The digital patient journey solution for patients undergoing elective hip and knee arthroplasty : Protocol for a pragmatic randomized controlled trial

1436 | J Adv Nurs. 2020;76:1436–1448.wileyonlinelibrary.com/journal/jan Received: 20 December 2019 | Revised: 12 February 2020 | Accepted: 19 February 2020 DOI: 10.1111/jan.14343 PROTOCOL The digital patient journey solution for patients undergoing elective hip and knee arthroplasty: Protocol for a pragmatic randomized controlled trial Miia Jansson PhD, RN, Postdoctoral Researcher1,2 | Anna-Leena Vuorinen PhD, Research Scientist3 | Marja Harjumaa PhD, Senior Scientist4 | Heidi Similä D.Sc. (Tech.), Senior Scientist4 | Jonna Koivisto PhD, Postdoctoral Researcher5 | Ari-Pekka Puhto MD, PhD, Orthopaedic Surgeon6 | Gillian Vesty PhD, Associate Professor7 | Minna Pikkarainen PhD, Professor of Connected Health1,4,8 This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2020 The Authors. Journal of Advanced Nursing published by John Wiley & Sons Ltd The peer review history for this article is available at https://publo ns.com/publo n/10.1111/jan.14343 1Research Group of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland 2Oulu University Hospital, Oulu, Finland 3VTT Technical Research Centre of Finland, Tampere, Finland 4VTT Technical Research Centre of Finland, Oulu, Finland 5Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland 6Division of Operative Care, Department of Orthopaedic and Trauma Surgery, Oulu University Hospital, Oulu, Finland 7School of Accounting, RMIT University, Melbourne, Australia 8Martti Ahtisaari Institute, Oulu Business School, Oulu University, Oulu, Finland Correspondence Miia Jansson, Research Group of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland. Email: [email protected] Funding information The research will be done in the project An Intelligent Customer-driven Solution for Orthopedic and Pediatric Surgery Care, which was funded by Business Finland, a Finnish funding agency, for the period 2018–2020. Abstract Aim: To describe a randomized controlled trial (RCT) protocol that will evaluate the effectiveness of a digital patient journey (DPJ) solution in improving the outcomes of patients undergoing total hip and knee arthroplasty. Background: There is an urgent need for novel technologies to ensure sustainability, improve patient experience, and empower patients in their own care by providing information, support, and control. Design: A pragmatic RCT with two parallel arms. Methods: The participants randomized assigned to the intervention arm (N = 33) will receive access to the DPJ solution. The participants in the control arm (N = 33) will receive conventional care, which is provided face to face by using paper-based methods. The group allocations will be blinded from the study nurse during the recruitment and baseline measures, as well as from the outcome assessors. Patients with total hip arthroplasty will be followed up for 8–12 weeks, whereas patients with total knee arthroplasty will be followed up for 6–8 weeks. The primary outcome is health-related quality of life, measured by the EuroQol EQ-5D-5L scale. Secondary outcomes include functional recovery, pain, patient experience, and self-efficacy. The first results are expected to be submitted for publication in 2020. Impact: This study will provide information on the health effects and cost benefits of using the DPJ solution to support a patient's preparation for surgery and postdischarge surgical care. If the DPJ solution is found to be effective, its implementation into clinical practice could lead to further improvements in patient outcomes. If the DPJ solution is found to be cost effective for the hospital, it could be used to improve hospital resource efficiency. | 1437 JANSSON et Al. 1 | INTRODUCTION Globally, the demand and costs of primary lower-limb arthroplasty have increased significantly over the past decade. Only in the USA, for instance, the demand for total hip arthroplasty (THA) has almost doubled from 14.2–25.7 per 10,000 population (Wolford, Palso, & Bercovitz, 2015). Correspondingly, the demand for total knee arthroplasty (TKA) has doubled from 24.3–45.3 per 10,000 population in men and from 33.0–65.5 per 10,000 population in women (Williams, Wolford, & Bercovitz, 2015). At the same time, the mean length of stay (LOS) in hospital has shortened by 1 day (Williams et al., 2015; Wolford et al., 2015) due to accelerated discharge methodologies (Hansen, 2017; Lombardi et al., 2016). These streamlined discharge methodologies, however, have not avoided criticism (Jansson, Harjumaa, Puhto, & Pikkarainen, 2019a): The current state of the elective primary lower-limb arthroplasty journey is not fully meeting the needs of healthcare professionals (Jansson, Harjumaa, Puhto, & Pikkarainen, 2019b) or of patients (Jansson, Harjumaa, Puhto, & Pikkarainen, 2020). Consequently, there is an urgent need for proactive care to increase patients’ engagement in a pre-operative preparation to decrease pre-operative risk factors, which may potentially lead to complications or a prolonged LOS (Hansen, Bredtoft, & Larsen, 2012). In addition, patients need to be more involved in their postdischarge surgical care to manage their situation at home after discharge. 