A Treatment Plan for Technology in Health Care

The following is a guest blog post by Andy Oram, writer and editor at O’Reilly Media.

The kind of health care reform that brings better care at a reasonable cost will consist of many, tightly interlocking strands. Each of us—everyday consumers and patients, health care providers, payers and public health officials, technology developers, policy makers, and clinical researchers—can do specific things to push health care forward, and many of these involve computer technology.

During a stint in the mental health field, I would meet regularly with a team of professionals from different disciplines (and with the patient) to work out a treatment plan. This article similarly lays out some tasks each of us in his or her respective fields can carry out. Like the meetings I attended many years ago, this is a collaborative approach where my suggestions are meant to elicit constructive responses and push-back.

Naturally, a treatment plan must start with a firm diagnosis and an assessment of the patient’s strengths and weaknesses. For health information technology, I try to provide that assessment in my report, The Information Technology Fix for Health: Barriers and Pathways to the Use of Information Technology for Better Health Care. Refer to it for background as we jump into action and assign tasks to each stakeholder.

Consumers/patients/citizens:

• Measure the vital signs that are important to your health, and extract them from the silos of devices or vendor web sites into your personal health record. The Blue Button Initiative promotes open standards that increasingly bring within your reach the records that others hold about you.
• This process is important because physicians will need your statistics to carry out effective diagnoses and planning—for instance, to know whether you need to make an office visit and even to check into the hospital. Collecting this data also means the clinical staff can review it before a visit and not waste your whole 15 minutes asking you about your condition.
• Casual readers may see this advice as simply an appeal to join the Quantified Self movement, but it is much, much more. Vital signs give you leverage that can drive change throughout the health care system. First, it creates a pressing need for the doctors’ electronic medical records to open up and accept patient-generated data. It can also lead to discussions about who owns your data—it should be you—and who gets to use it for research or other purposes. The ripple effects can render the entire health care industry more responsive and intelligent in handling patients—and also more respectful of their right to control the flow of their data.

Health care providers:

• Get involved in the design of the technologies you used. Demand to be on the design team, not just consultants on the sidelines, and demand that the software be easy to customize in deep ways that respond to your ways of doing things.
• This endeavor goes beyond ease of use and even beyond the prevention of errors related to confusing interfaces. It determines the types of data collected, when you can input and change the data, and whether it can empower the patients to choose life-enhancing behaviors. Therefore, advocate for data that patients can also use and understand, because they are responsible for their own behavior. Finally, insist that electronic record systems maintain public databases that can log the errors you find, as recommended in a recent  government report.

Payers and public health officials:

• Collect and release data to support clinical and cost-containment analyses by providers, payers, and consumers, working with them to ensure the data’s value, accuracy, and usability.  To open its secrets to modern analytical tools, data needs to be consistent, formatted in programmer-friendly ways, and timed to be delivered to the public promptly and regularly.
• What will be the payback for the investment in shared data sets? Treatment depends on clinical research, but it is well understood now that double-blind clinical studies can’t solve every problem: they are usually short-timed and their subjects are often unrepresentative of realistic populations, so they are often overturned in the field. Therefore, studies need to augmented by longitudinal, large-scale analytics (“big data” solutions) that can turn up trends hidden by the idiosyncrasies of double-blind studies. And your data is lifeblood of large-scale analytics.

Technology developers:

• Work on free and open source software solutions instead of competing with all your fellow developers to reinvent the programming wheels. Extending the Fast Health Interoperable Resources (FHIR) standard with fields focusing on patient-generated data would be one good step. Open source software does not prevent you from making money from your investment in a variety of ways, including web solutions (Software as a Service). In fact, combining efforts in free software solutions will give you more and better software, because you can exploit the contributions of everyone who is part of the development community. Free, open software also eliminates the current tussles over standards, because data formats will be transparent and therefore easy to produce and consume.
• The freedom to change and redistribute software will ultimately improve clinical settings as they can adapt the software to their needs, an especially important value to carry software to diverse regions of the world.

Policy makers:

• Require the collection and exchange of data about patients, providers, and public health (with the consent of the patient) to become an automatic part of the workflow within institutions, between institutions, and between provider and patient. The Meaningful Use guidelines make a start toward interoperability, but the certifications and showcases are not enough to ensure that it’s clean and structured consistently, or that the formats permit viable comparisons.
• Breaking down the silos between the providers’ data sets will also break down the silos of their thinking and allow better interventions in patients’ medical conditions. It will also welcome the addition of patient-generated data and observations of daily living, a rich source of information that will flesh out lab tests and other data from clinical visits.

Clinical researchers:

• Develop trials to validate that the new wave of low-cost applications and devices are accurate, safe, and effective. Traditional double-blind clinical trials are usually too expensive and slow to fit the budgets and schedules of modern technology development, so seek out sleeker, cleverer types of tests to provide the necessary validation.
• Your efforts will be much more than a leg up for companies making medical devices and software The validation of apps and devices will enable doctors to confidently prescribe their use and insurers to pay for them. They will, in turn, lead to a flood of new, patient-generated generated data that will significantly fine-tune treatment—especially when interoperability allows providers to collaborate—and will combine with open data sets to generate new treatments.

This treatment plans focuses on technology because it is a great facilitator, providing the tools and environment for effective treatments and reduced costs. The plan will not in any way diminish the other, less technologically focused stakeholder tasks. Public health officials still have to clean up poisonous environments, battle against obesity and tobacco use, and reduce disparities in gender, race, and environment. Doctors still need to learn compassionate care. Payers should move resolutely to fee-for-value reimbursement—although with a recognition that the data needed to properly stratify patients is sometimes scant—and expand their guidelines to include innovative treatment approaches such as telehealth and games. Clinical researchers still need to uncover whatever factors in the genes and other “omics” differentiate between patients in order to hone in on effective individualized treatments. Everyone with health problems should join support networks.

Progress depends on reformers building relationships with the players named in this article and determining how the interests of each player can be bent to meeting the goals of reform. For instance, take one of the dilemmas mentioned in this article: that devices and software apps are underutilized because they are unvalidated. The players we need to involve are:

Payers: They have an interest in bringing down the out-of-control costs of chronic illnesses that are making their plans unaffordable. This motivates them to encourage the use of medical devices and apps for day-in, day-out patient engagement and monitoring. But they want only devices and apps whose effectiveness has been validated.

Technology developers: They have an interest in getting their devices and apps validated so that they can be integrated into medical care and funded by payers, but double-blind clinical trials are too expensive and time-consuming for this purpose.

Clinical researchers: They have an interest in finding new funding, because traditional sources such as NIH and pharma companies are cutting back.

Consumers/patients/citizens: They urgently want to overcome chronic health conditions—but with solutions that are rock-bottom simple and low-cost. The consumer devices and free or low-cost apps can be this solution if they’re validated and covered by insurance.

The solution may therefore involve persuading payers to fund clinical researchers to develop new validation methods, perhaps by running modern “big data” statistical methods over data provided by payers and others. These methods, when shown to be good enough, can lead to quicker approvals for devices and apps and ultimately to realizing the promise of patient tracking.

Technology remains a key part of the mix. As stakeholders come to understand how technology can help them meet their goals, they can assess the status of the technologies and demand improvements that realize the mission of improved health care.