Access Decisions Research Articles

Perceptions of anonymised data use and awareness of the NHS data opt-out amongst patients, carers and healthcare staff

BackgroundEngland operates a National Data Opt-Out (NDOO) for the secondary use of confidential health data for research and planning. We hypothesised that public awareness and support for the secondary use of health data and the NDOO would vary by participant demography and healthcare experience. We explored patient/public awareness and perceptions of secondary data use, grouping potential researchers into National Health Service (NHS), academia or commercial. We assessed awareness of the NDOO system amongst patients, carers, healthcare staff and the public. We co-developed recommendations to consider when sharing unconsented health data for research.MethodsA patient and public engagement program, co-created and including patient and public workshops, questionnaires and discussion groups regarding anonymised health data use.ResultsThere were 350 participants in total. Central concerns for health data use included unauthorised data re-use, the potential for discrimination and data sharing without patient benefit. 94% of respondents were happy for their data to be used for NHS research, 85% for academic research and 68% by health companies, but less than 50% for non-healthcare companies and opinions varied with demography and participant group.Questionnaires showed that knowledge of the NDOO was low, with 32% of all respondents, 53% of all NHS staff and 29% of all patients aware of the NDOO.Recommendations to guide unconsented secondary health data use included that health data use should benefit patients; data sharing decisions should involve patients/public. That data should remain in close proximity to health services with the principles of data minimisation applied. Further, that there should be transparency in secondary health data use, including publicly available lists of projects, summaries and benefits. Finally, organisations involved in data access decisions should participate in programmes to increase knowledge of the NDOO, to ensure public members were making informed choices about their own data.ConclusionThe majority of participants in this study reported that the use of healthcare data for secondary purposes was acceptable when accessed by NHS. Academic and health-focused companies. However, awareness was limited, including of the NDOO. Further development of publicly-agreed recommendations for secondary health data use may improve both awareness and confidence in secondary health data use.

Art Of Designing A Novel Drug Formulation With Patient In Mind

Patients, ultimately consumer in traditional means, and health care systems will not accept new drug that fail to conform to consumer preferences or fail to deliver expected results in real world use because it will lead to increase the lack of patient adherence and that will ultimately cost to Pharmaceutical Industries. If research driven pharmaceutical industries still remain unengaged with patients during the Novel Drug Formulation development, then they are at risk of misinterpreting the need of patient that ultimately likely to have significant financial ramifications. Therefore, developing a therapy that ensure improvement in the lives of patients and their adherence to the therapy should be first rooted through a firm understanding of all aspects of the challenges faced by patients in their daily lives, during treatment, their needs and trade-offs they are willing to make to gain relief prior to conceptualisation of product design, research prioritization, product development, trial design, regulatory approval, access, reimbursement, and treatment decisions.

The Winn‐Dixie web access decision creates confusion

Juan Carlos Gil, a vision‐impaired longtime Winn‐Dixie customer, sued Winn‐Dixie because he could not access with his screen reader its website through which customers could order prescription refills for in‐store pickup and payment and because he could not link grocery coupons to its customer reward card for use with in‐store purchases. Gil made two claims under Title III of the Americans with Disabilities Act. First, he contended that the website itself was a public accommodation. Second, even if a website were not itself a public accommodation, its integration with and control by a public accommodation triggered the accessibility requirements of Title III. After trial, the district court ruled for Gil based on his second argument, reasoning that because Winn‐Dixie's grocery store and pharmacy unquestionably were public accommodations, the ADA required their associated website to be accessible.

Load Balancing Selection Method and Simulation in Network Communication Based on AHP-DS Heterogeneous Network Selection Algorithm

