Health Information CT #5

Strengthening Public Health and Primary Care Collaboration Through Electronic Health Records

Electronic health records

(EHRs) have great potential

to serve as a catalyst for

more effective coordina-

tion between public health

departments and primary

care providers (PCP) in

maintaining healthy com-


As a system for docu-

menting patient health data,

EHRs can be harnessed to

improve public health sur-

veillance for communica-

ble and chronic illnesses.

EHRs facilitate clinical alerts

informed by public health

goals that guide primary

care physicians in real time

in their diagnosis and treat-

ment of patients.

As health departments

reassess their public health

agendas, the use of EHRs to

facilitate this agenda in pri-

mary care settings should

be considered. PCPs and

EHR vendors, in turn, will

need to configure their EHR

systems and practice work-

flows to align with public

health priorities as these

agendas include increased

involvement of primary

care providers in addressing

public health concerns. (Am

J Public Health. 2012;102:

e13–e18. doi:10.2105/AJPH.


Neil Calman, MD, Diane Hauser, MPA, Joseph Lurio, MD, Winfred Y. Wu, MD, MPH, and Michelle Pichardo, MPH


(EHRs) have great potential to serve as a catalyst for more effec- tive coordination between public health departments and primary care providers in maintaining healthy communities. As promi- nent health risks to the community continue their shift from conta- gious diseases to chronic illnesses, public health departments are in- creasingly focused on conditions such as diabetes and obesity. At the same time, serious threats persist from traditional public health concerns, such as commu- nicable disease outbreaks.

Primary care providers, and particularly community health centers (CHCs), that provide care for low-income populations are on the front lines in treating and containing both communicable diseases and chronic illnesses that are more prevalent in these com- munities. Traditional models of primary care are also evolving, with increased focus on community- based approaches in response to changing financial incentives and formal recognition programs, such as the Patient-Centered Medical Home certification offered by the National Committee for Quality Assurance and the Joint Commis- sion.1,2 Use of these models is facilitated by the parallel increase in adoption of EHRs.

Federal incentive programs have been a proponent of EHR implementation and “meaningful use” of EHRs among primary care providers, with targeted funding to support their adoption among CHCs.3 The promotion of health information technology

to improve the public’s health is 1 of 5 focus areas for meaningful use of EHRs. Finally, 1 of the 3-part aims of the Centers for Medicare and Medicaid Services (CMMS) is the improvement of population health—a goal that will only be met through im- proved coordination of primary care and public health.4,5

In 2003, the potential for ad- dressing community health needs with the aid of EHR data exchange initiated a partnership between The New York City Department of Health and Mental Hygiene (NYC DOHMH) and The Institute for Family Health. Together, these organizations have developed, tested, implemented, and moni- tored the use of an EHR in meet- ing public health and primary care goals. NYC DOHMH is one of the world’s largest public health agencies, operating programs in disease control, environmental health, epidemiology, health care access, health promotion and disease prevention, and mental hygiene. It also makes public health-enabled EHRs available to over 2500 primary care providers throughout New York City as part of its Primary Care Information Project (PCIP).

The Institute for Family Health is a nonprofit organization that provides care to more than 80 000 patients in 26 federally qualified health center sites in New York City and New York State’s Mid- Hudson Valley. The Institute’s goal in establishing an EHR sys- tem was not only to enhance the quality of patient care in its own practices, but also to improve the

health of the communities it serves. Recognizing that the 2 organizations had parallel mis- sions to maintain healthy com- munities, the Institute and NYC DOHMH partnered in EHR data exchange initiatives to meet the shared goals of improving the surveillance and management of both communicable disease and chronic disease. Projects addressing these goals are de- scribed below.


