case 1 report
TRANSCRIPT
Madonna Khalil Tahera Yesmin Shaoze Pan MIE561: HEALTHCARE SYSTEMS; CASE 1 REPORT; TUESDAY FEBRUARY 9TH, 2016
Toronto East General Hospital RISK MANAGEMENT STRATEGY
Executive Summary
The following report outlines a risk management strategy that helps identify deteriorating
patients at Toronto East General Hospital (TEGH). Currently, 4 out of 40 patients deteriorate
every month due to preventable causes and/or advent effects. The patient’s status is tracked using
a Modified Early Warning Score to “flag” and identify in-patients who are at risk. Patients with a
MEWS score greater than 4 (calculated based on the patient’s vital signs) receive immediate
assistance from their physician or the outreach team.
The proposed solution will allow for early detection of in-patients who are at risk, by
recommending process, technological and people changes. Implementing those changes will:
1. Increase the frequency of MEWS scores generated per patient, and
2. Increase the accuracy of the measured vital signs to better detect patient deterioration.
A mobile application can facilitate documentation of the vital signs and provide automatic
updates of the patient’s status. This will eliminate the need of the two desktops currently required
to enter the vital signs into the system. The app will also be equipped with a notification system
that will inform the nurses if they have not generated a MEWS score for their patients, and the
remaining time in which they can enter the vital signs. The app will also be equipped with a
points system that will record how many MEWS scores each nurse successfully generated. This
point system can be used by the hospital to provide financial and non-financial incentives.
The report outlines technological and process changes that aim to increase the accuracy of the
MEWS scores. Technological changes include the utilization of an EarlySense system that will
automatically measure the respiratory rate. It is also recommended to schedule the times at which
patient vital signs are being measured to eliminate any disturbances to a patient’s sleep cycle.
Decreasing the MEWS threshold from 4 to 3 will increase the sensitivity of the system at the cost
of the specificity (a lower Positive Predictive Value), allowing for thorough examination of all
patients who may be at risk.
A preliminary cost analysis was performed with a total capital cost of $45,000- $120,000
depending on the platforms on which the hospital chooses to build the app (iOS, Android or
both). The app will require an operating cost of $20,000 per year. The installation of the
EarlySense system is approximately $78,000 with a Return on Investment less than a year. The
costs to implement other strategies (posters and colour-branded patient charts) approximately
$2000.
The implementation of the multiple initiatives outlined, will provide a cost-effective solution that
is customized to the hospital’s needs, accommodates the nurses’ busy work schedule, and
improves patient care.
Table of Contents Executive Summary ...................................................................................................................................... 0
Table of Contents .......................................................................................................................................... 0
1.0 Introduction ............................................................................................................................................. 1
1.1 Report Outline ..................................................................................................................................... 1
2.0 Project Overview .................................................................................................................................... 1
2.1 Current Scenario ................................................................................................................................. 1
2.2 Problem Analysis ................................................................................................................................ 2
2.2.1 MEWS Score Frequency .............................................................................................................. 2
2.2.2 MEWS Score Accuracy ............................................................................................................... 2
2.3 Project Scope ...................................................................................................................................... 3
2.4 Relevant Stakeholders ......................................................................................................................... 4
2.5 Assumptions ........................................................................................................................................ 4
3.0 Recommended Solutions ........................................................................................................................ 4
3.1 Frequency of MEWS Scores ............................................................................................................... 4
3.1.1 Mobile Application ...................................................................................................................... 4
3.1.2 Incentives ..................................................................................................................................... 5
3.1.3 Awareness .................................................................................................................................... 6
3.2 Accuracy of MEWS Scores ................................................................................................................ 6
3.2.1 Technological Changes ................................................................................................................ 7
3.2.2 Process Changes ........................................................................................................................... 7
4.0 Preliminary Cost Analysis ...................................................................................................................... 7
5.0 Conclusion .............................................................................................................................................. 8
6.0 Future Outlook ........................................................................................................................................ 8
