Rx for Ebola: Protect the Perimeter with Decision Support and Surveillance

A man walks into an emergency room with a globally notorious febrile illness wanted for mass killings in other countries.  Instead of being diagnosed and treated, he is released back into the community, continuing to expose health workers and community members without warning.   While this may sound like the September 2014 Ebola virus fumble in Dallas, it was also the scenario that drove the SARS epidemic in 2002-3 when, as today in Africa, health care facilities were a major node of transmission.

Back then, a small cadre of techies and local public health workers developed a scalable process of perimeter screening at emergency departments that fed into a public health surveillance system (the SARS Surveillance Project).   Front line health care workers welcomed a simple decision tool to distinguish routine fevers from possible SARS, allowing them to initiate infection control to protect themselves and their patients.  Health departments received immediate notification of suspect cases and daily trends of respiratory febrile illness.   In a matter of days the system was operational in Milwaukee, and within a few weeks across parts of Ohio, Colorado and Texas too.

The system might be considered laughably simple today (yes, it involved paper, pencil and arithmetic).  It was slapped together with tools at hand and without federal funding.  Nevertheless it scaled far faster than the anticipated SARS epidemic.  (We never found a SARS case, nor were there cases to find in our jurisdictions.)  The Dallas experience proves that a similar approach is needed today.   I hope our old publication might prove useful to today’s Ebola virus fighters.

We failed to get CDC to pick up or even endorse the project.  It fell victim to the “not invented here” syndrome.  (Although we showed we could rapidly scale to EDs serving more than a quarter of the US population, the last conversation ended with “We already work with an emergency department in California, thank you very much” [emphasis mine]).*

A larger question is: are we better equipped to scale up such a system today after US$ billions of investment into health information technology?   The short-term answer is “No”, outside some local centers of excellence.    But there is little reason we couldn’t get there with a little strategic leadership and investment.

Imagine that CDC translates Ebola suspect case definitions (symptoms, signs, travel, sick contacts) into standardized HIT data elements.  Imagine these are loaded into a standards-compliant rules repository accessible to electronic health record systems (EHRs).   Imagine that EHR systems upload these rules to alert triage personnel to ask 4-6 brief questions of febrile patients.   Imagine that responses suggesting Ebola trigger immediate infection control and public health reporting.  Imagine that patients, healthcare workers and the community are protected pending definitive diagnosis.  Imagine that emergency response receives the gift of a head start on the possible emergence of a generation of new cases.

In recent years the pieces of this more automated solution have been largely completed but not assembled and applied: widespread certified EHR use; specifications for capturing most of the needed data elements; methods to distribute clinical decision support rules; specifications for electronic public health reporting.   With a focused vision and public health investment an adaptable system that combines “situational” EHR decision support with surveillance could be achieved fairly rapidly.  In the meantime, I’m told, paper, pencil and basic http are still available to replicate the 2002 approach.


*(In fairness it must be told I joined CDC 8 years later, and during my two years there agency budgets for the public health use of health information technology markedly shrank.  Thus I must share responsibility for the current state, despite efforts to the contrary.)


A Trip in the Time Machine

What information management capabilities will future US health departments need?  Shaun Grannis (Regenstrief Institute), Torney Smith (Spokane Regional Health Department), David Ross (Public Health Informatics Institute) and I were asked to gaze over the horizon during a 2012 Public Health Accreditation Board think tank.  Our work was recently published online-ahead-of-print by the American Journal of Public Health.

We looked first at potential changes in health department function suggested by the Patient Protection and Affordable Care Act (“ACA”).  Some argue that health departments might exit direct individual health services, as uninsured populations fall and Accountable Care Organizations rise.   Perhaps health departments will no longer need to track individual clients and services?  On the other hand, others have proposed expanded health department roles in community-based preventive services.  Billing for individual services like vaccination is becoming more important than ever for department revenues.   Millions will remain uninsured even after ACA implementation, health departments will continue to track cases of reportable illness and injury, and will remain accountable for transparent and up-to-date data on population health trends.  In balance we found arguments that most health departments could jettison the responsibility for collecting and protecting individual health information unconvincing.  It is likely that faster, better and safer information management is needed instead.

We also looked at projected technology changes.  Perhaps health departments won’t need to collect surveillance data when interconnected electronic health records might make such data searchable on demand?  The slow pace of interoperability initiatives, and the likely demand that health performance data be independent, transparent and accountable made us skeptical that simply “grazing on others’ data” will be meet all needs within several decades.  Meanwhile numerous other information sources, for example data recorded by citizens and sensors, will probably be added to the floods of data obtained from health care providers.

Inevitably, then, most health departments will be subject to a growing glut of electronic information like other health organizations.  Indeed, if they will fulfill their mandates and avoid shrinking into vestigial remnants, they must manage information and knowledge more competently than ever before.   The good news is that as connectivity, standardization and cloud capabilities improve, it will be easier for individual local and state health departments to lease shared information systems rather than manage them locally.  By collaborating on such shared systems they will be able to focus more on how they want to use information to protect and improve the public’s health, and less on managing hardware and software.   However, this vision depends on goal-oriented collaboration and planning between local, state and federal agencies.

