At the tipping point, but yet not routine: Diffusion dynamics of inpatient palliative care

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Kamp, Martina Kern, Nazife Dinc, Birgitt van Oorschot, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8610908/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Early integration of specialised palliative care improves quality of life and outcomes in advanced cancer, yet its implementation in inpatient oncology remains inconsistent. This study evaluates the utilisation of specialised inpatient palliative care in German hospitals and interprets adoption patterns using Diffusion of Innovations theory. Methods We conducted a retrospective nationwide analysis of hospital cases reimbursed under the German diagnosis-related groups (DRG) system. The analysis included the most common oncological diseases and assessed utilisation of specialised inpatient palliative care overall and stratified by metastatic status, tumour entity, comorbidities, and treating medical specialties. Results Specialised inpatient palliative care was provided in 5.4% of hospital cases involving the most common malignant tumours. Among patients with organ metastases, utilisation increased to a median rate of 15.0% of hospital cases, with the highest rates observed in cases with brain (17.8%), bone (17.0%), and pleural metastases (16.1%). Palliative care involvement correlated positively with hospital mortality. Interpreted through diffusion of innovations theory, utilisation among patients with metastatic disease appears to have reached the tipping point associated with early adopters, while uptake among the early majority remains limited. Conclusion Despite longstanding guideline recommendations, specialised inpatient palliative care remains underutilised in German oncology care. From the perspective of diffusion of innovations theory, failure to move adoption beyond early adopters risks stagnation and prevents palliative care from becoming a routine component of inpatient oncology. To overcome this barrier, clinicians and policymakers should establish systematic referral pathways, implement interdisciplinary referral triggers, actively disseminate evidence on clinical effectiveness, increase awareness, strengthen palliative care training for healthcare professionals, and align reimbursement structures to support earlier and consistent palliative care integration. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Palliative medicine aims to improve the quality of life of patients and their families. It focuses on the prevention, identification, and relief of suffering across physical, psychological, social, and spiritual domains [ 1 ]. During its early years, palliative care focused on end-of-life support [ 2 ]. Over time, the concept of improving quality of life and alleviating suffering expanded beyond care limited to the terminal phase after cessation of life-prolonging treatment. Under the concept of early integration, palliative care now accompanies patients at earlier stages of disease in parallel with tumour-directed therapies. Studies by Jennifer Temel and colleagues demonstrated that early palliative care not only improves quality of life but may also positively influence survival [ 3 – 5 ]. Although subsequent studies did not consistently reproduce this survival benefit, the concept gained substantial momentum and became widely incorporated into clinical guidelines and recommendations [ 6 , 7 ]. The 2024 guideline update of the American Society of Clinical Oncology (ASCO) explicitly recommends early integration of palliative care into the treatment of patients with advanced cancer [ 8 ], generally defined a as initiation of palliative care within 8–12 weeks after diagnosis [ 8 – 10 ]. This raises the question of how widely the concept of early palliative care integration and palliative care integration for all patients with palliative oncological diagnoses have diffused into routine clinical practice. Everett M. Rogers’ diffusion of innovations theory explains how new ideas and technologies spread within social systems and under what conditions they are adopted or rejected [ 11 ]. The theory identifies five core attributes that shape adoption, which are relative advantage, compatibility, complexity, trialability, and observability. Rogers further distinguishes adopter groups according to their timing of adoption, namely innovators (approximately 2.5% of potential users), early adopters (approximately 13.5%), the early majority (approximately 34%), the late majority (approximately 34%), and laggards (approximately 16%) [ 11 ]. Although innovators and early adopters together constitute only about 16% of users, they play a critical role as opinion leaders by legitimising innovations within the wider system [ 11 , 12 ]. Diffusion typically accelerates once adoption extends beyond early adopters to the early majority, which generally occurs at an adoption level of approximately 15–20%. Crossing this tipping point is crucial, as innovations that fail to reach it often lose momentum and risk disappearing [ 11 , 12 ]. Against this background, the aim of the present study is to quantify the proportion of inpatient palliative care services reimbursed within the German diagnosis-related groups (DRG) system for the most common oncological diseases. We subsequently interpret these findings in light of the diffusion of innovation theory [ 12 , 13 ]. Methods Ethical Approval and Data Accessibility The institutional and local ethics committees at Friedrich Schiller University Jena (Study ID: 2025-3696-BO-D) and Brandenburg Medical School, Germany (Study ID: 190032024-ANF) approved data analysis. The reporting follows the STROBE guidelines for observational studies [ 14 ]. Study Design, Setting, and Data Sources We conducted a cross-sectional analysis using aggregated data from all hospitalisations in Germany in 2023. The dataset derived from routine administrative hospital data collected under § 21 of the German Hospital Remuneration Act and was provided by the Institute for the Remuneration System in the Hospital Sector (InEK GmbH, Siegburg, Germany). Cohort Definition, Participants, and Study Size The study aimed to analyse the frequency of palliative care involvement within the German DRG system among patients with common solid malignancies [ 15 ]. We defined common solid tumours as those accounting for more than 3% of all newly diagnosed cancer cases in Germany in 2023 [ 15 ]. These tumour entities included malignancies of the breast, prostate, pancreas, lung, colorectum, uterine corpus, cervix, stomach, ovary, kidney, bladder, oral cavity and pharynx, as well as malignant melanoma. Based on this definition, we applied the following inclusion criteria: (1) a diagnosis of one of the specified solid tumours as either a primary or secondary diagnosis, (2) hospital treatment during 2023 and (3) age 18 years or older. Owing to technical constraints of the dataset, the analysis focused on hospital cases rather than individual patients, and individual-level longitudinal data were unavailable. The study population therefore comprised all hospitalisations meeting these criteria in 2023. To calculate the number of cases for a particular diagnosis, we retrieved counts of hospital cases of each cohort (e.g. defined by the tumour type, combinations of diagnoses or the combination of tumour type and medical speciality), where the diagnosis was listed as either primary, secondary diagnoses or both as primary and secondary diagnoses. We calculated the count of hospital cases by the difference of the sum Definitions and Variables All diagnoses, in particular primary tumours and organ metastases, were identified and defined using the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, German Modification (ICD-10-GM, suppl. table 1) [ 16 ]. In the German DRG system, each case is assigned a single primary diagnosis and may have multiple secondary diagnoses. Medical procedures and treatments were identified using their corresponding procedural codes ( Operationen- und Prozedurenschlüssel, OPS ) [ 17 ]. The selection of analysed comorbidities was guided by the Charlson Comorbidity Index [ 18 ]. The individual specialist disciplines (e.g., oncology, radio-oncology, ...) were identified based on their respective codes from Annex 1 of the Federal Nursing Ordinance within the Federal Nursing Fee Ordinance of December 31, 2003. The mortality rate was defined as the proportion of fatal hospital cases relative to the total number of cases within the corresponding cohort. Fatal hospital cases are identified by querying the coded discharge reason documented according to Section 301, Paragraph 1, Sentence 1 of the German Social Code Book V (discharge reason 09: death). Addressing Bias We minimized selection bias by including all German hospital cases with the analysed tumours treated in 2023 that were billed within the DRG system, yielding a comprehensive national sample. Cases with fewer than five observations cannot be included for data protection reasons, which is unlikely to have affected the overall results. The analysis was limited to hospital cases rather than individual patients. The billing codes for specialized palliative care treatment from palliative care units that bill outside the DRG system cannot be captured. This particularly concerns the billing code for specialized palliative care treatment in a palliative care unit (8-98e) of approximately 70 palliative care units [ 19 , 20 ]. Measurement bias was reduced by identifying palliative and intensive care treatments using predefined OPS and ICD-10 codes, ensuring standardized case identification. Although some misclassification is possible, errors are expected to be minimal in billing data. Key clinical information, including treatment timing, integration of specialized inpatient palliative care, and patient-reported outcomes, was unavailable. To account for disease severity, relevant comorbidities were included, and a separate analysis of patients who died in hospital was performed. Data Management and Statistical Analysis Data were extracted from the InEK data browser and organized using Microsoft Excel for Mac (Version 16.93, Microsoft Corporation, Redmond, WA, USA). GraphPad Prism 9 for macOS (Version 9.5.1, GraphPad Software, La Jolla, CA, USA) was used for statistical analysis and visualization. Descriptive statistics were used to calculate frequencies, ratios, median values and interquartile ranges [IQR]. Odds ratios (ORs) were estimated using logistic regression models to assess associations between selected