Abstract
Objectives
Inflammatory bowel disease (IBD) is a chronic condition causing gastrointestinal inflammation. Digital health tools like the Tami app support symptom tracking, medication adherence, and personalized care. This study examines demographics, clinical characteristics, medication use, and symptom and patient-reported outcome (PRO) tracking behaviors among Tami app users in Germany.
Methods
This retrospective analysis included data from 2059 users aged ≥18 who registered between June 2023 and December 2024. Demographics, clinical characteristics, medication usage, and symptom/PRO tracking behavior were assessed. Group differences were analyzed using chi-square tests. Medications were categorized as conventional (aminosalicylates, azathioprine, methotrexate, corticosteroids, calcineurin inhibitors), advanced (biologics, small molecules), or other (painkillers, antidiarrheals, and vitamins/supplements).
Results
Of the 2059 users (mean age: 34.5 years; 73.8% female), 49.4% had ulcerative colitis (UC) and 49.2% had Crohn's disease (CD). Conventional therapies were used by 60.0% and advanced therapies by 57.1%. CD patients were more likely to use advanced therapies (70.0%) than conventional treatments (43.5%) (χ2 = 143.5, p < .0001). Users diagnosed 3–5 years earlier had higher advanced therapy use (χ2 = 90.1, p < .0001) and lower conventional therapy use (χ2 = 44.1, p < .0001) than those diagnosed within 2 years. Younger users (18–25 years) and those recently diagnosed (0–2 years) were more likely to track symptoms. The most frequently tracked PRO was the Treatment Satisfaction Questionnaire for Medication 9.
Conclusion
The Tami app is primarily used by younger, female IBD patients. Symptom tracking is highest among younger and recently diagnosed users. These findings underscore the app's potential as a digital tool to support IBD management.
Keywords
Background
Inflammatory bowel disease (IBD) is characterized by persistent inflammation in the gastrointestinal tract. IBD is accompanied by symptoms like abdominal pain, diarrhea, and rectal bleeding, as well as complications including perforation, fistula, and abscess formation. Patients’ quality of life is severely impacted by both diseases.1–3
The global prevalence of IBD has been steadily increasing, highlighting the growing need for effective management tools. 4 In this context, digital companion apps present a promising solution, offering personalized support for patients dealing with IBD. 5 Due to the heterogeneous nature of IBD, real-time data collection over extended periods, paired with diverse digital biomarkers, is becoming essential for advancing our understanding of its pathophysiology and progression. 5 Moreover, such apps can be particularly helpful for IBD patients, as their integration into daily routines offers a convenient and noninvasive method of disease management for individuals living with chronic conditions like IBD. 6
The current study focuses on characterizing the users of Tami, a digital companion app developed specifically for individuals with IBD in Germany and intended to support IBD patients in their day-to-day lives. Users can monitor health-related characteristics over time by regularly answering questions regarding the severity of symptoms and patient-reported outcomes (PROs) concerning health-related quality of life, treatment satisfaction and depressive symptoms, as well as track their medication use. Additionally, the app offers general guidance and advice for an overall healthier lifestyle, and a personalized patient engagement journey. Users get tailored in-app and push notifications for various engagement features. Through Tami, users can gain direct access to relevant information about their individual disease course, possible influencing factors, and therapy-supporting measures.
The aim of the study was to assess demographic and clinical characteristics, medication use patterns, and symptom/PRO tracking in Tami users from the launch of the app in June 2023 to December 2024. The presented baseline assessment will allow for future analysis, for example on linking patient-reported symptoms with disease activity, treatment responses, and quality of life, thereby supporting personalized treatment strategies and timely interventions.
Methods
Study design and data collection
This is a retrospective analysis of patient-reported data from Tami, a patient companion smartphone application developed and operated by Temedica GmbH (Munich, Germany). Tami is a disease-specific tool designed to support individuals with IBD in managing their condition. The application allows users to track the severity of their symptoms and PROs, monitor medication use, and document other relevant health factors over time. The manuscript was prepared in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for observational studies. 7
Study participants and informed consent
This study included registered Tami users who provided consent for the use of their demographic and health-related data for scientific purposes between 30 June 2023, and 31 December 2024. The inclusion criteria for study participants were as follows:
Provision of valid informed consent for the use of health data for scientific purposes (most recent consent, if updated); Age ≥18 years as of the data cut-off date, 31 December 2024. Users were required to have a valid year of birth to meet this criterion.
