visit and encounter diagnoses capture the richness of the encounter while the expected source of encounter payment and encounter discharge disposition provide information for follow up and payment. The majority of the candidate encounter data elements here are either mandatory or must support data elements of the US CORE Encounter Profile or Shall or Should data elements in many CDA use cases.
The Making EHR Data More Available for Research and Public Health (MedMorph) project's goal is to create a reliable, scalable, and interoperable method to get electronic health record data for multiple public health and research scenarios (use cases). MedMorph has identified Cancer Registry Reporting, Healthcare Surveys, Electronic Initial Case Reporting (eCR), Hepatitis C Reporting, Birth Reporting and Research (PCORNet) use cases that support the adoption of these encounter data elements. These specific use cases are described in more depth on their respective web pages.
Cancer Reporting: https://www.cdc.gov/cancer/npcr/
Hepatitis C Reporting: https://www.cdc.gov/hepatitis/pdfs/HepatitisCaseRprtForm.pdf
Health Care Surveys: https://www.cdc.gov/nchs/dhcs/nhcs_registry_landing.htm
Birth Reporting: https://www.cdc.gov/nchs/nvss/births.htm
Link to use case project page: https://www.cdc.gov/csels/phio/making-ehr-data-more-available.html Cancer Reporting: https://www.cdc.gov/cancer/npcr/ Hepatitis C Reporting: https://www.cdc.gov/hepatitis/pdfs/HepatitisCaseRprtForm.pdf Health Care Surveys: https://www.cdc.gov
Attachment describing this use case:
|Estimated number of stakeholders capturing, accessing using or exchanging||Estimate the number of stakeholders who would capture, access, use or exchange this data element or data class: All 50 states participate in one or more of the MedMorph public health and research use cases that exchange these encounter data elements. Up to 14 territorial or city jurisdictions also participate in one of these public health use cases and use these data elements.
All hospitals and physicians who diagnose or treat cancer are required to provide encounter information to state cancer registries.
Approximately 620,000 physicians in the US are active and have at least some component of ambulatory practice and thus are annually eligible to sampling and recruitment into the National Ambulatory Medical Care Survey (NAMCS), which samples from between 3,500 to 20,000 of these physicians annually. Presently each sampled physician submits one weeks' worth of patient encounters to NAMCS. Approximately 600 hospitals are in the National Hospital Care Survey (NHCS). 1/3 of that number are either in, or actively being recruited into, the EHR data submission mode for NHCS. NHCS is already receiving electronic CDA documents. When they reach their target of 200 hospitals submitting by this mode annually they will be receiving >1.2 million documents and sets including multiple sets of medication data annually.
Related to birth reporting, every year there are approximately 3.7 million births in the United States. Consumption of this data is widespread. Every jurisdiction in the country captures birth certification information and immunization administration. Most also capture birth defects and fetal deaths. Healthcare systems that provide care for expectant mothers should be collecting this data.
There were approximately 1,000,000 practicing physicians (as of 2020), approximately 120,000 certified physician assistants (as of 2019) and 290,000 licensed nurse practitioners (as of 2019). Most of these licensed clinicians interact with one of these public health use cases intermittently, annually. As of 2018 AHA reported 6,146 hospitals in the US experiencing 36,353,946 admissions. Almost all of those hospitals and many of the admissions interact with one or more of the public health and or research use cases. The vast majority of these exchanges include most or at least some of the encounter data elements contained in this submission.
|Maturity of Use and Technical Specifications for Data Element|
|Applicable Standard(s)||Encounter type/occurrence:
SNOMED CT (example, value set OID: 2.16.840.1.113883.3.666.5.307)
HCPCS (example, value set OID: 2.16.840.1.113883.3.464.1003.101.12.1087)
CPT (example, value set OID: 2.16.840.1.113883.3.464.1003.101.12.1001)
HL7 value set, encounter type: https://www.hl7.org/fhir/us/core/ValueSet-us-core-encounter-type.html
Encounter Diagnosis/ Primary Diagnosis/Discharge Diagnosis:
Code System http://terminology.hl7.org/CodeSystem/discharge-disposition
|Additional Specifications||HL7 FHIR US Core Implementation Guide STU3 based on FHIR R4, Encounter profile. (https://www.hl7.org/fhir/us/core/index.html) Encounter status, class, type, period (timing), reason, location, discharge disposition all must have/must support data elements
This Encounter profile is also required by the US Core IG Capability Statement. (https://www.hl7.org/fhir/us/core/capstatements.html)
CMS Quality Data Model (QDM) version 5.5 Guidance (https://ecqi.healthit.gov/sites/default/files/QDM-v5.5-Guidance-Update-May-2020-508.pdf)
HL7 C-CDA Release 2.0 (http://www.hl7.org/implement/standards/product_brief.cfm?product_id=492)
|Current Use||This data element has been used at scale between multiple different production environments to support the majority of anticipated stakeholders|
Encounter data is routinely captured in EHR systems used by hospitals, providers, and other healthcare stakeholders. Encounter-based EHR data is submitted by providers to CMS via QRDA I and III files and other data architectures from hospitals, providers, health IT firms, and vendors for eCQM public reporting in CMS IQR, QPP, and Promoting Interoperability programs. CMS requires the submission of patient and encounter based data for quality measurement for eligible hospitals/CAHs and clinicians using ONC Certified Health Electronic Record Technology (CEHRT)—this includes encounter details including admission and discharge date/times or office visit date/times to determine which patients are included in the measurement periods, type of encounter, and encounter diagnoses/primary reason, discharge dispositions, and encounter location details to determine the population of interest, or measure exclusions.
Widely available in EHR systems:
|Number of organizations/individuals with which this data element has been electronically exchanged||5 or more. This data element has been tested at scale between multiple different production environments to support the majority of anticipated stakeholders.|
Encounter data for quality measurement is electronically exchanged from organization’s EHR systems to CMS for reporting and payment quality measurement programs, via QRDA files and other data architectures. These encounter data elements have been tested for reliability and validity of capture during the development of CMS eCQMs and can be feasibly electronically captured and exchanged. Ongoing testing for exchanging these data in FHIR standards via HL7 Connectathons.
Encounter data has also been electronically exchanges with external organizations via C-CDA, as part of ONC’s requirements and a part of data exchange for the continuum of care to notify of admissions, discharges, and transfers of care.
|Restrictions on Standardization (e.g. proprietary code)||No challenges anticipated. This data is available in standard terminology that can be publicly access via the VSAC and HL7.|
|Restrictions on Use (e.g. licensing, user fees)||We are not aware of any restrictions.|
|Privacy and Security Concerns||This data, like any patient data should be exchanged securely. Current processes exist, governed by CMS and ONC, to securely transfer this data.|
|Estimate of Overall Burden||Encounter data is regularly captured by a broad range of healthcare providers, and should not cause burden to implement. This data is already regularly exchanged and available in standardized fields and terminology. It is also required by the US Core Capability Statement and therefore will be stood up by those stakeholders complying with the ONC requirement for the Standardized FHIR API for patient and population services.|
|Other Implementation Challenges||N/A|
Information related to interactions between healthcare providers and a patient.
Represents a date/time related to an encounter (e.g., scheduled appointment time, check in time, start and stop times).