SWITCH- Surgical Ward Innovation: Telemonitoring Controlled by Healthdot Evaluation of Implementation
Conditions: Monitoring
Sponsor: Catharina Ziekenhuis Eindhoven

 
 
 
 
 
 
 
SWITCH - Surgical Ward Innovation: 
Telemonitored controlled by Healthdot 
 
 
  
 
Evaluation of implementation 
 
 
 
 
 
 
 
 
 

SWITCH - Surgical Ward Innovation: Telemonitored controlled by Healthdot 
Evaluation of implementation 
 
 
 
2 
 
SWITCH-project – Surgical Ward Innovation: Telemonitored Controlled by Healthdot 
Subtitle: The evaluation of the implementation  
 
Short title 
Healthdot on surgical ward 
Version 
1.0 
Date 
02 March 2022 
Principal investigator(s)  
Drs. F.M.J.F. Schonck 
(friso.schonck@catharinaziekenhuis.nl) 
Investigator(s) 
Dr. R.A. Bouwman 
(Arthur.bouwman@catharinaziekenhuis.nl) 
Dr. S.W. Nienhuijs 
(simon.nienhuijs@catharinaziekenhuis.nl) 
Dr. M.D.P. Luyer (mischa.luyer@catharinaziekenhuis.nl) 
Prof. Dr. N.J.M van der Meer 
(nardo.vd.meer@catharinaziekenhuis.nl) 
Investigational site 
Department of Surgery, Catharina Hospital, 
Michelangelolaan 2, 5623 EJ Eindhoven, The 
Netherlands 
Other participating sites 
N/A 
 
 
Sponsor 
Catharina hospital Eindhoven 
 
 
Independent expert (s) 
Evert Koldewijn, Urologist at Urology Department, Catharina 
Hospital, Eindhoven 
Laboratory sites 
N/A 

SWITCH - Surgical Ward Innovation: Telemonitored controlled by Healthdot 
Evaluation of implementation 
 
 
 
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PROTOCOL SIGNATURE SHEET 
 
Name 
Signature 
Signature + 
Date 
Head of Department 
Nardo van der Meer 
 
Principal investigator 
Friso Schonck 
 
Investigator 
Simon Nienhuijs 
 
Investigator 
Arthur Bouwman 
 
Investigator 
Mischa Luyer 
 
Investigator 
Nardo van der Meer 
 
Additional/other 
Author 
 
 
Reviewer 
 
 
Reviewer 
 
 
 

SWITCH - Surgical Ward Innovation: Telemonitored controlled by Healthdot 
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TABLE OF CONTENTS 
APPROVAL/ PROTOCOL SIGNATURE SHEET 
 
 
 
 
 
    2 
TABLE OF CONTENTS 
 
 
 
 
 
 
 
 
    4 
LIST OF ABBREVIATIONS AND RELEVANT DEFINITIONS 
 
 
 
    5 
SUMMARY 
 
 
 
 
 
 
 
 
 
 
    6 
1. INTRODUCTION AND RATIONALE 
10 
2. OBJECTIVES  
12 
3. STUDY DESIGN 
14 
4. PROJECT POPULATION 
14
 
4.1 
Population (base) 
15
 
4.2 
Inclusion criteria 
16
 
4.3 
Exclusion criteria 
16
 
4.4 
Sample size calculation 
16 
5. TREATMENT OF SUBJECTS 
16 
6 Investigational product/treatment 
16 
6.1 
Name and description of non-investigational product(s) 
16 
6.2 
Summary of findings from non-clinical studies 
18 
6.3 
Summary of known and potential risks and benefits 
18 
7. 
METHODS 
 
187.1 Study parameters/endpoints 
18
 
7.1.1 Main study parameter/endpoint 
18
 
7.1.2 Secondary study parameters/endpoints (if applicable) 
19
 
7.1.3 Other study parameters (if applicable) 
19 
7.2 
Randomisation, blinding and treatment allocation 
20 
7.3 
Study procedures 
21 
7.4 
Withdrawal of individual subjects 
22 
7.5     Replacement of individual subjects after withdrawal 
  22 
7.6  
Follow-up of subjects withdrawn from treatment 
22 
7.7 
Premature termination of the study 
22 
8 STATISTICAL ANALYSIS 
23
 