References ..................................................................................................................................................... 9
Appendix A: Nurse Experience .................................................................................................................. 11
Appendix B: Updating A Patient’s Status ................................................................................................... 12
Appendix C: Proposed Timeline ................................................................................................................. 13
List of Figures FIGURE 1: MEWS CRITERIA........................................................................................................................................... 1
FIGURE 2: PATIENT DETERIORATION RATE ............................................................................................................................... 2
FIGURE 3: ROOT CAUSE ANALYSIS ......................................................................................................................................... 3
FIGURE 4: SCHEMATIC PROCEDURE ........................................................................................................................................ 5
FIGURE 5: COLOUR-BRANDED PATIENT CHART ......................................................................................................................... 6
FIGURE 6: NURSE'S COMPETENCY ........................................................................................................................................ 11
FIGURE 7: PROPOSED TIMELINE ................................................................................................................................... 13
List of Tables TABLE 1: STAKEHOLDERS .............................................................................................................................................. 4
TABLE 2 PRELIMINARY BUDGET .................................................................................................................................... 8
TABLE 3: PROCESS WORKFLOW ................................................................................................................................... 12
TABLE 4: MOBILE APPLICATION PROCEDURES ............................................................................................................. 12
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1.0 Introduction Home for the Peter Munk Cardiac Centre, the living donor program and the largest and most comprehensive
multi-organ transplant program in Canada, Toronto East General Hospital (TEGH) is renowned for its treatment
of complex patient needs. Currently, a patient's’ status (acute plus, acute, and less acute) is determined through
an individual Modified Early Warning Score (MEWS) that is dependent on the patient’s vital signs. However,
10% of the patients deteriorate of causes that are preventable if detected in a timely fashion. The following
report examines the case presented by the clients: Mr. Frank DeCicco and Ms. Sarah Coppinger. It provides a
cost-effective solution that is customized to the hospital’s needs, accommodates the nurses’ busy work
schedule, and improvises patient care.
1.1 Report Outline The following report will:
● Provide the overview of the project (Section 2.0) reflecting the current scenario (Section 2.1), detail
problem analysis (Section 2.2), scope of the project (Section 2.3), key stakeholders (Section 2.4) and the
assumptions articulated for the solutions (Section 2.5).
● Feature a detailed solutions (Section 3.0)
● Deliver a preliminary budget in Section 4.0 and then
● Conclude with future outlooks in Section 5.0 and Section 6.0.
2.0 Project Overview The following section outlines the current scenario at TEGH (Section 2.1), analyzes the problems (section 2.2),
and identifies the scope of the project along with any key stakeholders and assumptions, Sections 2.3, 2.4 and
2.5, respectively.
2.1 Current Scenario A MEWS score is currently utilized at TEGH to identify “at risk” patients based on their vital signs, to prevent
deterioration and escalate care as necessary. The MEWS is a function of a patient’s systolic blood pressure,
heart rate, respiratory rate, temperature, and level of alertness. Each range of the vital signs is assigned a value
(Figure 1), with the MEWS being equivalent to the sum of all the values. Patients with a MEWS greater than
four are considered to be in critical condition and require immediate and constant care. Figure 1 depicts the
values of each of the five vital signs and their respective MEWs Scores [1].
Figure 1: MEWS Criteria
2
On average, a nurse is responsible for 5 patients per 8-hour shift. To generate a MEWs score, all vital signs
must be measured and entered into the system within an hour of each other. Two of those vital signs (the
systolic blood pressure, and pulse) are taken via machine and automatically recorded into the system, while the
remaining three are taken by the nurse- the respiratory rate and temperature are entered using the Blood
Pressure machine by the patient's’ bedside, while the level of alertness is recorded using a Workstation on
Wheels (WOW). The week of January 25th, 80% of patients had MEWs score generated- with some units at
100% and some as low as 27% [1].
The MEWS system aims to:
1) Reduce response time to identify the patients whose
conditions are deteriorating.
2) Increase outreach calls and involvement to decrease the
sufferings and pains for the patients.
Currently one in 20 patients deteriorate while in the hospitals
care with one in ten having a potentially preventable event. On
average, 40 patients deteriorate of which 4 have a potentially
preventable event per month (Figure 2) [1].
This calls for an action plan that outlines process and people changes that enable proper data and information
collection necessary to identify deteriorating patients in a timely fashion.
2.2 Problem Analysis In order to develop a detailed solution that best fits the client’s needs, a root cause analysis (Figure 3) was
conducted. As can be seen in Figure 3, the main problem can be broken into two main parts: 1) the accuracy of
the MEWS Score, and 2) the frequency of generating the MEWS score/patient. Thus, the solution will target
increasing the rate at which the MEWS score is generated and its accuracy by proposing process, technological and
people changes.
