Vital Signs

The Public Health Information Network, or PHIN, is described in the HIMSS Dictionary as the CDC’s vision for fully capable, interoperable information systems across the many organizations in public health, and as a national initiative for a multi-organizational business and technical architecture. This post explains the idea, what studies found about electronic laboratory reporting, electronic case reporting, and data quality, and what clinicians can do to make reporting work.

MyHealthEData is a federal initiative to empower patients by making sure they control their health care data and decide how it is used, while keeping it secure. It is led by CMS, ONC, NIH, and the VA. This post explains the initiative and its policy context, what a single-center study found about inpatient portal access and disparities after the information blocking rule, and what an API reference implementation proposed for patient-controlled data export.

Healthcare data encryption disguises electronic health information so that unauthorized users cannot read it. This post explains encryption at rest and in transit, how the HIPAA Security Rule treats encryption as an addressable specification, what NIST guidance covers, what a scoping review of 52 primary care studies reported about insufficient encryption, and how a Portuguese case study estimated hospital cyberattack costs.

A detailed clinical model is an information model that expresses one or more clinical concepts and their context in a standardized, reusable way, as a set of discrete logical data elements. This post explains how DCMs relate to archetypes and FHIR resources, what a nursing study found when building 240 DCMs for perinatal nursing actions, and what a hospital study found when DCMs were used to reuse EHR data for COVID-19 research.

A critical access hospital, or CAH, is a rural community hospital that receives cost-based reimbursement and meets criteria set out in the Medicare Conditions of Participation. This post explains the federal limits on beds and length of stay, what a 45-study systematic review found about health IT barriers in CAHs, what a national analysis found about rural AI adoption and evaluation, and what a Pennsylvania study found about nurse staffing.

An algorithm is a step-by-step procedure for solving a problem or calculating a result, and in data mining it fixes the settings that shape a model. This post explains how simple clinical algorithms differ from machine learning models, what a widely cited study found about racial bias in a commercial risk algorithm, what an external validation found for a widely implemented sepsis prediction model, and what governance questions follow.

Under HIPAA, use refers to handling individually identifiable health information, by sharing, applying, examining, or analyzing it, inside the entity that maintains it, which separates it from disclosure outside the entity. This post explains the distinction, the permitted uses framework, what an oncology study found about patient views on consent and data use after deliberation, and what Australian data custodians reported about barriers to sharing data.

A security audit is a systematic evaluation of how well an information system conforms to established security criteria. This post explains what an audit examines, how it differs from audit logs, risk analysis, and security testing, what the HIPAA Security Rule requires for audit controls and periodic evaluation, what machine learning research found about detecting inappropriate record access, and how nursing audit log research could inform workload analysis.

An organized healthcare arrangement is a HIPAA concept in which participants share protected health information to manage a common enterprise and patients expect integrated care. This post explains the regulatory definition, what the Privacy Rule permits within an arrangement, including joint notices of privacy practices, what a survey of 115 hospitals found about notice readability, and what a California survey found about consumer views of data sharing.

A lab results interface, or LRI, supports the electronic transmission of clinical results from a laboratory information system into an electronic health record. This post explains the HL7 implementation guide behind the term, why code mapping matters, what a laboratory review of EHR test builds found, what the CLIA test report rule requires of results systems, and what a large health system’s surveillance program found about missed abnormal results.

Health information security refers to the physical, technological, and administrative safeguards used to protect identifiable health data from unwarranted access or disclosure. This post explains the three safeguard types, the HIPAA Security Rule’s general requirements, what a 2026 review says about clinician-level cybersecurity habits, and what a survey of 283 Israeli nurses and physicians found about WhatsApp use for clinical information.

Data validation is the checking of source data for accuracy and quality before the data are used, imported, or processed. This post explains common check types, how a harmonized framework groups data quality into conformance, completeness, and plausibility, what a systematic review of 29 studies found about the factors behind medical record data quality, and why checks matter most when data move between systems.

A biometric identifier is biologically unique data that identify a person. The HIMSS Dictionary notes that under HIPAA biometric identifiers are protected health information, and the de-identification rule lists finger and voice prints among identifiers to remove. This post explains the term, what a Zambian study of ear images for infant identification reported, what a scoping review of 65 articles found on voice data ethics, and why biometrics raise privacy questions that passwords do not.

An alert is a signal, written or acoustic, that announces a message or result or warns of a possible problem. The HIMSS Dictionary separates passive alerts, which appear on screen, from active alerts that notify a person immediately. This post covers what a 23-article review found about override rates, what a 39-article review found about design and role tailoring, and what a four-trust NHS study found about digital sepsis alerts.

The Unified Modeling Language, or UML, is a standard notation for specifying, visualizing, constructing, and documenting software systems. This post explains common UML diagram types, how a nursing guideline was modeled in UML for decision support, what a scoping review found about visual modeling languages for patient pathways, and how UML connects to HL7 modeling work.

The HIMSS Dictionary describes the science of clinical informatics as the transformation of clinical data into information, then knowledge, that supports clinical decision-making. This post explains that progression, what a study of 93 nursing handoffs found about knowledge in everyday communication, how certification and fellowship pathways developed, and why the field depends on understanding how clinicians actually decide.

A recovery point objective, or RPO, describes the age of the data that must be recovered from backup for normal operations to resume after a failure. This post explains RPO, how it differs from recovery time objective, what a retrospective study of 204 EHR downtime events found, and what research on ransomware says about the stakes for patient care.

In the HIMSS Dictionary, key management services generate and manage the keys that identify records when data arrive from several source systems into an EHR repository. This post explains why source keys can clash, how identity keys differ from the cryptographic keys that protect data, what a multihospital study found when checking keys across 1,573 tables, and what a machine learning study found for patient record linkage.

GUDID is the Food and Drug Administration’s database of device identification information for medical devices that carry a unique device identifier. This post explains what the database does and does not hold, how the device identifier and production identifier differ, what a multicenter informatics study found when UDIs were used in health records, and what a UK barcoding case study showed about scanning in practice.

Data analytics is the systematic use of data to drive fact-based decisions for planning, management, measurement, and learning. This post explains the four levels of analytics, what a 2025 systematic review found about nurse managers, what a 2024 scoping review found about public health policy tools, and why data quality and governance decide whether analytics helps.