Mobile applications in enhanced recovery after surgery: a systematic review of protocol adherence and outcomes

Introduction

Enhanced recovery after surgery (ERAS) programs are structured, multidisciplinary perioperative pathways designed to optimize postoperative recovery, minimize complications, and shorten hospital length of stay (LOS) (1). Initially developed for colorectal procedures, ERAS protocols have since been adapted to various surgical specialties, including thoracic, gynecologic, urologic, and breast surgery (2). These pathways incorporate evidence-based practices across all phases of perioperative care, from pre-admission to postoperative recovery (3).

Despite well-documented clinical benefits, consistent implementation of ERAS protocols remains challenging, among the barriers, patient adherence plays a critical role, as suboptimal engagement may compromise intended outcomes (4). In response, mobile health (mHealth) technologies have emerged as potential tools to support adherence by offering educational content, real-time monitoring, and streamlined communication between patients and providers (5).

However, current evidence on the effectiveness of mobile applications within ERAS pathways is inconclusive. While van der Storm et al. reported a 10% increase in adherence among app users (6) particularly in areas such as early mobilization and oral intake—Mata et al. observed no significant differences in adherence or clinical outcomes when comparing app-based and standard care (7). These inconsistent findings may be attributed to variations in app design, study methodologies, or surgical populations.

To date, no systematic review has focused on mobile applications within ERAS protocols across multiple surgical domains. Existing reviews have tended to focus either on broader digital health interventions, such as web-based tools or telehealth platforms, or on single surgical specialties (8,9). This systematic review aims to examine the role of mobile applications in the context of ERAS pathways, with a specific focus on their influence on protocol adherence and perioperative outcomes. By synthesizing current evidence, the review seeks to address a gap in the literature concerning the effectiveness of app-based interventions as targeted tools for enhancing surgical recovery. We present this article in accordance with the PRISMA reporting checklist (available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-25-37/rc).

Methods

This review was prospectively registered in the International Prospective Register of Systematic Reviews (PROSPERO) under the protocol ID CRD420250656160.

Additionally, the overall interpretation of findings considered principles from the GRADE (Grading of Recommendation, Assessment, Development, and Evaluation) framework to reflect on the certainty of evidence.

Search strategy and data extraction

A comprehensive literature search was performed on PubMed, EMBASE, and the Cochrane Library to identify relevant studies published up to February 2025. The search strategy included combinations of the following controlled vocabulary and free-text terms: “Enhanced Recovery After Surgery”, “enhanced recovery”, “fast-track surgery”, “digital health”, “mobile health”, “mobile applications”, and “health apps”. No language restrictions were applied (Appendix 1). In addition, a manual search of reference lists from eligible studies and relevant review articles was conducted (reference snowballing) to identify additional publications. The search strategy was developed to ensure broad capture of literature involving mobile applications specifically used to support perioperative care within ERAS protocols.

Study selection

Following deduplication, all records were independently screened by two reviewers (P.D.D. and R.E.N.d.N.O.) using a two-stage process. First, titles and abstracts were assessed for relevance. Full texts of potentially eligible studies were then reviewed against predefined inclusion and exclusion criteria. Discrepancies in study selection were resolved through discussion or consultation with a third reviewer (V.A.B.).

Eligibility criteria

Studies were eligible for inclusion if they met the following criteria: (I) employed a randomized controlled trial (RCT) design or an observational design (prospective or retrospective cohort studies); and (II) evaluated the use of mobile applications as an intervention to support postoperative recovery in adult patients undergoing surgery within an established ERAS protocol. Studies were not required to include a comparator group.

Studies were excluded if they (I) evaluated perioperative pathways not based on ERAS principles; (II) evaluated telerehabilitation or wearables without defined ERAS pathways; (III) incorporated wearable devices in addition to apps without isolating the app’s effects; or (IV) were published as conference abstracts, commentaries, editorials, or narrative reviews.