Data collection and management
Demographic and health-related information were continuously entered by users starting from their registration, with the option to update their data at any time. In cases of updates, the data status as of the cut-off date, 31 December 2024, was used for analysis.
All data were stored and processed in compliance with the General Data Protection Regulation (GDPR). Users were assigned unique identifiers to ensure privacy. Only these identifiers, not any direct personal information, were transferred to Temedica, a tech-, AI-, and data-enabled solution and service provider for the pharmaceutical industry, based in Munich, Germany. To protect the identity of participants, appropriate safeguards, such as encryption and anonymization of certain identifiers, were applied in accordance with local, regional, and national regulations.
Data were anonymized through a custom ingestion API and securely transferred into a Data Lake infrastructure. Subsequently, the data were structured and stored in pre-designed tables within a PostgreSQL database.
Variables
Demographics
To complete their app profile, Tami users were asked to provide the following information:
Age: Users selected their year of birth, with the app restricting entries before 1924. Age was calculated based on the analysis year (2024) and classified into five groups: 18–25, 26–35, 36–45, 46–55, and >55 years. Gender: Users could choose from female, male, or diverse. Diagnosis: Users selected their IBD diagnosis from the following options, based on the ICD-10 classification: Crohn's disease (CD), ulcerative colitis (UC), indeterminate colitis, or no diagnosis. Time Since Diagnosis: Users selected the year of their diagnosis, with the app restricting entries prior to their year of birth. Time since diagnosis was calculated based on the analysis year (2024) and grouped into: 0–2 years, 3–5 years, 6–10 years, 11–20 years, and >20 years. Medication Use: Users could select one or more medications they were using for their IBD treatment, either by brand name or active ingredient. Only medications approved for the selected diagnosis were available in the dropdown menu, preventing the selection of off-label treatments. Medications were categorized into three groups: conventional (aminosalicylates, azathioprine, methotrexate, corticosteroids, and calcineurin inhibitors), advanced (biologics and small molecules), and other (painkillers, antidiarrheals, vitamins/dietary supplements, and other medications). A detailed list of medications and their corresponding groups is provided in the supplementary materials (Table S1).
Symptom and PRO tracking
Users were able to report symptoms and PROs on a daily basis. For symptoms, patients could either enter numerical values or select a category, as specified below. For PROs, users completed standardized questionnaires (description below). For this analysis, we narrowed the scope to app user tracking behavior, with the primary aim of establishing a solid baseline characterization of the Tami cohort, rather than assessing symptoms and PRO outcomes.
Symptoms
Toilet visits: number of toilet visits;
Urgency of defecation: 0 (controlled) to 10 (uncontrolled) in 1-step increments;
Rectal bleeding: yes/no;
Diarrhea: Number of diarrhea events;
Gas and bloating: yes/no;
Sleep quality: good/medium/poor (coded by smiley face emojis);
Stress: Good/medium/poor (coded by smiley face emojis).
PROs
Beck Depressions-Inventar–Fast Screen (BDI-FS): The BDI-FS measures depressive symptoms and is a shortened version of the BDI-II consisting of 7 items, including Sadness, Pessimism, Past Failure, Loss of Pleasure, Self-Dislike, Self-Criticalness, and Suicidal Ideation. Each item can be scored on a range from 0 to 3 with higher scores indicating a more severe condition.
IBD disk: The IBD Disk is a self-administered tool for the assessment of the disability of patients with IBD in everyday life adapted from the validated “IBD Disability Index” tool. It consists of 10 items, each rated from 0 (absolutely disagree) to 10 (absolutely agree).