patient and treatment characteristics and binary outcomes [ 14 , 21 , 22 ]. Results are reported as ORs with 95% confidence intervals. Linear regression models were used to examine associations between selected patient and treatment characteristics and continuous outcomes. We chose a significance level α of 5% (0.05) for the present study and performed in total ten statistical evaluations (κ = 3). To adjust for multiple comparisons, Šidák's correction was applied (α adjusted = 1 – (1 – α) 1/κ ), and a significance level of < 0,017 was used [ 23 ]. Results In 2023, German hospitals recorded 15,200,893 adult patient hospitalisations. Solid malignant tumours featured in 1,637,202 (11%) of these hospitalisations. A malignant solid tumour was the primary diagnosis in 1,243,449 cases, the secondary diagnosis in 687,690, and both the primary and secondary diagnosis in 293,937 hospitalisations. The analysis focused on solid malignant tumours with an incidence of ≥ 3% in Germany, accounting for 1,292,726 hospitalisations, or 77% of all admissions involving patients with a solid malignant tumour. Females comprised 47.1% (608,178 cases) and males 52.9% (684,474 cases) of these patients (74 cases involved unknown or diverse gender). Patients aged ≥ 65 years represented 64.9% (839,533 cases), while those aged 18 to 29 years accounted for 0.31% (4,043 cases). The most common solid tumours were malignant lung tumours (254,444 hospitalisations; 19.7% of the analysed tumour cases), breast tumours (207,681 cases; 16.1%), and colorectal tumours (181,464 cases; 14%). Malignant cervical tumours generated the fewest number hospitalisations in this group (18,215 cases). Table 1 and accompanying Fig. 1 provide detailed age and gender distribution information for each tumour type. Metastases and Comorbidities The modified Charlson Comorbidity Index assessed comorbidities, which frequently co-occurred in these oncological hospital cases. Excluding the codes for the primary solid malignancies (C00–C76), the 1,292,726 hospital cases showed 1,691,508 codes for a Charlson Comorbidity Index-associated comorbidity (suppl. tabl. 2). Uncomplicated diabetes occurred in 15.4% of cases, lung disease in 11.2%, kidney disease in 10.4%, and acute myocardial infarction in 2.8%. As expected, pancreatic malignancies demonstrated high diabetes frequencies (31%), lung malignancies showed high rates of lung disease (30%), and cervical cancer higher rates of HIV infections (0.2%). Among the 1,292,726 hospitalizations examined, clinicians assigned 884,224 (877,750) ICD-10 codes for lymph node or organ metastases and 99,299 codes for organ metastases alone. The most frequent organ metastases were located in the liver and intrahepatic bile duct (11.3% of examined cases), bone or bone marrow (10.2%), lung (7.5%), peritoneum and retroperitoneum (5.2%), and cerebral metastases / leptomeningeal carcinosis (4.9%). As anticipated, different tumour entities exhibited distinct metastasis patterns. In-hospital mortality rate A total of 77,025 patients in the 1,292,726 analysed hospitalisations died during their hospital stay, yielding an overall in-hospital mortality rate of 6% (suppl. table 3). The median in-hospital mortality rate across the examined tumour entities was 4.7%. Malignant pancreatic tumours had the highest rate at 10.7%, and bladder malignancies had the lowest at 3.2%. Mortality increased significantly when clinicians diagnosed organ metastases. The median mortality rate for lung metastases was 12.5% (range: 4.1–15.5%), 18.4% for pleural metastases (range: 6.2–24.2%), 16.6% for liver metastases (range: 3.9–19.8%), and 14.3% for cerebral and/or leptomeningeal metastases (range: 10.1–20.3%). Specialized palliative care involvement Specialized palliative care was delivered in 70,382 of the 1,292,726 hospital cases analysed, corresponding to an overall rate of 5.4%. In these cases, hospitals recorded a total of 72,634 specialized palliative care procedure codes, including 22,184 codes (30.5%) for complex palliative care, 34,609 codes (47.6%) for specialized complex treatment on a palliative care unit, and 15,841 codes (21.8%) for palliative care consultation services (Table 2, Fig. 2 , suppl. Figure 1). Patients with pancreatic malignancies showed the highest utilization of specialized palliative care (10.1% of all cases), whereas patients with bladder cancer showed the lowest rate (2.2%). Across the analysed tumour entities, the median utilization rate reached 5% (interquartile range [IQR]: 4.3%–6.8%). We calculated odds ratios (OR, Fig. 3 ) for the use of specialized palliative care relative to all analysed hospital cases. Patients with pancreatic cancer (OR: 1.95; 95% CI: 1.9–2.0, Table 3), ovarian cancer (OR: 1.74; 95% CI: 1.68–1.8), and lung cancer (OR: 1.47; 95% CI: 1.44–1.49) showed the highest odds of specialized palliative care involvement. Linear regression analysis revealed a significant association between in-hospital mortality and the frequency of specialized palliative care involvement across the analysed tumour entities (y = 0.86x + 0.84; R² = 0.72; F = 28.5; p = 0.0002, Fig. 4 ). Of the total 77025 hospital cases in which patients died in hospital, 24566 hospital cases (31.9%) involved patients receiving specialized palliative care (table c). Among comorbidities captured by the Charlson Comorbidity Index, severe liver disease showed the strongest association with specialized palliative care involvement (OR: 5.35; 95% CI: 4.94–5.79), followed by paraplegia (OR: 3.00; 95% CI: 2.89–3.11), heart failure (OR: 1.56; 95% CI: 1.52–1.59), and dementia (OR: 1.45; 95% CI: 1.38–1.52, suppl. Figure 2). Next, we analysed the frequency of specialised palliative care involvement across medical specialties that commonly serve as the primary treating disciplines in oncological centres (Fig. 5 ). Haematology/oncology demonstrated the highest rate of specialised palliative care involvement (10.4%), followed by gastroenterology (6.8%) and radiation oncology (6.7%). In contrast, gynaecology (0.7%) and urology (1.0%) showed the lowest rates. Accordingly, the odds ratios ranged from 2.02 (95% CI: 1.98–2.05) for haematology/oncology to 0.12 (95% CI: 0.11–0.12) for gynaecology and 0.17 (95% CI: 0.16–0.18) for urology. Linear regression analysis again revealed a significant association between in-hospital mortality and the frequency of specialised palliative care involvement across medical specialties (y = 0.70x + 0.96; R² = 0.64; F = 15.7; p = 0.003). As the analysed tumour cases also included patients treated with curative intent, most tumour diseases with organ metastases no longer allow curative treatment and therefore require palliative care. To estimate the proportion of specialised palliative care among palliative tumour patients, we analysed hospital cases involving patients with organ metastases (Fig. 5 , Table 4). Across all analysed primary tumours and metastatic sites, the median rate of specialised palliative care involvement reached 15.0% (interquartile range [IQR]: 8.3%–19.4%). Among hospitalised cases involving one of the analysed tumours with additional cerebral metastases, specialised palliative care involvement reached 17.8%. Corresponding rates amounted to 17.0% for bone metastases, 16.1% for pleural metastases, and 14.3% for lung metastases. Compared with all analysed hospital cases, the presence of cerebral metastases markedly increased the likelihood of specialised palliative care involvement (OR: 3.8; 95% CI: 3.7–3.8). Bone metastases (OR: 3.6; 95% CI: 3.5–3.6), pleural metastases (OR: 3.3; 95% CI: 3.2–3.4), (retro)peritoneal metastases (OR: 3.4; 95% CI: 3.4–3.5), and lung metastases (OR: 2.9; 95% CI: 2.8–3.0) showed similarly elevated odds. Linear regression analysis again demonstrated a significant association between in-hospital mortality and the frequency of specialised palliative care involvement across metastatic tumour entities (y = 0.78x − 1.1; R² = 0.65; F = 41.4; p < 0.0001). Discussion Our analysis quantified the proportion of inpatient palliative care services reimbursed under the German diagnosis-related groups (DRG) system for the most common oncological diseases and yielded the following key findings. Specialised palliative care was provided in 5.4% of hospital cases involving the most common malignant tumours in Germany. The rate of inpatient palliative care treatment correlated with the hospital mortality. Among hospital cases with one of the analysed tumours and organ metastases, the median rate of specialised palliative care involvement reached 15.0%. Therefore, quality-of-life-centred early palliative care integration for patients with metastases appears to have reached the tipping point at which early adopters have accepted the concept, while adoption by the early majority has not yet occurred. In Germany, the rate of specialised inpatient care for the malignancies examined with an incidence ≥ 3% is 5.4%. This level remains well below the 15–20% tipping point described in the diffusion of innovations theory. These tumour cases include patients receiving curative treatment. Patients with organ metastases are highly likely to require palliative care, and clinical guidelines and recommendations explicitly advocate early palliative care integration and co-treatment for these groups [ 6 – 9 ]. The Lancet Oncology Commission (2025) identifies a profound "human crisis" in global cancer care, noting that current systems frequently neglect the emotional, relational, and existential dimensions of the patient experience despite significant biomedical progress [ 24 ]. This crisis stems from structural failures, including an over-reliance on technology, fragmented delivery models, and economic incentives that prioritise clinical throughput over compassionate, person-centred communication. To resolve this dehumanisation, the Commission advocates for the immediate, universal integration of palliative and psychosocial care, positioning empathetic engagement not as an elective supplement but as a fundamental requirement of oncological practice [ 24 ]. Across all analysed primary tumour entities and metastatic sites in the present study, the median utilisation of specialised palliative care reached 15.0%. The highest rates of inpatient specialised palliative treatment occurred in hospital cases with brain metastases (17.8%), bone metastases (17.0%), and pleural metastases (16.1%). Our findings align closely with our previous work on glioblastomas and cerebral metastases [ 19 , 20 ]. A German study based on statutory health insurance data from the state of Baden-Württemberg identified 3,535 patients