Validating a taxonomy of hospital at home (HaH) care models: An eDelphi study

Validating a taxonomy of hospital at home (HaH) care models: An eDelphi study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Validating a taxonomy of hospital at home (HaH) care models: An eDelphi study Kerstin Denecke, Octavio Rivera Romero This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6968513/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 17 You are reading this latest preprint version Abstract Background Hospital at home (HaH) is a model of acute healthcare that delivers hospital-level medical, nursing, and allied health services to patients in their own homes as a substitute for traditional hospital admission. The aim of this adapted Delphi study was to collect researcher’s opinions on a taxonomy for HaH care models. Methods We invited researchers with experience in HaH care to judge the relevance of items of a HaH taxonomy developed in previous work. In all three rounds, the participants scored the relevance of the characteristics regarding describing HaH care models on a 5-item Likert scale. Free text comments could be provided to each characteristic in all three rounds. Results Twenty persons joined the first round and sixteen persisted to the final round. 63 characteristics out of 90 achieved consent of which 27 obtained a strong agreement. The final taxonomy comprises 60 characteristics for 11 dimensions which in turn are aggregated into 5 perspectives. The results indicate that experts largely agree on metrics. Consensus is broad for many characteristics related to clinical characteristics. Patient-facing technology and also ecological sustainability as outcome seem to be less relevant currently. Conclusions The provided taxonomy can be used as checklist when new HaH care programs are developed to ensure key components are considered and reflected (e.g., patient eligibility, clinical services, technology use). It can be used as starting point for developing new HaH care models or updating existing ones. It provides also guidance for quality assessment. Hospital at home care model taxonomy validation delphi study Figures Figure 1 Figure 2 1. Background Hospital at Home (HaH) is an innovative healthcare delivery model that provides acute clinical care to patients in their own homes or nursing homes ( 1 ). Countries such as Australia, France, Israel, Italy, Spain, the United Kingdom and the United States have successfully implemented various forms of HaH care to meet increasing health care demands, improve patient satisfaction and reduce hospital-associated risks ( 2 , 3 ). Previous research has highlighted significant variability in their implementation across different health systems, revealing several clusters of HaH service models ( 4 , 5 ). These models differ in aspects such as patient selection criteria, nature and intensity of medical interventions, staffing configurations, and integration with hospital-based services ( 6 ). This heterogeneity poses challenges for comparing outcomes across programs and for scaling up successful HaH models in different health care contexts. Also technology use becomes more important with the raise of digital health ( 7 ), wearables and artificial intelligence which allows for continuous monitoring of the health status and active involvement of patients ( 8 , 9 ). While in the beginnings of HaH care technology was often restricted to communication technology, sensors, wearables, digital health and other upcoming technologies gain in interest for continuous monitoring and decision support ( 10 ). Leff et al. put defining a standard nomenclature for HaH in their research agenda for HaH-related research ( 11 ). In response, the development of a taxonomy of HaH care models has recently been undertaken Denecke 2025 ( 6 ). This taxonomy, based on the scientific literature, aims to describe different service models in a harmonised way, allowing for a structured evaluation and comparison of existing HaH approaches, while supporting the design of new ones. However, to ensure its usefulness and robustness, it is essential to validate and refine this taxonomy through expert input. The taxonomy consists of 12 unique dimensions structured into 5 perspectives following the progression from triaging, through care delivery, operational processes, and metrics for success: Persons and roles (2 dimensions), Target population (1 dimension), Service delivery and care model (6 dimensions), Outcomes and quality metrics (2 dimensions), and Training and education (1 dimension). Each dimension comprises between 1 and 19 characteristics. For example, the perspective Training and education has one dimension Training consisting in turn of 3 characteristics (Patient education, Informal caregiver training, Staff training). In this study, we build on the existing taxonomy and aim to validate the structure of the taxonomy to ensure that the categories and subcategories accurately represent the concepts relevant to HaH care models identified in the scientific literature; and validate the types of technologies used in HaH care with experiences from the real world. The latter aim addresses the observation from two reviews of scientific literature ( 6 , 12 ) according to which the technology usage in HaH care limits mostly to communication technology. We want to verify this observation with experts. By systematically addressing these objectives, we aim to contribute to a more standardised and accessible taxonomy for HaH care, ultimately facilitating better research, policy development and clinical practice. 2. Methods A modified Delphi method was used to validate the taxonomy ( 13 ). The Delphi method is often used to assess the presence or absence of consensus among participants ( 14 ). We have followed the recommendations for conducting and reporting of Delphi studies ( 15 , 16 ). The study design was submitted to the ethics committee of the canton of Bern, which confirmed that no ethics approval was necessary (Req-2025-00019). 2.1 Preparatory phase In the preparatory phase, the initial questionnaire for the Delphi study was set up. One question per characteristic was created where participants could select their extent of agreement of including the characteristic to the taxonomy on a 5-item scale (totally agree, partially agree, neither/nor, partially disagree, totally disagree), resulting in 75 statements related to the characteristics. After each question, a free text query was added to allow participants to comment or add additional characteristics. In the first round questionnaire (appendix 1), demographic questions were asked about the gender, education/background, year of working experience, sector where the person is currently working in, and continent of living. The experience with the care model HaH was collected with a 5-item Likert scale. We also asked the participants whether they developed a HaH care model or participated in such development and whether they delivered HaH care, again assessed on a 5-item Likert scale. We asked about the individuals’ understanding of the HaH care model by a free text response. This input was used to develop a definition of HaH care that was listed in the two subsequent rounds for collecting the participants’ level of agreement with this definition. 2.2 Delphi rounds We conducted three Delphi rounds as previous research found that it is preferable to conduct two or three rounds ( 17 – 19 ). In the first round the questionnaire comprised all characteristics from the taxonomy published by Denecke ( 6 ). Consensus was defined as an interquartile range (IQR) ≤ 1 on a 5-point Likert scale, with "strong agreement" at IQR = 0. Dissent was IQR > 1. Stability between rounds was assessed using the Wilcoxon signed-rank test ( 20 ), comparing medians of consecutive rounds. A statistically significant result indicated stable responses, following von der Gracht’s recommendations ( 21 ) and prior Delphi studies ( 22 – 25 ). Characteristics that achieved strong agreement already in the first round were removed in the second round to limit the effort for the participants and assuming this agreement will not change in following rounds. Participants were given the opportunity to change their minds for all other characteristics that did not achieve consensus in a round. Participants received a link to access the corresponding e-Delphi questionnaire via email. Further, they received their responses to the questionnaire of the previous round and figures showing the distribution of participants’ responses in percentages for each question and characteristic. 