Quality assessment and publication bias

The methodological quality of the included studies was assessed using two validated tools according to study design. For RCTs, we used the Cochrane Risk of Bias 2.0 (RoB 2) tool (10), which evaluates five domains: bias arising from the randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result. For observational studies (prospective or retrospective cohorts), we used the Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) tool. Two reviewers independently performed the assessments, and disagreements were resolved through discussion or consultation with a third reviewer.

Two reviewers (F.S.P. and R.E.N.d.N.O.) independently performed risk-of-bias assessments. To ensure consensus, any disagreements were resolved through discussion or adjudicated by a third reviewer. The assessments’ results were synthesized descriptively to inform the interpretation of findings and the overall strength of the evidence.

The overall quality of the evidence was assessed following the GRADE guidelines.

Data extraction

Two reviewers (F.S.P. and R.E.N.d.N.O.) independently performed data extraction, which a third author (V.A.B.) verified as accurate. The extracted variables included study characteristics (year of publication, country, study design, surgical specialty, sample size, interventional details, and reported outcomes) and patient demographics (age, sex, and type of surgery).

Outcomes

The primary outcome of this review was adherence to ERAS protocols, defined as the extent to which patients followed prescribed perioperative measures, including early mobilization, oral intake, preoperative preparation, and other protocol-specific components, as reported in the original studies. Secondary outcomes included several clinically relevant and patient-centered measures. Quality of recovery was assessed using validated instruments such as the Quality of Recovery-15 (QoR-15) scale, when available, capturing dimensions such as physical comfort, emotional state, and return to baseline function. Patient experience and satisfaction outcomes encompassed subjective assessments of care quality, app usability, and perceived benefits of digital support. Clinician-related outcomes included acceptance of the intervention, perceived workflow impact, and communication efficiency. Postoperative complications were reported as composite metrics or stratified by type (e.g., infection, thromboembolism, wound dehiscence), depending on study design. Hospital LOS was defined as the total number of inpatient days from surgery to discharge. Finally, 30-day readmission rates were reported as the proportion of patients requiring hospital readmission within 30 days following the index procedure.

For the purposes of this review, adherence is defined as the extent to which a patient follows the prescribed ERAS components (e.g., early mobilization, oral intake). Compliance refers to the measurable fulfillment of protocol elements, often used interchangeably with adherence in the included studies. Engagement is used to describe the patient’s active involvement, motivation, and interaction with digital health tools, which may influence adherence but is not directly equivalent.

Data synthesis

Due to substantial heterogeneity across the included studies, a meta-analysis was not feasible. Variations were observed in key methodological domains, including study design (RCTs, prospective and retrospective cohorts), surgical specialties (colorectal, gynecologic, thoracic, and breast procedures), and mobile application characteristics (e.g., level of personalization, platform, integration with clinical teams). Furthermore, outcome measures differed considerably—quality of recovery was assessed using scales such as the QoR-15 and the Patient Satisfaction Questionnaire III (PSQ-III). At the same time, adherence was variably defined and measured using app checklists, self-report logs, or clinical documentation. Clinical endpoints like pain, complications, and readmissions were inconsistently reported or lacked standardized metrics. This level of clinical and statistical heterogeneity precluded the calculation of pooled effect sizes, and as such, a qualitative synthesis was conducted.

Results

Study selection and characteristics

Through systematic database searches, 1,271 records were identified. After deduplication and screening, eight studies met the inclusion criteria and were included in the final synthesis. The included studies were published between 2019 and 2025 and conducted in Canada, Italy, the Netherlands, and the United States. Although most studies focused on colorectal surgery, patients undergoing thoracic procedures, gynecologic oncology surgeries, and breast reconstruction were also represented. The PRISMA flow diagram is presented in Figure 1.

Figure 1 PRISMA flow diagram. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Across the eight studies, a total of 1,623 patients were enrolled; 1,105 patients (68.1%) received ERAS care supported by a mobile application, and 518 (31.9%) received standard ERAS care without digital support. Sample sizes ranged from 47 to 484 patients. The mean age of participants ranged from 44.7 to 68 years. Studies involving gynecologic and breast surgery included only female participants, while male representation in colorectal cohorts ranged from 47% to 56%. A detailed summary of demographic and clinical characteristics is provided in Table 1.

