It still seems magical that Spotify creates a personalized music track for my life. Similarly, I now get personalized suggestions of what books to read, what recipes to cook, and even where to travel. This is the way we’re living our lives except for healthcare. It represents almost 20 percent of the U.S. economy and has a huge impact on my life, but I don’t have the ability to personalize my healthcare experience, personalize my medical treatments, or personalize how I’m treated as I move through the system.
What’s the missing piece? Data. We need to break data out of silos, exchange it, share it, leverage it, use it — all types of data — claims, clinical, new, and old. We can’t build personalized health without piecing together each patient’s individual experience to tell the full story. We cannot leverage the positive power of technology, including machine learning and AI, without data. Unlocking this information is difficult. But it’s critical work. And we need to democratize access to data, not treat it like a competitive asset, to bring the power of personalized medicine to every clinician and patient.
Data signals help patients personalize their choices
A nurse friend of mine has stage four breast cancer. Her clinicians gave her a treatment plan. But she took a close look at her health, her data, and the evidence and determined that in her particular case there was no evidence that the treatment options would extend her life, and they would probably cause her a lot of pain and suffering in the form of adverse effects. She decided not to get treatment and has lived a quite incredible life since then. Her doctors were surprised. But to her, it was simple — she didn’t want treatment because there was no evidence that it would work for her.
Data signals help care teams see the hidden patterns
We work with a care manager who follows up with patients after they have been in the hospital to help them get the care they need. Recently, she noticed a patient was getting treated at multiple emergency departments for falls. No one had noticed the pattern. But the care manager had access to the patient’s community health record from Manifest MedEx (MX) and could see the trend: The patient needed a walker. It did not take a huge amount of information or technology to deliver dramatically more effective and personalized care. It took data and someone to notice.
That’s the care we all want. We want healthcare that’s responsive to our needs, to our preferences, and to the simple things that make a difference.
You can’t personalize patient care without data
Exciting technology is in the pipeline to make the vision of personalized medicine a reality, but we don’t have a reliable health data infrastructure in place to power this future. It’s like saying you’re going to create self-driving cars, but there’s no GPS network.
Ten years ago, most data in healthcare was trapped on paper. Now, most — but not all — of it is digital. It’s huge that in just a decade we’ve been able to transition from paper to electronic data. And we are also getting better at sharing it.
But if we don’t have platforms to integrate it, match it to each patient, and identify signal, the data is just more noise for overburdened clinicians. If we want a future of personalized health, we’re going to have to make meaning from data. And this meaning needs to be available to everyone treating a patient.
With the yearly bluster and promise of HIMSS, I still find there have been few strides in solving interoperability. Many speakers will extol the next big thing in healthcare system connectivity and large EHR vendors will swear their size fits all and with the wave of video demo, interoperability is declared cured. Long live proprietary solutions, down with system integration and collaboration. Healthcare IT, reborn into the latest vendor initiative, costing billions of dollars and who knows how many thousands of lives.
Physicians’ satisfaction with electronic health record (EHR) systems has declined by nearly 30 percentage points over the last five years, according to a 2015 survey of 940 physicians conducted by the American Medical Association (AMA) and American EHR Partners. The survey found 34 percent of respondents said they were satisfied or very satisfied with their EHR systems, compared with 61 percent of respondents in a similar survey conducted five years ago.
Specifically, the survey found:
42 percent of respondents described their EHR system’s ability to improve efficiency as difficult or very difficult;
43 percent of respondents said they were still addressing productivity challenges related to their EHR system;
54 percent of respondents said their EHR system increased total operating costs; and
72 percent of respondents described their EHR system’s ability to decrease workload as difficult or very difficult.
Whether in the presidential election campaign or at HIMSS, outside of the convention center hype, our abilities are confined by real world facts. Widespread implementation of EHRs have been driven by physician and hospital incentives from the HITECH Act with the laudable goals of improving quality, reducing costs, and engaging patients in their healthcare decisions. All of these goals are dependent on readily available access to patient information.
Whether the access is required by a health professional or a computers’ algorithm generating alerts concerning data, potential adverse events, medication interactions or routine health screenings, healthcare systems have been designed to connect various health data stores. The design and connection of various databases can become the limiting factor for patient safety, efficiency and user experiences in EHR systems.
Healthcare, and the increasing amount of data being collected to manage the individual, as well as patient populations, is a complex and evolving specialty of medicine. The health information systems used to manage the flow of patient data adds additional complexity with no one system or implementation being the single best solution for any given physician or hospital. Even within the same EHR, implementation decisions impact how healthcare professional workflow and care delivery are restructured to meet the constraints and demands of these data systems.
Physicians and nurses have long uncovered the limitations and barriers EHRs have brought to the trenches of clinical care. Cumbersome interfaces, limited choices for data entry and implementation decisions have increased clinical workloads and added numerous additional warnings which can lead to alert fatigue. Concerns have also been raised for patient safety when critical patient information cannot be located in a timely fashion.
Solving these challenges and developing expansive solutions to improve healthcare delivery, quality and efficiency depends on accessing and connecting data that resides in numerous, often disconnected health data systems located within a single office or spanning across geographically distributed care locations including patients’ homes. With changes in reimbursement from a pay for procedure to a pay for performance model, an understanding of technical solutions and their implementation impacts quality, finances, engagement and patient satisfaction.