Towards an information-centric architecture framework for health information logistics: a design science research study

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However, patients with multimorbidity navigate complex, circular pathways, creating information fragmentation that compromises safety and efficiency. Current Health Information Systems often lack robust frameworks for inter-organizational Data Management (DM). This study aims to design a conceptual information architecture framework to resolve systemic gaps in awareness, access, and the integration of the patient’s voice. Methods: Applying Design Science Research (DSR), this study synthesizes rigor from a scoping review with relevance from a longitudinal analysis of 14 multimorbid patients (1954–2024). A representative 19-year user scenario was validated by clinical expertise, and along with root-cause and stakeholder analysis, systemic failures in information logistics were explicated. High-level functional and non-functional requirements were iteratively derived, foregrounding Information Governance (IG), DM, and Security and Privacy as essential constraints. Results: The resulting artifact is a prescriptive information-centric architecture framework (meta-artifact). The layered, modular design decouples metadata, clinical codes, and location pointers into lightweight information tokens, enabling a paradigm shift from physical record replication to governed virtual access. This structure separates concerns across user interaction, pathway logic, and secure storage, providing the structural flexibility required for complex inter-organizational DM. Critically, Health Information Quality (HIQ) is positioned as the functional mechanism to operationalize DM, enforcing structural imperatives (R6–R7) for data accuracy, currency, and contextual relevance. These mechanisms directly mitigate empirically identified failures such as data duplication (F1, F2) and coordination delays (F4). Conceptual feasibility was demonstrated through an acute care transition and discharge use case. Conclusions: This study contributes reusable prescriptive design knowledge, validating the utility of architectural frameworks in solving socio-technical information logistics problems. By embedding Security and Privacy, and IG and DM as authoritative vertical pillars, and operationalizing DM through HIQ, the architecture facilitates high-quality information assets to support inter-organizational information logistics, data-driven opportunities, proactive awareness, and on-demand virtual access, while sustaining interprofessional trust and collaboration. The standards- and vendor-neutral design ensures international relevance and accommodates emerging technologies, such as blockchain and AI. This framework provides a verifiable blueprint in which clinical reasoning and patient-centric pathways guide information logistics. Integrated Care Health Information Exchange Health Informatics Electronic Health Records Interoperability Information Governance Data Management Health Information Quality eHealth Design Science Research Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Accessible and usable health information at the point of care, often referred to as information logistics, is essential for safe, high-quality, and integrated healthcare [ 1 , 2 ]. Despite this necessity, a persistent gap remains between the logistics required by practice and what current Health Information Systems (HIS) and Electronic Health Records (EHRs), primarily optimized for documentation, actually provide [ 3 – 5 ]. This gap has widened by the shift toward specialized care and against the growing mandate for patient-centric coordination, driving patient mobility across providers and care levels [ 4 , 6 – 8 ]. The complexity is particularly salient for the growing population of multimorbid patients (individuals suffering from multiple diseases) [ 9 ], who follow complex, circular pathways and require continuous, integrated information flows [ 4 ]. This fragmentation translates directly into critical data management challenges: missing or delayed critical information increases uncertainty in decision-making, shifts information-seeking and requesting burden onto clinicians and patients [ 1 , 2 , 10 ], and contributes to costly duplicate testing [ 11 ]. To support coordination and patient safety in such complex, situated environments, a sociotechnical design perspective and robust data management that enables contextual, inter-organizational access through information networks, following patients along their pathway is indispensable [ 2 , 3 , 12 , 13 ]. Against this backdrop, the Valkyrie research project was initiated to design an architecture and develop a technical prototype that enables clinicians and patients to have virtual access to distributed patient records [ 14 , 15 ]. In this context, virtual access refers to embedded functionality that enables on-demand views of distributed patient records, contextually relevant to the current stage of the patient’s pathway, without any physical replication or exchange of complete patient records. An initial scoping review systematically examined existing approaches to inter-organizational EHR access and identified six distinct methods [ 16 ]. Crucially, the review found that existing designs consistently failed to meet the Valkyrie requirements for pathway-driven, cross-level access without duplicating patient records. Designs were often ad hoc or solely technology-driven rather than requirements-driven. The review established that Health Information Quality (HIQ), encompassing dimensions like accuracy, currency, and completeness [ 17 ], emerged as the leading facilitator for success, while poor information quality and a lack of trust constituted major systemic barriers. Addressing these fundamental challenges requires a systematic information architecture framework. The need for integrated information is particularly salient for complex patient groups, such as individuals with multimorbidity and mental health conditions, which are rising steadily, and who frequently undergo concurrent treatments and depend on continuous, inter-organizational information flows [ 15 , 18 ]. This complexity is compounded by the nature of clinical practice itself, which is inherently situated, with coordination and communication via rich social networks across a fragmented geographical and organizational landscape [ 19 , 20 ], and characterized by uncertainty in individual patient responses to symptoms, diagnoses, and interventions, and challenges of integrating their perspectives and needs into care decision-making [ 19 , 21 – 25 ]. Furthermore, health information architectures are shaped by specific contextual factors [ 26 ], including the Norwegian healthcare system's organization, which requires complex coordination between centralized specialist care and decentralized primary care. In Norway, Urgent Care (UC), General Practitioner (GP), and Community Nursing Service (CNS) are organized under 357 municipalities, with GPs and UC units acting as gatekeepers to specialized services [ 27 ]. Specialized care is organized under four state-owned regional health authorities. Despite Coordination Reforms aimed at strengthening integration and improving information logistics [ 28 – 30 ], different patient-facing services, such as the national portal “Helse Norge”, and international efforts increasingly emphasizing data integration through standards such as Health Level Seven (HL7), Fast Healthcare Interoperability Resources (FHIR), openEHR, Integrating the Healthcare Enterprise (IHE), the International Organization for Standardization (ISO) - ISO 13606, and ISO 13940 (ContSys), the continued information fragmentation for clinicians and limited abilities for patients to share their voices across heterogeneous EHR platforms persists in this context [ 23 , 31 – 33 ]. This underscores the urgent need for accessible information networks that follow the patient along their pathway, enabling virtual access to context-relevant pathway data without replicating records. To systematically manage this dynamic socio-technical complexity, architectures must serve as systematic tools for design, component structuring, clinical and patient integration, and embedding governing principles to reduce complexity and guide organizational improvements [ 19 , 26 , 34 , 35 ]. This conceptual framework is therefore designed with modularity, layered patterns, and explicit interfaces to reduce structural complexity and limit interdependencies [ 36 – 38 ] [ 39 ] [ 40 ]. Crucially, in response to the high-stakes environment and pervasive trust issues [ 16 ], we foreground Data Management (DM) [ 41 ] and Information Governance (IG) [ 42 ], as authoritative, vertical pillars that prescribe the non-functional constraints, alongside HIQ [ 17 ], essential for sustaining trust and reliability [ 16 , 17 , 36 , 43 ]. In accordance with the Design Science Research (DSR) methodology, this paper aims to design a conceptual information architecture framework as prescriptive design knowledge (meta-artifact), rigorously grounded in inter-organizational information requirements, intended to guide future design iterations for relevance to practice and contribute to reusable knowledge to the scientific communities. To this end, the research provides three critical contributions: first, it formalizes a theoretical paradigm shift from application-centric to information-centric architecture by decoupling information assets through metadata-centric tokens to enable long-term DM flexibility; second, it operationalizes inter-organizational DM through HIQ structural imperatives, directly mitigating systemic failures such as data duplication and coordination delays; and third, it establishes an architectural foundation to support the full spectrum of clinical reasoning, bridging the gap between intuitive pattern recognition and analytical hypothesis testing within context-aware pathway views. Ultimately, the study presents a verifiable "TO-BE" blueprint for inter-organizational logistics that accommodates emerging technologies, such as blockchain and Artificial Intelligence (AI), while strictly preserving organizational autonomy and interprofessional trust. Methods We follow the DSR paradigm to construct and evaluate an artifact that advances both practice and scientific knowledge [ 44 ]. This study's central outcome is the development of a conceptual information architecture framework, classified as a distinct meta-artifact, intended explicitly as prescriptive design knowledge [ 45 – 48 ]. Following Hevner’s three-cycle view (Fig. 1 ) [ 48 ], the Rigor Cycle explicitly draws upon a robust knowledge base, including domain expertise, the preceding scoping review, and the extant literature, with output as design products and processes (Meta-artifacts). The Design Cycle connects the Environment and guides the iterative formulation of the conceptual framework, which serves the Relevance Cycle by providing a systematic solution for the defined problem in inter-organizational health information logistics. This study applies the DSR method framework, consisting of problem definition, requirements definition, artifact design and development, demonstration, and evaluation [ 45 ]. Due to the conceptual nature of the artifact, evaluation activities primarily focused on justifying the problem statement (EVAL 1) and verifying the validity and consistency of the design decisions (EVAL 2) against established principles [ 49 ]. Problem Definition The problem definition involved triangulating existing literature, authors’ expertise, and an empirical analysis of 14 multimorbid patients’ longitudinal clinical encounters (spanning 1954–2024) across primary and specialist care in Northern Norway. This mixed population of 8 females (3 living and 5 dead) and 6 males (1 living and 5 dead), as reported by the participating clinician, enabled comparative analysis across the healthcare system, focusing on patterns of information logistics challenges. The 10 dead patients were randomly selected among 70 patients with documented mental and physical conditions. Records used in the analysis were anonymized in accordance with ethical guidelines. Analysis of these encounters revealed recurring patterns of information logistics challenges, including significant data duplication (F1, F2), delays (F4), and compartmentalization of patient voice (F6) (Table 1 ). A single-patient scenario spanning 2005–2024 was selected and validated with the participating clinician as a representative case to illustrate these systematic failures in DG, DM, and HIQ (Fig. 2 and Fig. 3 ). Stakeholders were identified (Table 2 ) using an iterative approach [ 50 ], an Actor-linkage matrix [ 51 ] was developed based on the case to map interactions and information flow intensity (Table 3 ), and a root-cause analysis (Fig. 4 ) was conducted to unpack the underlying origins of fragmented logistics, confirming a pervasive lack of awareness and access. Requirements and Designed Artifact High-level requirements were iteratively formulated by synthesizing the problem definition, Valkyrie principles, and the scoping review findings. The conceptual architecture framework (Fig. 5 ) outlines the necessary structure, detailing Security and Privacy and IG and DM as authoritative vertical pillars. This outline serves as the prescriptive foundation, guiding the translation of abstract problems into non-functional requirements, encompassing structural (layered, modularity principles) (Table 5 ) and environmental (IG, DM, HIQ constraints and enablers) (Table 4 ) [ 45 ]. Functional requirements were defined subsequently (Table 6 ), by expanding the outline and drawing on the information logistics architecture framework (Fig. 6 ), specifying system interaction categorized into Security and Privacy (R1–R3), Awareness and Accessibility (R4–R5), and Health Information Quality (HIQ) (R6–R7). The functional requirements explicitly address the barriers identified in the preceding scoping review (e.g., trust, poor HIQ) by mandating design features like access logs (R1) and robust data quality controls (R6, R7) [ 16 ]. Demonstration and Evaluation A use case was constructed based on a hospitalization and discharge scenario to demonstrate the conceptual feasibility-in-principle of the designed architecture framework (Fig. 7 ). This demonstration illustrates the system's functions in future state scenarios, focusing on successful interactions (Table 7 ). The conceptual nature of this early-stage artifact dictated an ex-ante evaluation [ 49 ]. This involved a formative, conceptual assessment comparing the framework against the defined problem, requirements, and existing approaches identified in the scoping review. EVAL 1 justified the relevance and practical importance of the problem, and EVAL 2 confirmed the validity and consistency of the conceptual and logical design prior to prototype development. Results This section contains the problem definition, including the user scenario (case), the requirements definitions, and the use case (demonstration). Problem Definition The problem definition starts with the user scenario, followed by stakeholder identification, information-flow intensity, root causes, and the problem definition. User Scenario – Parallel Clinical Pathways and Convergence The longitudinal user scenario tracks a multimorbid patient’s 19-year pathway (2005–2024), demonstrating interactions across specialist and primary care providers (Figure 2). The full chronology of events and actions is detailed in Supplemental Digital Appendix A. Initially, the patient managed distinct parallel clinical pathways (Cardiovascular, Neurological, Vascular, and Mental Health) until 2022. This complexity intensified significantly at the beginning of 2024, exposing systemic failures in information logistics during an acute care transition and subsequent discharge (Figure 3). This critical convergence of pathways confirmed systematic findings of data duplication (F1, F2), delays in timely information logistics (F4), and the compartmentalization of essential patient input (F6), as detailed in Table 1. The root-cause analysis (Figure 4) reveals that this information fragmentation creates uncertainty in care decisions, risks patient safety, and necessitates time-consuming manual work for clinicians. Table 1 lists the identified problems, confirming systematic challenges in inter-organizational DM. These include frequent instances of data duplication through cutting and pasting (F1) and code reuse (F2), significant delays in timely information logistics (F4), the lack of inter-organizational access (F5), and the compartmentalization of essential patient input (F6), all compromising HIQ. Table 1 Identified problems, assumed causes, problem groups, and possible consequences elicited from the user scenario # Identified problems Assumed causes Problem groups Possible consequences of the problems F1 Cutting and pasting patient data to achieve an overview of the patient’s illness Missing patient summary Data duplication Lowered HIQ Added manual work Uncertainties in clinical decision making F2 Reusing and repeating clinical codes for each new contact Clinical codes are used for different purposes (documentation and reimbursement) Data duplication Lowered HIQ Added manual work Uncertainties as to whether the codes relate to a pathway or a particular episode. F3 Sending messages with reminders and requests for information Missing access to patient records and medication lists Unintended use (Appropriation) Added manual work Need to await responses Uncertainties as to whether all relevant clinicians receive messages. F4 Health information, treatment plans, and medication lists arrive late at the point of care The clinical person responsible is also responsible of informing others. Untimely information logistics Added manual work Need to await responses Uncertainties in clinical decision-making Patients as information carriers F5 Symptoms can indicate both physical and mental health conditions but are not easily shared across clinical domains Missing access to essential information Missing integrated, patient-centric pathway view Can increase redundant work and limit effective examination, diagnoses, and treatment F6 Patients’ individual needs are mostly compartmentalized, and not easily shared There is no common recording and sharing of patient’s voices inter-organizationally. Missing integrated, patient-centric pathway view Missing patients’ voices can affect the treatment quality and progression. Table 2 lists the identified stakeholders followed by a description of the stakeholders. Table 2 Description of the stakeholders identified during the construction of the user scenario Identified stakeholders Description of stakeholders Patient A person who, due to symptoms or illness, becomes a patient and enrolls into the healthcare system. Although categorized as a patient by healthcare and belonging to one or more patient groups, their personal preferences and needs may result in different behaviors to identical treatment and medication options. Next of kin It is the patient’s closest relation, appointed by the patient, and is often a family member. Next of kin has the role of guardian for the patient and may be both informed and participate in decision making concerning the patient. They have broader privileges than relatives, including access to patient records. General Practitioner (GP) Healthcare professionals who specialize in general medicine. GPs are often the first contact point for citizens with symptoms of illness and encounter less severe conditions than specialists at a hospital and can prevent problems from escalating. GPs refer patients to specialists and receive discharge reports (epicrisis) from specialists. Medical physician Specialist