2.3 Analysis Quantitative data were analysed using descriptive statistics, including averages, medians and interquartile ranges (IQRs), to assess consensus strength. Percentages for each Likert scale response were also calculated and visualised to provide feedback in subsequent rounds. Characteristics were included in the final taxonomy if consensus was reached and at least 75% of participants had rated them 4 or 5 in the final relevant round. Open-ended responses were analysed using an iterative coding approach. KD coded all responses by theme and merged similar codes. Based on the final set of codes, KD and ORR agreed on modifications to existing items and the addition of new ones. This study will be reported according to CREDES guidelines (Conducting and REporting DElphi Studies ( 16 )). Appendix 4 presents a summary of the CREDES reporting (items 8–16) recommendations including a reference to sections and pages of this manuscript reporting them. 2.4 Participants The Delphi method uses a selected panel for feedback, without needing statistical representativeness. We aimed for a gender-balanced sample of 20–30 participants from North America, South America, Europe, and Australia/Oceania, where HaH care models are documented. We identified relevant networks and organizations through web searches and retrieved email addresses from their websites. Organizations included the World Hospital at Home Conference, HaH User Group, Sociedad Española de Hospitalización a Domicilio, Nordic Hospital at Home Society, and Healthcare at Home Summit. Corresponding authors from the latest Cochrane review ( 5 ) on HaH care models were also contacted. Invitations were emailed to experts, with 34 emails sent to 163 recipients and 1 mailing list; 8 emails were rejected. The study ran from January to April 2025. 3. Results 3.1 Characteristics of the panel 20 experts out of the 168 contacted persons and 1 mailing list responded to the survey in the first round. In the first round, 14 male and 6 female participants joined the panel. Table 1 shows the familiarity of the panel with the concept of HaH. Table 2 aggregates the participants’ characteristics. Table 1 Expertise of participants, n = 20 Statement Totally agree Partially agree Neither / nor Partially disagree Totally disagree I am familiar with the concept of hospital at home care 17 3 0 0 0 I developed a model of hospital at home care or participated in such development. 16 0 2 0 2 I delivered hospital at home care as a (health) professional. 14 2 1 1 2 Table 2 Summary of participants' characteristics. Round 1 Round 2 Round 3 N 20 16 16 Gender Female 6 4 4 Male 14 12 12 Education / Background Computer Science / Engineering 1 1 1 Psychology / Mental health 1 1 1 Medicine 16 14 14 Nursing 2 1 1 Other Health Sciences 1 1 1 Physiotherapy 2 1 1 Pharmacy 1 1 1 Years of working experience 5–10 years 1 1 1 > 10 years 19 15 15 Sector* Academia 8 7 7 Public health sector 11 8 8 Private health sector 2 2 2 Continent Europe 12 9 9 Australia and Oceania 5 4 4 North America 3 3 3 Level of experience with HaH care models I am familiar with the concept of hospital at home care 17 (totally agree) 14 (totally agree) 14 (totally agree) I developed a model of hospital at home care or participated in such development. 16 (totally agree) 12 (totally agree) 12 (totally agree) I delivered HaH care as a (health) professional. 14 (totally agree) 12 (totally agree) 12 (totally agree) *Some participants have several affiliations belonging to different sectors. 3.2 Definition of HaH care After round 1, a joint definition of HaH care was aggregated from 15 responses, though 5 participants misunderstood the question. The third round used this definition: “HaH is a model of acute healthcare delivering hospital-level services to patients at home as a substitute for hospital admission. It provides 24/7 supervision, diagnostics, therapeutics, medications, and technology comparable to in-hospital care, with governance remaining with the hospital. HaH is episodic, with a defined start and end, enabling safe acute care at home with the option for hospital transfer if necessary. This model is distinct from chronic disease management, outpatient therapies, virtual care, or home health services.”. In the third round, 13 out of 16 participants agreed with this definition, while 3 disagreed. Comments suggested changes like using “acute healthcare” instead of “acute inpatient care,” removing the mention of hospital governance, emphasizing the model's focus on acute medical problems, and clarifying that 24/7 supervision implies continuous remote monitoring or access to healthcare support. Incorporation of new items based on responses to the open-ended questions When creating the questionnaire for round 2, we removed all characteristics with an interquartile range (IQR) of 0 (strong agreement). In total, 25 items were removed. In the questionnaire of round 3, all items from round 2 were kept and asked again. Some changes were made: To the dimension “First point of contact”, we added “Medical specialist / specialist clinic”. To the dimension “Patient selection criteria”, we added “Appropriate insurance model”. Within the dimension “Technology involved”, we modified the characteristic “Tablet/Laptop/PC provided for patient use” into “Tablet/Laptop/PC provided for patient/family/friend/caregiver use”. Figure 1 summarizes the data collection process of the Delphi study. 3.3 Validated taxonomy The final version of the taxonomy consists of 5 perspectives, 11 dimensions, and 60 characteristics. The Outcome and quality metrics perspective has 2 dimensions: Intended outcome / purpose (7 characteristics), and Quality / outcome metrics (14 characteristics). The Persons and roles perspective includes 2 dimensions: First point of contact (6 characteristics), and Persons (8 characteristics). The Service delivery and care model perspective defines 5 dimensions: Care delivery approach (4 characteristics), Clinical applications (1 characteristic), Operational model (1 characteristic), Technology involved (5 characteristics), and Reimbursement (2 characteristics). The Target population perspective has one dimension: Patient selection criteria which includes 9 characteristics. Finally, the Training and education perspective includes one dimension, Training measurements, that has 3 characteristics. Figure 2 shows the final version of the taxonomy. Although 60 characteristics were included in the final version, 63 of the 90 studied characteristics reached consensus, of which 27 obtained a strong agreement. For 3 characteristics, participants agreed they are irrelevant (from Person involved: mental health support, from First point of care: Telephone triage, from Patient selection criteria: Literacy level)). Appendix 2 presents the results after round 3. Appendix 3 presents the results obtained in each round. All the characteristics proposed in three of the dimensions (Care delivery approach (n = 4), Intended outcome / purpose (n = 7), and Training measurements (n = 3)) reached agreement at the end of the Delphi process. In the rest of the dimensions, the following number of characteristics was agreed upon: 1/5 in Clinical application, 7/10 in First point of contact, 1/3 in Operational model, 10/13 in Patient selection criteria, 9/13 in Persons, 14/19 in Quality / outcome metrics, 2/5 in Reimbursement, and 5/8 in Technology involved. Only 5 characteristics did not achieve stability in participants' responses between rounds 2 and 3. 4 of these characteristics reached consensus (3 of them belonging to the Target population dimension: Adequate living conditions, Demographics, and Literacy level; and another to the Technology involved dimension: Remote monitoring). Only the Informal caregiver skills characteristic, which belongs to the Target population dimension, did not reach agreement, with an IQR value of 2, nor stability in the last round. 4. Discussion 4.1 Principal results Our study highlights areas of agreement and disagreement among sector experts regarding the characteristics used to describe and distinguish HaH care models. The results show that HaH care models can be categorised using five perspectives and 11 dimensions. Validating the original taxonomy using scientific literature revealed additional important characteristics in practice. The overall structure of the taxonomy was not questioned, and characteristics that were subject to disagreement or deemed unimportant were removed. Improvements were made to enhance the taxonomy's usability and clarity for both experts and non-experts. A total of 60 out of 90 characteristics were included in the final taxonomy. Technologies identified in the literature were only partially confirmed in practice, indicating the need to focus on patient monitoring and patient-facing technologies within the HaH care model. Our work is unique in that there is currently no validated taxonomy available to describe HaH care models. Nikmanesh et al. identified HaH care dimensions and components through a literature review ( 26 ). These included benefits, challenges, facilitators, management-related factors, medical conditions and factors associated with patients, families and caregivers. In contrast, our taxonomy is more comprehensive as it considers the complete care model, including training and education, outcomes and quality, service delivery, the target population and roles. 