The Institute of Medicine (IOM) Roundtable on Value and Science-Driven Healthcare views electronic health information as a pillar for the improved effectiveness, efficiency and safety of health care.  Information is also fundamental to the concept of a “learning health system,” which IOM has described as having the capacity both to apply and generate scientific evidence in the delivery of care.  While it is conceivable that such learning could occur without electronic health records (EHR), it is clear that the capacity the EHR offers to generate “big data” and thus a “collective memory” — from health care services delivered, resources used in that process, and patient and population health outcomes — would markedly accelerate improvement.

While the evolving transition from traditional fee-for-service to outcomes-based reimbursement, other forms of value-based purchasing (including networks restricted to higher value providers), and ultimately integration of clinical and financial risk would seem to make the need for provider implementation of EHR self-evident, the HITECH program demonstrates the need for external stimulus to accelerate EHR adoption.  Perhaps a better understanding is needed of the relationship between investment and return to organizational efficiency, effectiveness, and sustainability.

A reluctance to adopt an EHR may have many reasons, including both the performance and cost of the EHR itself.  Usability challenges complicate adoption, especially by physicians, and some arguments have been made that productivity can suffer.  Provider resistance to adoption may also result from concern that financial benefits accrue disproportionately to payor organizations.  In aggregate, slow adoption may represent concern that the business case for adopting EHR is poor.  However, in the absence of data from comparable analyses, we have more opinion than evidence.

What do we, in fact, know about the provider return on EHR investment, which in this case is essentially a return on information?  There are a number of studies that support a net benefit to provider organizations, exclusive of benefit to payors.  There are also studies that show impairment to productivity and adverse financial impact.  Despite many thoughtful analyses, the most compelling observation is that it is difficult to compare studies and to determine whether differences arise because of the technology and the manner of its deployment, or because of differences in the methods used to assess costs and benefits.  That is to say, there is no standard model for assigning the costs and benefits of EHR adoption and, as a result, no standard or comparable business case.

The manuscript “Return on Information: A Standard Model for Assessing Institutional Return on Electronic Health Records” proposes a framework to help providers identify and quantify both the costs and benefits of EHR implementation.  Based on the need expressed by the IOM Roundtable on Value & Science-Driven Health Care for broader development and use of the digital infrastructure, including EHR deployment, we — a group of individuals participating in the Roundtable’s Digital Learning Collaborative, in partnership with the Healthcare Financial Management Association (HFMA) — have developed a tool to facilitate assessment of potential returns.  Drawing from our collective experiences as health services researchers, policy-makers, economists, informaticists and, importantly, health care finance professionals, we reviewed the existing literature and presented a model that is being introduced now as a reference for business case development for provider investment in EHR.

The model suggests some assumptions that may be useful for attributing costs, such as delineating between a basic information infrastructure and the EHR specifically.  It even suggests where certain ledger entries might be found for expenses related to EHR implementation.  On the other hand, it categorizes potential benefits of EHRs, including organizational savings that may be directly attributable to the EHR — such as decreases in the cost of managing paper and reducing redundant tests — and benefits that may be less directly attributable, such improved quality.  In fact, the model provides support in contemplating how to handle the vexing question of direct or indirect attribution of outcomes to EHR implementation.

No model can be perfect at its inception.  Just as finance professionals recognize that Generally Accepted Accounting Practices (GAAP) provide reference for consistent expression of financial data, they also know that GAAP standards are dynamic and improve with use.  Similarly, the authors and sponsoring organizations anticipate and look forward to this model evolving, too.  This is why we are so excited that HFMA will provide a home for this model and steward its evolution.

The benefits a standard model would provide are enticing.  First, financial officers would not have to develop their own unique assumptions about possible costs and benefits for every EHR implementation.  A standard model would provide credibility in discussion with other executives, board members, and even in negotiations with EHR vendors.  Second, the comparability the model provides would help identify more efficient approaches to implementation, based on differences in experiences between provider sites, and would accelerate learning about best practices.  While there are likely numerous other opportunities a standard model offers, evaluation of both costs and benefits may provide insights about the relative performance of different EHR products, and that could help accelerate improvements in the technology itself.

We hope this model provides a useful reference for providers, policy-makers, product vendors, and researchers, among others.  Even more, we hope this model sharpens the business case for EHR implantation and advanced information technologies that improve the safety, quality and efficiency of health care and foster a learning health system.