doctor at the hospital medical department, examining and treating patients with physical (somatic) conditions. Psychiatrist Specialist doctor working in the psychiatry department at the hospital, diagnosing and treating patients with mental health conditions, such as depression, anxiety, and bipolar disorder. Psychiatrist 2 identified through the user scenario was a specialist in adult psychiatry, especially related to diagnosing dementia. District nurses/ home care nurses Nurses or nursing assistants employed by the municipalities and work in care units for patients at home or at care institutions for shorter or longer stays. Urgent care (UC) Organized under the municipalities offering acute medical services after GP’s closing time. Like the GP, they can refer patients to the hospital. As clinical pathways converged (Figure 3), more stakeholders became involved, interactions increased, and the information flow intensified. Using these insights, an actor-linkage matrix (Table 3) was constructed, showing the GP as the central hub with the highest intensity of information flow, particularly with CNS, and the medical physician. While CNS initiated the flow with the GP, the GP acted as the primary gatekeeper to specialized care. The patient exhibited minimal information flow, primarily as a receiver, reflecting the compartmentalization of the patient’s voice across organizations. In Table 3, blank cells indicate no information flow, while cells with question marks suggest that information flow is likely occurring but is not documented. The stars indicate the occurrence of information flow between stakeholders, with the number of stars representing the information flow intensity. Table 3 Mapping the intensity of the information flow between the identified stakeholders using an Actor-linkage matrix Using the synthesized empirical findings (Table 1) and the derived root-cause analysis (Figure 4), we assert that information fragmentation systematically creates uncertainty in care decisions, elevates patient safety risks, and necessitates substantial time-consuming manual clinician effort to assemble data from multiple sources. The analysis confirms that the information logistics crisis stems fundamentally from two persistent, pervasive system deficiencies: (1) a lack of awareness regarding parallel treatment activities elsewhere, and (2) limited virtual access to distributed patient records. This situation highlights a growing and urgent demand for comprehensive and timely information logistics when complex clinical pathways converge. Accordingly, the problem is defined as: Current patient and clinical integrations suffer from inter-organizational information logistics, which limit awareness of patients’ voices and treatment activities at other providers, and reduce access to distributed patient records. This restricts clinicians’ proactive use of essential health information at the point of care and constrains patients’ ability to share their voices and participate in care decisions. The synthesis of longitudinal patient data with inter-organizational stakeholder mapping confirms that information fragmentation is not merely a technical byproduct but a systemic failure of current health information logistics. The root-cause analysis (Figure 4) identifies a pervasive 'lack of awareness' and 'lack of access' as the primary drivers of clinical uncertainty and manual workload (F1–F6). However, this empirical problem definition also carries a crucial architectural mandate: opening patient records to resolve these gaps inherently introduces socio-technical side effects, specifically the risk of accidental disclosures of sensitive information and the exposure of discrepancies in work routines and documentation practices across organizations. These factors heighten concerns regarding DM, HIQ, security, and privacy. Consequently, successful mitigation requires that the prescriptive architecture framework explicitly operationalize governance and management factors as non-functional constraints, providing the structural foundation necessary to sustain inter-organizational trust and collaboration. Requirements and Framework Building on the empirical problem defined in the previous section, we now transition to the systematic definition of requirements necessary to address fragmentation and support robust information logistics. As posited within the DSR paradigm, the solution artifact, the conceptual information architecture framework, must function as a prescriptive design knowledge (meta-artifact), rigorously guiding the translation of problem constraints derived from the Relevance Cycle into requirement specifications. Conceptual Framework outline and governing pillars To guide this translation, we outline the conceptual information architecture framework (Figure 5), synthesizing core insights from the preceding scoping review and the foundational Valkyrie principles. This conceptual model is structured to integrate the overarching Valkyrie goals with authoritative, vertical pillars. Crucially, addressing the lack of inter-organizational awareness and access inherently heightens concerns about security, privacy, and HIQ, risking the formation of tension and distrust among collaborating stakeholders. Therefore, the framework explicitly prescribes the necessity of Security and Privacy, and IG/DM as non-functional constraints that must be aligned with system-wide standardization initiatives to enable inter-organizational trust and collaboration. Environmental Requirements Building upon the abstract conceptual information architecture framework outlined (Figure 5), we now systematically specify the high-level non-functional requirements that translate the defined problem of information fragmentation into tangible architectural constraints. These requirements dictate the essential contextual boundaries (environmental) constraints and the internal organization (structural) required to govern and realize the solution. Non-functional requirements, being generic and widely applicable, ensure fundamental qualities such as usability, security, and sustained interoperability [45]. Table 4 Description and justification of the inter-organizational high-level non-functional environmental requirements Inter-organizational high-level non-functional environmental requirements Description and justification The system should adhere to Valkyrie’s goal and overarching principles. It is a prerequisite that the artifact is aligned with Valkyrie’s goals and principles, facilitating integrated, patient-centric information logistics [15]. The system should be flexible to adapt to external regulations, standards, and recommendations. Due to the dynamic interplay in healthcare [19, 24, 25] and the differences in funding, priorities, and autonomy among healthcare providers, changes will likely occur across various time scales, requiring a flexible and adaptable system. The system should handle conflicts of interest and HIQ issues through inter-organizational IG. IG can improve normative and functional integration, reducing tension and handling conflicts of interest [43], which can arise when closed systems are opened to outsiders and differences in processes, procedures, and documentation routines are revealed [16]. The system should incorporate existing national infrastructures and components. It is crucial for the system’s overall success and its attractiveness to other healthcare domains and providers that national infrastructure and components are incorporated [11]. The system should ensure security and privacy by design. Ensuring that health information is safe and secure is crucial for patients’ and clinicians’ trust in the healthcare system and each other, and ultimately, the treatment quality [16]. The environmental requirements define the broader contextual constraints, derived from the problem domain and the overall Valkyrie objectives (Figure 5). These requirements (Table 4) prescribe essential socio-technical conditions, such as adherence to existing national infrastructure and external regulations. Specifically, they mandate that the system must proactively handle conflicts of interest and pervasive HIQ issues through rigorous inter-organizational IG, which is crucial when opening traditionally closed systems. The Prescriptive Information Logistics Architecture While the environmental requirements (Table 4) define the external constraints, the detailed conceptual architecture explicitly describes the internal composition and functionality required to solve the core problem. Figure 6 presents the conceptual information logistics architecture, visualizing the rigorous, layered, and modular structure prescribed to operationalize the framework and address the root causes and problem definition identified (lack of awareness and lack of access). The architecture is systematically divided into three horizontal layers, constrained vertically by the authoritative Security and Privacy and IG/DM pillars: Top Layer (Clinician/Patient Interaction): This layer directly addresses the problem of fragmented access and limited awareness by providing user interfaces embedded within existing EHRs and the National Patient Portal, thereby reducing workload by eliminating the need for additional logins. It introduces two key modules that respond directly to the defined problem: Awareness Module: This component delivers contextual notifications regarding a patient’s concurrent treatment activities at other providers. This function is enabled by structured, lightweight information tokens (metadata, clinical codes, location pointers) that are pushed from the underlying EHR systems. This mechanism directly mitigates the "lack of awareness" problem. Filter, Search, and Query Module: This component enables clinicians to actively search, filter, and organize inter-organizational patient records flexibly. This module relies on the Virtual EHR component located in the middle layer to provide read-only views of distributed data, thereby directly solving the "lack of access" problem. Middle Layer (Pathways and Virtual Access): This layer translates the heterogeneous tokens into a cohesive overview. It includes the Patient-centric pathway module, which maps information tokens into coherent pathway models to support coordination and awareness. Crucially, the Virtual EHR within this layer provides the on-demand, read-only views of distributed records necessary for detailed clinical review. Importantly, these components must work contextually together to ensure smooth transitions between the pathway overview and the detailed clinical review, supporting different clinical reasoning processes. Bottom Layer (Secure Storage and Provenance): This layer ensures that the tokens are securely stored and compliant with legal requirements [52], guaranteeing integrity and traceability. This foundational control is vital for reinforcing the IG/DM pillar and sustaining interprofessional trust. This strategic layering, separating concerns across user interaction, pathway logic, and secure storage, facilitates decoupling information from application constraints. This decoupling approach is essential for achieving the necessary long-term DM flexibility, enabling future information organization and reorganization independently from underlying application data models [2, 12, 13]. Structural Requirements The internal organization and design decisions visualized in the conceptual architecture (Figure 6) are formally specified by the structural requirements. These requirements serve as definitive prescriptive constraints to manage complexity and ensure the artifact functions as reusable design knowledge. As formalized in Table 5, the structural constraints are defined to maximize long-term utility: Modularity and Layered Pattern: The requirement for a modular design and layered pattern approach (Table 5) is explicitly mandated to promote the creation of reusable components and ensure ease of system maintenance and flexibility when incorporating internal or external additions. Standards-Neutrality: The prescription to avoid vendor lock-in by supporting open standards and APIs (Table 5) ensures DM flexibility and long-term architectural stability, allowing the framework to support international health information standards (e.g., HL7 FHIR, openEHR) without imposing a single rigid approach. These specified structural requirements confirm the prescriptive nature of the conceptual architecture, rigorously detailing the internal conditions necessary for the artifact to govern information assets and enable complex inter-organizational information logistics. Table 5 Description and justification of the inter-organizational high-level non-functional structural requirements Inter-organizational high-level structural Requirements Description and justification The system architecture should have a modular design and a layered pattern approach. A modular architecture promotes reusable components and can also make the architecture flexible to incorporate new internal or external additions to benefit the healthcare system’s stakeholders. Modularity and layered architectures promote the separation of concerns and ease system maintenance [36, 37, 40]. The system should avoid vendor lock-in by supporting open standards and APIs. Open standards and APIs can help lower entry barriers and empower healthcare providers to change modules or systems without data loss or significant conversion costs [39, 53]. The system should be embedded into local patient record systems/ clinical workflow. By following modularity [38] and virtualization ideas, the system’s user interface should be embedded into existing applications and workflows, which can help reduce the number of user interfaces and logins, and avoid vendor lock-in [53]. The system should protect health information from unauthorized use. The information tokens representing patients’ pathways must be securely stored and be available to authorized clinicians only. This is regulated by the Patient Journal Law §22 [52], and is essential for building trust among stakeholders. The system should offer high availability and accessibility. As a general requirement, the system should provide availability and accessibility that is equal to or greater than that of the distributed patient record systems it depends on, which also affects the system’s load time [16]. The system should support stakeholders in navigating and exploring patient pathway information according to personal preferences. Because of the dynamic and contextual nature of healthcare work [3, 25], clinicians must be offered various methods of navigating the information provided such as filtering, searching, and querying the information, with limited predefined navigation patterns. Structural Requirements Having formalized the non-functional constraints that govern the architecture's environment and internal structure, we now proceed to specify the functional requirements. Functional requirements detail how the envisioned system must interact with its users to rigorously address the identified information fragmentation problem [45]. These requirements translate the architectural pillars and components into tangible system behaviors. The functional requirements (Table 6) are systematically grouped into three core categories reflecting the authoritative vertical pillars of the conceptual framework and the defined problem: Security and Privacy, Awareness and Accessibility, and HIQ. Security and Privacy (R1–R3) The Security and Privacy requirements ensure the technical solution adheres to the legal and professional standards necessary to sustain stakeholder trust when accessing distributed patient records. They mandate transparent audit trails (R1), aligned with laws requiring logging of all clinical access to confidential information [52]. Furthermore, the system must control informed consent (R2), acknowledging the patient’s right to limit access to their confidential information [54, 55]. Operational efficiency is maintained by requiring the reuse of existing organizational authentication and authorization mechanisms (R3) wherever possible, avoiding the introduction of new logins or maintenance overhead [16]. Awareness and Accessibility (R4–R5) These requirements directly operationalize the fundamental issues identified in the root-cause analysis and the problem definition: lack of awareness and lack of access. The system must deliver notifications of parallel treatment activities (R4), ensuring clinicians gain timely awareness of concurrent events and medications. When further details are needed, the system must provide virtual access to distributed patient records (R5), addressing the access gap. Critically, R5 also explicitly mandates the integration of the patient’s voice and preferences, mitigating the empirically observed problem of compartmentalized patient input that affects treatment quality (F6) [23]. Table 6 Description and justification of the inter-organizational high-level functional requirements grouped into Security and privacy, Awareness and accessibility, and Health Information Quality Operationalizing Information Governance and Data Management through HIQ (R6–R7) The requirements concerning HIQ serve as the explicit operationalization of the IG/DM pillars. This enforcement is essential because opening distributed records exposes discrepancies in processes and documentation, risking reduced perceived HIQ and undermining interprofessional trust [16]. The R6 requirement enforces the basic quality dimensions of health data (accuracy, currency, reliability, and completeness) [17]. Its core prescriptive function is to mitigate the data management failures observed in the user scenario: namely, data duplication arising from the cutting and pasting of patient fragments (F1) and the uncritical reuse or repetition of clinical codes (F2). By demanding systematic consistency and accuracy across records, R6 structurally addresses the underlying causes of poor data quality at the point of ingestion and viewing. R7 addresses the contextual dimension of HIQ, requiring that information provided be understandable and useful to authorized personnel when and where needed. This is critical for resolving the acute problem of untimely information logistics (F4), where vital information and treatment plans arrive late, forcing clinicians into time-consuming manual workarounds (F3, F4). R7 ensures the system proactively filters and synthesizes inter-organizational information tokens to deliver context-relevant cues, thereby minimizing cognitive load and enabling the proactive use of essential information, supporting timely clinical decision-making. Use Case To illustrate how the proposed architecture framework operationalizes the defined functional requirements and validates its role as a prescriptive design knowledge (meta-artifact), we present a focused use case (Table 7). This scenario, inspired by the convergence of clinical pathways (Figure 3), demonstrates the system's functional requirements through a sequence of inter-organizational interactions during a critical high-risk event: a patient’s hospitalization and subsequent transfer to community care. The use case aims to prove the artifact’s conceptual feasibility in providing timely awareness and virtual access (R4, R5), while strictly adhering to the mandated vertical pillars of Security and Privacy (R1, R2, R3) and IG/DM (R6, R7). Figure 7 illustrates the interactions, in which Valkyrie Central (VC) is the new component that coordinates information logistics among the hospital’s, GP’s, and CNS units’ distributed EHR systems. The success scenarios S1 through S11 explicitly illustrate how the prescribed architecture manages the dual goals of access and governance, translating the high-level requirements into demonstrable functional flow: Enforcing Accountability and Trust (IG/DM