1.1 | Background As the demand and costs of primary joint replacement will have increased worldwide by 2030 (Culliford et al., 2015), hospital-based healthcare resources will become limited. Only in Australia, for instance, the total cost of THA/TKA may be AUD 5.32 billion by 2030 (Ackerman et al., 2019). At the same time, there is an urgent need for novel technologies to ensure sustainability, improve the patient experience, and empower patients to be responsible for their own care by providing information, support, and control (Gunter et al., 2016; Jansson et al., 2019b). While electronic health (eHealth) involves all aspects related to the application of information and communication technology (ICT) in healthcare provision, mobile health (mHealth) focuses on mobile devices and other wireless devices (WHO, 2011). The widespread deployment of mHealth technologies can help overcome some of the limitations faced by eHealth. In addition, modern mobile devices can include sensors, such as pedometers and accelerometers, that increase physical activity and other health outcomes. With the provision of healthcare services decreasing, the use of mHealth opens up big opportunities to deploy systems and services in a cost-effective way. In fact, the deployment of mobile technologies has resulted in increased patient satisfaction (Chen, Chuang, Lin, Lin, & Chuang, 2017; Clari et al., 2015; Daniels et al., 2016; Goode et al., 2018) and it has reduced postdischarge health problems (Clari et al., 2015; Daniels et al., 2016; Timmers et al., 2019) and thus reduced healthcare consumption (Clari et al., 2015; Martinez-Rico, Lizaur-Utilla, Sebastia-Forcada, VizcayaMoreno, & Juan-Herrero, 2018; Timmers et al., 2019) without an increase in adverse events (Clari et al., 2015; Goode et al., 2018). Despite the growing body of evidence, however, there is limited understanding of the effectiveness of the digital patient journey (DPJ) solutions used on a smart device that cover the whole patient journey (from home to hospital and back home). In addition, the effect of mHealth services and technologies on functional recovery in patients who have undergone THA/TKA is heterogenous and based on moderateto low-quality evidence. 2 | THE STUDY 2.1 | Aims The aim of this study is to design a detailed research protocol for the DPJ solution and evaluate its short-term effectiveness for patients undergoing elective THA/TKA. The primary outcome is to evaluate the effectiveness of the DPJ solution on health-related quality of life (QoL). The secondary trial aim is to evaluate the effectiveness of the DPJ solution on functional recovery, pain, patient experience, and selfefficacy. A cost–benefit analysis, including social project evaluation, will also be conducted from the hospital's and patients’ perspectives. At the end, the user experience with the intervention will be evaluated. 2.2 | Objectives To achieve the overall aim of the study, the following objectives are formulated: • To evaluate health-related QoL using the EuroQol EQ-5D-5L scale. • To determine the functional recovery using the Western Ontario and McMaster Universities Osteoarthritis (WOMAC), Oxford Hip Score (OHS), and the Oxford Knee Score (OKS). • To evaluate the intensity of pain using the subscales of WOMAC and the OHS/OKS, as well as the Visual Analogue Scale (VAS). • To assess the patient experience using three patient experience assessment scales. • To evaluate self-efficacy regarding preparation for surgery and postdischarge surgical care, using a single-item measurement defined for KEYWORDS arthroplasty, digital patient journey solution, mobile health, nursing, randomized controlled trial 1438 | JANSSON et Al. the purposes of the study and, regarding technology, using an adapted version of the healthcare technology self-efficacy (HTSE) scale. • To explore a cost–benefit analysis using clinical data retrieved from medical records and patient-reported experience measures (PREMs). 2.3 | Hypothesis The trial is designed to test the hypotheses at a 0.05 level of significance. To achieve the objectives of the study, the following hypothesis was formulated: The posttest QoL, functional recovery, pain, patient experience, and self-efficacy among patients undergoing elective THA/TKA in the intervention arm will significantly improve compared with the control arm. 2.4 | Trial design A pragmatic randomized controlled trial (RCT) using a two-arm preand posttest design will be conducted (Figure 1). This protocol was prepared in accordance with the SPIRIT 2013 statement. FIGURE 1 The enrolment, randomization, and follow-up of the study participants. THA, total hip arthroplasty; TKA, total knee arthroplasty Enrolment: - - - - - Revision of THA/TKA Bilateral THA/TKA THA/TKA following having rheumatoid arthritis Unable to walk without walking aids Unable to see or hear, which impedes the use of the DPJ solution