with advanced cancer who required palliative care in 2015. Of these patients, 669 (18.9%) were referred to specialised outpatient palliative care teams, and 45.1% of those referrals involved early integration of palliative care [ 25 ]. Earlier published data highlighted the gap between patient needs and actual service delivery. The analysis of health insurance records for 80,768 individuals revealed that only 7.8% of cancer patients accessed specialised outpatient palliative care in their final year, while the system provided just 8.4 complex palliative treatments per 10,000 inhabitants [ 26 ]. Another study analysing health insurance data on specialised palliative care indicate that approximately one third of all patients receive specialised palliative care during the last year of life [ 27 , 28 ]. However, comparative European analyses classify Germany, the Netherlands, the United Kingdom, and Switzerland as countries with a relatively high level of palliative care integration [ 29 ]. International data nevertheless reveal substantial variation in the timing of palliative care delivery. In Victoria, Australia, 66% of patients who died from cancer in 2018 received palliative care, 18% accessed palliative care at least three months before death [ 30 ]. The median interval between first palliative care contact and death was 22 days [ 31 ]. In Canada, 12.6% of inpatients received some form of palliative care during the year preceding death [ 32 ]. In the United States, 8.0% of patients with newly diagnosed metastatic cancer received early specialised palliative care within eight weeks of diagnosis in 2018 and 2019 [ 33 ]. Palliative care involvement varied by tumour type, with higher rates in lung cancer (12.0%) and lower rates in breast cancer (4.3%) [ 33 ]. An analysis of Medicare-insured individuals with advanced cancer further demonstrated an early palliative care integration of 10.4% in 2019 [ 34 ]. Across the entire analysed cohort, among hospital cases involving patients with metastatic malignancies, and within individual medical specialties, we observed a significant positive association between inpatient mortality and the rate of specialised palliative care involvement. Evidence on the relationship between inpatient palliative care utilisation and hospital mortality remains inconsistent. On the one hand, studies have shown that patients with a high predicted risk of short-term mortality are more likely to receive palliative care consultation during hospitalisation [ 35 ]. Several other studies have identified palliative care involvement as being associated with higher in-hospital mortality and a lower likelihood of intensive care unit admission [ 32 , 36 , 37 ]. On the other hand, other studies have reported a reduction in hospital mortality associated with palliative care involvement, including a systematic review demonstrating a 34% reduction in in-hospital mortality [ 38 , 39 ]. A retrospective Canadian study similarly reported higher overall hospital mortality among patients receiving palliative care; however, within the subgroup of terminally ill patients receiving palliative care, the probability of dying in hospital or being admitted to an intensive care unit was lower [ 32 ]. Everett M. Rogers’ diffusion of innovations theory explains how new ideas and technologies spread within social systems and under what conditions they are adopted or rejected [ 11 ]. Rogers distinguishes adopter groups according to their timing of adoption, namely innovators, early, the early majority, the late majority, and laggards [ 11 ]. Although innovators and early adopters together constitute only about 16% of users, they play a critical role as opinion leaders by legitimising innovations within the wider system [ 11 , 12 ]. Diffusion typically accelerates once adoption extends beyond early adopters to the early majority, which generally occurs at an adoption level of approximately 15–20%. Crossing this tipping point is crucial, as innovations that fail to reach it often lose momentum and risk disappearing [ 11 , 12 ]. Although Rogers did not originally develop diffusion of innovations theory for the healthcare sector, researchers increasingly apply it to explain the spread of healthcare innovations. In healthcare, the five innovation factors, relative advantage, compatibility, complexity, trialability, and observability, remain central but require contextual reinterpretation [ 12 , 13 , 40 , 41 ]. Stakeholders typically assess relative advantage in terms of clinical effectiveness, patient safety, and evidence-based outcomes. For early integration, evidence gained from randomised clinical trials in early integration [ 3 , 42 – 44 ]. Compatibility reflects alignment with professional norms, ethical standards, clinical workflows, and regulatory requirements, while complexity often relates to training demands, workflow disruption, and system interoperability [ 12 ]. For palliative care, must proactively cultivate awareness must proactively be cultivated regarding the necessity of early palliative care access to mitigate the systemic neglect of patient suffering. Oncology training programmes must mandate core competencies in palliative care for all healthcare professionals to ensure they possess the necessary skills to address the profound human suffering inherent in the cancer experience [ 24 ]. In spite of emerging standards and recommendations palliative care appears to be more firmly established and widely accepted primarily as end-of-life care in everyday clinical settings. Interpreting our present data through the lens of diffusion of innovations theory, quality-of-life-centred palliative care for patients with metastatic cancer in Germany remains largely confined to innovators and early adopters, while the early majority has not yet embraced the concept. Utilisation rates around 15% therefore mark a fragile threshold rather than a successful transition to self-sustaining diffusion. This finding is particularly noteworthy given that early palliative care integration has been discussed for more than 15 years [ 3 ]. Without broader acceptance by the early majority, early palliative care risks remaining a niche practice instead of becoming a normative component of oncological care. This stagnation has important implications, as it limits population-level access to timely palliative care despite strong evidence and guideline recommendations. From a diffusion and implementation science perspective, failure to convince the early majority necessitates a shift in strategy. Innovations that stall at the early-adopter stage rarely diffuse further through social influence alone and instead require structural reinforcement through policy, organisational change, and incentive realignment [ 11 , 12 ]. For early palliative care, this implies that continued reliance on professional advocacy and guidelines is insufficient. Instead, health systems must actively lower adoption barriers by embedding early palliative care into standard care pathways, adjusting reimbursement mechanisms, disseminating information on efficacy, raising awareness and training for health care professionals. Without such measures, early palliative care is unlikely to cross into early-majority adoption and may continue to be perceived as optional rather than essential. Limitations This study has several limitations: Hospital cases do not correspond directly to individual patients, as some may be hospitalised multiple times but receive specialised inpatient palliative care only once, potentially underestimating patient-level coverage. The evaluation reported on hospital cases, not on health care professionals, and thus provided only indirect evidence on the percentages of innovators and early adopters, assuming that the percentages of patients receiving palliative care and percentages of healthcare professionals initiating such transfers to palliative care would be correlated. Secondary diagnoses (e.g., organ metastases coded as C79.x) may be recorded multiple times within a case, slightly affecting counts. Around 70 palliative care units in Germany operate as “special facilities” (Besondere Einrichtungen), managing roughly 17,500 cases [ 19 ], and these cases would not be captured in the reimbursement database. However, some units submit data to InEK for reporting but do not bill statutory health insurance, so their activity may have been captured partially. Hospital mortality was calculated per case without specifying cause but remains a relevant indicator of disease severity. Outpatient care is not included. Patient may receive specialized outpatient palliative care after discharge. These data are not available. Findings rely on accurate coding in the InEK database. Misclassification may introduce bias. Finally, the dataset lacks key information on symptom burden, psychosocial stress, and caregiver experience and quality-of-life. Conclusion Specialised inpatient palliative care for patients with metastatic cancer in Germany reaches only around 15% of hospital cases, indicating that early adopters have embraced the practice, but the early majority has not yet followed. According to Rogers’ diffusion of innovations theory, this stalled adoption risks preventing early palliative care from becoming a normative component of oncological care. Clinicians should proactively integrate palliative care into standard pathways, while health systems align incentives and expand capacity to overcome structural barriers. Without such coordinated action, timely access remains limited, and patients may not fully benefit from quality-of-life-centred care. Declarations Acknowledgements None Disclosure of Potential Conflicts of Interest All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript. Declaration of generative AI and AI-assisted technologies in the writing process AI-assisted technology was neither used for the generation, evaluation or interpretation of the data presented in the manuscript, nor for the creation of text, figures or tables. AI-based tools (chat GPT) may have been used to improve language and text readability. Human Ethics and Consent to Participate declarations: not applicable: The study complied with the ethical standards set in the 1964 Declaration of Helsinki and its subsequent revisions. Approval for the study protocol was granted by the institutional and local ethics committee at Brandenburg Medical School, Germany (Study ID: 190032024-ANF). Our manuscript exclusively utilized publicly available data, no individual patient data, thus obviating the need for individual patient consent. Funding information The study was not funded Clinical trial number not applicable References World Health Organization (WHO) (2002) WHO definition of palliative care. World Health Organization (WHO). https://www.who.int/health-topics/palliative-care . Accessed 16.09.2019 2019 Hui D, Bruera E (2020) Models of Palliative Care Delivery for Patients With Cancer. 