Meaningful Use Scholarly Project Synthesis Paper

SCHOLARLY PROJECT SYNTHESIS

Jennifer Dilly

Ferris State University

August 8, 2012

Abstract

The American Recovery and Reinvestment Act (ARRA) and its provision, the Health Information Technology for Economic and Clinical Health (HITECH) Act aim to address the use of technology for improving patient care. Using technology in a meaningful way that improves quality of care has been termed as Meaningful Use (MU). Facilities nationwide have the opportunity to earn financial incentives by proving their use of health information technology complies with MU criteria. Two quality measure sets, Stroke and Venous Thromboembolism (VTE), are part of the criteria required to comply with MU. This author describes a Scholarly Project conducted to evaluate compliance of Spectrum Health Zeeland Community Hospital with the measure sets. An overview of MU is provided, including criteria for attestation of compliance related to the quality measure sets, as well as the project’s goals, objectives, and activities. An analysis of adherence to professional performance and standards of practice related to the project’s implementation has been provided. Recommendations for future implementations and application of knowledge learned during the project are also included.

Keywords: Meaningful Use, quality measures, healthcare reform, nursing informatics

Meaningful Use Scholarly Project Synthesis Paper

The American Recovery and Reinvestment Act (ARRA) and its provision, the Health Information Technology for Economic and Clinical Health (HITECH) Act, were passed in 2009 (Furukawa & Poon, 2011). The HITECH Act addresses the need for hospitals to adopt health information technology and use it to improve health care delivery and quality of care, a term coined as Meaningful Use (MU) (Goldschmidt, 2012). As part of MU, hospitals are required to show how their adopted technology records and monitors certain points of patient care to earn financial incentives. There are multiple stages of MU with Stage 1 requiring the attestation of the capability to measure and report on different types of patient information including items such asvital signs, smoking status, medications, allergies, patient receipt of discharge instructions, recorded patient problem lists, and two sets of clinical quality measures (Benson, 2011). The two measure sets involve care surrounding stroke and venous thromboembolism (VTE) for various patient populations.

According to Furukawa and Poon (2011), since the passage of ARRA and HITECH Acts, many facilities have successfully attested to MU Stage 1. Some facilities, however, are still adopting technology and learning the requirementsfor MU including how to achieve the requirements and acquire the attached incentives. Spectrum Health Zeeland Community Hospital (SHZCH), a facility currently adopting new health information technology, is one of those facilities trying to learn how the MU criteria will be met. A Scholarly Project was conducted at SHZCH to help the executive team identify how the facility will meet requirements for MU specifically related to the Stroke and VTE measure sets. The project included identification of gaps in the adopted technology and requirements that may still presentafter the adoption, and what can be improved to close those gaps.

The intent of this paper is to present the outcomes of the Meaningful Use Scholarly Project conducted at SHZCH. A description of the project is providedincluding how the project was carried outand any issues encountered during the implementation. Personal and professional accountability practiced during the project is addressed as is a description surrounding the adherence to multiple standards expected from a Nursing Informatics Specialist (NIS). Issues related to compliance with the standards are included. A self-evaluation, evaluations from the preceptor for the project and from the presentation recipients is provided in summarized form. Recommendations related to the project have been made. Finally a description of the application of knowledge from theory, practice and research into the project is included.

Project Description

The goal of the Meaningful Use Scholarly Project was to investigate how the MU requirements, related to two of the required quality measure sets, Stroke and VTE, will be met for the facility, and present the information to SHZCH executive team. A Planning Guide with goals, objectives, activities and their timelines is provided in Appendix A. The goal, while seemingly simple, required a multifaceted base of knowledge. The executive team, a multidisciplinary team, required knowledge of not only the clinical requirements, but also technical and financial information surrounding the requirements.

Multiple objectives were set to meet the goal, providing succinct and precise information to the team. The first objective included obtaining and reviewing literature sources, systematic reviews, and other pertinent information from credible web sources and subject matter experts. All aspects of MU specific to hospital requirements were investigated including timelines and requirements to meet the immediate and future stages,the financial implications, as well as the technological advancements meant to help hospitals meet the requirements. Sources of information surrounding MU and quality metrics were not hard to find. Databases in the online library were searched for research and systematic reviews, there were multiple web sources to search including The Centers for Medicare and Medicaid Services (CMS), various nursing informatics sites, and other regulatory agency web sites, and a fair amount of information about how other hospitals are or have been preparing for MU was retrieved from the electronic health record (EHR) vendor’s web site and learning center. At one point there was almost too much information and therefore eliminating those sources that were not as succinct as others was necessary.

