Good Morning. In today’s presentation I will review and describe my activities and experiences during the first year of the Public Health Informatics Fellowship. I will talk about my progress in mastering the informatics competencies & applying these to public health practice.
While pursuing my graduate studies & practicing clinical medicine I learned about the fellowship while searching for public health informatics training…
I’m part of the organizational chart but you pretty much need a magnifying lens to find me here!
Public Health Informatics definition: How it applies to my assignment?
Of these critical competencies that you’re familiar with from Dr. Janise Richard’s chapter, I will tell you about my progress on nine competencies that I’ve focused on.
Because my major fellowship projects are collaborating with the Indian Health Service, I will start my project presentation with a very brief introduction of IHS.
As our sister federal agency under the Dept of Health & Human Services, IHS provides health care to about 75% of American Indian’s and Alaskan Natives.
IHS’ hospitals and clinics are predominantly in remote areas. A major strength of the IHS system is the ability to provide accessible services in locations where there are no other alternatives. This is also a weakness with respect to physicians’ physical access to training and consultation. This is why informatics tools are especially useful to the clinicians in the IHS.
NCHSTP where I work is focused on the problems of HIV, STDs, and TB in American Indian and Alaskan native population. To give you an idea of the impact of these problem on AI/AN people here are some health disparities surveillance data. The rate of HIV among AI/AN… Native people have… The rate of TB among native people…
Only 12% of US healthcare organizations have electronic medical record systems. IHS is unusual among health care organizations in that it has a complete electronic medical record system “RPMS” : Resource Patient Management System RPMS is modeled on VA Medical Record System
My 2 main projects with IHS are the Map to LOINC & ID-Web projects. The initial vision was to combine these 2 projects that’s why this slide shows the brochure we developed. We are still working on that connection between them.
At IHS most of the clinical labs use RPMS. However, there are 5 lab systems, 3 pharmacy systems, 5 dictation systems, and 2 order entry systems in use at IHS. This variety of systems create problems in communication between one IHS to other IHS lab or between IHS lab to Quest lab or vice versa. LOINC can facilitate the exchange of data between these sites.
As you know LOINC is the accepted healthcare industry standard for lab test names. To remind you: The LOINC committee and the Regenstrief Institute issued a press release this year that the United States Departments of Health and Human Services (HHS), Defense (DoD) and Veterans Affairs (VA) will adopt laboratory LOINC to standardize the electronic exchange of clinical laboratory results.
Therefore, our objective is to create a semi-automated tool to map clinical laboratory data to LOINC so that it can be exchanged with ease between different information systems. This is a project of IHS in collaboration with CDC which was conceptualized Dec 2000 with the initial funding received April/May 2001.
The specific aims of the project were: To develop a generalizable process to map local laboratory test names to LOINC. To accommodate future changes in the lab tests names, and LOINC Codes . To meet all data security and confidentiality standards during the data export. To develop a process that can be expanded to other sites.
The process will include automated download of lab test files from participating clinical facilities, automated identification and elimination of duplicates, automated and manual mapping of unique test names to LOINC, and because we wanted to test and analyze the standardized data , we asked our contractor to develop a program to export LOINCed lab test names to a central site in HL7 data format.
During the 1 st half of my fellowship year, I assisted in standardizing IHS lab data to LOINC and manually mapped lab test names to LOINC codes which led to the completion of our pilot phase last September 2002. And this year in March, our patch that contains the LOINC codes and associated software was released nationally for any site to install. At present, we are scaling up & have expanded to 19 sites. This year it is our goal to add 25 sites to standardize their data to LOINC using this process. As I mentioned earlier we have an ongoing project to enhance surveillance for HIV, STD, TB and we are interested in using LOINCed lab data for this purpose.
I’m also excited to tell you about the 2nd project I’m part of because it has great potential for supporting providers in delivering high quality primary care. In particular, I will be sharing to you the approach that provides periodic information on quality of care indicators through feedback of information to and from health care providers, and engages providers on using this information to improve systems of care.
This is how it works: ID-Web provides information on caseload and quality of care indicators related to HIV, STDs, and hepatitis B in 5 clinical facilities. It also provides links to training on national clinical guidelines, for which CME credit can be earned. The project is operating at five pilot sites, which have access to this information through a secured website. In a few minutes I will walk through the web site screens to show you what they look like.