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PLoS One 20: e0334616 doi: 10.1371/journal.pone.0334616 Greer JA, Jacobs J, Pensak N, MacDonald JJ, Fuh CX, Perez GK, Ward A, Tallen C, Muzikansky A, Traeger L, Penedo FJ, El-Jawahri A, Safren SA, Pirl WF, Temel JS (2019) Randomized Trial of a Tailored Cognitive-Behavioral Therapy Mobile Application for Anxiety in Patients with Incurable Cancer. Oncologist 24: 1111–1120 doi: 10.1634/theoncologist.2018-0536 Greer JA, Jacobs JM, Pensak N, Nisotel LE, Fishbein JN, MacDonald JJ, Ream ME, Walsh EA, Buzaglo J, Muzikansky A, Lennes IT, Safren SA, Pirl WF, Temel JS (2020) Randomized Trial of a Smartphone Mobile App to Improve Symptoms and Adherence to Oral Therapy for Cancer. J Natl Compr Canc Netw 18: 133–141 doi: 10.6004/jnccn.2019.7354 Temel JS, Jackson VA, El-Jawahri A, Rinaldi SP, Petrillo LA, Kumar P, McGrath KA, LeBlanc TW, Kamal AH, Jones CA, Rabideau DJ, Horick N, Pintro K, Gallagher Medeiros ER, Post KE, Greer JA (2024) Stepped Palliative Care for Patients With Advanced Lung Cancer: A Randomized Clinical Trial. JAMA 332: 471–481 doi: 10.1001/jama.2024.10398 Tables Tables 1 to 4 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Tab1genderage.xlsx table 1 Age and gender distribution Tabl2SPC.xlsx table 2 Rate of specialized palliative care treatment in the analysed tumours for all hospital and fatal cases Tab3OR.xlsx table 3 Odds ratios Tab4SPCmets.xlsx table 4 Rate of specialized palliative care treatment in hospital cases involving cancer patients with metastases suppltab1codedefinition.xlsx suppl. table 1 Used ICD-10-GM codes Suppl. table 1 provides an overview about ICD-10-GM codes and their definition used for our analyses. suppltab2CCI.xlsx suppl. table 2 Comorbidities according to the Charlson Comorbidity Index suppltab3mortality.xlsx suppl. table 3 In-hospital mortality in the entire cohort and in hospital cases involving patients with metastases supplfig1absolutefigures.png suppl. figure 1 Different types of specialised palliative care across different tumour types supplfig2ORCCI.png suppl. figure 2 Odds ratios for specialised palliative care utilisation for different comorbidities This figure presents odds ratios for specialised palliative care treatment according to comorbidities. Odds ratios are calculated relative to the overall frequency of specialised palliative care utilisation in the entire analysed cohort. Abbreviations: *except hemiplegia. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8610908","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":615114132,"identity":"4885772d-0c65-4f05-b854-d03ca2fbb15f","order_by":0,"name":"Marcel A. Kamp","email":"data:image/png;base64,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","orcid":"","institution":"Brandenburg Medical School Theodor Fontane","correspondingAuthor":true,"prefix":"","firstName":"Marcel","middleName":"A.","lastName":"Kamp","suffix":""},{"id":615114133,"identity":"62eb5d9f-000c-46fd-be40-5f090e470940","order_by":1,"name":"Martina Kern","email":"","orcid":"","institution":"Helios Hospital Bonn/Rhein-Sieg","correspondingAuthor":false,"prefix":"","firstName":"Martina","middleName":"","lastName":"Kern","suffix":""},{"id":615114134,"identity":"db38f0f0-12b0-49c5-a7ce-2e2d523687ca","order_by":2,"name":"Nazife Dinc","email":"","orcid":"","institution":"Friedrich Schiller University Jena","correspondingAuthor":false,"prefix":"","firstName":"Nazife","middleName":"","lastName":"Dinc","suffix":""},{"id":615114135,"identity":"55a18393-1a59-4936-ae18-4363836983b4","order_by":3,"name":"Birgitt van Oorschot","email":"","orcid":"","institution":"-","correspondingAuthor":false,"prefix":"","firstName":"Birgitt","middleName":"van","lastName":"Oorschot","suffix":""},{"id":615114136,"identity":"bc84b75c-ff87-4fec-b3be-74764441bec9","order_by":4,"name":"Lukas Radbruch","email":"","orcid":"","institution":"University Hospital Bonn","correspondingAuthor":false,"prefix":"","firstName":"Lukas","middleName":"","lastName":"Radbruch","suffix":""},{"id":615114137,"identity":"bb29c71d-6b43-4eae-99ca-0b9b87446c5c","order_by":5,"name":"Christiane Sass","email":"","orcid":"","institution":"Brandenburg Medical School Theodor Fontane","correspondingAuthor":false,"prefix":"","firstName":"Christiane","middleName":"","lastName":"Sass","suffix":""}],"badges":[],"createdAt":"2026-01-15 13:23:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8610908/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8610908/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105984277,"identity":"1c1aff53-b697-4f45-9726-8a86fc6e4a84","added_by":"auto","created_at":"2026-04-02 07:13:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":324933,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eGender distribution\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eGender distribution across the analysed tumour entities in the total study cohort (A) and among hospital cases resulting in in-hospital death (B).\u003c/p\u003e","description":"","filename":"Fig1gender.png","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/a25ac67ec83d6d7e9f8f8d66.png"},{"id":105984134,"identity":"adea0d03-b427-4b54-aa87-56defb17b442","added_by":"auto","created_at":"2026-04-02 07:13:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":309032,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eFrequency of palliative care involvement in hospital cases with oncologic patients.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePanel A shows the proportion of hospital cases that included specialized palliative care involvement care as defined by OPS codes 8-982, 8-98e, and 8-98h. Panel B depicts the proportion of hospital cases of patients with frequent organ metastases that included specialized palliative care involvement. The shaded pink area indicates the tipping-point range described by diffusion of innovations theory (approximately 15–20% adoption), beyond which acceptance extends from early adopters to the early majority and diffusion becomes self-sustaining.\u003c/p\u003e","description":"","filename":"Fig2frequency.png","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/9f6bcd56256c1befd80ff826.png"},{"id":105984201,"identity":"1244c8f5-69b0-45c0-92d8-90cb94113452","added_by":"auto","created_at":"2026-04-02 07:13:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":341805,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eOdds ratios for specialised palliative care utilisation.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis figure presents odds ratios for specialised palliative care treatment according to tumour entities (A), presence of metastases (B), and treating medical specialties (C). Odds ratios are calculated relative to the overall frequency of specialised palliative care utilisation in the entire analysed cohort (OR = 1).\u003c/p\u003e\n\u003cp\u003eAbbreviations: OR, odds ratio\u003c/p\u003e","description":"","filename":"Fig3Oddsratios.png","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/f796f3781db0750595f0d9da.png"},{"id":105984273,"identity":"31384ade-90f6-48b6-84d9-ce221aad97d3","added_by":"auto","created_at":"2026-04-02 07:13:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":409205,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eLinear regression analyses\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eLinear regression analyses for the association between in-hospital mortality and the frequency of specialised palliative care involvement for different tumour types (A.: y = 0.86x + 0.84; R² = 0.72; F = 28.5; p = 0.0002), in case presence of metastases (B: y = 0.78x − 1.1; R² = 0.65; F = 41.4; p \u0026lt; 0.0001) and across different medical specialties (C: y = 0.70x + 0.96; R² = 0.64; F = 15.7; p = 0.003).\u003c/p\u003e","description":"","filename":"Fig4linearregression.png","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/c9770e5ce74a64ecf658f140.png"},{"id":105984200,"identity":"bcf195dc-c5ad-407c-a1c8-5ad35e5d7a58","added_by":"auto","created_at":"2026-04-02 07:13:29","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1275705,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSankey diagram\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe Sankey diagram illustrates frequency of specialised palliative care in presence of metastases (A.) and across different medical specialties\u003c/p\u003e","description":"","filename":"Fig5Sankey.png","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/87a501b1b24793cc499162c9.png"},{"id":106979536,"identity":"26e8a6f9-a716-4599-8565-c374234187c7","added_by":"auto","created_at":"2026-04-15 11:28:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2439118,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/6389e38c-203e-4593-9334-71c74086dbda.pdf"},{"id":105984199,"identity":"a470ec60-51b4-45e8-948b-31e45602c0d5","added_by":"auto","created_at":"2026-04-02 07:13:28","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":145651,"visible":true,"origin":"","legend":"\u003cp\u003etable 1\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAge and gender distribution\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Tab1genderage.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/278c0372ebbba4eb8e14ec61.xlsx"},{"id":105984202,"identity":"2b04fbd9-778d-4c03-a3ff-0c39ace0e3b0","added_by":"auto","created_at":"2026-04-02 07:13:29","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":25710,"visible":true,"origin":"","legend":"\u003cp\u003etable 2\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRate of specialized palliative care treatment in the analysed tumours for all hospital and fatal cases\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Tabl2SPC.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/fb4ba3b43b71994a061c383a.xlsx"},{"id":105984140,"identity":"d209ca29-8500-48e6-a2f7-c6d23f5177d5","added_by":"auto","created_at":"2026-04-02 07:13:16","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":21691,"visible":true,"origin":"","legend":"\u003cp\u003etable 3\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOdds ratios\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Tab3OR.