There were multiple opportunities to meet with subject matter experts in quality departments, product analysts, leads for the main campus’ MU project, and the Spectrum Health system’s Chief Medical Information Officer (CMIO). These experts were credible with providing information because they have recently prepared and attested to MU for their hospital, and in some cases, have worked on this type of readiness planning in other facilities as well. While literature sources provide a plethora of information, the first-hand knowledge learned from these contacts seemed to help the most.

The second objective included learning the documentation needed for the Stroke and VTE measure sets. Quality Net (2012) is CMS’s web site source for their various quality measure set information including all specifications for required documentation to meet each measure and was the primary source for working with the measure sets. As the measure sets are extensive, they needed to be identified and summarized in a succinct outline (Appendix B) including the creation of algorithms (Appendix C) for clear understanding of what documentation helps prove that quality care was given and each measure was met (Kallem, 2011). While the executive team may not need to understand all care points surrounding the measures, preparation to answer any question related to the measures was still necessary.

Surprisingly, outlining and summarization of the measures took a much longer period of time to complete. The VTE set was the first to be outlined and the original thought was since there were fewer measures, the time taken to do so would not take as long as the Stroke set. On the contrary, the VTE set was much lengthier and more complex because the patient populations were not straightforward. The populations were split into three different sub-populations, populations that included many types of patients making it difficult for caregivers to know which patients could be included. Immediately the importance of how the system monitors what patients may fall into this population became apparent.

The Stroke measure set outlining was not as lengthy as the VTE set, but the activity still took an extended period of time. At this point, the need to see how many patients for this facility would fall into this measure set became apparent as well. Although pulling data surrounding patients who may have fallen into the populations in past years was not on the original planning guide, time was taken to do so. The data pull revealed few patients may have been included in the measures had they been implemented in the past. As evidenced by the data pull, the care providers may not see these types of patients often. Care providers that may not have the chance to practice care for these types of patients often, may remember the standards of care the measure set is based on. A system built to guide caregivers in giving evidence-based care becomes important (Kallem, 2011).

Once the measure sets were understood, the learning of the Cerner EHR used to capture the documentation surrounding the measures was important. Learning the EHR included the basic documentation system and all other tools within the system used to capture and monitor the documentation. The learning took place by attendance in a fundamental course, by meeting with various data abstractors, conference calls and meetings with key quality and MU leads, review of Cerner products with system developers, review of Cerner products via web sources, and review of Power Plans that guide ordering of treatment within Cerner for patients included in the measure sets.

Attending the Cerner fundamental course gave a great overview of how and where nurses and physicians document and how orders are placed. Unfortunately, the greatest challenge in this project was that access to the build this facility is adopting was not granted. Not having access to the system to go back and review it after the measures were outlined hindered a detailed view of how the measures are captured as well as the completion of a subsequent objective (a full gap assessment). Other activities, such as meeting with data abstractors, however, facilitated some of the learning of other aspects of how the system guides or at least monitors the provision of care. For example, the abstractors were able to show how the system was set up to notify the caregivers of points of care within the measure set yet to be addressed. Caregivers could address the notification by selecting choices, set up in the system as drop down boxes, such as ‘yes’, ‘no’, ‘contraindicated’, or ‘no reason given’.

Learning the Cerner Lighthouse and eQuality check products helped with the understanding of how to monitor care for the included population. Searching for and reviewing information from the Cerner web site and learning center, UCern, helped with this learning. A representative from the Spectrum Health system provided a learning session for the Lighthouse product as well. After the learning session and the webinar for the eQuality product I was able to ascertain what functionality this facility will have in relation to monitoring the compliance with the measure sets.