The mobile applications evaluated across the included studies demonstrated considerable variability in design and functionality. Most apps provided preoperative education, reminders, daily health checks, and progress tracking, while some offered advanced features such as real-time feedback, patient-clinician messaging, and automated alerts based on recovery scores. Integration with the clinical team was present in the majority of cases, though the degree of personalization ranged from low to high. Table 2 summarizes the core characteristics of each mobile application, including platform compatibility, feature sets, and level of clinical integration.

Risk of bias assessment

The methodological quality of the included studies was appraised using two validated instruments, in accordance with Cochrane and PRISMA guidelines: the RoB 2.0 tool for RCTs and the ROBINS-I tool for non-randomized studies. Figure 2 summarizes the overall risk-of-bias evaluations (10).

Figure 2 Risk of bias assessment of included studies. (A) RoB 2 assessment for RCTs, evaluating three studies (Mata et al., Temple-Oberle et al., and van der Storm et al.) across key domains: randomization process, deviations from intended interventions, and missing outcome data. Color coding reflects the level of bias: green, low risk; yellow, some concerns. (B) Risk of bias assessment for non-randomized studies using the ROBINS-I tool. Bar graphs display the proportion of studies rated as low, moderate, or serious risk of bias and an overall evaluation of observational study quality. RCT, randomized controlled trial; RoB 2, Risk of Bias 2.0.

Among the three RCTs assessed using RoB 2.0, all were judged to raise some concerns regarding risk of bias, primarily due to the lack of blinding and the use of self-reported outcome measures. The study by Mata et al. [2019] was rated as having low risk of bias in domains related to the randomization process, missing outcome data, and selection of the reported result (7). However, some concerns were identified in domains associated with deviations from intended interventions and outcome measurement. Specifically, the absence of participant and caregiver blinding, combined with reliance on partially self-reported adherence data, may have introduced both performance and detection biases.

Similarly, van der Storm et al. [2025] was judged to be at low risk of bias for randomization and missing data but raised some concerns related to unblinded intervention delivery and the self-reported nature of the primary outcome (6). These issues may have influenced patient behavior and reporting accuracy. The trial by Temple-Oberle et al. [2023] followed a comparable pattern, with low risk in the domains of randomization and data completeness, but some concerns in relation to deviations from intended interventions and measurement of outcomes—once again due to the absence of blinding and use of subjective, self-reported adherence measures (11).

Overall, all three RCTs were judged to have some concerns regarding risk of bias, with the primary limitations stemming from the inherent difficulty of blinding participants and providers in digital health interventions and the consequent reliance on self-reported outcomes (Figure 2A).

For the five observational studies, risk of bias was assessed using the ROBINS-I tool. As shown in Figure 2B, all were judged to be at moderate risk of bias, largely attributable to residual confounding and limitations in the classification of interventions and outcome measurement. Domains with the most frequent concerns included confounding (D1), deviations from intended interventions (D4), and classification of the interventions (D3)—reflecting the methodological challenges typical of non-randomized designs. Nonetheless, all studies demonstrated low risk of bias in at least three domains, most consistently in relation to participant selection (D2), missing data (D5), and selection of reported results (D7), indicating reasonable transparency and execution rigor.

Collectively, while the included studies support the potential benefits of mobile application–assisted ERAS protocols, the overall moderate risk of bias—particularly among observational studies—emphasizes the need for cautious interpretation and reinforces the importance of future high-quality randomized trials to confirm these findings.

According to the GRADE assessment, the outcomes evaluated in this review were: ERAS protocol adherence, surgical site infection (SSI), recovery quality (QoR‑15), patient satisfaction, and LOS. ERAS protocol adherence was rated as moderate‑certainty evidence. SSI, QoR‑15, patient satisfaction, and LOS were rated as low‑certainty evidence.