Syndromic surveillance, the practice of monitoring encounters for symptoms that may represent infectious diseases and other conditions of public health con- cern, can be facilitated by EHRs through automated data report- ing to public health departments. The Institute for Family Health partnered with NYC DOHMH to become one of the first ambula- tory settings to participate in syn- dromic surveillance.6 Routinely collected chief complaint infor- mation along with important de- mographic data from Institute patients are de-identified and transmitted to NYC DOHMH daily through a secure encrypted data transfer mechanism. Respi- ratory illness, fever, diarrhea, and vomiting are the key symp- toms monitored, with analysis to determine when the incidence of these syndromes exceeds ex- pected thresholds.

Figures 1 and 2 present the percentage of patient visits on


November 2012, Vol 102, No. 11 | American Journal of Public Health Calman et al. | Peer Reviewed | Strengthening Collaboration | e13

a daily and rolling weekly basis in which influenza-like illness (ILI) was the documented reason for visit at all of the Institute’s care

sites in New York City and the Mid-Hudson Valley (Upstate), re- spectively, during the H1N1 epi- demic. These data illustrate that

the peak in ILI visits at Upstate sites lagged the peak experienced in New York City sites by 5months, which guided the Institute to

redistribute immunization re- sources well after the New York City peak. The ability to conduct this type of disease monitoring in real time has the potential to in- form primary care providers and public health departments of shifting needs during outbreaks. As increasing numbers of health care providers implement public health---enabled EHRs, public health departments have the potential to receive syndromic surveillance data that present a more comprehensive profile of the population.

Like many public health de- partments, NYC DOHMH moni- tors the incidence of disease through registries and required reporting of notifiable conditions, such as tuberculosis, by health care providers. Despite legal man- dates in most states, reporting rates for these conditions are not optimal.7,8 The Institute facil- itated public health reporting by creating alerts within its EHR that remind providers at the point of care that a particular diagnosis is reportable and provide a link to the reporting form. Patient demo- graphics are automatically popu- lated in the form to minimize providers’ time and effort in sub- mitting reports.

Institute data on immunization and lead screening, which must be submitted to the city’s public health registries, are automatically uploaded from the Institute’s EHR system to NYC DOHMH, elimi- nating the need for providers or staff to submit reports. Primary care providers can use registry data to look up immunization his- tories for patients in their prac- tices, potentially reducing both gaps and duplication in immuni- zation schedules.

Findings from epidemiological investigation by public health agencies can inform primary care

FIGURE 1—Percentage of patient visits at New York City sites for influenza-like illness (ILI): Institute for

Family Health, June 8–December 4, 2009.

FIGURE 2—Percentage of patient visits at New York State’s Mid-Hudson Valley sites for influenza-like

illness (ILI): Institute for Family Health, June 8–December 4, 2009.


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practices. This information trig- gers message distribution through channels such as the Health Alert Network in which nearly all large public health entities participate, and that may be delivered to the point of care through EHRs.9,10

The Institute and NYC DOHMH have tested and implemented point-of-care public health alerts for a variety of conditions. For example, New York City has issued messages about West Nile Virus detection through its Health Alert Network, which Institute staff programmed as alerts for their primary care providers, prompting them to consider this condition for patients presenting with fever and headache. In an- other example, a NYC DOHMH alert about increased cases of Legionella in a Bronx neighbor- hood prompted the Institute to create an alert to local providers to consider this condition in pa- tients with respiratory symptoms. An order set attached to the alert facilitated urine antigen testing that would otherwise have been unlikely. Such alerts can prompt primary care providers to take timely action to appropri- ately treat patients for emerging conditions.

Primary care providers can also be encouraged to take an active role in disease surveillance efforts. During a measles outbreak, Insti- tute providers treating patients with rash and fever responded to programmed prompts and col- lected specimens requested by NYC DOHMH at the time patients presented to the clinic. At the onset of the H1N1 epidemic in 2009, clinical alerts requested that providers at Institute sites collect viral specimens for a pilot surveillance project to determine the viral etiologies to respiratory illness in the community.11 Be- cause of the success of this alert,

the Institute has continued to provide community level samples for detecting ILI.