The next objective was to perform a gap analysis, contained in Appendix D, between needed documentation for the measure sets realized by outlining the measures, and the actual capability of Cerner to guide caregivers in documenting necessary points of care. Performing the gap analysis helped identify further needs for compliance with the requirements for MU (VanAuken, Chrysler, Gricenko-Wells, & Simkin 2011). The first gap was clearly identified as an inability to view the full Cerner documentation system built specifically for the facility. The Cerner Lighthouse and eQuality check products, learned for the previous objective, provided the only view of how the documentation is captured and caregivers are notified that the measure is or is not met. Although some review was possible, without access to fully research and review the documentation system that draws data into the Lighthouse and eQuality check products, I was unable to fully ascertain whether the requirements for each measure’s data elements were present, whether the data elements were written in verbiage that helped pass the measure, and whether care givers could bypass necessary documentation to comply with each measure.

Meeting with data measure abstractors helped identify another gap including a minimal amount of hard stopsand an inability of the hard stops to actually help care providers be reminded or stopped when care is not documented adequately. An example includes one of the discharge summary screens for physicians. When a patient is discharged, this screen lists what measure set the patient is in and what measures should be complied with, and the physician is unable to move past this screen without answering. The physician is guided to answer whether a certain medication was given, however, the measure is not considered met unless there is clear record of administration in the medication administration record (Quality Net, 2012). Many times the data abstractors find that there is no record of administration and the measure set is then out of compliance (personal communication, N. Bowers, June 25, 2012).

Furthermore, there are many opportunities for care providers to free-text documentation into the system. There is also quite a bit of scanned-in documentation such as handwritten progress notes, hand written documentation completed in the emergency department, outside consultations and test results. The gap in this process is evident as, per Kathy Millard an analyst from Spectrum Health, free-text or scanned-in paper documentation does not draw into the quality monitoring products such as Lighthouse and eQuality Check (personal communication, July 17, 2012). Both of these products take data from the provided documentation in various parts of the system and notify caregivers whether the measure set has been met.

The Lighthouse and eQuality Check products could prove helpful for guiding care givers, except in cases in which the Quality Dashboards for Stroke and VTE patients are not initiated. Lack of initiation of these dashboards is the next gap identified. There are many timed measures in which care needs to have been given within a few hours or a few days of hospital arrival. If the correct dashboard is not initiated, care givers will not be provided with a way to monitor measure compliance and certain points of care could be missed. Also, if a patient was admitted for one diagnosis and has a stroke during the admission, care givers will also need to remember to initiate the dashboards. Failure to do this could allow for lack of compliance with the measures.

Finally, lack of education surrounding compliance with the measures, knowledge of MU requirements, and dashboard initiation is a gap as well. The question of who does the education and what it contains has been posed to nursing and physician education leads as well as nursing informatics staff. No answer regarding this has been received from the physician lead; however, staff from the Nursing Informatics department has stated that education will be provided during staff training on the new system. The Vice President of Physician Services has been notified regarding the physician responsibilities related the measures as well as the dashboard initiation.

The gap analysis led to the next objective of recommending improvement suggestions lending the hospital to be in complete compliance with MU requirements related to the measure sets. There were a total of five recommendations made. The first recommendation included obtaining access to the facility’s specific build. The recommendation was for the Quality department staff, staff with a highly invested interest in the quality measure outcomes, to not only learn the basics of the system, but also be able to search out the data points that matter in the Stroke and VTE measures. Kallem (2011) believes that knowing the measures’ intricacies is important, but understanding that the method for capturing data surrounding the measures in an EHR is different and detrimental to the measure outcomes. Allowing the Quality department staff to view how the system is set up will allow for further recommendations and ultimately better outcomes.

Secondly, access to the Computerized Physician Order Entry (CPOE) system built for the hospital is another recommendation. Many of the measures are dependent upon what the physician orders. While much of the care is directed by what is ordered through the Power Plans and measures are met by nurses documented administration of medication ordered through the Power Plans, physicians documentation of reason for the care also need to be included. For example, if a required medication is not ordered, physicians are expected to document the reason why. At this point, there has been no view of what guides physicians or reminds them to document those reasons. A view of the CPOE system may help identify what is set up to help with compliance with Stroke and VTE measures.

Third, confirming the MU educational plans for nurses and physicians in regards to dashboard initiation and documentation requirements is very important. The staff are currently learning the basic documentation system and will learn more department specific functions in subsequent courses. The leads for MU are aware that this facility has not yet implemented these measures and that the staff will need education surrounding them. There has been assurance that the training will take place within the department specific courses.