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Development of a New Fleet Disease and Injury Surveillance Capability Using ESSENCE

Image of 36936513. The new capability of using in-theater data in ESSENCE enables unprecedented, near real-time disease and injury surveillance for the U.S. Navy fleet.

2/1/2025 By: Wendi S. Bowman, MPH; Sasha A. McGee, Ph.D., MPH; Lisa A. Pearse, M.D., MPH; Courtney Coker, MS, MPH; Jamaal A. Russell, Dr.P.H., MPH; Asha J. Riegodedios, MSPH

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Abstract

Historically, disease and illness surveillance on U.S. Navy vessels relied on weekly data updates and required manual data processing. Established surveillance approaches for fixed military hospitals and clinics were not designed to be applied to the highly mobile populations aboard ships. This paper describes the development of a new surveillance capability through utilization of the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE). The pilot program successfully instituted a near real-time D&I surveillance system defined for shipboard operations. Following initial data and system assessment, an operational surveillance strategy was developed and implemented at the Navy’s four regional Navy Environmental and Preventive Medicine Units responsible for global fleet assets. Despite early implementation challenges, preventive medicine users reported that the fleet ESSENCE system was effective in identifying potential outbreaks, with sufficient efficiency for daily surveillance.

What are the new findings?

This new capability using in-theater data in ESSENCE enables unprecedented, near real-time D&I surveillance for the U.S. Navy fleet. While currently targeting gastrointestinal and respiratory illness trends, the infrastructure has flexibility to add new modules in response to fleet and preventive medicine requirements.

What is the impact on readiness and force health protection?

High quality D&I surveillance of operational forces by Navy preventive medicine assets accelerates technical support and response to outbreaks and other public health threats. Rapid implementation of appropriate control measures is the key to minimizing the effect of these events on both the force and the mission.

Background

Force protection against public health threats depends on timely, accurate public health surveillance data. A robust and flexible disease and illness surveillance system is imperative for the U.S. Department of the Navy, due to its highly mobile population with frequent missions to isolated and resource-limited locations around the globe, confined living conditions aboard ships, and the dynamic nature of diseases.

Historically, D&I surveillance involved labor-intensive, manual methods that produced weeks-long delays in situational awareness.1-5 U.S. Navy vessels have since adopted electronic health record capabilities, allowing more time-efficient D&I surveillance methods. Shipboard medical visits are entered into Armed Forces Health Longitudinal Technology Application-Theater (AHLTA-T) or Shipboard Automated Medical System, employing a ‘store and forward’ model designed for low communication environments; data are stored until internet connectivity is available, at which time they are transmitted to a central data repository, the Theater Medical Data Store. With the recent addition of TMDS data into the Department of Defense’s Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE), the Navy and Marine Corps Force Health Protection Command proposed an initiative to advance an automated D&I surveillance capability.

Millions of outpatient medical encounter records and laboratory results are systematically queried using ESSENCE, to detect health events of potential public health significance and support public health investigations.6 Since 2003, ESSENCE began supporting force health protection by collecting near real-time health surveillance data on U.S. military health system beneficiaries from on-base, fixed location military hospitals and clinics. Beginning in 2017, the Armed Forces Health Surveillance Division Integrated Biosurveillance Branch worked to acquire mobile, forward-operating clinical data from the TMDS, structured those data for ESSENCE integration, and collaborated with security experts to mitigate potential risks associated with data access. By October 2022, TMDS data became available to selected ESSENCE users for evaluation and pilot testing and, since June 28, 2024, have been ingested into ESSENCE in batches every 12 hours. This integration of TMDS data with ESSENCE provided the NMCFHPC with an opportunity to improve maritime situational awareness.

This report details the steps taken to develop a timely, accurate, and comprehensive Navy fleet D&I surveillance capability, along with the successes and challenges that will guide further refinement and expansion of this tool.

Methods

From October 2022 until June 2023, AFHSD-IB and NMCFHPC worked together to develop and test the initial surveillance capability. The implementation plan 1) assessed TMDS data quality and the utility of available ESSENCE analytic tools, 2) developed an initial shipboard surveillance capability for regional surveillance, 3) recommend and implemented ESSENCE system improvements, and 4) tested and evaluated the capability.