2.2.1 MEWS Score Frequency
The lack of MEWS scores generated for each patients and consistency in generating them reduces the amount
of outreach calls made. As a result, it becomes difficult to identify patients that may be deteriorating or at risk
since the main objective of the system is not being met: “flagging” patients who are in need of immediate care.
The small number of MEWS scores that are currently being generated may be an inherent result of the high
workload experienced by the nurses and the difficulty of entering the MEWS scores. To increase the outreach
calls, a better methodology of taking and entering the vital signs must be developed- one that allows nurses and
physicians to constantly observe a patient’s status.
2.2.2 MEWS Score Accuracy
The accuracy of the MEWS score generated is directly proportional to the accuracy of taking the vital signs.
The lack of an automated system that measures and collects all five vital signs is a major contributor. A
standardized method of measuring the vital signs can eliminate human errors and discrepancies from one
patient’s measurement to the next depending on which nurse took them. In addition, it is evident that there
exists a training gap (see Appendix A). Thus, to increase the accuracy, technological and process changes are
necessary.
Figure 2: Patient Deterioration Rate
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Figure 3: Root Cause Analysis
By resolving the main problems, the proposed solution (Section 3.0) will allow for early detection of in-patients
who at risk, by optimizing the system and procedures currently in place at TEGH. In doing so, it will aim to
reduce, if not eliminate, preventable deaths that occur as a result of adverse effects, or delayed diagnosis-
resulting in a 10% increase in patient mortality.
2.3 Project Scope The main purpose of the project is to reduce the patient deterioration rate per month. Identification of
deteriorated patients quickly is the most fundamental task- highly dependent on accurate and efficient MEWS
score generation. The MEWS scores generated for each patient are depended on the technology used to take the
vital signs, the process by which they are taken, and the level of experience of those who take them.
Due to the lack of empirical data from the client, the recommended solution will incorporate different measures
from the existing literatures. The solution will not focus on altering the methods by which a MEWS score is
generated, but the process of generating it.
PROBLEM SUB
PROBLEMS
THEORIES MOST LIKELY
ROOT
CAUSES
Involvement in
inputting MEWS score
Complexity in taking
the vital signs
Lack of awareness
High workload
Lack of motivation
MEWS need to be
generated within 1 hour
No visual
representation of
MEWS for each patient
Nurse/
Operator
Technology
Process
Lack of proper
information on
deteriorating
patients’ conditions
MEWS scores
are not
measured
frequently
MEWS scores
are not
measured
accurately
4
2.4 Relevant Stakeholders Table 1 identifies the key stakeholder and how they would be affected by the proposed solution.
Table 1: Stakeholders
Stakeholder Interests/ Conflicts
Patient - Improved Patient Care
- Faster Response time
- Higher mortality rate
Patient’s Family - Increase co-operation with the Healthcare team
- Increase level of competency and trust in the physician
Physicians - Reduce the frequency of outreach calls
- Identify patients that require escalated levels of care easily.
Nurses - Reduce the amount of work required to produce the MEWS score.
Hospital Board of
Directors
- Improving hospital statistics will increase the chances of receiving
funding.
- reducing the cost of lawsuits against deteriorated patients
2.5 Assumptions The following assumptions were made when developing the proposed solution:
● Each nurse is responsible for the same patients on a weekly basis .
● There exists one Workstation On Wheels (WOW) per Ward.
● Each Ward has a central computer on which Patient MEWS scores are visible, and those in risk of
deterioration highlighted.
● Nurses are allowed to carry mobile phones while on duty, and to use them for work purposes only.
● The MEWS score calculation is correct and accurate given the inputted vital signs.
● Nurses are aware of how a MEWS score is generated, and the process that is taken.
3.0 Recommended Solutions The proposed solution is composed of multiple initiatives that aim to increase the number of MEWS generated
(section 3.1) and their accuracy (section 3.2). These objectives will be met through the use of a mobile
application, posters and laminated cards to ensure that nurses follow the procedure specified by the hospital, and
the employment of advanced medical equipment.
3.1 Frequency of MEWS Scores One of the important role players in reducing the number deteriorated patients is the frequency their MEWS
scores are generated. The following sections outline methods that facilitate the process (Section 3.1.1), provide
nurses with incentives to generate the MEWS Scores (Section 3.1.2) and increase their awareness if they have
not done so (Section 3.1.3).