Public health departments will need new tools and partners to address the growing epidemic of chronic disease. The functionality of EHRs can be expanded to em- power CHCs and other clinicians to provide better preventive and acute care through clinical deci- sion supports.12,13 Still, primary care providers are challenged to incorporate dozens of care guide- lines into practice. The finite re- sources available across the health care system make it critically im- portant to have a public health agenda that prioritizes services that have the greatest impact on health.1,14,15

Recognizing this need, NYC DOHMH launched the Take Care New York (TCNY) initiative in 2004.16 TCNY set an ambitious agenda to prioritize actions to help New York City improve health in 10 key areas, each of which causes significant illness and death but is amenable to intervention. NYC DOHMH established population-level tar- gets for each of these priority areas, which include 10 goals for all New Yorkers:

1. Have a regular doctor or other health care provider.

2. Be tobacco-free. 3. Keep your heart healthy. 4. Know your HIV status. 5. Get help for depression. 6. Live free of alcohol and drugs. 7. Get checked for cancer. 8. Get the immunizations that

you need. 9. Make your home safe and

healthy. 10. Have a healthy baby.

To integrate the TCNY agenda into its primary care efforts, the Institute collaborated with NYC DOHMH in developing a model clinical-decision support system at its practice sites that is orga- nized around these goals. Health department and Institute staff reviewed each goal in the context of medical evidence and practice guidelines. A logic model was created for each goal that incor- porated available EHR data and workflows, and also assessed feasibility and acceptability in practice. More than 40 alerts addressing TCNY goals are cur- rently programmed into the Insti- tute’s EHR. Mindful of issues such as “alert fatigue,”17 reminders were engineered to fit into clinical workflows and incorporated tools to facilitate adherence, such as drop-down order sets, documen- tation screens, links to patient education materials, and the op- tion to suppress the alert if the recommendation was not indi- cated for the patient.

Health screening recommenda- tions incorporated into many of the TCNY alerts often require care management and follow-up to improve health outcomes. As part of its health care quality program, the Institute has used EHR data to develop disease registries and reports that enable outreach workers and care managers to identify and contact patients who are overdue for a test, screening, or visit, or have a clinical measure that requires special attention. Another critical component of the TCNY partnership is a reporting system to monitor these measures at each practice site. A current report on all patients with docu- mented HIV test results, corre- sponding to TCNY Goal 4, is presented in Figure 3. This exam- ple is illustrative of the need to couple automated alerts with

a supportive health-care delivery system. Rates of HIV testing began improving markedly in 2011 as the Institute’s health centers began to incorporate on-site rapid test- ing, market related messages to patients, and redirect electronic alerts and order sets to nursing staff to encourage testing prior to the patient seeing the provider.

Alerts can also guide providers to public health resources to which they can refer patients. For example, the provider alert to address smoking, TCNY Goal 2, contains an embedded, prepopu- lated referral form for the Fax-to- Quit line operated by the New York State Department of Health. Other possibilities include refer- rals to free mammography and additional cancer screening pro- grams operated by publicly funded or other programs. This functionality is particularly perti- nent to CHCs that serve patients whose lack of insurance often creates barriers to health services. Public health programs should consider partnering with primary care providers to use EHRs to inform them of these types of community programs at the point of care.

EHR data can be used to iden- tify primary care patients at risk for developing certain chronic diseases or the sequelae of existing chronic conditions. Research has demonstrated that the data typi- cally stored in EHRs can be used to identify patients at high risk for certain diseases and that patient knowledge of increased risk of disease may motivate preventive behavior such as obtaining cancer screenings or vaccinations.18---20

The Institute has employed clini- cal data in the EHR to identify and reach out to patients at increased risk for disease, with initial pro- jects focused on colon cancer screening and diabetes.