This article proposes an Analytic Hierarchy Process Dempster-Shafer (AHP-DS) and similarity-based network selection algorithm for the scenario of dynamic changes in user requirements and network environment; combines machine learning with network selection and proposes a decision tree-based network selection algorithm; combines multiattribute decision-making and genetic algorithm to propose a weighted Gray Relation Analysis (GRA) and genetic algorithm-based network access decision algorithm. Firstly, the training data is obtained from the collaborative algorithm, and it is used as the training set, and the network attributes are used as the attribute set, and the continuous attributes are discretized by dichotomization, and the attribute that can make the greatest information gain is selected as the division feature, and a decision tree with strong generalization ability is finally obtained, which is used as the decision basis for network access selection. The simulation results show that the algorithm proposed in this thesis can effectively improve user service quality under three services, and the algorithm is simple and effective with low complexity. It first uses AHP-DS hierarchical analysis to establish a recursive hierarchy for the network selection problem and obtains the subjective weights of network attributes through the judgment matrix. Then, it uses a genetic algorithm to adjust the subjective weight, defines the fitness function in the genetic algorithm-based on gray correlation analysis, adjusts the weights of the selection operator, crossover operator, and variation operator in the genetic algorithm, and gets the network with the largest fitness as the target network, which can effectively improve the user service quality.

Intrusion detection system for data warehouse with second level authentication

Data Warehouse (DW) security has always been a critical challenge for DW designers because of its global availability and accessibility. Over time, different researchers have suggested different DW security solutions, such as Role Based Access Controls (RBAC), Extended RBAC, Temporal RBAC (TRBAC), Risk-based access control, etc. Intrusion Detection System (IDS) and some other customized security solutions for DWs have also been proposed. Here, Risk-based access control provides additional security by utilizing risk value for each access decision. In RBAC systems, if an attacker obtains access to the system using some compromised credentials, the RBACs has no mechanism to secure DW elements which are accessible to the compromised user's role. The Intrusion Detection System (IDS) aims to solve this limitation; it monitors the user activities and alerts the system administrator whenever a user deviates from routine behavior. However, in the IDS solution for DWs, most of the real intrusions go undetected. In this work, we propose a second level authentication within the IDS, where a minute deviation from the user’s past behavior is detected. It brings more robustness to the user's historical profile and makes the system less susceptible to false negatives. The proposed solution has been implemented on standard TPC-H databases, and results indicate a significant decrease in undetected real intrusions, which is one of the main achievements of the proposed mechanism.

Conversion of a colorectal cancer guideline into clinical decision trees with assessment of validity.

ObjectiveThe interpretation and clinical application of guidelines can be challenging and time-consuming, which may result in noncompliance to guidelines. The aim of this study was to convert the Dutch guideline for colorectal cancer (CRC) into decision trees and subsequently implement decision trees in an online decision support environment to facilitate guideline application.MethodsThe recommendations of the Dutch CRC guidelines (published in 2014) were translated into decision trees consisting of decision nodes, branches and leaves that represent data items, data item values and recommendations, respectively. Decision trees were discussed with experts in the field and published as interactive open access decision support software (available at www.oncoguide.nl). Decision tree validation and a concordance analysis were performed using consecutive reports (January 2016–January 2017) from CRC multidisciplinary tumour boards (MTBs) at Amsterdam University Medical Centers, location AMC.ResultsIn total, we developed 34 decision trees driven by 101 decision nodes based on the guideline recommendations. Decision trees represented recommendations for diagnostics (n = 1), staging (n = 10), primary treatment (colon: n = 1, rectum: n = 5, colorectal: n = 9), pathology (n = 4) and follow-up (n = 3) and included one overview decision tree for optimal navigation. We identified several guideline information gaps and areas of inconclusive evidence. A total of 158 patients’ MTB reports were eligible for decision tree validation and resulted in treatment recommendations in 80% of cases. The concordance rate between decision tree treatment recommendations and MTB advices was 81%. Decision trees reported in 22 out of 24 non-concordant cases (92%) that no guideline recommendation was available.ConclusionsWe successfully converted the Dutch CRC guideline into decision trees and identified several information gaps and areas of inconclusive evidence, the latter being the main cause of the observed disagreement between decision tree recommendations and MTB advices. Decision trees may contribute to future strategies to optimize quality of care for CRC patients.

A comparison of reweighting estimators of average treatment effects in real world populations.

Regulatory agencies typically evaluate the efficacy and safety of new interventions and grant commercial approval based on randomized controlled trials (RCTs). Other major healthcare stakeholders, such as insurance companies and health technology assessment agencies, while basing initial access and reimbursement decisions on RCT results, are also keenly interested in whether results observed in idealized trial settings will translate into comparable outcomes in real world settings—that is, into so‐called “real world” effectiveness. Unfortunately, evidence of real world effectiveness for new interventions is not available at the time of initial approval. To bridge this gap, statistical methods are available to extend the estimated treatment effect observed in a RCT to a target population. The generalization is done by weighting the subjects who participated in a RCT so that the weighted trial population resembles a target population. We evaluate a variety of alternative estimation and weight construction procedures using both simulations and a real world data example using two clinical trials of an investigational intervention for Alzheimer's disease. Our results suggest an optimal approach to estimation depends on the characteristics of source and target populations, including degree of selection bias and treatment effect heterogeneity.