Every public health department will need certain capabilities to navigate the course ahead, making these capabilities appropriate for consideration in the process of health department accreditation.  We hope our article and will initiate lively discussion on what such capabilities should look like.  What do you think?

A High Altitude View of US Public Health Systems

The long-awaited second edition of Springer-Verlag’s Public Health Informatics and Information Systems was released this winter under the able editorship of JA Magnuson and Paul Fu.  I was privileged to write a chapter on US public health information systems, and took the perspective of a newcomer asking: “How did US systems come to be this way?”

That states perform surveillance, vital registration and other functions in divergent ways using non-interoperable systems is an artifact of an decentralized eighteenth-century constitution that delegated public health authority to state, not national government.   Today this lack of standardization is a source of aggravation in the face of increasing HIT interoperability driven by Meaningful Use and EHR certification.   The federal government has levers to increase standardization in public health just as it does in health care, including facilitating inter-state consensus, adopting industry standards, and making their use a condition of funding.  Inconsistency of priority, direction and funding over the past two decades has failed to deliver standardization now when it is most urgent.

Despite this, I was able to direct emerging informaticians to the products of several recent attempts to standardize public health business processes, vocabularies, and data formats across system domains as varied as chronic disease surveillance, immunization management, newborn screening, vital statistics and communicable disease surveillance.  I like to think there will be less “wheel re-invention” as a consequence.

On the other hand I was disappointed to see how few of these are reflected in the current CDC Public Health Information Network website.  PHIN ideally would provide “one source of truth” regarding standardized information exchange for health departments. If the website is any indication the plan to resuscitate national efforts for public health interoperability has stalled once more.   It would be wonderful if the textbook’s 3rd Edition could direct learners with confidence to a federal source for public health information exchange and interoperability specifications and profiles.

I’m delighted to see that my chapter is among those most often accessed online.  Nevertheless, I cannot help but hope that rapid progress in US public health information systems will push it quickly out of date!

Network with ATL Colleagues: INTERFACE Weds. APRIL 2, 2014


NTERFACE:ATL networking event WEDNESDAY, April 2nd from 6:30-8:00 pm at Marriott Courtyard lobby bar

Please join my INTERFACE:ATL networking event THIS WEDNESDAY, April 2nd from 6:30-8:00 pm at the Marriott Courtyard lobby bar, 130 Clairemont Ave. in Decatur.
Meet health informatics peers to learn who’s doing what. Several state epidemiologists will likely be on hand. Free to attend, pay own food and drink. See you Wednesday!

Provider Backlash Threatens to Gut MU Public Health Objectives

The chorus of health care provider complaints about growing federal HIT requirements, from Meaningful Use (MU) to switching to ICD-10 diagnosis codes threatens to claim some public health victims.  On February 19 the Meaningful Use workgroup of the US HIT Policy Committee (HITPC) responded to the latter’s pressure to reduce the number of Stage 3 MU objectives by voting to delete electronic reporting of reportable lab results (ELR), syndromic surveillance (SS), and reducing requirements for reporting to public health registries.  They declined to endorse a new objective for clinical case reporting of reportable conditions, but appear posed to recommend continuing reporting to immunization information systems (IIS, often called immunization registries) and adding the capability for EHRs to upload immunization histories from an IIS.

Ironically, ELR and SS were common (but far from universal) even before Meaningful Use. An impediment to rapid expansion of ELR to new hospitals was the need to convert in-house lab codes to LOINC (but this is now MU-required for in-hospital lab reporting anyway).  Meanwhile, providers that had happily submitted HL7 Admission, Discharge and Transfer (ADT) messages for SS in the past were confronted by more complex message requirements in Meaningful Use rules.  Some providers questioned why they should spend time and money sending standardized data when many public health jurisdictions could not accept it electronically.   Thus these efforts resemble half-built bridges, with those on neither shore willing to invest enough to finally meet in the middle.

The MU Workgroup decisions reflect a narrowing of HITPC focus from simultaneously meeting five large social goals (one being improving public and population health) to enabling “transformation of care” as envisioned in medical homes and accountable care organizations.

Some providers might enjoy short-term savings by avoiding MU standardized reporting, but then face ongoing costs and retarded outbreak response associated with inefficient manual reporting.  Of course such cost-efficacy depends on health department adoption of standardized electronic reporting.  Progress was reported in 2013 with 95% of jurisdictions receiving some ELR, and the share of 20 million annual reports received electronically rising 62% from 54% in 2012. That represents 1,600,000 fewer manual reports yearly and 1,600,000 more communicable illnesses addressed more quickly and efficiently, just in the earliest stages of MU.

Public health advocates are typically best represented at the MU workgroup level, so greater effort is required to modify HITPC recommendations and proposed rules changes. The MU Workgroup will return to the discussion (unclear how final are the recommendations at this point) on  March 4 and it seems likely HITPC will take up the topic March 11.  Interested parties can tune in.  Health.e.volution has learned the Joint Public Health Informatics Task Force of public health associations is crafting a strategy, so concerned agencies and individuals can contact their association to get involved.

