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Data governance: it’s not what you may think it is

In today’s healthcare environment, the subject of data governance is at the top of the list for hospital executives. Within the framework of strategic planning, quality, big data and regulation, your data reflects everything you do: patient care, cost practices and outcomes. In fact, the very sustainability of your organization relies on quality data. Dr. Elliot King, Department of Communication Chair, Loyola University, MD, makes the powerful point that “Data is an organization’s most valuable asset.

Data governance is a proactive process that provides the necessary framework to ensure data can be trusted and that there is clear accountability in place should an adverse event occur as an outcome of poor data quality. This structure is vital in managing the use, monitoring, maintenance and protection of an organization’s data. Without it, you may be missing crucial information needed to align clinical and business goals while reducing risk.

Data governance is not the routine maintenance of your data with oversight by the Information Services/Technology department. Data governance is a commitment organizationally to a process that manages the integrity of data. In turn, there is increased consistency and confidence in clinical and business decision making. There is better organizational planning, data transparency and optimized staff effectiveness through less re-work and decreased risk of regulatory fines.

In 2001, Congress passed The Data Quality Act (also referred to as the Information Quality Act). Embedded within a two-sentence rider was the requirement that the information you provide to any Federal agency must be consistent, of high quality and have data integrity. In other words, you are required by law to provide quality data.

Consider these notable comments:   

  • When asked about the biggest challenges and opportunities associated with the significant influx of data in healthcare, Anil Jain, MD, Vice President with (IBM) Watson Health responded: “The biggest challenges relate to the interoperability of data and then standardizing and cleansing the data.” “Just because you can get the data, that does not mean you can make sense of it.”
  • “Accurately measuring costs and outcomes is the single most powerful lever we have today for transforming the economics of health care” Dr. Robert Kaplan, Emeritus Professor of Leadership Development, Harvard Business School

The American Health Information Management Association (AHIMA) has been a leading authority on health information management since 1928 and was one of four parties responsible for ICD-10 Coding Guidelines as well as a contributor to the AMA’s CPT terminology. Some important AHIMA tenets are that Information Governance (IG) should ensure information is trustworthy, actionable, and aligned with organizational strategy. It is needed for all information, whether it is in electronic or paper form. EHRs are assets. Like other critical assets—people, capital, inventory, etc.—information is a strategic asset that requires high-level oversight in order to effectively use it for organizational decision-making, performance improvement, cost management, and risk mitigation. Information Governance requires a system-wide, multidisciplinary team (clinical, finance, decision support, materials management, risk management, pharmacy & IT) with executive-level sponsorship.  

How “Bad Data” Can Increase Risk

The Controlled Risk Insurance Company (CRICO) is the patient safety and medical malpractice insurer for the Harvard medical community. The Massachusetts-based company has expanded its proprietary coding system to capture EHR-related problems that have contributed to patient harm, and to guide the hospitals, physicians, and other providers it serves toward addressing vulnerabilities in their systems.

Results from a 2013 analysis of 147 medical malpractice cases were found to have an EHR-related contributing factor:

Top Issues in Claims w/EHR factors % Cases
Incorrect Information in the EHR 20%
Hybrid health records/EHR Conversion issues 16%
System failure – electronic routing of data 12%
System failure – unable to access data 10%
Pre-populating/copy & paste 10%
Failure of system design to meet the need 9%
EHR user training/education 7%
Lack of integration/incompatible systems 7%
EHR user error (other than data entry) 7%

These errors can range from faulty data entry (inches vs. centimeters can distort BMI calculation), unexpected automatic data conversions (2.5 becomes 25 impacting medication error), accessing wrong patient file or field, and repeated errors (mistakes that persist in patient records for years). Which EHR vulnerabilities are most troubling? CRICO’s early analysis reveals that incorrect information in the EHR was a factor in 20% of the 147 medical error cases reviewed. Half of the cases resulted in severe injury with $61 million in direct payments and legal expenses. This risk can and should be eliminated.

How Good Data Goes Bad

EHR system conversions are one of the most prevalent sources of data issues. Whenever data from different sources (multiple hospitals, physician office, and outpatient clinics) is merged, the result can be inconsistency, duplication and questionable validity. Data may not be compatible when different systems are linked/interfaced together. Additionally, formal data standards can be old or not consistently applied over time.  Without standards, you may end up with data that can’t be used for accurate comparisons or other analytics.

Deferring ownership of clinical data to IT is all too common; everybody uses data but nobody really knows who “owns” it. Your IT department needs to know how to resolve technical issues with data; don’t assume they know what the content should be. Data content issues fall into the overview of clinical and informatics staff, working hand in hand.

