Health Information Chapter 5

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Healthcare Data Sets and Standards

Data represent

Basic facts and measurements

In healthcare, these data facts usually describe:

specific characteristics of individual patients.

The term data is plural. Although the singular form is:

datum

Datum (singular form of data)

•The term that is frequently used to describe a single fact or measurement is data element
•For example, age, gender, insurance company, and blood pressure are all data elements concerning a patient.

The term information refers to:

•Data that have been collected, combined, analyzed, interpreted, and/or converted into a form that can be used for specific purposes

In other words, data represent _____; information represents _______.

facts; meaning

In healthcare settings, data are stored where?

•In the individual's health record whether that record is in paper or electronic format
•Data elements in the health record are then combined, analyzed, and interpreted by the patient's physician and other clinicians

Example of data elements in the health record being combined?

•Test results are combined with the physician's observations and the patient's description of his or her symptoms to form information about the disease or condition that is affecting the patient.

What are data and information used by physicians for?

Physicians use both data and information to •diagnose diseases
•develop treatment plans
•assess the effectiveness of care, and
•determine the patient's prognosis

Data about patients can be extracted from individual health records and combined as what?

Aggregate data

What is aggregate data used for?

•used to develop information about groups of patients
•Example: data about all of the patients who suffered an acute myocardial infarction during a specific time period could be collected in a database.

What is it possible to identify from the aggregate data? What is an example?

•Common characteristics that might predict the course of the disease or provide information about the most effective way to treat it
•Research using aggregated data might be used for disease prevention
•Ex: researchers identified the link between smoking and lung cancer by analyzing aggregate data about patients with a diagnosis of lung cancer; smoking cessation programs grew from the identification of the causal effect of smoking on lung cancer and a variety of other conditions

Modern efforts at standardizing healthcare data began when?
What happened at this time?

•In the 1960s
•Healthcare facilities began to use computers to process larger amounts of data than could be handled manually
•During the 1960s, the idea of standardization became widely accepted

What was the goal of processing large amounts of data? What became evident as a result?

•The goal was to make comparisons among data from multiple providers
•It soon became evident that healthcare organizations needed to use standardized, uniform data definitions in order to arrive at meaningful data comparisons

The first data standardization efforts focused on what? What was the intent?

•Focus was generally on hospitals and specifically on hospital discharge data
•The intent of the efforts was to standardize definitions of key data elements commonly collected in hospitals

How was discharge data collected?

•Discharge data were collected in hospital discharge abstract systems
•These systems used databases compiled from aggregate data on all the patients discharged from a particular facility

What did the need of uniform discharge data lead to?

The need to compare uniform discharge data from one hospital to the next led to the development of data sets, or lists of recommended data elements with uniform definitions

What does the extensive use of information across org boundaries demand?

•The extensive use of information within and across organizational boundaries demands standards that promote interoperable electronic interchange of data and information. •Information standards are critical in the migration to electronic health records (EHRs)

What is wrong with the data sets originally developed to support uniform data collection?

They are inadequate for an electronic environment, and many public and private organizations have been actively engaged in the process of developing healthcare information standards to support EHR development and information interchange

Key players in the standards development community do what?

negotiate, refine, and revise standards

Which federal initiatives recognized the critical importance of healthcare information standards?

•Consolidated Health Informatics (CHI) initiatives
•Office of the National Coordinator of Health Information Technology (ONC).

Consolidated Health Informatics (CHI) initiative:

The effort to achieve CHI through federal agencies spearheaded by the Office of National Coordinator for Health Information Technology

Office of the National Coordinator (ONC) for Health Information Technology:

Office that provides leadership for the development and implementation of an interoperable health information technology infrastructure nationwide to improve healthcare quality and delivery

What did the report titled "Toward a National Health Information Infrastructure" say? Who authored this report?

•Author: The National Committee on Vital and Health Statistics (NCVHS)
•"if information in multiple locations is to be searched, shared, and synthesized when needed, we will need agreed-upon information guardians that can exchange data with each other ...we will need equitable rules of data exchange so that competitors (within or between healthcare provider systems, health information management companies, or health Web services) will be willing to connect and share data"

What will help improve patient care, increase safety, and assist clinical and administrative decision-making?

Developing a Nationwide Health Information Network (NHIN) that will improve patient care, increase safety, and assist clinical and administrative decision-making.

It is essential that the ___ ____________ understand the purpose, content, and importance of healthcare data sets and standards

HIM professional

The HIM professionals work with many:

of these data sets and data standards on the job

Data standard:

Data standards are the agreed upon specifications for the values acceptable for specific data fields

In the years to come, the roles of the HIM professional will be influenced and likely change as:

standards continue to develop, be adopted, and ultimately implemented.

