Aligning the Demands for Performance Data

by Crystal Kallem, RHIT, and David Gans, FACMPE


Healthcare organizations struggle to meet the increasing requests for performance measurement data. AHIMA and MGMA offer recommendations to drive much-needed change.


The healthcare industry is striving to improve quality of care and reduce ever-increasing costs of services. As the industry moves toward widespread adoption of electronic health records, interoperability, and value-based purchasing, it is vital to align the performance measurement reporting initiatives being implemented by government, employer groups, and health insurance payers. Disparate data collection and reporting requirements force healthcare organizations to prioritize resources as they strive to meet the overwhelming demands for data today.

AHIMA and the Medical Group Management Association (MGMA) have led an effort to frame the issues and outline recommendations that help the industry address the issue collaboratively.

Many Requests, Many Variations

Public and private organizations that request performance measurement data have different sets of requirements and specifications for reporting results. Healthcare organizations must assess each component of a measure’s requirements to ensure complete and accurate reporting.

The Challenge of Complying with Varying Requests

A large number of public and private organizations are demanding data from providers, and each requestor has its own set of requirements and specifications for supplying it. Healthcare organizations are tasked with assessing each component of a measure’s requirements to ensure that appropriate data are collected and reported accurately.

For example, a payer and an accrediting organization may each have a similar quality measure for diabetes, but they may have different criteria or data collection specifications. A healthcare organization must assess each measure’s numerator and denominator statements, data element and abstraction specifications, allowable data sources, data submission deadlines, analytic specifications, and other elements. The above figure “Many Requests, Many Variations” illustrates the multiple variables that cause organizations to struggle in meeting varied data collection and reporting requirements. 

Although health IT holds the promise to improve these types of inefficiencies, the current electronic environment requires that data be mapped from a healthcare organization’s internal systems to the various performance measurement data requirements. Not only do the data need to be mined from multiple electronic systems, but they must be formatted to comply with each requestor’s data submission formats and specifications. Careful attention must be dedicated to these details to obtain appropriate, quality information.

The issues surrounding data collection and reporting have persisted for several years. In September 2004, AHIMA and Barbara Siegel, then director of health information at Hackensack University Medical Center, testified before the National Committee on Vital and Health Statistics (NCVHS) work group on quality. Siegel, MS, RHIT, FAHIMA, articulated a wide range of challenges associated with quality measure data collection and reporting requirements. Her examples included the lack of qualified staff to support quality measurement reporting, the variations in quality measure definitions and outcomes, the incomparability of measurement results, and the lack of physician support due to variation in measurement methodologies.1

Three years later these issues remain the same, and the demands for data continue to increase. Siegel reports that Hackensack’s manual data collection case load has increased 30 percent since 2004, requiring the addition of two new full-time staff. In total, the organization has experienced a 72 percent increase in the financial resources required to support these increased demands for data.2

To address these challenges, AHIMA and MGMA collaborated with the Agency for Healthcare Research and Quality (AHRQ) to pinpoint the issues surrounding data collection and reporting and engage key leaders from across the industry to coordinate and initiate solutions to drive change.

To help frame the issues, AHRQ sponsored an AHIMA and MGMA task force charged with articulating the increasing challenges healthcare organizations face as they respond to data collection and reporting requirements. The challenges were categorized into the following areas:

  • Inefficiencies associated with performance measurement
  • Variations among performance measurement systems
  • Organizational and cultural issues
  • Technological barriers
  • Economic pressures
  • Competing priorities3

The Challenges of Data Collection and Reporting

To help frame the issues surrounding the collection and reporting of performance measure data, AHIMA and MGMA identified and organized six categories of challenges that healthcare organizations face.