Pillars): Access to patient records, whether through detailed review (S1) or updated status access (S6), is contingent upon the fulfillment of R1 (Access logs/Transparency) and R2 (Informed Consent). The Use Case demonstrates that clinicians cannot retrieve information (S1, S6) until the system confirms consent (S2, S7) and logs all access activities (S4, S9). This rigorous sequencing confirms the necessity of embedding governance mechanisms directly within the information access process to build and maintain inter-organizational trust. Table 7 Use case description and success scenarios of the future system’s inter-organizational virtual information logistics during a patient’s hospitalization and transfer to a community service institution # Use case description Precondition The patient is hospitalized after being sent from the Urgent Department to Hospital Medical in an ambulance, suffering from tubulointerstitial nephritis and sepsis. The GP and the CNS have earlier involvement with the patient and are informed of the patient's hospitalization through a messaging service by the medical physician. Main success scenario S1. During the patient examination, the medical physician requests access to the Virtual EHR to review the patient’s medical history. S2. The system checks the patient’s informed consent with the National Patient Portal. S3. The system grants the medical physician access to patient records at the GP and CNS using local organizational credentials. S4. The system logs the medical physician’s search activity. S5. The system notifies the GP and CNS of the patient’s hospital examination and discharge preparations. S6. The GP and CNS request updates on the patient’s medical and medication status through Virtual EHR before hospital discharge. S7. The system repeats the informed consent check with the National Patient Portal, this time for the GP and CNS. S8. The system grants the GP and responsible nurses at CNS access to view the patient’s medical status and medication list from the hospital’s patient records using local organizational credentials. S9. The system logs the GP and CNS search activities. S10. The system notifies the medical physician about the patient's arrival at the community institution. S11. The system provides the GP and medical physician with access to CNS’s patient records via Virtual EHR. Mitigating Fragmentation through Proactive Logistics: By leveraging lightweight information tokens, VC facilitates timely communication (S5, S10). This immediate, context-aware notification ensures that downstream stakeholders (GP, CNS) can begin discharge planning and resource allocation earlier, directly mitigating the historically observed problem of untimely information logistics (F4) and reducing reliance on messaging workarounds (F3). Operationalizing Health Information Quality (HIQ): The architecture enforces R6 (Accuracy, Consistency, Currency, and Completeness) and R7 (Understandable and Useful Information) by prescribing mechanisms that mitigate the risks associated with information fragmentation (F1, F2, F4). The tokens and Virtual EHR component ensure that clinicians access read-only views of source data via location pointers (S3, S8, S11). This design choice supports data currency and prevents duplication errors (F1, F2) common in replication models. By granting access to the current medication list directly from the hospital EHR (S8), the system ensures accuracy and currency, which is vital for safe transitions of care. The demonstration thus confirms that the layered, modular structure of the conceptual framework structurally supports the functional requirements necessary to resolve the defined problems while adhering to the prescriptive constraints of IG/DM and Security/Privacy. Discussion This study proposes a conceptual information-centric architecture framework for inter-organizational logistics aligned with the Valkyrie principles. Guided by DSR, we progressed from problem definition (user scenario, stakeholder, and root-cause analysis in Fig. 3 -Figure 4, Table 1 ) to high-level non-functional (Table 4 -Table 5) and functional requirements (Table 6 ), guided by the architecture framework (Fig. 5 , Fig. 6 ), and demonstrated the architecture’s feasibility with an illustrative use case (Fig. 7 , Table 7 ). In this section, the architecture framework is evaluated according to the Relevance, Rigor, and Design cycles (Fig. 1 ) explaining how it addresses the defined problem and requirements, its contribution to the scientific community, its benefits, limitations, and future work. Significance and Feasibility of the Problem Definition (EVAL 1) Safe, coordinated, and person-centered care fundamentally depends on resolving the awareness and access gaps that currently fragment inter-organizational information logistics [ 2 , 4 , 56 ]. This research provides the formal EVAL 1 (Problem Justification) by demonstrating that these gaps represent recurrent, systemic failures in HIQ and DM. While the 19-year longitudinal scenario serves as the narrative vehicle, the framework's prescriptive mandate is derived from a broader synthesis of 14 multimorbid patients, which revealed consistent socio-technical failures, including significant data duplication (F1, F2), untimely logistics (F4), and the systemic compartmentalization of the patient’s voice (F6). This approach derives prescriptive authority by systematically linking descriptive knowledge of fragmentation and compromised trust with concrete structural guidelines to resolve these gaps. These empirical findings justify the research need within the Relevance Cycle, proving that existing EHR approaches consistently fail to support pathway-driven access in fragmented landscapes. As multimorbidity continues to rise against a backdrop of strained clinical resources, closing these gaps is both necessary and urgent [ 18 , 57 ]. By grounding the problem in decades of clinical encounters, this work establishes an architectural mandate: the system cannot merely facilitate access but must explicitly operationalize governance and management pillars as non-functional constraints to sustain inter-organizational trust. Validating the Framework as Prescriptive Design Knowledge (EVAL 2) As a prescriptive meta-artifact, the conceptual framework provides a systematic solution by bridging descriptive problem knowledge with concrete structural solution patterns. This section serves as the EVAL 2 (Design Consistency) by verifying that the architectural design decisions are valid and logically aligned with the defined requirements established through the lens of Hevner’s three DSR cycles: Relevance cycle : The root-cause analysis (Fig. 4 ) identified that information fragmentation creates clinical uncertainty and necessitates time-consuming manual assembly of data. The framework addresses these environmental needs by prioritizing awareness and access as primary targets for architectural intervention. By integrating patients’ voices (R5) and addressing social factors such as housing and finances (F6), the framework prescribes a shift beyond technical data exchange to support a holistic, integrated care perspective. This systematic response to empirically observed failures provides a rigorous justification for the artifact’s utility in improving DM practices. Design cycle : The architecture responds with two integrated mechanisms: Awareness and Virtual Access, in which lightweight information tokens (metadata, clinical codes, and location pointers) enable near-real-time notifications (R4), and the Virtual EHR component allows on-demand, read-only views (R5). This validates the structural decision to decouple information from application constraints, facilitating long-term DM flexibility. The Design Cycle confirms that the architectural structure, separating user interaction, pathway logic, and secure storage, is functionally consistent with the need to resolve fragmentation while mitigating the synchronization overhead and security exposure inherent in traditional record replication models. Rigor cycle : The framework’s feasibility is confirmed by its alignment with international standards and agendas, such as the WHO shared EHR mandates and the EU Shared Health Data Space [ 2 , 31 ]. By embedding IG and DM as authoritative vertical pillars, the design translates legal mandates (e.g., audit trails, consent) and HIQ principles into structural imperatives. The Use Case rigorously demonstrated the necessity of embedding these controls; by requiring consent checks (R2) and audit trails (R1) for every access instance (S2, S4, S7, S9), the design ensures accountability and transparency. This confirms that the governance pillars are not merely theoretical ideals, but prescriptive mechanisms essential for operationalizing inter-organizational trust. Theoretical Innovation: Shifting to Information-Centric Logistics The primary contribution of this meta-artifact is the formalization of a paradigm shift from application-centric to information-centric architecture. Existing approaches identified in the scoping review predominantly rely on physical record replication or assume homogeneous data models, both of which struggle with synchronization burdens and technical heterogeneity [ 16 ]. In contrast, this framework introduces module decoupling via interface connections [ 36 – 39 ], which allows information assets, bundled as metadata-centric tokens, to exist and be reorganized independently of the underlying application’s constraints. This theoretical innovation addresses the "lack of awareness" and "lack of access" problems by providing a prescriptive solution pattern for harmonized-on-demand views. By structurally separating the user interface from the pathway logic and secure token storage, the framework provides a goal-oriented "TO-BE" vision essential for achieving long-term DM flexibility. Furthermore, this architecture is designed to support the full spectrum of clinical reasoning, and to enable future data-driven innovations, such as process mining [ 58 ], learning health systems [ 59 , 60 ], and AI [ 61 ], without compromising organizational autonomy or data sovereignty. Consequently, by enabling proactive awareness and governed virtual access, the artifact serves as a distinct form of prescriptive design knowledge, offering a verifiable blueprint where clinical reasoning and patient-centric pathways, rather than technical replication, guide inter-organizational information logistics. Advancing Inter-Organizational Integration and Pathway Efficiency The Use Case (Fig. 7 ) validates the framework’s capacity to support high-risk transitions, such as patient transfers between hospital and community care, by systematically addressing critical information logistics gaps [ 62 , 63 ]. The dual mechanism of proactive notifications (Awareness Module) and on-demand, read-only access (Virtual EHR) facilitates earlier preparation for patient needs, medication reconciliation, and service planning. This efficiency gain stems from reducing dependence on manual information-chasing, messaging workarounds, and phone calls. Furthermore, by making the patient's voice and preferences explicitly visible across organizations (R5), the framework structurally promotes better-informed planning, and addresses social factors, such as housing and financial concerns, that often influence referral and treatment progression. This integrated visibility is vital to correcting the historical imbalance in which information often flows only through key gatekeepers, such as the GP. Operationalizing Information Governance and Data Management Central to the framework's evaluation is demonstrating the effectiveness of the explicit integration of the IG/DM vertical pillar in the design. The architecture moves beyond merely facilitating access to prescribing how that access must be governed through HIQ requirements (R6 and R7) to sustain trustworthiness. The design enforces R6 (Data Quality Constraints) by specifying that access is enabled only through tokens that contain location pointers, ensuring that the data used remains verifiable and current without data replication. Furthermore, the system addresses R7 (Data Context and Relevance) by filtering information through notifications (R4) to minimize cognitive load. This systematic operationalization of IG and DM through HIQ provides the necessary foundation for high-quality information assets. Flexibility for Emerging Technologies By establishing a foundation of HIQ-enforced virtual access, the framework offers the necessary stability for integrating emerging technologies. Each clinical event can generate an encrypted token written to a patient-specific distributed ledger, which strengthens traceability and tamper-resistance for cross-organizational auditability [ 64 ]. Still, it also raises questions about performance, energy use, and AI governance that must be considered during design and evaluation [ 64 , 65 ]. Similarly, AI tools can be employed to aid in information retrieval and contextual notifications, contributing to the interpretation of structured and unstructured documents. However, because the framework enforces strict provenance and HIQ through its vertical pillars, it provides the structural safeguard required to manage the risks of hallucination and bias often associated with pre-trained AI models [ 61 ]. Consequently, this architectural flexibility allows for data-driven innovations, such as process mining and learning health systems,without compromising organizational autonomy or the underlying integrity of the inter-professional trust. Privacy and Access Balance Opening access across organizations requires careful handling of privacy. The framework reduces risk by sharing tokens rather than complete records, checking consent before showing details, and logging who accessed what and when. Transparency for patients through access logs, harmonized consent, and disclosure routines across organizations helps build trust. Lack of trust was one of the main barriers identified in earlier work and can lead to situations in which clinicians do not trust information derived from external sources, including clinicians’ examinations and patients’ recordings [ 16 , 31 ]. In addition, the pathway view is designed with context awareness to show only what is necessary for the current task, thereby limiting exposure to unrelated information. Stakeholder Dynamics and Pathway Complexity Stakeholder identification in the broader sample revealed additional actors beyond those in Table 2 (e.g., social welfare services, police, prison health services). No pathway coordinator was present in the user scenario, though pathways for mental health and substance abuse began in 2019 [ 66 ]. This underscores the dynamic nature of stakeholder roles and boundaries in inter-organizational contexts [ 50 ] and shows that fixed arrangements and static handoffs are inadequate, especially for multimorbid patients with unpredictable, circular pathways, as illustrated in the user scenario. Anticipated future influential stakeholders include security and information governance and data management experts (e.g., super users, HIQ experts, data stewards, information architects), system vendors, and ICT services at hospitals, regions, and national. Additionally, nurses, health secretaries, and pathway coordinators are expected to become more visible due to their significant roles in integrated care. By focusing on patient-centric pathways rather than clinical pathways within organizational boundaries, the framework remains flexible when new actors join or leave the process. The user scenario and actor-linkage matrix (Table 3 ) also show how information tends to flow through the GP, while the sharing of patients’ voices is often limited. Making the patient’s inputs visible throughout the pathway, in both directions, can help reduce the current imbalance. Limitations The findings of this study are situated within the Norwegian context and represent an early-stage conceptual meta-artifact, necessitating reliance on ex-ante evaluations (EVAL 1 and EVAL 2) to justify the problem and verify design consistency. While the 19-year longitudinal scenario serves as the primary narrative vehicle, it is a representative synthetic case validated by clinical expertise to embody the systemic failures observed in the broader data. The empirical foundation of this study is a synthesized analysis of 14 multimorbid patients, which revealed recurring patterns of informational fragmentation, specifically data duplication (F1, F2), logistics delays (F4), and the compartmentalization of the patient’s voice (F6). Nevertheless, this convenience-based sample cannot represent the exhaustive diversity of multimorbid pathways or the high variability of documentation practices across medical specialties. Furthermore, technical risks, including latency and source system downtime, and organizational risks, such as inconsistent local governance and variations in informed consent handling, may affect the framework's reliability when scaled. Consequently, further DSR iterations and longitudinal human-centric evaluations are required to assess the framework's generalizability and impact on cognitive workload across heterogeneous inter-organizational settings. Although the design aims for international relevance through standards-based interfaces, layered modularity, and vendor-neutral principles, adaptation to other contexts will require alignment with local governance structures, infrastructure capabilities, and legal frameworks. This includes harmonizing privacy regulations, consent models, and interoperability standards. Multiple researchers from clinical, sociological, and technical fields participated in data extraction, analysis, and validation, thereby strengthening the study and reducing individual bias. However, the absence of broader stakeholder involvement – such as patients, nurses, and external actors – at this stage limits the completeness of the requirements and evaluation needed in future iterations. Ethical and social risks also require attention. While many aspects are legally regulated, grey areas may emerge during design, such as balancing transparency with professional discretion or managing conflicting interpretations of consent. Empowering patients with access and insight into their own medical history and status aligns with national ambitions but introduces some trade-offs. For example, preventing another clinician from mentioning sensitive results during a parallel activity before the patient has had a direct consultation remains challenging in an inter-organizational setting. Additionally, some patients, particularly those with mental health conditions or substance use disorders, may struggle to manage sensitive information securely due to impaired judgment or situational vulnerability. Future iterations are expected to generate more knowledge about these risks and their consequences. Scalability and emerging technologies pose further limitations. Blockchain-based token storage and AI-assisted data processing may improve security and efficiency but introduce challenges related to performance, energy use, governance, and explainability. These technologies require careful evaluation before integration to avoid unintended complexity or inequities in access. However, technology alone cannot resolve the complexity of information logistics in integrated care. Building and maintaining trust inter-organizationally depends on evolving security and privacy mechanisms, sustaining HIQ, collaboration among professionals, strengthening DM and IG inter-organizationally, and involving stakeholders in design, testing, and evaluation to advance knowledge and mitigate risk [ 16 ]. Future Research Directions To advance the utility of this prescriptive framework and facilitate its transition from a conceptual architecture