Data dictionary:

A descriptive list of the data elements to be collected in an information system or database whose purpose is to ensure consistency of terminology

Why did a health information services clinical data standards committee develop a data dictionary?

As a first step toward implementing an EHR system.

What guidelines were used in developing the data dictionary?

•Design a plan
•Develop an enterprise data dictionary
•Ensure collaborative involvement and buy-in
•Develop an approvals process and documentation trail
•Identify and retail details of data versions
•Design for flexibility and growth
•Design room for expansion of field values
•Follow established ISO/International Electrotechnical Commission (IEC) 11179 guidelines or rules for metadata registry
•Adopt nationally recognized standards and normalize field definitions across data sets
•Beware of differing standards for the same concepts
•Use geographic codes and standards that conform to the National Spatial Data Infrastructure and Federal Geographic Data Committee
•Test the information system
•Provide ongoing education and training
•Assess the extent to which the data elements maintain consistency and avoid duplication

Data dictionaries include the following components:

•A list of data elements collected in individual health records
•Definitions of the data elements
•Descriptions of the attributes of each data element
•Specifications for the size of the data field in the information system
•Descriptions of the data views to be accessed by various users
•Location where the data are stored

What simple data element did the clinical data standards committee start with in building the data dictionary?

•Patient gender

Committee members looked at which two standard references for patient data sets in acute care setting? What did both data sets indicate?

•The Uniform Hospital Discharge Data Set (UHDDS)
•Uniform Ambulatory Care Data Set (UACDS)
•Both data sets indicated that gender should be recorded as either "male" or "female"

Why did this "either-or" choice for gender present a problem?

•Gender re-assignment
•Congenital defects in birth that made it difficult to determine a baby's gender

What did the clinical lab rep on the committee stress the importance of during discussions of the problem with gender? And why?

•Documenting the gender of every patient
•The normal range for most lab tests varies by gender (this info was a surprise to committee members)
•After the committee's initial discussion, the health info mgmt director agreed to research other data sets and standards

After the committee's initial discussion, the HIM director agreed to research what? What was found?

•Other data sets and standards
•He found the Health Level Seven (HL7) Version 3.0 recommended three values for admin gender: F, M, UN, w/ display names of Female, Male, Undifferentiated, and definitions, Female, Male, the gender of a person could not be uniquely defined as male or female, such as hermaphrodite

The HIM director found the F, M, UN code system to have been selected by what organization as one of the terminologies used in their specifications for clinical documents and messages?

Healthcare Information Technology Standards Panel (HITSP);
•The committee decided to adopt this HL7 standard for administrative gender

The challenges the committee faced in defining this relatively simple data element raised its awareness of what?

How difficult it would be to adequately define every data element to be included in the new EHR system.

What did the committee discover in gathering information on every healthcare data set available? Why were they committed to this process?

•That the implementation of the EHR system would be a huge project
•But they were committed to the process bc it would improve the quality of the data collected in the system

What would the collection of consistent, reliable, and valid data do for the system?

•It would improve administrative and clinical decision making
•Make it possible to perform meaningful performance improvement comparisons, and •Result in the ability to move healthcare information electronically between disparate healthcare information systems.

without data there is no what?

information

Creating a data set is a method to:

Capture and arrange certain data elements in order to turn data into information

What is the definition of a data set?

A list of recommended data elements with uniform definitions that are relevant for a particular use.

As an example of a data set, the Medicare Provider Analysis and Review (MEDPAR) File available from the Centers for Medicare and Medicaid Services (CMS) contains what?

•Data from claims for services provided to beneficiaries admitted to Medicare-certified inpatient hospitals and skilled nursing facilities (SNF)
•The data set for this file is the data contained in the billing form's fields

Another example of a data set is the QDS:

¶The quality data set (QDS) published by the National Quality Forum (NQF).
•The QDS provides a standardized core set of data that should be captured in patients' electronic health records and be included in any quality measure (NQF 2009a)

During the 1960s, the idea of standardization became widely accepted under the leadership of which groups?

•Under the leadership of the National Center for Health Statistics (NCHS) and
•The NCVHS in collaboration with other organizations, data sets were developed for a variety of healthcare settings

Which were the first sets of data to be created?

Data sets for acute care, long-term care, and ambulatory care were the first to be created.

What were two purposes of healthcare data sets?

1. To identify the data elements taht should be collected for each patient
2. To provide uniform definitions for common terms
•The use of uniform definitions ensures that data collected from a variety of healthcare settings will share a standard definition

Standardizing data elements and definitions makes it possible to compare:

•The data collected at different facilities
•For example, when data are standardized, the term admission means the same thing at City Hospital and at University Hospital.
•Because both hospitals define admission in the same way, they can be compared with each other on such things as number of admissions and percentage of occupancy.

