HHS 503 Ch.6 (1).pdf

Health Information Management Technology: An Applied Approach, Sixth Edition Chapter 6: Data Management ahima.org ahima.org © 2020 AHIMA Data Management The definition and structure of data elements and the creation, storage, and transmission of data elements Organizations need to know and understan...

Health Information Management Technology: An Applied Approach, Sixth Edition Chapter 6: Data Management ahima.org ahima.org © 2020 AHIMA Data Management The definition and structure of data elements and the creation, storage, and transmission of data elements Organizations need to know and understand How data is produced Why certain types and formats of data are produced How data are stored and managed How to ensure data integrity ahima.org © 2020 AHIMA Data Sources Locations where data is being generated and stored within an organization Includes both Clinical data Example: test results and history Administrative data elements Example: Billing data and demographic ahima.org © 2020 AHIMA Common Data Sources In Healthcare Electronic health record (EHR) Practice management system Lab information systems Radiology information systems Picture archival and communications (PACs) Other clinical documentation systems (home health, therapy, long-term care) Master patient index Other patient index (indices) Databases Registries ahima.org © 2020 AHIMA System Characterization Process of creating an inventory of all systems that contain data, including documenting where the data are stored, what type of data are created or stored, how they are managed, with what hardware and software they interact, and providing basic security measures for the systems ahima.org © 2020 AHIMA Data Elements A single or individual fact that represents the smallest unique subset of a larger database sometimes referred to as the raw facts and figures Examples Age Gender Blood Pressure ahima.org © 2020 AHIMA Data Dictionary A listing of all the data elements within a specific system that defines each individual data element, standard input of the data element, and specific data length ahima.org © 2020 AHIMA ahima.org © 2020 AHIMA Data Sets A recommended list of data elements that have defined and uniform definitions that are specific to a type of healthcare industry ahima.org © 2020 AHIMA Common Data Sets in Healthcare Uniform Hospital Discharge Data Set (UHDDS) Uniform Ambulatory Care Data Set (UACDS) Data Elements for Emergency Department Systems (DEEDS) Minimum Data Set (MDS) Outcomes and Assessment Information Set (OASIS) Essential Medical Data Set (EMDS) ahima.org © 2020 AHIMA Databases A collection of data that are organized in such a way that its contents can be easily accessed, managed, reported, and updated ahima.org © 2020 AHIMA Types of Database Relational database Object-oriented database ahima.org © 2020 AHIMA Database Lifecycle Initial study (determining need for database) Design (identify data fields, structure, and so forth) Implementation (development of database) Testing and evaluation (ensuring system works as expected) Operation (use of database) Database maintenance and evaluation (updating and backing up database and ensuring that it still meets needs) ahima.org © 2020 AHIMA Indices A report or list from a database that provides guidance, indication, or other references to the data contained in the database. Serves as a guide or indicator to locate something within a database or other systems storing data ahima.org © 2020 AHIMA Common Healthcare Indices Master patient index Disease index Operation or procedure index Physician index ahima.org © 2020 AHIMA Data Mapping A process that allows for connections between two systems. Source data Location from which the data originates, such as a database or a data set Target data Location from which the data is mapped or to where it is sent ahima.org © 2020 AHIMA Example Data Map Target Data ICD-10-CM code ICD-10-CM name Equivalence SNOMED CT code SNOMED CT name A00.0 Cholera, unspecified 63650001 Cholera Source Data ahima.org © 2020 AHIMA Equal Mapping Relationships No match Approximate match Exact match ahima.org © 2020 AHIMA Data Warehousing The process of collecting the data from different data sources within an organization and storing it in a single database that can be used for decision making ahima.org © 2020 AHIMA Data Warehouse A single database that makes it possible to access data that exists in multiple databases through one single query and reporting interface Data mining ahima.org © 2020 AHIMA Information Governance An organization-wide framework for managing information throughout its lifecycle and supporting the organization’s strategy, operations, regulatory, legal, risk, and environmental requirements ahima.org © 2020 AHIMA Information Governance Valued strategic asset Business intelligence Situation, Background, Assessment, Recommendation (SBAR) Enterprise information management ahima.org © 2020 AHIMA AHIMA’s Information Governance Principles Accountability Transparency Integrity Protection Compliance Availability Retention Disposition ahima.org © 2020 AHIMA AHIMA’s Information Governance Adoption Model (IGAM)TM ahima.org © 2020 AHIMA AHIMA’s Information Governance Adoption Model (IGAM)TM Adoption Levels Adoption Level Adoption Level Details Level 1 – At Risk This level describes an environment where information governance concerns, requirements, and opportunities are not addressed at all, are addressed minimally, or are addressed in an ad hoc manner. Level 2 – Aware This level describes an environment where there is a developing recognition that information governance has an impact on the organization and that the organization may benefit from a more defined information governance program. Level 3 – Aspirational This level describes the essential, or minimum, requirements that must be addressed to meet the organization’s legal, regulatory, and business requirements. Level 3 is characterized by defined policies and procedures and the implementation of processes specifically intended to improve information governance. Level 4 – Aligned This level describes an organization that has established a proactive information governance program throughout its operations and has established continuous improvement for it. Information governance issues and considerations are routinely integrated into business decisions. The organization is substantially more than minimally compliant with good practice and easily meets its legal and regulatory requirements. Level 5 – Actualized This level describes an organization that has integrated information governance into its overall infrastructure and business processes to such an extent that compliance with program requirements and legal, regulatory, and other responsibilities are routine. ahima.org © 2020 AHIMA Data Governance Process for ensuring that control and accountability for enterprise data management is established through