to technical instantiation, future research should prioritize the following dimensions: Inter-organizational IG/DM and behavioral complexity: Future studies must investigate the specific organizational and technical configurations required to implement inter-organizational IG/DM frameworks at scale. A critical focus should be placed on how these governance structures can systematically reduce behavioral complexity—the socio-technical friction arising from inconsistent documentation routines, varying professional standards, and lack of inter-organizational trust. Research should explore how technical mechanisms mandated by the framework (e.g., tokens and audit trails) can be aligned with social incentives to empower clinicians and data stewards to maintain HIQ locally. Component prototyping for clinical reasoning: Building on the framework’s middle layer, research is needed to design and develop specific components capable of supporting the full spectrum of clinical reasoning. This includes exploring how semantic enrichment and advanced filtering can facilitate rapid, intuitive pattern recognition and support analytical, deductive testing with detailed virtual views. Governance of intelligent information access: As the framework supports the integration of emerging technologies, future work should examine how data-driven methods, such as AI-assisted summarization or semantic mapping, can work together with context-awareness and virtual access. These investigations must remain grounded in the framework’s pillars to ensure that any assisted synthesis maintains strict security and privacy and adheres to FATE principles (Fairness, Accountability, Transparency, and Ethics). Longitudinal Human-Centric Evaluation: Critical next steps involve evaluating the framework’s impact on real-world clinical and patient integration through interactive prototypes. These assessments should prioritize human-centered metrics, such as cognitive workload reduction and time-to-answer, and explore how the patient’s voice and preferences can be more robustly integrated into the shared inter-organizational pathway. The Valkyrie project is working on further artifact iterations and will report on this work in future papers. Conclusions This research addressed the persistent challenges of inter-organizational information logistics by designing and evaluating a conceptual information architecture framework that functions as a prescriptive meta-artifact. Grounded in a longitudinal empirical analysis of multimorbid patient encounters, the framework provides a rigorous foundation for bridging fragmented EHR landscapes without relying on the inherent risks and synchronization overhead of full record replication. The primary contribution of this work is three-fold. First, it formalizes a theoretical shift from application-centric to information-centric architecture, decoupling information assets through metadata-centric tokens to ensure long-term DM flexibility. Second, it operationalizes DM through HIQ structural imperatives, providing a concrete mechanism to mitigate empirically identified failures such as data duplication and coordination delays. Finally, it establishes a foundation for the full spectrum of clinical reasoning, bridging the gap between intuitive pattern recognition and analytical hypothesis testing within context-aware pathway views. Ultimately, this study contributes a goal-oriented 'TO-BE' vision to the DSR knowledge base. It provides a verifiable blueprint that aligns emerging technical innovations, such as AI and blockchain, with the complex socio-technical mandates of modern, patient-centric healthcare delivery, while strictly preserving inter-professional trust and organizational autonomy. Abbreviations AI Artificial Intelligence CNS Community Nursing Service DSR Design Science Research EHR Electronic Health Records FHIR Fast Healthcare Interoperability Resources GP General Practitioner HIQ Health Information Quality HIS Health Information Systems HL7 Health Level Seven IG Information Governance IHE Integrating the Healthcare Enterprise ISO The International Organization for Standardization UC Urgent Care Declarations Ethics Approval All procedures were conducted under ethical guidelines and regulations, with approvals obtained from the relevant institutional review boards: Nordland Hospital Trust, University Hospital of North Norway, and Bodø Municipality (consent 02985, 2022); The National Archives of Norway (consent H-142, 2023); and the Norwegian Directorate for E-health (2024). Data from deceased patients were handled in compliance with national regulations regarding posthumous medical records. For living patients, written informed consent was obtained before accessing their records, and they were informed of their right to withdraw from the study at any time without consequences. The data was de-identified by a clinician and stored anonymously and securely to maintain confidentiality throughout the study. Consent for publication The authors and the responsible institutional authorities approve the publication of this work and confirm that it has not been previously published and is not under consideration elsewhere. Availability of data and materials The detailed scenario description is available as a supplement to this manuscript. However, the data used to construct the scenario cannot be shared due to its sensitive nature and the strict privacy regulations governing patient records in Norway. Competing Interest The authors declare that they have no competing interests Funding This work is part of the Valkyrie project, funded by the Research Council of Norway (reference 312492). The funder had no role in the design, execution, or reporting of this research. Authors’ Contributions ØSS conducted data extraction, formal analysis, writing, and visualization through tables and figures. FO curated, investigated, and analyzed the encounter data and validated the results. CG and TS contributed to refining the study's conceptualization and design. All authors ensured the study’s quality and integrity by critically reviewing the methodology and content and approved the final manuscript. The medical writer (FO) participated in his capacity as a public healthcare professional. Acknowledgements The authors would like to thank The National Archives of Norway, Nordland Hospital Trust, University Hospital of North Norway, and the Municipality of Bodø for their assistance in preparing the data used for this analysis. We would also like to thank Johan Gustav Bellika for critically reviewing the manuscript and providing constructive feedback to improve it before submission. This work was conducted as part of the Valkyrie project, a research initiative funded by the Research Council of Norway (reference 312492). The funder had no role in the research. References Veenstra M, Skinner MS, Sogstad MKR. A nation-wide cross-sectional study of variations in homecare nurses’ assessments of informational continuity–the importance of horizontal collaboration and municipal context. BMC health services research. 2020;20:1-11. World Health Organization. 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Data to knowledge to improvement: creating the learning health system. Bmj. 2024 Jan 25;384:e076175. PMID: 38272498. doi: 10.1136/bmj-2023-076175. Chatterjee S, Fruhling A, Kotiadis K, Gartner D. Towards new frontiers of healthcare systems research using artificial intelligence and generative AI. Taylor & Francis; 2024. p. 263-73. Syversen MO, Glatkauskas M, Sedeniussen SJ, Hauge M, Benny S, Horgen K, et al. Discrepancies in medication lists after hospital discharge in patients with multiple long-term conditions. Research in Social and Administrative Pharmacy. 2025. Kneck Å, Flink M, Frykholm O, Kirsebom M, Ekstedt M. The information flow in a healthcare organisation with integrated units. International journal of integrated care. 2019;19(3):20. PMID: 31592046. Chelsom J, Marco-Ruiz L, Skeidsvoll Solvang Ø, Cassidy S, Lintvedt O, Granja C, et al. Federated Electronic Health Records Using a Blockchain. Stud Health Technol Inform. 2024 Aug 22;316:1219-23. PMID: 39176600. doi: 10.3233/shti240630. Beinke JH, Fitte C, Teuteberg F. Towards a stakeholder-oriented blockchain-based architecture for electronic health records: design science research study. Journal of medical Internet research. 2019;21(10):e13585. Ådnanes M, Kaspersen SL, Melby L, Lassemo E. Pakkeforløp for psykisk helse og rus-fagfolks erfaringer første året. 2020. Additional Declarations No competing interests reported. Supplementary Files SupplementalDigitalAppendixAppendixA.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 03 Mar, 2026 Reviews received at journal 03 Mar, 2026 Reviews received at journal 16 Feb, 2026 Reviewers agreed at journal 26 Jan, 2026 Reviewers agreed at journal 12 Jan, 2026 Reviewers invited by journal 12 Jan, 2026 Editor assigned by journal 22 Dec, 2025 Submission checks completed at journal 22 Dec, 2025 First submitted to journal 19 Dec, 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. 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. 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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-8408262","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":573220076,"identity":"8e43f751-1e54-45d1-82d6-686f50dea7bf","order_by":0,"name":"Øivind Skeidsvoll 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1","display":"","copyAsset":false,"role":"figure","size":145847,"visible":true,"origin":"","legend":"\u003cp\u003eDesign Science Research method for artifact design [48]\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8408262/v1/51993c2dc4d935ac989ee7c3.png"},{"id":100400946,"identity":"c83dd151-b819-49a2-bba9-b6e15c84bffa","added_by":"auto","created_at":"2026-01-16 11:58:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":331612,"visible":true,"origin":"","legend":"\u003cp\u003eVisualization of healthcare events, actions, and the information flow between actors along clinical pathways for a patient with mental and physical health issues\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8408262/v1/ef21f26808e41372c99ad553.png"},{"id":100401293,"identity":"c357a380-c543-4835-931f-258ffebfe7e1","added_by":"auto","created_at":"2026-01-16 11:58:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":360355,"visible":true,"origin":"","legend":"\u003cp\u003eVisualization of healthcare events, actions, and the information flow between actors for a patient with mental and physical health issues when the clinical pathways converge\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8408262/v1/57ba0646eb96d0e17938e14b.png"},{"id":100399788,"identity":"570ff549-58d5-4b3e-b6cd-2d9ebad51c8f","added_by":"auto","created_at":"2026-01-16 11:57:36","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":57409,"visible":true,"origin":"","legend":"\u003cp\u003eRoot-cause analysis of the information logistics problem\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8408262/v1/44ef8cd6f40fce774297625f.png"},{"id":100400592,"identity":"00f8aece-e6bf-43ea-bd45-771ca2151117","added_by":"auto","created_at":"2026-01-16 11:58:19","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":153216,"visible":true,"origin":"","legend":"\u003cp\u003eOutline of the conceptual information architecture framework\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8408262/v1/3a904f4e4200bf996f7f71e5.jpeg"},{"id":100400097,"identity":"4e018a40-f48a-47be-a2a2-5b3eaf57d4a9","added_by":"auto","created_at":"2026-01-16 11:57:53","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":175391,"visible":true,"origin":"","legend":"\u003cp\u003eThe conceptual information logistics architecture with layers and modules interacting across two EHRs, a national patient portal, and the Valkyrie Central (VC)\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8408262/v1/696dcc2584e63485b10191f9.png"},{"id":100400458,"identity":"c353c2da-6ef9-430d-bd7f-0f647c7e31cb","added_by":"auto","created_at":"2026-01-16 11:58:10","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":305362,"visible":true,"origin":"","legend":"\u003cp\u003eUse case of the inter-organizational information logistics based on the functional requirements\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8408262/v1/f53151af8472afaf66214ba9.png"},{"id":100422868,"identity":"dbfd8d25-da65-4fa6-b5f1-704fc88446cc","added_by":"auto","created_at":"2026-01-16 14:11:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2440356,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8408262/v1/095c7173-c4a5-4b39-bb56-f4c18123e8fa.pdf"},{"id":100400457,"identity":"37ff57c2-8c58-4dcb-bc29-ddd9c7b92877","added_by":"auto","created_at":"2026-01-16 11:58:10","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":17668,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalDigitalAppendixAppendixA.docx","url":"https://assets-eu.researchsquare.com/files/rs-8408262/v1/be678ea3556f0813690ed577.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Towards an information-centric architecture framework for health information logistics: a design science research study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccessible and usable health information at the point of care, often referred to as information logistics, is essential for safe, high-quality, and integrated healthcare [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Despite this necessity, a persistent gap remains between the logistics required by practice and what current Health Information Systems (HIS) and Electronic Health Records (EHRs), primarily optimized for documentation, actually provide [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e–\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This gap has widened by the shift toward specialized care and against the growing mandate for patient-centric coordination, driving patient mobility across providers and care levels [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e–\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The complexity is particularly salient for the growing population of multimorbid patients (individuals suffering from multiple diseases) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], who follow complex, circular pathways and require continuous, integrated information flows [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This fragmentation translates directly into critical data management challenges: missing or delayed critical information increases uncertainty in decision-making, shifts information-seeking and requesting burden onto clinicians and patients [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and contributes to costly duplicate testing [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. To support coordination and patient safety in such complex, situated environments, a sociotechnical design perspective and robust data management that enables contextual, inter-organizational access through information networks, following patients along their pathway is indispensable [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAgainst this backdrop, the Valkyrie research project was initiated to design an architecture and develop a technical prototype that enables clinicians and patients to have virtual access to distributed patient records [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In this context, virtual access refers to embedded functionality that enables on-demand views of distributed patient records, contextually relevant to the current stage of the patient’s pathway, without any physical replication or exchange of complete patient records. An initial scoping review systematically examined existing approaches to inter-organizational EHR access and identified six distinct methods [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Crucially, the review found that existing designs consistently failed to meet the Valkyrie requirements for pathway-driven, cross-level access without duplicating patient records. Designs were often ad hoc or solely technology-driven rather than requirements-driven. The review established that Health Information Quality (HIQ), encompassing dimensions like accuracy, currency, and completeness [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], emerged as the leading facilitator for success, while poor information quality and a lack of trust constituted major systemic barriers. Addressing these fundamental challenges requires a systematic information architecture framework.\u003c/p\u003e \u003cp\u003eThe need for integrated information is particularly salient for complex patient groups, such as individuals with multimorbidity and mental health conditions, which are rising steadily, and who frequently undergo concurrent treatments and depend on continuous, inter-organizational information flows [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This complexity is compounded by the nature of clinical practice itself, which is inherently situated, with coordination and communication via rich social networks across a fragmented geographical and organizational landscape [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and characterized by uncertainty in individual patient responses to symptoms, diagnoses, and interventions, and challenges of integrating their perspectives and needs into care decision-making [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22 CR23 CR24\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e–\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Furthermore, health information architectures are shaped by specific contextual factors [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], including the Norwegian healthcare system's organization, which requires complex coordination between centralized specialist care and decentralized primary care. In Norway, Urgent Care (UC), General Practitioner (GP), and Community Nursing Service (CNS) are organized under 357 municipalities, with GPs and UC units acting as gatekeepers to specialized services [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Specialized care is organized under four state-owned regional health authorities. Despite Coordination Reforms aimed at strengthening integration and improving information logistics [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e–\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], different patient-facing services, such as the national portal “Helse Norge”, and international efforts increasingly emphasizing data integration through standards such as Health Level Seven (HL7), Fast Healthcare Interoperability Resources (FHIR), openEHR, Integrating the Healthcare Enterprise (IHE), the International Organization for Standardization (ISO) - ISO 13606, and ISO 13940 (ContSys), the continued information fragmentation for clinicians and limited abilities for patients to share their voices across heterogeneous EHR platforms persists in this context [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e–\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This underscores the urgent need for accessible information networks that follow the patient along their pathway, enabling virtual access to context-relevant pathway data without replicating records.