Semantic-Based Multi-Domain Data Access Authorization

Different domains employ variety of access control rules to protect the resources lay within their perimeters. When trying to access a resource from outside one’s domain, various issues are arising which prevent cooperating among those domains without endangering the security of the protected resources. The main challenge is how to efficiently handle the rights of users throughout the period of interoperation between various domains. In this paper, we propose a semantic-based multi-domain authorization approach that protects the resources on the multiple domains and, at the same time, provides a steady, flexible and secure authorized access to the protected resources. Two algorithms are described, one for single-domain authorization and the other is for multi-domain authorization. Our approach is based on dynamically merging access control policy rules for various domains in one large ontology, then extracting the access decision. We develop a proof-of-concept implementation and give the complexity analysis for our approach.

To PICC or not to PICC? A cross-sectional survey of vascular access practices in the ICU.

Vascular access patterns in the intensive care unit (ICU) have shifted from non-tunneled central venous catheters (CVCs) towards peripherally inserted central catheters (PICCs). We evaluated perceptions of critical care practitioners regarding these devices and variation in evidence-based practice. A 35-question survey on ICU vascular access was deployed in 13 Michigan hospitals. Descriptive statistics summarized responses. Differences in utilization, perceptions and evidence-based practices between PICCs and CVCs, by participant and site-level characteristics, were assessed. 314 of 621 eligible providers responded to the survey (response rate 51%). 15% of providers reported not routinely using ultrasound when placing CVCs. Respondents whom were trainees, from larger hospitals, and from closed ICUs were more likely to use ultrasound (p<0.001). Additionally, 21% of respondents stated they did not specify number of CVC lumens, while 46% did not specify number of PICC lumens (p<0.001). The likelihood of specifying PICC lumens increased when vascular access protocols were in place (p=0.001). 2/3 of respondents (n=173, 66%) stated more research on ICU vascular access was needed. Variation in guideline-based vascular access practices exists in the ICU. Defined local protocols may improve guideline adherence. Studies evaluating vascular access decisions and patient safety in the ICU appear necessary.

Estimation of manufacturing development costs of cell-based therapies: a feasibility study

Background aimsCell-based therapies (CBTs) provide opportunities to treat rare and high-burden diseases. Manufacturing development of these innovative products is said to be complex and costly. However, little research is available providing insight into resource use and cost drivers. Therefore, this study aimed to assess the feasibility of estimating the cost of manufacturing development of two cell-based therapy case studies using a CBT cost framework specifically designed for small-scale cell-based therapies. MethodsA retrospective costing study was conducted in which the cost of developing an adoptive immunotherapy of Epstein-Barr virus-specific cytotoxic T lymphocytes (CTLs) and a pluripotent stem cell (PSC) master cell bank was estimated. Manufacturing development was defined as products advancing from technology readiness level 3 to 6. The study was conducted in a Scottish facility. Development steps were recreated via developer focus groups. Data were collected from facility administrative and financial records and developer interviews. ResultsApplication of the manufacturing cost framework to retrospectively estimate the manufacturing design cost of two case studies in one Scottish facility appeared feasible. Manufacturing development cost was estimated at £1,201,016 for CTLs and £494,456 for PSCs. Most costs were accrued in the facility domain (56% and 51%), followed by personnel (20% and 32%), materials (19% and 15%) and equipment (4% and 2%). ConclusionsBased on this study, it seems feasible to retrospectively estimate resources consumed in manufacturing development of cell-based therapies. This fosters inclusion of cost in the formulation and dissemination of best practices to facilitate early and sustainable patient access and inform future cost-conscious manufacturing design decisions.

