When public health captures standardized data by using an electronic health record (EHR) with a standardized taxonomy it gives public health professionals a powerful voice in the healthcare marketplace.

A review of the evolution of public health and its correlation to data collection and use will help clarify the importance of good solid data.

Public Health 1.0 (late 19th to late 20th century)

Modernization of public health practice during the Public Health 1.0 era included advances in vaccines, antibiotics, epidemiology, lab sciences, developing a system of sanitation, and establishing standards in food and water safety but, while public health practice was advancing, the methods used to record that practice were not.

Data collection in this era:

For most of this era, pen and paper were used to record data. From quills to ballpoint pens, from parchment to modern paper mediums, although technology brought convenience, the basic limitations of data documentation remained the same. While pen and paper were quick to capture data, the data was imprisoned on that paper for life!  Aggregate data could not be pulled from paper records without tallying hash marks garnered from multiple individual records.

Public Health 2.0 (1980s to late 2010s)

The 1988 Institute of Medicine (IOM), now the National Academy of Medicine, report, The Future of Public Health1 is largely accepted as the catalyst for Public Health 2.0. The report ushered in an era of defined functions for public health (assessment, policy development, and assurance). Performance standards were established for public health, and it became more professionalized.

The IOM committee had felt that public health was too focused on providing clinical care and was unprepared for the future – a future defined by the advent of chronic diseases like the HIV/AIDS epidemic. Public Health 2.0 defined an era in which public health became more focused on improving health through prevention, management, and treatment of diseases.

Data collection in this era:

While the early versions of electronic health records (EHRs) began to be developed in the 1960s and sparsely used in the 1970s and 1980s, it was not until the early 1990s that the Institute of Medicine (IOM) published a study recommending the use of EHRs to improve patient records. However, as this article explains, “widespread use of EHRs was delayed by high costs, data entry errors, poor initial physicians’ acceptance, and lack of any real incentive.” The move from paper records took even longer for public health departments. In fact, by 2013, still only 22% of public health departments were reporting a successful EHR implementation!

Without structure and reportability, it was difficult to demonstrate the real impact of public health work in communities or the outcomes for clinical interventions.

State and Federal data ‘silos’ were developed to capture local public health data in large databases, located remotely at the State Department of Health or a Federal agency. While these systems were good at capturing data entered directly into their screens, they lacked the ability to provide evidence-based outcomes and gave precious little to no data back to local health departments.

The Great Recession of 2008 brought budget cuts and huge losses in personnel. Many health departments lost funding for important programs, with communities who were most in need being hit the hardest by reduced funds. The whole system began crumbling.

Public Health 3.0 (late 2010s to present)

Public Health 3.0 is a more sharply defined focus on addressing ALL the factors that affect a person’s overall health — the social determinants of health or “the conditions in which people are born, live, work, and age.” (OASH Public Health 3.0 whitepaper)

In 2016, the Office of the Assistant Secretary for Health (OASH) released a whitepaper entitled, Public Health 3.0: A Call to Action to Create a 21st Century Public Health Infrastructure. While public health departments had come so far and had so much success transforming communities’ health, there was still something missing: equity.

In that whitepaper, Karen B. DeSalvo, MD, MPH, MSc, then Acting Assistant Secretary for the US Department of Health and Human Services (HHS), says, “…The challenge now is to institutionalize these efforts and replicate these triumphs across all communities for all people. Our collaborative action must ensure, for the first time in history, that every person in America has a truly equal opportunity to enjoy a long and healthy life.”

A primary goal of PH 3.0 was to proactively uncover the root causes of public health indicators, that may otherwise remain hidden for years before they emerge as chronic health issues in children, teens, and adults. As a result, health departments began documenting social determinants of health, adverse childhood experience (ACE) scores, etc.

Data collection in this era: The crucial need to collect standardized data

Public Health 3.0 focuses on cross-sector collaboration, drawing in community partners to help address community needs holistically. As a result, the ability to collect meaningful data, share it, and communicate it effectively became crucial.

