Figure 1. Scenes at St. Mary's Polyclinic. (a) Paper-based
patient records. (b) Mobile van-based field
operations.
For the most part, such hospitals and organizations are keenly aware of
the need of a good EMR system. Unfortunately, the current state of
art of available EMR systems is woefully inadequate: they are typically
expensive proprietary systems. In addition to cost, being closed and
proprietary has other severe disadvantages. First, each hospital has
its own unique needs; but it is difficult, if not impossible, to
thoroughly customize such closed systems to cater to these different and
specific needs. This difficulty is especially pronounced for the
kind of hospitals that we work with because of their lack of
resources. Second, the proprietary nature of such systems also makes
it difficult to make them communicate and share data with other peer
systems.
Furthermore, these systems lack good support for "distributed
operations"--by "distributed operations," we mean the ability of sharing
information and coordinating actions across many different sites.
When they do support network access, these existing systems are typically
constrained within the walls of a single hospital, on a single local area
network (LAN). SMPC has many operations, such as mobile vans that
run "camps" in the field (Figure 1(b)), or outlying clinics in rural
areas, which are all beyond the confines of the main hospital (which we
shall call the "mother-ship hospital"). The mobile camps and
outlying clinics do not even have Internet access. Existing systems
offer no way of information-sharing among these widely distributed and
disconnected sites.
There has been increasing interest in online medical record systems that
allow patients to, for example, easily take their records to a different
hospital or doctor, as the likes of Microsoft and Google have recently
launched their own initiatives in this space. These initiatives,
however, have been mainly a "first-world" phenomenon. (The interface
of Google Health, for example, is unfortunately inappropriate for the
developing world context that we are targeting: it is designed for
individual patients to manage their own records and is a
fundamentally wrong fit for institutions that need to
manage a large number of these records.) The irony is that those in
the vast under-served areas of the world, those who have practically no
access to quality health care today, may have the most to gain from a
system that allows them to be heard and seen, but are below the radar
screen of the current US-based initiatives. What we need is to
design and engineer a distributed medical record system relevant for the
needs of the local contexts. Digital Polyclinic is an attempt to
plug this critical gap, and we believe this effort could also bring more
awareness and interest in working on this important problem.
2. The Digital Polyclinic system
Figure 2. Digital Polyclinic: a
distributed electronic medical record system.
We are working on a distributed electronic medical record system, which we
call the Digital Polyclinic (DPC). DPC is designed to cater to the
unique needs of the hospitals like SMPC and address the inadequacies of
the current systems discussed above. Figure 2 is an illustration of
DPC.
2.1 Support for distributed operations
DPC has a number of unique advantages. First is its flexible support
for distributed operations. For the sites that have access to the
Internet, DPC allows these sites to synchronize and share patient
records. For example, a rural clinic can easily share and
synchronize its records with the mother-ship hospital's database.
But perhaps even more interestingly, DPC allows sites that do not have
immediate Internet access to participate in the system as well. For
example, a van, as part of a mobile camp, carries a laptop, which houses a
component of the mother-ship database, into the field. During the
field operation, the laptop can be entirely self-sufficient and support
staff work without network connectivity. At the end of the trip,
when the laptop returns to the mother-ship hospital, it rejoins the
network and synchronizes with the mother-ship database. New patient
records collected in the field earlier or updates are all automatically
"uploaded" back into the mother-ship database.
Furthermore, even authorized US-based staff or volunteers (including
volunteers from medical school students) can "log onto" the system and
provide help. They may search, sort, and filter based on certain
criteria, before they decide on what cases they might want to help
with. Indeed, some of the records being examined could have been
collected by a van-driven field trip earlier.