3.1.1 Mobile Application
The mobile application will be developed on Android and iOS platforms to help the nurses monitor the patient
and enter the MEWS scores. These two platforms were chosen due to their popularity- as of 2015, the global
market shares were dominated by Android at 82.8%, iOS at 13.9%, and windows phones at 2.3% [2]. If nurses
do not have a phone that supports either system, the hospital may subsidize a basic android phone for $100-
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$200 [3]The basic user functions of the application include 1) a login screen, 2) the ability to create a new nurse
and patient profile, and 3) managing and updating the patient’s status and vital signs.
The app allows nurses to create a personal profile with their personal ID to log into the application. The IDs
must match the hospital database during the registration process. Once a nurse successfully logs into the app,
she/he will have access to all patients in her/his ward. The app will display the patient’s name, age, current
MEWS. The patient’s vital signs are also visible to the nurse on their own personal profiles where nurses can
input the MEWS scores for each patient during the assigned shift schedule. For instance: 5:50 am-2:00 pm,
1:50pm - 9:00 pm, and 8:50 pm - 3:00 am. Nurses have to check mark that they completed the head to toe
examination along with measuring the vital
signs.
To simplify the process, the vital signs will be
entered based on their MEWS criteria as
presented in Figure 1. For example, when
entering the systolic blood pressure the nurse
will select the range in which the measured
value exists: ≤70 mmHg, 71-80 mmHg, 81-100
mmHg, and 101-199 mmHg ≥200 mmHg [4].
After the vital are entered, nurses will be
prompted to confirm the values by way of a
pop up window that will encourage them to
double check the entered metrics. While
entering the data, a notification system will
also be utilized to indicate the amount of time
remaining to ensure that a MEWS score is
successfully generated. Notifications will be
sent to the Nurse if not all of the vital signs are entered at the 30 minute, 45 minute, and 55 minute mark. If a
patient’s MEWS score breaches the threshold level of 4, the nurse, and outreach team will be immediately
notified, along with the patient’s physician. Figure 4 provides a schematic of this procedure.
The application is only operable when connected to the hospital’s internet network. The database is stored
online in the cloud server and the applicable medications for each patient is also available on the app. Any
updates made on the server will be automatically updated to the app. It also indicates the percentage of patients
that have a MEWS entered. Team supervisors/leads will have access to all patients in the hospital and can
monitor progress of all patients and nurses when inputting information. A web terminal that syncs all of the
patients’ information, will be accessible via computer, tablet and mobile browser as applicable. Basically a
master web app that have full access to the patient database of all the ward. The terminal also requires a nurse’s
id to login and there is a record of who have accessed the terminal. Major changes such as nurses changing
shifts and changing assigned patients need to be done via the web terminal for the ease to operate than on a
phone.
Appendix B outlines the procedures that the nurse would follow when updating a patient’s status.
3.1.2 Incentives To motivate and maintain a high participation rate, a “point reward system” will be incorporated into the Mobile
Application. Studies identify that nurses are not only perceptive to financial rewards but they also value non-
financial and psychological rewards [5]. For each MEWS score generated and head-to-toe examination
completed, the nurse will be rewarded “one point” respectively. A monthly evaluation (the sum of all the
Figure 4: Schematic Procedure
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points) will be available to the nurse and their superiors that will encourage constructive criticism and positive
feedback. To encourage nurses to input MEWS score and monitor the patients’ MEWS scores (to escalate high
risk patients to their physicians as needed) we propose the following reward schemes.
Financial Incentives
Financial rewards can be provided on a monthly basis to the highest performing nurse hospital wide. The nurse
with the highest number points will warrant themselves. The reward can be of the monetary value that the
hospital deems fit. This will encourage friendly competition between the nurses while optimizing patient care.
Non-financial Incentives
Nurses will also be able to challenge each other- that is, they can challenge a colleague to exceed the number of
MEWS score they generated, with whomever wins the challenge gaining additional points. Friendly
competitions can also exist between wards, where the best performing ward is awarded a prize. Again, the
rewards can will be decided by the client as to what best meets their needs.
Both of these incentives (financial and non-financial) will increase employee morale improving the work
environment. There are inevitable psychological rewards that follow, including a sense of accomplishment,
control in a sector where outcomes can sometimes feel outside of an individuals’ control, and a sense of
appreciation.
3.1.3 Awareness
In order to ensure timely input of vital signs, posters can be displayed around the hospital and by the patient’s
bed. This measure can be directly applied in current system, with no changes necessary. However, after the
implementation of the mobile app this might not be needed as there will be a reminder for each nurses to input
the MEWS score.
