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Development of a computerized provider order entry system for laboratory

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par Gérard Bisama Mutshipayi
University of Ghana - Master of Science (MSc) 2015
  

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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)

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