Short Inflammatory Bowel Disease Questionnaire (SIBDQ): The SIBDQ measures health-related quality of life and consists of 10 questions distributed across four dimensions: social, bowel, emotional, and systemic. Each question is rated on a 7-point Likert scale, ranging from 1 (a severe problem) to 7 (not a problem at all). The total SIBDQ score can range from 10 (indicating poor health-related quality of life) to 70 (indicating optimal health-related quality of life).
Treatment Satisfaction Questionnaire for Medication (TSQM)-9: The TSQM-9 assesses treatment satisfaction of IBD patients through three domains, namely effectiveness (items 1–3), convenience (items 4–6), and global satisfaction (items 7–9). Each item is rated on a Likert scale ranging from 1 (extremely dissatisfied, difficult, inconvenient, or not at all certain) to 7 (extremely satisfied, easy, convenient, or certain).
Analysis
Demographic and clinical characteristics were summarized using total counts and proportions across demographic groups (age and gender) and clinical characteristics (years since diagnosis, medication group use).
For medication use, the number and proportion of users who used at least one medication within each group (conventional, advanced, and other) were calculated. Additionally, the proportion of patients using advanced versus conventional medications was assessed overall and stratified by diagnosis, age, and time since diagnosis.
For symptom and PRO data, the number and proportions of users who completed at least one symptom/PRO entry were reported. The mean patient-level tracking frequency was calculated for those who logged at least one entry, with subgroup analyses conducted by diagnosis, age, and time since diagnosis.
Data processing and statistical analyses were conducted using Python (version 3.10). Group differences were evaluated using independent χ2 tests where applicable, with statistical significance set at p < .05. Graphs were generated using GraphPad Prism 10.
Results
Demographic and clinical characteristics
Since the launch of Tami, 2092 users have registered and provided consent for their data to be used for scientific purposes. Of these, 2059 users (98.4%) were ≥18 years old and formed the basis for subsequent analyses. The ages of users ranged from 18 to 91 years, with a mean age of 34.5 years (SD: 11.8). The largest age group was 26–35 years, comprising 31.6% of users (Table 1).
Demographic and clinical characteristics of Tami users.
Regarding gender distribution, 1519 users (73.8%) identified as female, 528 (25.6%) as male, and 12 (0.6%) either identified as diverse or did not disclose their gender.
In terms of medical diagnoses, 49.4% of users reported a diagnosis of UC, and 49.2% reported a diagnosis of CD. The remaining 1.4% of users either reported indeterminate colitis or no diagnosis. A total of 2045 users (99.3%) provided information about the year of their diagnosis, which was used to calculate the time since diagnosis. The time since diagnosis ranged from 0 to 49 years, with a mean of 7.6 years (SD: 8.6). The most common group was those with 0–2 years since diagnosis, which accounted for 37.3% of users (including those with missing data).
A more detailed breakdown of cohort characteristics by diagnosis is available in the supplementary materials (Table S2).
Medication use
All 2059 users (100%) provided information on their medication use. Users were allowed to list multiple medications, with the average number of medications documented being 1.7 (SD: 1.1) per user. The maximum number of different medications reported by a single user was 10.
Conventional therapies were the most commonly used medication group, with 1236 users (60.0%) reporting their use (Figure 1A). This was followed by advanced therapies, used by 1176 users (57.1%). Additionally, 247 users (13.3%) reported using other medications. When stratified by diagnosis, users with CD reported a significantly higher use of advanced therapies (70.0%) compared to conventional therapies (43.5%) (χ2 = 143.5, p < .0001). In contrast, users with UC reported a significantly higher use of conventional therapies (76.2%) compared to advanced therapies (44.3%) (χ2 = 215.3, p < .0001). There were no significant differences in the use of advanced or conventional medication between age groups, nor between age groups within UC and CD subgroups.

Medication use. Proportion of all Tami users reporting use of medication group: (a) by diagnosis, (b) by years since diagnosis. χ2 test: ns = not significant, *p < .05, ****p < .0001.