Data Assessment

An initial assessment of ESSENCE TMDS data in January 2023 demonstrated a total of 246 data fields, including many necessary for operational health surveillance, such as patient and reporting unit, demographic fields, clinical notes and vital statistics, laboratory and pharmacy data, discharge diagnosis codes, chief complaints, and D&I category fields. While many fields were sufficiently complete for both surveillance and disease threat characterization, they were often difficult to query due to unstructured formats (i.e., use of free text). The completeness of ship data was evaluated using the Navy Vessel Register.7 The list of expected ships (excluding inactive ships, those in Navy Sealift Command, and forward medical units not identified as ships) were compared to ships with data recorded in ESSENCE at least once from January 2022 through December 2023.

Table of percentage of ships with data in ESSENCEFrom January through June 2023, over 75,000 health care encounters on U.S. Navy fleet vessels were captured in ESSENCE. Approximately 81% of expected ships had encounters documented. The distribution of health encounters, by ship size, is shown in Table 1.

Data timeliness was assessed based on the difference between the date of the health care encounter and when the data were uploaded into ESSENCE, for those ships with data in ESSENCE (Table 2). An ESSENCE upload date signifies the most recent date a record is updated rather than the date the record was first received, so observed timeliness in Table 2 may overestimate the true interval. Within 10 days, 78% of clinical encounters were visible in ESSENCE. Encounter data from smaller ships were not as timely as data captured from larger ships.

Table of percentage of health encounter records

Table of observations, findings, associated actions for development of fleetsurveillance capability using ESSENCE TMDS dataSystem Assessment

NMCFHPC’s qualitative review of ESSENCE’s functionality and capability revealed several issues that required resolution with the AFHSD-IB ESSENCE team. In some cases, the ESSENCE developers modified the system’s functionality to address limitations. Several modifications were implemented to improve user experience and better meet surveillance needs (Table 3). Other issues were addressed through ESSENCE queries designed to minimize data quality limitations.

Shipboard Surveillance Pilot

NMCFHPC’s fleet surveillance methodology for the pilot program involved the creation of dashboards to visually display time series graphs of the query results. A series of graphs were initially generated to determine the best way to aggregate data for ships (e.g., as a function of ship size, geography, mission relevancy, syndrome category) to facilitate efficient data review. Displaying data for a single ship in each time series graph was found to be optimal for ease of data review and interpretation (Figure 1).

Three outcomes of interest were selected to be displayed on dashboards as time series graphs: all daily health care encounters for the past three months, weekly gastrointestinal illness encounters for the past year, and weekly respiratory illness encounters for the past year. Ships were divided into four geographic areas, representing each of the Navy’s four regional Navy Environmental and Preventive Medicine Units, based on home port as indicated in the Naval Vessel Register.7 Time series graphs for all ships associated with a specific NEPMU (range: 16-73 ships) and specific outcome were displayed on a single dashboard. In the end, over 600 time series graphs were developed to form the final set of 12 total dashboards (with three outcomes per NEPMU).

Fleet surveillance was initiated for all four NEPMUs from April through June 2023, following individual training and distribution of a companion training guide. Each NEPMU had one to three users (either environmental health officers, preventive medicine physicians, or preventive medicine technicians) who were tasked with reviewing the dashboards (Figure 1) at least twice per week to identify trends that indicated a potential public health concern. When unusual trends were observed, NEPMUs viewed a listing of individual encounter data (clinical notes, demographics, discharge diagnosis, lab results) for a specific date to facilitate their initial public health threat assessment. Findings suggesting a potential outbreak triggered communication between NEPMU and the ship for support.

During the pilot program, one NEPMU began closely monitoring a large ship with an apparent gastrointestinal outbreak. Before initiating contact with the ship, a risk assessment was completed within minutes, based solely on the ESSENCE data details. Analysis revealed that most patients had similar symptoms, and before their illness, many patients reported consuming street food during a recent port visit. Norovirus was laboratory confirmed as the etiologic agent. Details were confirmed upon direct communication with the fleet. The ESSENCE gastrointestinal illness dashboard continued to be used for ongoing monitoring of control measure effectiveness during the outbreak, which took more than three weeks to resolve (Figure 2).