\u003c/p\u003e \u003cp\u003eTo systematically manage this dynamic socio-technical complexity, architectures must serve as systematic tools for design, component structuring, clinical and patient integration, and embedding governing principles to reduce complexity and guide organizational improvements [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This conceptual framework is therefore designed with modularity, layered patterns, and explicit interfaces to reduce structural complexity and limit interdependencies [\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e–\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Crucially, in response to the high-stakes environment and pervasive trust issues [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], we foreground Data Management (DM) [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] and Information Governance (IG) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], as authoritative, vertical pillars that prescribe the non-functional constraints, alongside HIQ [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], essential for sustaining trust and reliability [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn accordance with the Design Science Research (DSR) methodology, this paper aims to design a conceptual information architecture framework as prescriptive design knowledge (meta-artifact), rigorously grounded in inter-organizational information requirements, intended to guide future design iterations for relevance to practice and contribute to reusable knowledge to the scientific communities.\u003c/p\u003e \u003cp\u003eTo this end, the research provides three critical contributions: first, it formalizes a theoretical paradigm shift from application-centric to information-centric architecture by decoupling information assets through metadata-centric tokens to enable long-term DM flexibility; second, it operationalizes inter-organizational DM through HIQ structural imperatives, directly mitigating systemic failures such as data duplication and coordination delays; and third, it establishes an architectural foundation to support the full spectrum of clinical reasoning, bridging the gap between intuitive pattern recognition and analytical hypothesis testing within context-aware pathway views. Ultimately, the study presents a verifiable \"TO-BE\" blueprint for inter-organizational logistics that accommodates emerging technologies, such as blockchain and Artificial Intelligence (AI), while strictly preserving organizational autonomy and interprofessional trust.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eWe follow the DSR paradigm to construct and evaluate an artifact that advances both practice and scientific knowledge [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This study's central outcome is the development of a conceptual information architecture framework, classified as a distinct meta-artifact, intended explicitly as prescriptive design knowledge [\u003cspan additionalcitationids=\"CR46 CR47\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e–\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Following Hevner’s three-cycle view (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], the Rigor Cycle explicitly draws upon a robust knowledge base, including domain expertise, the preceding scoping review, and the extant literature, with output as design products and processes (Meta-artifacts). The Design Cycle connects the Environment and guides the iterative formulation of the conceptual framework, which serves the Relevance Cycle by providing a systematic solution for the defined problem in inter-organizational health information logistics.\u003c/p\u003e\u003cp\u003eThis study applies the DSR method framework, consisting of problem definition, requirements definition, artifact design and development, demonstration, and evaluation [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Due to the conceptual nature of the artifact, evaluation activities primarily focused on justifying the problem statement (EVAL 1) and verifying the validity and consistency of the design decisions (EVAL 2) against established principles [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eProblem Definition\u003c/p\u003e\u003cp\u003eThe problem definition involved triangulating existing literature, authors’ expertise, and an empirical analysis of 14 multimorbid patients’ longitudinal clinical encounters (spanning 1954–2024) across primary and specialist care in Northern Norway. This mixed population of 8 females (3 living and 5 dead) and 6 males (1 living and 5 dead), as reported by the participating clinician, enabled comparative analysis across the healthcare system, focusing on patterns of information logistics challenges. The 10 dead patients were randomly selected among 70 patients with documented mental and physical conditions. Records used in the analysis were anonymized in accordance with ethical guidelines.\u003c/p\u003e\u003cp\u003eAnalysis of these encounters revealed recurring patterns of information logistics challenges, including significant data duplication (F1, F2), delays (F4), and compartmentalization of patient voice (F6) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A single-patient scenario spanning 2005–2024 was selected and validated with the participating clinician as a representative case to illustrate these systematic failures in DG, DM, and HIQ (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Stakeholders were identified (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) using an iterative approach [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], an Actor-linkage matrix [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] was developed based on the case to map interactions and information flow intensity (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), and a root-cause analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) was conducted to unpack the underlying origins of fragmented logistics, confirming a pervasive lack of awareness and access.\u003c/p\u003e\u003cp\u003eRequirements and Designed Artifact\u003c/p\u003e\u003cp\u003eHigh-level requirements were iteratively formulated by synthesizing the problem definition, Valkyrie principles, and the scoping review findings. The conceptual architecture framework (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) outlines the necessary structure, detailing Security and Privacy and IG and DM as authoritative vertical pillars. This outline serves as the prescriptive foundation, guiding the translation of abstract problems into non-functional requirements, encompassing structural (layered, modularity principles) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) and environmental (IG, DM, HIQ constraints and enablers) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFunctional requirements were defined subsequently (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), by expanding the outline and drawing on the information logistics architecture framework (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), specifying system interaction categorized into Security and Privacy (R1–R3), Awareness and Accessibility (R4–R5), and Health Information Quality (HIQ) (R6–R7). The functional requirements explicitly address the barriers identified in the preceding scoping review (e.g., trust, poor HIQ) by mandating design features like access logs (R1) and robust data quality controls (R6, R7) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDemonstration and Evaluation\u003c/p\u003e\u003cp\u003eA use case was constructed based on a hospitalization and discharge scenario to demonstrate the conceptual feasibility-in-principle of the designed architecture framework (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). This demonstration illustrates the system's functions in future state scenarios, focusing on successful interactions (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe conceptual nature of this early-stage artifact dictated an ex-ante evaluation [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. This involved a formative, conceptual assessment comparing the framework against the defined problem, requirements, and existing approaches identified in the scoping review. EVAL 1 justified the relevance and practical importance of the problem, and EVAL 2 confirmed the validity and consistency of the conceptual and logical design prior to prototype development.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThis section contains the problem definition, including the user scenario (case), the requirements definitions, and the use case (demonstration).\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eProblem Definition\u003c/h3\u003e\n\u003cp\u003eThe problem definition starts with the user scenario, followed by stakeholder identification, information-flow intensity, root causes, and the problem definition.\u003c/p\u003e\n\u003ch4\u003eUser Scenario \u0026ndash; Parallel Clinical Pathways and Convergence\u003c/h4\u003e\n\u003cp\u003eThe longitudinal user scenario tracks a multimorbid patient\u0026rsquo;s 19-year pathway (2005\u0026ndash;2024), demonstrating interactions across specialist and primary care providers (Figure 2). The full chronology of events and actions is detailed in Supplemental Digital Appendix A. Initially, the patient managed distinct parallel clinical pathways (Cardiovascular, Neurological, Vascular, and Mental Health) until 2022. This complexity intensified significantly at the beginning of 2024, exposing systemic failures in information logistics during an acute care transition and subsequent discharge (Figure 3). This critical convergence of pathways confirmed systematic findings of data duplication (F1, F2), delays in timely information logistics (F4), and the compartmentalization of essential patient input (F6), as detailed in Table 1. The root-cause analysis (Figure 4) reveals that this information fragmentation creates uncertainty in care decisions, risks patient safety, and necessitates time-consuming manual work for clinicians.\u003c/p\u003e\n\u003cp\u003eTable 1 lists the identified problems, confirming systematic challenges in inter-organizational DM. These include frequent instances of data duplication through cutting and pasting (F1) and code reuse (F2), significant delays in timely information logistics (F4), the lack of inter-organizational access (F5), and the compartmentalization of essential patient input (F6), all compromising HIQ.\u003c/p\u003e\n\u003cp\u003eTable 1 Identified problems, assumed causes, problem groups, and possible consequences elicited from the user scenario\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003eIdentified problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003eAssumed causes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eProblem groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003ePossible consequences of the problems\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eCutting and pasting patient data to achieve an overview of the patient\u0026rsquo;s illness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003eMissing patient summary\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eData duplication\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eLowered HIQ\u003c/p\u003e\n \u003cp\u003eAdded manual work\u003c/p\u003e\n \u003cp\u003eUncertainties in clinical decision making\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eReusing and repeating clinical codes for each new contact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eClinical codes are used for different purposes (documentation and reimbursement)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eData duplication\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eLowered HIQ\u003c/p\u003e\n \u003cp\u003eAdded manual work\u003c/p\u003e\n \u003cp\u003eUncertainties as to whether the codes relate to a pathway or a particular episode.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eF3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSending messages with reminders and requests for information\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMissing access to patient records and medication lists\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eUnintended use (Appropriation)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eAdded manual work\u003c/p\u003e\n \u003cp\u003eNeed to await responses\u003c/p\u003e\n \u003cp\u003eUncertainties as to whether all relevant clinicians receive messages.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eHealth information, treatment plans, and medication lists arrive late at the point of care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eThe clinical person responsible is also responsible of informing others.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eUntimely information logistics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eAdded manual work\u003c/p\u003e\n \u003cp\u003eNeed to await responses\u003c/p\u003e\n \u003cp\u003eUncertainties in clinical decision-making Patients as information carriers\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eF5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003eSymptoms can indicate both physical and mental health conditions but are not easily shared across clinical domains\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eMissing access to essential information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eMissing integrated, patient-centric pathway view\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eCan increase redundant work and limit effective examination, diagnoses, and treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eF6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePatients\u0026rsquo; individual needs are mostly compartmentalized, and not easily shared \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eThere is no common recording and sharing of patient\u0026rsquo;s voices inter-organizationally.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eMissing integrated, patient-centric pathway view\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003eMissing patients\u0026rsquo; voices can affect the treatment quality and progression.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;2 lists the identified stakeholders followed by a description of the stakeholders.\u003c/p\u003e\n\u003cp\u003eTable 2 Description of the stakeholders identified during the construction of the user scenario\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIdentified stakeholders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDescription of stakeholders\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eA person who, due to symptoms or illness, becomes a patient and enrolls into the healthcare system. Although categorized as a patient by healthcare and belonging to one or more patient groups, their personal preferences and needs may result in different behaviors to identical treatment and medication options. \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNext of kin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eIt is the patient\u0026rsquo;s closest relation, appointed by the patient, and is often a family member. Next of kin has the role of guardian for the patient and may be both informed and participate in decision making concerning the patient. They have broader privileges than relatives, including access to patient records.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGeneral Practitioner (GP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHealthcare professionals who specialize in general medicine. GPs are often the first contact point for citizens with symptoms of illness and encounter less severe conditions than specialists at a hospital and can prevent problems from escalating. GPs refer patients to specialists and receive discharge reports (epicrisis) from specialists.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedical physician\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSpecialist doctor at the hospital medical department, examining and treating patients with physical (somatic) conditions.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePsychiatrist\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSpecialist doctor working in the psychiatry department at the hospital, diagnosing and treating patients with mental health conditions, such as depression, anxiety, and bipolar disorder. Psychiatrist 2 identified through the user scenario was a specialist in adult psychiatry, especially related to diagnosing dementia.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDistrict nurses/ home care nurses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNurses or nursing assistants employed by the municipalities and work in care units for patients at home or at care institutions for shorter or longer stays. \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUrgent care (UC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOrganized under the municipalities offering acute medical services after GP\u0026rsquo;s closing time. Like the GP, they can refer patients to the hospital.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAs clinical pathways converged (Figure 3), more stakeholders became involved, interactions increased, and the information flow intensified. Using these insights, an actor-linkage matrix (Table 3) was constructed, showing the GP as the central hub with the highest intensity of information flow, particularly with CNS, and the medical physician. While CNS initiated the flow with the GP, the GP acted as the primary gatekeeper to specialized care. The patient exhibited minimal information flow, primarily as a receiver, reflecting the compartmentalization of the patient\u0026rsquo;s voice across organizations. In Table 3, blank cells indicate no information flow, while cells with question marks suggest that information flow is likely occurring but is not documented. The stars indicate the occurrence of information flow between stakeholders, with the number of stars representing the information flow intensity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 3 Mapping the intensity of the information flow between the identified stakeholders using an Actor-linkage matrix\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUsing the synthesized empirical findings (Table 1) and the derived root-cause analysis (Figure 4), we assert that information fragmentation systematically creates uncertainty in care decisions, elevates patient safety risks, and necessitates substantial time-consuming manual clinician effort to assemble data from multiple sources. The analysis confirms that the information logistics crisis stems fundamentally from two persistent, pervasive system deficiencies: (1) a lack of awareness regarding parallel treatment activities elsewhere, and (2) limited virtual access to distributed patient records. This situation highlights a growing and urgent demand for comprehensive and timely information logistics when complex clinical pathways converge. Accordingly, the problem is defined as:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCurrent patient and clinical integrations suffer from inter-organizational information logistics, which limit awareness of patients\u0026rsquo; voices and treatment activities at other providers, and reduce access to distributed patient records. This restricts clinicians\u0026rsquo; proactive use of essential health information at the point of care and constrains patients\u0026rsquo; ability to share their voices and participate in care decisions.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe synthesis of longitudinal patient data with inter-organizational stakeholder mapping confirms that information fragmentation is not merely a technical byproduct but a systemic failure of current health information logistics. The root-cause analysis (Figure 4) identifies a pervasive \u0026apos;lack of awareness\u0026apos; and \u0026apos;lack of access\u0026apos; as the primary drivers of clinical uncertainty and manual workload (F1\u0026ndash;F6). However, this empirical problem definition also carries a crucial architectural mandate: opening patient records to resolve these gaps inherently introduces socio-technical side effects, specifically the risk of accidental disclosures of sensitive information and the exposure of discrepancies in work routines and documentation practices across organizations. These factors heighten concerns regarding DM, HIQ, security, and privacy. Consequently, successful mitigation requires that the prescriptive architecture framework explicitly operationalize governance and management factors as non-functional constraints, providing the structural foundation necessary to sustain inter-organizational trust and collaboration.