It’s Time for a New Kind of Electronic Health Record

It’s Time for a New Kind of Electronic Health Record

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Well before the Covid-19 pandemic struck, electronic health records were the bane of physicians’ existences. In all too many cases, EHRs seemed to create a huge amount of extra work and generate too few benefits. The pandemic has made the deficiencies of these systems glaringly apparent. This article discusses how EHRs should be transformed so they become an indispensable tool in keeping individual patients and patient populations healthy.

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The Covid-19 pandemic presents the U.S. health care system with a mind-boggling array of challenges. One of the most urgent is coping with a simultaneous glut and dearth of information. Between tracking outbreaks, staying abreast of the latest information on effective treatments and vaccine development, keeping tabs on how each patient is doing, and recognizing and documenting a seemingly endless stream of weird new symptoms, the entire medical community is being chronically overwhelmed.

Sorting through large amounts of information and finding the nuggets that apply to a particular patient’s situation is something that computers ought to be good at. But we still have problems of knowing what data is important and what is the right treatment and prevention plan for each patient.

During the Obama administration, the federal government supplied billions of dollars — and providers kicked in billions more — to speed the adoption of electronic health records. But even though up to 96% of hospitals and 86% of physician offices have adopted them, we still don’t have EHRs that can rise to the information challenges that clinicians face every day, let alone those posed by Covid-19.

Providers still encounter continual frustration on many levels: user interfaces and usability issues, the quality of the data entered, the limited ability of the data to support discovery and interoperability among systems, just to name a few. These limitations have confounded the ability of clinicians to deliver care during the Covid-19 crisis.

An overhaul of the electronic health record is overdue. It must go beyond fixing the user interface or improving interoperability. It must address the fundamental problems exposed by the pandemic. The overhaul must also support the ability of providers to adopt the new value-based-care business model of health care — one that rewards providers for outcomes rather than the volume of services and that shifts their focus from reactive sick care to the proactive management of health.

To address these needs, the electronic health record must transition from an emphasis on a person’s medical record to an emphasis on a person’s plan for health and from a focus on supporting clinical transactions to a focus on delivering information to the provider and the patient.

From the Record to the Plan

A redesign of the EHR is essential, but what should it look like? EHRs are reasonably good at the “record” part — keeping track of what happened to the patient — but they must evolve to address the “health” part by helping providers plan for what they want to happen. EHRs could become tools for making those plans and keeping them on track if we design them with that goal in mind.

Intermountain Healthcare, Virginia Mason, and Kaiser Permanente are pioneers in adopting the new health care business model. Their experiences point the way to the next generation of EHRs.

What would a “plan-centric” EHR system look like? It would include:

  • A library of care plans that covers a wide range of situations. Variations in patient circumstances and preferences would dictate variations in the plans. A patient with well-managed diabetes would have a different plan from one who is still struggling for control. A patient who lived alone would have a different plan from one who lived with a large, supportive family.
  • Algorithms to form a patient’s master plan. Patients hardly ever have just one clear, manageable issue. A master plan would combine appropriate algorithms for treating, say, a patient’s asthma, arthritis, depression, and weight reduction, automatically resolving conflicts and redundancies.
  • Care team support. Each team member — the patient’s primary care provider, specialists, nurse practitioners, pharmacists, case managers and the patient — would see both the master plan and their own to-do list. Team members could assign tasks to one another.
  • The ability to traverse care settings, geographies, and different EHRs. The plan would need to travel seamlessly with the patient. Providers would have interoperable systems that could integrate a patient’s plan regardless of its origin.
  • Decision support and workflow logic. The system must remind team members of upcoming and overdue activities, suggest changes in the plan when patient conditions and care needs change, and route messages to the appropriate team member regarding new test results or patient events.
  • Analytics for both individual patients and populations. The system must be able to assess how well the plan is achieving its goals, both for the individual patient and for the larger population that may be under the provider’s care. It should be able to apply lessons learned in treating one patient to other patients.

Imagine a plan-centric EHR ready to deal with Covid-19, incorporating the latest evidence-based treatments into each patient’s care plan based on their current status and underlying health conditions, and then feeding back data on how each patient responded in order to improve the plan for the next patient. Such capabilities could transform outcomes and save many lives.

From Transaction-Oriented to Intelligence-Oriented

As befits systems with origins in billing, the design focus of EHRs has been transactional: documenting a visit, retrieving a lab result, sending a prescription to the pharmacy. This focus is not all bad: It has reduced some types of errors and made it easier to generate work lists and logic to help ensure that the clinical order is complete.

However, exquisite transaction support is not enough to address the challenges that afflict care delivery: failure to follow the evidence, brittle operational and clinical processes, and the near impossibility of keeping up with advances in medicine. EHRs can compound these limitations by being very difficult to update.

We must reimagine the EHR not as a document but as a system that supports the generation and tracking of multiple documents, events, and processes. It must surround each transaction and clinical process with intelligence to ensure clinical appropriateness and sound execution.