8.1 
Other study parameters 
23 
9. ADMINISTRATIVE ASPECTS, MONITORING AND PUBLICATION 
23 
 
9.1   Handling and storage of data and documents 
23
 
9.2   Monitoring and Quality Assurance 
24
 
9.3   Amendments 
24
 
9.4   Annual progress report 
24
 
9.5   End of study report 
24
 
9.6   Public disclosure and publication policy 
24 
10. REFERENCES 
25 
11. ATTACHMENTS 
27 
 

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LIST OF ABBREVIATIONS AND RELEVANT DEFINITIONS  
 
ABR 
General Assessment and Registration form (ABR form), the 
application form that is required for submission to the accredited 
Ethics Committee; in Dutch: Algemeen Beoordelings- en 
Registratieformulier (ABR-formulier) 
AE 
Adverse Event 
AR 
Adverse Reaction 
CA 
Competent Authority 
CCMO 
Central Committee on Research Involving Human Subjects; in 
Dutch: Centrale Commissie Mensgebonden Onderzoek 
CV 
Curriculum Vitae 
DSMB 
Data Safety Monitoring Board 
EWS 
Early warning score 
GCP 
Good Clinical Practice 
GDPR 
General Data Protection Regulation; in Dutch: Algemene 
Verordening Gegevensbescherming (AVG) 
IB 
Investigator’s Brochure 
IC 
Informed Consent 
Investigational 
site 
Institution or site where the clinical investigation is carried out 
IRB 
Institutional review board 
METC  
Medical research ethics committee (MREC); in Dutch: medisch-
ethische toetsingscommissie (METC) 
Sponsor 
The sponsor is the party that commissions the organisation or 
performance of the research, for example a pharmaceutical 
company, academic hospital, scientific organisation or 
investigator. A party that provides funding for a study but does 
not commission it is not regarded as the sponsor, but referred to 
as a subsidising party. 
WMO 
Medical Research Involving Human Subjects Act; in Dutch: Wet 
Medisch-wetenschappelijk Onderzoek met Mensen 
 
 
 
 
 

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SUMMARY 
Brief summary:  
Healthcare has undergone major development in recent decades due to the application of 
new technology. One of these developments concerns the monitoring of in-hospital admitted 
patients and remote monitoring of discharged patients with smart autonomous sensors (1). 
This technological development is highly desirable as the current manually performed 
monitoring is sub-optimal and has not undergone major development, unlike prevention, 
diagnosis and treatment, since the 90’s (2). Hospital care is currently in a transitional phase, 
which has been accelerated by the COVID-19 pandemic, to more outpatient care, shortened 
length of admissions and single day admission. The demographics of the hospitalized 
patients have therefore changed to a more vulnerable and comorbid population which makes 
them more prone for complications (3). On addition, the health care sector experiences staff 
shortages, especially within nursing care while the demand for hospital care expands. As a 
result, the workload is high, time is scarce and quality of care can be negatively influenced 
(4). Monitoring is according to current hospital protocol manually measured, three times a 
day and displayed as EWS score. This method is time-consuming, inefficient, subjective and 
error prone (3). Smart autonomous sensors have the potential, illustrated in previous 
research and literature, to cope with these challenges (5). However, implementation and 
integration of a new system is complex and must be carried out step by step with all those 
involved (6).  
This study aims to step-by-step implement and evaluate an already validated smart 
monitoring device, the Philips Healthdot, on a hospital ward at the Catharina hospital. 
 
Rationale: Ward monitoring is crucial in early recognition of complications and clinical 
deterioration. Smart autonomous monitoring enables continuous observation, is expected to 
reduce nursing workload, improve efficiency without compromise in confidence and might 
cause earlier recognition of clinical decline. 
 
Objective:  
Primary objectives 
Evaluation of the implementation of a continuous monitoring method on the surgical ward 
● The degree to which the Healthdot monitoring method is implemented as originally 
planned 
● Average amount of manual spot checks per hospital admission day  
 
Secondary objectives 
● The intention and attitude towards the use of the Healthdot monitoring method.  

SWITCH - Surgical Ward Innovation: Telemonitored controlled by Healthdot 
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● The extent to which the Healthdot monitoring method can be successfully carried out 
by the healthcare employees 
● Amount of manual spot checks per hospital admission day per patient 
● The perception among nursing staff given the satisfactory and agreeableness 
regarding workload.  
● Relation between device false alarms (noise) and correct alarms based on the 
alarming protocol. 
● Number of unexpected events that occur during or result from the use of the 
Healthdot medical device.  
● The amount of time needed to perform and process a complete manual spot check or 
digital monitoring check.  
● Cost-effectiveness analysis based on the duration of admission, the associated 
admission costs and the monitoring method 
● Advanced algorithm analyses for improved monitoring protocols 
 
Project design: 
This project is a 6 months monocenter prospective cohort at the Catharina hospital in the 
Netherlands. Every patient admitted to the one surgery department will receive a Healthdot. 
Implementation of the Healthdot will be performed stepwise. During phase 1 (month 1-3, the 
pre-implementation phase), the current standard method of care with manual spot checks 
and EWS will be continued. During this phase Healthdots will be applied only for training 
purposes in preparation to the implementation phase, phase 2 (month 3-6). This phase 
consists of primarily Healthdot monitoring and manual spot checks only if indicated. After 
these 6 months, the implementation will be evaluated and optimized and potentially 
extended. 
 
Participants:  
The main research population for answering the research objectives are the nurses and 
physicians working at the specific surgical ward at the Catharina hospital. 
In total around 500 patients, 250 during each phase, admitted to one surgical ward at the 
Catharina hospital will participate and receive a Healthdot as the new standard of care. 
These patients will sign informed consent for use of anonymized data.  This population 
differs in age, gender, admission cause, admission duration and comorbidities but reflects 
the demographics of the general population on this ward which is essential to investigate 
implementation and prevent selection bias.  
 

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Main implementation study parameters/endpoints:  
The medical research council (MRC) provided a document in 2000, the MRC model, to help 
researchers use the correct research designs, methods and measuring instruments (6). This 
model was revised in 2021 and forms the basis of the design of this project (6). This model 
structures the analysis using psychometric properties such as: acceptability, adoption, 
appropriateness, costs, feasibility, fidelity, penetration and sustainability (7). 
 