Contents of data sets vary by what?

Their purpose

Data sets are not meant to limit what?

•The number of data elements that can be collected
•Most healthcare orgs collect additional data elements that have meaning for their specific administrative and clinical operations

Data sets may be formed for such activities as:

•Research, clinical trials, quality and safety improvement, reimbursement, accreditation, and exchanging clinical info
•The MEDPAR File, for example, allows researchers to track inpatient history and patterns/outcomes of care over time

What does the QDS act as, and what does it provide?

The QDS acts as a dictionary for quality measurement
•Providing a common framework for defining clinical data necessary to measure performance and accelerate improvement in patients' quality of care

Having defined data sets ensures the consistency of what?

Data collection and reporting

What do standardized data sets provide?

They provide information about the effectiveness of interventions and treatments for specific diseases, thereby improving the quality and safety of healthcare, maximizing the effectiveness of health promotions and care, minimizing the burden on those responsible for generating the data, and helping facilitate efficient reuse of data.

Types of data sets

Data sets Required or Recommended by the Federal Government:
Uniform Hospital Discharge Data Set

Data sets Required or Recommended by the Federal Government: A number of data reporting requirements come from federal initiatives, some are mandated through:

Published federal regulations, such as the Medicare prospective payment system (PPS), while some are only recommendations

Uniform Hospital Discharge Data Set

•In 1969, a conference on hospital discharge abstract systems was sponsored jointly by:•NCHS, the National Center for Health Services Research and Development, and
• Johns Hopkins University

What were the recommendations from the Uniform hospital discharge data set? What did these end up being called?

•Conference participants recommended that all short-term general hospitals in the United States collect a minimum set of patient-specific data elements
•Recommended that these data elements be included in all databases compiled from hospital discharge abstract systems
•They called the list of patient-specific data items the Uniform Hospital Discharge Data Set (UHDDS)

What was the purpose of the Uniform Hospital Discharge Data Set (UHDDS)? How are the UHDDS data collected?

•To list and define a set of common, uniform data elements
•The data elements are collected from the health records of every hospital inpatient and later abstracted from the health record and included in national databases

Every hospital "inpatient" refers to what?

A patient who is provided with room, board, and continuous general nursing services in an area of an acute care facility where patients generally stay at least overnight

In 1974, the federal government adopted the UHDDS as the standard for:

collecting data for the Medicare and Medicaid programs

What happened when the Prospective Payment Act was enacted in 1983?

•UHDDS definitions were incorporated into the rules and regulations for implementing diagnosis-related groups (DRGs)

What was a key component of the UHDDS definitions being incorporated ino the rules and regs for implementing diagnosis-related groups? What was the result?

•A key component was the incorporation of the definitions of principal diagnosis, principal procedure, and other significant procedures into the DRG algorithms.
•As a result, accurate DRG assignment depends on accurate selection and coding of the principal diagnosis and principal procedure and the appropriate sequencing of other significant diagnoses and procedures

Who revised the UHDDS?

•NCVHS revised the UHDDS in 1984
•The new UHDDS was adopted for all federal health programs in 1986
•The UHDDS has been revised several times since 1986. The current version includes the recommended data elements shown in figure 5.1.

What happens because UHDDS data definitions are a component of DRGs?

•Because UHDDS data definitions are a component of DRGs, short-term, general hospitals in the United States generally collect patient-specific data in the format recommended by the UHDDS.

Data elements listed in the most current version of the UHDDS:

1. Personal Identification
2. DOB
3. Sex
4. Race and ethnicity
5. Residence
6. Hospital ID (institution number)
7. Admission date
8. Type of admission
9. Discharge date
10. & 11. Physician identification (attending physician and operating physician)
12. Principal diagnosis
13. Other diagnoses
14. Qualifier for other diagnoses
15. External cause-of-injury code
16l Birth weight of neonate
17. Procedures and dates
18. Disposition of the patient
19. Patient's expected source of payment
20. Total charges

What is ambulatory care, and where is care given?

•Ambulatory care includes medical and surgical care provided to patients who depart from the facility on the same day they receive care.
•The care is provided in physicians' offices, medical clinics, same-day surgery centers, outpatient hospital clinics and diagnostic departments, emergency treatment centers, and hospital emergency departments.
•Patients who receive ambulatory care services in hospital-based clinics and departments are referred to as outpatients

what is included in the Uniform Ambulatory Care Data Set? What is the trend in hospitalization since the 1980s?

