Improving and Expanding Electronic Health Records in a Rural Setting

Improving and Expanding Electronic Health
Records in a Rural Setting: Clinical Decision
Support System & Public Health Component
The decision-trees developed by ICTPH are in line with the SOAP consultation format used for patient visits at the clinics.
The starting point is a review of common symptoms a patient might be presenting (e.g. cough). The system then guides the
nurse into establishing the nature of those symptoms by asking about the presence of certain characteristics (e.g. site, onset,
character, radiation, associated factors, time, relieving factors, and severity) based on a series of Yes/No questions. This in
turn, directs the nurse to review the relevant body systems to be examined at the next stage, the physical exam (e.g. chest
exam). Once that is completed, it is envisaged that the CDSS would deliver a set of probable diagnosis (e.g. tuberculosis,
pneumonia), accompanied by a list of necessary lab tests (e.g. chest exam). The results of these labs tests are then fed back
into the system to yield a final diagnosis (e.g. pneumonia) (See Figure 2).
The decision-trees developed by ICTPH will be made for a limited list of diseases that are a) most relevant to a rural setting,
b) are reported as prevalent within the community by the clinic physician and c) are able to be diagnosed at the primary
care level. Diseases meeting these criteria are grouped and classified by body systems (respiratory, cardiovascular, etc).
The CDSS will only be able to diagnose this limited set of diseases, and it will recommend referrals for any disease that falls
outside of its scope.
EHR
A similar methodology to that used for the creation of CDSS protocols was employed for developing protocols that identify
individuals/communities at risk of developing diseases due to environmental conditions around them. The proposed starting
point for the inclusion of public health aspects is the collection of additional information regarding individual patients and
community level data (Kukafja et al., 2007). It is important that needed data be collected at a single time and then be reused
rather than collected repeatedly by different users (Chute and Koo, 2002). If data is collected at multiple points in time by
different groups of people certain amount of uniformity of data collection is lost. As a result it would become difficult to
compare the information collected. By gathering necessary data at a single point in time by one group, instances of data
entry errors and confusions would be reduced.
In order to gather appropriate data that would be easy to input into the EHR system, as well as easy to quantify, it is imperative
to minimize the instances of open-ended questions. As such, decision trees (Annex #3 & #4) will be utilized that would take
the user from various individual and community level environmental factors (i.e. cooking/drinking water, toilet use, trash
policy, etc.), ultimately down to diseases individuals and communities would be at risk for. The environmental public health
component will start with the water, waste system, sewage system, and indoor air pollution factors. After a series of levels
of questions, certain combinations of results will ultimately lead the respondent household or community to be susceptible
to gastrointestinal (GI) diseases and upper respiratory infection (URI), the two health problems greatly affecting Tamil Nadu
rural populations (ICTPH Baseline Epidemiological data, 2008).
The decision tree is formed with the aid of multiple choice type questions, prompting the user to choose from a list of
responses ranging from simple yes/no options to more complex choices (i.e. regarding cooking practices: in the home,
separate building, outdoors, or other). Certain answers will ultimately lead down to an at-risk conclusion whereas others will
not cause households or communities to be at risk for health problems. To be able to utilize these decision trees, two surveys
were created (Annex #1 & #2), one developed to be administered to communities and another to individuals. These surveys
will essentially direct respondents through the decision tree, and will provide ICTPH with information that will enable the
EHR system to quantify the results.
The community-level survey was created with the intention of having the local government, and/or focus groups in the
village as respondents. The community survey will identify problem areas in the hamlet (each village is divided into a
number of smaller regions called hamlets) (See Figure 3). This information will enable ICTPH the opportunity to see the
most predominant environmental concerns in each hamlet that put their respective population at-risk for GI and URI.
ICTPH will then be able to intervene at the hamlet level to implement initiatives that tackle these health concerns before
symptoms arise.
For example, an initial question would be asking the hamlet where they receive their main source of drinking water from:
surface water, piped water in home/yard, outdoor community water pump, well, or other. If the respondent community
answered surface water the decision tree would prompt them to a new series of questions and would then ask them if the
surface water is used for any other purposes. Response choice to that question would be: Defecating, bathing, washing
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