To share data broadly, that data must be built upon a common language or ‘taxonomy’. If we do not use an established standard, then it will be almost impossible to accurately assess data coming from multiple providers. To successfully become a community Chief Health Strategist, public health data must be consumable and mapped within the data collection system.

Startlingly however, most EMRs and EHRs on the market for use in public health today, are not built with a recognized nursing Language! Some health records have even refused to use a standard language and substituted their own ‘proprietary’ language, only allowing their users to communicate with other users of the same system.

Data collection for the modern public health department

Failure to utilize a standard language amplifies the problem of communication as public health documentation evolves and becomes more and more sophisticated.

The primary goal in Public Health 3.0 is to detect early health indicators and address adverse impacts to a community’s health upstream.  How can a state health department compare one county’s data to another, without using a common standard? How can the health departments compare one neighborhood to another without a standard measurement? If you cannot measure your impact, how can you prove it? How can you improve on it?

Standardized taxonomy is critical for good data

As you can see, a standardized taxonomy is critical for the forward-thinking public health department.

To measure what you are doing and determine the impact of those activities on your community, there must be a standard measurement from nurse to nurse, client to client, and location to location.  Much like the 1-foot ruler that is so widely accepted as a standard today.

Because we all agree that 12 inches equals 1 foot, we can communicate accurately.  But you don’t have to go very far back in history to discover that the length of a ‘foot’ has varied over time and was understood differently by time, by culture, and even by location. Trying to build a house together while maintaining proprietary ‘lengths’ considered a ‘foot’ would make the house lean one way or the other or even topple over!

We see the same issue with some public health data when a vendor ignores the American Nurses Association – recognized, standardized taxonomy, and substitutes their own ‘homemade’ documentation schema. How can we merge, aggregate, or compare and contrast our data?

The standards a standardized taxonomy should meet

If you’ve read our article, What Criteria Should a Standardized Terminology Meet, you know not all standardized taxonomies/standardized terminologies are created equal. The Omaha System is an excellent example of what standards a public health department should hold for the standardized taxonomy they choose to use. Why?

The American Nursing Association (ANA) has recognized 12 standard nursing languages however, of those, only three can be used in nursing practice, the others are for academic and theoretical use. Out of the three used for nursing practice only one, the Omaha System:

  • Supports inter-professional practice (this is critical for Public Health 3.0)
  • Maps nursing documentation to SNOMED-CT (this is critical for Public Health 3.0)
  • Contains all three components:
  • Assessment – Surveillance
  • Intervention – Performance
  • Outcomes – How the client’s health was impacted

The Omaha System offers multiple advantages:

The Omaha System gives you the ability to accurately compare, merge, and dovetail data, with each piece of data enhancing the understanding of the overall picture. Cross-sector collaboration using this data builds a strong, solid data set.

The Omaha System provides:

Instead of creating a pieced together ‘house of cards,’ instead your data accurately proves your impact and, as a result, raises the value of the work you do in your communities as public health professionals.

Using a standardized taxonomy with evidence-based outcomes, gives you a powerful voice to impact public health policy and direction. By using a common language, the aggregated data can paint the big picture of what is going on and display for the world that public health prevention has far-reaching impact.

Next Steps

First, ask yourself if your data delights you. If your data does not delight you, you should look for a new EHR, one that:

  • Was built specifically for Public Health/Community Health
  • Utilizes an ANA-recognized language for documentation
  • Offers evidence-based outcomes to prove impact
  • Incorporates Social Determinants of Health
  • Can document community interventions (community as the client)
  • Is mapped to SNOMED-CT
  • Can exchange meaningful, standardized data with other non-proprietary systems

To learn more, download our e-Book, Standardized Terminologies for EHRs.

If you’re ready to see an EHR that can offer you everything we’ve talked about, request a demo or price quote of our EHR, Nightingale Notes today!

References:

  1. Institute of Medicine. The future of public health. Washington (DC): The National Academies Press; 1988