What is Good Data?

Your data must be available and easily accessible. This requires integration to enable all caregivers to see patient data in the right location at the right time while supporting patient care decisions and optimum utilization of resources.

You must have standardization as a bedrock of your data tables/files.

  • Any information that is recorded using free text is not reportable.  
  • Non-standardized procedures, for example, can result in duplicates or incorrect selection while documenting a patient’s surgical procedure. Procedures that cannot be tied to industry standards may introduce insufficient specificity.
  • A recent study published in the Journal of the American Medical Informatics Association found that a lack of standardization of observable markers of diabetes being collected in the EHR resulted in a significant variation from the standards created by the American Diabetes Association to diagnose the disease. The findings point to the need for standardization to avoid confusion among symptoms related to other conditions the patient may have.

Data must be complete. You must be able to show improved outcomes, regardless of the acuity mix of your patients. Data must be consistent. Necessary information is collected for all patients, all the time and data must be accurate.  A single source of truth ensures that each time a data element is used, it means the same thing everywhere it appears.

Introducing Data Governance

The most important point of data governance is to recognize that senior leadership and stakeholders must be engaged to ensure that your data meets the requirements of “good data;” not only within your EHR but also with every other system with which it interacts. Governance means putting a strategy and process in place for the proper proactive management of good data practices.

Some example considerations in the development of a successful strategy for the management of data are:

  • Put audit and validity checkpoints in place to keep your data accurate. Any interaction with humans will generate data errors – your aim is to identify and remediate as part of everyday activities across your hospital/health system.
  • Institute a schedule of routine audits of information that crosses from one system to another to find items that impact accuracy of cost and charge for supplies used during patient care.  Missing supply, implant or pharmacy charge coding and inaccurate mapping to codes can have a significant impact on revenue and case costing analytics.
  • Challenge the content of your reports. “Apples-to-apples” comparisons aren’t always what they seem to be. Do you collect data that does not result in action? If so, why are you collecting it? Can you see your data in real time to allow proactive action to mitigate unplanned barriers to efficiency?
  • Find any free text that can be converted to a standardized list of selections.
  • Review all of the lists of options selected by staff during the documentation process to search for duplicates, missing options and “home grown” areas that need to be updated to today’s clinical and regulatory standards.
  • Ensure that you are meeting all regulatory requirements by examining the data used to report to outside entities.

Introducing and establishing data governance is a challenging endeavor that takes discipline and time. Check out The American Health Management Association for more information.

What to Expect When You are Expecting to Convert Your EHR

In the current world of population health management and value-based reimbursement models, many health systems are embarking on the conversion of their EHR as a major goal in reaching full integration and the ability to analyze clinical and financial performance. An EHR conversion has 2 simultaneous tracks each requiring significant resources:

  1. Legacy system support
  2. Converting and implementing the new EHR

In spite of the best project planning, the preparatory work needed for the overall success of each track is often overlooked, especially in high cost/high revenue departments such as Surgical Services. These highly visible and costly projects must be managed in a way that reflects the focused scrutiny that perioperative and other critical patient care areas should receive.  In a recent survey reported in Healthcare IT News, “87% of financially struggling hospitals now regret changing their EHR systems.”  While there were several reasons cited for this regret, the ease of achieving “buy-in” of physicians and other clinicians and the impact on clinician ability to deliver hands-on care with the same effectiveness is worth noting because of the potential impact on operational efficiency once the conversion is completed.

There are still good reasons for hospitals to proceed with an EHR conversion, or, given the expense, to optimize an existing system. However, keeping the potential regret in mind, it has been our experience, that recognizing the following failure and corresponding solution will serve you well as you undertake your conversion effort.

The “BIG MISTAKE”: Failure to Optimize the “Gap” Period Between the Decision to Convert and Software Vendor Kick-off

Project Managers often assume that the optimization work specific to perioperative services, as well as critical standards and integration decisions, can be done as part of the design and build portion of the conversion work plan often without appropriate multi-disciplinary collaboration (i.e. Anesthesia, IT, Finance, Materials Management, Pharmacy, Radiology, Physician offices, etc.). This can lead to a new EHR that is not optimized and incorporates incomplete or inaccurate data, directly impacting your ability to improve upon your prior system experience and to derive/extract the level of analytic data required. Even worse is the convergence of limited resources and aggressive vendor timelines that often result in the decision to simply move legacy data with the intention of “fixing” it later.

