Basic Statistics Should Be a Core Competency of Every Citizen of the World

A medical educator recently argued in her blog that medical school admissions requirements should minimize requirements in math and science topics, especially areas like calculus and physics. There is no question that medicine, and even informatics for that matter, require knowledge and competency in many areas beyond math and science.

However, the problem with the math we teach to potential healthcare professionals and informaticians, indeed to everyone in society, is that we teach the wrong math. I took three semesters of calculus in college and can say that I have almost never used any of it. On the other hand, I had almost no education in statistics, a type of math I use not only in my work, but also in my function as an informed citizen. Indeed, most healthcare professionals, whether clinicians or researchers, use statistics daily. Likewise, as thoughtful citizens in society, we also encounter statistics daily in the news and other aspects of our lives.

For these reasons, I believe that statistics should be a core competency of every citizen in the modern world.

It is not even the mathematics in statistics that are most important, but rather the concepts and the thinking they engender. Every citizen in the world should understand the basic concepts of inferential statistics and be able to answer such questions as:

• What does statistical significance mean? How is it different from a clinical (not necessarily in the medical context) significance?
• What is the difference between absolute and relative risk? What is the meaning of large relative risk differences in the setting of small absolute risk?
• In health-related topics, how do we discern and compare different types of health risks?
• Also in health, what do sensitivity and specificity of diagnostic tests mean, and how does prevalence impact the risk of disease in the face of positive or negative diagnostic tests?

One of the most articulate advocates of this view is John Allen Paulos, whose books Innumeracy and A Mathematician Reads the Newspaper inform us why basic numeracy and statistical competency are so important. These kinds of engaging writings, and basic education about statistics, should be a part of every high school education, not to mention in the education of clinicians and informaticians.

Universal EHR? No. Universal Data Access? Yes.

A recent blog posting calls for a "universal EMR" for the entire healthcare system. The author provides an example and correctly laments how lack of access to the complete data about a patient impedes optimal clinical care. I would add that quality improvement, clinical research, and public health are impeded by this situation as well.

However, I do not agree that a "universal EMR" is the best way to solve this problem. Instead, I would advocate that we need universal access to underlying clinical data, from which many different types of electronic health records (EHRs), personal health records (PHRs), and other applications can emerge.

What we really need for optimal use of health information is not an application but a platform. This notion has been advanced by many, perhaps most eloquently by Drs. Kenneth Mandl and Isaac Kohane of Boston Children's Hospital [1,2]. Their work is being manifested in the SMART platform that is being funded by an ONC SHARP Award.

Mandl and Kohane point to the iPhone as an example of building a platform on top of a common data store. I see this in action every day on my iPhone, when different applications make use of various data stores built into the phone, such as its GPS data. (Android and other phones offer similar functionality.) Not only Google Maps uses this data, but also my LA Fitness app that tells me where the nearest club is located when I am in a different city and hoping to find a gym.

A common data store, on top of which a thousand flowers (or apps) can bloom, is the ideal situation to the health information system "ecosystem." This will allow new ideas and innovations to flourish, while insuring that interoperable data will be accessible by all apps that have appropriate and authorized access. It will insure competition and a healthy marketplace to bring out the best in health information technology.

References

1. Mandl, KD and Kohane, IS (2009). No small change for the health information economy. New England Journal of Medicine. 360: 1278-1281.
2. Mandl, KD and Kohane, IS (2012). Escaping the EHR trap--the future of health IT. New England Journal of Medicine. 366: 2240-2242.

The Workforce Group of the ONC Health IT Policy Committee Makes Its Recommendations

For the last nine months, I have had the opportunity to be part of a workgroup of the ONC Health IT Policy Committee focusing on the health IT workforce issues. This week, Larry Wolf, co-chair of the workgroup made a presentation of the group's recommendations to a meeting of the full Health IT Policy Committee.

The recommendations of the workgroup can be summarized as follows:

1. ONC should summarize and publicize the results of the several workforce development programs it has funded.
2. ONC should summarize and widely disseminate the core competencies for members of the workforce that it has identified.
3. ONC should publicize the resources and best practices that they and other organizations have made available.
4. There is an emerging need for soft and hard skills related to team-based care, population health and patient engagement. ONC should recommend new program development and funding to address these needs.
5. ONC should learn from what is happening with the current workforce. It should do this by recommending funding of studies on the impact of health IT on the workforce, such as turnover, enrollment in healthcare vocations (schools), and new jobs, such as nurse informaticists.
6. The current Standard Occupational Classification (SOC) does not address health IT. ONC should host an SOC input process from the health IT community.

While I agree with all of the recommendations that our group made, I would have added two additional recommendations, which actually build on the fourth and fifth recommendations in the list. The first of these emanates in part from the slide presentation, which might be read by some to imply that informatics and IT jobs in healthcare are "technician" jobs. While healthcare organizations certainly need well-trained health IT technicians, this ignores the larger role that informatics will play as advanced health IT is adopted and used as an integral part of efforts such as quality measurement and improvement, accountable and coordinated care, and biomedical advances such as personalized medicine. Health IT is not merely a support function, but a critical component of our armamentarium to achieve the triple aim of improved health, better care, and lower cost.