FIGURE 1. Time Series Graphs for Gastrointestinal Diseases Reported from Individual U.S. Navy Ships. This figure is a compendium of four graphs, each of which presents one line along the horizontal, or x-, axis that depicts the number of gastrointestinal diseases reported from a specific (anonymous) ship in the U.S. Navy over the course of 52 weeks, from the sixteenth week of 2022 through the sixteenth week of 2023. The horizontal, or x-, axis is divided into 52 units of measure, each representing an individual week. The vertical, or y-, axis indicates the number of recorded gastrointestinal diseases. One dot, representing the total reported gastrointestinal diseases, is plotted for each week. Each individual graph displays the number of reported cases , commensurate with the degree of incidence and ship size. Two graphs present data from two different medium sized ships, one graph presents data from a small ship, and another from a large ship. The dots representing the total reported gastrointestinal disease cases for a specific week are color-coded: blue for a normal range, yellow for a level indicating warning, and red for an alert. The warnings and alerts occurred at different weeks during the same year, with each ship having a minimum of two weeks with alert levels. The large ship’s two weeks of alert levels were consecutive, with a dramatic decline back to normal immediately thereafter; the small ship’s two weeks of warning levels were separated by four full weeks of normal levels, with zero or only one report in those weeks. The small ship is reported on a scale of one to three reports on the y axis; the large ship is reported on a scale of zero to 25, and its two weeks at alert level involved reports above 20 in the first week and 25 in the second week. The small ship had eight total reports and an annual count average of 0.15. This ship had 290 total reports and a count average of 5.47. The two medium sized ships demonstrated drastically different levels of variation. One medium ship had nearly zero infections for approximately 35 weeks, with four consecutive weeks at warning level—but cases still below five each week, and five weeks, with only two consecutive, at an alert level but reports at five or less in those weeks. During the last week of the surveillance period, however, the first medium sized ship jumped from an alert level with under 10 reports to approximately 70, necessitating the largest scale for a y axis among the four graphs. This ship had 110 total reports and a count average of 2.08. The other medium sized ship expressed much greater variability in its case counts, only reporting cases near zero for one week, with cases consistently around 10 per week and spiking to above 25 in two weeks; only two other weeks were labeled at a warning level, just below 20 cases, although four other weeks had equal or higher case counts and were labeled as normal. This ship had 574 total reports and a count average of 10.83.

FIGURE 2. Gastrointestinal Health Encounters Onboard a U.S. Navy Ship Experiencing an Outbreak, May 2023–August 2023. This graph one line along the horizontal, or x-, axis that depicts the number of gastrointestinal health encounters reported from a specific (anonymous) ship in the U.S. Navy that experienced an outbreak of gastrointestinal disease over the course the late spring and summer of 2023. The horizontal, or x-, axis is divided into 24 units of measure, each representing five calendar days, starting from the beginning of May through the end of August. The vertical, or y-, axis indicates the number of recorded gastrointestinal health care encounters, labeled in units of 5, to 40. Specific daily data reports of significant numbers are labeled as either yellow squares, which indicate an alert level, or red dots, which indicate a higher level of alert. Only three days, which were close in time but non-consecutive, were labeled as yellow alerts. Four days, one between the first two yellow alerts, and the other three, consecutively, preceding the third yellow alert, were labeled as red alerts during that same period, reaching a peak of just over five reports. One week elapsed with lower numbers and no alerts, but at the start of the second week of June, three consecutive days were labeled as red alerts, with similar report numbers. Reports then subsided for nearly three weeks, with no alerts and reports well below five per day, but on the last day of June reports suddenly increased to approximately 13 in one day and stayed at that level for one week—with only one day, with nearly no reports, not labeled at red level. After a dramatic decline in reports for three days, case numbers spiked to their highest levels for five consecutive days, peaking at 25, and then declining again for two days to below five, and then rose even higher, exceeding 35 reports each day for three days (with a fourth day at only 20 reports). A week of high variability but declining reports followed, and by the beginning of August reports were consistently below five in number, and remained at that level.

Three months after the pilot program was initiated, user responses on the utility of the ESSENCE shipboard dashboards, as an integrated part of routine surveillance at the NEPMU, were collected via electronic survey, administered with Microsoft 365 Forms. Virtual user forums served as a mechanism for gathering additional details on strengths and limitations, developing potential solutions to those limitations, and informing a plan to expand the capability throughout the fleet public health community.

