Semi-retired, I am trying to organize some memories about what has felt like a pretty remarkable life. Posting them on this website allows friends, family and colleagues to leave embellishments or to correct inevitable errors of memory, fact and attribution. I hope you enjoy the first story describing how in 1977 activists at Stanford University contributed to the fall of apartheid in South Africa.
I stepped away from this website and closed my consulting business in 2017 when I joined what is now the Public Health Institute at Denver Health, supervising epidemiology, emergency response and informatics innovation. After responding to COVID-19, hepatitis A and fentanyl epidemics I’ve semi-retired. I am now donating my time to CDC/associations to establish public health Fast Healthcare Interoperability Resources (FHIR) and the International Joint Commission to prepare for climate change health effects along US-Canada boundary waters.
I’ll post about current activities here, and will likely add some remembrances too. I hope others’ comments will help repair any false memories, of which there are likely to be a few!
Thanks to all who remain part of my professional and personal cadre.
How do changes in the environment affect human behavior and human health? Even events as traumatic as the 2010 Deep Horizon oil rig disaster left few fingerprints of mental or behavioral effects using traditional public health survey technology. Are there few effects, or do traditional methods fail to discern them? The inability of hypothesis-driven surveys to yield medical diagnoses doesn’t mean that families’ health behaviors, social or economic well-being and connection to the gulf haven’t changed in meaningful ways.
Sudden changes to local waters can create big effects. The 1993 Milwaukee cryptosporidium outbreak (from Lake Michigan drinking water) killed nearly 100 people and left an entire city on edge for years every time it rained heavily. 2014’s sudden, if temporary, loss of municipal drinking water in Toledo, OH (due to harmful algal blooms) and Charleston, WV (due to a chemical spill) indicate how fragile human health and community well-being are in the face of sudden environmental changes (which will increase with anthropomorphic climate change). Gradual changes in environmental quality, such as mercury and PCB contamination of fish and rising beach closings from sewage pollution affect large populations and major economic activities, but their effects are harder to assess.
Does environmental degradation spur diarrhea or depression, anxiety or apathy, fishing or flight? What is the time course and effect size of different types of events on both human health and human attitudes? Historians and archeologists try to answer such questions using old letters, diaries and physical evidence. Today massive new caches of information have become far more immediately available as each of us leaves a near-real time internet trail of observations (posts, photos), emotions (“likes”, emoticons and “flameouts”), actions (consuming, advocating), location changes (visiting, avoidance, in- or out-migration) and physiologic measurements (from our FitBits and Apple watches). These data are now time-stamped, geo-positioned, #hashtagged and otherwise encrusted with useful metadata. Methods to create, mine and understand such massive, untidy data are evolving as rapidly in civil society/non-profit organizations, marketing firms, and technology start-ups as in academia or government.
I was recently honored to be named US co-chair of the Health Professional Advisory Board (HPAB) of the International Joint Commission (IJC), a treaty-based organization that has been preventing and resolving US-Canada conflict over our thousands of miles of shared shorelines and waters since 1907. IJC has issued a Request for Information (due July 24, 2015) asking businesses, civil society organizations, academics, government agencies and individuals to describe or propose how to use social networking and similar internet information to study changes in human health and behavior contemporaneous with environmental change in our boundary waters. Please forward this Request for Information to anyone who might be able to contribute.
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.)
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?
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!
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!
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.
Please share as desired with those interested in health informatics. I look forward to seeing you in Decatur September 19.
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.