However, medication use was influenced by the time since diagnosis (Figure 1B). Users diagnosed 3–5 years ago reported a significantly higher use of advanced therapies (χ2 = 90.1, p < .0001) and a lower use of conventional therapies (χ2 = 44.1, p < .0001) compared to users diagnosed 0–2 years ago. This pattern was consistent across both UC and CD users.
Symptom and PRO tracking
Toilet visits and diarrhea were the most tracked symptoms, with 65.7% of users tracking these symptoms at least once (Figure 2A). Among users who tracked each symptom, average symptom tracking frequency was as follows: blood in stool (26.2 times, SD = 104.1), diarrhea (28.1 times, SD = 104.8), gas and bloating (25.8 times, SD = 98.4), sleep quality (27.1 times, SD = 106.8), stress (26.4 times, SD = 100.3), toilet visits (28.1 times, SD = 104.8), and urgency of defecation (26.3 times, SD = 102.3). Regarding PROs, the Treatment Satisfaction Questionnaire for Medication (TSQM-9) was the most frequently completed, with 42.9% of users filling it out at least once. On average, users who tracked each PRO did so as follows: BDI-FS (1.5 times, SD 1.8), IBD disk (2.1 times, SD 4.5), SIBDQ (1.4 times, SD 2.6), and TSQM-9 (1.3 times, SD 1.3).

Reporting rates of symptoms and PROs. Proportion of all Tami users reporting each symptom/PRO at least once: (a) overall, (b) by age group, (c) by years since diagnosis. BDI-FS: Beck Depressions-Inventory–Fast Screen; IBD: inflammatory bowel disease; PRO: patient reported outcome; SIBDQ: Short Inflammatory Bowel Disease Questionnaire; TSQM-9: Treatment Satisfaction Questionnaire for Medication 9. χ2 test: *p < .05, **p < .01.
Tracking behavior for both symptoms and PROs did not differ significantly by diagnosis.
Certain symptoms were reported more frequently by younger users (18–25 years) compared to older age groups (26–35 years) (Figure 2B). Specifically, blood in stool (χ2 = 4.5, p < .05), gas and bloating (χ2 = 4.1, p < .05), sleep quality (χ2 = 4.9, p < .05), stress (χ2 = 5.4, p < .05), and urgency of defecation (χ2 = 7.0, p < .01) were more commonly reported by the youngest age group. The only PRO differing by age was the SIBDQ, which was reported more frequently by 18–25-year-olds than by 26–35-year-olds (χ2 = 5.0, p < .05).
Recently diagnosed users (0–2 years since diagnosis) reported symptoms more frequently than users diagnosed 3–5 years ago (Figure 2C). Symptoms such as blood in stool (χ2 = 4.36, p < .05), diarrhea (χ2 = 4.3, p < .05), gas and bloating (χ2 = 7.0, p < .01), toilet visits (χ2 = 4.3, p < .05), and urgency of defecation (χ2 = 6.5, p < .01) were reported more often by those with a shorter duration since diagnosis. However, reporting of PROs did not vary based on time since diagnosis.
In summary, toilet visits and diarrhea were the most frequently tracked symptoms, with younger and newly diagnosed users showing higher engagement in symptom reporting, while PRO reporting remained low overall and did not vary significantly by diagnosis or time since diagnosis. We found an overall association between age, time since diagnosis, and symptom tracking based on chi-square independence analysis (all symptoms, p < .0001).
Discussion
In this observational study, we aimed to describe the demographic and clinical characteristics, medication use patterns, and symptom and PRO tracking among Tami users from June 2023 to December 2024.
Demographic and clinical characteristics
Our study found that Tami is predominantly used by females aged 18–45, which contrasts with the more balanced gender distribution typically seen in IBD populations, where males and females are generally represented equally.8,9 This gender imbalance may reflect a bias in the adoption of digital health technologies, where females are more likely to engage with health-related tools for disease management and self-care. 10 The overrepresentation of women and younger individuals in our study is consistent with other health-app related research and may reflect a structural pattern of health app users. Additionally, younger individuals, particularly those aged 18–29, are more inclined to use mobile health applications compared to older demographics. 11 The combination of gender bias and age-related preferences for digital tools likely contributed to the observed predominance of female and younger users within the Tami app.