Tensions between Access and Control in Makerspaces

Makerspaces have complex access control requirements and are increasingly protected through digital access control mechanisms (e.g., keycards, transponders). However, it remains unclear how space administrators craft access control policies, how existing technical infrastructures support and fall short of access needs, and how these access control policies impact end-users in a makerspace. We bridge this gap through a mixed-methods, multi-stakeholder study. Specifically, we conducted 16 semi-structured interviews with makerspace administrators across the U.S. along with a survey of 48 makerspace end-users. We found four factors influenced administrators' construction of access control policies: balancing safety versus access; logistics; prior experience; and, the politics of funding. Moreover, administrators often made situational exceptions to their policies: e.g., during demand spikes, to maintain a good relationship with their staff, and if they trusted the user(s) requesting an exception. Conversely, users expressed frustration with the static nature of access control policies, wishing for negotiability and for social nuance to be factored into access decisions. The upshot is that existing mechanisms for access control in makerspaces are often inappropriately static and socially unaware.

Blockchain-Based IoT Access Control System: Towards Security, Lightweight, and Cross-Domain

Most IoT devices cannot afford to be a blockchain node due to the high computation and storage loads. Thus, the blockchain is usually deployed on one delegate node, e.g., the edge device or cloud, which may encounters three drawbacks: (1) The delegate node becomes the single failure point when the number of delegate notes are limited. (2) The delegate node replicating the blockchain data can lead to privacy information leak. (3) The delegate node is vulnerable to the Distributed Denial of Service (DDoS) attack. To tackle these drawbacks, we consider to minimize the redundant of blockchain to make the IoT devices as the specialized blockchain nodes. In this paper, we integrate a permissioned blockchain (HLF), an attribute-based access control (ABAC) and an identity-based signature (IBS) to build a security, lightweight, and cross-domain blockchain-based IoT access control system. Specifically, we divided the IoT system into different function domains, named IoT domains. Then, we establish a local blockchain ledger for each IoT domain to enable more IoT devices as blockchain nodes. The local blockchain ledger records the IoT domain entities’ attributes, policy files’ digests, and access decisions. Meanwhile, we use the channel technology of HLF to realize cross-domain access and use the IBS to filter the legal access requests for each IoT domain to prevent DDoS attacks. We also design a policy decision point (PDP) selection algorithm that select multiple IoT devices (blockchain nodes) to achieve the real-time distributed policy decisions (off-chain). Finally, we implement and evaluate the proposed system to demonstrate its practicality.

Scaling up the Big Health Data Ecosystem: Engaging all Stakeholders!

There is now an urgent need to scale up our collective capability to learn insights from health data, to improve patient care pathways and health services, to ensure that public health measures and strategies are underpinned by real time evidence, and to accelerate research such as the development of drugs, vaccines and AI algorithms. Europe is investing within and across countries in research infrastructures to enable this scaling up, most frequently through federated architectures. The latest development is the plan from the European Commission to create a European Health Data Space. However, any architecture to combine data or to run distributed queries is critically dependent upon the data being held or mapped to a standardised form (structurally and semantically). Standards exist to achieve this, although more stakeholder engagement is needed in defining practical clinical models and value sets, but the real adoption of interoperability is disappointing and needs further incentivisation and investment. Data quality is another concern that can only be improved if there is awareness that this is important, a willingness to invest and a recognition that many stakeholders need to become motivated to improve quality. Scaling up the uses of data also means involving new actors such as industry. Societal trust is a vital prerequisite for enabling novel uses of data. Transparency is a critical success factor for trust. Data access governance rules must be developed through open public consultation. The bodies who make access decisions must publish information about the data accesses they have permitted. For the public to be on board they have to understand much more than most people do about the nature of health data, how it can be used for the benefit of society and what safeguards protect them when the data are used.

OP544 Appraising Variation In Health Technology Assessment Of Novel Immuno-Oncology Medicines In Australia, Canada, France, And The United Kingdom