4.2 Interpretation and relation to initial taxonomy version Participants perceived ecological benefits, such as reduced travel time and CO₂ emissions, as relatively unimportant, likely due to the healthcare sector's focus on patient-centred care. Similarly, there was notable disagreement regarding outcomes such as drug prescriptions and workload reduction for professionals, revealing a misalignment between stakeholder priorities. This highlights the challenge of balancing diverse perspectives in healthcare innovation. Nevertheless, there was consensus on many key quality and outcome metrics, including clinical effectiveness, satisfaction and cost efficiency. Dissent regarding several other characteristics may be attributed to variability in the implementation of local healthcare systems and organisational structures. For example, the three potential initial points of contact — community healthcare staff, nursing homes and ambulance services — were introduced based on participant feedback, but consensus was not achieved and they were rated as relatively unimportant. This likely reflects differences in how HaH care is provided and initiated across regions. A similar pattern emerged in the reimbursement dimension. The characteristics 'bundled payments', 'outpatient-based reimbursement model' and 'community-based reimbursement model' also failed to reach consensus, suggesting that these reimbursement models may not be equally relevant or feasible in different healthcare contexts. Further, while in the literature three operational models were identified, only half of the participants considered the operational models ‘insurance driven’ and ‘third-party provider managed’ relevant. These findings highlight the impact of national policies and funding mechanisms on the perceived importance and applicability of specific HaH components. Differences in the application of HaH care model originate from differing interpretations. While the original taxonomy had a broader scope, including post-acute or chronic disease management, most participants defined it strictly in terms of acute medical care, leading to disagreement. Similarly, no consensus was reached on patient-facing technologies (e.g. digital tools, data management or devices for patients/caregivers), possibly due to professional bias among the panel or limited real-world adoption, as noted in prior research ( 12 ). In contrast, technology for healthcare professionals was met with clearer agreement. Consensus was reached on ten patient selection criteria, but not on the three that were newly added. While these are important, they may not be universally applicable: for example, shared language is crucial in multilingual regions, and caregiver skills vary depending on the HaH model. No agreement was reached on three technologies intended for use by patients or caregivers: digital health tools, data management tools, and devices. In contrast, the five agreed technology criteria focused on the needs of healthcare professionals. This may reflect the provider-centric perspective of our panel and the limited adoption of patient-facing technology in current HaH settings — an issue also noted in our previous review. Pandit et al. ( 27 ) highlight the potential of digital tools such as wearables for HaH care, but also point out barriers such as a lack of tailored design, weak data algorithms and poor electronic health record (EHR) integration. Consensus was reached on ten patient selection criteria, but not on the three that were newly added. These criteria, which include factors such as shared language with the care team and the skills of informal caregivers, may not be universally applicable, as their relevance depends on local healthcare contexts and the specific design of HaH models. It is likely that such context-specific factors contributed to the lack of agreement. 4.3 Strengths and limitations of this study Our Delphi study concluded after three rounds, with dissent on 27 characteristics. Further rounds might have achieved consensus, but we prioritized avoiding participant attrition due to their limited availability. Expert selection was unsystematic, conducted by a single author, and despite efforts to include global representation, no participants from Asia, South America, or Africa joined—possibly due to underdeveloped or differently conceptualized HaH models in those regions. Most experts had health science backgrounds, introducing potential bias, though this aligns with the original taxonomy’s scientific focus. Despite modest participation (20 in Round 1, 16 thereafter), outreach to international organizations suggests reasonable representativeness. Future validation could involve larger expert panels at forums like the World Hospital at Home Congress. 5. Conclusions The provided taxonomy can be used as checklist when new HaH care programs are developed to ensure key components are considered and reflected (e.g., patient eligibility, clinical services, technology use). For example, the patient selection criteria in the taxonomy help not to miss important aspects. Existing HaH care programs can benchmark themselves against the taxonomy to identify gaps or areas for improvement. The list of outcome metrics provides guidance on quality metrics useful for measuring effectiveness of care model implementations. The taxonomy can be used by policymakers and payers to understand the structural and operational elements of HaH programs, which will aid the development of targeted reimbursement models and regulatory guidelines. Future work could study whether these aspects should gain more practical relevance. The role of patient-facing technology in HaH care models requires still research and implementation into practice. Abbreviations CREDES Conducting and REporting DElphi Studies HaH Hospital at home IQR Interquartile range Declarations Acknowledgements We acknowledge the Delphi panel members for participating in the Delphi study and providing their expertise. Author’s contribution KD: Conceptualization, Setting up the study, Paper initial draft, Panel member acquisition, Paper finalization ORR: Statistics, Testing of the questionnaire, Paper initial draft, Paper finalization Funding No funding supported this research. Data availability Not applicable. Ethics approval and consent to participate All participants consented to the anonymous analysis of their judgements. The study was conducted in compliance with the Declaration of Helsinki. A clarification of responsibility was submitted to and approved by the cantonal ethics committee of Bern (Req-2025-00019). They confirmed that no ethics approval is required for the study. Consent for publication Not applicable Competing interests The authors declare no competing interests. References What is Hospital at Home? [Internet]. World Hospital at Home Community. 2024. Available from: https://whahc-community.kenes.com/mod/page/view.php?id=1042 Shepperd S, Doll H, Angus RM, Clarke MJ, Iliffe S, Kalra L, et al. Avoiding hospital admission through provision of hospital care at home: a systematic review and meta-analysis of individual patient data. CMAJ Can Med Assoc J J Assoc Medicale Can. 2009 Jan 20;180(2):175–82. Leff B, Burton L, Mader SL, Naughton B, Burl J, Inouye SK, et al. Hospital at home: feasibility and outcomes of a program to provide hospital-level care at home for acutely ill older patients. Ann Intern Med. 2005 Dec 6;143(11):798–808. Shepperd S, Iliffe S, Doll HA, Clarke MJ, Kalra L, Wilson AD, et al. Admission avoidance hospital at home. Cochrane Database Syst Rev. 2016 Sep 1;9(9):CD007491. Edgar K, Iliffe S, Doll HA, Clarke MJ, Gonçalves-Bradley DC, Wong E, et al. Admission avoidance hospital at home. Cochrane Database Syst Rev. 2024 Mar 5;3(3):CD007491. Denecke K. Mapping the landscape of Hospital at home (HaH) care: a validated taxonomy for HaH care model classification. BMC Health Serv Res. 2025 Jan 15;25(1):84. Aapro M, Bossi P, Dasari A, Fallowfield L, Gascón P, Geller M, et al. Digital health for optimal supportive care in oncology: benefits, limits, and future perspectives. Support Care Cancer Off J Multinatl Assoc Support Care Cancer. 2020 Oct;28(10):4589–612. Zysman M, Creisson A, Ghrenassia G, Nisse-Durgeat S, Boyer A, Matranga M, et al. Employing Digital Health for the Follow-up and Monitoring of Patients Undergoing Anticancer Treatment: First Results of Satelia®Onco on Patient Satisfaction and Recommendations of Use in France. Clin Oncol R Coll Radiol G B. 2025 Apr 26;43:103856. Xu S, Kantarcigil C, Rangwala R, Nellis A, San Chun K, Richards D, et al. Digital health technology for Parkinson’s disease with comprehensive monitoring and artificial intelligence-enabled haptic biofeedback for bulbar dysfunction. J Park Dis. 2025 Apr 4;1877718X251329354. Lim R, Boord M, Soriano J, Bilton R, Roughead EE. Monitoring the effects of medications in residential aged care (nursing home) using digital health technologies: insights from the ReMInDAR and ADEPT projects. Age Ageing. 2025 Mar 3;54(3):afaf019. Leff B, DeCherrie LV, Montalto M, Levine DM. A research agenda for hospital at home. J Am Geriatr Soc. 2022 Apr;70(4):1060–9. Denecke K, May R, Borycki EM, Kushniruk AW. Digital health as an enabler for hospital@home: A rising trend or just a vision? Front Public Health. 