IHS’ electronic medical record system provides the source of data for ID Web. Use of laboratory and clinical data on the diseases of interest from data fields already present in the Resource Patient Management System (RPMS), assures that ID Web accurately reflects medical records. All privacy and confidentiality standards are met for the website by excluding patient identifiers--like name, chart number, date of birth, and social security number. These identifiers are excluded from any posted data. Only summary data are posted to the website.
This is the screenshot of the actual ID-Web website. The website is developed and maintained by an IHS contractor, Cereplex, Inc. The ID-Web website is a secure point of access for health care providers and administrators. Only registered users have access to the data presented, which is protected by banking level security.
The website provides an interactive query tool to display information on thirteen clinical care indicators.
The analysis can be run on monthly, quarterly, or yearly basis using this query tool.
This page is a demo only (not real data) showing comparison between facilities on a given indicator—in this case, percent of women seen for prenatal care who have been screened for chlamydia. Again, this is not real data. As you can see, the indicator is shown for two facilities. The colors indicate high, medium and low values of the indicator. In this case, the first facility has a very low score and the second facility has a medium score. Neither one has a score in the range that we would like to see (above 80%).
And if providers want to look at their own testing rates, they can go on the web. Each of the rows in this chart shows a specific clinicians values on the indicator (in this case, percent of patients with new STD/HIV diagnosis who have had documented risk-reduction counseling) . Note again that we are not showing real data here—this is just a demo for the purpose of the presentation. Only registered users can access the real data. The users will only be able to see their own user specific information. All the personal information of their peers is masked. At the bottom of the page, where it says View CME Topic, there is a link to the training module for CME credit.
This year, I helped with the process of validation of ID-Web data for 5 IHS pilot sites. Currently, we are still validating data at 4 pilot sites & hoping in the near future to expand the project to other sites. This pilot project demonstrates a potentially powerful tool to assist providers in delivering high quality care for HIV, STDs, and Hepatitis B which could be expanded to include other infectious diseases. Larger scale implementation of this project within the IHS system will be dependent on its perceived value. Support of data entry is also important because the ID-Web data can only be as accurate as the data entered into RPMS. A demo of the system is available at this web address.
Here are my presentations for the year. I co-presented the Map to LOINC project last Feb 18 to the NEDSS Working group here at CDC because we are interested in exploring how our collaboration with IHS might relate to other CDC activities. I submitted an abstract for the ID-Web Project and was accepted for oral presentation at the 15 th IHS Research Conference at Scottsdale, AZ last May 2003. I have participated fully in fellowship activities such as: my topical presentation on Decision Support Systems in Health which provided an overview of the purpose of decision support as well as potential application in practice; and also led the journal club on GIS.
I attended several training courses which helped me in understanding different informatics and IT concepts.
I attended 4 conferences. As the other fellows mentioned in their presentations these conferences provided good breadth in informatics concepts and areas. The tutorials at AMIA & HIMSS were excellent.
I also had opportunities to travel in connection with the IHS projects. I went to ABQ twice. The best travel was to see Indian Reservations in Arizona and New Mexico.
I am very grateful to the ff…
There have been 2 papers published on mapping lab test names to LOINC. They are not directly applicable to our project because we had to work within the constraints of an existing electronic medical record system. Only one of the papers (Zollo and Huff) gave the % of lab test names mapped to LOINC and this was 81% which gave us a benchmark to aim for. We were aware from this prior experience reported by Zollo and Huff that some manual mapping would be necessary.
There are many published papers supporting the use of feedback to improve quality of care…a recent paper that is particularly relevant is a report of a system implemented at Kaiser-Permanente in Calif. Feedback in the form of quality of care indicators allowed the medical staff there to identify system problems & brainstorm system solutions. For example, chlamydia screening was increased by 40%.