•Since the 1980s, the number and the length of inpatient hospitalizations have gone down dramatically
•At the same time, the number of healthcare procedures performed in ambulatory settings has gone up

What are the reasons for the trend of length of hospitalizations since the 1980s?

•Technological improvements in diagnostic and therapeutic procedures and the development of short-acting anesthetics have made it possible to perform many medical and surgical procedures in ambulatory facilities.
•Surgical procedures that once required inpatient hospitalization and long recovery periods now are being performed in same-day surgery centers
•Third-party payers have extended coverage to include most procedures performed on an outpatient basis
•The Medicare prospective payment system limits reimbursement for inpatient care and, in effect, encourages the use of ambulatory and/or outpatient care as an alternative to more costly inpatient services

What do ambulatory care orgs depend on, like hospitals? What was needed as a result?

•Having accurate data and information
•A standardized data set to guide the content and structure of ambulatory health records and data collection systems in ambulatory care was needed

What did NCVHS approve in 1989?

•The Uniform Ambulatory Care Data Set (UACDS)
•The committee recommended its use in every facility where ambulatory care is delivered

Several of the data elements that make up the UACDS are similar to those used in the UHDDS. Why is it easier this way? Give an example:

•For example, the UACDS data elements that describe the personal identifier, residence, date of birth, gender, and race/ethnicity of the patient are the same as the definitions in the UHDDS.
•The reason for keeping the same demographic data elements is to make it easier to compare data for inpatients and ambulatory patients in the same facility.

What elements does the UACDS include specific to ambulatory care? Why are these needed?

•The reason for the encounter with the healthcare provider
•Additionally, it includes optional data elements to describe the patient's living arrangements and marital status
•These data elements (shown in figure 5.2) are unique to the UACDS
•Ambulatory care practitioners need information about the living conditions of their patients because patients and their families often need to manage at-home nursing care (such as activity restrictions after a surgical procedure). Hospital staff members provide such nursing services in acute care settings

Figure 5.2 UACDS data elements:

1. Provider identification, address, type of practice
2. Place of encounter
3. Reason for encounter
4. Diagnostic services
5. Problem, diagnosis, or assessment
6. Therapeutic services
7. Preventative services
8. Disposition

What is the goal of UACDS?

•To improve data comparison in ambulatory and outpatient care settings.
•Provides uniform definitions that help providers analyze patterns of care
•The data elements in the UACDS are those most likely to be needed by a variety of users

How do UHDDS and UACDS differ?

•Unlike the UHDDS, the UACDS has not been incorporated into federal regulations.
•Therefore, it is a recommended, rather than a required, data set.
•In practical terms, it has been subsumed by other data definition efforts, most notably the core data elements recommended as part of the NHIN

Uniform data collection is also important to what other kind of care?

Long-term care

Long-term care incorporates and provides:

•The healthcare services provided in residential facilities for individuals who are unable to live independently because of a chronic illness or disability
•Long-term care facilities also provide dietary and social services as well as housing and nursing care

To participate in the Medicare and Medicaid programs, long-term care facilities must develop what?

¶A comprehensive functional assessment for every resident
•From this assessment, a nursing home resident's plan of care is developed

Minimum Data Set Version 2.0 (MDS 2.0):

•A federally mandated standard assessment form that Medicare- and/or Medicaid-certified nursing facilities must use to collect demographic and clinical data on nursing home residents
•Consists of a core set of screening and assessment elements based on common definitions
•To meet federal requirements, long-term care facilities must complete an MDS for every resident at the time of admission and at designated reassessment points throughout the resident's stay

What is the difference between the MDS and other data sets?

•The MDS uses some of the same data elements and definitions used in other data sets. •However, it is far more extensive and includes more clinical data than either the UHDDS or the UACDS
•The data collected via the MDS are used to develop care plans for residents and to document placement at the appropriate level of care

How does the MDS organize data?

•The MDS organizes data according to 20 main categories
•Each category includes a structured list of choices and responses
•The use of structured lists automatically standardizes the data that are collected

The major categories of data collected in the MDS include:

1. Demographic information
2. Identification and background information
3. Cognitive patterns
4. Communication/hearing patterns
5. Vision patterns
6. Mood and behavior patterns
7. Psychosocial well-being
8. Physical functioning and structural problems
9. Continence in past 14 days
10. Disease diagnoses
11. Health conditions
12. Oral/nutritional status
13. Oral/dental status
14. Skin condition
15. Activity pursuit patterns
16. Medications
17. Special treatments and procedures
18. Discharge potential and overall status
19. Assessment information
20. Therapy supplement for Medicare PPS

What is data collected by the MDS used for?