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/25a17fa83d55fdd164c3f5e5.xlsx"},{"id":105984143,"identity":"ebfd3078-8a13-4297-8786-43408b7c7f54","added_by":"auto","created_at":"2026-04-02 07:13:18","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":27446,"visible":true,"origin":"","legend":"\u003cp\u003etable 4\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRate of specialized palliative care treatment in hospital cases involving cancer patients with metastases\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Tab4SPCmets.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/5cb354511f7887f3a59171de.xlsx"},{"id":105984135,"identity":"a55fb396-4f42-4d8d-98e8-59fe645e77dc","added_by":"auto","created_at":"2026-04-02 07:13:13","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":25461,"visible":true,"origin":"","legend":"\u003cp\u003esuppl. table 1\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eUsed ICD-10-GM codes\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSuppl. table 1 provides an overview about ICD-10-GM codes and their definition used for our analyses.\u003c/p\u003e","description":"","filename":"suppltab1codedefinition.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/29d157c4997cb970526a20d1.xlsx"},{"id":105984276,"identity":"59fac9c1-a6fc-418e-beb5-a1d7a5d64b3b","added_by":"auto","created_at":"2026-04-02 07:13:34","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":22529,"visible":true,"origin":"","legend":"\u003cp\u003esuppl. table 2\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eComorbidities according to the Charlson Comorbidity Index\u003c/em\u003e\u003c/p\u003e","description":"","filename":"suppltab2CCI.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/91f009670760b48fda46ac49.xlsx"},{"id":105984141,"identity":"4b24ee7d-7793-41cb-8b51-d153ed77640a","added_by":"auto","created_at":"2026-04-02 07:13:17","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":17703,"visible":true,"origin":"","legend":"\u003cp\u003esuppl. table 3\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn-hospital mortality in the entire cohort and in hospital cases involving patients with metastases\u003c/em\u003e\u003c/p\u003e","description":"","filename":"suppltab3mortality.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/fe9a61ee2a8b8a2bd5d0d7bc.xlsx"},{"id":105984278,"identity":"af936150-ddcd-47fa-a49a-b78d789cf27b","added_by":"auto","created_at":"2026-04-02 07:13:35","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":237560,"visible":true,"origin":"","legend":"\u003cp\u003esuppl. figure 1\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDifferent types of specialised palliative care across different tumour types\u003c/em\u003e\u003c/p\u003e","description":"","filename":"supplfig1absolutefigures.png","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/d4963cbe4778a84d0e45d045.png"},{"id":105984275,"identity":"054691db-cc51-4d65-b57f-4d57f960c51d","added_by":"auto","created_at":"2026-04-02 07:13:34","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":438333,"visible":true,"origin":"","legend":"\u003cp\u003esuppl. figure 2\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOdds ratios for specialised palliative care utilisation for different comorbidities\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis figure presents odds ratios for specialised palliative care treatment according to comorbidities. Odds ratios are calculated relative to the overall frequency of specialised palliative care utilisation in the entire analysed cohort.\u003c/p\u003e\n\u003cp\u003eAbbreviations: *except hemiplegia.\u003c/p\u003e","description":"","filename":"supplfig2ORCCI.png","url":"https://assets-eu.researchsquare.com/files/rs-8610908/v1/ef00b4ada7bb369209529b81.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"At the tipping point, but yet not routine: Diffusion dynamics of inpatient palliative care","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePalliative medicine aims to improve the quality of life of patients and their families. It focuses on the prevention, identification, and relief of suffering across physical, psychological, social, and spiritual domains [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. During its early years, palliative care focused on end-of-life support [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Over time, the concept of improving quality of life and alleviating suffering expanded beyond care limited to the terminal phase after cessation of life-prolonging treatment. Under the concept of early integration, palliative care now accompanies patients at earlier stages of disease in parallel with tumour-directed therapies. Studies by Jennifer Temel and colleagues demonstrated that early palliative care not only improves quality of life but may also positively influence survival [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Although subsequent studies did not consistently reproduce this survival benefit, the concept gained substantial momentum and became widely incorporated into clinical guidelines and recommendations [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The 2024 guideline update of the American Society of Clinical Oncology (ASCO) explicitly recommends early integration of palliative care into the treatment of patients with advanced cancer [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], generally defined a as initiation of palliative care within 8\u0026ndash;12 weeks after diagnosis [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis raises the question of how widely the concept of early palliative care integration and palliative care integration for all patients with palliative oncological diagnoses have diffused into routine clinical practice. Everett M. Rogers\u0026rsquo; diffusion of innovations theory explains how new ideas and technologies spread within social systems and under what conditions they are adopted or rejected [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The theory identifies five core attributes that shape adoption, which are relative advantage, compatibility, complexity, trialability, and observability. Rogers further distinguishes adopter groups according to their timing of adoption, namely innovators (approximately 2.5% of potential users), early adopters (approximately 13.5%), the early majority (approximately 34%), the late majority (approximately 34%), and laggards (approximately 16%) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although innovators and early adopters together constitute only about 16% of users, they play a critical role as opinion leaders by legitimising innovations within the wider system [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Diffusion typically accelerates once adoption extends beyond early adopters to the early majority, which generally occurs at an adoption level of approximately 15\u0026ndash;20%. Crossing this tipping point is crucial, as innovations that fail to reach it often lose momentum and risk disappearing [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAgainst this background, the aim of the present study is to quantify the proportion of inpatient palliative care services reimbursed within the German diagnosis-related groups (DRG) system for the most common oncological diseases. We subsequently interpret these findings in light of the diffusion of innovation theory [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cstrong\u003eEthical Approval and Data Accessibility\u003c/strong\u003e \u003c/p\u003e\u003cp\u003e The institutional and local ethics committees at Friedrich Schiller University Jena (Study ID: 2025-3696-BO-D) and Brandenburg Medical School, Germany (Study ID: 190032024-ANF) approved data analysis. The reporting follows the STROBE guidelines for observational studies [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design, Setting, and Data Sources\u003c/h2\u003e \u003cp\u003eWe conducted a cross-sectional analysis using aggregated data from all hospitalisations in Germany in 2023. The dataset derived from routine administrative hospital data collected under \u0026sect;\u0026nbsp;21 of the German Hospital Remuneration Act and was provided by the Institute for the Remuneration System in the Hospital Sector (InEK GmbH, Siegburg, Germany).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCohort Definition, Participants, and Study Size\u003c/h3\u003e\n\u003cp\u003eThe study aimed to analyse the frequency of palliative care involvement within the German DRG system among patients with common solid malignancies [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. We defined common solid tumours as those accounting for more than 3% of all newly diagnosed cancer cases in Germany in 2023 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These tumour entities included malignancies of the breast, prostate, pancreas, lung, colorectum, uterine corpus, cervix, stomach, ovary, kidney, bladder, oral cavity and pharynx, as well as malignant melanoma. Based on this definition, we applied the following inclusion criteria: (1) a diagnosis of one of the specified solid tumours as either a primary or secondary diagnosis, (2) hospital treatment during 2023 and (3) age 18 years or older. Owing to technical constraints of the dataset, the analysis focused on hospital cases rather than individual patients, and individual-level longitudinal data were unavailable. The study population therefore comprised all hospitalisations meeting these criteria in 2023.\u003c/p\u003e \u003cp\u003eTo calculate the number of cases for a particular diagnosis, we retrieved counts of hospital cases of each cohort (e.g. defined by the tumour type, combinations of diagnoses or the combination of tumour type and medical speciality), where the diagnosis was listed as either primary, secondary diagnoses or both as primary and secondary diagnoses. We calculated the count of hospital cases by the difference of the sum\u003c/p\u003e\n\u003ch3\u003eDefinitions and Variables\u003c/h3\u003e\n\u003cp\u003eAll diagnoses, in particular primary tumours and organ metastases, were identified and defined using the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, German Modification (ICD-10-GM, suppl. table 1) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In the German DRG system, each case is assigned a single primary diagnosis and may have multiple secondary diagnoses. Medical procedures and treatments were identified using their corresponding procedural codes (\u003cem\u003eOperationen- und Prozedurenschl\u0026uuml;ssel, OPS\u003c/em\u003e) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The selection of analysed comorbidities was guided by the Charlson Comorbidity Index [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The individual specialist disciplines (e.g., oncology, radio-oncology, ...) were identified based on their respective codes from Annex 1 of the Federal Nursing Ordinance within the Federal Nursing Fee Ordinance of December 31, 2003.