Implementing an Electronic Health Record as an Objective Measure of Care Provider Accountability for a Resource-poor Rural Area in the Dominican Republic

Robert C. Palmer, Judith S. Simms-Cendan, M.D., Michelle H. Kim College of Medicine, University of Central Florida palmrc5@gmail.com

Results

Site-specific Simulation Training Exercise At the Clinical Skills and Simulation Center (CSSC) of UCF COM, trip participants composed of nursing and medical students tested the use of the UCF COM-issued Dell Latitude laptop for data entry. Participants were given 30 minutes to obtain, and simultaneously, record a patient history with Spanish-speaking standardized patients. A generalized patient scenario was generated from the previous year’s patient records. A track consisting of sounds pertaining to the site location (e.g., passing motor vehicles, livestock, popular local music, and idle chat in Spanish) was played to further simulate the work environment. Faculty and students with native-level Spanish proficiency monitored the session in order to provide the participant with feedback (Figure 3). A feedback session was held after the event to gain insight into improving functionality of the electronic form for the user.

Figure 3. Left: A native Spanish-speaking medical student observes the site-Specific simulation training exercise of another student. Right: A medical student participates in the site-specific simulation training exercise with a Spanish-speaking standardized patient .

EHR Deployment A total of 34 medical volunteers participated in the UCF/USF COM STIMT from December 18-22, 2011. The group was equally divided in two teams: one utilized the electronic health record and the other utilized paper-based records. This STIMT was 3 days and covered a total of 5 site locations among the electronic health record and paper-based record teams. The OpenMRS system was used to record the demographics, history, physical exam, assessment, and plan of 125 patients. On July 28-August 4, 2012 14 medical volunteers from the UCF COM participated in a STIMT alongside medical students and faculty from the Universidad Católica Nordestana. Students utilized the EHR at 6 site locations and intermittently reverted to paper documentation during peak clinic flow. Data recorded via paper documentation was entered into the EHR the evening of the day that it was obtained. The demographics, history, physical exam, assessment, and plan of 700 patients were recorded.

• Pollard C, et al. J Rural Health. Winter 2009;25(1):77-84. • de Lusignan S., et al. Inform Prim Care. 2007;15(4):255-261. • http://model.pih.org/electronic_medical_records/benefits_challenges. Accessed January 31, 2011. • Berger EJ, et al. AMIA Annu Symp Proc. 2007;11:46-50. • Lober WB, et al. AMIA Annu Symp Proc. 2008;6:434-438. • Fraser HS, et al. AMIA Annu Symp Proc. 2006:264-268. • Kanter AS, et al. Int J Med Inform. Dec 2009;78(12):802-807. • http://cdn2.digitaltrends.com/wpcontent/uploads/2009/07/keyboard_dock_1_20100127.jpg • http://duracellpowerpack600.org/wp-content/uploads/2011/03/Duracell-PowerPack-600.jpg • http://webobjects2.cdw.com/is/image/CDW/2192921?$product_230$

References

Pre-clinical medical and nursing students deployed a highly-portable EHR system at various resource-poor communities across the northern Dominican Republic. Future uses of the portable EHR include: longitudinal patient tracking, given its capability to serve as an objective means for evaluating interventions; assessing healthcare needs; and providing continuity of patient care. Data obtained from this trip will be used to generate new patient scenarios for pre-trip simulation training and determine the appropriate medications and supplies for the subsequent trip. The simulation component provides an environment to practice patient documentation with an EHR as well as clinical skills in a non-English language and distinct cultural context. The data collected from this project will also allow the efficiency of the medical record system to be enhanced, such as the creation of coded input for the more frequently encountered illnesses. Several problems and potential solutions were detailed in the post-experience assessment; especially, diminished efficiency during peak clinic flow. A reconfiguration of the software to function independent of network connectivity is one focus; perhaps, the creation of an ‘EHR app’. Additionally, the intake form will be recreated from a functionality-drives-technology philosophy using focus groups composed of trip participants and IT professionals to optimize work flow efficiency. For future trips the amount of time required for system setup, user training time necessary for EHR utilization, and length of patient encounter will be recorded to establish baseline data.