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Another project uses patients’ demographic data to screen for Hepatitis B. Screening for Hepatitis B is not recommended for the general population; how- ever, screening is indicated for immigrants from certain countries where prevalence is high.21,22 Us- ing data on patients’ country of origin, which is part of an organi- zational initiative to collect patient data at the granular level, the In- stitute implemented an alert for Hepatitis B screening that prompts providers to order appropriate testing if the patient is from a country in which Hepatitis B is endemic but has not been tested or diagnosed with this condition. In the first 5 months after imple- mentation, the alert “fired” 32 515 times and resulted in the ordering of 785 Hepatitis B surface anti- gen tests, with 10 previously unknown cases of Hepatitis B identified. Early identification of chronic infectious diseases in pri- mary care practices can prevent adverse outcomes like cirrhosis and liver cancer.

Racial and ethnic disparities in health remain a persistent public health problem. Minimal progress in this area has been attributed, in part, to a lack of standardized demographic data in health care settings that can identify gaps and point toward best practices for eliminating disparities.23---26 Re- cent federal health care reform and health information technology legislation call for health care providers to collect data on pa- tients’ race, ethnicity, and lan- guage as part of health system change, and lays the foundation for identifying and addressing health disparities throughout the health care system.3,27 EHRs can become powerful tools in these efforts when they enable health quality data to be monitored via patient demographics at the gran- ular level.

The Institute has documented patients’ race, ethnicity, and preferred language for health care in its EHR system since its implementation in 2002, with a recent expansion of demographic

data collection based on recom- mendations from The Institute of Medicine.28 These data enable the Institute to monitor care pro- cesses and outcomes for patients in particular racial and ethnic groups. Progress reports on TCNY measures are run by patient race and ethnicity, as are disease registries and other clinical reports. Disparities iden- tified in the HbA1c levels of Institute patients with diabetes spurred the development of an enhanced diabetes-care model that incorporates outreach and care management for patients with clinical indicators outside of the recommended range, who are more likely to be of minority race or ethnicity. Documenting granu- lar health data is the first step in identifying gaps in care for which both front line providers and public health agencies can then marshal resources to identify individuals and groups experi- encing barriers to high-quality primary care and to target public health education campaigns.


Multiple sources of health data can inform the priorities and actions of public health departments, pri- mary care providers, individuals, and communities, when appropri- ately analyzed and coordinated. EHRs can form the hub of infor- mation exchange as primary care providers document illnesses that can be uploaded to public health departments to monitor disease and inform point-of-care decisions about treatment through provision of relevant public health informa- tion. Public health departments can use aggregated EHR data, along with other sources of data, to prioritize community interven- tions and public health messages, as well as recommendations for primary care screenings and treatment. Individuals and com- munities make daily decisions about their health and lifestyles that are reported to their primary care providers and to public

health departments through

community surveys and assess-

ments. EHRs can help public

health departments and primary

care providers efficiently coordi-

nate their priorities to ensure that

patients and communities receive

consistent, high-impact health

messages. Data from one point

on the hub can inform action on

another point, forming a commu-

nity health information ecosys-

tem that fosters coordination

of data and health promotion

activities. Figure 4 diagrams the

potential flow of information be-

tween stakeholders. Although the partners in the

initiatives described herein were successful in integrating public health and primary care function- ality, there are currently several challenges to expanding these col- laborations more broadly. First,








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FIGURE 3—Institute for Family Health office visits in which patients aged 18 years and older have

documented HIV test result or self-reported HIV status: 2009–2011.


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adoption of EHRs among primary care providers is growing yet lim- ited. Roughly 25% of office-based physicians in the United States have a basic EHR system and another 10% have a fully func- tional EHR system.29 Furthermore, there are many EHR systems in existence today, and this variability can make it difficult for public health agencies to engage with multiple primary care partners and ensure that key communities are represented in health partnerships. Standards for the coding and transmission of public health data by EHRs are in development, but many such standards have yet to be developed and others have not been broadly adopted by the EHR vendor community and by public health departments. Limited re- sources constrain the ability of public health agencies and primary care providers to collaborate and innovate.