\u003c/p\u003e \u003cp\u003eThe mortality rate was defined as the proportion of fatal hospital cases relative to the total number of cases within the corresponding cohort. Fatal hospital cases are identified by querying the coded discharge reason documented according to Section 301, Paragraph 1, Sentence 1 of the German Social Code Book V (discharge reason 09: death).\u003c/p\u003e\n\u003ch3\u003eAddressing Bias\u003c/h3\u003e\n\u003cp\u003eWe minimized selection bias by including all German hospital cases with the analysed tumours treated in 2023 that were billed within the DRG system, yielding a comprehensive national sample. Cases with fewer than five observations cannot be included for data protection reasons, which is unlikely to have affected the overall results. The analysis was limited to hospital cases rather than individual patients. The billing codes for specialized palliative care treatment from palliative care units that bill outside the DRG system cannot be captured. This particularly concerns the billing code for specialized palliative care treatment in a palliative care unit (8-98e) of approximately 70 palliative care units [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Measurement bias was reduced by identifying palliative and intensive care treatments using predefined OPS and ICD-10 codes, ensuring standardized case identification. Although some misclassification is possible, errors are expected to be minimal in billing data. Key clinical information, including treatment timing, integration of specialized inpatient palliative care, and patient-reported outcomes, was unavailable. To account for disease severity, relevant comorbidities were included, and a separate analysis of patients who died in hospital was performed.\u003c/p\u003e\n\u003ch3\u003eData Management and Statistical Analysis\u003c/h3\u003e\n\u003cp\u003eData were extracted from the InEK data browser and organized using Microsoft Excel for Mac (Version 16.93, Microsoft Corporation, Redmond, WA, USA). GraphPad Prism 9 for macOS (Version 9.5.1, GraphPad Software, La Jolla, CA, USA) was used for statistical analysis and visualization.\u003c/p\u003e \u003cp\u003eDescriptive statistics were used to calculate frequencies, ratios, median values and interquartile ranges [IQR]. Odds ratios (ORs) were estimated using logistic regression models to assess associations between selected patient and treatment characteristics and binary outcomes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Results are reported as ORs with 95% confidence intervals. Linear regression models were used to examine associations between selected patient and treatment characteristics and continuous outcomes. We chose a significance level α of 5% (0.05) for the present study and performed in total ten statistical evaluations (κ =\u0026thinsp;3). To adjust for multiple comparisons, Šid\u0026aacute;k's correction was applied (α\u003csub\u003eadjusted\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1 \u0026ndash; (1 \u0026ndash; α)\u003csup\u003e1/κ\u003c/sup\u003e), and a significance level of \u0026lt;\u0026thinsp;0,017 was used [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn 2023, German hospitals recorded 15,200,893 adult patient hospitalisations. Solid malignant tumours featured in 1,637,202 (11%) of these hospitalisations. A malignant solid tumour was the primary diagnosis in 1,243,449 cases, the secondary diagnosis in 687,690, and both the primary and secondary diagnosis in 293,937 hospitalisations.\u003c/p\u003e \u003cp\u003eThe analysis focused on solid malignant tumours with an incidence of \u0026ge;\u0026thinsp;3% in Germany, accounting for 1,292,726 hospitalisations, or 77% of all admissions involving patients with a solid malignant tumour. Females comprised 47.1% (608,178 cases) and males 52.9% (684,474 cases) of these patients (74 cases involved unknown or diverse gender). Patients aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years represented 64.9% (839,533 cases), while those aged 18 to 29 years accounted for 0.31% (4,043 cases). The most common solid tumours were malignant lung tumours (254,444 hospitalisations; 19.7% of the analysed tumour cases), breast tumours (207,681 cases; 16.1%), and colorectal tumours (181,464 cases; 14%). Malignant cervical tumours generated the fewest number hospitalisations in this group (18,215 cases). Table\u0026nbsp;1 and accompanying Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provide detailed age and gender distribution information for each tumour type.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eMetastases and Comorbidities\u003c/h3\u003e\n\u003cp\u003eThe modified Charlson Comorbidity Index assessed comorbidities, which frequently co-occurred in these oncological hospital cases. Excluding the codes for the primary solid malignancies (C00\u0026ndash;C76), the 1,292,726 hospital cases showed 1,691,508 codes for a Charlson Comorbidity Index-associated comorbidity (suppl. tabl. 2). Uncomplicated diabetes occurred in 15.4% of cases, lung disease in 11.2%, kidney disease in 10.4%, and acute myocardial infarction in 2.8%. As expected, pancreatic malignancies demonstrated high diabetes frequencies (31%), lung malignancies showed high rates of lung disease (30%), and cervical cancer higher rates of HIV infections (0.2%).\u003c/p\u003e \u003cp\u003eAmong the 1,292,726 hospitalizations examined, clinicians assigned 884,224 (877,750) ICD-10 codes for lymph node or organ metastases and 99,299 codes for organ metastases alone. The most frequent organ metastases were located in the liver and intrahepatic bile duct (11.3% of examined cases), bone or bone marrow (10.2%), lung (7.5%), peritoneum and retroperitoneum (5.2%), and cerebral metastases / leptomeningeal carcinosis (4.9%). As anticipated, different tumour entities exhibited distinct metastasis patterns.\u003c/p\u003e\n\u003ch3\u003eIn-hospital mortality rate\u003c/h3\u003e\n\u003cp\u003eA total of 77,025 patients in the 1,292,726 analysed hospitalisations died during their hospital stay, yielding an overall in-hospital mortality rate of 6% (suppl. table 3). The median in-hospital mortality rate across the examined tumour entities was 4.7%. Malignant pancreatic tumours had the highest rate at 10.7%, and bladder malignancies had the lowest at 3.2%. Mortality increased significantly when clinicians diagnosed organ metastases. The median mortality rate for lung metastases was 12.5% (range: 4.1\u0026ndash;15.5%), 18.4% for pleural metastases (range: 6.2\u0026ndash;24.2%), 16.6% for liver metastases (range: 3.9\u0026ndash;19.8%), and 14.3% for cerebral and/or leptomeningeal metastases (range: 10.1\u0026ndash;20.3%).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSpecialized palliative care involvement\u003c/h2\u003e \u003cp\u003e Specialized palliative care was delivered in 70,382 of the 1,292,726 hospital cases analysed, corresponding to an overall rate of 5.4%. In these cases, hospitals recorded a total of 72,634 specialized palliative care procedure codes, including 22,184 codes (30.5%) for complex palliative care, 34,609 codes (47.6%) for specialized complex treatment on a palliative care unit, and 15,841 codes (21.8%) for palliative care consultation services (Table\u0026nbsp;2, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, suppl. Figure\u0026nbsp;1). Patients with pancreatic malignancies showed the highest utilization of specialized palliative care (10.1% of all cases), whereas patients with bladder cancer showed the lowest rate (2.2%). Across the analysed tumour entities, the median utilization rate reached 5% (interquartile range [IQR]: 4.3%\u0026ndash;6.8%). We calculated odds ratios (OR, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) for the use of specialized palliative care relative to all analysed hospital cases. Patients with pancreatic cancer (OR: 1.95; 95% CI: 1.9\u0026ndash;2.0, Table\u0026nbsp;3), ovarian cancer (OR: 1.74; 95% CI: 1.68\u0026ndash;1.8), and lung cancer (OR: 1.47; 95% CI: 1.44\u0026ndash;1.49) showed the highest odds of specialized palliative care involvement. Linear regression analysis revealed a significant association between in-hospital mortality and the frequency of specialized palliative care involvement across the analysed tumour entities (y\u0026thinsp;=\u0026thinsp;0.86x\u0026thinsp;+\u0026thinsp;0.84; R\u0026sup2; = 0.72; F\u0026thinsp;=\u0026thinsp;28.5; p\u0026thinsp;=\u0026thinsp;0.0002, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Of the total 77025 hospital cases in which patients died in hospital, 24566 hospital cases (31.9%) involved patients receiving specialized palliative care (table c).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong comorbidities captured by the Charlson Comorbidity Index, severe liver disease showed the strongest association with specialized palliative care involvement (OR: 5.35; 95% CI: 4.94\u0026ndash;5.79), followed by paraplegia (OR: 3.00; 95% CI: 2.89\u0026ndash;3.11), heart failure (OR: 1.56; 95% CI: 1.52\u0026ndash;1.59), and dementia (OR: 1.45; 95% CI: 1.38\u0026ndash;1.52, suppl. Figure\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eNext, we analysed the frequency of specialised palliative care involvement across medical specialties that commonly serve as the primary treating disciplines in oncological centres (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Haematology/oncology demonstrated the highest rate of specialised palliative care involvement (10.4%), followed by gastroenterology (6.8%) and radiation oncology (6.7%). In contrast, gynaecology (0.7%) and urology (1.0%) showed the lowest rates. Accordingly, the odds ratios ranged from 2.02 (95% CI: 1.98\u0026ndash;2.05) for haematology/oncology to 0.12 (95% CI: 0.11\u0026ndash;0.12) for gynaecology and 0.17 (95% CI: 0.16\u0026ndash;0.18) for urology. Linear regression analysis again revealed a significant association between in-hospital mortality and the frequency of specialised palliative care involvement across medical specialties (y\u0026thinsp;=\u0026thinsp;0.70x\u0026thinsp;+\u0026thinsp;0.96; R\u0026sup2; = 0.64; F\u0026thinsp;=\u0026thinsp;15.7; p\u0026thinsp;=\u0026thinsp;0.003).