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Chapter 3: Research Methodology

3.3 Our Conceptual Model

Figure 1: Conceptual Model for the TAVI system

The figure shown above represents the conceptual model for the personalized patient education system (TAVI system). The model illustrates how the system works. For instance, it contains four major elements; TAVI patient, risk variables or patient assessment, associated risks and patient education messages (Fink 32). Each of the elements has other components. For instance, the risk variable has five primary components namely;

• Baseline Multimodality Imaging
• Clinical Examinations & Medications
• Clinical Risks
• Multidisciplinary Team Review & Procedure Planning
• Personal Information & Baseline Demographics

On the other hand, associated risks element, focuses on preoperative risks and considerations while the patient education messages element is subdivided into general and personalized messages. An analysis of the system shows that risk variables element is helpful in determining the number and type of preoperative risks predisposed to the patient as well as considerations that can be made by the patient during decision making. Basically, the whole personalized education system begins with the admission of a patient, after which a medical examination is undertaken. This enables the medical practitioner to feed the information into the system. The completion of this stage leads to the advancement to the second stage, which could be patient assessment in terms of variable risks or communication through patient education massages. Taramasso et al (160) note that risk variable assessment is usually the most basic thus comes first, however, the patient education messages element is important in progressive medical examinations as it enables the medical practitioners to continue with the previous communication process that had already been established during the first encounter.

The risk variable element is concerned with assessing the patient based on risks involved when performing the TAVI procedure, MOT review, multimodal imaging, clinical examination and personal information on the client’s preferences. After the completion of this process, the associated risks are identified and fed into the system. The identification of the risks are supportive of the preoperative risks and considerations (Kasemsap et al, 153). Personal information about the patients’ medical history, preferences and family history among other personal information that might influence the successful TAVI procedure are considered. This leads to the last step of the TAVI system which is patient education through messages. Messages communicated to patients could either be generic messages or personalized messages. In most cases, the messages are combined, with a specific focus being laid on disseminating information that is personalized and specific in informing the patient on their conditions, and the available options. Haussig et al (593) note that the general information accessible to patients details basic procedures while personalized messages are specifically customized to meet the needs of the clients identified during the stage of patient assessment. Personalized information mainly contains procedural considerations that are

considerate of the patients own risks and possible outcome after the TAVI procedure.

Figure 2: TAVI System: Functional Layers

Figure 2 builds on the conceptual model for TAVI system illustrated in figure 1. Figure 2 outlines functional layers of TAVI system. The first layer is composed of inputs, the second layer entails analysis of the inputs, and the third layer is output which is stored in databases. The input layer involves collection of patient such as medical records, charts, encounters and clinical examinations. The first layer is enabled by booking clerks, physicians and nurses. This leads to the second step of entering the collected patient data into a TAVI patient assessment system. The process progresses to the second layer which involves analyzing the patient data and making a decision criteria based on two sets of decision rules. The decision criteria facilitates generation of two primary outputs; personalized patient education document and patient report (Fink 34). The analysis layer is conducted by automated and assistive information technologies while the output layer involves nurses and physicians whose main role is to edit/ review and download output or make comments on the generated patient report and the education documents. It is expected that the system will go through all the functional layers in a period ranging from 45 minutes to one hour.

3.4       Research Methodology

TAVI system will follow the clinical decision rules (CDRs). According to Abidi and Sibte (121), this is a tool that is specifically designed with the aim of helping clinicians make bedside diagnosis as well as informed therapeutic decisions. In a similar scenario, the solution approach for TAVI will be undertaken using six main steps.

Step 1: Understanding the clinical pathway. Prior to implementing TAVI, the clinicians have to gain knowledge and understand the stages through which personalized patient education can be delivered.

Step 2: Understanding the data collection protocol. It is important for clinicians to have knowledge of the patient assessment process, whereby the data collected becomes a proof-of-concept during decision making.

Step 3: Identify risk variables when using TAVI patient assessment system. This assessment will help identify and understand preoperative considerations and risks facing the patient.

Step 4: Obtaining educational content

Step 5: Developing decision rules

Step 6: Developing templates of personalized patient education documents and patient reports.

