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Healthcare IT roadmap: Starting small, scaling for growth

Complex new regulations for Accountable Care Organizations mean IT has to work overtime to keep up.
Written by Mansoor Khan,, Contributor
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Commentary - On March 31, The Centers for Medicare & Medicaid Services (CMS) proposed new regulations for Accountable Care Organizations (ACOs). While they are complex – and in excess of 400 pages in length – it is clear that technology will play a significant role in implementing ACOs. Institutions already creating ACOs have begun implementing electronic medical records (EMRs) and ancillary documentation solutions. However, for the multiple stages of meaningful use requirements, hospitals and provider groups must begin the process of integrating substantive population, provider, panel, patient, and problem area-analytics into their planning processes and workflows.

As providers assume greater financial responsibility for patient health outcomes, and they push to execute on the objectives of error reduction, standardization and improved coordination, the need for a stronger technology backbone that helps manage a population and individual patients is even greater than ever before. Throughout the process, it is critical to examine scalable approaches for applying analytics to these processes to improve patient care through patient-driven order sets, automation reminders, and/or personalized patient education materials.

Clinical IT needs at an ACO
Going forward, if healthcare systems are to successfully execute on the above-mentioned objectives of error reduction, standardization, and improved coordination, they will require additional information technologies (IT). In general, two sets of technologies are needed. First, systems are required to capture, standardize and structure health information and transactions. Representative solutions include EMRs, Picture Archiving and Communication systems (PACS), and Computerized Physician Order Entry (CPOE). These solutions serve as the informatics backbone- making data available in more places, removing the known errors associated with the absence or miscommunication of information, and helping to increase clinician productivity.

The second set of solutions is analytics and clinical decision support. These systems interpret longitudinal data to inform care providers and health system planners. Unlike EMRs, which help standardize the documentation of care, clinical decision support and analytics aim to standardize the delivery of care. Specifically, they intend to improve patient care by providing clinicians with insight and guidance using known patient histories.

Strategies to meet ACO requirements: Start small & grow quickly
The ACO roadmap does need to be well-planned. Most institutions interested in creating ACOs have already begun implementing EMRs and ancillary documentation solutions. They are required for Stages 1 and 2 of the Meaningful Use requirements under the American Recovery & Reinvestment Act (ARRA) of 2009 and The Health Information Technology for Economic and Clinical Health Act (HITECH). However, even for Stage 1, providers and hospitals alike are finding that they require additional technology like real-time, targeted alerts; evidence-based order sets; patient safety surveillance; lab orders and results; as well as patient reminders; and public health reporting to accomplish critical objectives around clinical decision support and ancillary reporting.

To create effective ACOs, organizations need the right kind of solid IT infrastructure. The type of continuous quality improvement envisioned in the ACO model also requires comprehensive clinical decision support (CDS) at the point of care; not to mention population-, practice-, provider- and patient-level reporting to determine whether the encounters are successful and compliant. CDS and analytics must support the clinical and administrative needs of an ACO seamlessly, based on one evidence-based platform that satisfies multiple stakeholders, at many touch points in the care process.

Dressing up static order sets and adding a few hard-coded rules cannot be called Clinical Decision Support anymore. To meet the numerous requirements of delivering effective care, engaging patients and continuously improving processes, organizations will need to deploy systems that provide multi-parameter, real-time decision support. Additionally to meet the Continuous Improvement requirement such systems need to provide a large library of evidence-based content that is truly integrated with both population management analytics and analytics showing the financial impact of discrete clinical events. Only when all these technologies are integrated on a Web services-based platform that is also able to process the Clinical Document Architecture, will our health system reap the benefits of Accountable Care.

Where to start: Focus on what’s important now
When creating an ACO, the best way to facilitate a positive experience within an organization is to choose a specific area that needs improvement. Some health systems will focus on population management analytics first, while others may pick high-volume disease states around which to innovate. A third system may choose to close known gaps in care using alerts at the point of care. While the ideal starting point is institution- and situation-specific, the key is not to try and do everything at once. Selecting one or two issues to focus on and resolving them will create a platform to grow the ACO.

Make it enjoyable, or at least non-disruptive
Moving to an ACO is challenging. Changing clinical workflows and IT tools as part of that transformation can be intimidating to the organization. Ideally, introduction of analytics and clinical decision support, patient-driven orders, or automated patient-education, should be as non-disruptive to clinicians as possible. From a technology perspective, this includes using existing IT tools and frameworks as much as possible, and augmenting them with data and transactions deployed using web-based services. When entirely new solutions are needed, an outstanding user experience, as well as clinical excellence, is paramount in any selection process.

Ensure whatever goes in can change over time
As ACOs continue to evolve, the informatics requirements will rightly change as well. Rigid clinical IT solutions may be excellent at accomplishing key tasks specified today in a Request for Proposal (RFP). However, flexibility to grow and adapt to changes in provider needs, clinical priorities, deployment models, and information requests is equally important. Any clinical knowledge embedded in a solution must also be flexible when adjusting functionality. The solution provider, whether a vendor or in-house developer, must furnish provider tools and services to manage the content over time, as medical science in general (evidence), and comparative effectiveness research in particular, evolve.

An approach to achieving a step-wise, non-disruptive, flexible strategy for ACO-enabling analytics is using a modular system on a common platform. This approach enables the system to be easily implemented initially, and will allow it to grow over time. By employing a common platform architecture, the ACO is assured all data, rules, evidence, and quality measures, will be consistent across the enterprise. Also, data integration requirements are kept to a minimum. At the same time, modular functionality on the platform allows for the addition of new use cases and capabilities in run-time as they become needed.

As the ACO model gains momentum in the healthcare market the innovators must be there to give hospital, payor and EMR clients new methods to ensure each care encounter is as informed as possible, and each health system leader has the information required to design effective health- improvement strategies. By taking the appropriate steps to plan their IT strategy, providers will be uniquely positioned to reap the financial windfalls associated with consistently providing evidence-driven, informed care.

biography
Mansoor Khan, Sc.D MIT, is chief executive officer at DiagnosisOne, a clinical decision support and analytics company. He has more than 15 years of technical information technology and management experience in multiple industries.

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