IntroductionDemonstrating the value of medicines through health technology assessment (HTA) systems is becoming increasingly complex. Innovative therapies – such as immuno-oncology (IO) agents – are testing limits of methodological approaches in markets with established HTA systems. The objective of this study is to understand how requirements, approaches, and decision-making differ between select HTA agencies with a focus on specific PD-1/PD-L1 (programmed death receptor-1/programmed death-ligand 1) agents and cancer indications, and to describe how this variation impacts patient access. To achieve this objective, we conducted a detailed HTA dossier review for several recently launched IO products across Australia (AU), Canada (CA), France (FR), and the United Kingdom (UK).MethodsContent experts reviewed HTA dossiers for pembrolizumab, nivolumab, and atezolizumab for non-small cell lung cancer (NSCLC) first-line monotherapy, NSCLC combination therapy, and adjuvant melanoma. A systematic analytic framework was developed to understand best-practice methodology across systems. Information on submitted data, patient/expert input, and access decisions were extracted; key themes were identified and refined through workshop discussion, and probed further through blinded primary research with eight individuals with current or recent experience of HTA systems.ResultsWe identified six major elements of variation impacting decision-making: evidentiary expectations for biomarkers, use/impact of patient-centered data; use/impact of real-world data, acceptance of surrogate endpoints, approaches for clinical data extrapolation, and accepted time horizons. Considerable variation in time to access was observed; for pembrolizumab (NSCLC first-line monotherapy), time from product registration to HTA decision ranged from 42 (CA) to 487 (AU) days; time from registration to listing ranged from 189 (CA) to 605 (AU) days.ConclusionsEvaluated HTA systems demonstrate a large degree of variability in approaches to decision-making for novel IO medicines; resultant access decisions and time to access are also highly variable. Inconsistency between systems and duplication of effort when assessing similar clinical/economic data could be contributing to limited or delayed patient access; the relationship merits further exploration. Assessed HTA systems are currently undergoing process revisions but expert input suggests that this is not expected to reduce variation, and could further increase complexity. The influence of parallel scientific advice programs between HTA agencies and regulatory bodies in reducing variation must also be determined.

PRO83 Unmet Need, Strength of Evidence, and Price: IMPACT on Time to Access for Orphan Medicines in England and France

Orphan medicines are often associated with diseases of high unmet need with limited treatment options, thereby warranting rapid patient access. However, time to access for orphan medicines is highly variable, with months to years before an access and pricing decision. This research investigates the impact of disease unmet need, strength of supporting evidence, and price on the time to access for orphan medicines in England and France. 14 therapies with orphan designation and EMA approval (2014-2018) in non-oncology indications were selected. Following a structured literature review they were qualitatively assessed on their unmet need based on available treatment options, and the robustness of supporting clinical and economic evidence. HTA reports and published prices in both countries were reviewed to understand the impact of unmet need, strength of evidence, and price on time to access. Time to HTA decision (EMA approval to draft NICE recommendation/ TC decision) and price negotiation length (draft NICE to final NICE recommendations/ TC to CEPS decision) were considered. Time to HTA decision was <1–26 months in England, and 4–23 months in France. Price negotiations took 3–46+ months in England, and 4–41+ months in France. Strength of evidence had the largest impact; evidence package uncertainty caused extended HTA timelines but had no identifiable impact on length of price negotiation. No relationship between unmet need, or price, on decision timelines were identified. This research shows a trend between strength of evidence and time to HTA decision, but no trend for unmet need or price. None of the three factors had an observable impact on price negotiation timelines. Based on insights from former HTA and pricing committee members, factors such as early engagement, flexibility, and cooperation between the orphan medicine manufacturer and the Health Authority are important for driving faster negotiations. However, this needs validation through future research.

PCN196 Comparison of German Market Access Decisions for Melanoma Based on the Prismaccess Database

PCN196 Comparison of German Market Access Decisions for Melanoma Based on the Prismaccess Database

Deep Reinforcement Learning For Multi-User Access Control in Non-Terrestrial Networks

Non-Terrestrial Networks (NTNs) composed of space-borne (e.g., satellites) and airborne vehicles (e.g., drones and blimps) have recently been proposed by 3GPP as a new paradigm of infrastructures to enhance the capacity and coverage of existing terrestrial wireless networks. The mobility of non-terrestrial base stations (NT-BSs) however leads to a dynamic environment, which imposes unique challenges for handover and throughput optimization particularly in multi-user access control for NTNs. To achieve performance optimization, each terrestrial user equipment (UE) should autonomously estimate the dynamics of moving NT-BSs, which is different from the existing user access control schemes in terrestrial wireless networks. Consequently, new learning schemes for optimum multi-user access control are desired. In this article, we therefore propose a UE-driven deep reinforcement learning (DRL) based scheme, in which a centralized agent deployed at the backhaul side of NT-BSs is responsible for training the parameter of a deep Q-network (DQN), and each UE independently makes its own access decisions based on the parameter from the trained DQN. With the proposed scheme, each UE is able to access a proper NT-BS intelligently to enhance the long-term system throughput and avoid frequent handovers among NT-BSs. Through comprehensive simulation studies, we justify the performance of the proposed scheme, and show its effectiveness in addressing the fundamental issues in the NTNs deployment.