3.4.1    Understanding the Clinical Pathway

Figure 3: BPMN Diagram: The current clinical pathway for TAVI patients

As noted in the previous section, the solution approach encompasses six steps. The first step is to understand the clinical pathway of TAVI patients. The process has to engage TAVI team members at the identified research institution, which is QEII hospital. This enabled the researchers to understand the clinical pathway. In the case of this research, a shadowing of TAVI team members was undertaken in September, 2016. The process was conducted for the whole month, for a span of two days in each week. During the first week, the TAVI clinical team had a chance to interact with five newly admitted TAVI patients. In addition, the team made a follow up on three TAVI patients. The team also observed that the clinical pathway for patients begun with receiving the patient after a referral by a physician. This is followed by preparation of a medication plan by an interventional cardiologist. The cardiology office then requests the patient to perform a diagnostic examination. This examination includes carrying out a CT scan, echocardiography, cardiac catheterization and blood tests. The test results are forwarded to a cardiologist where the cardiologist office books the patient for a first visit. The first visit entails seeing a nurse and a surgeon. The nurse describes to the patient, the results collected during the first examination then asks the patient for his or her medical history among other past medical experiences such blood pressure, weight and other vital signs. The nurse, after reviewing this medication data conducts a mini mental test. The nurse then educates the patient verbally, followed by a short educational video on the TAVI procedure. The video is displayed through a desktop computer.

After debriefing by the nurse, the patient is required to visit a surgeon and a cardiologist. These two specialists will again review the patient’s medical reports as updated by the nurse. They will then check the physical ability of the patient in addition to analyzing other symptoms related to the patients’ health and wellness. This will enable them to engage the patient based on evidence derived from medical reports collected and advice on the best treatment option (Jiang et al, 303). In some instances, additional diagnostic and physical examination will be required to decide on the best medical procedure for the patient. Additionally, TAVI team members are required to meet on a weekly basis to evaluate decisions made by assessing the eligibility of the patient. The patient will then be notified of the final decision after which the cardiologist will confirm and schedule a TAVI procedure to be performed on the patient. This procedure is detailed in figure 3 (BPMN Diagram).

3.4.2 Obtaining a Data Collection Protocol

The data collected for this research was based on an assessment of patients using the TAVI patient assessment system at GEEII Hospital. The assessment was conducted on new TAVI patients in order to establish their eligibility for a TAVI procedure. The assessment was conducted in five stages; the collection of personal information as well as baseline demographic data. Second, the system conducted clinical risks associated with the procedure. Third, the clinical examination and medication process was undertaken. Fourth, the multidisciplinary team conducted a review of the patient data after which they undertook procedural planning. The fifth step involved conducting baseline multimodality imaging. Brueck et al (2) note that each of these components has related variables. Nonetheless, it is noted that the data from the patients during the medical examination, as well as previous records of medical and health history are important to the decision making process. This assessment enables TAVI team to make informed decisions based on evidence collected regarding the health conditions of the patient.

• Identifying associated preoperative considerations, risks and risk variables

Each patient considered for the TAVI procedure is believed to have an associated preoperative considerations and risks. In order to understand these risks and considerations, it is necessary to identify risk variables that will help determine both the number and time of risks likely to affect a TAVI patient. While conducting the research, the researcher, with the help of TAVI team members identified 13 possible risks and associated considerations that could arise from the sample TAVI patients used. They include;

• Possibility of developing vascular complications
• Increased risk of stroke and heart complications
• Increased procedural risk
• Increased risk of failure of pacemaker
• Increased predictor of mortality
• Possibility of considering a specific anesthetic
• Risk of prolonged stay in hospital
• Risk of kidney damage
• Need to check availability of blood products
• Risk of active cancer
• Possibility failure of information prognosis
• Demand for special assessment and consideration of wait time
• Increased risk of infection endocarditis
• Risk of eligibility of research study

After identifying these risks and considerations, the TAVI team facilitated the identification of risk variables attached to each of the risk identified. This is summarized in table 1 below.

Table 1: Risk variables associated with identified risks and considerations

3.4.4    Obtaining Educational Content

The identification of main risks and considerations, as well as their associated risk variables enabled the researchers to proceed to the next step of obtaining educational content of the messages they would want delivered on TAVI patient assessment system. The content that was introduced into the system was obtained from Dr. Beydoun and Dr. Nadeem. They both work as interventional cardiologists at the hospital in which the study was undertaken, QEII Hospital, located in Halifax. The cardiologists played an essential role in the provision of educational content and literature. Their literature was purely based on evidence thus, reinforcing the requirement for the TAVI system’s personalized patient education to be evidence based (Greenhalgh et al, g3725; DiCenso et al, 32). The educational content was guided by the 10 risks and considerations earlier identified leading to consideration for 10 categories of educational messages. 19 risks variables were then linked to the educational content leading to the formation of 19 personalized educational messages for the client. In addition to the personalized patient educational messages, the researchers, with the help of the two cardiologists identified 7 general educational messages that would be used by all TAVI patients regardless of their TAVI procedure. This totaled to 26 messages for the system. The educational content to be included in the TAVI system were summarized as follows.

