HIT Working Group Conference Call – March 8, 2013

National Kidney Disease Education Program (NKDEP) Health Information Technology Working Group (HIT WG) Meeting


Uptal D. Patel, MD; Andrew Narva, MD, FACP, FASN; Eileen Newman, MS, RD; Patrick Archdeacon, Theresa Cullen, MD, MS; MD; Paul Drawz, MD; Kensaku Kawamoto, MD; Neil R. Powe, MD, MPH, MBA; Thomas Sequist, MD; Kimberly Smith, MD, MS

Meeting Summary

Welcome, Uptal D. Patel, MD 
Dr. Patel welcomed members and thanked them for their attendance and their feedback on the proposed action plan.

Partnership with Pharmacy Working Group on e-Prescriptions Effort, Uptal D. Patel, MD Dr. Patel outlined the effort to include estimated glomerular filtration rate (eGFR) in e-prescriptions, which will be pursued in collaboration with NKDEP’s Pharmacy Working Group (PhWG). The PhWG includes community and academic pharmacists and is focused on supporting medical therapy management and professional education for pharmacists around chronic kidney disease (CKD), in addition to the e-prescription effort. The PhWG is working to identify and engage a partner to pilot test inclusion of eGFR in e-prescriptions as a key next step. This may help identify both positive and negative impacts that may not be foreseen. The HITWG will be integral to determining technical issues regarding inclusion of eGFR in e-prescriptions.

In discussing the e-prescription effort, it was suggested that the effort be expanded to include two-way communication—not only from physician to pharmacist (e.g., eGFR) but also from pharmacist to physician (e.g., prescription fill data). Fill data from the pharmacy could provide physicians an idea of the level of medication adherence for CKD patients as well as for patients with other conditions. Barry Carter, professor in the Department of Pharmacy Practice & Science at the University of Iowa, is focused on improving collaborative care between pharmacists and physicians using a two-way information framework and may be able to provide insight. Dr. Narva will reach out to Dr. Carter, who has worked with NKDEP in the past. Additionally, it may be beneficial to expand this effort beyond the kidney community and to consider inclusion of other measures, such as liver function.

Next Step

  • Dr. Narva will reach out to Dr. Carter to learn more about a two-way e-prescription framework.

Incorporating CKD Data into EHRs, Group Discussion

Two strategies were discussed as having the most potential for leading to successful incorporation of CKD-related data into EHRs:

1. Create a CKD clinical quality measure (CQM) with numeric rather than categorical values
Creating a CQM with numeric rather than categorical (e.g., yes/no) data elements would require EHR vendors to implement these elements in a searchable fashion. In drafting the measure, it may be helpful to review measures put forth by the American Board of Internal Medicine’s CKD Practice Improvement Module (see attached Measures Catalogue) and/or the Kidney Care Quality Alliance. Once a draft measure is developed, it may be helpful to share the measure with the Centers for Medicare & Medicaid Services (CMS) and other relevant Federal partners such as the Agency for Healthcare Research and Quality (AHRQ) via the Kidney Interagency Coordinating Committee (KICC), an National Institute of Diabetes and Digestive and Kidney Diseases-led initiative to encourage collaboration among Federal agencies involved in kidney-related activities.

Endorsement of the measure by the National Quality Forum (NQF) could help convince EHR vendors of the measure’s importance and motivate vendors to incorporate it. Several NQF-endorsed, kidney-related measures exist; however, they rely on categorical billing data and would not allow for data elements to be searchable. Acquiring NQF approval may be time consuming and will depend on the next cycle of measure reviews. It may be beneficial to review a previous NQF submission to better understand the scope. Since NQF recently completed two kidney measure reviews, it would be appropriate—and may be more timely—to submit for review as a diabetes measure.

Including the measure—or individual data elements—in meaningful use (MU) could also motivate vendors to incorporate kidney data; however, it is not clear whether the Office of the National Coordinator (ONC) requires a CQM for incorporation in MU, or if cases demonstrating the benefits of certain data elements would be sufficient to justify incorporation. Additionally, it is not clear whether measures need to be endorsed by NQF before they can be incorporated into MU by ONC.

Two possible measures were discussed:

  • The proportion of CKD patients with controlled blood pressure (e.g., numerator = patients with a blood pressure < 60 and/or UACR > 30)
  • The proportion of proteinuric patients treated with a angiotensin converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARB) (e.g., numerator = patients prescribed an ACE inhibitor or ARB, denominator = patients with UACR > 30)

The group agreed that an ACE/ARB measure would be the most appropriate measure to pursue. Because CMS previously experienced data issues with an ACE measure during a CKD pilot, they may be more likely to support improving data interoperability around a similar measure.

