4. Conclusion
During the review of the literature, we have identify the
following key point that will be considered in our study as guideline in the
solution we are seeking to provide on the computerization and automation of the
laboratory test order and result:
1. The testing process is complex since it involve many actors
from the order to the identification of the patient and the management of
laboratory test data.
2. The difference between clinical services creates a
breakdown of communication of flow of information of the test orders and
results since each specialties has a specifics group of diagnostics
investigation and, documents the patient record in a particular way that can
create duplication of patient information in the same hospital.
3. The automation of the management of the laboratory and
related diagnostics with a standard EMR has been proven to bring significant
improvement comparing to the paper based method. But specific health
information tools like CPOE has been proved to be more efficient for laboratory
data management than the customization of an EMR.
4. Even though some success stories has been cited and the
benefits of the electronic medical record has been proven after a lot of
implementation, the case of failure has also been recognized since the
deployment of the system does not provide the expected satisfaction. Those
challenges should be solve prior and during the deployment of the all health
information system.
5. A participatory involvement of medical stall in the system
requirement is an important step in the deployment of any health information
system and a qualitative assessment should be conducted to have feedback of the
medical practitioner on their user experience to avoid the case of abandon of
health system observed in some project.
6. The patient satisfaction should be key factor when
developing any health information system and the impact of the information
system on the medical staff workload should be minimized as possible.
7. theavailability and low cost of mobile phone even in poor
setting area makes mobile technology a viable medium to improve patient and
clinician communication experience in health care .
CHAPTER 3
5. METHODOLOGY
In this chapter, we describe the method used to analyze and
design the CPOE. We describe the mains source of the data used to build the
system starting from the chosen workflow to the business requirement
definitions. The workflow has been adapted to fit the need of a district
hospital in Ghana. We also describe the various stages in the system
development process as well as tools and techniques used to model and design
the system.
5.1. Data collection
The study was focused on the laboratory test used in the
diagnosis ofthree infectious diseases: malaria, tuberculosis and Drug
susceptibility testing (DST), and human immunodeficiency virus
(HIV).(M'ikanatha, Lynfield, Beneden, & Valk, 2013). For each of these
three diseases cited above the laboratory tests technique was based on the
criteria used by laboratory to confirm diseases, as described in case
definition for Integrated Disease Surveillance and Response in Ghana which is
based on technical guide for Integrated Disease Surveillance and Response
(IDSR) in the African region edited by World Health Organization (WHO) and
Centre for Disease Control and Prevention (CDC).(WHO & CDC, 2010) the table
3.1 shows for the chosen infectious disease the common laboratories test that
are used for diagnosis.
|
Diseases
|
Specimen
|
Laboratory tests
|
|
Malaria
|
Blood
|
Rapid diagnostic test (RDT).
|
|
Polymerase Chain Reaction (PCR) test.
|
|
Detection of parasites in thick or thin peripheral blood films
|
|
Tuberculosis and related drug resistance test
|
Sputum
|
Sputum specimen positive for Acid-Fast Bacilli (AFB) by
microscopy.
|
|
Sputum specimen positive on culture forAFB.
|
|
No specimen
|
The Mantoux tuberculin skin test.
|
|
Sputum
|
Isolation of M. tuberculosis
|
|
Nucleic acid amplification (NAA) tests
|
|
Drug susceptibility testing (DST)
|
|
HIV
|
Blood
|
Enzyme-linked Immunosorbent Assay (ELISA)
|
|
Western blot tests(WB)
|
|
P24 HIV antigen based testing.
|
Table 3.1: List of laboratory
tests for malaria, tuberculosis and HIV based on WHO IDSR and CDC.(CDC, 2015a,
2015b)(CDC, 2014a, 2014b)(WHO & CDC, 2010)(CDC, 2012)(Caminero,
2005)
The identification of patient information was based on the
recommended minimum data element, data analyses, report and presentation as
described in WHO Recommended Surveillance Standard (RSS) document. Phone number
and email of the patient will also be collected to allow the reception of SMS
and email notification.The identification information of the clinicians
ordering the laboratory test has beenalso collected with his/her phone number
and email, to allow the system to send laboratory results alert to the
clinicians. The Table 3.2 contains the set of data for the patient and
clinicians based on the WHO RSS
|
Disease
|
Minimum set of data
|
|
All (Malaria, Tuberculosis, HIV)
|
- Names of Patient
- Date of birth
- Sex
- Patient ID number or folder number (if available)
- Patient cell phone number (Compulsory)
- Patient e-mail (optional)
- Names of clinician who ordered the test
- Licence number of the clinician who ordered the test
- Cell phone number of the clinician who ordered the test
- Email address of the clinician who ordered the test
- Specimen condition
- Final lab results
- Notification type chosen by the clinician
- Date at which the clinician ordered the test
- Date Lab receive the specimen
- Date of final lab results
- Date of notification of the result to the patient
- Date results sent to the clinicians
- Location of patient ( at least at the District level)
- Location type (Urban/Rural) of patient
|
|
Malaria
|
- Pregnancy status
|
|
Tuberculosis
|
- Is it the first test for TB
- Reason: diagnosis, follow-up
- Date of the first diagnosis
- Treatment failed
- Treatment interrupted
|
|
HIV
|
- Pregnancy status
|
Table 3.2: Recommended minimum
data element of patient identification based on WHO RSS. (WHO, 1999)
| 