Primary endpoints 
Evaluation of the implementation of a continuous monitoring method on the surgical ward 
● Fidelity: The usability and degree of implementation of the Healthdot at the surgical 
ward. Measured with the System usability scale (SUS), Score > 68 at M6 (8) 
● Acceptability: The workload regarding the amount of spot checks in addition to the 
standard monitoring. Calculated with data from the electronic patient file records. 
Success in case of average reduction of 20% at M6 compared to M3 
Secondary endpoints 
● Adoption: The intention and attitude towards the use of the Healthdot monitoring 
method. Measured with evidence-based practise attitude scale (EBPAS)(9, 10).  
● Feasibility: The extent to which the Healthdot monitoring method can be successfully 
carried out by the healthcare employees. Measured with a thematic analysis and 
input from the core group (Braun and Clark)(11) 
● Acceptability: The workload regarding the amount of spot checks per hospital 
admission day per patient. Calculated with data from the electronic patient file 
records.  
● Acceptability: The perception among nursing staff given the satisfactory and 
agreeableness regarding workload. Measured with the integrated workload scale 
(IWS) (12, 13). 
● Appropriateness: Relation between device false alarms (noise) and correct alarms 
based on the alarming protocol. Measured as signal to noise ratio (SNR) 
● Appropriateness: Number of unexpected events that occur during or result from the 
use of the Healthdot medical device. Measured as adverse device events (ADE) 
● Feasibility: The amount of time needed to perform and process a complete manual 
spot check or digital monitoring check. Measured by manual time measurement. 
● Costs: Cost-effectiveness analysis based on the duration of admission, the 
associated admission costs and the monitoring method. Calculation based on 
provided care and associated costs 
● Algorithm improvement: Advanced algorithm analyses for improved monitoring 
protocols with use of artificial intelligence (AI) 

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Nature and extent of the burden and risks associated with participation, benefit and 
group relatedness:  
This implementation study is a quality project in collaboration with the quality and care 
department at the Catharina hospital as part of to the transition of care.  
Nursing staff and physicians will be trained to work with the Healthdot and its dashboard to 
evaluate the readings. The implementation of a new system, especially in healthcare, is 
challenging because of sometimes interfering interests and great responsibilities (6). With 
use of the stepwise approach and continuous evaluation with all involved, benefits such as 
reduction in workload and qualitative vial parameter live readings will be apparent (14). 
Admitted patients receiving the Healthdot might, in rare cases, experience allergic symptoms 
or discomfort wearing the Healthdot although these side effects are very rare in previous 
research (15-17). Potential chemical, electrical and biological hazards have not been 
identified(15-17). Patient related benefits include improved confidence throughout continuous 
monitoring, less impact on day-night rhythm compared to manual spot checks and more time 
for non-medical patient care (18). 
 
 
 
 
 

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1. INTRODUCTION AND RATIONALE’ 
 
the healthcare sector is a complex system which is currently in a transitional phase. As part 
of this transition there are changes and developments in the field of new systems and 
techniques. Implementation of such a new system within the healthcare system is 
challenging and still very limited investigated (19). Implementation of a new system within a 
multidisciplinary team is a enormous challenge and must be carried out step-by-step. For this 
reason, the medical research council (MRC) provided a document in 2000, the MRC model, 
to help researchers use the correct research designs, methods and measuring instruments 
(6). This model was revised in 2021 and forms the basis of the design of this project, aimed 
at implementing a smart monitoring sensor at the surgical department (6). 
 
Medical devices to monitor vital parameters were introduced during the 20th century. Around 
1990 routine monitoring with use of a universal scoring system, early warning score (EWS) 
was proposed. EWS was introduced as a potential solution for the high incidence of adverse 
events and preventable deaths in hospitalized patients (2, 3). This system was designed to 
identify the likelihood of patients deteriorating during hospitalization (2). Clinical decline is 
known to be preceded by changes in vital parameters. Early recognition of these alterations 
is crucial because early start of the appropriate treatment enhances the outcome of the 
patient (20). Postoperative complications are frequently encountered at the surgical ward. 
These complications are associated with a longer length of stay and can lead to major 
adverse events such as unplanned intensive care unit (ICU) admissions, cardiorespiratory 
arrest or even death (21). 60% of the patients with these major complications showed prior to 
the event vital sign deterioration which is frequently not recognized by medical staff or spot 
check monitoring (2). 
 
Over the years various improvements have been made to better stratify the risk for 
complications in the pre-and intra-operative setting. Vital signs are collected pre-operative 
and continuously during surgery. Postoperative monitoring at the hospital ward consist of 
three spot checks a day and consists of heart rate, respiratory rate, oxygen saturation, blood 
pressure, temperature and pain scores. These parameters are scored and displayed as an 
overall EWS score. Technological developments introduced possibilities to electrify some of 
these vital parameter measurements with enhanced accuracy as a result (5, 15, 22). The 
original EWS system was, based on new insights, improved and replaced for the modified 
EWS (MEWS) which included oxygen saturation and the national EWS (NEWS) which 
included the use of supplemental oxygen saturation (20, 21). Despite these advances, EWS 
methodological outcomes are moderate and discrimination is poor in daily practise (2, 3). 
Additionally, the application of many different subtypes is widespread and validation studies 
contain methodological and reporting shortcomings (2, 3). These factors question the clinical 
reliability of EWS and require a development regarding monitoring methods. 
 