Inclusion criteria: Exclusion criteria: -Ability to speak, read, and, understand Finnish Diagnosis of primary osteoarthritis of the hip or knee Aged 18 years or over Primary, elective THA/TKA Able to provide signed informed content Access to a smart device, such as smart phone or tablet computer Patient screening and recruitment during presurgery meeting Baseline assessments (n = 66) Randomization Intervention arm Digital patient journey solution Control arm Standard care Discharge outcome assessments Patients undergoing THA will be followed up for 8–12 weeks while patients undergoing TKA will be followed up for 6–8 weeks, and the outcomes will be evaluated - - - - - | 1439 JANSSON et Al. 2.5 | Ethics and trial registration The study has been reviewed and approved by ethical committee of North Ostrobothnia's hospital district in June 2019 (Ref no. 39/2019). The study will adhere to ethical standards founded on informed and voluntary consent. Written informed consent will be obtained from participants prior to inclusion in the study (Declaration of Helsinki, 2013). Participation is voluntary; participant withdrawal from the study will be respected without any disadvantage to or repercussions for the participant. The randomization of participants will ensure that all participants have an equitable chance of being allocated to either the intervention or control arms. The trial is registered prospectively at ClinicalTrials. gov (NCT04083326). 2.6 | Study setting and recruitment This study will be conducted in a single joint-replacement centre in a 900-bed, tertiary-level university teaching hospital in northern Finland. In 2018, there were a total of 365 THAs and 361 TKAs performed in the hospital by nine orthopaedic surgeons. Patients undergoing a primary, elective THA/TKA will be invited to take part in the study. The patients will be screened and recruited during the usual presurgical visit by the study nurse. The participants will be recruited between September and December 2019. Once enrolled, the patients will be randomly assigned to either the intervention arm or the control arm. 2.6.1 | Inclusion criteria The following inclusion criteria are formulated: • 18 years or older. • A diagnosis of primary osteoarthritis of the hip or knee (M16.0, M16.1, M17.0, and M17.1). • Undergoing primary, elective THA/TKA. • Access to a smart device, such as smart phone or tablet computer. • Ability to speak, read, and understand Finnish. • Able to give signed informed consent. 2.6.2 | Exclusion criteria The following exclusion criteria are formulated: • Undergoing a THA/TKA revision. • A bilateral THA/TKA. • THA/TKA following having rheumatoid arthritis. • Inability to walk without walking aids. • Unable to see or hear, which impedes the use of the DPJ solution. 2.7 | Sample size calculation We aim to detect a difference of 0.24 points (standard deviation = 0.27) in the EQ-5D-5L scores, which is considered a clinically important difference (Bilbao et al., 2018; Conner-Spady, Marshall, Bohm, Dunbar, & Noseworthy, 2018). Setting an alpha level of 0.05 and power of 0.9, 56 patients (28 in each arm) would need to be recruited. As we furthermore predict a dropout rate of 15% that increases the number of enrolled patients to 66. 2.8 | Randomization and blinding The participants will be randomized in permuted blocks of two and four, stratified by age (≤70 years old or >70 years old) and by whether or not they have had a prior joint replacement (yes or no) to either the intervention arm or the control arm in a 1:1 ratio. The allocation sequence is concealed from the study nurse using opaque and sealed envelopes until the baseline measures are completed. Due to the nature of the research, blinding will not be possible for either the participants or the healthcare team (excluding the orthopaedic surgeons). However, for the patients and for the study nurse, the group assignment will be masked during the recruitment until the baseline measures are completed. In addition, the group allocation will be masked from the outcome assessors. Due to the nature of the intervention, the risk for contamination is minimal; the DPJ solution is tailored according to patients’ individual timetable and individual needs and the journey can be accessed only with a personal activation code that each participant receives from the study nurse. In addition, the healthcare personnel is not specifically trained but all patients are treated as per usual. Therefore, we do not expect that control patients would benefit from obtaining information about the DPJ used in this study to the extent that it would affect their health-related QoL, or any other health outcome used in the study. 