2023 Feb 17;11:1137798. McKenna HP. The Delphi technique: a worthwhile research approach for nursing? J Adv Nurs. 1994 Jun;19(6):1221–5. Hsu CC, Sandford BA. The Delphi Technique: Making Sense of Consensus. [cited 2023 Aug 24]; Available from: https://scholarworks.umass.edu/pare/vol12/iss1/10/ Hasson F, Keeney S, McKenna H. Research guidelines for the Delphi survey technique. J Adv Nurs. 2000 Oct;32(4):1008–15. Jünger S, Payne SA, Brine J, Radbruch L, Brearley SG. Guidance on Conducting and REporting DElphi Studies (CREDES) in palliative care: Recommendations based on a methodological systematic review. Palliat Med. 2017 Sep;31(8):684–706. Beech B. Studying the future: a Delphi survey of how multi‐disciplinary clinical staff view the likely development of two community mental health centres over the course of the next two years. J Adv Nurs. 1997 Feb;25(2):331–8. Green B, Jones M, Hughes D, Williams A. Applying the Delphi technique in a study of GPs’ information requirements. Health Soc Care Community. 1999 May;7(3):198–205. Procter S, Hunt M. Using the Delphi survey technique to develop a professional definition of nursing for analysing nursing workload. J Adv Nurs. 1994 May;19(5):1003–14. Argyrous G. Statistics for research: with a guide to SPSS. 3rd ed. Los Angeles: SAGE; 2011. 585 p. von der Gracht HA. Consensus measurement in Delphi studies. Technol Forecast Soc Change. 2012 Oct;79(8):1525–36. De Vet E. Determinants of forward stage transitions: a Delphi study. Health Educ Res. 2004 Jul 14;20(2):195–205. Seagle DE. CHARACTERISTICS OF THE TURFGRASS INDUSTRY IN 2020: A DELPHI STUDY WITH IMPLICATIONS FOR AGRICULTURAL EDUCATION PROGRAMS. J South Agric Educ Res. 2002;(52):1–13. Benjumea J, Ropero J, Dorronzoro-Zubiete E, Rivera-Romero O, Carrasco A. A Proposal for a Robust Validated Weighted General Data Protection Regulation-Based Scale to Assess the Quality of Privacy Policies of Mobile Health Applications: An eDelphi Study. Methods Inf Med. 2023 Dec;62(5–06):154–64. Denecke K, Romero OR, Petersen C, Benham-Hutchins M, Cabrer M, Davies S, et al. Defining and Scoping Participatory Health Informatics: An eDelphi Study. Methods Inf Med. 2023 Sep;62(03/04):090–9. Nikmanesh P, Arabloo J, Gorji HA. Dimensions and components of hospital-at-home care: a systematic review. BMC Health Serv Res. 2024 Nov 25;24(1):1458. Pandit JA, Pawelek JB, Leff B, Topol EJ. The hospital at home in the USA: current status and future prospects. NPJ Digit Med. 2024 Feb 27;7(1):48. Additional Declarations No competing interests reported. Supplementary Files Appendix14.pdf Supplementary information Appendix 1: Questionnaire Appendix 2: Results obtained in the last round Appendix 3: Results of each round Appendix 4: CREDES table Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 10 Feb, 2026 Reviews received at journal 04 Feb, 2026 Reviews received at journal 12 Nov, 2025 Reviews received at journal 06 Nov, 2025 Reviews received at journal 31 Oct, 2025 Reviewers agreed at journal 23 Oct, 2025 Reviewers agreed at journal 21 Oct, 2025 Reviewers agreed at journal 20 Oct, 2025 Reviewers agreed at journal 20 Oct, 2025 Reviewers agreed at journal 14 Sep, 2025 Reviewers agreed at journal 10 Sep, 2025 Reviewers agreed at journal 15 Aug, 2025 Reviewers invited by journal 14 Jul, 2025 Editor assigned by journal 05 Jul, 2025 Editor invited by journal 30 Jun, 2025 Submission checks completed at journal 27 Jun, 2025 First submitted to journal 27 Jun, 2025 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. 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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-6968513","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":485137169,"identity":"d8f53c7b-9f6d-43f8-992b-e1dcdd391a66","order_by":0,"name":"Kerstin Denecke","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIie3PsWrDMBSF4WsEmlTPEgbnFa4J2EvIsyQEnMWBjhkzuYv9Lt4abwoGexGdPRQSKGTqIOgS00AbHArpELljB/2gAxo+hABstn8Y7xcvR0I/PhIF4GwGiLwhY6TJX8jNzIshIp7ytw/9+Apuk+8OJzVZPtMHCd32PvFYE3KJRxDqZRFkbbwqU3fm5Oo+8XlML3+pANsk9EBXq2KfIXFSAxkdie7J/j36BP21xJqZiccp8OsrLCTQytkgEVlMucKKCZWMRaYWQZky3OUGwpua6PW58t1GBfpUT0cRZcGhM5Cf2K+bHAY2m81mM/UNT3JWc2TWHmIAAAAASUVORK5CYII=","orcid":"","institution":"Bern University of Applied Sciences","correspondingAuthor":true,"prefix":"","firstName":"Kerstin","middleName":"","lastName":"Denecke","suffix":""},{"id":485137170,"identity":"366a76fb-1e51-474f-af6b-358ba6f65edd","order_by":1,"name":"Octavio Rivera Romero","email":"","orcid":"","institution":"Universidad de Sevilla","correspondingAuthor":false,"prefix":"","firstName":"Octavio","middleName":"Rivera","lastName":"Romero","suffix":""}],"badges":[],"createdAt":"2025-06-24 19:23:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6968513/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6968513/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87036099,"identity":"151248a7-996f-4692-9cfa-efc353f1ca27","added_by":"auto","created_at":"2025-07-18 13:19:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":63804,"visible":true,"origin":"","legend":"\u003cp\u003eData collection in the Delphi study, RR - Response rate\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6968513/v1/89537cf8eb7bb134b99b9346.png"},{"id":87036102,"identity":"ad026544-6205-42e5-8eab-4e8b6697b83c","added_by":"auto","created_at":"2025-07-18 13:19:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":228559,"visible":true,"origin":"","legend":"\u003cp\u003eHaH taxonomy with characteristics that found agreement and were considered relevant (EHR - Electronic health record, HCP - Healthcare professional)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6968513/v1/76318265c53cdd4ada80980e.png"},{"id":87040071,"identity":"4cf39f26-a612-46e4-b22a-94ee1726a165","added_by":"auto","created_at":"2025-07-18 13:43:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":972088,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6968513/v1/b17ae757-9000-4891-89d7-0147a2653a91.pdf"},{"id":87036105,"identity":"5c24b0d4-7542-40e2-bf60-3781c6d58e91","added_by":"auto","created_at":"2025-07-18 13:19:27","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":492577,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary information\u003c/p\u003e\n\u003cp\u003eAppendix 1: Questionnaire\u003c/p\u003e\n\u003cp\u003eAppendix 2: Results obtained in the last round\u003c/p\u003e\n\u003cp\u003eAppendix 3: Results of each round\u003c/p\u003e\n\u003cp\u003eAppendix 4: CREDES table\u003c/p\u003e","description":"","filename":"Appendix14.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6968513/v1/e7f83cfbfe9d2709f3be495a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Validating a taxonomy of hospital at home (HaH) care models: An eDelphi study","fulltext":[{"header":"1. Background","content":"\u003cp\u003eHospital at Home (HaH) is an innovative healthcare delivery model that provides acute clinical care to patients in their own homes or nursing homes (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Countries such as Australia, France, Israel, Italy, Spain, the United Kingdom and the United States have successfully implemented various forms of HaH care to meet increasing health care demands, improve patient satisfaction and reduce hospital-associated risks (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Previous research has highlighted significant variability in their implementation across different health systems, revealing several clusters of HaH service models (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). These models differ in aspects such as patient selection criteria, nature and intensity of medical interventions, staffing configurations, and integration with hospital-based services (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). This heterogeneity poses challenges for comparing outcomes across programs and for scaling up successful HaH models in different health care contexts. Also technology use becomes more important with the raise of digital health (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), wearables and artificial intelligence which allows for continuous monitoring of the health status and active involvement of patients (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). While in the beginnings of HaH care technology was often restricted to communication technology, sensors, wearables, digital health and other upcoming technologies gain in interest for continuous monitoring and decision support (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Leff et al. put defining a standard nomenclature for HaH in their research agenda for HaH-related research (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn response, the development of a taxonomy of HaH care models has recently been undertaken Denecke 2025 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). This taxonomy, based on the scientific literature, aims to describe different service models in a harmonised way, allowing for a structured evaluation and comparison of existing HaH approaches, while supporting the design of new ones. However, to ensure its usefulness and robustness, it is essential to validate and refine this taxonomy through expert input. The taxonomy consists of 12 unique dimensions structured into 5 perspectives following the progression from triaging, through care delivery, operational processes, and metrics for success: Persons and roles (2 dimensions), Target population (1 dimension), Service delivery and care model (6 dimensions), Outcomes and quality metrics (2 dimensions), and Training and education (1 dimension). Each dimension comprises between 1 and 19 characteristics. For example, the perspective Training and education has one dimension Training consisting in turn of 3 characteristics (Patient education, Informal caregiver training, Staff training).