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In the Catharina hospital, two studies were conducted with the Philips Healthdot, the PEACH 
(16) study and the TRICA study (15, 17). The TRICA study, performed at the surgical 
department, contributed to the CE-marking of the Healthdot as a monitoring device. The 
PEACH study has investigated outpatient monitoring after bariatric surgery with a positive 
result(15, 17). 
 
With the transition to surgery in ambulatory setting, accelerated by the COVID-19 pandemic, 
the hospitalized patients are older, have more comorbidities and are therefore more prone to 
complications. Early vital sign alterations such as tachypnoea and tachycardia are common 
underdiagnosed in post-operative surgery patients (22). Automated monitoring is able to 
identify these micro-events and thereby offers the potential to improve ward monitoring and 
the medical care (22). 
 
The application of smart monitoring devices as a solution for these limitations is a hot topic 
within the transition of care. Many domestic and international study groups have 
demonstrated the effectiveness of a smart monitoring sensor in improved patient monitoring 
on the hospital ward (5, 14, 23-25). 
 
Concluding, automated monitoring has great potential for improvement of hospital ward care. 
Implementation of such a new monitoring system is challenging and requires a careful 
stepwise approach. This study will investigate whether the implementation of the Healthdot 
can be achieved in a 6-month period.  
 
 

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2. OBJECTIVES 
 
Objective:  
Primary objectives 
Evaluation of the implementation of a continuous monitoring method on the surgical ward 
● Fidelity: The usability and degree of implementation of the Healthdot at the surgical 
ward 
● Acceptability: The workload regarding the amount of spot checks in addition to the 
standard monitoring.  
 
Secondary objectives 
● Adoption: The intention and attitude towards the use of the Healthdot monitoring 
method.  
● Feasibility: The extent to which the Healthdot monitoring method can be successfully 
carried out by the healthcare employees 
● Acceptability: The workload regarding the amount of spot checks per hospital 
admission day per patient 
● Acceptability: The perception among nursing staff given the satisfactory and 
agreeableness regarding workload.  
● Appropriateness: Relation between device false alarms (noise) and correct alarms 
based on the alarming protocol. 
● Appropriateness: Number of unexpected events that occur during or result from the 
use of the Healthdot medical device.  
● Feasibility: The amount of time needed to perform and process a complete manual 
spot check or digital monitoring check.  
● Costs: Cost-effectiveness analysis based on the duration of admission, the 
associated admission costs and the monitoring method 
● Advanced algorithm analyses for improved monitoring protocols 
 
Primary hypothesis: 
Previous own research (TRICA-trial, PEACH-trial) (15, 17) has shown that the Healthdot 
monitoring device is non-inferior to manual monitoring with EWS on the surgical ward 
regarding predicting and alarming of deteriorating patients based on vital parameter 
alterations. Our hypothesis is that implementation of this new monitoring method is a 
challenge but that a stepwise and careful approach, with involvement of all healthcare staff, 
will have a positive effect on the nursing workload and efficiency without reduction in 

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confidence and thereby improvement of the overall workability and efficiency at the surgical 
ward.  
 
Secondary hypothesis: 
We hypothesize that the implementation of het Healthdot will be accepted and supported by 
the nursing staff and physicians since previous research has generated a positive attitude 
towards the use of the Healthdot in our hospital. Our assumption is that the attitude towards 
this change will shift towards an even more positive mindset during the implementation 
phase and that the training prior to this will have an important contribution. This change will 
be measured by the questionnaires, calculations and the Braun and Clarke thematic 
analysis. The device performance and signal-to-noise ratio and adverse device events will be 
analysed and are not expected to adversely affect the workability based on previous 
research.  
 
These hypotheses will be accepted or rejected based on the outcome of this clinical 
investigation. 

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3. Project DESIGN 
 
This project is designed as a 6-month monocentric prospective cohort at the Catharina 
hospital in the Netherlands. In the presently unlikely event that other sites will be included 
during the conduct of het study, amendments will be submitted to all respective internal and 
external approvers (ICBE, METC). Every patient admitted to the one surgery department 
during the duration of the study will receive a Healthdot as monitoring device. Implementation 
of the Healthdot as the new standard of care regarding monitoring will be performed stepwise 
in different phases: pre-condition phase, pre-implementation phase, implementation phase 
and maintenance and evolution.  
During phase 1 (month 1-3) patients will receive the current standard monitoring method with 
manual spot checks and EWS. During this phase all healthcare staff involved will receive 
appropriate training regarding application of the device, reading and assessing the data and 
protocol explanation to optimize the infrastructure before implementation. 
During phase 2 (month 4-6) patients will be monitored with the Healthdot primarily and 
receive additional manual spot checks if indicated. After these 6 months, the implementation 
will be evaluated and optimized and potentially extended. 
 
Figure 1: Flowchart project design 

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Surgical 
war
d 
Month 1 
Month 2 
Month 3 
Month 4 
Month 5 
Month 6 
Spot check + 
EWS 
Spot check + 
EWS 
Spot check + 
EWS 
Healthdot  
Healthdot 
Healthdot 
Focus 
Training   
Training 
Training 
Implementation Implementation Implementation 
Infrastructure Infrastructure Infrastructure Evaluation 
Evaluation 
Evaluation 
Baseline data 
Baseline data 
Baseline data 
Study data 
Study data 
Study data 
Table 1: Overview focus during project phases  
Table 2: Measurement timetable for psychometric properties 
 
4. PROJECT POPULATION 
a. Population (base)  
Around 10 nurses and 5 physicians, working at the designated surgical ward, will sign 
informed consent and participate as the primary research population in the core group for in 
depth analysis regarding the implementation evaluation. 
 