2.9 | The intervention 2.9.1 | The experimental intervention The participants randomized in the intervention arm will receive the same information as the control arm plus have access to the closed DPJ solution, used on a smart device. The functionality of the DPJ solution is based on an existing mobile care coordination and patient engagement platform (BuddyCare, version 2.24.0) enhanced with messaging functionality and video calls (Near Real Connect, version 1.13 for Android, version 1.10 for iOS). The flow and content of the DPJ solution was developed in collaboration with the technology providers, the clinicians responsible for the THA/TKA journey, and the researchers. It started with a process mapping workshop to build a comprehensive understanding of the current patient journey 1440 | JANSSON et Al. (Jansson et al., 2019a). The starting point for the journey was previous work done in lean transformation projects, which was then updated by the clinicians responsible for the organization of care. After the process mapping technology providers familiarized the clinicians and researchers with the current functionality of the technology, further development needs were identified by the research consortium and later through an interview study (Jansson et al., 2019a, 2019b, 2020). Through the solution, the patient can familiarize himself or herself with the phases of care through a visual timeline representation of the journey, get information on how to prepare for surgery and postdischarge surgical care, receive reminders and notifications, fill in questionnaire forms, communicate with the care personnel via a messaging functionality and video calls, or search for information from frequently asked questions. The DPJ solution can be downloaded from the Google Play and App Store by anybody, but a personal activation code is required to enter the solution. The study participants will receive this code from the study nurse and the study nurse will also help to install the DPJ solution onto the participant's smart device if required. The DPJ solution has three views: checklist, timeline, and menu views and the user can navigate between these views using the blue navigation panel at the bottom of the screen (Figure 2). The timeline is a visual timeline representation of the care pathway (the path) and is the main view. The timeline contains all the important tasks and instructions that are to be conducted before and after the surgery in chronological order. Tasks are marked with different colours based on their urgency using blue, green, orange, and pink colours. Tasks should be conducted if they are orange. Pink stands for urgent tasks, green tasks have been successfully conducted, and blue ones are upcoming. There is also a search functionality that can be used to search for any information along the timeline. The checklist contains the same information as the timeline, but the tasks are presented in a list format. It is also possible to navigate to a certain part of the timeline by selecting a task in the checklist. The menu contains all the information presented in the timeline, the forms presented in the timeline, a reporting tool for pain, a step-monitoring functionality, a messaging functionality, videos, information about the hospital, the contact information of the hospital, and user settings containing information disclosure. FIGURE 2 The digital patient journey solution can be used during the whole care path [Colour figure can be viewed at wileyonlinelibrary. com] | 1441 JANSSON et Al. The DPJ solution can be used during the whole care path. Its detailed content was developed and validated by the clinicians responsible for the THA/TKA journey. The technology providers supported the process by defining the required information and the clinicians provided the information in digital format; based on existing patient counselling materials. The DPJ solution contains all the relevant information about the operation, information videos and pictures, forms for anamnesis, anaesthesia, treatment follow-up, and reminders (e.g., when to start fasting and when to discontinue certain medication before the surgery). In addition, the DPJ solution gives instructions on how to get to the treatment unit and comprehensive guidance for wound care and rehabilitation at home after the operation. The patient solution does not run alone – the platform gives a web-based hospital dashboard for clinicians to manage the participants and their journey (e.g., to add new users, create personal activation codes, and add personalized events to the timeline, including pre-scheduled chat and video appointments). In our study, the dashboard will be used only by the study nurse. 