Outcomes

All included studies reported outcomes related to ERAS protocol adherence, quality of recovery, patient satisfaction, and postoperative complications. The use of mobile applications was generally associated with improved adherence. Beeson et al. observed that in-app checklists and reminders supported adherence to early mobilization, oral intake, and medication routines (12). Bertocchi et al. reported an overall ERAS adherence rate of 74.1%, with 62.4% of patients adhering specifically to the iColon app; a strong correlation was identified between app use and adherence (r=0.94, P<0.001) (13). Similarly, van der Storm et al. found higher adherence rates in the intervention group (76.4% vs. 66.4%, P=0.003), with substantial differences in early oral intake (87.5% vs. 45.6%, P<0.001) and mobilization (93.1% vs. 66.2%, P<0.001) (6). Kneuertz et al. noted that 95% of SeamlessMD patients received preoperative instructions and fully adhered to preoperative fasting and hygiene protocols (14). By contrast, Mata et al. found no significant difference in overall adherence between groups (62% vs. 59%, P=0.53) (7).

Quality of recovery was assessed using the QoR-15 scale in three studies. Beeson et al. reported higher patient-reported scores in domains such as communication with family and personal hygiene and lower scores in sleep quality and return to daily activities, although differences were not statistically tested across all domains (12). Temple-Oberle et al. observed significantly higher overall QoR-15 scores in the mobile app group at 2 weeks (127.58±22.03 vs. 117.68±17.52, P=0.02) and 6 weeks (136.64±17.53 vs. 129.76±16.42, P=0.03) (11). In contrast, van der Storm et al. reported no significant differences in recovery scores between groups (6).

Patient satisfaction and user experience were generally positive across the included studies. In Beeson et al., 72% of app users and 86% of non-users found the tool helpful for managing self-care, with particular value attributed to structured educational content and daily monitoring (12). In the study by Bertocchi et al., 94.9% of patients provided positive feedback on the iColon app, and 92.7% believed it improved their quality of care (13). Temple-Oberle et al. found no significant difference in PSQ-III satisfaction scores between groups at 2 or 6 weeks. However, indirect costs were significantly lower in the intervention group at 6 weeks ($85.80±85.20 vs. $363.40±159.52, P=0.02) (11). Kneuertz et al. reported that 77.4% of patients rated their hospital experience as “excellent”, and 93.5% stated they would recommend the hospital based on their experience using the mobile application (14).

Clinician experience and acceptance of mobile applications were also explored. Kneuertz et al. noted a reduction in unnecessary postoperative communication and improved workflow efficiency (14). Beeson et al. found that seven of eight clinicians supported broader implementation of the app, citing improved consistency of information and reduced administrative burden (12). Similarly, van der Storm et al. reported that the app did not increase clinician workload. Schlund et al. (2020, Colorectal Disease) identified lower hospital costs among app users ($11,560 vs. $13,946, P=0.024). However, concerns were raised in some studies about accessibility and usability among patients with low digital literacy (15).

Postoperative complications were variably reported. Between groups, Mellucci et al. and Mata et al. observed no significant differences in complication rates, 30-day readmissions, or composite complication scores (7,16). Temple-Oberle et al. found no significant differences in wound infection rates, hematoma, seroma, or dehiscence. One patient in the app group experienced a pulmonary embolism, identified through a QoR-15-triggered alert (11). Schlund et al. reported a significantly lower SSI rate in the app group (3.4% vs. 11.3%, P=0.019) (15). van der Storm et al. found no difference in overall complication rates (26.4% vs. 23.5%, P=0.736) but reported lower pain scores on postoperative day 7 in the app group [Visual Analog Scale (VAS) 2.5 vs. 3.3, P=0.021] (6).