Adults, male or female above 18 years old, admitted to one surgical ward at the Catharina 
hospital will be included in this prospective cohort study. Admission will mainly concern 
postoperative patients, but readmissions, clinical observation, treatment of complications or 
transfers from other departments or the intensive care unit are also reasons for admission. 
Most of the patients that will be treated at this department receive care of oncological 
surgical nature, but also general surgical patients, urological and gynaecological patients can 
be admitted to this department.  
 
FG 

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This ward has an average annual turnover of approximately 900-1000 patients each year 
based on the previous three years. A study period of 6 months is proposed to obtain a total 
of 500 patients in total, 250 patients during each study phase. 
 
b. Inclusion criteria  
Nurses and physicians are the primary research population for answering the research 
objectives.  
Nurses and physicians, participating in het focus group will sign informed consent.  
Nurses working at the surgical ward who will fill in the IWS questionnaire at multiple 
occasions will sign for informed consent on this questionnaire form (attachment 3) for use of 
the anonymized data.  
Patients won’t be included for participation since the Healthdot will be the new standard of 
care regarding monitoring. Patients will however sign informed consent at admission for use 
of anonymized data.  
 
Core/focus group 
 
Nurses 
● Registered in the national register of medical professions (Big register) 
● Appointed as a nurse at the Catharina hospital and working in the surgical department 
during the study period. 
● Willingness to participate in the core group for evaluation of the implementation 
 
 
Physicians 
● Registered in the national register of medical professions (Big register) 
● Appointed at the Catharina hospital as a physician or resident. 
● Willingness to participate in the core group for evaluation of the implementation 
 
Nursing team working at this surgical ward will fill in the IWS on a weekly base. Every nurse 
will consent to the voluntary participation for this one question inquiry and consent to use of 
the anonymous data. No additional informed consent will be asked to this group. 
 
c. Exclusion criteria 
Core/focus group 
 
Nurses & Physicians 
● Termination of employment within the study period 
● Not willingness to participate in the core group 
 
d. Sample size calculation 
Sample size calculation is not applicable for implementation projects. Nevertheless, we 
expect to obtain data from at least 500 patients, 250 patients during each phase, based 
on the average annual turnover of approximately 900-1000 patients each year over the 
previous three years at this ward. Our core group contains out of 10 nurses and 5 
physicians. 
 
 

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5. TREATMENT OF SUBJECTS 
This study does not compare treatments the implementation of a new medical monitoring 
device which will be discussed in chapter 5. 
 
6. INVESTIGATIONAL PRODUCT  
 
a. Name and description of investigational product(s) 
The Healthdot is a CE marked wearable data logger (15, 17). It consists of an 
adhesive layer, electronics and a battery. The intern mechanism contains an accelerometer 
which is able to measure movement including movement of the lung and heart. This 
movement data is processed with a validated algorithm to calculate heart rate, 
respiratory rate, posture and physical activity which are stored on the device and transferred 
through the LoRa network via the local gateway and/or gateways 
provided by KPN. The entire technological infrastructure system consists of: 
 
1. Healthdot 
 
2. Gateway 
 
3. KPN-LoRa network 
 
4. Server 
 
5. Guardian dashboard 
 
 
 
 
 
 
 
 
Required training  
The investigators, nursing staff and physicians will receive a training and e-learning during 
the pre-implementation phase about the application of the Healthdot, the activation sequence 
and data reading. In addition, the structure of the study with the questionnaires, the 
timetable, the procedures in cases of malfunctions/ ADEs will be provided in a protocol.  
 
Contra-indications 
• 
Known to have severe allergy for the tissue adhesive used in the Healthdot. 
• 
Any skin condition, for example prior severe rash, discoloration, scars or open wounds 
at the area of application 
• 
Pregnant, or breastfeeding 
• 
Use of topical that is known to influence the skin at the test area (such as medical and 
nonmedical creams or lotions) 
• 
Patient with active implantables such as Implantable Cardioverter Defibrillator (ICD) 
and pacemaker 

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• 
Unable to understand instructions 
• 
Left lower rib (place where Healthdot will be applied) is involved in the area of surgery, 
area of disinfection or area where bandages are needed. 
• 
Transfer to a different ward during hospitalization 
 
Indications for switching Healthdot 
• 
No successful measurement after 4 hours or earlier if clinically necessary. 
• 
When the Healthdot is not connected within 60 min after application 
 
Indications to remove the Healthdot 
• 
In case that an exclusion criterion is met during the study 
 
 
b. Summary of findings from non-clinical studies 
Research into the implementation of a new technology in healthcare can only be investigated 
in a clinical setting. No non-clinical studies are therefore contributing. 
c. Summary of known and potential risks and benefits 
Previous research and findings from the literature show that the use of the Healthdot as a 
monitoring device is a validated measurement method that is at least as effective as the 
manually performed measurements with EWS according to the protocols in the Catharina 
hospital. 
Serious adverse device events have not been established and mild adverse device events 
such as hypersensitivity reactions or rash have been observed only to a limited extent (15). 
Application of the Healthdot at the surgical ward is therefore possible in a safe manner, with 
the aim to implement this new monitoring method. Clinical observation and any additional 
spot checks remain available if indicated and the stepwise structure ensures optimization of 
the infrastructure before the implementation starts. This procedure optimally guarantees 
security and implementation can be carried out within a secure framework. 
 