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs the analysed tumour cases also included patients treated with curative intent, most tumour diseases with organ metastases no longer allow curative treatment and therefore require palliative care. To estimate the proportion of specialised palliative care among palliative tumour patients, we analysed hospital cases involving patients with organ metastases (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Table\u0026nbsp;4). Across all analysed primary tumours and metastatic sites, the median rate of specialised palliative care involvement reached 15.0% (interquartile range [IQR]: 8.3%\u0026ndash;19.4%). Among hospitalised cases involving one of the analysed tumours with additional cerebral metastases, specialised palliative care involvement reached 17.8%. Corresponding rates amounted to 17.0% for bone metastases, 16.1% for pleural metastases, and 14.3% for lung metastases. Compared with all analysed hospital cases, the presence of cerebral metastases markedly increased the likelihood of specialised palliative care involvement (OR: 3.8; 95% CI: 3.7\u0026ndash;3.8). Bone metastases (OR: 3.6; 95% CI: 3.5\u0026ndash;3.6), pleural metastases (OR: 3.3; 95% CI: 3.2\u0026ndash;3.4), (retro)peritoneal metastases (OR: 3.4; 95% CI: 3.4\u0026ndash;3.5), and lung metastases (OR: 2.9; 95% CI: 2.8\u0026ndash;3.0) showed similarly elevated odds. Linear regression analysis again demonstrated a significant association between in-hospital mortality and the frequency of specialised palliative care involvement across metastatic tumour entities (y\u0026thinsp;=\u0026thinsp;0.78x\u0026thinsp;\u0026minus;\u0026thinsp;1.1; R\u0026sup2; = 0.65; F\u0026thinsp;=\u0026thinsp;41.4; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur analysis quantified the proportion of inpatient palliative care services reimbursed under the German diagnosis-related groups (DRG) system for the most common oncological diseases and yielded the following key findings.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSpecialised palliative care was provided in 5.4% of hospital cases involving the most common malignant tumours in Germany.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe rate of inpatient palliative care treatment correlated with the hospital mortality.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAmong hospital cases with one of the analysed tumours and organ metastases, the median rate of specialised palliative care involvement reached 15.0%. Therefore, quality-of-life-centred early palliative care integration for patients with metastases appears to have reached the tipping point at which early adopters have accepted the concept, while adoption by the early majority has not yet occurred.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eIn Germany, the rate of specialised inpatient care for the malignancies examined with an incidence\u0026thinsp;\u0026ge;\u0026thinsp;3% is 5.4%. This level remains well below the 15\u0026ndash;20% tipping point described in the diffusion of innovations theory. These tumour cases include patients receiving curative treatment. Patients with organ metastases are highly likely to require palliative care, and clinical guidelines and recommendations explicitly advocate early palliative care integration and co-treatment for these groups [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The Lancet Oncology Commission (2025) identifies a profound \"human crisis\" in global cancer care, noting that current systems frequently neglect the emotional, relational, and existential dimensions of the patient experience despite significant biomedical progress [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This crisis stems from structural failures, including an over-reliance on technology, fragmented delivery models, and economic incentives that prioritise clinical throughput over compassionate, person-centred communication. To resolve this dehumanisation, the Commission advocates for the immediate, universal integration of palliative and psychosocial care, positioning empathetic engagement not as an elective supplement but as a fundamental requirement of oncological practice [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Across all analysed primary tumour entities and metastatic sites in the present study, the median utilisation of specialised palliative care reached 15.0%. The highest rates of inpatient specialised palliative treatment occurred in hospital cases with brain metastases (17.8%), bone metastases (17.0%), and pleural metastases (16.1%). Our findings align closely with our previous work on glioblastomas and cerebral metastases [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. A German study based on statutory health insurance data from the state of Baden-W\u0026uuml;rttemberg identified 3,535 patients with advanced cancer who required palliative care in 2015. Of these patients, 669 (18.9%) were referred to specialised outpatient palliative care teams, and 45.1% of those referrals involved early integration of palliative care [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Earlier published data highlighted the gap between patient needs and actual service delivery. The analysis of health insurance records for 80,768 individuals revealed that only 7.8% of cancer patients accessed specialised outpatient palliative care in their final year, while the system provided just 8.4 complex palliative treatments per 10,000 inhabitants [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Another study analysing health insurance data on specialised palliative care indicate that approximately one third of all patients receive specialised palliative care during the last year of life [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, comparative European analyses classify Germany, the Netherlands, the United Kingdom, and Switzerland as countries with a relatively high level of palliative care integration [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. International data nevertheless reveal substantial variation in the timing of palliative care delivery. In Victoria, Australia, 66% of patients who died from cancer in 2018 received palliative care, 18% accessed palliative care at least three months before death [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The median interval between first palliative care contact and death was 22 days [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In Canada, 12.6% of inpatients received some form of palliative care during the year preceding death [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In the United States, 8.0% of patients with newly diagnosed metastatic cancer received early specialised palliative care within eight weeks of diagnosis in 2018 and 2019 [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Palliative care involvement varied by tumour type, with higher rates in lung cancer (12.0%) and lower rates in breast cancer (4.3%) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. An analysis of Medicare-insured individuals with advanced cancer further demonstrated an early palliative care integration of 10.4% in 2019 [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAcross the entire analysed cohort, among hospital cases involving patients with metastatic malignancies, and within individual medical specialties, we observed a significant positive association between inpatient mortality and the rate of specialised palliative care involvement. Evidence on the relationship between inpatient palliative care utilisation and hospital mortality remains inconsistent. On the one hand, studies have shown that patients with a high predicted risk of short-term mortality are more likely to receive palliative care consultation during hospitalisation [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Several other studies have identified palliative care involvement as being associated with higher in-hospital mortality and a lower likelihood of intensive care unit admission [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. On the other hand, other studies have reported a reduction in hospital mortality associated with palliative care involvement, including a systematic review demonstrating a 34% reduction in in-hospital mortality [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. A retrospective Canadian study similarly reported higher overall hospital mortality among patients receiving palliative care; however, within the subgroup of terminally ill patients receiving palliative care, the probability of dying in hospital or being admitted to an intensive care unit was lower [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEverett M. Rogers\u0026rsquo; diffusion of innovations theory explains how new ideas and technologies spread within social systems and under what conditions they are adopted or rejected [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Rogers distinguishes adopter groups according to their timing of adoption, namely innovators, early, the early majority, the late majority, and laggards [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although innovators and early adopters together constitute only about 16% of users, they play a critical role as opinion leaders by legitimising innovations within the wider system [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Diffusion typically accelerates once adoption extends beyond early adopters to the early majority, which generally occurs at an adoption level of approximately 15\u0026ndash;20%. Crossing this tipping point is crucial, as innovations that fail to reach it often lose momentum and risk disappearing [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough Rogers did not originally develop diffusion of innovations theory for the healthcare sector, researchers increasingly apply it to explain the spread of healthcare innovations. In healthcare, the five innovation factors, relative advantage, compatibility, complexity, trialability, and observability, remain central but require contextual reinterpretation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Stakeholders typically assess relative advantage in terms of clinical effectiveness, patient safety, and evidence-based outcomes. For early integration, evidence gained from randomised clinical trials in early integration [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Compatibility reflects alignment with professional norms, ethical standards, clinical workflows, and regulatory requirements, while complexity often relates to training demands, workflow disruption, and system interoperability [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. For palliative care, must proactively cultivate awareness must