THE MEANINGFUL USE OF ELECTRONIC HEALTH RECORDS FOR

SYNDROMIC SURVEILLANCE: ZIKA VIRUS

Eeshika Mitra, BDS

MPH Epidemiology Class of 2016

Texas A&M Health Science Center School of Public Health

Objective

To analyze the effective use of the Electronic Health Records, their strengths and limitations in the

existing syndromic surveillance systems and comparison of different systems for improved reporting of outbreaks

Background

The earliest idea of recording patient information was introduced first in the 1960’s by Larry Weed who

introduced the concept of the Problem Oriented Medical Record into medical practice [14]. The first

medical record system was invented by Regenstrief Institute in 1972.

Brief Background:

In accordance with the HITECH Act and Stage 3, the federal government has made available

incentive payments for the implementation and Meaningful Use (MU) of the Electronic Health

Records (EHR) totaling up to $ 27 billion over 10 years with $44,000 (Medicare) and

$63,750(Medicaid) [6].

Why this study:

- With the collaborative efforts of the Medicare and Medicaid Services (CMS) taking the lead and

the Department of Health and Human Services (DHHS) , standardization and criteria for the

“Meaningful Use” of the Electronic Health Record” to improve the reporting of notifiable disease is

being made [6].

- In order for the EHRs to support improved health care, a set of core and menu objectives are

designed in the final regulation to be implemented by hospitals and eligible professionals.

Importance to Public Health professionals for surveillance purposes:

Some of the core set of objectives mandate recording of patient information like patient

demographics (sex, race. date of birth, date of admission to hospital etc.), submit electronic data

on reportable diseases and help in the health information exchange across health agencies for

communication during an outbreak [6].

Difference between an EMR and EHR:

- EMR is used by the physicians and include scheduling, patient registration, writing prescriptions,

receiving lab reports etc. while the EHR is used to transmit health care related data and their

functions include authentication of patient and providers, drug claim adjudication, hospital

discharge summaries, secure messaging etc.

- Major vocabulary standards required to record symptom and diagnostic information used in the

EHR systems are SNOMED (symptoms), ICD-9CM (diagnoses), AHFS and ATC (medications), LOINC (laboratory information) and CPT (procedure codes used for billing purposes).

(2)

EHRs: Advantages and Syndromic surveillance In the study performed in North Carolina, case reporting efficiency was shown to be substantially improved even in smaller

Local Health departments by implementing best practices of EHR with reduced expenses.

EHRs use data from automated medical record systems with insurance coverage, give individuals reason to believe that

the data is complete. Also, individuals can receive a strong financial incentive to receive care from their providers since their

clinical information is reported to the insurer for reimbursement purposes [1].

There is some degree of criterion validity for the data presented, when similar patterns of illness is observed over time in

specific disease surveillance systems , hospital discharge records or any other large ambulatory care record system [1].

During the aftermath of the attacks on September 11, 2001, federal state and local public health agencies were able to

implement what is known as the “drop in” surveillance for combatting the adverse health outcomes in New York City and

elsewhere. These were having lower implementation costs as compared to maintaining ongoing syndromic surveillance in

multiple geographic regions [5].

The ROC areas (i.e sensitivity) for the use of structured and narrative EHR data from the Veterans Administration to

detect Gastrointestinal diseases showed high values of 0.75 – 0.92 [15].

Methods - Literature Review

Data Sources: Mesh words were used and search was performed. Prospective trials that

examined the use of EHR and have been successfully implemented in various state and local

health departments for surveillance and measured their effectiveness were included.

A total of 15 articles were found in the existing databases. With a full text review and

abstraction along with arbitration of a second reviewer, 8 articles met the inclusion criteria.

Comparisons were made between the various surveillance systems and a detail analysis of

how the use of these systems varied across different health care settings was studied.

Zika virus is a transmitted by the Aedes Egypti species and also thrives mostly during the

seasons with high rainfall. In Tanzania, the early warning was developed in the States in

collaboration with the Real time Outbreak and Disease Surveillance [RODS] Laboratory . It is

based on the rainfall observations and thus is useful for the prediction of malaria in some

areas. The USAID Africa Data Dissemination website FEWA-NET used rainfall based

indicators to predict the risk for malaria[9]

One study conducted by Jefferson et al, compared three surveillance systems for HINI

Influenza virus surveillance, of which it appeared that the SMOG (Syste`me militaire

d’observation de la grippe) was the best-performing system for the for 2009 A (H1N1)

influenza. The SMOG system had a small number of units participating and so facilitated the

implementation of control procedures and for the purpose of training practitioners[9].

In 2001, with the use of Epicare, clinicians identified 152,435 lower respiratory infection

illness visits that had 106,670 episodes during 1,143,208 person years by the use of the

ICD9CM [1].