Hospital LOS did not significantly differ in most studies. Mata et al. reported a median hospital LOS of 4 days in the app group compared to 3 days in controls (P=0.33) (7). Mellucci et al. found that patients using the patient engagement technology (PET) app had a lower risk of prolonged hospitalization beyond 3 days [odds ratio (OR) 0.5, 95% confidence interval (CI): 0.4–0.8] (16). Readmission rates showed mixed findings. Bertocchi et al. reported that non-adherent patients had a significantly higher risk of 30-day readmission (P=0.014) (13). Schlund et al. (15) found no significant difference in readmission rates (15.0% vs. 10.6%, P=0.345). Mellucci et al. [2019] observed reduced readmission risk among older app users (OR 0.2, 95% CI: 0.1–0.7) and those with high engagement (OR 0.3, 95% CI: 0.1–0.8, P<0.05) (16).

Discussion

This systematic review evaluated eight studies encompassing 1,623 patients to examine the role of mHealth applications within ERAS protocols. The main finding is that these digital tools are consistently associated with improved patient adherence, particularly regarding early mobilization and oral intake—core elements of ERAS pathways. This benefit was observed across multiple surgical disciplines, despite variations in study design and app functionalities.

Enhanced adherence emerged as the most reproducible outcome of mobile app integration. Several studies demonstrated statistically significant gains in adherence among app users (6,13), aligning with prior literature from non-surgical settings in which digital reminders and self-monitoring were shown to promote behavioral change and treatment fidelity (5). However, this effect was not universal. One randomized trial by Mata et al. reported no significant difference between groups, highlighting that adherence benefits may depend on factors such as interface quality, patient literacy, and clinical reinforcement (7). These findings reflect the broader reality of digital health: success is often context-dependent and reliant on implementation quality rather than technology alone (17).

Patient-reported outcomes such as perceived recovery, emotional well-being, and self-efficacy were variably affected. Temple-Oberle et al. found significantly higher QoR-15 scores in the app group at both 2 and 6 weeks, reinforcing the potential of mobile platforms to support recovery beyond traditional metrics (11). This is consistent with findings in cardiac ERAS programs, where digital engagement has been associated with improved self-efficacy and reduced anxiety (8,11) Conversely, other studies reported no significant difference or mixed results, particularly when recovery domains such as sleep or return to baseline activities were examined independently (6,12). These inconsistencies suggest that while apps may support communication and education, they are unlikely to fully address recovery dimensions dependent on physical rehabilitation or systemic support.

Satisfaction and usability outcomes were generally favorable across studies. Patients frequently reported valuing app features such as real-time monitoring, structured perioperative guidance, and expectation management, which likely contributed to enhanced engagement and perceived support during recovery (13,14). These findings are consistent with prior meta-analyses demonstrating that personalization and user-centered design are critical determinants of digital health tool acceptability and sustained use (18). Nevertheless, the absence of significant differences in standardized satisfaction scores, combined with persistent barriers faced by digitally underserved populations, reinforces the importance of equity-oriented development and accessibility testing. Notably, data from Schlund et al. and Temple-Oberle et al. suggest that mobile applications may also contribute to reduced hospital costs and indirect patient expenses, underscoring their potential economic value (11,15). However, platform usability—including aspects such as interface intuitiveness, navigation flow, and technical reliability—was not systematically assessed in most studies. These elements are crucial for maintaining adherence, especially among older adults or individuals with limited digital proficiency. To optimize future implementations, studies should incorporate validated usability instruments [e.g., the System Usability Scale (SUS)] and report patient experience metrics to ensure that digital solutions are not only technically effective but also accessible, inclusive, and user-friendly.

In the broader digital health landscape, evidence from orthopaedic care further corroborates our findings. A recent systematic review and meta-analysis of six RCTs on total knee arthroplasty (TKA) rehabilitation demonstrated that app-based telerehabilitation significantly improved outcomes such as pain control, range of motion, functional scores (both objective and subjective), patient satisfaction, and adherence, compared to conventional therapy (effect size for subjective function ≈0.57; 95% CI: 0.11–1.02) (19). While these studies did not explicitly utilize full ERAS pathways, they emphasize the pivotal role of mobile applications in enhancing recovery through structured perioperative guidance and patient engagement. Integrating these insights strengthens the generalizability of our conclusions across surgical specialties and highlights the opportunity for orthopaedic-specific adaptations of ERAS-aligned mHealth tools.