Year end presentation_aj2003
Public Health Informatics Fellowship: 1 st Year Experiences in Review <ul><li>AJ Rosario, MD, MPH </li></ul><ul><li>CDC/NCHSTP/OD/PIO </li></ul><ul><li>Year-End Presentations </li></ul><ul><li>June 13, 2003 </li></ul>
<ul><li>Quezon City, Metro Manila, Republic of the Philippines – “Pinoy” </li></ul><ul><li>Degrees: BS Biology, MD, MPH </li></ul><ul><li>Residency training in Infectious Dermatology / Lecturer for Medical Transcriptionist at Cybercity </li></ul><ul><li>Family moved in 1991; Came to the U.S. in 2001 after MPH </li></ul>My Background
<ul><li>NCHSTP Mission Statement </li></ul><ul><li>The National Center for HIV, STD, and TB Prevention (NCHSTP) is responsible for public health surveillance, prevention research, and programs to prevent and control human immunodeficiency virus (HIV) infection and acquired immunodeficiency syndrome (AIDS), other sexually transmitted diseases (STDs), and tuberculosis (TB). Center staff work in collaboration with governmental and nongovernmental partners at community, State, national, and international levels, applying well-integrated multidisciplinary programs of research, surveillance, technical assistance, and evaluation. </li></ul><ul><li>NCHSTP/OD/PIO Graduates </li></ul><ul><ul><li>Alan Sim – 1998-2000 </li></ul></ul><ul><ul><li>Nabeel Khan – 2000-2002 </li></ul></ul><ul><li>Current PHI Fellow </li></ul><ul><ul><li>A J Rosario – 2002-2004 </li></ul></ul><ul><ul><li>MOTTO: Be Flexible !!! </li></ul></ul>CDC CIO Assignment
Public Health Informatics “ The systematic application of information and computer science and technology to public health practice, research, and learning” Yasnoff WA, O’Carroll PW, Koo D, Linkins RW, Kilbourne EM: Public Health Informatics: Improving and Transforming Public Health in the Information Age. J Public Health Management and Practice 6(6):67-75, 2000
Critical Competencies <ul><li>Project management skills and Knowledge </li></ul><ul><li>Change management </li></ul><ul><li>Information management </li></ul><ul><li>Basic information systems and theory </li></ul><ul><li>Plan, design, and develop information systems </li></ul><ul><li>Implement information systems </li></ul><ul><li>Evaluate information systems </li></ul><ul><li>Apply information technology hardware </li></ul><ul><li>Apply information technology software </li></ul>Richards J: Core Competencies in Public Health Informatics. Public Health Informatics and Information Systems 6:98-113, 2002
<ul><li>Agency of the US Public Health </li></ul><ul><li>Service, Department of Health </li></ul><ul><li>and Human Services </li></ul><ul><li>Operates a comprehensive </li></ul><ul><li>health service delivery system </li></ul><ul><li>for approximately 1.5 million of </li></ul><ul><li>the nation's 2 million American </li></ul><ul><li>Indians and Alaska Natives </li></ul><ul><li>12 Administrative Areas </li></ul><ul><li>560 Federally recognized tribes </li></ul>Indian Health Service
Background <ul><ul><li>HIV: AI/AN rate was 1.5 times the average rate for Whites, 1996-2000 </li></ul></ul><ul><ul><li>STD: AI/AN have the 2 nd highest rates of chlamydia, gonorrhea, & syphilis of any racial/ ethnic group in US </li></ul></ul><ul><ul><li>TB: AI/AN rate showed smallest decline of any racial/ethnic group since 1992 and was more than twice as high as the U.S. rate in 2002 </li></ul></ul><ul><ul><li> </li></ul></ul>
<ul><li>IHS Electronic Medical Record System </li></ul><ul><li>Integrated solution for clinical, financial, and administrative information </li></ul>Resource Patient Management System (RPMS)
<ul><li>2 IHS Projects </li></ul><ul><ul><li>Map to LOINC </li></ul></ul><ul><ul><li>- ID-Web </li></ul></ul>
IHS lab Quest lab IHS lab <ul><ul><li>5 Laboratory systems </li></ul></ul><ul><ul><li>3 Pharmacy systems </li></ul></ul><ul><ul><li>5 Dictation systems </li></ul></ul><ul><ul><li>2 Order Entry systems </li></ul></ul>Problems encountered by the RPMS with multiple information systems