2.9.2 | The control intervention During the study period, a specialist assessment, conducted in conjunction with pre-operative surgical visits and patient education, will be performed on the same day. Traditionally preand postoperative information is provided face to face using paper-based methods. Patients will be admitted and mobilized on the day of the surgery and discharged 2–3 days after surgery using well-defined discharge criteria (Hansen, 2017). Follow-up will be conducted by a physiotherapist (if not contraindicated) 6–8 weeks postdischarge for patients who have undergone TKA and 8–12 weeks postdischarge for patients who have undergone THA. 2.10 | Data collection methods Data will be collected by an independent study nurse who will be blinded during the recruitment and baseline measures. The outcome data will include: (a) paper-based questionnaires, (b) data collected by the DPJ solution, and (c) data from medical records. Repeated measures will be conducted preand postsurgery (Table 1). Patients who have undergone THA will be followed up for 8–12 weeks while patients who have undergone TKA will be followed up for 6–8 weeks and the outcomes will be evaluated. In addition, the patient experience and intensity of pain will be measured continuously through the journey using patient-reported outcome measures (PROMs) and PREMs. The patients in the digital journey arm will be asked to complete the relevant self-assessments through online questionnaires (excluding baseline measures); meanwhile, the patients in the conventional care arm will be asked to complete identical assessments by paper-based methods. The patients in the digital journey arm will get a push notification when the assessment is due, followed by reminders until the dedicated response time ends. A cost–benefit analysis will be conducted using clinical data retrieved from medical records and PROMs (Table 2). 2.11 | Outcomes and outcome measures 2.11.1 | Demographics Age, gender, marital and work statuses, the level of education, height and weight, the number of comorbidities, the site of surgery, the number of previous prosthetic joints, previous surgical experience, and the use of pre-surgical walking aids and opioids will be considered. In addition, the use of ICT, the Internet, and smart phone applications for measuring physical activity during sports and exercise will be considered. 2.11.2 | Primary outcome The EuroQol EQ-5D-5L assessment will be used in this study. It is a five-level, five-dimensional (i.e., the dimensions of mobility, selfcare, usual activities, pain or discomfort, and anxiety or depression) conventionalized assessment tool, used to measure health-related QoL (Herdman et al., 2011). In addition, the tool includes a VAS whereupon participants are asked to rate their health on a scale from 0 (the worst health you can imagine) to 100 (the best health you can imagine). The instrument has been validated and can be delivered by paper format or digital format (Mulhern, O`Gorman, Rotherham, & Brazier, 2015). 2.11.3 | Secondary outcomes The WOMAC is a disease-specific, self-administered health status instrument that assesses pain, stiffness, and function in patients with osteoarthritis (Bellamy, Buchanan, Goldsmith, Campbell, & Stitt, 1988). Pain is measured on a scale of 0–120 points, stiffness is measured from 0–8 points, and function is measured from 0–68 points. Higher scores indicate poorer statuses. The WOMAC is a globalized, PROM, available in 85 different language translations, and validated using Likert, numerical rating, and VAS formats. The Finnish version of the WOMAC has been validated among patients who have had elective THA/TKA due to primary osteoarthritis (Soininen, Paavolainen, Gronblad, & Kaapa, 2008). The WOMAC can be delivered by paper format or digital format (Bellamy et al., 2011). The OHS and OKS are PROMs containing 12 questions about the activities of daily living, coordination, functional mobility, gait, negative affect, occupational performance, pain, seating, and sleep (Dawson, Fitzpatrick, Carr, & Murray, 1996). Each of the questions has five categories of response. Each question is scored from 1–5 (from the least difficult to the most difficult) yielding a total score of 12–60. The OHS and OKS can be delivered by paper format or digital format. 1442 | JANSSON et Al. TABLE 1 The measures and measurement points per study arm Timepoint Enrolment Baseline Study period Close-out After surgical decision making Before the first intervention Pre-operative surgical visits Induction The day before surgery Discharge Rehabilitation Follow-up visita User experience Enrolment Eligibility screen X Informed consent X Randomization X Interventions Intervention X X X X X X Control Assessmentsb Demographics X EQ-5D-5L X X WOMAC X X OHS/OKSc X X Patient experience (long) X X Patient experience (short)d X X X X X Technological self-efficacy X X Self-efficacy regarding preoperative preparation X Self-efficacy regarding postoperative rehabilitation X Self-efficacy during the rehabilitationd X Application user experienced X Abbreviations: EQ-5D-5L, the EuroQol EQ-5D-5L scale; OHS, the Oxford Hip Score; OKS, the Oxford Knee Score; THA, total hip arthroplasty; TKA, total knee arthroplasty; WOMAC, the Western Ontario and McMaster Universities Index. aThe digital patient journey solution can be used during the whole care pathway. Follow-up will be conducted by a physiotherapist (if not contraindicated) 6–8 weeks postdischarge for patients who have undergone TKA and 8–12 weeks postdischarge for patients who have undergone THA. bThe patients in the digital journey arm will be asked to complete the relevant self-assessments through online questionnaires (excluding baseline measures); meanwhile, the patients in the conventional care arm will be asked to complete identical assessments