\u003c/p\u003e\u003cp\u003eIn this study, we build on the existing taxonomy and aim to validate the structure of the taxonomy to ensure that the categories and subcategories accurately represent the concepts relevant to HaH care models identified in the scientific literature; and validate the types of technologies used in HaH care with experiences from the real world. The latter aim addresses the observation from two reviews of scientific literature (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) according to which the technology usage in HaH care limits mostly to communication technology. We want to verify this observation with experts. By systematically addressing these objectives, we aim to contribute to a more standardised and accessible taxonomy for HaH care, ultimately facilitating better research, policy development and clinical practice.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eA modified Delphi method was used to validate the taxonomy (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The Delphi method is often used to assess the presence or absence of consensus among participants (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). We have followed the recommendations for conducting and reporting of Delphi studies (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The study design was submitted to the ethics committee of the canton of Bern, which confirmed that no ethics approval was necessary (Req-2025-00019).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Preparatory phase\u003c/h2\u003e\u003cp\u003eIn the preparatory phase, the initial questionnaire for the Delphi study was set up. One question per characteristic was created where participants could select their extent of agreement of including the characteristic to the taxonomy on a 5-item scale (totally agree, partially agree, neither/nor, partially disagree, totally disagree), resulting in 75 statements related to the characteristics. After each question, a free text query was added to allow participants to comment or add additional characteristics.\u003c/p\u003e\u003cp\u003eIn the first round questionnaire (appendix 1), demographic questions were asked about the gender, education/background, year of working experience, sector where the person is currently working in, and continent of living. The experience with the care model HaH was collected with a 5-item Likert scale. We also asked the participants whether they developed a HaH care model or participated in such development and whether they delivered HaH care, again assessed on a 5-item Likert scale. We asked about the individuals\u0026rsquo; understanding of the HaH care model by a free text response. This input was used to develop a definition of HaH care that was listed in the two subsequent rounds for collecting the participants\u0026rsquo; level of agreement with this definition.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Delphi rounds\u003c/h2\u003e\u003cp\u003eWe conducted three Delphi rounds as previous research found that it is preferable to conduct two or three rounds (\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). In the first round the questionnaire comprised all characteristics from the taxonomy published by Denecke (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eConsensus was defined as an interquartile range (IQR)\u0026thinsp;\u0026le;\u0026thinsp;1 on a 5-point Likert scale, with \"strong agreement\" at IQR\u0026thinsp;=\u0026thinsp;0. Dissent was IQR\u0026thinsp;\u0026gt;\u0026thinsp;1. Stability between rounds was assessed using the Wilcoxon signed-rank test (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), comparing medians of consecutive rounds. A statistically significant result indicated stable responses, following von der Gracht\u0026rsquo;s recommendations (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) and prior Delphi studies (\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCharacteristics that achieved strong agreement already in the first round were removed in the second round to limit the effort for the participants and assuming this agreement will not change in following rounds. Participants were given the opportunity to change their minds for all other characteristics that did not achieve consensus in a round. Participants received a link to access the corresponding e-Delphi questionnaire via email. Further, they received their responses to the questionnaire of the previous round and figures showing the distribution of participants\u0026rsquo; responses in percentages for each question and characteristic.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Analysis\u003c/h2\u003e\u003cp\u003eQuantitative data were analysed using descriptive statistics, including averages, medians and interquartile ranges (IQRs), to assess consensus strength. Percentages for each Likert scale response were also calculated and visualised to provide feedback in subsequent rounds. Characteristics were included in the final taxonomy if consensus was reached and at least 75% of participants had rated them 4 or 5 in the final relevant round. Open-ended responses were analysed using an iterative coding approach. KD coded all responses by theme and merged similar codes. Based on the final set of codes, KD and ORR agreed on modifications to existing items and the addition of new ones. This study will be reported according to CREDES guidelines (Conducting and REporting DElphi Studies (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)). Appendix 4 presents a summary of the CREDES reporting (items 8\u0026ndash;16) recommendations including a reference to sections and pages of this manuscript reporting them.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Participants\u003c/h2\u003e\u003cp\u003eThe Delphi method uses a selected panel for feedback, without needing statistical representativeness. We aimed for a gender-balanced sample of 20\u0026ndash;30 participants from North America, South America, Europe, and Australia/Oceania, where HaH care models are documented. We identified relevant networks and organizations through web searches and retrieved email addresses from their websites. Organizations included the World Hospital at Home Conference, HaH User Group, Sociedad Espa\u0026ntilde;ola de Hospitalizaci\u0026oacute;n a Domicilio, Nordic Hospital at Home Society, and Healthcare at Home Summit. Corresponding authors from the latest Cochrane review (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) on HaH care models were also contacted. Invitations were emailed to experts, with 34 emails sent to 163 recipients and 1 mailing list; 8 emails were rejected. The study ran from January to April 2025.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Characteristics of the panel\u003c/h2\u003e\u003cp\u003e20 experts out of the 168 contacted persons and 1 mailing list responded to the survey in the first round. In the first round, 14 male and 6 female participants joined the panel. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the familiarity of the panel with the concept of HaH. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e aggregates the participants\u0026rsquo; characteristics.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eExpertise of participants, n\u0026thinsp;=\u0026thinsp;20\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStatement\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotally agree\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePartially agree\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNeither / nor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePartially disagree\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTotally disagree\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eI am familiar with the concept of hospital at home care\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eI developed a model of hospital at home care or participated in such development.\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eI delivered hospital at home care as a (health) professional.\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of participants' characteristics.