out an organization Focuses on how healthcare organizations create processes, policies, and procedures for keeping information that is relevant to patient care and healthcare operations ahima.org © 2020 AHIMA Data Stewardship Creation of responsibility for data through principles and practices to ensure that the appropriate knowledge and use of the data from personal health information is being used appropriately ahima.org © 2020 AHIMA Data Sharing For patient care Two or more information systems must be able to share information Two or more information systems collect and use the shared information ahima.org © 2020 AHIMA Data Integrity The assurance that the data entered into an electronic system or maintained on paper are only accessed and amended by individuals with the authority to do so. Includes Data governance Patient authentication Authorship validation Amendment and records correct Audit validation ahima.org © 2020 AHIMA Common Standards Development Organizations Health Level 7 Digital Imaging and Communication in Medicine Institute of Electrical and Electronics Engineers National Council for Prescription Drug Programs Standards of how to move patient data from one provider to another ahima.org © 2020 AHIMA Data Information Exchange Allow for electronic exchange of information between providers’ electronic systems Needed to support interoperability Capability of two or more information systems and software applications to communicate and exchange information ahima.org © 2020 AHIMA Data Information Exchange Standards development organization Data Interchange Standards are created to support the electronic exchange of information ahima.org © 2020 AHIMA Standards Development Organizations Health Level 7 Institute of Electrical and Electronics Engineers National Council for Prescription Drug Programs ahima.org © 2020 AHIMA Data Strategy Clearly defines the organization’s data policies and procedures, roles and responsibilities for data governance, business rules for data governance, process for controlling data redundancy, management of key master data, use of structured and unstructured data, storage for all healthcare data, and safeguards and protections of the data ahima.org © 2020 AHIMA Data Strategy Components Data standardization and integration Data quality Metadata management – Data about data Data modeling Data ownership Data stewardship ahima.org © 2020 AHIMA Enterprise Information Management Information assets Information collected during day-to-day operations of a healthcare organization that has value within an organization Enterprise information management Set of functions created by an organization to plan, organize, and coordinate the people, processes, technology, and content needed to manage information for the purposes of data quality, patient safety, and ease of use ahima.org © 2020 AHIMA Data Visualization and Presentation Options Tables Graphs Data and information should be meaningful ahima.org © 2020 AHIMA Critical Thinking Skills Look at situation from multiple angles Legal Ethical Policy Best practices And more Recommend action ahima.org © 2020 AHIMA Data Quality Ensuring the information entered into the patient’s record is reliable and has integrity in order to support patient care, patient safety, and provide evidence for reimbursement and accreditation ahima.org © 2020 AHIMA AHIMA’s Data Quality Management Model Domains Application Collection Warehousing Analysis ahima.org © 2020 AHIMA AHIMA’s Data Quality Management Model Characteristics Accuracy Accessibility Comprehensiveness Consistency Currency Definition Precision Relevancy Timeliness ahima.org © 2020 AHIMA Clinical Documentation Integrity A program designed to ensure the quality and integrity of the patient data while supporting healthcare operations such as coding and reimbursement (CDI) Goals Obtain specific documentation that clinical documentation integrity can be used to identify the patient’s severity of illness Identify missing, conflicting, or unclear documentation Support code assignment and reimbursement Facilitate health record completion Support communication between care providers Facilitates education Improve quality of care ahima.org © 2020 AHIMA CDI Queries – Test Question Communication tool for CDI staff to communicate with providers to obtain clinical clarification, provide a documentation alert, clarify documentation, or ask additional questions regarding documentation Paper queries Electronic queries ahima.org © 2020 AHIMA Data Collection Tools Screen design Structured data Unstructured data Forms design Best practices Forms control ahima.org © 2020 AHIMA Clinical Documentation Integrity Process to conduct concurrent and retrospective reviews of medical information to review for conflicting, incomplete, or nonspecific provider documentation in order to verify clinical specific and documentation is appropriate and supports the medical codes assigned ahima.org © 2020 AHIMA Clinical Documentation Integrity (continued) Legibility Reliability Precision Completeness Consistency Clarity Timeliness ahima.org © 2020 AHIMA CDI Tools Audits Queries ahima.org © 2020 AHIMA CDI Reporting Support successes of the CDI team and show improvement is important and can be accomplished through reporting Common CDI reporting areas Discharges available/discharges reviewed for CDI Number of queries by provider and impact on DRG Number of queries resulting in severity of illness changes Provider response to queries and turnaround time by provider Outcomes of CDI queries by physician (agree or disagree with CDI specialist) Case mix index (CMI) impact by services line Reimbursement impact by queries ahima.org © 2020 AHIMA CDI Education Education based on the finding from CDI work is essential to enhance the quality and completeness of documentation to support severity of illness. Education consists of provider education, coding education, documentation education, and other education based on trends. ahima.org © 2020 AHIMA Data Management and Bylaws Written documents that provide details and information regarding the rules and regulations established by a healthcare organization to help support healthcare operations Bylaws can support and facilitate the collection and assurance of quality data ahima.org © 2020 AHIMA Common Types of Bylaws Used Provider contracts with facilities Delineate all expectations of the provider as they care for patients in a specific ambulatory care setting Medical staff bylaws Describe the manner in which providers will practice medicine within an organization that aligns with the mission and values of the organization Hospital bylaws Written documents that govern the staff members who create data within the record for additional support of patient care and reimbursement ahima.org © 2020 AHIMA HIM Roles in Data Management Information governance Data governance Clinical documentation integrity ahima.org © 2020 AHIMA