The distribution of UC and CD subtypes in Tami users was relatively balanced which aligns with previous studies that have reported a similar distribution of UC and CD in the German population. 12 The average time since diagnosis was 7.6 years, with over one-third diagnosed within the past two years, indicating that the app serves patients across a wide range of disease stages, from newly diagnosed individuals to those with long-standing disease. These findings suggest that the Tami app is a versatile tool, providing support for individuals at various stages of their IBD journey.
Medication use
Our findings indicate notable differences in medication use patterns compared to a recent German claims data analysis from 2017 to 2022. 13 In that study, 66.6% of UC patients used conventional therapies and 11.2% used advanced therapies, while 57.5% of CD patients used conventional and 20.4% advanced therapies. In contrast, in our cohort, a higher proportion of UC patients used both conventional (76.2%) and advanced therapies (44.3%). Among CD patients, we observed a lower use of conventional therapies (43.5%) and a substantially higher use of advanced therapies (70.0%). Both datasets show that advanced therapy use is more common in CD than UC patients, which is consistent with established treatment paradigms for IBD, where CD is more often managed with biologics and small molecules, 14 while UC is typically treated with conventional therapies such as aminosalicylates and corticosteroids, particularly in the early stages or during remission periods. 15 Overall, however, our data suggest a markedly greater reliance on advanced therapies, which may reflect a user base that is more severely affected by IBD and therefore more likely to seek out digital health tools for disease management. As age-related differences in the administration of advanced therapies among IBD patients have been reported,16,17 it is noteworthy that our app user cohort is characterized by younger and predominantly female users (74%), who may therefore be more eligible for such treatments. These demographic distinctions compared to claims data likely contribute to the stronger affinity for digital health solutions observed in this population.
Our data also showed differences in medication use when comparing patient groups based on time since registration. Users diagnosed for more than two years reported a decrease in the use of conventional medications and an increase in the use of advanced therapies, which aligns with the natural history of IBD: Over time, conventional therapies may become less effective, prompting a transition to advanced therapies to achieve disease control.14,15 This highlights the importance of personalized treatment regimens that adapt as the disease progresses and treatment responses evolve.
Symptom and PRO tracking
Symptom tracking was more common among younger users (18–25 years) and those diagnosed within the past two years. As age and time since diagnosis are correlated, it is most likely that both contribute to the observed effects. This may be due to increased disease awareness and a desire to manage disease activity actively, especially during the early stages of IBD. Younger patients are also more familiar with digital tools, which could contribute to their higher engagement in symptom monitoring. 11 In contrast, PRO tracking showed consistent engagement across all age groups and disease durations. While symptom tracking was more influenced by age and time since diagnosis, PRO tracking remained relatively stable across IBD patients at different disease stages, reflecting its importance in assessing treatment effectiveness and quality of life. Understanding which patient groups engage most actively with digital health tools (e.g., younger women, or patients on advanced treatments) is crucial for tailoring interventions. Digital monitoring, for example, could enable earlier detection of flares, supporting timely adjustments in medication strategies, as demonstrated in studies where app-based monitoring or telemedicine led to improved disease control and reduced hospitalizations.18,19
Limitations
In this study, several limitations should be considered. Firstly, the research was conducted on a novel application launched in June 2023, resulting in a limited cohort and a short observation period. This includes the short observation period for users who turned 18 in the year before the end of the observation period as only the year of birth is reported and the exact date when they turn 18 is unknown. Another limitation pertains to the reliance on user-reported data, which may be influenced by false data inputs or delays in profile updates (e.g., current medication usage). Entry of off-label medication use was restricted. This may have led to an incomplete understanding of the medication landscape within the study cohort. Lastly, the popularity of app usage varies among patient populations, and the underlying reasons and patient's motivation are unknown, which may result in a sample cohort that does not accurately represent the broader IBD patient population in Germany.
