Do No Harm. Matthew Webster
we get there, but the technological seeds are in place to cause data to grow exponentially—far more than the amount of data we collect now.
Data Is That Important
No matter your perspective on the Affordable Care Act (ACA), it has hastened the push toward Electronic Health Records (EHRs) that both technology and the HITECH Act began. It represents another step toward a more paperless office. The overarching goals are about transforming the medical care through the sharing and analysis of information. There are several benefits to doing so, but the outcome is more data in more locations.
Providing insurance to millions of Americans who did not have it before is a tremendous help—especially during a pandemic. Aggregating the information from insurance companies, hospitals, doctor's offices, and so on, can help leaders identify key neighborhoods where the problem is worse and provide appropriate responses. New York City, for example, is starting to experiment with closing areas that are harder hit from COVID.6 Whether or not that plan is successful, it demonstrates the power of what data can be used for. It also aids in community outreach so we can respond more locally to local problems. This would not be possible without solid actionable data being at least semi-centralized.
From a hospital perspective, that information is very valuable. Thirty years ago, if a patient came into a hospital unconscious, there was no information about that patient. Today, depending on the sharing capabilities of a region, doctors have the ability to look up the medical history of a patient or even lab tests they have had in the past. This prevents the waste of performing the tests again and provides healthcare professionals with invaluable information on how to treat patients more quickly based on their background. That extra information can help save both lives and money.
But from a pandemic perspective, it can help hospitals predict where the influx of patients will be coming from so they can better plan to handle those patients. Information is absolutely critical. Without it, hospitals can be overwhelmed. Even with that information, hospitals can be overwhelmed, but at least they are better prepared to save lives.
The ACA also has provisions for fighting fraud from potentially dishonest providers. Being specifically focused on the data, participating organizations can have their data accessed to search for fraudulent activity. Centralized data does have specific value as part of an overall fraud reduction strategy.7
The ACA also has provisions for Accountable Care Organizations (ACOs). The primary function of ACOs is to create cost savings by encouraging doctors, hospitals, and other health providers to coordinate patient care more efficiently. In order to do that, they need data from the members who are part of the network of services that the ACO is part of. So again, the drivers are there to have data in more locations.
In the final analysis we certainly have improvements to make, but we are making very larges strides as a society to cut back on individual medical expenses through the use of IoMT and better communication networks. Our care is becoming more personalized as we gather data on patients on a regular basis. We are responding to medical issues before they become major problems. The access we have to medical records is saving us from having to redo the same tests time and again. We are reducing our error rates, which is a boon for hospitals and patients alike.
This Is Data Aggregation?
Almost ironically, the need to aggregate data is also a cause of some of the dispersion of data. Every company needs data in order to operate effectively. The more centralized that information, the better. Years ago, the information was by hand and needed to be pulled out manually—a time-consuming and painful process by today's standards. Assessments on that data were time-consuming and difficult. Now, with modern technology, they are much easier. But each system needs the data for different purposes. The insurance company needs to get all the requisition codes to analyze the data in a different way. A hospital needs to aggregate data from a host of different systems so that it has a more complete record. In the end, it is not about one aggregation, but many.
Many IoMT devices do not keep the data local to the hospital they are operating in. They send data to the cloud. This is not by accident. It has tremendous advantages for both the hospital and the device provider. Previously, a physical server needed to be installed and supported within the organization in order to maintain medical records. This created an extra burden for the IT staff and the hospital to support. Many things could go wrong—servers could go down, connectivity could be blocked, etc. There is also a maintenance overhead that comes with that extra device. The manufacturers of IoMT devices that depend on servers would need to support a patching process, provide tech support when the software components would go down, etc. This equals a lot of overhead that hospitals and manufacturers would like to avoid. Having a cloud service is a win-win for the providers because it reduces the technical overhead for IoMT and then provides an additional service that the manufacturer can charge for continually. Years ago, companies would sometimes forgo support to save time and money—a loss of revenue. It also helps the manufacturers because they can have more data to analyze and make their product better.
EHR systems are used to aggregate and access health records by hospitals, doctors, and other health providers. They are critical for the purpose of having centralized data. They also are moving to the cloud with many of the same advantages that are afforded to the IoMT cloud providers with similar benefits to the providers. The cloud, in short, helps to get companies out of the IT game (to an extent), allowing them to focus on what they do best—helping people.
Health insurance companies also need many of the same records that hospitals and doctor's offices require. They have to analyze the data and pay out claims, and they too are utilizing the cloud for many of the same reasons as other companies. Again, aggregation means diffusion of data.
With Health Information Exchanges (HIEs) we start to get into connections that not everyone is aware of. HIEs aggregate data within a Health Information Network. The goal of HIEs is to facilitate a faster, safer, and more efficient transfer of data than the previous way of having to walk or fax information over from one place to another. While typically they do not exchange information outside of their networks, they are known to connect to state or federal bodies to exchange information—yet another place where data interconnects.
There are additional grants built into the America Recovery and Reinvestment Act (ARRA) of 2009 for building Regional Health Information Organizations (RHIOs). The primary goal of RHIOs is to share health information within a region while following both state and local guidelines. Part of the overarching goal of RHIOs is to allow for the interconnection of medical information to a specific region. In some cases, they even share information with multiple regions.
The Center for Medicaid and Medicare Services (CMS) has the tremendous responsibility of overseeing patient data for several medically related federal programs. They do not necessarily collect the data themselves, though. Many of their programs are contracted out to third-party companies. When you connect into CMS web sites, these sites are often built on corporate networks.
All of these institutions that have medical information are the tip of the iceberg for where and how medical information is aggregated, stored, and exchanged. There are claims clearinghouses, labs, other types of information exchanges, data warehouses, other government entities, research institutions, service providers, biopharmaceutical agencies, aggregators, and so on. The potential location for data almost never stays within a single organization. It becomes part of an extremely rich interconnected ecosystem of partners.
So far, we have been exploring data strictly from a HIPAA perspective, but there is also data that looks like HIPAA data, but in reality, it is not.
Non-HIPAA Health Data?
Over the last decade, a number of new devices and applications have hit the market. These include everything from wearable devices that track physiological data to