Free EMR Newsletter Want to receive the latest news on EMR, Meaningful Use, ARRA and Healthcare IT sent straight to your email? Join thousands of healthcare pros who subscribe to EMR and EHR for FREE!

Modern Information Technology Endorsed by Government Health Quality Agency

Posted on April 22, 2014 I Written By

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

If you want to see a blueprint for real health reform, take the time to read through the white paper, “A Robust Health Data Infrastructure,” written by an independent set of experts in various areas of health and information technology. They hone in, more intently than any other official document I’ve seen, on the weaknesses of our health IT systems and the modernizations required to fix them.

The paper fits very well into the contours of my own recent report, The Information Technology Fix for Health. I wish that my report could have cited the white paper, but even though it is dated November 2013, it was announced only last week. Whether this is just another instance of the contrasting pace between technologists and a government operating in a typically non-agile manner, or whether the paper’s sponsor (the Agency for Healthcare Research and Quality) spent five months trying to figure out what to do with this challenging document, I have no way of knowing.

The Robert Wood Johnson Foundation played an important role organizing the white paper, and MITRE, which does a lot in the health care space, played some undescribed role. The paper’s scope can almost be described as sprawing, with forays into side topics such as billing fraud, but its key points concern electronic health records (EHRs), patient ownership of information, and health data exchange.

Why do I like this white paper so much? Two reasons. First, it highlights current problems in health information technology. The authors:

  • Decry “the current lack of interoperability among the data resources for EHRs” as leading to a “crippled” health data infrastructure (p. 2), and demand that “EHR software vendors should be required to develop and publish APIs for medical records data, search and indexing, semantic harmonization and vocabulary translation, and user interface applications” (p. 44).

  • Report with caution that “The evidence for modest, but consistent, improvements in health care quality and safety is growing.” Although calling these “encouraging findings,” the authors can credit only “the potential for improved efficiency” (p. 2 of the paper).

  • Warn that the leading government program to push health care providers into a well-integrated health care system, Meaningful Use, fails to meet its goals “in any practical sense.” Data is still not available to most patients, to biomedical researchers, or even to the institutions that currently exchange it except as inert paper-based documents (p. 6). The authors recommend fixes to add into the next stage of Meaningful Use.

  • Lament the underpopulated landscape of business opportunities for better interventions in patient care. “Current approaches for structuring EHRs and achieving interoperability have largely failed to open up new opportunities for entrepreneurship and innovation” (p. 6).

Second, the paper lays out eminently feasible alternatives. The infrastructure they recommend is completely recognizable to people who have seen how data exchange works in other fields: open standards, APIs, modern security, etc. There is nothing surprising about the recommendations, except that they are made in the context of our current disfunction in handling health information.

A central principle in the white paper is that “the ultimate owner of a given health care record is the patient him/herself” (p. 4), a leading demand of health reformers and a major conclusion in my own report. Patient control solves at one stroke the current abuse of patient data for marketing, and allows patients to become partners in research instead of just subjects.

The principle of patient control leads to data segmentation, a difficult but laudable attempt to protect the patient from bias or exploitation. Patients may want to “restrict access to certain types of information to designated individuals or groups only (e.g., mental health records, family history, history of drug abuse) while making other types of information more generally available to medical personnel (e.g., known allergies, vaccination records, surgical history)” (p. 33).

This in turn leads to the most novel suggestion in the paper, the notion of a “patient privacy bundle.” Because most people have trouble deciding how to protect sensitive parts of their records, and don’t want to cull through all their records each time someone asks for research data, the health care field can define privacy policies that
meet common needs and let patients make simple choices. Unfortunately, a lot of hurdles may make it unfeasible to segment data, as I have pointed out.

Other aspects of the white paper are also questionable, such as their blithe suggestion that patients offer deidentified data to researchers, although this does appeal to some patients as shown by the Personal Genome Project. (By the way, the authors of the white paper mischaracterized that project as anonymous.) Deidentification expert Khaled El Emam (author of O’Reilly’s Anonymizing Health Data) pointed out to me that clnical and administrative data involves completely different privacy risks from genomic data, but that the white paper fails to distinguish them.

I was a bit disappointed that the paper makes only brief mentions of patient-generated data, which I see as a crucial wedge to force open a provider-dominated information system.

The paper is very research-friendly, though, recognizing that EHRs “are already being supplemented by genomic data, expression data, data from embedded and wireless sensors, and population data gleaned from open sources, all of which will become more pervasive in the years ahead” (p. 5). Several other practical features of health information also appear. The paper recognizes the strains of storing large amounts of genomics and related “omics” data, pointing out that modern computing infrastructures can scale and use cloud computing in a supple way. The authors also realize the importance of provenance, which marks the origin of data (p. 28).