Conclusion
In this study, we characterized the demographic and clinical profiles of IBD patients using Tami, an indication-specific app for German-speaking IBD patients. Our results show that Tami is primarily used by younger women with IBD, who demonstrate higher engagement with digital tracking and a greater reliance on advanced therapies compared to claims data. These findings underscore the considerable heterogeneity within the IBD patient population and emphasize the importance of understanding their demographic and clinical characteristics in real-world settings. A deeper insight into patient characteristics and perspectives can inform and enhance current treatment strategies, ultimately improving the quality of life for individuals with IBD. Building on these findings, future research will focus on better understanding patients reasoning for using the app, exploring PROs and disease severity through standardized questionnaires, symptom tracking within the app, and longitudinal analysis of patient behavior and symptom patterns. These studies will help estimate the potential of integrating patient-generated data from digital health solutions like Tami with clinical care, to optimize therapy, reduce complications, and enhance quality of life for individuals with IBD.
Supplemental Material
sj-docx-1-dhj-10.1177_20552076261418855 - Supplemental material for Retrospective analysis of characteristics of Tami users, a digital patient companion for inflammatory bowel disease
Supplemental material, sj-docx-1-dhj-10.1177_20552076261418855 for Retrospective analysis of characteristics of Tami users, a digital patient companion for inflammatory bowel disease by Ann-Sophie Stratil, Benjamin Friedrich, Tim Hahn, Andreas Lügering and Steffeni Papukchieva in DIGITAL HEALTH
Supplemental Material
sj-pdf-2-dhj-10.1177_20552076261418855 - Supplemental material for Retrospective analysis of characteristics of Tami users, a digital patient companion for inflammatory bowel disease
Supplemental material, sj-pdf-2-dhj-10.1177_20552076261418855 for Retrospective analysis of characteristics of Tami users, a digital patient companion for inflammatory bowel disease by Ann-Sophie Stratil, Benjamin Friedrich, Tim Hahn, Andreas Lügering and Steffeni Papukchieva in DIGITAL HEALTH
Footnotes
Acknowledgements
We would like to thank all Tami users who provided consent for the analysis of their data. Their contributions are essential for generating valuable insights and advancing patient care. We also acknowledge AbbVie for funding the development of the app used for data analysis, which played a crucial role in enabling these findings, and would like thank Stefan Rath and Selina Dindorf from AbbVie for their dedicated support and collaboration throughout this project.
Ethical considerations
This retrospective study used anonymized, aggregated patient-reported data from consenting adult users of the Tami companion app and was therefore exempt from formal ethics committee approval. All participants provided valid informed consent for the use of their health and demographic data and could withdraw consent at any time; users who withdrew prior to the data cut-off were excluded. Data were anonymized via a secure ingestion pipeline, and processed in full compliance with GDPR and the Tami platform's terms of use. No identifiable personal information or nonconsented content was assessed.
Consent to participate
Informed consent for health data usage was obtained from all subjects involved in the study. Users could withdraw their informed consent at all times. If user withdrew the previously given informed consent prior to data cut off on 31 December 2024, the user's data was not part of the analysis.
Author contributions
AS conducted data analysis, literature research, and manuscript preparation. BF, SP, TH, and AL contributed to the interpretation of findings and provided critical revisions to the manuscript. All authors reviewed and edited the manuscript and approved the final version of the manuscript.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of conflicting interests
The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: A-SS, SP, and BF are employees of Temedica GmbH. AL has served on scientific advisory boards, and/or served as speaker or moderator for AbbVie, Biogen, BMS, Falk Foundation, Ferring, Hexal, Janssen, MSD, Nutrimmun, Pfizer, Takeda, and Tillotts Pharma. None resulted in potential conflicts of interest. TH reports no commercial or financial relationships that could be construed as a potential conflict of interest.
Data availability
The data presented in this study are available on reasonable request from the corresponding author. The data are not publicly available due to the private nature of the data.
Guarantor
BF
Statement on use of AI tools
The authors declare that they used ChatGPT (OpenAI, San Francisco, CA, USA) to assist in language editing and text refinement during manuscript preparation. The authors reviewed and approved all content.
Supplemental material
Supplemental material for this article is available online.
References
Supplementary Material
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