Responses indicated that each NEPMU had at least one intermediate or advanced user with prior ESSENCE experience. The frequency of dashboard review varied depending upon ship distribution within a regional area. The NEPMU with the fewest ships reported that dashboard review once a week was sufficient, due to other available surveillance methods; NEPMUs with more ships reported reviewing their dashboards daily. NEPMUs reported being able to easily identify concerning trends using the dashboards within 15-30 minutes, with additional time needed when a review of underlying data was necessary. Users also noted timely data updates for many ships within ESSENCE, particularly ships with larger populations. Notable challenges included reports of the system being slow at times, and low numbers of encounters that complicated trend detection and quick risk assessments. Users also reported that data interpretation was complicated by a lack of understanding of various EHR data entry challenges aboard ships, such as software technical issues, paper record use, and intermittent electronic communication access.

Discussion

This report recounts a major advancement in timely and reliable public health surveillance for ships, made possible through use of ESSENCE TMDS data. Surveillance methodology using ESSENCE for on-base military hospitals and clinics could not be applied to fleet surveillance due to differences in both data structure and populations served (i.e., smaller, healthier, closed populations aboard ships).8 This pilot program developed, within three months, a new capability to monitor mobile populations ranging from 50 to 5,000 people that addressed their complexities and unique challenges.

In the past, D&I surveillance involved collecting and compiling reports from individual ships, a time-intensive multi-step process, but now data are automatically collected and available every 12 hours, a major advancement. This new capability supports expeditious and efficient data review, facilitates communication between the fleet and preventive medicine experts, and contributes to disease outbreak identification and containment.

Initial data assessments for this pilot program revealed remarkably higher levels of completeness and timeliness compared to legacy D&I surveillance strategies.4,5,9 Nearly three-quarters of encounters for ships (with all sizes combined) were visible within seven days, a notable improvement over the weeks-long delays with earlier methods. These gains in data timeliness and completeness were achieved without requiring additional time or effort from a ship’s medical staff. Nonetheless, the delay between the health care encounter date and the ESSENCE upload date is a potential limitation that may require further study to improve this surveillance capability.

Several challenges had to be overcome for this pilot program’s success. Lack of standardized discharge diagnostic code usage was problematic, likely due to lack of synchronization of updates to shipboard information technology. For ships still using International Classification of Diseases, 9th Revision, Clinical Modification codes, queries were developed using chief complaint text. The field containing the ship name was unstructured (i.e., utilized free text) and names were not entered using a single standardized naming convention, presenting another major barrier. Hundreds of queries had to be developed and refined to obtain reliable results for ship-specific data. The final set of queries were complex, as a result of accounting for various naming patterns observed in the data. Periodic data review and revisions will be necessary to ensure queries continue to reliably capture ship data as expected. Ongoing, collaborative engagement between military surveillance experts (AFHSD-IB and NMCFHPC), the ESSENCE developers, and theater data owners was essential for the success of this pilot program.

Two major challenges remain. The first challenge is the need to develop more efficient methods of surveilling shipboard populations with low numbers of health care encounters. Medical departments on smaller ships may only see 5-15 patients a week, making the determination of daily trends for specific outcomes (e.g., gastrointestinal illness, respiratory illness) difficult. The surveillance of all health care encounters, instead of individual syndromes, was evaluated as a solution but was further complicated by large numbers of periodic administrative encounters that interfered with the detection of potential public health threats. The second challenge involves intermittent data gaps in ship time series graphs, which can interfere with data trend interpretation. Anecdotal evidence suggests that these gaps are related to routine shipboard operations (e.g., maintenance, pulling into port). Geographic-specific operations or EHR system technical limitations may also lead to temporary use of paper medical records. More study is needed to fully assess these occurrences and develop approaches to improve the reliability of fleet surveillance.

This new capability provides an extraordinary opportunity to expand and improve operational fleet D&I surveillance. The methods and framework developed by this pilot program can be further adapted and expanded for surveillance of other health events of interest, such as injuries and mental illnesses. Additionally, the availability of near real-time data that are accessible by public health responders is ideal not only for threat detection, but reviewing and pursuing data quality improvements. Although mechanisms may differ, expansion efforts are being pursued. ESSENCE TMDS data were used for surveillance during a military exercise, Exercise Talisman Sabre 2023, and provided effective, timely public health information beyond outbreak-specific surveillance. Near real-time D&I surveillance promotes enhanced situational awareness at regional commands as well as headquarters, facilitating development of operational plans that can mitigate potential public health threats as early as possible. 