\u003c/p\u003e\n\u003ch3\u003eRequirements and Framework\u003c/h3\u003e\n\u003cp\u003eBuilding on the empirical problem defined in the previous section, we now transition to the systematic definition of requirements necessary to address fragmentation and support robust information logistics. As posited within the DSR paradigm, the solution artifact, the conceptual information architecture framework, must function as a prescriptive design knowledge (meta-artifact), rigorously guiding the translation of problem constraints derived from the Relevance Cycle into requirement specifications.\u003c/p\u003e\n\u003ch4\u003eConceptual Framework outline and governing pillars\u003c/h4\u003e\n\u003cp\u003eTo guide this translation, we outline the conceptual information architecture framework (Figure 5), synthesizing core insights from the preceding scoping review and the foundational Valkyrie principles. This conceptual model is structured to integrate the overarching Valkyrie goals with authoritative, vertical pillars. Crucially, addressing the lack of inter-organizational awareness and access inherently heightens concerns about security, privacy, and HIQ, risking the formation of tension and distrust among collaborating stakeholders. Therefore, the framework explicitly prescribes the necessity of Security and Privacy, and IG/DM as non-functional constraints that must be aligned with system-wide standardization initiatives to enable inter-organizational trust and collaboration.\u0026nbsp;\u003c/p\u003e\n\u003ch4\u003eEnvironmental Requirements\u003c/h4\u003e\n\u003cp\u003eBuilding upon the abstract conceptual information architecture framework outlined (Figure 5), we now systematically specify the high-level non-functional requirements that translate the defined problem of information fragmentation into tangible architectural constraints. These requirements dictate the essential contextual boundaries (environmental) constraints and the internal organization (structural) required to govern and realize the solution. Non-functional requirements, being generic and widely applicable, ensure fundamental qualities such as usability, security, and sustained interoperability [45].\u003c/p\u003e\n\u003cp\u003eTable 4 Description and justification of the inter-organizational high-level non-functional environmental requirements\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eInter-organizational high-level non-functional environmental requirements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eDescription and justification\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003eThe system should adhere to Valkyrie\u0026rsquo;s goal and overarching principles.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eIt is a prerequisite that the artifact is aligned with Valkyrie\u0026rsquo;s goals and principles, facilitating integrated, patient-centric information logistics [15].\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003eThe system should be flexible to adapt to external regulations, standards, and recommendations.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eDue to the dynamic interplay in healthcare [19, 24, 25] and the differences in funding, priorities, and autonomy among healthcare providers, changes will likely occur across various time scales, requiring a flexible and adaptable system.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003eThe system should handle conflicts of interest and HIQ issues through inter-organizational IG.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eIG can improve normative and functional integration, reducing tension and handling conflicts of interest [43], which can arise when closed systems are opened to outsiders and differences in processes, procedures, and documentation routines are revealed [16].\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003eThe system should incorporate existing national infrastructures and components.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eIt is crucial for the system\u0026rsquo;s overall success and its attractiveness to other healthcare domains and providers that national infrastructure and components are incorporated [11]. \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003eThe system should ensure security and privacy by design.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eEnsuring that health information is safe and secure is crucial for patients\u0026rsquo; and clinicians\u0026rsquo; trust in the healthcare system and each other, and ultimately, the treatment quality [16].\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe environmental requirements define the broader contextual constraints, derived from the problem domain and the overall Valkyrie objectives (Figure 5). These requirements (Table 4) prescribe essential socio-technical conditions, such as adherence to existing national infrastructure and external regulations. Specifically, they mandate that the system must proactively handle conflicts of interest and pervasive HIQ issues through rigorous inter-organizational IG, which is crucial when opening traditionally closed systems.\u003c/p\u003e\n\u003ch4\u003eThe Prescriptive Information Logistics Architecture\u003c/h4\u003e\n\u003cp\u003eWhile the environmental requirements (Table 4) define the external constraints, the detailed conceptual architecture explicitly describes the internal composition and functionality required to solve the core problem. Figure 6 presents the conceptual information logistics architecture, visualizing the rigorous, layered, and modular structure prescribed to operationalize the framework and address the root causes and problem definition identified (lack of awareness and lack of access).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe architecture is systematically divided into three horizontal layers, constrained vertically by the authoritative Security and Privacy and IG/DM pillars:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eTop Layer (Clinician/Patient Interaction):\u003c/strong\u003eThis layer directly addresses the problem of fragmented access and limited awareness by providing user interfaces embedded within existing EHRs and the National Patient Portal, thereby reducing workload by eliminating the need for additional logins. It introduces two key modules that respond directly to the defined problem:\u003cul style=\"list-style-type: circle;\"\u003e\n \u003cli\u003eAwareness Module: This component delivers contextual notifications regarding a patient\u0026rsquo;s concurrent treatment activities at other providers. This function is enabled by structured, lightweight information tokens (metadata, clinical codes, location pointers) that are pushed from the underlying EHR systems. This mechanism directly mitigates the \u0026quot;lack of awareness\u0026quot; problem.\u003c/li\u003e\n \u003cli\u003eFilter, Search, and Query Module: This component enables clinicians to actively search, filter, and organize inter-organizational patient records flexibly. This module relies on the Virtual EHR component located in the middle layer to provide read-only views of distributed data, thereby directly solving the \u0026quot;lack of access\u0026quot; problem.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMiddle Layer (Pathways and Virtual Access):\u003c/strong\u003e This layer translates the heterogeneous tokens into a cohesive overview. It includes the Patient-centric pathway module, which maps information tokens into coherent pathway models to support coordination and awareness. Crucially, the Virtual EHR within this layer provides the on-demand, read-only views of distributed records necessary for detailed clinical review. Importantly, these components must work contextually together to ensure smooth transitions between the pathway overview and the detailed clinical review, supporting different clinical reasoning processes.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eBottom Layer (Secure Storage and Provenance):\u003c/strong\u003e This layer ensures that the tokens are securely stored and compliant with legal requirements [52], guaranteeing integrity and traceability. This foundational control is vital for reinforcing the IG/DM pillar and sustaining interprofessional trust.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis strategic layering, separating concerns across user interaction, pathway logic, and secure storage, facilitates decoupling information from application constraints. This decoupling approach is essential for achieving the necessary long-term DM flexibility, enabling future information organization and reorganization independently from underlying application data models [2, 12, 13].\u003c/p\u003e\n\u003ch4\u003eStructural Requirements\u003c/h4\u003e\n\u003cp\u003eThe internal organization and design decisions visualized in the conceptual architecture (Figure 6) are formally specified by the structural requirements. These requirements serve as definitive prescriptive constraints to manage complexity and ensure the artifact functions as reusable design knowledge. As formalized in Table 5, the structural constraints are defined to maximize long-term utility:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eModularity and Layered Pattern: The requirement for a modular design and layered pattern approach (Table 5) is explicitly mandated to promote the creation of reusable components and ensure ease of system maintenance and flexibility when incorporating internal or external additions.\u003c/li\u003e\n \u003cli\u003eStandards-Neutrality: The prescription to avoid vendor lock-in by supporting open standards and APIs (Table 5) ensures DM flexibility and long-term architectural stability, allowing the framework to support international health information standards (e.g., HL7 FHIR, openEHR) without imposing a single rigid approach.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThese specified structural requirements confirm the prescriptive nature of the conceptual architecture, rigorously detailing the internal conditions necessary for the artifact to govern information assets and enable complex inter-organizational information logistics.\u003c/p\u003e\n\u003cp\u003eTable 5 Description and justification of the inter-organizational high-level non-functional structural requirements\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003eInter-organizational high-level structural Requirements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eDescription and justification\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eThe system architecture should have a modular design and a layered pattern approach.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eA modular architecture promotes reusable components and can also make the architecture flexible to incorporate new internal or external additions to benefit the healthcare system\u0026rsquo;s stakeholders. Modularity and layered architectures promote the separation of concerns and ease system maintenance [36, 37, 40].\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eThe system should avoid vendor lock-in by supporting open standards and APIs.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eOpen standards and APIs can help lower entry barriers and empower healthcare providers to change modules or systems without data loss or significant conversion costs [39, 53].\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eThe system should\u0026nbsp;be embedded into local patient record systems/ clinical workflow.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eBy following modularity [38]\u0026nbsp;and virtualization ideas, the system\u0026rsquo;s user interface should be embedded into existing applications and workflows, which can help reduce the number of user interfaces and logins, and avoid vendor lock-in [53].\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eThe system should protect health information from unauthorized use.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eThe information tokens representing patients\u0026rsquo; pathways must be securely stored and be available to authorized clinicians only. This is regulated by the Patient Journal Law \u0026sect;22 [52], and is essential for building trust among stakeholders.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eThe system should offer high availability and accessibility.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eAs a general requirement, the system should provide availability and accessibility that is equal to or greater than that of the distributed patient record systems it depends on, which also affects the system\u0026rsquo;s load time [16].\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eThe system should support stakeholders in navigating and exploring patient pathway information according to personal preferences.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eBecause of the dynamic and contextual nature of healthcare work [3, 25], clinicians must be offered various methods of navigating the information provided such as filtering, searching, and querying the information, with limited predefined navigation patterns. \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch4\u003e\u003cbr\u003eStructural Requirements\u003c/h4\u003e\n\u003cp\u003eHaving formalized the non-functional constraints that govern the architecture\u0026apos;s environment and internal structure, we now proceed to specify the functional requirements. Functional requirements detail how the envisioned system must interact with its users to rigorously address the identified information fragmentation problem [45]. These requirements translate the architectural pillars and components into tangible system behaviors.\u003c/p\u003e\n\u003cp\u003eThe functional requirements (Table 6) are systematically grouped into three core categories reflecting the authoritative vertical pillars of the conceptual framework and the defined problem: Security and Privacy, Awareness and Accessibility, and HIQ.\u0026nbsp;\u003c/p\u003e\n\u003ch5\u003eSecurity and Privacy (R1\u0026ndash;R3)\u003c/h5\u003e\n\u003cp\u003eThe Security and Privacy requirements ensure the technical solution adheres to the legal and professional standards necessary to sustain stakeholder trust when accessing distributed patient records. They mandate transparent audit trails (R1), aligned with laws requiring logging of all clinical access to confidential information [52]. Furthermore, the system must control informed consent (R2), acknowledging the patient\u0026rsquo;s right to limit access to their confidential information [54, 55]. Operational efficiency is maintained by requiring the reuse of existing organizational authentication and authorization mechanisms (R3) wherever possible, avoiding the introduction of new logins or maintenance overhead [16].\u003c/p\u003e\n\u003ch5\u003eAwareness and Accessibility (R4\u0026ndash;R5)\u003c/h5\u003e\n\u003cp\u003eThese requirements directly operationalize the fundamental issues identified in the root-cause analysis and the problem definition: lack of awareness and lack of access. The system must deliver notifications of parallel treatment activities (R4), ensuring clinicians gain timely awareness of concurrent events and medications. When further details are needed, the system must provide virtual access to distributed patient records (R5), addressing the access gap. Critically, R5 also explicitly mandates the integration of the patient\u0026rsquo;s voice and preferences, mitigating the empirically observed problem of compartmentalized patient input that affects treatment quality (F6) [23].\u003c/p\u003e\n\u003cp\u003eTable 6 Description and justification of the inter-organizational high-level functional requirements grouped into Security and privacy, Awareness and accessibility, and Health Information Quality\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cimg 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\"\u003e\u003c/p\u003e\n\u003ch5\u003e\u003cbr\u003e\u003c/h5\u003e\n\u003ch5\u003eOperationalizing Information Governance and Data Management through HIQ (R6\u0026ndash;R7)\u003c/h5\u003e\n\u003cp\u003eThe requirements concerning HIQ serve as the explicit operationalization of the IG/DM pillars. This enforcement is essential because opening distributed records exposes discrepancies in processes and documentation, risking reduced perceived HIQ and undermining interprofessional trust [16]. The R6 requirement enforces the basic quality dimensions of health data (accuracy, currency, reliability, and completeness) [17]. Its core prescriptive function is to mitigate the data management failures observed in the user scenario: namely, data duplication arising from the cutting and pasting of patient fragments (F1) and the uncritical reuse or repetition of clinical codes (F2). By demanding systematic consistency and accuracy across records, R6 structurally addresses the underlying causes of poor data quality at the point of ingestion and viewing. R7 addresses the contextual dimension of HIQ, requiring that information provided be understandable and useful to authorized personnel when and where needed. This is critical for resolving the acute problem of untimely information logistics (F4), where vital information and treatment plans arrive late, forcing clinicians into time-consuming manual workarounds (F3, F4). R7 ensures the system proactively filters and synthesizes inter-organizational information tokens to deliver context-relevant cues, thereby minimizing cognitive load and enabling the proactive use of essential information, supporting timely clinical decision-making.\u003c/p\u003e\n\u003ch3\u003eUse Case\u003c/h3\u003e\n\u003cp\u003eTo illustrate how the proposed architecture framework operationalizes the defined functional requirements and validates its role as a prescriptive design knowledge (meta-artifact), we present a focused use case (Table 7). This scenario, inspired by the convergence of clinical pathways (Figure 3), demonstrates the system\u0026apos;s functional requirements through a sequence of inter-organizational interactions during a critical high-risk event: a patient\u0026rsquo;s hospitalization and subsequent transfer to community care.\u003c/p\u003e\n\u003cp\u003eThe use case aims to prove the artifact\u0026rsquo;s conceptual feasibility in providing timely awareness and virtual access (R4, R5), while strictly adhering to the mandated vertical pillars of Security and Privacy (R1, R2, R3) and IG/DM (R6, R7). Figure 7 illustrates the interactions, in which Valkyrie Central (VC) is the new component that coordinates information logistics among the hospital\u0026rsquo;s, GP\u0026rsquo;s, and CNS units\u0026rsquo; distributed EHR systems.\u003c/p\u003e\n\u003cp\u003eThe success scenarios S1 through S11 explicitly illustrate how the prescribed architecture manages the dual goals of access and governance, translating the high-level requirements into demonstrable functional flow:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eEnforcing Accountability and Trust (IG/DM Pillars):\u003c/strong\u003e Access to patient records,\u0026nbsp;whether through detailed review (S1) or updated status access (S6), is contingent upon the fulfillment of R1 (Access logs/Transparency) and R2 (Informed Consent). The Use Case demonstrates that clinicians cannot retrieve information (S1, S6) until the system confirms consent (S2, S7) and logs all access activities (S4, S9). This rigorous sequencing confirms the necessity of embedding governance mechanisms directly within the information access process to build and maintain inter-organizational trust.