Atlanta Networking Sept. 19

Please share as desired with those interested in health informatics.   I look forward to seeing you in Decatur September 19.

Stage 2 MU Guidance for Health Departments Published, Funding Lags

The first year of Stage 2 Meaningful Use requirements is coming up fast (October, 2013).  Meaningful use participants will need to achieve ongoing submission of public health reports to health departments.  A multi-organizational taskforce has issued guidance materials for local and state health departments to help them 1) declare their readiness to receive data from eligible professionals (EPs) and hospitals (EHs); 2) establish systems whereby EPs and EHs register their intent to submit data; 3) on-board data submitters; and 4) provide necessary acknowledgement of on-going data submission.  That’s a lot to get ready for!  (Some health departments are also acquiring electronic health record (EHR) systems and will themselves need to demonstrate that they are meeting other Meaningful Use objectives as well.)

Unfortunately, as in earlier years, the President’s FY 2014 proposed budget fails to include dedicated funding to help health departments exchange information with EHR systems (with the notable exception of the National Healthcare Safety Network, which is not part of Stage 2 Meaningful Use regulations).  State health departments are heavily dependent (45%) on federal funding, especially from the Centers for Disease Control and Prevention (CDC).  While several CDC funding programs encourage recipients to use funds for achieving connectivity for Meaningful Use Population and Public Health objectives, CDC’s proposed budgets for programs that would support meaningful use objectives (like immunization and emergency preparedness) would shrink in 2014.  Health departments may indirectly benefit from increased funding for ONC if it facilitates health information exchange, and in a few states partial funding for public health information exchange is addressed in state Medicaid plans.  Most affected health departments will need to make do with existing or shrinking resources as Stage 2 ratchets up expectations.

The ONC’s budget proposal (page 33) seems to suggest that ONC is establishing a dashboard of public health participation in meaningful use information exchange.  This would be an important indicator for policy-makers and public health advocates to watch.

Who will you meet? Food, drink, informatics networking in DC near TEDMED April 18

Join our first Washington DC area INTERFACE networking salon for those interested in improving public health through informatics.   After work, just blocks from TEDMED 2013 –there’s no telling who you’ll meet!  Join us Thursday, April 18 from 5:30-7:00 pm at the Notti Bianche bar inside GW University Inn, 824 New Hampshire Blvd NW.   Just steps from the Foggy Bottom Metro.  No charge; excellent food and drink available for purchase.   RSVP at sfoldy@sbcglobal.net.  Pass it on!

Meaningful Use and the Learning Health System-HIMSS

At the 2013 Health Information Management Systems Society (HIMSS) meeting in New Orleans on March 3 I’ll provide guidance to the Physician IT Seminar on how to convert Meaningful Use advances in electronic health records and health information exchange into real learning opportunities to improve care and health.  The Institute of Medicine’s vision for a Learning Health System is “by 2020, 90% of clinical decisions will be supported by accurate, timely, and up-to-date clinical information and will reflect the best available evidence.”  How do the Meaningful Use rules carry us closer to this goal?

I’ve diagrammed critical elements for a learning health system, below.  At its base, and most critically, the electronic health record (EHR) captures information.  This may be entered by clinicians, or received from either patients or other health care providers.  This use of the EHR to “learn about the patient” is fundamental to all other improvements in care.

Various objectives in Stage 1 and 2 Meaningful Use require data capture.  They also require that EHRs be able to exchange information with other clinicians and to some extent with patients.  Meaningful Use objectives also require public health reporting, quality reporting, and decision support, each setting the stage for still more sophisticated learning.

Today, naturally, many providers are obsessed with the implementation of the Meaningful Use objectives and the receipt of incentive payments.  But it is never too soon to consider how these EHR objectives can be pressed into the service of “accurate, timely, and up-to-date clinical information and… the best available evidence.” It is already happening.   For example, in late 2012 a mysterious surge in fungal meningitis cases was detected in Tennessee, and was rapidly traced to certain lots of injection steroids produced by the New England Compounding Center.  Little was known about how to treat the predominant fungus,  Exserohilum rostratum.  Investigators used electronic health record reviews to rapidly identify exposed patients, and to track the success of treatment.   A rapid decline in case mortality among infected persons resulted within just two weeks.  That is truly a learning health system in action.*

Information alone does not bring about learning.  Learning requires a “central nervous system” to process incoming information in light of other knowledge.   Public health agencies, like local and state health departments, the Centers for Disease Control and Prevention (CDC), and the Food and Drug Administration (FDA) are examples of such “central nervous systems.”  But a good brain is useless without being attached to sensory and motor organs.   The Exserohilum rostratum outbreak helps show the Meaningful-Use-certified EHR is beginning to serve a valuable sensory function.   Equipped with decision support tools, it is destined to be a powerful motor organ as well.


*Thanks to the American Medical Informatics Association Public Health Informatics Workgroup for a great webcast on informatics use and needs associated with this outbreak.