JAMIA: External support-based EHR strategy can be effective in rural settings
An external support resource centered on a national technical expertise center supported by global developer and implementer groups can be effective in successfully implementing and maintaining EHRs at multiple sites in resource-limited settings, according to a study in the May edition of the Journal of the American Medical Informatics Association.
Martin C. Were, MD, from the Indiana University School of Medicine and Regenstrief Institute in Indianapolis, and colleagues developed an implementation model for an open-source EHR in three Ugandan HIV clinics which relied on shared responsibility between local sites and an external three-pronged support infrastructure consisting of a national technical expertise center, an implementer's community and a developer's community.
The technical expertise center forms the core of the external support resource and consists of highly trained IT and informatics personnel from within the country who are familiar with the local healthcare and IT exigencies as well as all technical aspects of implementing and maintaining EHRs, stated the authors.
“The developer and implementer communities complement the technical expertise center by providing the initial EHR program(s) and updates, along with suggestions on how to resolve implementation and support issues beyond the technical expertise center’s expertise,” Were and colleagues wrote.
To assess the impact of the EHR (OpenMRS) implemented using the technical expertise center model, the researchers conducted a formal time-motion study at the Masaka Healthcare Centre before and after implementing OpenMRS using methods previously employed in rural Kenya and in the U.S. The pre-implementation time motion study was performed in January and February of 2007 and the post-implementation in July and August 2008.
Before implementation, chart notes, log books and Ministry of Health registries were handwritten by clinicians and staff who had little if any access to prior visit data, and reports were generated manually. After implementation, visit data were recorded by clinicians onto paper-based, clinician-defined encounter forms that contained numeric fields and check boxes for specific diagnoses and other patient characteristics.
According to the report, an implementation model pre–post time–motion study at Masaka revealed that primary care providers spent a third less time in direct and indirect care of patients and 40 percent more time on personal activities after EHRs implementation. Time spent by previously enrolled patients with non-clinician staff fell by half and with pharmacy by 63 percent. Surveyed providers were highly satisfied with the EHR and its support infrastructure, Were and colleagues wrote.
“The implementation model addresses both the human-resource and cost constraints of implementing EHRs, lowers the general threshold for implementation and offers a viable option for scaling up EHRs in resource-limited settings which, in this case, had salutary effects on provider productivity,” the authors concluded.
Martin C. Were, MD, from the Indiana University School of Medicine and Regenstrief Institute in Indianapolis, and colleagues developed an implementation model for an open-source EHR in three Ugandan HIV clinics which relied on shared responsibility between local sites and an external three-pronged support infrastructure consisting of a national technical expertise center, an implementer's community and a developer's community.
The technical expertise center forms the core of the external support resource and consists of highly trained IT and informatics personnel from within the country who are familiar with the local healthcare and IT exigencies as well as all technical aspects of implementing and maintaining EHRs, stated the authors.
“The developer and implementer communities complement the technical expertise center by providing the initial EHR program(s) and updates, along with suggestions on how to resolve implementation and support issues beyond the technical expertise center’s expertise,” Were and colleagues wrote.
To assess the impact of the EHR (OpenMRS) implemented using the technical expertise center model, the researchers conducted a formal time-motion study at the Masaka Healthcare Centre before and after implementing OpenMRS using methods previously employed in rural Kenya and in the U.S. The pre-implementation time motion study was performed in January and February of 2007 and the post-implementation in July and August 2008.
Before implementation, chart notes, log books and Ministry of Health registries were handwritten by clinicians and staff who had little if any access to prior visit data, and reports were generated manually. After implementation, visit data were recorded by clinicians onto paper-based, clinician-defined encounter forms that contained numeric fields and check boxes for specific diagnoses and other patient characteristics.
According to the report, an implementation model pre–post time–motion study at Masaka revealed that primary care providers spent a third less time in direct and indirect care of patients and 40 percent more time on personal activities after EHRs implementation. Time spent by previously enrolled patients with non-clinician staff fell by half and with pharmacy by 63 percent. Surveyed providers were highly satisfied with the EHR and its support infrastructure, Were and colleagues wrote.
“The implementation model addresses both the human-resource and cost constraints of implementing EHRs, lowers the general threshold for implementation and offers a viable option for scaling up EHRs in resource-limited settings which, in this case, had salutary effects on provider productivity,” the authors concluded.