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eTable 7 Use case description and success scenarios of the future system\u0026rsquo;s inter-organizational virtual information logistics during a patient\u0026rsquo;s hospitalization and transfer to a community service institution\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003e#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eUse case description\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrecondition\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe patient is hospitalized after being sent from the Urgent Department to Hospital Medical in an ambulance, suffering from tubulointerstitial nephritis and sepsis. The GP and the CNS have earlier involvement with the patient and are informed of the patient\u0026apos;s hospitalization through a messaging service by the medical physician.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMain success scenario\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eS1.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eDuring the patient examination, the medical physician requests access to the Virtual EHR to review the patient\u0026rsquo;s medical history.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eS2.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eThe system checks the patient\u0026rsquo;s informed consent with the National Patient Portal.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eS3.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eThe system grants the medical physician access to patient records at the GP and CNS using local organizational credentials.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eS4.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eThe system logs the medical physician\u0026rsquo;s search activity.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eS5.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eThe system notifies the GP and CNS of the patient\u0026rsquo;s hospital examination and discharge preparations.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eS6.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eThe GP and CNS request updates on the patient\u0026rsquo;s medical and medication status through Virtual EHR before hospital discharge.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eS7.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eThe system repeats the informed consent check with the National Patient Portal, this time for the GP and CNS.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eS8.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eThe system grants the GP and responsible nurses at CNS access to view the patient\u0026rsquo;s medical status and medication list from the hospital\u0026rsquo;s patient records using local organizational credentials.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eS9.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eThe system logs the GP and CNS search activities.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eS10.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eThe system notifies the medical physician about the patient\u0026apos;s arrival at the community institution.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003eS11.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eThe system provides the GP and medical physician with access to CNS\u0026rsquo;s patient records via Virtual EHR.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eMitigating Fragmentation through Proactive Logistics:\u003c/strong\u003e By leveraging lightweight information tokens, VC facilitates timely communication (S5, S10). This immediate, context-aware notification ensures that downstream stakeholders (GP, CNS) can begin discharge planning and resource allocation earlier, directly mitigating the historically observed problem of untimely information logistics (F4) and reducing reliance on messaging workarounds (F3).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eOperationalizing Health Information Quality (HIQ):\u003c/strong\u003e The architecture enforces R6 (Accuracy, Consistency, Currency, and Completeness) and R7 (Understandable and Useful Information) by prescribing mechanisms that mitigate the risks associated with information fragmentation (F1, F2, F4). The tokens and Virtual EHR component ensure that clinicians access read-only views of source data via location pointers (S3, S8, S11). This design choice supports data currency and prevents duplication errors (F1, F2) common in replication models. By granting access to the current medication list directly from the hospital EHR (S8), the system ensures accuracy and currency, which is vital for safe transitions of care.\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe demonstration thus confirms that the layered, modular structure of the conceptual framework structurally supports the functional requirements necessary to resolve the defined problems while adhering to the prescriptive constraints of IG/DM and Security/Privacy.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study proposes a conceptual information-centric architecture framework for inter-organizational logistics aligned with the Valkyrie principles. Guided by DSR, we progressed from problem definition (user scenario, stakeholder, and root-cause analysis in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e-Figure 4, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) to high-level non-functional (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e-Table\u0026nbsp;5) and functional requirements (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), guided by the architecture framework (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), and demonstrated the architecture\u0026rsquo;s feasibility with an illustrative use case (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). In this section, the architecture framework is evaluated according to the Relevance, Rigor, and Design cycles (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) explaining how it addresses the defined problem and requirements, its contribution to the scientific community, its benefits, limitations, and future work.\u003c/p\u003e \u003cp\u003eSignificance and Feasibility of the Problem Definition (EVAL 1)\u003c/p\u003e \u003cp\u003eSafe, coordinated, and person-centered care fundamentally depends on resolving the awareness and access gaps that currently fragment inter-organizational information logistics [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. This research provides the formal EVAL 1 (Problem Justification) by demonstrating that these gaps represent recurrent, systemic failures in HIQ and DM. While the 19-year longitudinal scenario serves as the narrative vehicle, the framework's prescriptive mandate is derived from a broader synthesis of 14 multimorbid patients, which revealed consistent socio-technical failures, including significant data duplication (F1, F2), untimely logistics (F4), and the systemic compartmentalization of the patient\u0026rsquo;s voice (F6).\u003c/p\u003e \u003cp\u003e This approach derives prescriptive authority by systematically linking descriptive knowledge of fragmentation and compromised trust with concrete structural guidelines to resolve these gaps. These empirical findings justify the research need within the Relevance Cycle, proving that existing EHR approaches consistently fail to support pathway-driven access in fragmented landscapes. As multimorbidity continues to rise against a backdrop of strained clinical resources, closing these gaps is both necessary and urgent [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. By grounding the problem in decades of clinical encounters, this work establishes an architectural mandate: the system cannot merely facilitate access but must explicitly operationalize governance and management pillars as non-functional constraints to sustain inter-organizational trust.\u003c/p\u003e \u003cp\u003eValidating the Framework as Prescriptive Design Knowledge (EVAL 2)\u003c/p\u003e \u003cp\u003eAs a prescriptive meta-artifact, the conceptual framework provides a systematic solution by bridging descriptive problem knowledge with concrete structural solution patterns. This section serves as the EVAL 2 (Design Consistency) by verifying that the architectural design decisions are valid and logically aligned with the defined requirements established through the lens of Hevner\u0026rsquo;s three DSR cycles:\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eRelevance cycle\u003c/span\u003e: The root-cause analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) identified that information fragmentation creates clinical uncertainty and necessitates time-consuming manual assembly of data. The framework addresses these environmental needs by prioritizing awareness and access as primary targets for architectural intervention. By integrating patients\u0026rsquo; voices (R5) and addressing social factors such as housing and finances (F6), the framework prescribes a shift beyond technical data exchange to support a holistic, integrated care perspective. This systematic response to empirically observed failures provides a rigorous justification for the artifact\u0026rsquo;s utility in improving DM practices.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eDesign cycle\u003c/span\u003e: The architecture responds with two integrated mechanisms: Awareness and Virtual Access, in which lightweight information tokens (metadata, clinical codes, and location pointers) enable near-real-time notifications (R4), and the Virtual EHR component allows on-demand, read-only views (R5). This validates the structural decision to decouple information from application constraints, facilitating long-term DM flexibility. The Design Cycle confirms that the architectural structure, separating user interaction, pathway logic, and secure storage, is functionally consistent with the need to resolve fragmentation while mitigating the synchronization overhead and security exposure inherent in traditional record replication models.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eRigor cycle\u003c/span\u003e: The framework\u0026rsquo;s feasibility is confirmed by its alignment with international standards and agendas, such as the WHO shared EHR mandates and the EU Shared Health Data Space [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. By embedding IG and DM as authoritative vertical pillars, the design translates legal mandates (e.g., audit trails, consent) and HIQ principles into structural imperatives. The Use Case rigorously demonstrated the necessity of embedding these controls; by requiring consent checks (R2) and audit trails (R1) for every access instance (S2, S4, S7, S9), the design ensures accountability and transparency. This confirms that the governance pillars are not merely theoretical ideals, but prescriptive mechanisms essential for operationalizing inter-organizational trust.\u003c/p\u003e \u003cp\u003eTheoretical Innovation: Shifting to Information-Centric Logistics\u003c/p\u003e \u003cp\u003eThe primary contribution of this meta-artifact is the formalization of a paradigm shift from application-centric to information-centric architecture. Existing approaches identified in the scoping review predominantly rely on physical record replication or assume homogeneous data models, both of which struggle with synchronization burdens and technical heterogeneity [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In contrast, this framework introduces module decoupling via interface connections [\u003cspan additionalcitationids=\"CR37 CR38\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], which allows information assets, bundled as metadata-centric tokens, to exist and be reorganized independently of the underlying application\u0026rsquo;s constraints.\u003c/p\u003e \u003cp\u003eThis theoretical innovation addresses the \"lack of awareness\" and \"lack of access\" problems by providing a prescriptive solution pattern for harmonized-on-demand views. By structurally separating the user interface from the pathway logic and secure token storage, the framework provides a goal-oriented \"TO-BE\" vision essential for achieving long-term DM flexibility. Furthermore, this architecture is designed to support the full spectrum of clinical reasoning, and to enable future data-driven innovations, such as process mining [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], learning health systems [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], and AI [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], without compromising organizational autonomy or data sovereignty. Consequently, by enabling proactive awareness and governed virtual access, the artifact serves as a distinct form of prescriptive design knowledge, offering a verifiable blueprint where clinical reasoning and patient-centric pathways, rather than technical replication, guide inter-organizational information logistics.\u003c/p\u003e \u003cp\u003eAdvancing Inter-Organizational Integration and Pathway Efficiency\u003c/p\u003e \u003cp\u003eThe Use Case (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) validates the framework\u0026rsquo;s capacity to support high-risk transitions, such as patient transfers between hospital and community care, by systematically addressing critical information logistics gaps [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. The dual mechanism of proactive notifications (Awareness Module) and on-demand, read-only access (Virtual EHR) facilitates earlier preparation for patient needs, medication reconciliation, and service planning. This efficiency gain stems from reducing dependence on manual information-chasing, messaging workarounds, and phone calls. Furthermore, by making the patient's voice and preferences explicitly visible across organizations (R5), the framework structurally promotes better-informed planning, and addresses social factors, such as housing and financial concerns, that often influence referral and treatment progression. This integrated visibility is vital to correcting the historical imbalance in which information often flows only through key gatekeepers, such as the GP.\u003c/p\u003e \u003cp\u003eOperationalizing Information Governance and Data Management\u003c/p\u003e \u003cp\u003eCentral to the framework's evaluation is demonstrating the effectiveness of the explicit integration of the IG/DM vertical pillar in the design. The architecture moves beyond merely facilitating access to prescribing how that access must be governed through HIQ requirements (R6 and R7) to sustain trustworthiness. The design enforces R6 (Data Quality Constraints) by specifying that access is enabled only through tokens that contain location pointers, ensuring that the data used remains verifiable and current without data replication. Furthermore, the system addresses R7 (Data Context and Relevance) by filtering information through notifications (R4) to minimize cognitive load. This systematic operationalization of IG and DM through HIQ provides the necessary foundation for high-quality information assets.\u003c/p\u003e \u003cp\u003eFlexibility for Emerging Technologies\u003c/p\u003e \u003cp\u003eBy establishing a foundation of HIQ-enforced virtual access, the framework offers the necessary stability for integrating emerging technologies. Each clinical event can generate an encrypted token written to a patient-specific distributed ledger, which strengthens traceability and tamper-resistance for cross-organizational auditability [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Still, it also raises questions about performance, energy use, and AI governance that must be considered during design and evaluation [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Similarly, AI tools can be employed to aid in information retrieval and contextual notifications, contributing to the interpretation of structured and unstructured documents. However, because the framework enforces strict provenance and HIQ through its vertical pillars, it provides the structural safeguard required to manage the risks of hallucination and bias often associated with pre-trained AI models [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Consequently, this architectural flexibility allows for data-driven innovations, such as process mining and learning health systems,without compromising organizational autonomy or the underlying integrity of the inter-professional trust.\u003c/p\u003e \u003cp\u003ePrivacy and Access Balance\u003c/p\u003e \u003cp\u003eOpening access across organizations requires careful handling of privacy. The framework reduces risk by sharing tokens rather than complete records, checking consent before showing details, and logging who accessed what and when. Transparency for patients through access logs, harmonized consent, and disclosure routines across organizations helps build trust. Lack of trust was one of the main barriers identified in earlier work and can lead to situations in which clinicians do not trust information derived from external sources, including clinicians\u0026rsquo; examinations and patients\u0026rsquo; recordings [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In addition, the pathway view is designed with context awareness to show only what is necessary for the current task, thereby limiting exposure to unrelated information.\u003c/p\u003e \u003cp\u003eStakeholder Dynamics and Pathway Complexity\u003c/p\u003e \u003cp\u003eStakeholder identification in the broader sample revealed additional actors beyond those in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (e.g., social welfare services, police, prison health services). No pathway coordinator was present in the user scenario, though pathways for mental health and substance abuse began in 2019 [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. This underscores the dynamic nature of stakeholder roles and boundaries in inter-organizational contexts [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] and shows that fixed arrangements and static handoffs are inadequate, especially for multimorbid patients with unpredictable, circular pathways, as illustrated in the user scenario. Anticipated future influential stakeholders include security and information governance and data management experts (e.g., super users, HIQ experts, data stewards, information architects), system vendors, and ICT services at hospitals, regions, and national. Additionally, nurses, health secretaries, and pathway coordinators are expected to become more visible due to their significant roles in integrated care. By focusing on patient-centric pathways rather than clinical pathways within organizational boundaries, the framework remains flexible when new actors join or leave the process. The user scenario and actor-linkage matrix (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) also show how information tends to flow through the GP, while the sharing of patients\u0026rsquo; voices is often limited. Making the patient\u0026rsquo;s inputs visible throughout the pathway, in both directions, can help reduce the current imbalance.\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eThe findings of this study are situated within the Norwegian context and represent an early-stage conceptual meta-artifact, necessitating reliance on ex-ante evaluations (EVAL 1 and EVAL 2) to justify the problem and verify design consistency. While the 19-year longitudinal scenario serves as the primary narrative vehicle, it is a representative synthetic case validated by clinical expertise to embody the systemic failures observed in the broader data. The empirical foundation of this study is a synthesized analysis of 14 multimorbid patients, which revealed recurring patterns of informational fragmentation, specifically data duplication (F1, F2), logistics delays (F4), and the compartmentalization of the patient\u0026rsquo;s voice (F6).