In addition, a color branded
patient chart is recommended.
The taking of vital signs
logically fits within processes
that nurses are already doing.
Redesigning the patient charts
will provide an additional
visual cue to the nurses.
Figure 6 [6] provides an
example of a colour branded
patient chart currently used in
Ysbyty Glan Clwyd (YGC)
hospital located in Rhyl,
Denbighshire, in central North
Wales. The patient chart
highlights the measurements
of the vital signs that indicate
that the patient is deteriorating [6].
3.2 Accuracy of MEWS Scores The accuracy of the vital signs taken by the nurses is essential for proper detection of patient deterioration-
especially using MEWS scores. The following section outlines technological and process changes (sections
Figure 5: Colour-Branded Patient Chart
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3.3.1 and 3.3.2, respectively) that aim to increase the accuracy at which the MEWS scores are taken by the
nurses.
3.2.1 Technological Changes The lack of an automated system to collect the vital signs gives rise to human error- decreasing the accuracy of
the MEWS score and inevitably preventing the detection of deteriorating patients. For example, the respiratory
rate (along with the patient’s body temperature) tends to be the first vital sign that changes in patients who are
deteriorating [7] and yet it is the least accurately taken. Early detection of heart rate/respiratory rate problems
can lead to earlier intervention, which guarantee enhanced patient safety [8].
EarlySense System is an automated system that reduces nurse’s workload. The system has the capability of
monitoring the patient’s respiratory rate, heart rate and display the patient’s physical position (lying in bed,
sitting up, or away from the bed etc.). When the vital signs change dramatically, the system will alert the nurses
via mobile notification. The server can generate unit alert reports and trends and send mobile alerts if a patient
gets out of bed. The server includes a central display station that shows each patient’s status information.
Assuming each ward has 8 beds equipped with 8 EarlySense sensor, one desktop pc, one central station, one
pager transmitter. The installation of the EarlySense system will cost approximately 78,000 CAD [8]. The
EarlySense brochure suggests that the ROI reaches breakeven within less than a year [9].
3.2.2 Process Changes Process changes in the current vital sign collection procedures and MEWS platform can be incorporated to
further increase the accuracy of the score generated. Such changes include decreasing the MEWS threshold
(section 3.3.2.1) and the time interval in which nurses can enter the vital signs (section 3.3.2.2), and the time at
which the vital signs are measured (3.3.2.3). If these changes are applied in the current system, the number of
[9]preventable deterioration cases can be decreased substantially.
3.2.2.1 MEWS Threshold
MEWS is intended to improve communication between the nursing staff and junior doctors and to ‘flag-up’
patients who need to be given immediate priority. A study conducted in general wards has shown that the
sensitivity of th3e MEWS used with a threshold score of four was 75% which the specificity was 83% [10].
Decreasing the threshold will increase sensitivity at the expense of sensitivity. That is, the positive predictive
value would decrease. However, this is in accordance with the hospitals objectives stated in Section 2.0, to
increase the number of outreach calls. Applying this change, would decrease the number of code blues, code
omegas etc., as more patients will be “flagged-up” and attended to immediately.
3.2.2.2 Time of Vital Sign Measurements
Vital sign taking of the hospitalized patients in the middle of night is one of the main reasons of interrupted
sleep [11] which can cause various problems like diminished wound healing, declining cellular immunity,
increased mortality rates and elevated blood pressure [12]; [13]. In order to eliminate such side effects, vital
signs should be taken at the start/end of every shift: 6am, 2pm and 10pm. In such cases a restful sleep from 10
PM -6 AM can be attained. This can prevent many problems in the patients which ensures less deterioration in
their conditions and less sufferings.
4.0 Preliminary Cost Analysis The app development cost (capital cost) tabulated below is based on cost estimators with the targeted app
design. The design is optioned with: Cloud infrastructure, small number of screens, standard login, structured
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data suited for database, use of data from a variety of existing sources, no integrate data from 3rd party cloud
Application Programming Interface, no engagement with users, operable offline, encrypted data on device and
server, tracking of analytic data, regular data backups, and a web portal to administer the app. The cost to
maintain the app is approximately $20,000 per year. Depending on the client’s preferences, they may proceed
with any of the options listed in Table 2.