•The data collected by the MDS are used to develop a resident assessment protocol (RAP) summary for each resident
•The MDS provides a structured way to organize resident information and develop a resident care plan
•Problems identified through the assessment process are documented and a RAP is triggered

For each triggered resident assessment protocol (RAP), the facility must describe the following factors:

•Nature of the condition (may include presence or lack of objective data and subjective complaints)
•Complications and risk factors that affect the decision to proceed to care planning
•Factors that must be considered in developing individualized care plan interventions
•Need for referrals/further evaluation by appropriate healthcare professionals

What do nursing home personnel use data from the MDS and RAP for?

To plan, carry out, and assess the care given to individual residents

Other settings, such as rehabilitation and post-acute care:

Are considering versions of the MDS for use in patient assessment, but to date none has been implemented

Who was responsible for developing MDS Version 3.0?

•The Department of Health and Human Services (HHS) has developed MDS Version 3.0.
•The date for implementation is October 1, 2010

Because the MDS is used nationwide to collect data about residents in long-term care facilities, the data can and will be used as a basis for what?

•The data can and will be used as a basis for identifying and assessing resident safety and quality improvement activities in nursing homes
•For example, MDS data can give valuable information about the incidence of falls and their impact on the care of nursing home residents
•From those data, prevention measures can be developed and implemented to address a common and significant problem in elderly care

The Outcomes and Assessment Information Set (OASIS-C)

•Is a standardized data set designed to gather data about Medicare beneficiaries who are receiving services from a home health agency. •OASIS-C includes a set of core data items that are collected on all adult home health patients. •The data are used in measuring patient outcomes to assess the quality of home healthcare services
•Under the prospective payment program for home health, OASIS-C data are used as the basis of reimbursement for home health services

The OASIS-C data set became effective what date? What does the OASIS-C include? How many data elements are contained?

•January 1, 2010
•OASIS-C includes process items that support measurement of evidence-based practices across the post-acute care spectrum that have been shown to prevent exacerbation of serious conditions, can improve care received by individual patients, and can provide guidance to agencies on how to improve care and avoid adverse events
•OASIS-C contains more than 30 new data elements

OASIS-C data are grouped into the following categories:

• Patient Tracking Items
• Clinical Record Items
• Patient History and Diagnoses
• Living Arrangements
• Sensory Status
• Integumentary Status
• Respiratory Status
• Cardiac Status
• Elimination Status
• Neuro/Emotional/Behavioral Status
• Activities of Daily Living (ADLs)/Instrumental Activities of Daily Living (IADLs)
• Medications
• Care Management
• Therapy Need and Plan of Care
• Emergent Care
• Data Collected at Transfer/Discharge

What is data collected through OASIS-C used to assess?

•The patient's ability to be discharged or transferred from home care services.
•They also are used to evaluate the quality and outcome of services given to the patient

The following three initiatives do not represent the development and dissemination of information standards, but each does collect and use standardized data in assessing utilization, quality, and cost of healthcare for selected populations; so they are important data sets to the healthcare industry:

•Health Plan Employer Data and Information Set •Data Elements for Emergency Departments
•Joint Commission Core Measures for ORYX

The Health Plan Employer Data and Information Set (HEDIS)

•Is sponsored by the National Committee for Quality Assurance (NCQA)
•HEDIS is a set of standard performance measures designed to provide healthcare purchasers and consumers with the information they need to compare the performance of managed healthcare plans

What is HEDIS designed to collect?

•HEDIS is designed to collect administrative, claims, and health record review data
•It collects standardized data about specific health-related conditions or issues so that the success of various treatment plans can be assessed and compared

What does HEDIS data form the basis for?

Forms the basis for performance improvement (PI) efforts for health plans
•Also used to develop physician profiles: (The goal of physician profiling is to positively influence physician practice patterns)

HEDIS contains how many measures related to conditions? From where are the data elements abstracted? What are health record data combined with?

•HEDIS contains more than 50 measures related to conditions such as heart disease, cancer, diabetes, asthma, chlamydia infection, smoking cessation, and menopause counseling
•It includes data related to patient outcomes and data about the treatment process used by the clinician in treating the patient.
•Standardized HEDIS data elements are abstracted from health records in clinics and hospitals
•The health record data are combined with enrollment and claims data and analyzed according to HEDIS specifications

An example of a focus area for HEDIS is diabetes care and treatment. Other examples of HEDIS clinical measures include:

•Adolescent immunizations
•Smoking cessation programs
•Antidepressant medication management
•Breast cancer screening
•Cholesterol screening after a heart attack
•Prenatal care during the first trimester

Why would health plans often release data from HEDIS studies publicly? How are results compared?

•To document substantial positive effects on the health of their clients
•Results are compared over time and with data from other sources
•From the data, health plans determine opportunities for PI and develop potential interventions

HEDIS is an example of what kind of data collection tool? What does it illustrate the need for?