Public health departments and primary care providers must integrate their efforts in the de- velopment of electronic health re- cords if the United States is going to successfully move from a health care system that is based on vol- ume of services to that which is focused on maintaining healthy communities. Primary care pro- viders, as “deputized public health officers,” have the ability to act as the eyes of the health department in the community. They are made more efficient and effective in this role when supported by public health---enabled electronic health records.

Primary care providers, particu- larly CHCs, rely on public health departments to provide the ex- pert guidance and situational awareness that facilitates effective health care delivery. EHRs provide

a mechanism for health depart- ments to deliver such guidance in real time, as providers make care decisions. As public health depart- ments develop new guidelines and priorities for improving population health, it will be important to con- sider how they can be facilitated by EHRs in primary care settings. Primary care providers and EHR vendors, in turn, will need to con- figure their EHR systems to align with public health priorities. In this time of rapid health information technology advancement and health care realignment, it is critical that public health departments and primary care providers jointly plan how to harness the power of EHRs and achieve the benefits of integration. j

About the Authors Neil Calman, Diane Hauser, Joseph Lurio, and Michelle Pichardo are with The Institute for Family Health, New York, NY. Winfred Y. Wu is with the New York

City Department of Health and Mental Hygiene, New York, NY. Correspondence should be sent to Diane

Hauser, Senior Associate, The Institute for Family Health Program Development/ Research, 16 East 16th Street, New York, NY 10003 (e-mail: dhauser@institute2000. org). Reprints can be ordered at http://www. by clicking the “Reprints” link.

This article was accepted July 20, 2012.

Contributors N. Calman and D. Hauser conceptualized the essay and were responsible for its completion in coordination with all coauthors. All authors contributed intellectual content and participated in the revision and editing of the essay.

Acknowledgments The projects described in this article were supported by several federal agencies, including The Centers for Disease Control and Prevention (grant P01 HK000029), the Health Resources and Services Ad- ministration (grant H2LCS18144), and The Department of Homeland Security (grant 2009-OH-091-ES0001).

The authors would like to acknowl- edge the work of many colleagues at The New York City Department of Health and Mental Hygiene and The Institute for Family Health who have been integral to the successful collaboration of the 2 organizations, as well colleagues at the Columbia University Department of Biomedical Informatics who have pro- vided and continue to provide expert guidance.

Human Participant Protection Institutional review board approval was received for projects described in the manuscript that involved human research subjects.

References 1. The National Committee for Quality Assurance. Patient-Centered Medical Home. Available at: http://www.ncqa. org/tabid/631/Default.aspx. Accessed July 29, 2011.

2. The Joint Commission. Primary Care Medical Home. Available at: http://www. aspx. Accessed July 29, 2011.

3. Medicare and Medicaid programs; electronic health record incentive pro- gram: final rule. Fed Regist. 2010;75 (144):44313---44588.

4. Medicare and Medicaid programs; opportunities for alignment under Medicaid and Medicare: proposed rule. Fed Regist. 2011;76(94): 28196---28207.

FIGURE 4—Exchange of health data between public health, primary care, individuals, and communities.


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5. Fielding JE, Teutsch SM. Integrating clinical care and community health: de- livering health. JAMA. 2009;302(3): 317---319.

6. Hripcsak G, Soulakis ND, Li L, et al. Syndromic surveillance using ambulatory electronic health records. J Am Med In- form Assoc. 2009;16(3):354---361.

7. Doyle TJ, Glynn K, Groseclose SL. Completeness of notifiable infectious dis- ease reporting in the United States: An analytical literature review. Am J Epide- miol. 2002;155:866---874.

8. Konowitz PM, Petrossian GA, Rose DN. The underreporting of disease and physi- cians’ knowledge of reporting require- ments. Public Health Rep. 1984;99:31---35.

9. Lurio J, Morrison FP, Pichardo M, et al. Using electronic health record alerts to provide public health situational aware- ness to clinicians. J Am Med Inform Assoc. 2010;17(2):217---219.