Logical Observations, Identifier, Names and Codes <ul><li>March 21, 2003 : HHS, DoD and VA </li></ul><ul><li>- 1 st set of uniform standards for the electronic exchange of clinical health information </li></ul><ul><li>all federal agencies that deal with health care data will adopt laboratory LOINC </li></ul><ul><li>http://www.hhs.gov/news/press/2003pres/20030321a.html </li></ul>
<ul><li>- To develop a semi-automated process to map local laboratory tests files to LOINC </li></ul><ul><li>CDC-IHS collaboration </li></ul><ul><li>December 2000 </li></ul><ul><li>Funding: April/ May 2001 </li></ul>Map to LOINC Project (Objective)
<ul><ul><li>Map laboratory test names to LOINC </li></ul></ul><ul><ul><li>Accommodate future changes in test names /codes </li></ul></ul><ul><ul><li>Meet all data security and confidentiality standards </li></ul></ul><ul><ul><li>Expand to other sites </li></ul></ul>Map to LOINC Project (Specific Aims)
Map to LOINC Project (Overall Process) <ul><ul><li>Automated download of lab test names </li></ul></ul><ul><ul><li>Automated identification /elimination of duplicates </li></ul></ul><ul><ul><li>Automated / Manual mapping of unique test names to LOINC </li></ul></ul><ul><ul><li>Export in HL7 format </li></ul></ul>
<ul><li>Mapped laboratory test names to LOINC </li></ul><ul><li>Completed our 5 pilot sites (Sept 2002) </li></ul><ul><li>Generated HL7 messages successfully </li></ul><ul><li>Expanded to other additional sites (+19) </li></ul><ul><li>Continue expansion of the project to other IHS sites </li></ul><ul><li>(100+ sites) </li></ul>Map to LOINC Project (Current Status and Future Tasks)
Improving Quality of Care Feedback Systems Solution
ID-Web Project (Objective) <ul><li>Feedback on HIV, STDs, and hepatitis B </li></ul><ul><ul><li>Caseload </li></ul></ul><ul><ul><li>Care (13 Clinical Indicators) </li></ul></ul><ul><li>Links to Training (for CME credit) on National Guidelines </li></ul>
ID-Web Project (Methods) RPMS ID- Web Lab and clinical data 13 guidelines-based indicators of clinical care
ID-Web Project (Current Status and Future Tasks) <ul><li>Data validation - FY2003 </li></ul><ul><li>Expand the project beyond pilot sites - FY2004 </li></ul><ul><li>Demonstrates a potentially powerful tool to assist providers in delivering high quality care for HIV, STDs, and Hepatitis B </li></ul><ul><li>Could be expanded to include other infectious diseases </li></ul><ul><li>Larger scale implementation will be dependent on: </li></ul><ul><ul><ul><li>Perceived value </li></ul></ul></ul><ul><ul><ul><li>Support of data entry </li></ul></ul></ul><ul><li>Demo of the system </li></ul><ul><li>http://www. webepi.com/index.jsp </li></ul>
Presentations JOURNAL CLUB: Geographic Information Systems (GIS) in Public Health Practice in the New Millennium - (Authored by William A. Yasnoff and Edward J. Sodnik.
<ul><li>MENTORS </li></ul><ul><li>Tonya Martin </li></ul><ul><li>Jeanne Bertolli </li></ul><ul><li>NCHSTP/OD/PIO </li></ul><ul><li>Nabeel Khan </li></ul><ul><li>2 nd Year Fellows </li></ul><ul><li>1 st Year Fellows </li></ul>Acknowledgements <ul><li>PHIFP </li></ul><ul><li>Janise Richards </li></ul><ul><li>Tim Green </li></ul><ul><li>Rosaline Dhara </li></ul><ul><li>Barbara McDonnell </li></ul><ul><li>Leticia Dy </li></ul><ul><li>Phillip Lamb </li></ul>
My Blessings #13 Engaged Aug 13 Wedding Dec 13 Thanks! Enjoy the rest of Friday the 13th!
Literature Review <ul><li>L.M. Lau et al. A Method for the Automated Mapping of Laboratory Results to LOINC. Proceedings of AMIA Annual Conference 2000. </li></ul><ul><li>K.A. Zollo and S.M.Huff. Automated Mapping of Observation Codes Using Extensional Definitions. JAMIA. 2000 </li></ul>
Literature Review <ul><li>Effect of a clinical practice improvement intervention on Chlamydial screening among adolescent girls. Shafer MA, Tebb KP, Pantell RH, Wibbelsman CJ, Neuhaus JM, Tipton AC, et al. JAMA. 2002 Dec 11;288(22):2846-52. </li></ul>