Table 2 Preliminary Budget
App Developer Estimate Option 1: iOS Option 2: Android Option 3: Android
and iOS
Option 4: Option 3 and
Web Application
Imason Calculator [14] $68,800 $68,800 $84,600 N/A
Kinvey Calculator [15] $84,205 $82,631 $121,812 $160,986
Kony Calculator [16] $45,354 $45,354 $96,609 $120,693
The EarlySense System will cost $78,000 (see section 3.2.1) while the Colour-branded patient charts and
posters will come to a total of $1000 each [17].
5.0 Conclusion The introduction of a mobile app, vital sign measuring technology and process changes will increase the
number of MEWS scores generated and their accuracy. The ease of entering the vital signs into the mobile app
will allow for flexibility within the nurses’ schedules, with the constant notifications highlighting the
importance of entering the vital signs. The Point/Reward system will provide incentives (financial and non-
financial) to increase nurse participation. Process changes such as decreasing the MEWS threshold, scheduling
the vital sign measurements, and having colour-branded patient charts will also enhance the detection of patient
deterioration.
6.0 Future Outlook If the client chooses to proceed with the outline solution, the next steps would include:
i. Providing a detailed Project timeline that outlines (Appendix C)
a. the time required to develop the app,
b. the duration of the pilot study, and
c. Training Durations
ii. An app interface developed for the client’s inspection
iii. An advanced budget with vendor quotes
iv. Provide visual of the patient’s vital signs as a function of time.
Further initiative that can be pursued if the client sees them fit will include:
i. Shortening the time period in which all the vital signs must be entered.
ii. Redistribute the weight of the MEWS score among the five vital signs to gain a better a representation of
the patient’s condition.
iii. Organize a training session to ensure that standardized procedures are followed when taking the vital
signs.
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References
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Appendix A: Nurse Experience
Other factors that affect the accuracy of the MEWs score generated include:
1. The nurse’s experience and competency.
2. Artificial enhancements delivered to the patient (i.e., drug therapies) that may affect the results obtained.
Figure 3 displays the wide range of the nurses’ level of
expertise and experience. As can be seen, less nurses are
able to identify whether a patient is at risk (question 1)
and if they are deteriorating (question 2) if they are
working in wards that care for patients that are less acute.
The answer to both question is composed of two parts: 1)
check the patient’s vital signs, and 2) perform a head-to-toe examination. An answer is deemed correct, green, if the nurse
gets both parts of the questions. Whereas, an answer is partially accurate, yellow, if the nurse only mentions part one or
two of the answer, but not both. Finally, an answer is incorrect, red, if the nurse does not mention either parts of the
answer.
Figure 6: Nurse's Competency
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Appendix B: Updating A Patient’s Status
Use Case: Monitor a patient
Primary Actor: Nurses
Short Description: Nurses can register a patient’s information and update his/her MEWS score.
Trigger: A patient’s status needs to be updated.
Trigger Type: External
Table 3: Process Workflow
Mobile App Inputs Mobile App Outputs
Nurse Username and Password Assigned Patients, and number of
Patient Name Patient Profile (medical history, last MEWS score generated, etc.)
Vital Signs Updated MEWS scores
Table 4: Mobile Application Procedures
Sequential Procedures Input Output
The nurse logs into the application username details patient profiles and state page
2. To assign a patient to a bed, click on the “Register”
button to create a new profile.
patient details Registration Page
To enter the MEWS score, click on the entries for the
patient’s systolic blood pressure, heart rate, respiratory
rate, temperature and AVPU score.
Patient’s vital Sign Updated MEWS Scores and
patient profile
If MEWS Score is greater than threshold (i.e., >4), an
alert is sent to the outreach team, and the main desktop in
the ward.
Notify the Outreach Team Patient is “Flagged” as at risk
13
Appendix C: Proposed Timeline
The following Gant Chart presents a preliminary outline that details the project lifetime, from the the time the app is being
developed to the final implementation process.
Year 1 Year 2 Year 3
(partial)
PHASES MONTHS
M
2
M
4
M
6
M
8
M
10
M
12
M
14
M
16
M
18
M
20
M
22
M
24
M
26
M
28
1 Planning and Mobile App
Development 12
2 Feasibility Test and Train
the nurses for pilot study 2
3 Pilot study in one unit 4
4 Feedback and correction
of the App in needed 2
5 Train All the nurses 2
6 Run The App and
observation by the
development team
6
28 Total= 2 Years 4 Month
Figure 7: Proposed Timeline