 
7. METHODS 
a. Study parameters/endpoints 
i. Main study parameter/endpoint 
Primary parameters and endpoints 
Evaluation of the implementation of a continuous monitoring method on the surgical ward 
● Fidelity: The usability and degree of implementation of the Healthdot at the surgical 
ward 
o Measured with the System usability scale (SUS), Score > 68 at M6 (8, 26) 

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● Acceptability: The workload regarding the amount of spot checks in addition to the 
standard monitoring. 
o Calculated with data from the electronic patient file records. Success in case 
of average reduction of 20% at M6 compared to M3  
ii. Secondary study parameters/endpoints (if applicable) 
Secondary parameter and endpoints 
● Adoption: The intention and attitude towards the use of the Healthdot monitoring 
method.  
o Measured with evidence-based practise attitude scale (EBPAS) (9, 10). 
● Feasibility: The extent to which the Healthdot monitoring method can be successfully 
carried out by the healthcare employees.  
o Measured with a thematic analysis (Braun and Clark) with core group (11). 
● Acceptability: Amount of manual spot checks per hospital admission day per patient 
o Calculated with data from the electronic patient file records.  
● Acceptability: The perception among nursing staff given the satisfactory and 
agreeableness regarding workload.  
o Measured with the integrated workload scale (IWS) (12, 13). 
● Appropriateness: Relation between device false alarms (noise) and correct alarms 
based on the alarming protocol.  
o Measured as signal to noise ratio (SNR) 
● Appropriateness: Number of unexpected events that occur during or result from the 
use of the Healthdot medical device. Measured as adverse device events (ADE) 
● Feasibility: The amount of time needed to perform and process a complete manual 
spot check or digital monitoring check. Measured manually. 
● Costs: Cost-effectiveness analysis based on the duration of admission, the 
associated admission costs and the monitoring method 
● Advanced algorithm analyses for improved monitoring protocols with advanced AI 
software 
iii. Other study parameters (if applicable) 
Additional anonymized data will, in case of informed consent, be collected from the 
electronic patient file such age, gender, reason for admission, medical history, 
duration of admission, complications and laboratory results. This additional data will 
be used to relate the primary and secondary results to any influencing factors/ 
baseline characteristics and potentially correct for these factors. 
 

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Variables eCRF 
Characteristic 
Input 
Indication 
Open 
Type of invasive interventions/surgery 
Open 
Gender 
M/F 
Age 
Open 
BMI 
Kg/m2 
Comorbidities  
 
Charlson comorbidity index 
Charlson Comorbidity Index (CCI) - MDCalc 
Hospital stay 
 
Admission date 
D/M/Y 
Discharge date 
D/M/Y 
Elective or emergency 
Open 
Complications 
 
Clavien-Dindo classification 
Grade I-V 
Complications type  
Cardiac, Pulmonary, Kidney failure, 
infectious, traumatic, surgical related 
(perforation, leakage, bleeding) 
Urgent consultations (SIT) during 
hospitalization 
0-99 
ICU admission 
Yes/no 
Mortality <30 days 
Yes/no 
Re-admission < 30 days 
Yes/no 
Fidelity 
 
Total minutes monitored 
Min 
Amount of heart rate measurements 
Total number per admission 
Amount of respiratory rate measurements 
Total number per admission 
Artefact heart rate measurements 
Total number per admission 
Artefact respiratory rate measurements 
Total number per admission 
Total amount of spot checks  
Total number per admission 
Device 
 
Premature removal of device 
Yes/no 
Replacement of device 
Yes/no 
Bijzonderheden device 
Yes/no 
 
 
b. Randomisation, blinding and treatment allocation 
N/A 
 

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c. Project procedures 
Prior to the start of the pre-implementation phase there will be a pre-implementation 
phase during months 1-2. This phase will consist of training the medical staff through 
e-learning and physical meetings. During this phase, medical staff will have the 
opportunity to apply the Healthdot, learn to activate it and practise with the Guardian 
dashboard. This phase serves as preparation for the implementation and aims to 
optimize the intra-structure in advance. In addition, during this phase, baseline data 
will be collected about the standard spot check measurements, feeling of confidence 
and attitude towards a change in the monitoring method. This study is a quality 
project and a change in standard of care. Nurses and physicians voluntarily 
participating in the focus group will sign informed consent for participation. Nurses not 
participating in the focus group but working at the surgical ward during this project will  
 
During the first phase, the daily output will consist of:  
● 3x daily spot check according to the hospital protocol where the vital values are 
manually entered in the electronic patient file and scored with EWS. In addition, 
the Healthdot will be applied for training purposes. Data from the Healthdot during 
this phase will not be used in clinical care. 
 
Table 2: Current (M)EWS protocol at the Catharina hospital for ward monitoring 
 
• 
During phase 2, the Healthdot is the primary monitoring method. Each patient 
admitted to the surgical ward will receive the Healthdot during intake until 
discharge. In case the hospitalization duration is longer than the battery life, 
approximately 14 days, the Healthdot will be replaced by a new device. The 
Healthdot measures heart rate, respiration rate and physical activity every 5 
minutes. These parameters are displayed in the Guardian dashboard as a 
trendline and automatically transferred to the electronic patient file 3 times a day 
(08u,12u,17u). These measurements are scored in accordance with the alarm 
protocol and, if necessary, provide a notification. In case of an additional 
measurement, a spot check will be performed by the nursing staff. 