10. Garrett NY, Mishra N, Nichols B, et al. Characterization of public health alerts and their suitability for alerting in electronic health record systems. J Public Health Manag Pract. 2011;17 (1):77---83.

11. Tokarz R, Kapoor V, Wu W, et al. Longitudinal molecular microbial analysis of influenza- like illness in New York City, may 2009 through may 2010. Virol J. 2011;8:288.

12. Dexheimer J, Talbot T, Sanders D, et al. Prompting clinicians about pre- ventive care measures: a systematic re- view of randomized controlled trials. J Am Med Inform Assoc. 2008;15: 311---320.

13. Garg AX, Adhikari NK, McDonald H, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005;293: 1223---1238.

14. Farley TA, Dalal MA, Mostashari F, Frieden TR. Deaths preventable in the U.S. by improvements in the use of clinical preventive services. Am J Prev Med. 2010;38(6):600---609.

15. Teutch SM, Fielding JE. Closing the gap in clinical preventive services. Am J Prev Med. 2010;38(6):684---685.

16. Frieden TR. Take Care New York: a focused health policy. J Urban Health. 2004;81(3):314---6.

17. van der Sijs H, Aarts J, Vulto A, Berg M. Overriding of drug safety alerts in computerized physician order entry. J Am Med Inform Assoc. 2006;13(2):138---147.

18. Marshall T. Identification of patients for clinical risk assessment by prediction of cardiovascular risk using default risk factor values. BMC Public Health. 2008; 8:25.

19. McCaul KD, Branstetter AD, Schrpeder DM, Glasgow RE. What is the relationship between breast cancer risk and mammography screening? A meta- analytic review. Health Psychology. 1996;15(6):423---429.

20. Brewer NT, Gibbons FX, Gerrard M, Chapman GB, McCaul KD. Meta-analysis of the relationship between risk percep- tion and health behavior: the example of vaccination. Health Psychol. 2007; 26(2):136---145.

21. Weinbaum CM, Williams I, Mast EE, et al.; Centers for Disease Control and Prevention. Recommendations for identi- fication and public health management of persons with chronic hepatitis B virus infection. MMWR Recomm Rep. 2008; 57(RR-8):1---20.

22. Lok ASF, McMahon BJ. AASLD Practice Guideline Update. Chronic Hepa- titis B: Update. Alexandria, VA: American Association for the Study of Liver Dis- eases; 2009.

23. Institute of Medicine. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington DC: Na- tional Academies Press; 2001.

24. Russell L. Measuring the Gaps: Col- lecting Data to Drive Improvements in Health Care Disparities. Washington, DC: Center for American Progress; 2010.

25. Bierman AS, Nicole L, Collins KS, et al. Addressing racial and ethnic barriers to effective health care: the need for better data. Health Aff (Millwood). 2002; 21:91---102.

26. Wynia M, Hasnain-Wynia R, Hotze T, et al. Collecting and Using Race, Eth- nicity and Language Data in Ambulatory Settings: A White Paper With Recommen- dations From the Commission to End Health Care Disparities. Chicago: Ameri- can Medical Association; 2011.

27. Patient Protection and Affordable Care Act, Pub. L. No. 111---148, 124 Stat. 119(2010). Available at: http://www. content-detail.html. Accessed July 29, 2011.

28. Institute of Medicine. Race, Ethnicity and Language Data: Standardization for Health Care Quality Improvement. Wash- ington, DC: The National Academies Press; 2009.

29. Hsiao C-J, Hing E, Socey TC, Cai B. Electronic Medical Record/Electronic Health Record Systems of Office-based Physicians: United States, 2009 and Pre- liminary 2010 State Estimates. National Center for Health Statistics (NCHS) Health E-stat. December 2010. Available at: hestat/emr_ehr_09/emr_ehr_09.htm. Accessed January 2, 2012.


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