Regarding safety, the majority of studies reported no increase in postoperative complications or readmissions with app use. Some even suggested favorable trends, such as reduced infection rates or lower postoperative pain, although not all were statistically significant (6,15). Such trends may reflect improved adherence to perioperative hygiene measures and the early recognition of symptoms enabled by app-based alerts. Nevertheless, studies such as Mellucci et al. found no measurable benefit, underscoring the need for cautious interpretation (16). Given that the majority of included studies were observational in nature, residual confounding and selection bias cannot be ruled out as contributors to the observed associations.

Beyond clinical outcomes, critical issues related to digital equity, readability, and health literacy remain underexplored. Despite the patient-facing nature of mHealth applications, none of the included studies conducted a formal readability analysis or assessed the appropriateness of app content for users with limited health or digital literacy. This omission is particularly relevant given that engagement with digital tools is strongly influenced by a patient’s ability to comprehend and navigate technology, and that vulnerable populations—including older adults, individuals with lower socioeconomic status, and those with limited formal education—are disproportionately affected by such barriers. The absence of stratified outcomes based on literacy level or technological familiarity represents a significant gap in the current literature. Future studies should adopt inclusive design principles, evaluate usability across diverse literacy profiles, and incorporate standardized tools to assess digital and health literacy. Doing so is essential not only to improve engagement and effectiveness but also to ensure that mHealth tools contribute to narrowing—rather than exacerbating—existing disparities in surgical care.

This review has several limitations. The majority of included studies were observational in nature and of moderate methodological quality, which limits the strength of causal inferences. Considerable heterogeneity in app design, implementation strategies, and outcome assessment further complicates direct comparisons across studies. Key outcomes—such as cost-effectiveness, impact on clinician workflow, and long-term recovery trajectories—were inconsistently reported or altogether absent. Notably, digital literacy, a well-recognized determinant of user engagement and intervention effectiveness, was rarely assessed or stratified. Furthermore, due to the small number of included studies, we did not perform a formal evaluation of publication bias (e.g., funnel plots or Egger’s test), as these methods are unreliable with fewer than 10 studies. Nonetheless, this omission constitutes a limitation, and the possibility of unpublished negative findings cannot be ruled out. Finally, the limited sample size across studies constrains the generalizability of our conclusions, and few investigations conducted subgroup analyses by surgical risk, age, or baseline technological familiarity.

Despite these limitations, this review highlights a growing body of evidence suggesting that mobile applications can enhance ERAS protocol delivery without increasing risk. Their integration into perioperative care appears particularly promising for improving patient adherence and experience. Given emerging data suggesting potential cost savings—including reduced hospital LOS, fewer complications, and lower indirect patient expenses—future studies should incorporate structured cost-effectiveness analyses to better inform scalability and health system decision-making. Future research should also prioritize large-scale RCTs with standardized outcome definitions, economic evaluations, and implementation science frameworks. Moreover, digital equity and accessibility must be considered to ensure that technological advances translate into real-world benefits across diverse patient populations.

Conclusions

This systematic review indicates that mobile applications, when incorporated into ERAS protocols, have the potential to improve patient adherence, support perioperative recovery, and enhance patient satisfaction without evidence of increased complications or readmission rates. While specific studies suggest additional benefits such as reduced pain and infection rates, these findings remain context-specific. They should be interpreted cautiously due to methodological heterogeneity and the predominance of observational data. Further research through well-designed, multicenter RCTs is warranted to determine mHealth interventions’ effectiveness, cost-efficiency, and scalability across diverse surgical populations and healthcare settings.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-25-37/rc

Peer Review File: Available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-25-37/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-25-37/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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