\u003c/p\u003e \u003cp\u003eNevertheless, this convenience-based sample cannot represent the exhaustive diversity of multimorbid pathways or the high variability of documentation practices across medical specialties. Furthermore, technical risks, including latency and source system downtime, and organizational risks, such as inconsistent local governance and variations in informed consent handling, may affect the framework's reliability when scaled. Consequently, further DSR iterations and longitudinal human-centric evaluations are required to assess the framework's generalizability and impact on cognitive workload across heterogeneous inter-organizational settings.\u003c/p\u003e \u003cp\u003eAlthough the design aims for international relevance through standards-based interfaces, layered modularity, and vendor-neutral principles, adaptation to other contexts will require alignment with local governance structures, infrastructure capabilities, and legal frameworks. This includes harmonizing privacy regulations, consent models, and interoperability standards.\u003c/p\u003e \u003cp\u003e Multiple researchers from clinical, sociological, and technical fields participated in data extraction, analysis, and validation, thereby strengthening the study and reducing individual bias. However, the absence of broader stakeholder involvement \u0026ndash; such as patients, nurses, and external actors \u0026ndash; at this stage limits the completeness of the requirements and evaluation needed in future iterations.\u003c/p\u003e \u003cp\u003eEthical and social risks also require attention. While many aspects are legally regulated, grey areas may emerge during design, such as balancing transparency with professional discretion or managing conflicting interpretations of consent. Empowering patients with access and insight into their own medical history and status aligns with national ambitions but introduces some trade-offs. For example, preventing another clinician from mentioning sensitive results during a parallel activity before the patient has had a direct consultation remains challenging in an inter-organizational setting. Additionally, some patients, particularly those with mental health conditions or substance use disorders, may struggle to manage sensitive information securely due to impaired judgment or situational vulnerability. Future iterations are expected to generate more knowledge about these risks and their consequences.\u003c/p\u003e \u003cp\u003eScalability and emerging technologies pose further limitations. Blockchain-based token storage and AI-assisted data processing may improve security and efficiency but introduce challenges related to performance, energy use, governance, and explainability. These technologies require careful evaluation before integration to avoid unintended complexity or inequities in access. However, technology alone cannot resolve the complexity of information logistics in integrated care. Building and maintaining trust inter-organizationally depends on evolving security and privacy mechanisms, sustaining HIQ, collaboration among professionals, strengthening DM and IG inter-organizationally, and involving stakeholders in design, testing, and evaluation to advance knowledge and mitigate risk [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFuture Research Directions\u003c/p\u003e \u003cp\u003eTo advance the utility of this prescriptive framework and facilitate its transition from a conceptual architecture to technical instantiation, future research should prioritize the following dimensions:\u003c/p\u003e \u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eInter-organizational IG/DM and behavioral complexity: Future studies must investigate the specific organizational and technical configurations required to implement inter-organizational IG/DM frameworks at scale. A critical focus should be placed on how these governance structures can systematically reduce behavioral complexity\u0026mdash;the socio-technical friction arising from inconsistent documentation routines, varying professional standards, and lack of inter-organizational trust. Research should explore how technical mechanisms mandated by the framework (e.g., tokens and audit trails) can be aligned with social incentives to empower clinicians and data stewards to maintain HIQ locally.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eComponent prototyping for clinical reasoning: Building on the framework\u0026rsquo;s middle layer, research is needed to design and develop specific components capable of supporting the full spectrum of clinical reasoning. This includes exploring how semantic enrichment and advanced filtering can facilitate rapid, intuitive pattern recognition and support analytical, deductive testing with detailed virtual views.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eGovernance of intelligent information access: As the framework supports the integration of emerging technologies, future work should examine how data-driven methods, such as AI-assisted summarization or semantic mapping, can work together with context-awareness and virtual access. These investigations must remain grounded in the framework\u0026rsquo;s pillars to ensure that any assisted synthesis maintains strict security and privacy and adheres to FATE principles (Fairness, Accountability, Transparency, and Ethics).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eLongitudinal Human-Centric Evaluation: Critical next steps involve evaluating the framework\u0026rsquo;s impact on real-world clinical and patient integration through interactive prototypes. These assessments should prioritize human-centered metrics, such as cognitive workload reduction and time-to-answer, and explore how the patient\u0026rsquo;s voice and preferences can be more robustly integrated into the shared inter-organizational pathway.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e \u003cp\u003eThe Valkyrie project is working on further artifact iterations and will report on this work in future papers.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis research addressed the persistent challenges of inter-organizational information logistics by designing and evaluating a conceptual information architecture framework that functions as a prescriptive meta-artifact. Grounded in a longitudinal empirical analysis of multimorbid patient encounters, the framework provides a rigorous foundation for bridging fragmented EHR landscapes without relying on the inherent risks and synchronization overhead of full record replication.\u003c/p\u003e \u003cp\u003eThe primary contribution of this work is three-fold. First, it formalizes a theoretical shift from application-centric to information-centric architecture, decoupling information assets through metadata-centric tokens to ensure long-term DM flexibility. Second, it operationalizes DM through HIQ structural imperatives, providing a concrete mechanism to mitigate empirically identified failures such as data duplication and coordination delays. Finally, it establishes a foundation for the full spectrum of clinical reasoning, bridging the gap between intuitive pattern recognition and analytical hypothesis testing within context-aware pathway views.\u003c/p\u003e \u003cp\u003eUltimately, this study contributes a goal-oriented 'TO-BE' vision to the DSR knowledge base. It provides a verifiable blueprint that aligns emerging technical innovations, such as AI and blockchain, with the complex socio-technical mandates of modern, patient-centric healthcare delivery, while strictly preserving inter-professional trust and organizational autonomy.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArtificial Intelligence\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCNS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCommunity Nursing Service\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDSR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDesign Science Research\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eEHR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eElectronic Health Records\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eFHIR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFast Healthcare Interoperability Resources\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGeneral Practitioner\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHIQ\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealth Information Quality\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHIS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealth Information Systems\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHL7\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealth Level Seven\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIG\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInformation Governance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIHE\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntegrating the Healthcare Enterprise\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eISO\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe International Organization for Standardization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eUC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUrgent Care\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch5\u003eEthics Approval\u003c/h5\u003e\n\u003cp\u003eAll procedures were conducted under ethical guidelines and regulations, with approvals obtained from the relevant institutional review boards: Nordland Hospital Trust, University Hospital of North Norway, and Bodø Municipality (consent 02985, 2022); The National Archives of Norway (consent H-142, 2023); and the Norwegian Directorate for E-health (2024). Data from deceased patients were handled in compliance with national regulations regarding posthumous medical records. For living patients, written informed consent was obtained before accessing their records, and they were informed of their right to withdraw from the study at any time without consequences. The data was de-identified by a clinician and stored anonymously and securely to maintain confidentiality throughout the study.\u0026nbsp;\u003c/p\u003e\n\u003ch5\u003eConsent for publication\u003c/h5\u003e\n\u003cp\u003eThe authors and the responsible institutional authorities approve the publication of this work and confirm that it has not been previously published and is not under consideration elsewhere.\u003c/p\u003e\n\u003ch5\u003eAvailability of data and materials\u003c/h5\u003e\n\u003cp\u003eThe detailed scenario description is available as a supplement to this manuscript. However, the data used to construct the scenario cannot be shared due to its sensitive nature and the strict privacy regulations governing patient records in Norway.\u003c/p\u003e\n\u003ch5\u003eCompeting Interest\u003c/h5\u003e\n\u003ch5\u003eThe authors declare that they have no competing interests\u003c/h5\u003e\n\u003ch5\u003eFunding\u003c/h5\u003e\n\u003cp\u003eThis work is part of the Valkyrie project, funded by the Research Council of Norway (reference 312492). The funder had no role in the design, execution, or reporting of this research.\u003c/p\u003e\n\u003ch5\u003eAuthors’ Contributions\u003c/h5\u003e\n\u003cp\u003eØSS conducted data extraction, formal analysis, writing, and visualization through tables and figures. FO curated, investigated, and analyzed the encounter data and validated the results. CG and TS contributed to refining the study's conceptualization and design. All authors ensured the study’s quality and integrity by critically reviewing the methodology and content and approved the final manuscript. The medical writer (FO) participated in his capacity as a public healthcare professional.\u003c/p\u003e\n\u003ch5\u003eAcknowledgements\u003c/h5\u003e\n\u003cp\u003eThe authors would like to thank The National Archives of Norway, Nordland Hospital Trust, University Hospital of North Norway, and the Municipality of Bodø for their assistance in preparing the data used for this analysis. We would also like to thank Johan Gustav Bellika for critically reviewing the manuscript and providing constructive feedback to improve it before submission. This work was conducted as part of the Valkyrie project, a research initiative funded by the Research Council of Norway (reference 312492). The funder had no role in the research.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eVeenstra M, Skinner MS, Sogstad MKR. 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PMID: 38272498. doi: 10.1136/bmj-2023-076175.\u003c/li\u003e\n\u003cli\u003eChatterjee S, Fruhling A, Kotiadis K, Gartner D. Towards new frontiers of healthcare systems research using artificial intelligence and generative AI. Taylor \u0026amp; Francis; 2024. p. 263-73.\u003c/li\u003e\n\u003cli\u003eSyversen MO, Glatkauskas M, Sedeniussen SJ, Hauge M, Benny S, Horgen K, et al. Discrepancies in medication lists after hospital discharge in patients with multiple long-term conditions. Research in Social and Administrative Pharmacy. 2025.\u003c/li\u003e\n\u003cli\u003eKneck \u0026Aring;, Flink M, Frykholm O, Kirsebom M, Ekstedt M. The information flow in a healthcare organisation with integrated units. International journal of integrated care. 2019;19(3):20. PMID: 31592046.\u003c/li\u003e\n\u003cli\u003eChelsom J, Marco-Ruiz L, Skeidsvoll Solvang \u0026Oslash;, Cassidy S, Lintvedt O, Granja C, et al. Federated Electronic Health Records Using a Blockchain. Stud Health Technol Inform. 2024 Aug 22;316:1219-23. PMID: 39176600. doi: 10.3233/shti240630.\u003c/li\u003e\n\u003cli\u003eBeinke JH, Fitte C, Teuteberg F. Towards a stakeholder-oriented blockchain-based architecture for electronic health records: design science research study. Journal of medical Internet research. 2019;21(10):e13585.\u003c/li\u003e\n\u003cli\u003e\u0026Aring;dnanes M, Kaspersen SL, Melby L, Lassemo E. Pakkeforl\u0026oslash;p for psykisk helse og rus-fagfolks erfaringer f\u0026oslash;rste \u0026aring;ret. 2020.\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-medical-informatics-and-decision-making","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"midm","sideBox":"Learn more about [BMC Medical Informatics and Decision Making](http://bmcmedinformdecismak.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/midm/default.aspx","title":"BMC Medical Informatics and Decision Making","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Integrated Care, Health Information Exchange, Health Informatics, Electronic Health Records, Interoperability, Information Governance, Data Management, Health Information Quality, eHealth, Design Science Research","lastPublishedDoi":"10.21203/rs.3.rs-8408262/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8408262/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Integrated care fundamentally depends on timely awareness and access to distributed patient records. However, patients with multimorbidity navigate complex, circular pathways, creating information fragmentation that compromises safety and efficiency. Current Health Information Systems often lack robust frameworks for inter-organizational Data Management (DM). This study aims to design a conceptual information architecture framework to resolve systemic gaps in awareness, access, and the integration of the patient’s voice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eApplying Design Science Research (DSR), this study synthesizes rigor from a scoping review with relevance from a longitudinal analysis of 14 multimorbid patients (1954–2024). A representative 19-year user scenario was validated by clinical expertise, and along with root-cause and stakeholder analysis, systemic failures in information logistics were explicated. High-level functional and non-functional requirements were iteratively derived, foregrounding Information Governance (IG), DM, and Security and Privacy as essential constraints.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The resulting artifact is a prescriptive information-centric architecture framework (meta-artifact). The layered, modular design decouples metadata, clinical codes, and location pointers into lightweight information tokens, enabling a paradigm shift from physical record replication to governed virtual access. This structure separates concerns across user interaction, pathway logic, and secure storage, providing the structural flexibility required for complex inter-organizational DM. Critically, Health Information Quality (HIQ) is positioned as the functional mechanism to operationalize DM, enforcing structural imperatives (R6–R7) for data accuracy, currency, and contextual relevance. These mechanisms directly mitigate empirically identified failures such as data duplication (F1, F2) and coordination delays (F4). Conceptual feasibility was demonstrated through an acute care transition and discharge use case.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e This study contributes reusable prescriptive design knowledge, validating the utility of architectural frameworks in solving socio-technical information logistics problems. By embedding Security and Privacy, and IG and DM as authoritative vertical pillars, and operationalizing DM through HIQ, the architecture facilitates high-quality information assets to support inter-organizational information logistics, data-driven opportunities, proactive awareness, and on-demand virtual access, while sustaining interprofessional trust and collaboration. The standards- and vendor-neutral design ensures international relevance and accommodates emerging technologies, such as blockchain and AI. This framework provides a verifiable blueprint in which clinical reasoning and patient-centric pathways guide information logistics.\u003c/p\u003e","manuscriptTitle":"Towards an information-centric architecture framework for health information logistics: a design science research study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 08:59:34","doi":"10.21203/rs.3.rs-8408262/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-03T10:44:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-03T09:11:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-16T23:30:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"282197776730714668124608432057451368686","date":"2026-01-26T22:05:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308410440797826839144376718883629049841","date":"2026-01-12T11:32:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-12T10:11:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-22T07:07:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-22T07:02:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Informatics and Decision Making","date":"2025-12-19T21:26:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-informatics-and-decision-making","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"midm","sideBox":"Learn more about [BMC Medical Informatics and Decision Making](http://bmcmedinformdecismak.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/midm/default.aspx","title":"BMC Medical Informatics and Decision Making","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dadd9aaa-0429-4c23-975d-a32a23820ee8","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T08:09:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 08:59:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8408262","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8408262","identity":"rs-8408262","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}