My second additional recommendation builds on the recommendation for learning about the current workforce. In light of the larger role for health IT described in the previous paragraph, we need a much more comprehensive understanding than just impact on the current workforce and new jobs. We need to better understand not only of current workforce practices but also how to develop and educate the best workforce going forward into the new era of accountable and coordinated care and new advances such as personalized medicine.

I look forward to the continued efforts of the workgroup and our academic program at Oregon Health & Science University is certainly incorporating this forward-looking view as we revise and augment the curricula of our programs.

PCORI Clinical Data Research Network Funding Opportunity Casts Broad Vision for Clinical Data Use for Research

A couple weeks ago, the Patient-Centered Outcomes Research Institute (PCORI), an organization funded under the Affordable Care Act (ACA), released a funding opportunity to establish a series of Clinical Data Research Networks (CDRNs). The goal for these CDRNs is to develop a data infrastructure that will allow them to provide the data infrastructure for comparative effectiveness research (CER) to be done both within and outside their networks. (A separate announcement for complementary Patient-Powered Research Networks was also made and is included in the PDF announcing funding for the CDRNs.)

Naturally my institution is evaluating whether we have the resources and commitment to apply ourselves, and this gave me a reason to review the funding opportunity announcement in detail. I generated the following summary for my local colleagues, but also can state that no matter what we do, the funding opportunity presents a comprehensive vision for what CDRNs in general should look like, and indeed advances our moving toward the Institute of Medicine (IOM) vision of the learning health system [1].

A total of $56M will be awarded for eight or so $7M projects. Applicants can ask for a higher budget than $7M, but that must be approved by PCORI before a proposal at a higher funding level is submitted. The proposal process will entail two steps, the first of which is the submission of a letter of intent by June 19, 2013. PCORI will then invite some but not all of those submitting a letter of intent to submit full proposals, which will be due by September 27, 2013.

Each CDRN will be required to engage two or more different health systems and have one million or more patients enrolled among them. All systems will be required to have an electronic health record (EHR) system in place and the ability to standardize data among them. In essence, the system must adhere to the data standards specified by Stage 2 of the federal meaningful use program. This includes adoption of standards such as Consolidated Clinical Document Architecture (CCDA) for patient summaries, SNOMED CT for problem lists, RxNorm for electronic prescriptions, ICD-10-CM for diagnoses, ICD-10-PCS for procedures, CMS PQRI 2009 Registry XML Specification for quality reporting, and HL7 Version 2.5.1 for reporting of public health laboratory data and immunization administration. (A succinct overview of these standards in provided in a summary of all of the Stage 2 meaningful use requirements by Metzger and Rhoads [2].)

Another requirement is the ability of the CDRN to identify and recruit cohorts of patients with defined conditions. In particular, three patient cohorts must be able to be identified:

• A disorder of applicant’s choosing that includes 10,000 identified patients
• One or more rare diseases with prevalence less than 1 per 1500 persons in the US
• Overweight or obese patients, identified for presence of diabetes or pre-diabetes

Among the other requirements for the CDRN are:

• Ability to capture complete information on these patients over time, which could be a challenge due to patients getting care in multiple locations that has been shown to be widespread [3, 4]
• Process for patient as well as clinician engagement in governance as well as setting of research priorities.
• Commitment and active involvement of leadership of all participating organizations to play an active role in the governance of the CDRN and its meeting all key objectives
• Willingness to serve as a national data infrastructure resource for the conduct of CER by researchers both within and outside of the network - the award itself does not fund any research but the CDRN must engage CER researchers, including those outside network
• Demonstration of capacity to connect with patients for collecting data and recruiting them into clinical trials
• Capacity to support large CER randomized trials, with the embedding of research activity in functioning healthcare systems while not disrupting their usual healthcare business functions - this will require support of these activities from the respective administrative and executive leadership of participating organizations
• Integrating human subjects oversight, institutional review board (IRB) activities, and informed consent procedures across the network
• Policies to maintain data security, patient privacy, and confidentiality, along with organizational privacy
• Providing access to biological specimens for research purposes
• Robust governance, with the ability to identify and act upon unanticipated problems or issues
• Description of the efficient use of human and other resources to accomplish the project

One additional capacity I would have liked to see required would be participation in informatics and related research looking at the organization and function of the CDRNs and their data collection and usage issues. The development of CDRNs is necessary to advance the learning health system, but it is something for which there are still many unknowns. A research agenda to explore the issues of how to collect and use for research the operational clinical data on a network of multiple healthcare delivery systems and one million patients is critical to make sure our knowledge of how to do this effectively is learned and documented.

References

1. Smith, M, Saunders, R, et al. (2012). Best Care at Lower Cost: The Path to Continuously Learning Health Care in America. Washington, DC, National Academies Press.

2. Metzger, J and Rhoads, J (2012). Summary of Key Provisions in Final Rule for Stage 2 HITECH Meaningful Use. Falls Church, VA, Computer Sciences Corp.

3. Bourgeois, FC, Olson, KL, et al. (2010). Patients treated at multiple acute health care facilities: quantifying information fragmentation. Archives of Internal Medicine. 170: 1989-1995.

4. Finnell, JT, Overhage, JM, et al. (2011). All health care is not local: an evaluation of the distribution of emergency department care delivered in Indiana. AMIA Annual Symposium Proceedings, Washington, DC. 409-416.