References1. Lazarus, R., Kleinman, K. P., Dashevsky, I., DeMaria, A., & Platt, R. (2001). Using automated medical records for rapid identification of illness syndromes (syndromic surveillance): the example of lower respiratory infection. BMC

public health, 1(1), 1.2. http://www.healthcareitnews.com/news/zika-virus-outbreak-makes-disease-surveillance-critical-healthcare-it-tool-expert-says3. http://www.cdc.gov/ehrmeaningfuluse/syndromic.html4. Pavlin, J. A. (2003). Investigation of disease outbreaks detected by “syndromic” surveillance systems. Journal of Urban Health, 80(1), i107-i114.5. Reingold, A. (2003). If syndromic surveillance is the answer, what is the question?. Biosecurity and Bioterrorism: Biodefense Strategy, Practice, and Science, 1(2), 77-81.6. Blumenthal, D., & Tavenner, M. (2010). The “meaningful use” regulation for electronic health records. New England Journal of Medicine, 363(6), 501-504.7. http://apps.who.int/iris/bitstream/10665/204348/1/zikasitrep_5Feb2016_eng.pdf8. http://www.rand.org/blog/2016/02/electronic-health-records-yesterdays-ebola-and-todays.html9. Jefferson, H., Dupuy, B., Chaudet, H., Texier, G., Green, A., Barnish, G., ... & Meynard, J. B. (2008). Evaluation of a syndromic surveillance for the early detection of outbreaks among military personnel in a tropical country. Journal of

Public Health, 30(4), 375-383.10. https://www.healthit.gov/policy-researchers-implementers/meaningful-use-regulations11. May, L., Chretien, J. P., & Pavlin, J. A. (2009). Beyond traditional surveillance: applying syndromic surveillance to developing settings–opportunities and challenges. BMC Public Health, 9(1), 1.12. Cox, J., Abeku, T., Beard, J., Turyeimuka, J., Tumwesigye, E., Okia, M., & Rwakimari, J. (2007). Detecting epidemic malaria, Uganda. Emerg Infect Dis, 13(5), 779-80.13. Samoff, E., DiBiase, L., Fangman, M. T., Fleischauer, A. T., Waller, A. E., & MacDonald, P. D. (2013). We Can Have It All: Improved Surveillance Outcomes and Decreased Personnel Costs Associated With Electronic Reportable Disease

Surveillance, North Carolina, 2010. American journal of public health, 103(12), 2292-2297.14. http://www.nasbhc.org/atf/cf/%7BCD9949F2-2761-42FB-BC7A-CEE165C701D9%7D/TA_HIT_history%20of%20EMR.pdf15. Hripcsak, G., Soulakis, N. D., Li, L., Morrison, F. P., Lai, A. M., Friedman, C., ... & Mostashari, F. (2009). Syndromic surveillance using ambulatory electronic health records. Journal of the American Medical Informatics

Association, 16(3), 354-361.

Further Research Opportunities Inclusion of new diseases in syndromic surveillance systems:

- It was recommended by the Institute of Medicine study that a balance is required between strengthening the proven

approach of traditional surveillance and innovative surveillance systems [11].

- Some of the nationally notifiable diseases as recommended by the IHR by all countries are poliomyelitis, smallpox, human

influenza caused by a new subtype, SARS and other diseases of regional concern such as meningococcal disease and

dengue [11]. Hence it is important that emerging new infections such as the Zika virus also be included.

EHR areas of improvement:

- It is important that the duration between a patient being seen and the data being available for analysis be short in order to

deliver appropriate response and carry out an outbreak investigation [1].

- In addition, the EHR Systems should be able to detect increased frequency of events that would help to trigger more

intensive assessment and increase the amount of diagnostic testing that would be indicated [1].

- It is important that the EHR can enable diagnostic and demographic accuracy for the purpose of enabling reliable

evaluation of geographic clustering of the specific emerging infections or syndromes [1].

Collaboration between public and private health sector :

- For further research in the Meaningful use of EHR, it is highly desirable that there is good collaboration between academic

institutions and health departments in both research and teaching. Also there is an increased need for well trained and well

equipped public health professionals to be hired and retained by local and state public health agencies for substantial

improvement in this emerging field [5].

- Since advocating syndromic surveillance systems can be difficult but at the same time strengthen local and state public

health agencies, there is an increasing necessity for assurance that these resources invested will produce real and

sustainable increases in the intrinsic ability for conducting vital public health functions [5].COMPONENT NUMBER OF STATES

RESPONDING

No. %

General communicable disease

surveillance (web based)Integrated 23 (58)Standalone 15 (38)Unspecified 2 (5)

HIV/AIDS Surveillance (web based)Integrated 1 (6)Standalone 15 (83)Unspecified 2 (11)Tuberculosis Case reporting (web

based)Integrated 11 (50)Standalone 11 (50)Lead poisoning surveillance (web

based )Integrated 5 (29)Standalone 11 (65)Unspecified 1 (6)Automated electronic laboratory

reporting Integrated 20 (71)Standalone 4 (14)Unspecified 4 (14)Manual electronic laboratory

reporting

(web-based) Integrated 15 (63)Standalone 5 (21)Unspecified 4 (17)Master Patient IndexIntegrated 9 (43)Standalone 2 (10)Unspecified 10 (48)Outbreak management systemIntegrated 4 (50)Standalone 4 (50)

TABLE. Number and percentage of states reporting components of fully operational and implemented electronic

disease surveillance systems* --- United States, 2007Reference: http://www.cdc.gov/nchs/data/databriefs/db79_fig2.png

Reference: Buggey T. (2007, Summer). A Picture Is Worth .... Journal of Positive

Behavior Interventions, 9(3), 151-158. Retrieved December 14, 2007, from

Academic Search Premier database.