Table 2: personalized patient education messages with the related risk variables

3.4.5    Developing Decision Rules

Decision rules are important in a personalized patient education system since they enable the system to limit the number of messages accessible to a patient based on the complexity of TAVI procedure and their medical history as well as preferences. The researchers developed decision rules based on the risk variables and education content available as illustrated in table 2 above. Two sets of rules were developed. Raval (12) notes that in such a system, the first set of rules is important in enabling the patient determine the type and number of risks and considerations that could arise from the TAVI procedure. The rules are based on an analysis and categorization of risk variables identified after assessing a patient.

For instance, a TAVI patient diagnosed with severe pulmonary hypertension, which according to the system is classified as a risk variable, will be able to find information on the risk of “increasing predictor of mortality’. The system will arrive at this decision by analyzing information in the system as supported by the 63 rules under the first set of rules.

Pulignano et al (D455) add that the second set of rules is equally important since it enables the system to determine the number and type of personalized patient educational messages to be displayed on the system’s monitor. The second set of decision rules is composed of 19 rules. The rules are linked to specific results determined by an assessment of risks and considerations. The determination is based on an assessment of information collected after patient assessment in addition to educational content and messages fed into the system. A reflection at the example of a patient at risk of severe pulmonary hypertension shows that the system will determine the risk of increasing predictor of mortality. The system will further analyze the results according to the second set of rules. This will enable it to deliver a specific message to the patient on the risk of death. These examples highlight the ability of the personalized patient education system to provide patients with specific and customized educational messages.

The researcher considered a further evaluation of the system based on the two sets of decisions. This led to the derivation of the following examples.

Set #1 Examples:

• R1: IF LVEF = 21- 30% OR LVEF ≤ 20% THEN Increase Procedural Risk
• R2: IF Baseline card. Rhythm & Conduction Abnormality = RBBB THEN Increase Risk of Pacemaker
• R3: IF Baseline card. Rhythm & Conduction Abnormality = PAF OR Permanent THEN Increase Risk of Stroke
• R4: IF Dialysis dependent = Yes THEN Increase Predictor of Mortality
• R5: IF Peripheral Vascular Dis. = Yes THEN Increase Risk of Vascular Complication
• R6: IF Cerebrovascular disease = Yes THEN Increase Risk of Stroke
• R7: IF Cerebrovascular event = Yes THEN Increase Risk of Stroke
• R8: IF Pulmonary Hypertension = Yes AND Severe: >55 mmHg THEN Increase Predictor of Mortality
• R9: IF Chronic lung disease = Severe THEN Increase Predictor of Mortality AND Needs Specific Procedural Consideration
• R10: IF Home Oxygen = Yes THEN Increase Predictor of Mortality AND Needs Specific Procedural Consideration

Set #2 Examples:

• IF {R1} THEN Message 1 (M1)
• IF {R2} THEN Message 19 (M19)
• IF {R3} THEN Message 12 (M12)
• IF {R4} THEN Message 9 (M9)
• IF {R6 + R7} THEN Message 13 (M13)
• IF {R9 + R10} THEN Message 14 (M14)

3.4.6    Developing Patient Report and Personalized Patient Education Document Templates

The researchers upon developing decision rules came up with two templates depicting the main outputs of the system; personalized patient education document and the patient report. Whereas the personal report contained the patient’s information in terms of basic identification information, and a list of preoperative risks and considerations as noted during the assessment, the personalized patient education document detailed main personal information of the patient as well as a list of preoperative risks and considerations. Access to the patient’s report was limited to physicians and nurses while that of personalized patient education document was used by the patient. The document contained personalized messages for the patient.

4. Proposed Clinical Pathway for TAVI Patients based on Researchers Approach

Figure 4: BPMN Diagram: The proposed clinical pathway for TAVI patients as supported by researchers approach

After researching the current TAVI system used at QEII Hospital, the researcher proposed the introduction of a web-based system. The system will be vital for first clinical visits for TAVI patients. Patient assessment will be the main component of the system. The research further proposed the adoption of a TAVI system that generates two output, into the current pathways illustrated in this methodology. Further improvements of the system will ensure that only legalized booking clerks including TAVI team nurses, surgeon and cardiologists can add or make changes to the data fed into the system (Zhao et al, 125). All information collected after examination and assessment of the patient will be entered into the TAVI system. Feeding all the information into the system is vital in enabling it to generate an accurate personalized patient education document and a patient report. All these documents enhance the precision of decision making in regard to TAVI procedures. The personalized patient education document can also be shared to family members of the patient to encourage them to contribute towards decision making and informed consent. The system is highly effective since it provides specific information that enables the recognition of risks and considerations associated with a TAVI procedure.

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