•HEDIS is an example of a population-based data collection tool
•It illustrates the need for developing standardized data definitions and uniform collection methods
•It also emphasizes the importance of data quality management

Data Elements for Emergency Department Systems (DEEDS):

•A data set published in 1997 by the Centers for Disease Control and Prevention (CDC) through its National Center for Injury Prevention and Control (NCIPC)
•The purpose of this data set is to support the uniform collection of data in hospital-based emergency departments and to reduce incompatibilities in emergency department records

What does DEEDS recommend in terms of data elements in hospitals? What are its recommendations?

•DEEDS recommends the collection of 156 data elements in hospitals that offer emergency care services
•As with the UHDDS and UACDS, this data set contains recommendations on both the content and the structure of the data elements to be collected

The data are organized into the following eight sections:

•Patient identification data
•Facility and practitioner identification data
•Emergency department payment data
•Emergency department arrival and first-assessment data
•Emergency department history and physical examination data
•Emergency department procedure and result data
•Emergency department medication data
•Emergency department disposition and diagnosis data

DEEDS incorporates national standards for?

Electronic data interchange (EDI), so its implementation in an EHR system can make possible communication and integration with other information systems (NCIPC 2006)

Joint Commission Core Measures for ORYX:

•The Joint Commission (JC) is one of the largest users of healthcare data and information
•Primary function is the accreditation of hospitals and other healthcare organizations
•In 1997, the JC introduced the ORYX initiative to integrate outcomes data and other performance measurement data into its accreditation processes. (The initiative was named ORYX after an African animal that can be thought of as a different kind of zebra.)
•The goal of the initiative is to promote a comprehensive, continuous, data-driven accreditation process for healthcare facilities

What does the ORYX initiative utilize to improve the safety and quality of healthcare?

The ORYX initiative uses nationally standardized performance measures to improve the safety and quality of healthcare

What are its program objectives?

The program's objectives include:
•Establishing a national comparative database to support benchmarking, health services research, and internal PI activities
•Fostering standardization of performance measures
•Encouraging the use of evidence-based treatment protocols

What was the goal of the ORYX initiative? What are the core measures based on?

•To integrate outcomes and other performance measures into the accreditation process through data collection about specific core measures (Joint Commission 2009)
•The core measures are based on selected diagnoses/conditions such as diabetes mellitus, the outcomes of which can be improved by standardizing care
•They include the minimum number of data elements needed to provide an accurate and reliable measure of performance
•Core measures rely on data elements that are readily available or already collected

Data Sets for a Nationwide Health Information Network (NHIN):

•The National Health Information Network (NHIN) is a network of networks
•Envisioned by the government
•Where health information may be exchanged securely and seamlessly across diverse entities, within communities, and across the country
•This initiative is part of a strategy intended to provide a set of harmonized standards-based specifications for the exchange of health information

The NHIN was created on the following core set of capabilities (NHIN Today n.d.):

•Ability to find and retrieve healthcare information within and between health information exchanges and other organizations
•Ability to deliver a summarized patient record to support patient care and to support the patient's health
•Ability to support consumer preferences regarding the exchange of his or her information, including the ability to choose not to participate in the NHIN
•Support secure information exchange
•Support of a common trust agreement that establishes the obligations and assurances to which all NHIN participants agree
•Ability to match patients to their data without a national patient identifier
•Support of harmonized standards, which have been developed by voluntary consensus standards bodies for exchange of health information among all such entities and networks

NHIN Dimensions and Core Data Elements:

•To support the development of networked health information systems, NHIN defines three dimensions of the infrastructure that provide a means for conceptualizing the capture, storage, communication, processing, and presentation of information for each group of information users
•A set of core data elements has been developed for each dimension as part of the NCVHS report titled Toward a National Health Information Infrastructure (NCVHS 2000).

The three NHIN dimensions:

•Personal health dimension
•Healthcare provider dimension
•Population health dimension

(One of three NHIN dimensions) Personal health dimension:

•Core content of the personal health dimension will be controlled by the individual in both the initial input of data and the ability to edit personal data
•Individuals will select data elements that are relevant to their specific age, gender, health history, health and wellness concerns, and other factors
•The core content in table 5.1 represents a minimum data set
•The intent of NHIN is to develop standards for a personal health record and a data dictionary that supports a consistent format that will allow healthcare providers to access the data as needed and authorized by the individual

(One of three NHIN dimensions) Healthcare provider dimension (HPD):

The HPD includes:
•Information captured during the patient care process and concurrently integrates it with clinical guidelines, protocols, and selected information the provider is authorized to access from the personal health record, as well as information from the population health dimension that is relevant to the patient's care
•The HPD would be useful to providers in any and all care settings