proactively be cultivated regarding the necessity of early palliative care access to mitigate the systemic neglect of patient suffering. Oncology training programmes must mandate core competencies in palliative care for all healthcare professionals to ensure they possess the necessary skills to address the profound human suffering inherent in the cancer experience [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn spite of emerging standards and recommendations palliative care appears to be more firmly established and widely accepted primarily as end-of-life care in everyday clinical settings. Interpreting our present data through the lens of diffusion of innovations theory, quality-of-life-centred palliative care for patients with metastatic cancer in Germany remains largely confined to innovators and early adopters, while the early majority has not yet embraced the concept. Utilisation rates around 15% therefore mark a fragile threshold rather than a successful transition to self-sustaining diffusion. This finding is particularly noteworthy given that early palliative care integration has been discussed for more than 15 years [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Without broader acceptance by the early majority, early palliative care risks remaining a niche practice instead of becoming a normative component of oncological care. This stagnation has important implications, as it limits population-level access to timely palliative care despite strong evidence and guideline recommendations. From a diffusion and implementation science perspective, failure to convince the early majority necessitates a shift in strategy. Innovations that stall at the early-adopter stage rarely diffuse further through social influence alone and instead require structural reinforcement through policy, organisational change, and incentive realignment [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. For early palliative care, this implies that continued reliance on professional advocacy and guidelines is insufficient. Instead, health systems must actively lower adoption barriers by embedding early palliative care into standard care pathways, adjusting reimbursement mechanisms, disseminating information on efficacy, raising awareness and training for health care professionals. Without such measures, early palliative care is unlikely to cross into early-majority adoption and may continue to be perceived as optional rather than essential.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHospital cases do not correspond directly to individual patients, as some may be hospitalised multiple times but receive specialised inpatient palliative care only once, potentially underestimating patient-level coverage.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe evaluation reported on hospital cases, not on health care professionals, and thus provided only indirect evidence on the percentages of innovators and early adopters, assuming that the percentages of patients receiving palliative care and percentages of healthcare professionals initiating such transfers to palliative care would be correlated.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSecondary diagnoses (e.g., organ metastases coded as C79.x) may be recorded multiple times within a case, slightly affecting counts.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAround 70 palliative care units in Germany operate as \u0026ldquo;special facilities\u0026rdquo; (Besondere Einrichtungen), managing roughly 17,500 cases [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and these cases would not be captured in the reimbursement database. However, some units submit data to InEK for reporting but do not bill statutory health insurance, so their activity may have been captured partially.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHospital mortality was calculated per case without specifying cause but remains a relevant indicator of disease severity.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eOutpatient care is not included. Patient may receive specialized outpatient palliative care after discharge. These data are not available.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eFindings rely on accurate coding in the InEK database. Misclassification may introduce bias.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eFinally, the dataset lacks key information on symptom burden, psychosocial stress, and caregiver experience and quality-of-life.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSpecialised inpatient palliative care for patients with metastatic cancer in Germany reaches only around 15% of hospital cases, indicating that early adopters have embraced the practice, but the early majority has not yet followed. According to Rogers\u0026rsquo; diffusion of innovations theory, this stalled adoption risks preventing early palliative care from becoming a normative component of oncological care. Clinicians should proactively integrate palliative care into standard pathways, while health systems align incentives and expand capacity to overcome structural barriers. Without such coordinated action, timely access remains limited, and patients may not fully benefit from quality-of-life-centred care.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDisclosure of Potential Conflicts of Interest\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDeclaration of generative AI and AI-assisted technologies in the writing process\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAI-assisted technology was neither used for the generation, evaluation or interpretation of the data presented in the manuscript, nor for the creation of text, figures or tables. AI-based tools (chat GPT) may have been used to improve language and text readability.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHuman Ethics and Consent to Participate declarations:\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003enot applicable: The study complied with the ethical standards set in the 1964 Declaration of Helsinki and its subsequent revisions. Approval for the study protocol was granted by the institutional and local ethics committee at Brandenburg Medical School, Germany (Study ID: 190032024-ANF).\u0026nbsp;Our manuscript exclusively utilized publicly available data, no individual patient data,\u0026nbsp;thus obviating the need for individual patient consent.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding information\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study was not funded\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eClinical trial number\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003enot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization (WHO) (2002) WHO definition of palliative care. 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J Natl Compr Canc Netw 18: 133\u0026ndash;141 doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.6004/jnccn.2019.7354\u003c/span\u003e\u003cspan address=\"10.6004/jnccn.2019.7354\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTemel JS, Jackson VA, El-Jawahri A, Rinaldi SP, Petrillo LA, Kumar P, McGrath KA, LeBlanc TW, Kamal AH, Jones CA, Rabideau DJ, Horick N, Pintro K, Gallagher Medeiros ER, Post KE, Greer JA (2024) Stepped Palliative Care for Patients With Advanced Lung Cancer: A Randomized Clinical Trial. JAMA 332: 471\u0026ndash;481 doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.2024.10398\u003c/span\u003e\u003cspan address=\"10.1001/jama.2024.10398\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8610908/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8610908/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eEarly integration of specialised palliative care improves quality of life and outcomes in advanced cancer, yet its implementation in inpatient oncology remains inconsistent. This study evaluates the utilisation of specialised inpatient palliative care in German hospitals and interprets adoption patterns using Diffusion of Innovations theory.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe conducted a retrospective nationwide analysis of hospital cases reimbursed under the German diagnosis-related groups (DRG) system. The analysis included the most common oncological diseases and assessed utilisation of specialised inpatient palliative care overall and stratified by metastatic status, tumour entity, comorbidities, and treating medical specialties.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSpecialised inpatient palliative care was provided in 5.4% of hospital cases involving the most common malignant tumours. Among patients with organ metastases, utilisation increased to a median rate of 15.0% of hospital cases, with the highest rates observed in cases with brain (17.8%), bone (17.0%), and pleural metastases (16.1%). Palliative care involvement correlated positively with hospital mortality. Interpreted through diffusion of innovations theory, utilisation among patients with metastatic disease appears to have reached the tipping point associated with early adopters, while uptake among the early majority remains limited.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003e Despite longstanding guideline recommendations, specialised inpatient palliative care remains underutilised in German oncology care. From the perspective of diffusion of innovations theory, failure to move adoption beyond early adopters risks stagnation and prevents palliative care from becoming a routine component of inpatient oncology. To overcome this barrier, clinicians and policymakers should establish systematic referral pathways, implement interdisciplinary referral triggers, actively disseminate evidence on clinical effectiveness, increase awareness, strengthen palliative care training for healthcare professionals, and align reimbursement structures to support earlier and consistent palliative care integration.\u003c/p\u003e","manuscriptTitle":"At the tipping point, but yet not routine: Diffusion dynamics of inpatient palliative care","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-02 07:12:18","doi":"10.21203/rs.3.rs-8610908/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2fac0519-c83a-4ab3-bbbb-d56a0def1394","owner":[],"postedDate":"April 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-15T11:27:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-02 07:12:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8610908","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8610908","identity":"rs-8610908","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}