Author Affiliations

Battelle Memorial Institute, supporting U.S. Navy and Marine Corps Force Health Protection Command, Portsmouth, VA: Ms. Bowman; Integrated Biosurveillance Branch, Armed Forces Health Surveillance Division, Public Health Directorate, Defense Health Agency, Silver Spring, MD: Dr. McGee, Dr. Russell; Navy and Marine Corps Force Health Protection Command, Portsmouth: Ms. Coker, Dr. Pearse, Ms. Riegodedios

Acknowledgments

The authors would like to thank the many experts who contributed to the success of this collaborative effort, including participating Preventive Medicine and Environmental Health officers and Preventive Medicine technicians of the 4 regional U.S. Navy and Environmental Preventive Medicine units; U.S. Naval Forces Europe and U.S. Sixth Fleet; the Johns Hopkins University Applied Physics Laboratory; the Defense Health Agency's Joint Operational Medicine Information Systems Program Management Office; CDR Lucas Johnson from NMCFHPC, for strategic direction; CDR Eric Larsen from NEPMU-5, for insightful and continual recommendations during the pilot; and Ms. Digna Forbes from NMCFHPC, for support with pilot implementation.

Disclaimers

The views expressed in this article are those of the authors and do not necessarily reflect official policy nor position of the Department of Defense, Defense Health Agency, Department of the Navy, or the U.S. Government. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the U.S. Navy. Several of the authors are U.S. Government employees. This work was prepared as part of official duties. Title 17 U.S.C. §105 provides that Copyright protection under this title is not available for any work of the United States Government. Title 17 U.S.C. §101 defines a U.S. Government work as a work prepared by a military service member or employee of the U.S. Government as part of that person’s official duties. This material is based upon work supported by the DOD Information Analysis Center Program Management Office (DoD IAC PMO) and sponsored by the Defense Technical Information Center (DTIC) and the Navy and Marine Corps Force Health Protection Command (NMCFHPC) under contract FA807518D0005-FA807523F0016.

References

  1. Navy and Marine Corps Public Health Center. Navy and Marine Corps Public Health Center Technical Manual NMCPHC-TM 6220.12: Medical Surveillance and Reporting. U.S. Dept. of Defense. 2013. Accessed Apr. 8, 2024. https://www.med.navy.mil/navy-and-marine-corps-force-health-protection-command/preventive-medicine/programand-policy-support/disease-surveillance 
  2. Shaw E, Hermansen L, Pugh W, et al. Disease and Non-Battle Injuries Among Navy and Marine Corps Personnel During Operation Desert Shield/Desert Storm. Defense Technical Information Center, U.S. Dept. of Defense. Accessed Apr. 8, 2024. https://apps.dtic.mil/sti/citations/ada250652
  3. Pugh WM. A Strategy for Computing Disease and Non-Battle Injury Rates. Defense Technical Information Center, U.S. Dept. of Defense. Accessed Apr. 8, 2024. https://apps.dtic.mil/sti/citations/ada223916 
  4. Kauvar DS, Gurney J. Exploring nonbattle injury in the deployed military environment using the Department of Defense trauma registry. Mil Med. 2020;185(7-8):e1073-e1076. doi:10.1093/milmed/usz481 
  5. Bohnker BK, Sherman SS, McGinnis JA. Disease and nonbattle injury patterns: afloat data from the U.S. Fifth Fleet (2000-2001). Mil Med. 2003;168(2):131-134. doi:10.1093/milmed/168.2.131 
  6. Burkom H, Loschen W, Wojcik R, et al. Electronic surveillance system for the Early Notification of Community-Based Epidemics (ESSENCE): overview, components, and public health applications. JMIR Public Health Surveill. 2021;7(6):e26303. doi:10.2196/26303 
  7. Naval Sea Systems Command. Navy Vessel Register. U.S. Navy, U.S. Dept. of Defense. Accessed Dec. 15, 2023. https://www.nvr.navy.mil 
  8. Meadows SO, Engel CC, Collins RL, et al. 2018 Department of Defense Health Related Behaviors Survey (HRBS): Results for the Active Component. RAND Corporation. 2021. Accessed Sep. 5, 2024. https://www.rand.org/nsrd/projects/hrbs.html 
  9. Hauret KG, Pacha L, Taylor BJ, Jones BH. Surveillance of Disease and Nonbattle Injuries During US Army Operations in Afghanistan and Iraq. US Army Med Dep J. 2016;(2-16):15-23. https://medcoeckapwstorprd01.blob.core.usgovcloudapi.net/pfw-images/dbimages/apr-sept2016.pdf

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