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRound 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRound 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRound 3\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eGender\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEducation / Background\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComputer Science / Engineering\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePsychology / Mental health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedicine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNursing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther Health Sciences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysiotherapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePharmacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eYears of working experience\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026ndash;10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSector*\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcademia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePublic health sector\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrivate health sector\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eContinent\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEurope\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAustralia and Oceania\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNorth America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLevel of experience with HaH care models\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI am familiar with the concept of hospital at home care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (totally agree)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (totally agree)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (totally agree)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI developed a model of hospital at home care or participated in such development.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (totally agree)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (totally agree)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (totally agree)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI delivered HaH care as a (health) professional.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (totally agree)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (totally agree)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (totally agree)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*Some participants have several affiliations belonging to different sectors.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Definition of HaH care\u003c/h2\u003e\u003cp\u003eAfter round 1, a joint definition of HaH care was aggregated from 15 responses, though 5 participants misunderstood the question. The third round used this definition: \u0026ldquo;HaH is a model of acute healthcare delivering hospital-level services to patients at home as a substitute for hospital admission. It provides 24/7 supervision, diagnostics, therapeutics, medications, and technology comparable to in-hospital care, with governance remaining with the hospital. HaH is episodic, with a defined start and end, enabling safe acute care at home with the option for hospital transfer if necessary. This model is distinct from chronic disease management, outpatient therapies, virtual care, or home health services.\u0026rdquo;.\u003c/p\u003e\u003cp\u003eIn the third round, 13 out of 16 participants agreed with this definition, while 3 disagreed. Comments suggested changes like using \u0026ldquo;acute healthcare\u0026rdquo; instead of \u0026ldquo;acute inpatient care,\u0026rdquo; removing the mention of hospital governance, emphasizing the model's focus on acute medical problems, and clarifying that 24/7 supervision implies continuous remote monitoring or access to healthcare support.\u003c/p\u003e\u003cp\u003eIncorporation of new items based on responses to the open-ended questions\u003c/p\u003e\u003cp\u003eWhen creating the questionnaire for round 2, we removed all characteristics with an interquartile range (IQR) of 0 (strong agreement). In total, 25 items were removed. In the questionnaire of round 3, all items from round 2 were kept and asked again. Some changes were made: To the dimension \u0026ldquo;First point of contact\u0026rdquo;, we added \u0026ldquo;Medical specialist / specialist clinic\u0026rdquo;. To the dimension \u0026ldquo;Patient selection criteria\u0026rdquo;, we added \u0026ldquo;Appropriate insurance model\u0026rdquo;. Within the dimension \u0026ldquo;Technology involved\u0026rdquo;, we modified the characteristic \u0026ldquo;Tablet/Laptop/PC provided for patient use\u0026rdquo; into \u0026ldquo;Tablet/Laptop/PC provided for patient/family/friend/caregiver use\u0026rdquo;. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the data collection process of the Delphi study.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Validated taxonomy\u003c/h2\u003e\u003cp\u003eThe final version of the taxonomy consists of 5 perspectives, 11 dimensions, and 60 characteristics. The Outcome and quality metrics perspective has 2 dimensions: Intended outcome / purpose (7 characteristics), and Quality / outcome metrics (14 characteristics). The Persons and roles perspective includes 2 dimensions: First point of contact (6 characteristics), and Persons (8 characteristics). The Service delivery and care model perspective defines 5 dimensions: Care delivery approach (4 characteristics), Clinical applications (1 characteristic), Operational model (1 characteristic), Technology involved (5 characteristics), and Reimbursement (2 characteristics). The Target population perspective has one dimension: Patient selection criteria which includes 9 characteristics. Finally, the Training and education perspective includes one dimension, Training measurements, that has 3 characteristics. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the final version of the taxonomy.\u003c/p\u003e\u003cp\u003eAlthough 60 characteristics were included in the final version, 63 of the 90 studied characteristics reached consensus, of which 27 obtained a strong agreement. For 3 characteristics, participants agreed they are irrelevant (from Person involved: mental health support, from First point of care: Telephone triage, from Patient selection criteria: Literacy level)). Appendix 2 presents the results after round 3. Appendix 3 presents the results obtained in each round. All the characteristics proposed in three of the dimensions (Care delivery approach (n\u0026thinsp;=\u0026thinsp;4), Intended outcome / purpose (n\u0026thinsp;=\u0026thinsp;7), and Training measurements (n\u0026thinsp;=\u0026thinsp;3)) reached agreement at the end of the Delphi process. In the rest of the dimensions, the following number of characteristics was agreed upon: 1/5 in Clinical application, 7/10 in First point of contact, 1/3 in Operational model, 10/13 in Patient selection criteria, 9/13 in Persons, 14/19 in Quality / outcome metrics, 2/5 in Reimbursement, and 5/8 in Technology involved. Only 5 characteristics did not achieve stability in participants' responses between rounds 2 and 3. 4 of these characteristics reached consensus (3 of them belonging to the Target population dimension: Adequate living conditions, Demographics, and Literacy level; and another to the Technology involved dimension: Remote monitoring). Only the Informal caregiver skills characteristic, which belongs to the Target population dimension, did not reach agreement, with an IQR value of 2, nor stability in the last round.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Principal results\u003c/h2\u003e\u003cp\u003eOur study highlights areas of agreement and disagreement among sector experts regarding the characteristics used to describe and distinguish HaH care models. The results show that HaH care models can be categorised using five perspectives and 11 dimensions. Validating the original taxonomy using scientific literature revealed additional important characteristics in practice. The overall structure of the taxonomy was not questioned, and characteristics that were subject to disagreement or deemed unimportant were removed. Improvements were made to enhance the taxonomy's usability and clarity for both experts and non-experts. A total of 60 out of 90 characteristics were included in the final taxonomy. Technologies identified in the literature were only partially confirmed in practice, indicating the need to focus on patient monitoring and patient-facing technologies within the HaH care model.\u003c/p\u003e\u003cp\u003eOur work is unique in that there is currently no validated taxonomy available to describe HaH care models. Nikmanesh et al. identified HaH care dimensions and components through a literature review (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). These included benefits, challenges, facilitators, management-related factors, medical conditions and factors associated with patients, families and caregivers. In contrast, our taxonomy is more comprehensive as it considers the complete care model, including training and education, outcomes and quality, service delivery, the target population and roles.