This approach may provide a useful complementary solution to conventional
tele-medicine (although the database should be useful for the conventional
tele-medicine case as well). Conventional tele-medicine has a
potential scalability problem: there are simply not enough skilled doctors
who are capable and willing to staff live teleconferencing-style
sessions. DPC attempts to optimize the time of the most skilled
staff as a hierarchy of trained front-line data collectors and back-office
"triage staff" can offload a significant portion of the workload as they
get to sift through the database first. The rank of these front-line
workers can also grow more quickly through increased training through the
system. The most skilled staff, as a result, gets to work only on
the perhaps most demanding cases. In addition to "space-shifting,"
which refers to the ability of linking people from different places, DPC
also provides valuable "time-shifting," which refers to the fact that the
service seekers and the service providers do not necessarily have to
"meet" each other at the same time: for example, records collected on a
van trip can be examined later, after the van has returned and
synchronized with the mother-ship. This approach can work well for
the non-emergency and preventive cases that the system specifically
targets. In some sense, one may think of the system as a distributed
"Patient's and Doctor's Facebook" for the poor. (Such a "facebook"
can be linked to other schemes such as collection of donation to fund
certain procedures, or "micro-insurance," instituted through self-help
groups.)
Of course, we do not expect a single exchange through the database can
solve everything--instead, we consider DPC to be a mechanism to get people
into "the system," where "the system" may entail repeated and
regularly scheduled visits and checkups (probably effected by a van),
drop-off of medicines, and pick up of patients for further tests at the
mother-ship hospital, and all of these events are entered into a
historical trail that gets recorded and coordinated by DPC.
A theme of DPC that we have described so far is a single coherent system
seen by "everyone," regardless where they are. This "single system
image" is important for a variety of reasons. For example, consider
immunization records: villagers can get immunized by multiple
organizations, and only when these organizations are sharing the same
system can they effectively coordinate their activities. (And being
part of the "network," the DPC system can, for example, easily link
immunization records to an SMS system, so that the system can
automatically send out immunization reminders via SMS.)
Being a single coherent system has other advantages: for example, public
health professionals can mine the database for aggregate trends and plan
activities such as targeted prevention and awareness campaigns. Case
data from the database, particularly multimedia data, may help with
education and training programs.
2.2 DPC architecture: open-source local databases plus a
cloud-based back-end
Figure 2 may appear as a traditional client-server system; but DPC is not
exactly like such a system. Without the network, a traditional
client-server system cannot function. On the other hand, in DPC, for
example, a mobile van, housing a laptop that is disconnected, needs to be
self-sufficient. So DPC needs to support "disconnected
operations." Consequently, each DPC "client" includes a local
database, and most of the operations are executed locally. These
local databases interact with "the cloud" only when necessary.
Both the "client" and "server" components in DPC are based on an existing
open-source medical record system called OpenEMR. Our work on
OpenEMR so far has been two-fold: (1) introducing distributed operation
features into OpenEMR, and (2) tailoring OpenEMR for the context of
serving the underprivileged in India, which entails mundane details such
as the fact that traditional means of establishing a patient's identity
using name, date of birth, or tax ID does not work--we have had to
introduce features such as fuzzy matching in searches and picture IDs.
The use of an open-source system is significant. It goes to the
heart of the problems associated with traditional conventional closed
systems discussed in Section 1. It addresses the cost problem of
closed systems: our open-source system is free. It addresses the
customization problem of closed systems: the open-source system is easily
customizable, and indeed, the OpenEMR system that we are working on will
provide a framework specifically designed to facilitate customization
(such as a mechanism that allows different hospitals to easily create new
forms). It addresses the compatibility problem of closed systems:
the different instances of the OpenEMR derivatives are designed to be able
to easily communicate with each other to share data.
As as a result of employing this architecture, we hope to build a wide
network of these databases, all inter-linked with each other and able to
communicate with each other. We believe that this would be a
significant improvement of the traditional approach of different
organizations keeping expensive, inflexible, and incompatible isolated
individual databases of their own. We hope that the DPC system will
help the vast underprivileged population to be finally heard and seen and
to have access to the kind of services that have been so far beyond their
reach.