Conclusions

Abstract The increased availability of open source electronic medical record systems has transformed the ability of short term international medical trip (STIMT) teams to record patient data. This is not only beneficial for providing longitudinal care of a patient population, but it also offers an objective means for evaluating a STIMT’s success and enhancing student education. The goal for this project was to assess the feasibility of implementing the Open Medical Record System (OpenMRS) at various resource-poor rural sites. An Electronic Health Record (EHR) based on an OpenMRS platform was developed for use in the primary care setting of a STIMT. Medical and nursing students were trained to use the system in a site-specific simulated environment with Spanish-speaking standardized patients at the Clinical Skills and Simulation Center of UCF College of Medicine. The EHR system, utilizing a laptop, power generator, router, and school-issued iPads, was transported and set up in rural communities surrounding Jarabacoa and the Duarte province in the Dominican Republic. The highly-portable EHR system was successfully deployed on two separate STIMTs by pre-clinical medical students and nursing students to various resource-poor communities across the northern Dominican Republic. The demographics, history, physical exam, assessment, and plan of 825 patients were recorded. Future applications will include its use as an objective means for evaluating interventions, assessing healthcare needs, and providing continuity of patient care. In addition, patient data can be utilized to generate standardized patient scripts for pre-trip simulation training.

Materials and Methods EHR Customization The OpenMRS 1.82 Enterprise WAR package and its required supplementary applications were downloaded from the OpenMRS site and installed on a UCF COM-issued Dell Latitude E6410. An initial intake form and complete medical intake form were created using this program (Figure 1). Mobile EHR System Production A mobile data intranet was constructed using the following components: a Dell Latitude E6410—the laptop issued to all UCF class of 2014 medical students—as a central server for the OpenMRS program; a Netgear N600 WNDR3400 wireless dual band router to provide secure wireless access to the central server; first and second generation UCF COM-issued iPads to interface with the central server for data entry at the Dominican Republic site location; and a Duracell Powerpack 600 or gas-powered generator to power the system when electricity was not available (Figure 2). The server and battery pack were purchased using UCF COM FIRE project funding.

Figure 1. Upper left panel: Via the Administration page of OpenMRS the user can access the ‘Patient Xform Design’ and ‘Manage form’ functions to create patient intake form templates. Upper right panel: The initial patient intake form created using the ‘Patient Xform design’ function Lower left panel: Using the ‘manage forms’ function, concepts are added from the OpenMRS dictionary to the schema design, which are then loaded into the Xform designer. Lower right panel: The complete patient intake form created using the Xforms designer of the ‘manage forms’ function.

Figure 2. A data migration model that displays the interconnectivity between a central server and mobile EHR systems, which consist of multiple tablet computers with keyboards, laptop, router, and battery pack.

Acknowledgements The authors gratefully acknowledge the contribution of Luke Read and Colin Forward of Mixed Emerging Technology Integration Lab (METIL) for IT consultation, Michelle H. Kim for careful review of the project and providing post-trip survey data, the OpenMRS team for technical support, Cameron Kluth for network expertise, and the UCF COM FIRE committee for financial support.

Students worked in teams of two and were paired based upon level of medical training and Spanish proficiency. On the first trip once patients were evaluated, he or she was sent to the pharmacy station where medications were dispensed utilizing the prescription information previously recorded electronically which ensured accurate dispensing of patient medications; medical teams fetched medications during the second STIMT to prevent clinic backup. Patient records are currently maintained on a Dell Latitude E6410. Patient data is accessible via the host laptop and may be exported via a Microsoft Excel file. The patient information is primarily text-based and not in a coded format. The categories of data obtained include the following: internal database ID, given name, family name, gender, age, birth date, date and time of encounter, address, history of chief complaint, past medical history, past surgical history, menstrual history, obstetrics history, medications, allergies, review of systems, height, weight, pulse, respiratory rate, systolic and diastolic blood pressure, physical exam, assessment and plan, attending physician, medical student, pharmacy checkpoint, and educational station checkpoint.

Post-experience Survey A total of 13 medical volunteers (9 medical students and 4 nurses) were surveyed after the second STIMT to gain feedback regarding their experience using the EHR. •Self-rated Spanish proficiency: fluent (54%), intermediate (15%), and basic (31%). •Number of past STIMT experiences: >4 (8%), 3-4 (8%), 1-2 (46%), and none (38%). •Past documentation experience (more than one selection was permitted, allowing the percentage total to exceed 100%): none (23%), paper records (54%), electronic records (62%). •Ease of EHR data entry: very difficult (8%), difficult (31%), neutral (31%), easy (15%), very easy (8%). •Ease of previous record access: difficult (15%), neutral (31%), easy (31%), very easy (8%), and did not use (15%). Participant essay responses centered on the need to address poor EMR efficiency during peak clinic flow. Solutions included providing iPad keyboards to all users, replacing text boxes with check boxes, incorporating ‘smart text’, and allowing the EHR to record data independent of network connectivity.