(One of three NHIN dimensions) Population health dimension:

•Acknowledges the importance of population-based health data and resources that are necessary to improve public health
•These data will help public health professionals to identify public health threats, assess population health, focus programs and policies on well-defined health problems, inform and educate individuals about health issues, evaluate programs and services, conduct research to address health issues, and perform other public health services
•In subsequent publications this is also referred to as the population health dimension

Core content of the personal health dimension - Personal health record:

•Personal identification information
•Emergency contact information
•Lifetime health history; summary of caregiver records from all sources of care, including immunizations, allergies, family history, occupational history, environmental exposures, social history, medical history, treatments procedures, medication history, outcomes
•Lab results, for example, EKGs; or links to results, for example, MRI results at a radiology department data warehouse, digital images of biopsy slides, or digital video of coronary angiography
•Emergency care information, for example, allergies, current medications, medical/surgical history summary
•Provider identification and contact information
•Treatment plans and instructions
•Health risk factor profile, recommended clinical preventative services, and results of those services
•Health insurance coverage information

Core content of the personal health dimension - Other Elements:

•Correspondence: records of patient-provider communication, edits made to PHR, or concerns about accuracy of information in health care provider medical records
•Instructions about access by other persons and institutions
•Audit log of individuals/institutions who access electronic records
•Self-care trackers: nutrition, physical activity, medications, dosage schedules
•Personal library of quality health information resources
•Healthcare proxies, living wills, and durable power of attorney for health care

Core content of the personal health dimension - Elements from the Community Health Dimension:

•Local public health contact information
•Local healthcare services (for example, walk-in clinics)
•Environmental measures and alerts pertinent to an individual's home, neighborhood, school, and workplace

Core content of the healthcare provider dimension - Patient Record Elements:

•Personal identification information
•Sociodemographic identifiers (gender, birthday, age, race/ethnicity, marital status, living arrangements, education level, occupation)
•Health insurance information (including covered benefits)
•Legal consents or permissions
•Referral information
•Correspondence
•Patient history information (may include longitudinal history from PHD, immunizations, allergies, current medications)
•Stated reason for visit
•External causes of injury/illness

Core content of the healthcare provider dimension - Patient Record Elements:

•Symptoms
•Physical exams
•Assessment of patient signs and symptoms
•Diagnoses
•Laboratory, radiology, and pharmacy orders
•Laboratory results
•Radiological images and interpretations
•Record of alerts, warnings, and reminders
•Operative reports
•Vital signs from ICU
•Vital signs from PHD
•Treatment plans and instructions
•Progress notes
•Functional status
•Discharge summaries
•Instructions about access
•Audit log of individuals who accessed patient record
•Patient amendments to patient record
•Provider notes, such as knowledge of patient, patient-provider interactions, patient's access to services

Core content of the healthcare provider dimension - Other Elements That Support Clinical Practice:

•Protocols, practice guidelines
•Clinical decision-support programs
•Referral history

Core content of the healthcare provider dimension - Elements from the Community Health Dimension:

Depending on the patient, the HCPD would include additional contextual information necessary for understanding, treating, and planning the care of the patient:
•Aggregate data on the health care of community members
•Community attributes affecting health (for example, economic status and population age
•Community health resources (for example, home health services)
•Community health (for example, possible environmental hazards at home, work, school, or in the community at large)

Core content of the population health dimension - Public Health Data:

•Infant mortality, immunization levels, and communicable disease rates
•Environmental, social, and economic conditions
•Measures related to public health infrastructure, individual healthcare providers, and healthcare institutions
•Other summary measures of community health
•Registries
•Disease surveillance systems
•Survey data
•Data on Healthy People objectives and Leading Health indicators

Core content of the population health dimension - Information from the HCPD (with personally identifiable information removed except under legally established public health protocols and strict security):

•Health status and outcomes, health events, health risks, health behaviors, and other individual characteristics
•Healthcare utilization and access, health insurance status
•Health care of community members

Core content of the population health dimension - Other Elements:

•Directories of community organizations and services
•Planning, evaluation, and policy documents
•Compendia of laws and regulations
•Material to support public education campaigns
•Practice guidelines and training materials for public health officials

One of the keys to interoperable electronic information exchange is:

•Having defined core data sets
•The continuity of care record core data set is one example
•A document created by the Core Services Content Working Group of the NHIN Cooperative addressed HITSP's Component 32 (C32), a standard that addresses how to exchange continuity of care information (NHIN Resources n.d.)
•HITSP is charged with the identification and harmonization of data and technical standards for healthcare

Continuity of care record core data set:

•Patient administrative and clinical data
•Basic information about the patient's payer
•Advance directives
•Patient's sources of support
•Patient's current functional status
•Problems
•Family history
•Social history
•Alerts
•Medications (Johns 216)
•Medical devices or equipment need by the patient
•Immunization history
•Vital signs (as appropriate)
•Results of laboratory, diagnostic, and therapeutic results
• Diagnostic and therapeutic procedures
• Encounters
• Plan of care
• Healthcare providers

Standards for Electronic Data and Electronic Data Interchange: What were the original uniform data sets such as the UHDDS and the UACDS were created for?