Challenges

        Examples

Inefficiencies associated with performance measurement

  • Staff resource requirements for manual data collection or electronic data mapping
  • Concurrent versus retrospective data collection
  • Performance measurement metrics requiring subjective decisions during interpretation of compliance with metrics
  • Changes in data collection metrics require training, software updates, and changes to data collection forms
  • Performance measure specifications that don’t align with updated code sets
  • Limitations of code sets
  • Difficulties locating medical records for data abstraction

Variations among performance measurement systems

  • Measure specifications (inclusion and exclusion criteria)
  • Data element definitions and values
  • Data source requirements
  • Data submission requirements
  • Data validation requirements
  • Support for education and training
  • Performance measure maintenance and retirement
  • Sampling methodologies
  • Multiple, varied reporting deadlines

Organizational and cultural issues

  • Shortage of a trained work force
  • Absence of complete and reliable documentation in the medical record
  • Poor legibility of clinical documentation
  • Delays in documentation availability dictation or transcription processes
  • Lack of consistent policies for the use of secondary data
  • Conflicting organizational priorities
  • Lack of physician and stakeholder acceptance
  • Fear that voluntary performance measurement initiatives will become mandatory
  • Lack of communication among care settings

Technological
barriers

  • Multiple disparate systems and limited system interoperability
  • Lack of standardized data set for collection of performance measurement data in EHR systems
  • Absence of metadata standards
  • Lack of interoperability among care settings
  • Onerous costs associated with technology implementation and interfacing
  • Limited performance measurement capabilities within EHR systems

Economic pressures

  • Limited organizational resources to support performance measurement activities
  • Increased costs associated with performance measurement inconsistencies
  • Limited financial incentives to support performance measurement initiatives

Competing priorities

  • Need to prioritize state and local performance measurement mandates and payer and employer performance measurement initiatives, in addition to unaligned national initiatives
  • Absence of a national healthcare quality framework and lack of measurement selection standards that result in the absence of a national healthcare quality data set and report card*
*Institute of Medicine. Envisioning the National Health Care Quality Report. Washington, DC: National Academies Press, 2001.

These issues are elaborated through the examples given in the table above, “The Challenges of Data Collection and Reporting.”

Without broadly agreed-upon standards for performance measurement metrics, variations among performance measurement systems will continue to increase in scope and thus further enhance the burdens taxing healthcare organizations today.

The Need for Standards on Data Use and Content

The above issues need to be addressed to improve efficiency and reduce costs for the majority of organizations who are still manually collecting data for a wide variety of performance measurement initiatives. The lack of coherent policies and practices for the secondary data use impedes goals to improve our healthcare system.

Further inflating the problem is a lack of standards for terminology development and use of outdated classification systems. Terminologies and classifications form the information content of electronic health record systems and serve as the basis for performance measurement data collection. Effective and efficient performance measurement requires solid data standards, but with more than 20 comprehensive terminology and classification systems in use, the US struggles to develop, implement, and maintain these systems in a coordinated manner.4

A national framework for the secondary use of health data must be established and include a robust infrastructure of policies, standards, and best practices to facilitate the collection, storage, aggregation, linkage, and transmission of health data with appropriate protections.5

AHRQ acknowledged the need to address the issues surrounding data stewardship with a request for information released in summer 2007. The request sought input on the creation of a national health data stewardship entity.

AHRQ’s request describes a proposed mission for this public-private entity that would “set uniform operating rules and standards for sharing and aggregating public and private sector data on quality and efficiency; offer guidance on implementation of such national operating rules and standards; and provide a framework for collecting, aggregating and analyzing data, to afford means of more effective oversight of health care data analyses and reporting in the United States.” 6

The current prevalence of paper and electronic records in the industry will require the development of practical solutions today while setting a vision and plan as the adoption of electronic health record systems increases in the future. Data stewardship operating rules and requirements will help reduce cost, increase operational efficiency in the secondary data use life cycle, and improve the accuracy of measures and reports based on secondary data.7

Recommendations for Action

Taking into account the significance of the problem, AHIMA has partnered with MGMA to drive change. During testimony on June 19, 2007, before the NCVHS quality work group, AHIMA and MGMA outlined three specific recommendations for the healthcare industry—government, public and private institutions, payers, and professional organizations—to address collaboratively:

  • Form a public-private entity to oversee and evaluate policies and procedures for healthcare performance measurement. The formation of such an entity would provide a unified and coordinated approach to improve quality measurement design and provide clear and consistent guidance to healthcare providers regarding data collection and reporting requirements.
  • Provide funding to support research on the quality of data reported for performance measurement. Both administrative and clinical data quality should be assessed and compared to inform efforts aimed at standardizing data content for performance measurement initiatives.
  • Provide funding to support additional research on the costs associated with performance measurement data collection and reporting. Improvements in healthcare quality could result in billions of dollars of savings for the healthcare industry; however, under current financing systems these savings generally accrue to the payer, not to the providers who collect and report the data. Without adequate data to demonstrate the costs associated with these initiatives, healthcare providers must continue to prioritize their resources.8

What can individual healthcare professionals and providers do? They can:

  • Monitor the national quality enterprise to stay abreast of performance measurement initiatives and related changes
  • Support changes to performance metrics as measure sets are harmonized and enhanced
  • Implement procedures to ensure data are of high quality and available to support quality measurement and improvement, patient safety, population health, clinical research, and health information exchange
  • Share challenges and successes with regard to performance measurement data collection and reporting by identifying data and analytic variations, sharing best practices for mining data from existing electronic systems, and demanding data standards that support automated performance measurement in the future

Without question, the development, adoption, implementation, and maintenance of standards for performance measurement must be coordinated so that data can be repurposed for secondary uses. Healthcare professionals must be aware and knowledgeable of the issues surrounding disparate collection and reporting requirements to help promote change locally, ultimately leading to improvements in patient care.

Notes

  1. Rode, Dan, and Barbara Siegel. “Testimony of the American Health Information Management Association to the Workgroup on Quality of the National Committee on Vital and Health Statistics.” September 14, 2004. Washington, DC.
  2. Kallem, Crystal, David Gans, and Allison Viola. “Burden of Data Collection.” Testimony to the National Committee on Vital and Health Statistics Work Group on Quality. June 19, 2007. Washington, DC. Available online at www.ncvhs.hhs.gov/070619qag.htm.
  3. Agency for Healthcare Research and Quality. “Collecting and Reporting Data for Performance Measurement: Moving toward Alignment.” Report of proceedings from the AHRQ Conference on Health Care Data Collection and Reporting. November 2006. Chicago, IL. 
  4. AHIMA and American Medical Informatics Association. “Healthcare Terminologies and Classifications: An Action Agenda for the United States.” 2006. Available online at www.ahima.org/perspectives.
  5. Safran, Charles, et al. “Toward a National Framework for the Secondary Use of Health Data.” September 2006. American Medical Informatics Association. Available online at www.amia.org/inside/initiatives/healthdata/2006.
  6. “National Health Data Stewardship.” Federal Register 72, no. 106 (June 4, 2007): 30803–05. Available online at www.access.gpo.gov/su_docs/fedreg/a070604c.html.
  7. Mon, Donald T. “Development of a National Health Data Stewardship Entity: Response to Request for Information.” August 3, 2007. AHIMA.
  8. Kallem, Crystal, David Gans, and Allison Viola. “Framing the Testimony: Burden of Data Collection.” Testimony to the National Committee on Vital and Health Statistics Work Group on Quality. June 19, 2007. Washington, DC. Available online at www.ncvhs.hhs.gov/070619p1.pdf.

Crystal Kallem (crystal.kallem@ahima.org) is a director of practice leadership at AHIMA. David Gans (dng@mgma.com) is vice president of practice management resources at the Medical Group Management Association.


Article citation:
Kallem, Crystal; Gans, David N.. "Aligning the Demands for Performance Data" Journal of AHIMA 78, no.10 (November 2007): 56-60.