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The protocol alarms in case the respiration rate is above 20/min and or the heart rate 
is 110 or more for 15 minutes consecutive.  
 
     Table 3: New CREWS protocol for monitoring with Healhtdot on the ward 
 
Indications for spot check monitoring 
• 
Based on previous research, the Healthdot measurements can be relied upon, 
and no additional spot check monitoring will be routinely necessary for respiration 
and heart rate unless clinical doubt about the obtained value. 
• 
Additional spot check monitoring for blood pressure, oxygen saturation and 
temperature may be requested by any member of the treatment team 
Premature termination of the study 
• 
In the event that the International Workload Scale (IWS) (13) is in the highest 
category at moment 4-5 for more than 50% of the staff. 
d. Withdrawal of individual subjects 
Subjects of the core group can leave the study at any time for any reason if they 
wish to do so without any consequences.  
 
i. Replacement of individual subjects after withdrawal 
Participants who withdraw their participation from the core group won’t be replaced. 
 
e. Follow-up of subjects withdrawn from treatment 
 
N/A 
f. Premature termination of the study 
In case the International Workload Scale (IWS) will be in the highest category of this scale 
for more than 50% of the staff at month 4-5 during phase two of this project. 
 
 

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8. STATISTICAL ANALYSIS 
The statistical analysis at professional (nurses/ physicians) level will be performed by 
means of descriptive statistics. Each continuous parameter is analyzed for normality by 
the Shapiro-Wilk test and visually by a figure. Normality-based reporting will be done 
using medians and interquartile ranges (IQR) or means and standard deviations (SD). 
Frequencies and percentages are reported for categorical data. Each continuous 
parameter is checked for normality by the Shapiro-Wilk test and visually by a figure. 
Normality-based reporting is performed using medians and interquartile ranges (IQR) or 
means and standard deviations (SD). 
All analysis are performed using IBM SPSS Statistics 26.0 for Windows (IBM Armork, 
New York, USA) with 95% confidence interval and p < .05 as statistically significant. 
The core group consisting of nurses, physicians and investigators will conduct a 
structured analysis into the fidelity, feasibility and acceptance of the implementation and 
this information is processed and objectified by means of a Braun and Clarke thematic 
analysis. 
 
 
Table 4: psychometric properties and statistical analysis 
a. Other study parameters 
 
N/A 
 
9. ADMINISTRATIVE ASPECTS, MONITORING AND PUBLICATION 
a. Handling and storage of data and documents 
Paper research documents are stored in a folder in a lockable cabinet at the primary 
investigators office. 
Digital data will be collected with use of research manager. Access to this system will be 
logged and encrypted. 

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b. Monitoring and Quality Assurance  
Monthly evaluation, starting after 3 months, with the focus group to assure the safety and 
quality of care during this project. Thereby, repetitive measurements of the IWS will 
provide important information regarding the safety of care and base of support from all 
involved. 
 
c. Amendments  
Amendments are changes made to the research after a favourable opinion by the 
accredited METC has been given. All amendments will be notified to the METC that gave 
a favourable opinion.  
 
A ‘substantial amendment’ is defined as an amendment to the terms of the METC 
application, or to the protocol or any other supporting documentation, that is likely to 
affect to a significant degree: 
- 
the safety or physical or mental integrity of the subjects of the trial; 
- 
the scientific value of the trial; 
- 
the conduct or management of the trial; or 
- 
the quality or safety of any intervention used in the trial. 
 
All substantial amendments will be notified to the METC and to the competent authority. 
 
Non-substantial amendments will not be notified to the accredited METC and the 
competent authority, but will be recorded and filed by the sponsor.  
d. Annual progress report 
 
N/A for nWMO project 
e. Annual safety report 
 
N/A for nWMO project 
f. Temporary halt and (prematurely) end of study report 
 
N/A for nWMO project 
g. Public disclosure and publication policy 
The results will be processed into one or more scientific articles that will be submitted to 
scientific journals in the field of monitoring, surgery, medical technology and general 
health care. Publication rights belong to the investigator. Research results are the 
property of the sponsor. 
 
 
 