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Interpretation and relation to initial taxonomy version\u003c/h2\u003e\u003cp\u003eParticipants perceived ecological benefits, such as reduced travel time and CO₂ emissions, as relatively unimportant, likely due to the healthcare sector's focus on patient-centred care. Similarly, there was notable disagreement regarding outcomes such as drug prescriptions and workload reduction for professionals, revealing a misalignment between stakeholder priorities. This highlights the challenge of balancing diverse perspectives in healthcare innovation. Nevertheless, there was consensus on many key quality and outcome metrics, including clinical effectiveness, satisfaction and cost efficiency.\u003c/p\u003e\u003cp\u003eDissent regarding several other characteristics may be attributed to variability in the implementation of local healthcare systems and organisational structures. For example, the three potential initial points of contact \u0026mdash; community healthcare staff, nursing homes and ambulance services \u0026mdash; were introduced based on participant feedback, but consensus was not achieved and they were rated as relatively unimportant. This likely reflects differences in how HaH care is provided and initiated across regions. A similar pattern emerged in the reimbursement dimension. The characteristics 'bundled payments', 'outpatient-based reimbursement model' and 'community-based reimbursement model' also failed to reach consensus, suggesting that these reimbursement models may not be equally relevant or feasible in different healthcare contexts. Further, while in the literature three operational models were identified, only half of the participants considered the operational models \u0026lsquo;insurance driven\u0026rsquo; and \u0026lsquo;third-party provider managed\u0026rsquo; relevant. These findings highlight the impact of national policies and funding mechanisms on the perceived importance and applicability of specific HaH components.\u003c/p\u003e\u003cp\u003eDifferences in the application of HaH care model originate from differing interpretations. While the original taxonomy had a broader scope, including post-acute or chronic disease management, most participants defined it strictly in terms of acute medical care, leading to disagreement. Similarly, no consensus was reached on patient-facing technologies (e.g. digital tools, data management or devices for patients/caregivers), possibly due to professional bias among the panel or limited real-world adoption, as noted in prior research (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In contrast, technology for healthcare professionals was met with clearer agreement.\u003c/p\u003e\u003cp\u003eConsensus was reached on ten patient selection criteria, but not on the three that were newly added. While these are important, they may not be universally applicable: for example, shared language is crucial in multilingual regions, and caregiver skills vary depending on the HaH model. No agreement was reached on three technologies intended for use by patients or caregivers: digital health tools, data management tools, and devices. In contrast, the five agreed technology criteria focused on the needs of healthcare professionals. This may reflect the provider-centric perspective of our panel and the limited adoption of patient-facing technology in current HaH settings \u0026mdash; an issue also noted in our previous review. Pandit et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) highlight the potential of digital tools such as wearables for HaH care, but also point out barriers such as a lack of tailored design, weak data algorithms and poor electronic health record (EHR) integration.\u003c/p\u003e\u003cp\u003eConsensus was reached on ten patient selection criteria, but not on the three that were newly added. These criteria, which include factors such as shared language with the care team and the skills of informal caregivers, may not be universally applicable, as their relevance depends on local healthcare contexts and the specific design of HaH models. It is likely that such context-specific factors contributed to the lack of agreement.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Strengths and limitations of this study\u003c/h2\u003e\u003cp\u003eOur Delphi study concluded after three rounds, with dissent on 27 characteristics. Further rounds might have achieved consensus, but we prioritized avoiding participant attrition due to their limited availability. Expert selection was unsystematic, conducted by a single author, and despite efforts to include global representation, no participants from Asia, South America, or Africa joined\u0026mdash;possibly due to underdeveloped or differently conceptualized HaH models in those regions. Most experts had health science backgrounds, introducing potential bias, though this aligns with the original taxonomy\u0026rsquo;s scientific focus. Despite modest participation (20 in Round 1, 16 thereafter), outreach to international organizations suggests reasonable representativeness. Future validation could involve larger expert panels at forums like the World Hospital at Home Congress.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThe provided taxonomy can be used as checklist when new HaH care programs are developed to ensure key components are considered and reflected (e.g., patient eligibility, clinical services, technology use). For example, the patient selection criteria in the taxonomy help not to miss important aspects. Existing HaH care programs can benchmark themselves against the taxonomy to identify gaps or areas for improvement. The list of outcome metrics provides guidance on quality metrics useful for measuring effectiveness of care model implementations.\u003c/p\u003e\u003cp\u003e The taxonomy can be used by policymakers and payers to understand the structural and operational elements of HaH programs, which will aid the development of targeted reimbursement models and regulatory guidelines. Future work could study whether these aspects should gain more practical relevance. The role of patient-facing technology in HaH care models requires still research and implementation into practice.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCREDES\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConducting and REporting DElphi Studies\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHaH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHospital at home\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInterquartile range\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch3\u003eAcknowledgements\u003c/h3\u003e\n\u003cp\u003eWe acknowledge the Delphi panel members for participating in the Delphi study and providing their expertise.\u003c/p\u003e\n\u003ch3\u003eAuthor\u0026rsquo;s contribution\u003c/h3\u003e\n\u003cp\u003eKD: Conceptualization, Setting up the study, Paper initial draft, Panel member acquisition, Paper finalization\u003c/p\u003e\n\u003cp\u003eORR: Statistics, Testing of the questionnaire, Paper initial draft, Paper finalization\u003c/p\u003e\n\u003ch3\u003eFunding\u003c/h3\u003e\n\u003cp\u003eNo funding supported this research.\u003c/p\u003e\n\u003ch3\u003eData availability\u003c/h3\u003e\n\u003cp\u003eNot applicable. \u0026nbsp;\u003c/p\u003e\n\u003ch4\u003eEthics approval and consent to participate\u003c/h4\u003e\n\u003cp\u003eAll participants consented to the anonymous analysis of their judgements. The study was conducted in compliance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eA clarification of responsibility was submitted to and approved by the cantonal ethics committee of Bern (Req-2025-00019). They confirmed that no ethics approval is required for the study.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eConsent for publication\u003c/h3\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch4\u003eCompeting interests\u003c/h4\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWhat is Hospital at Home? [Internet]. World Hospital at Home Community. 2024. Available from: https://whahc-community.kenes.com/mod/page/view.php?id=1042\u003c/li\u003e\n \u003cli\u003eShepperd S, Doll H, Angus RM, Clarke MJ, Iliffe S, Kalra L, et al. Avoiding hospital admission through provision of hospital care at home: a systematic review and meta-analysis of individual patient data. CMAJ Can Med Assoc J J Assoc Medicale Can. 2009 Jan 20;180(2):175\u0026ndash;82.\u003c/li\u003e\n \u003cli\u003eLeff B, Burton L, Mader SL, Naughton B, Burl J, Inouye SK, et al. Hospital at home: feasibility and outcomes of a program to provide hospital-level care at home for acutely ill older patients. Ann Intern Med. 2005 Dec 6;143(11):798\u0026ndash;808.\u003c/li\u003e\n \u003cli\u003eShepperd S, Iliffe S, Doll HA, Clarke MJ, Kalra L, Wilson AD, et al. Admission avoidance hospital at home. Cochrane Database Syst Rev. 2016 Sep 1;9(9):CD007491.\u003c/li\u003e\n \u003cli\u003eEdgar K, Iliffe S, Doll HA, Clarke MJ, Gon\u0026ccedil;alves-Bradley DC, Wong E, et al. Admission avoidance hospital at home. Cochrane Database Syst Rev. 2024 Mar 5;3(3):CD007491.