Next Steps

  • Dr. Smith to determine timing for the next NQF reviews of kidney and diabetes measures.
  • Draft the ACE/ARB measure that was tentatively agreed upon during the call.
  • Share the draft measure with CMS and other Federal partners at an upcoming KICC meeting.
  • Determine whether ONC requires a CQM in order to include data in MU and whether MU measures must be endorsed by NQF.
  • Submit the measure to NQF.

2. Partner with Health eDecisions to include a measure in a clinical decision support template 
Health eDecisions focuses on enabling the translation of clinical decision support (CDS) interventions into implementable components in order to increase the speed and ease of adoption by the provider community. Working Group member Dr. Kawamoto is initiative coordinator for Health eDecisions. Health eDecisions is run by the Standards and Interoperability (S&I) Framework, a community of participants from the public and private sectors who are focused on providing the tools, services, and guidance to facilitate the functional exchange of health information. The S&I Framework is one approach adopted by ONC's Office of Standards & Interoperability to fulfill its charge of enabling harmonized interoperability specifications to support national health outcomes and healthcare priorities, including MU and the ongoing efforts to create better care, better population health, and cost reduction through delivery improvements.

Currently, Health eDecisions is focusing on developing various CDS templates and/or rules to import across EHR systems. Health eDecisions will be pursuing a pilot phase with several EHR vendors within the next few months, which could be an opportunity for the Working Group to incorporate a kidney measure into an EHR via the CDS template, test the incorporation of the measure, and/or define kidney data use cases. Though Health eDecisions is not officially tied to MU, the initiative expects that the Health eDecision CDS products will be considered for MU stage 3. Therefore, a successful kidney data pilot may drive incorporation of kidney data into MU. In general, the Health eDecision process is based on vendor input; however, other Government groups have led similar disease-specific approaches alongside Health eDecisions. For example, the Centers for Disease Control and Prevention recently led an immunization-focused pilot with Health eDecisions.

Dr. Kawamoto is available to facilitate a kidney data pilot effort with Health eDecisions on behalf of the Working Group and welcomes support from any interested Working Group members.

Next Steps

  • Working Group members interested in being more involved in this effort should contact Dr. Patel and Dr. Kawamoto.
  • Dr. Kawamoto will explore options for an HIT Working Group collaboration with Health eDecisions.

Priorities, Group Discussion 
The Working Group agreed that the actions discussed to date (listed below) were appropriate as a starting point. Working Group members are encouraged to share additional ideas as they arise.

  • Partnering with the PhWG on the e-prescriptions effort.
  • Developing a numeric kidney CQM.
  • Collaborating on a pilot project with Health eDecisions.
  • Drafting a paper—which will be led by Dr. Drawz—endorsing inclusion of kidney data in EHRs.

Other Working Group Items, Group Discussion 
Dr. Cullen recently referred Dr. Neil Calman, President and Chief Executive Officer of the Institute for Family Health, a network of community health centers in New York to the Working Group. Dr. Calman is interested in collaborating with the Working Group to develop a kidney data use case and to identify best practices for care of CKD patients using clinical decision support built into his network’s EHR system. 

NKDEP was recently reviewed by a Scientific Evaluation Board (SEB) at the National Institute of Diabetes and Digestive and Kidney Disease. During the review, the SEB recognized the importance of NKDEP working in the HIT space. However, the SEB noted that the space is evolving rapidly and the Working Group will need to move quickly. They also recommended the group explore ways to work with ONC to make NKDEP educational materials available through EHRs.

Engaging Additional Experts and Stakeholders, Group Discussion
The Working Group is interested in identifying a representative from ONC who is invested in CKD and would be interested in joining or supporting the Working Group. Working Group members were encouraged to think about any contacts they have at ONC who might be a good fit for the Working Group.

Next Steps

  • Working Group members to check for contacts at ONC.

Next Meeting
The next Working Group conference call will be held in late May or early June.

  1. For the purposes of this summary, the term “measure” refers to a clinical quality measure including a numerator and denominator, while “element” refers to a discrete piece of lab data (e.g., eGFR, UACR).

  2. Step will depend on timing of the next NQF review of kidney disease or diabetes measure