by paper-based methods. cThe Oxford hip/knee score will be collected 6 weeks prior to surgery and 3 months after surgery from all patients by using the Omavointi service. dOnly for the intervention arm. | 1443 JANSSON et Al. The intensity of pain will be measured using the WOMAC, OHS/ OKS, and the VAS formats, which together form a widely used method to measure the intensity of pain experienced by an individual (McCormack, Horne, & Sheather, 1988) that is valid and reliable (Williamson & Hoggart, 2005). The score range of the VAS is 0–100. A higher score indicates that the patient experienced more pain. The patient is asked to mark a point on the line they feel represents the degree of the pain they suffered. The distance between the left end of the line and the point marked by the patient represents the intensity of the pain they experienced. A VAS for pain will be delivered at 1st, 3rd, 7th, and 14th day after discharge for the intervention arm only. The patient experience will be measured using the three patient experience assessment scales, which are formulated to assess: (a) care-related information, (b) the patient experience regarding a specific ward or part of the care path, and (c) the broad patient experience regarding the whole patient journey. The information-related patient experience will be investigated in connection with the DPJ solution info packages using two questions: (a) information understandability will be assessed on a 5-point Likert scale and (b) information Phone calls from/to the patient pre-surgery dd/mm/yyyy + reason (number [%]) per study arm Number of pre-surgical outpatient visits dd/mm/yyyy + reason (number [%]) per study arm Pre-surgery consultation by anaesthetist (physical/paper consultation) dd/mm/yyyy + reason (number [%]) per study arm Cancellations, no-shows, or postponement of surgery (yes/no) dd/mm/yyyy + reason (number [%]) per study arm Nursing intensity during hospitalization (at the ward, in the operating theatre, and in the recovery room) Rafaela/HOIq score/daily/patient per study arm PERIHOIq score/daily/patient per study arm The patient is mobilized according to the programme (yes/ no) Number (%) per study arm The patient is mobilized for elbows according to the programme (yes/no) Number (%) per study arm Length of hospital stay Days per study arm The total amount of pain killers Total amount of pain killers/ medicine/patient per study arm Discharge within 2–3 postoperative days (yes/no) Number (%) per study arm The need for follow-up care (yes/no) Number (%) per study arm Phone calls from/to the patient and follow-up postsurgery (between discharge and the control/ follow-up visit) dd/mm/yyyy + reason (number [%]) per study arm Cancellation, no-shows, or the postponement of the control/follow-up visit (yes/no) dd/mm/yyyy + reason (number [%]) per study arm An early (between discharge and the control/follow-up visit) complication dd/mm/yyyy + reason (number [%]) per study arm If infection: germ, amount of antibiotics/medicine/patient per study arm Need for revision (yes/no) dd/mm/yyyy + reason (number [%]) per study arm Other unplanned procedures (yes/no) dd/mm/yyyy + reason (number [%]) per study arm Readmissions to the hospital (yes/no) dd/mm/yyyy + reason (number [%]) per study arm Additional care (unplanned) due to complications (yes/no) dd/mm/yyyy + reason (number [%]) per study arm Additional care (planned) due to complications (yes/no) dd/mm/yyyy + reason (number [%]) per study arm Transportation costs and additional travel (time) dd/mm/yyyy + reason (number [%]) per study arm, estimated price TABLE 2 A cost–benefit analysis will be conducted using clinical data retrieved from medical records and patientreported experience measures 1444 | JANSSON et Al. sufficiency will be assessed by using yes–no answer alternatives with an opportunity to elaborate a no answer with free text. The patient experience regarding hospital staff and operations on a specific ward or care-path part will be investigated with a short five-question questionnaire. Four statements will be answered on a 5-point Likert scale with answer alternatives from completely disagree to completely agree and one question will be an open question, intended for additional feedback. The questionnaire is compiled based on a howRwe questionnaire (Benson & Potts, 2014). The patient experience will be investigated more thoroughly at discharge and at a follow-up meeting. The long patient experience questionnaire entails 18 questions: 17 statements will be answered on a 5-point Likert scale with answer alternatives from completely disagree to completely agree and there will be one open question, intended for additional feedback. The questionnaire is compiled based on the following questionnaires: 11 scale by Finnish institute for health and welfare (THL, 2018), the Nordic Patient Experience Questionnaire (Skudal et al., 2012), the Generic Short Patient Experience Questionnaire (Sjetne, Bjertnaes, Olsen, Iversen, & Bukholm, 2011), and the Picker Patient Experience Questionnaire (Jenkinson, Coulter, & Bruster, 