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It should help ensure that care follows the evidence, identify treatment options that result from the dazzling pace of medical discovery, and alert providers that care processes have deviated from acceptable levels of performance. This intelligence must detect acts of commission (the choice of an outdated treatment approach) and omission (a patient has failed to keep an appointment to see a specialist).

The EHR must provide the ability for clinicians to easily analyze patient data to discover new treatments, uncover safety issues, and identify unusual clinical findings. Such capabilities would have enabled, for example, the much faster discovery of blood clotting in Covid-19 patients.

Intelligence can be leveraged to help address clinician concerns with EHR usability. Logic that presents the physician with data and potential actions tailored to reflect the patient’s conditions, the physician’s preferences, and the medical evidence can save the physician time and improve the quality of care.

Many of these intelligence and plan capabilities are present to some degree in today’s EHR. However, the old fee-for-service business model has not rewarded their refinement and extensive use.

Some providers — including Kaiser Permanente, Geisinger, Intermountain Healthcare, and UPMC — are using their EHRs in this way, but these organizations share a key characteristic: They insure a significant percentage of their patients as well as providing their care, and therefore their financial incentives are more like those of payers. They have already embraced the new value-based-care business model that the rest of the industry is moving toward.

Achieving the Intelligent, Plan-Centric IT Foundation

We will always need medical record documentation and transaction capabilities. An accurate, comprehensive health record is critical to the delivery of care and is also a required legal document.

How can we preserve these functions of the EHR while migrating it to the new intelligent, plan-centric design?

One major obstacle to fixing the EHR problem is that the health care industry is in the middle of a transition to the new business model. But the change is happening so gradually — in fits and starts, depending on the payer and the political environment — that it’s difficult for providers and EHR vendors alike to gauge the appropriate moment for a system redesign. Consequently, providers will have to juggle two opposing business models for an unknown period of time, and their information technology portfolio will have to support both.

Exasperated users might support the idea of tossing out what we have and starting over from scratch, but that’s not going to happen for a number of reasons: the stupefyingly large cost, the enormous development and implementation time, the disruption of operations, and the potential danger to patients during the transition.

Health care should take a lesson from banking. Instead of rewriting legacy systems, the banking community modified current systems, added complementary applications, and “wrapped” legacy systems with newer technologies and capabilities. To transform the EHR from a (quasi) document into the new design, we need a full array of complementary applications that “wrap around” appropriately modified EHRs and provide significant care-plan and intelligence support. Providers can make these investments as needed to match the pace and address the specific needs of their migration to value-based care and measure the return on investment as they go. These applications and capabilities might include the following:

  • Population health management. Providers will be accountable for the health and health care of populations of people with common health conditions such as diabetes and asthma. Population-health-management systems combine data from diverse sources (EHRs, claims, patient-monitoring devices, census, and other demographic databases that can track social determinants of health). The population-health-management systems “surround” the EHR so that the provider can view the plan from the record and the population health management system can send alerts and messages to the EHR inbox.
  • Health information exchanges. Connecting a wide variety of health care organizations in a region or state, the HIE enables them to exchange data about a patient. For example, when a patient presents at an emergency room, the care team can use the exchange to retrieve patient data from other care settings and get a complete clinical picture of the patient. Some HIEs have developed applications that measure regional care quality and costs, portals that enable patients to see their aggregated clinical data, and alert systems that tell a provider when one of its patients has been seen elsewhere.
  • Patient-health-management applications. These enable consumers to aggregate their health data, view their health status, track their appointments and prescription refills, converse with their care team, participate in care communities, view and alter their shared care plan, and research health issues.
  • Big data analytics systems. These aggregate very large amounts of health and health care data to compare the effectiveness of treatments, identify medication and device safety problems, facilitate medical discovery, and analyze shifting patterns of patient characteristics and diseases. Artificial intelligence can be used to support automatic correction of data inconsistencies and extraction of data from images, sound, and free text: for example, going through free text and pulling out quality measures or problems that were not previously in a patient’s problem list.

Many health systems have begun to adopt the strategy of surrounding their EHRs with the next generation of intelligent, plan-centric capabilities. As the health care business model evolves, organizations such as Mass General Brigham (formerly Partners HealthCare), Memorial Hermann, Geisinger, CommonSpirit Health, and Cedars Sinai are vigorously implementing population health, big data analytics, and patient-health-management applications.

Embracing transformation

Health care delivery is in the early stages of an extraordinary change. This change is being driven by the relentless movement to the value-based care model and the problems exposed by the Covid-19 crisis. This ongoing transformation is paving the way for a new EHR design: a platform that fuses the current EHR with complementary systems, capabilities, and technologies.

Achieving the intelligent, plan-centric health care platform will require a level of industry cooperation that is unlike, and in some ways antithetical to, the way we’ve always done things. The pandemic has shown us health care collaboration at its best. In that respect, the response to the pandemic mirrors the new business model that we are trying to build.

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