\u003c/li\u003e\n \u003cli\u003eDenecke K. Mapping the landscape of Hospital at home (HaH) care: a validated taxonomy for HaH care model classification. BMC Health Serv Res. 2025 Jan 15;25(1):84.\u003c/li\u003e\n \u003cli\u003eAapro M, Bossi P, Dasari A, Fallowfield L, Gasc\u0026oacute;n P, Geller M, et al. Digital health for optimal supportive care in oncology: benefits, limits, and future perspectives. Support Care Cancer Off J Multinatl Assoc Support Care Cancer. 2020 Oct;28(10):4589\u0026ndash;612.\u003c/li\u003e\n \u003cli\u003eZysman M, Creisson A, Ghrenassia G, Nisse-Durgeat S, Boyer A, Matranga M, et al. Employing Digital Health for the Follow-up and Monitoring of Patients Undergoing Anticancer Treatment: First Results of Satelia\u0026reg;Onco on Patient Satisfaction and Recommendations of Use in France. Clin Oncol R Coll Radiol G B. 2025 Apr 26;43:103856.\u003c/li\u003e\n \u003cli\u003eXu S, Kantarcigil C, Rangwala R, Nellis A, San Chun K, Richards D, et al. Digital health technology for Parkinson\u0026rsquo;s disease with comprehensive monitoring and artificial intelligence-enabled haptic biofeedback for bulbar dysfunction. J Park Dis. 2025 Apr 4;1877718X251329354.\u003c/li\u003e\n \u003cli\u003eLim R, Boord M, Soriano J, Bilton R, Roughead EE. Monitoring the effects of medications in residential aged care (nursing home) using digital health technologies: insights from the ReMInDAR and ADEPT projects. Age Ageing. 2025 Mar 3;54(3):afaf019.\u003c/li\u003e\n \u003cli\u003eLeff B, DeCherrie LV, Montalto M, Levine DM. A research agenda for hospital at home. J Am Geriatr Soc. 2022 Apr;70(4):1060\u0026ndash;9.\u003c/li\u003e\n \u003cli\u003eDenecke K, May R, Borycki EM, Kushniruk AW. Digital health as an enabler for hospital@home: A rising trend or just a vision? Front Public Health. 2023 Feb 17;11:1137798.\u003c/li\u003e\n \u003cli\u003eMcKenna HP. The Delphi technique: a worthwhile research approach for nursing? J Adv Nurs. 1994 Jun;19(6):1221\u0026ndash;5.\u003c/li\u003e\n \u003cli\u003eHsu CC, Sandford BA. The Delphi Technique: Making Sense of Consensus. [cited 2023 Aug 24]; Available from: https://scholarworks.umass.edu/pare/vol12/iss1/10/\u003c/li\u003e\n \u003cli\u003eHasson F, Keeney S, McKenna H. Research guidelines for the Delphi survey technique. J Adv Nurs. 2000 Oct;32(4):1008\u0026ndash;15.\u003c/li\u003e\n \u003cli\u003eJ\u0026uuml;nger S, Payne SA, Brine J, Radbruch L, Brearley SG. Guidance on Conducting and REporting DElphi Studies (CREDES) in palliative care: Recommendations based on a methodological systematic review. Palliat Med. 2017 Sep;31(8):684\u0026ndash;706.\u003c/li\u003e\n \u003cli\u003eBeech B. Studying the future: a Delphi survey of how multi‐disciplinary clinical staff view the likely development of two community mental health centres over the course of the next two years. J Adv Nurs. 1997 Feb;25(2):331\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003eGreen B, Jones M, Hughes D, Williams A. Applying the Delphi technique in a study of GPs\u0026rsquo; information requirements. Health Soc Care Community. 1999 May;7(3):198\u0026ndash;205.\u003c/li\u003e\n \u003cli\u003eProcter S, Hunt M. Using the Delphi survey technique to develop a professional definition of nursing for analysing nursing workload. J Adv Nurs. 1994 May;19(5):1003\u0026ndash;14.\u003c/li\u003e\n \u003cli\u003eArgyrous G. Statistics for research: with a guide to SPSS. 3rd ed. Los Angeles: SAGE; 2011. 585 p.\u003c/li\u003e\n \u003cli\u003evon der Gracht HA. Consensus measurement in Delphi studies. Technol Forecast Soc Change. 2012 Oct;79(8):1525\u0026ndash;36.\u003c/li\u003e\n \u003cli\u003eDe Vet E. Determinants of forward stage transitions: a Delphi study. Health Educ Res. 2004 Jul 14;20(2):195\u0026ndash;205.\u003c/li\u003e\n \u003cli\u003eSeagle DE. CHARACTERISTICS OF THE TURFGRASS INDUSTRY IN 2020: A DELPHI STUDY WITH IMPLICATIONS FOR AGRICULTURAL EDUCATION PROGRAMS. J South Agric Educ Res. 2002;(52):1\u0026ndash;13.\u003c/li\u003e\n \u003cli\u003eBenjumea J, Ropero J, Dorronzoro-Zubiete E, Rivera-Romero O, Carrasco A. A Proposal for a Robust Validated Weighted General Data Protection Regulation-Based Scale to Assess the Quality of Privacy Policies of Mobile Health Applications: An eDelphi Study. Methods Inf Med. 2023 Dec;62(5\u0026ndash;06):154\u0026ndash;64.\u003c/li\u003e\n \u003cli\u003eDenecke K, Romero OR, Petersen C, Benham-Hutchins M, Cabrer M, Davies S, et al. Defining and Scoping Participatory Health Informatics: An eDelphi Study. Methods Inf Med. 2023 Sep;62(03/04):090\u0026ndash;9.\u003c/li\u003e\n \u003cli\u003eNikmanesh P, Arabloo J, Gorji HA. Dimensions and components of hospital-at-home care: a systematic review. BMC Health Serv Res. 2024 Nov 25;24(1):1458.\u003c/li\u003e\n \u003cli\u003ePandit JA, Pawelek JB, Leff B, Topol EJ. The hospital at home in the USA: current status and future prospects. NPJ Digit Med. 2024 Feb 27;7(1):48.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Hospital at home, care model, taxonomy, validation, delphi study","lastPublishedDoi":"10.21203/rs.3.rs-6968513/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6968513/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHospital at home (HaH) is a model of acute healthcare that delivers hospital-level medical, nursing, and allied health services to patients in their own homes as a substitute for traditional hospital admission. \u0026nbsp;The aim of this adapted Delphi study was to collect researcher’s opinions on a taxonomy for HaH care models.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe invited researchers with experience in HaH care to judge the relevance of items of a HaH taxonomy developed in previous work. In all three rounds, the participants scored the relevance of the characteristics regarding describing HaH care models on a 5-item Likert scale. Free text comments could be provided to each characteristic in all three rounds.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwenty persons joined the first round and sixteen persisted to the final round. 63 characteristics out of 90 achieved consent of which 27 obtained a strong agreement. The final taxonomy comprises 60 characteristics for 11 dimensions which in turn are aggregated into 5 perspectives. The results indicate that experts largely agree on metrics. Consensus is broad for many characteristics related to clinical characteristics. Patient-facing technology and also ecological sustainability as outcome seem to be less relevant currently.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe provided taxonomy can be used as checklist when new HaH care programs are developed to ensure key components are considered and reflected (e.g., patient eligibility, clinical services, technology use). It can be used as starting point for developing new HaH care models or updating existing ones. It provides also guidance for quality assessment.\u003c/p\u003e","manuscriptTitle":"Validating a taxonomy of hospital at home (HaH) care models: An eDelphi study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-18 13:19:23","doi":"10.21203/rs.3.rs-6968513/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-10T17:47:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-04T12:14:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-12T15:25:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-06T21:25:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-31T10:23:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"232244061241599709343490738724220930495","date":"2025-10-23T08:06:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"168420338325480196214281650788056700526","date":"2025-10-21T13:01:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"248688676222629257404398596745807651706","date":"2025-10-20T17:34:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"131287625098424142218487453452597164853","date":"2025-10-20T14:45:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"67498943968199062219714611355006723774","date":"2025-09-14T23:42:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76724624991166384157259301647829379427","date":"2025-09-10T19:19:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60500352091634204939859864634837923752","date":"2025-08-15T08:28:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-14T10:42:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-05T20:41:29+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-01T02:24:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-27T21:15:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2025-06-27T21:13:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b05bf8b4-80f0-4760-b198-e841db4b2d8a","owner":[],"postedDate":"July 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-22T15:08:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-18 13:19:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6968513","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6968513","identity":"rs-6968513","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}