Technologists are already putting in place the tools for a modern health IT system. The white paper did not mention SMART, but it’s an ideal API–open source, government-sponsored, and mature–through which to implement the white paper’s recommendations. The HL7 committee is working on a robust API-friendly standard, FHIR, and there are efforts to tie SMART and FHIR together. The Data Distribution Service has been suggested as a standard to tie medical devices to other data stores.

So the computer field is rising to its mission to support better treatment. The AHRQ white paper can reinforce the convictions of patient advocates and other reformers that better computer systems are feasible and can foster better patient interventions and research.

Barriers and Pathways to Healthcare IT

Posted on April 3, 2014 I Written By

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

Those who follow health IT for a long time can easily oscillate between overenthusiasm and despair. Electronic records will bring us into the 21st century! No, electronic records just introduce complexity and frustration! Big data will find new cures! No, our data’s no good!

Indeed, a vast gulf looms between the demands that health reformers make on information technology and the actual status of that technology. But if we direct a steady vision at what’s available to us and what it provides, we can plan a path to the future.

This is the goal of a report I recently wrote for O’Reilly Media: The Information Technology Fix for Health: Barriers and Pathways to the Use of Information Technology for Better Health Care. As part of a comprehensive overview, it dissects the issues on some topics that often appear on this blog:

  • Patient empowerment. After looking at the various contortions hospitals go through to provide portals and pump up patients’ interest in following treatment regimes, I conclude that the best way to get patients involved in their care is to leave their data in their own hands.

    But wresting data out of doctors’ grip will be heavy exercise. Well aware that previous attempts at giving patients control over data (Google Health and Microsoft HealthVault) have shriveled up, and that new efforts by Box and Apple seem to be taking the same path, I suggest a way forward by encouraging people to collect health data that will hopefully become indispensable to doctors.

  • What’s wrong with current EHRs? We know that doctors grab any opportunity handed them to complain about their EHRs. Even more distressing, the research bears out their pique; my report cites examples from the medical literature finding only scattered benefits from EHRs. Sometimes their opacity and awkward interfaces contribute to horrific medical errors.

    One might think that nobody is actually getting what they want from their EHR, but in fact plenty of providers are quietly enjoying their records–success has a lot to do with their preparation and whether they take the extra effort to make effective use of data gathered by the EHRs.

    New interfaces such as tablets, convenient storage in the cloud, and agile programming may be producing a new crop of EHRs that will meet the needs of more clinicians. But open source software would lead to the most widespread advances, enabling more customization and a better response to bug reports.

  • The viability of ACOs. Accountable care, pretty much a synonym for the notion of pay-for-value, is on the agendas of nearly all payers, from CMS on down. It certainly makes sense to combine data and keep close tabs on people as they move from one institution to another. But it’s really a job to be done on a national level, or at least a regional one. Can a loose collection of hospitals and related institutions muster the data and the resources to analyze patient data, created viable health information exchanges, and perform data analysis? I don’t think the current crop of ACOs will meet their goals, but they’ll provide valuable insights while they try.

  • Can standards such as ICD-10 improve the data we collect? What about the promise of new standards, such as FHIR? I’m a big believer in standards, but I’ve seen enough of them fail to know they must be simple, lithe, and unambiguous.

    That doesn’t characterize ICD-10 to be sure. Perhaps it does pretty well in the unambiguous department. But like most classifications, it’s a weak representation of the real world: a crude hierarchy trying to reflect many vectors of interlocking effects–for instance, the various complications associated with diabetes. And although ICD-10 may lead to more precise records, the cost of conversion is so burdensome that the American Medical Association has asked the government to just let doctors spend their money on more pressing needs. The conversion has also been ruthlessly criticized on the EMR & EHR site.

    FHIR is a radical change of direction for the HL7 standards body. For the first time, a standard is being built from the ground up to be web-friendly as well as sleek. It currently looks like a replacement for C-CDA, so I hope it is extended to hold patient-generated data. What we don’t need is another hundred vendors going off to create divergent formats.

    For real innovation, we should look to the open SMART Platform. Its cleverness is that it functions as a one-way valve channeling data from silo’d EHRs at health providers to patient-controlled sites.

We need to know what current systems are capable of contributing to innovative health solutions, and when to enhance what we have versus seeking a totally disruptive solution. I look forward to more discussion of these trends. Comment on this article, write your own articles on the topics in the report, and if you like, comment to me privately by writing to the infofix alias @ the oreilly.com domain.