•They were created for use in paper-based (manual) health record systems
•They were not designed to accommodate the data needs of the current healthcare delivery system or the demands of EHRs and clinical information systems

The NHIN initiative has clearly identified what need?

•The need to develop standards that allow data to be easily, accurately, and securely communicated electronically among various computer systems
•This is referred to as interoperability
•Without standards for interoperability, EHRs and the NHIN will not realize their full benefits

Which types of standards are being developed to support the EHR and the NHIN vision?

•Some involve defining data structure and content
•Others specify technical approaches for transmitting data
•Others provide rules for protecting the privacy and security of data

HITSP, who is supported financially by the Office of the National Coordinator for Health Information Technology (ONC), assists in the development of the NHIN through:

•Their harmonization efforts to manage information in standardized processes that enable data sharing

Definition of Data Standard for Electronic Data Exchange:

•Data standards provide the ability to record a certain data item in accordance with the agreed upon standard
•Data content standards are "clear guidelines for the acceptable values for specified data fields"
•Data exchange standards are protocols that help ensure that data transmitted from one system to another remain comparable

Healthcare data exchange standards supply the specifications for:

•The format of data exchanges, thereby providing the ability to send and receive medical and administrative data in an understandable and usable manner across information systems

Transmission standards are also referred to as? What do they support and indicate?

•Communication, messaging, and transaction standards
•Support the uniform format and sequence of data during transmission from one healthcare entity to another
•These standards would indicate where each data element occurs in the electronic file

What was one of the purposes of HIPAA's Administrative Simplification rules?

•To standardize information exchange and in August, 2000, HHS published regulations for electronic transactions
•These regulations apply to transactions that occur among healthcare providers and healthcare plans and payers (Rode 2001)

What is the long-term goal of the transaction standards? How will this be done?

•The long-term goal of the transaction standards is to allow providers and plans or payers to seamlessly transfer data back and forth with little intervention
•To do this, HHS adopted the electronic transaction standards of ASC X12 Insurance Subcommittee (Accredited Standards Committee Health Care Task group [X12N]). The standards adopted for EDI are called ANSI ASC X12N

HIPAA standards also include code sets standards for:

The electronic exchange of health-related information.

To illustrate how the adoption and utilization of standards for data representation and data exchange facilitates billing functions, what should be considered?

The codes sets are data standards used to identify specific data elements such as the diagnosis on a claim should be considered.

A data set on the claim form is made up of? What standard is used to send diagnosis, etc. electronically?

•The compendium of data elements on the claim form make up a data set
•In order to send the diagnosis and other items that make up the data set electronically, the healthcare provider uses the ASC X12N 837 messaging standard
•The 837 specifies the format for each data element. For example, one specification for the format of the diagnosis would be the diagnosis codes have a maximum size of five (5) characters

When was a new version of the standard for electronic healthcare transactions approved?

•A new version of the standard for electronic healthcare transactions (Version 5010 of the X12 standard) was approved in 2009 for implementation by 2012
•This new version is essential to the use of ICD-10-CM and ICD-10-PCS codes that are slated for implementation in 2013

Healthcare organizations must integrate data that originate from:

•Various databases within facilities as well as in databases outside the facility
•They also must be able to respond to requests to transfer data to other facilities, payers, accrediting and regulating agencies, quality improvement organizations, and other information users
•These goals can only be accomplished when every database system is either operating on the same platform or using common standards

Healthcare information standards describe accepted methods for what?

Collecting, maintaining, and/or transferring healthcare data among computer systems

Healthcare information standards are designed to provide a common language that makes it easy to:

•Exchange info
•Share info
•Communicate w/in and across disciplines and settings
•Integrate disparate data systems
•Compare info at a regional, national, and international level
•Link data in a secure environment

Having the ability to exchange, share, communicate, integrate, compare, and link data is important to healthcare delivery; and make possible important activities such as:

•Disease surveillance
•Health and healthcare population monitoring
•Decision making and policy development

The long-term vision of data exchange standards is to:

•Enhance the comparability, quality, integrity, and utility of health information from a wide variety of public sources through uniform data policies and standards

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