The SOLUTION: Pre-Project Optimization Work & Decisions

By knowing what to expect in advance and allowing the time for key decisions, your pre-project optimization work will allow you to walk into the EHR kick-off meeting prepared to support your existing legacy system while focusing on the new system’s design and build.  The pre-project optimization phase is as critical to your success as the new system implementation phase and helps you stay on time and within budget.

A well facilitated pre-project optimization phase offers the opportunity to:

  • Ask the right questions to avoid common failure points in system conversions; define leading practices and understand the differences between your legacy system and the new EHR; find out what you don’t know.
  • Articulate the strategic, clinical, and financial goals of the EHR conversion.
  • Ensure that interdependencies among other departments, important to the strategic success of the OR, are included in decisions that are made in the early part of the overall conversion project.
  • Take a fresh look at industry standards for core data and practices needed to evaluate and achieve the right level of data granularity. As the significance of analytics continues to increase, standardized data is integral to making the best design decisions about how you will capture and analyze data as well as time to evaluate the impact on various types of staff.
  • Update or rework core data tables consistent with the structure of your new vendor system (is moving legacy data really the best decision?).
  • Understand the entire perioperative workflow from a patient-centric viewpoint and find opportunities to eliminate inefficiencies, redundancies, reduce cost, and improve patient care and the electronic documentation of that care.
  • Prepare for the variety of staff resources needed for the design, training, testing and roll-out of the new system while maintaining the same level of quality patient care; plan for “peak” periods of build activity (i.e. conversion of surgeon preference cards). Set your project team up for success by not underestimating the commitments needed for a project of this size and significance.
  • Prepare for the possible re-assignment of internal resources from maintaining your legacy system to new system activities (how and by whom will the legacy system be managed?); ensure a smooth cut-over from old to new systems.

Pre-Project Optimization and focused decisions on 6 core areas of master data will directly impact the perioperative continuum from accurate scheduling of cases to appropriate patient & room readiness to the effectiveness of supply chain to cost analysis to patient/clinician satisfaction. The level of advance effort and/or the decisions related to each core area may vary but they are equally important. They include:

  • Master Surgical Procedure file: this core file must be clinically discrete and impacts every other area of the department (accurate case scheduling estimates, pre-certification, clinical supply, equipment & instrumentation requirements, case documentation, case charges, payment delay/denial and reporting).
  • Supply Item Master file: this core file of supply item descriptions & associated critical reporting data must be up-to-date, with a standardized format that links the supply to your purchasing system (actual cost) and charge master (revenue). Every supply used in the perioperative department must be available for documentation in the patient’s record for real-time inventory control; maintenance is determined by system integration and/or interfaces.
  • Surgeon Preference Cards: these files (typically in the thousands) must be thoroughly updated for the top performers to reduce inventory, increase surgeon & staff satisfaction and improve patient care during the procedure (have the right items available at the right time with minimal returns because content is specific to a clinically accurate procedure); support ability to move from clinical preference to clinical acceptability through “apples-to-apples” comparison & contribution margin analysis.
  • Clinical Documentation: the need for “good data” is greatest in the capture of clinical patient care information as evidence of value based care. Review of current clinical documentation (surgeon, nursing, resident, and anesthesia) must occur in order to transition to effective design and consistent data collection. This must be achieved to ensure portability and accessibility of one of your organization’s most valuable assets.
  • Perioperative Throughput Efficiency: review of all real-time throughput metrics & introduction of industry standard time capture definitions will ensure that your system captures the right level of detail needed to make the best decisions for process improvements.
  • Critical Operational Reporting: “catalog” needed reports that must be converted on Day 1 of the new EHR to maintain operational management of the department; ensure future ability to produce actionable perioperative statistical, quality, financial and regulatory reports to include surgeon-procedure case costing, resource utilization, data integrity audits, and quality of care.

Changes in reimbursement and associated patient revenue combined with the significant cost outlay related to EHR conversion is dramatically impacting the financial bottom line of hospitals as recently noted in Becker’s Hospital Review. One hospital commented that they knew their “post implementation strategy will focus on clinical productivity and operational efficiencies to return to normalized operations by year end.” Shifting some of this effort upfront during a pre-optimization phase within perioperative services can help to mitigate the burden required to normalize operations after an implementation.

Keeping your staff successful in meeting all of the expectations of a new  EHR should be everyone’s common goal! Understanding the perioperative portion of patient care and the link to other departments and/or applications is a key determinant in achieving the return on investment expected for the new EHR vendor system. Ongoing financial sustainability requires having the data you need to improve the quality of care, patient/clinician satisfaction, and meet the needs of regulatory, cost, and quality reporting.