2002). The patient experience instruments are formulated for this study and thus, they are not yet validated elsewhere. The DPJ solution acceptance and user experience will also be investigated at the end of the study with regard to, for example, perceived usefulness, ease of use, ease of adoption, and trust. A 28-item questionnaire is drawn up for this study based on, for example, the Technology Acceptance Model for Mobile Services (Kaasinen, 2005). The first question on whether the solution was in regular use will be assessed by using yes–no answer alternatives with an opportunity to elaborate a no answer further by giving a reason for not using the solution. Twenty-three user experience-related questions are answered on a 5-point Likert scale. Three questions regarding user satisfaction and expected future use have answer scale from 0–10, with the higher number indicating higher satisfaction and the final open question about improvement ideas or other feedback is free text. 2.11.4 | Other pre-defined outcomes A cost–benefit analysis will be conducted using clinical data retrieved from medical records and PREMs. Data to be collected from medical records are listed in Table 2. Additional methodology informed by the Global Reporting Initiative (GRI, 2015) will be used to measure the social benefits of the project from the clinician and patient perspectives (Annisette, Vesty, & Amslem, 2017; Vesty, Brooks, & Oliver, 2015). This measurement will capture the improved communication flows between the patient and the clinicians and ultimately it will enhance the reputational benefit of the healthcare provider. Provider time-based costs (e.g., the cost of: the average LOS, nursing intensity, preand postsurgery patient contact, readmission, and adverse events) and other resource consumption costs (e.g., the cost of: medication, physiotherapy interventions, and unused bed capacity), as well as patient time-based costs (e.g., the cost of: estimated transportation time and costs, additional travel, phone calls, fees, and the loss of income of both patient and family) will be calculated (Table 2). Technological self-efficacy will be measured using a version of the HTSE instrument (Asimakopoulos, Asimakopoulos, & Spillers, 2017), adapted to the context of digital health services. The self-reported instrument consists of four items measured on a 5-point Likert-scale where a higher response indicates a higher perception of technological self-efficacy. The items have been translated to Finnish by the research team. The technological self-efficacy questionnaire will be administered to both the digital journey and conventional care arms as part of the baseline and follow-up visit measurements. Self-efficacy regarding pre-operative preparation and post-operative rehabilitation will be measured by self-reported survey items developed for the purposes of this study. The items inquire about the patient's perceived self-efficacy to perform actions related to pre-operative preparations and postoperative rehabilitation. Both measurements contain one item each and are measured on a fivepoint Likert scale, where a higher response indicates a higher perception of pre-operative and postoperative self-efficacy, respectively. The pre-operative and postoperative self-efficacy survey items will be administered to both the digital journey and conventional care arms as part of the baseline and discharge measurements. In addition, the postoperative rehabilitation survey items will be administered to the digital journey arm during the rehabilitation phase via the DPJ solution on postoperative weeks 1, 3, and 5. The self-reported postoperative rehabilitation measurement contains four items developed for the purposes of this study that inquire about the patient's perception of whether he or she will be able to walk longer distances as the rehabilitation process progresses. The items are measured using a 5-point Likert scale, where a higher response indicates a higher perception of self-efficacy regarding postoperative rehabilitation. 2.12 | Statistical methods Data analysis will be performed according to the intention-to-treat (ITT) principle; patients will be analysed in the arms to which they will be randomly allocated, regardless of their exposure to the intervention. All outcomes will be analysed. Per protocol analyses are conducted secondarily to investigate the efficacy of the DPJ. Descriptive statistics will be calculated and presented between the study arms. Quantitative variables will be described using mean and standard deviation or median and interquartile range as appropriate. Categorical variables will be described using frequency and percentage values. Differences between the arms will be analysed using statistical tests accounting for repeated measures design and the results will be presented with a 95% confidence interval and the corresponding p-value. Inference will be based on the effect and the 95% confidence interval together with the p-value. The outcome assessor will not be involved with the intervention or the assessment of patients.