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10. REFERENCES 
 
1. Joshi M, Ashrafian H, Aufegger L, Khan S, Arora S, Cooke G, et al. Wearable sensors to 
improve detection of patient deterioration. Expert Rev Med Devices. 2019;16(2):145-54. 
2. Petersen JA, Antonsen K, Rasmussen LS. Frequency of early warning score assessment 
and clinical deterioration in hospitalized patients: A randomized trial. Resuscitation. 
2016;101:91-6. 
3. Gerry S, Bonnici T, Birks J, Kirtley S, Virdee PS, Watkinson PJ, et al. Early warning 
scores for detecting deterioration in adult hospital patients: systematic review and critical 
appraisal of methodology. BMJ. 2020;369:m1501. 
4. Mok WQ, Wang W, Liaw SY. Vital signs monitoring to detect patient deterioration: An 
integrative literature review. Int J Nurs Pract. 2015;21 Suppl 2:91-8. 
5. Majumder S, Mondal T, Deen MJ. Wearable Sensors for Remote Health Monitoring. 
Sensors (Basel). 2017;17(1). 
6. Skivington K, Matthews L, Simpson SA, Craig P, Baird J, Blazeby JM, et al. A new 
framework for developing and evaluating complex interventions: update of Medical Research 
Council guidance. BMJ. 2021;374:n2061. 
7. K. Mettert CL, C. Dorsey, H. Halko, B. Weiner. Measuring implementation outcomes: An 
updated systematic review of measures’ psychometric properties. Implementation Research 
and Practise. 2020. 
8. S. Peres TP, R. Phillips. Validation of the System Usability Scale (SUS). SAGE Journals. 
2013. 
9. Aarons GA. Mental health provider attitudes toward adoption of evidence-based practice: 
the Evidence-Based Practice Attitude Scale (EBPAS). Ment Health Serv Res. 2004;6(2):61-
74. 
10. van Sonsbeek MA, Hutschemaekers GJ, Veerman JW, Kleinjan M, Aarons GA, Tiemens 
BG. Psychometric properties of the Dutch version of the Evidence-Based Practice Attitude 
Scale (EBPAS). Health Res Policy Syst. 2015;13:69. 
11. Braun V, Clarke V. What can "thematic analysis" offer health and wellbeing researchers? 
Int J Qual Stud Health Well-being. 2014;9:26152. 
12. Pickup L, Wilson JR, Norris BJ, Mitchell L, Morrisroe G. The Integrated Workload Scale 
(IWS): a new self-report tool to assess railway signaller workload. Appl Ergon. 
2005;36(6):681-93. 
13. R. Kramer AJ, M. Zelstra. How Busy is Too Busy? Validation of the Dutch Integrated 
Workload Scale. Proceedings of Fifth International Rail Human Factors Conference. 2015. 
14. Patel V, Orchanian-Cheff A, Wu R. Evaluating the Validity and Utility of Wearable 
Technology for Continuously Monitoring Patients in a Hospital Setting: Systematic Review. 
JMIR Mhealth Uhealth. 2021;9(8):e17411. 
15. Jacobs F, Scheerhoorn J, Mestrom E, van der Stam J, Bouwman RA, Nienhuijs S. 
Reliability of heart rate and respiration rate measurements with a wireless accelerometer in 
postbariatric recovery. PLoS One. 2021;16(4):e0247903. 
16. Scheerhoorn J, van Ede L, Luyer MDP, Buise MP, Bouwman RA, Nienhuijs SW. 
Postbariatric EArly discharge Controlled by Healthdot (PEACH) trial: study protocol for a 
preference-based randomized trial. Trials. 2022;23(1):67. 
17. van der Stam JA, Mestrom EHJ, Scheerhoorn J, Jacobs F, de Hingh I, van Riel NAW, et 
al. Accuracy of vital parameters measured by a wearable patch following major abdominal 
cancer surgery. Eur J Surg Oncol. 2021. 
18. Downey CL, Brown JM, Jayne DG, Randell R. Patient attitudes towards remote 
continuous vital signs monitoring on general surgery wards: An interview study. Int J Med 
Inform. 2018;114:52-6. 
19. Manetti S, Vainieri M, Guidotti E, Zuccarino S, Ferre F, Morelli MS, et al. Research 
protocol for the validation of a new portable technology for real-time continuous monitoring of 
Early Warning Score (EWS) in hospital practice and for an early-stage multistakeholder 
assessment. BMJ Open. 2020;10(12):e040738. 

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20. Chen L, Zheng H, Chen L, Wu S, Wang S. National Early Warning Score in Predicting 
Severe Adverse Outcomes of Emergency Medicine Patients: A Retrospective Cohort Study. J 
Multidiscip Healthc. 2021;14:2067-78. 
21. G. Smith DP, P. Meredith, P. Schmidt, P. Featherstone. The ability of the National Early 
Warning Score (NEWS) to discriminate patients at risk of early cardiac arrest, unanticipated 
intensive care unit admission, and death. Resuscitation. 2013. 
22. Duus CL, Aasvang EK, Olsen RM, Sorensen HBD, Jorgensen LN, Achiam MP, et al. 
Continuous vital sign monitoring after major abdominal surgery-Quantification of micro 
events. Acta Anaesthesiol Scand. 2018;62(9):1200-8. 
23. Bellomo R, Ackerman M, Bailey M, Beale R, Clancy G, Danesh V, et al. A controlled trial 
of electronic automated advisory vital signs monitoring in general hospital wards. Crit Care 
Med. 2012;40(8):2349-61. 
24. Breteler MJM, KleinJan EJ, Dohmen DAJ, Leenen LPH, van Hillegersberg R, Ruurda JP, 
et al. Vital Signs Monitoring with Wearable Sensors in High-risk Surgical Patients: A Clinical 
Validation Study. Anesthesiology. 2020;132(3):424-39. 
25. M. Weenk MK, T. van de Belt, L. Engelen, H. van Goor, S. Bredie. Wireless and 
continuous monitoring of vital signs in 
patients at the general ward. Resuscitation. 2019. 
26. PLANNED. Translation and validation of the Dutch System Usability Scale. 2022. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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11. Attachments 
SUS 
 
 
 
 
 
 
 
 
 
 
 

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EBPAS 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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IWS (Dutch question options)