Evidence-based treatment recommendations for neck and low back pain across Europe: A systematic review of guidelines.

Background and objectiveThis systematic review synthesized evidence from European neck and low back pain (NLBP) clinical practice guidelines (CPGs) to identify recommended treatment options for use across Europe.Databases and Data TreatmentComprehensive searches of thirteen databases were conducted, from 1st January 2013 to 4th May 2020 to identify up‐to‐date evidence‐based European CPGs for primary care management of NLBP, issued by professional bodies/organizations. Data extracted included; aim and target population, methods for development and implementation and treatment recommendations. The AGREE II checklist was used to critically appraise guidelines. Criteria were devised to summarize and synthesize the direction and strength of recommendations across guidelines.ResultsSeventeen CPGs (11 low back; 5 neck; 1 both) from eight European countries were identified, of which seven were high quality. For neck pain, there were consistent weak or moderate strength recommendations for: reassurance, advice and education, manual therapy, referral for exercise therapy/programme, oral analgesics and topical medications, plus psychological therapies or multidisciplinary treatment for specific subgroups. Notable recommendation differences between back and neck pain included, i) analgesics for neck pain (not for back pain); ii) options for back pain‐specific subgroups—work‐based interventions, return to work advice/programmes and surgical interventions (but not for neck pain) and iii) a greater strength of recommendations (generally moderate or strong) for back pain than those for neck pain.ConclusionsThis review of European CPGs identified a range of mainly non‐pharmacological recommended treatment options for NLBP that have broad consensus for use across Europe.SignificanceConsensus regarding evidence‐based treatment recommendations for patients with neck and low back pain (NLBP) from recent European clinical practice guidelines identifies a wide range of predominantly non‐pharmacological treatment options. This includes options potentially applicable to all patients with NLBP and those applicable to only specific patient subgroups. Future work within our Back‐UP research team will transfer these evidence‐based treatment options to an accessible clinician decision support tool for first contact clinicians.

Promoting health equity through the built environment in Duluth, MN: External Resources and Local Evolution Toward Health in All Policies.

Communities, professionals, and researchers recognize that environmental factors contribute to the health inequities experienced by vulnerable populations in the U.S. These environmental health injustices persist despite well-developed systems for both public health and environmental protection. The root cause of these issues is often "siloed" decision-making by separate health and environmental institutions. Health Impact Assessment (HIA) can be an important tool for bridging these silos to promote health equity at the local level. This raises the question: how can external resources best support local initiatives? This paper examines the interaction between national, state, and non-governmental efforts to promote HIA and local actions to promote healthy and equitable built environment in Duluth, MN. A wide range of local activities in Duluth aimed to alter the long term trends, decision processes, and institutions shaping its built environment. These included integrating health in brownfield redevelopment, local land use plans, food access, and transportation decisions. Technical and financial support from external groups played a key role in developing the community's capacity to promote health equity across public, private, and non-profit organizations. These multiple streams of action culminated in the mayor's declaration in 2016 that health and fairness would be adopted as key goals of the city's new Comprehensive Plan. How did such innovative efforts thrive in a small, post-industrial city with limited resources? Duluth's experiences provide insight into how external governmental, funding, academic, and non-profit entities can more effectively, efficiently, and equitably support the evolution of local initiatives.

Managing flood flow connectivity to landscapes to build buffering capacity to disturbances: An ecohydrologic modeling framework for drylands

Increased flooding, droughts, and sediment transport are watershed-scale problems negatively impacting agriculture and ecosystems in drylands worldwide. Vegetation loss in upland watersheds is leading to scouring floods, which in turn decreases infiltration, soil moisture levels, and downstream groundwater recharge. Management to confront these intractable problems has been hindered by a lack of accessible decision support tools for both land and water managers that synthesize the watershed processes that buffer against dryland disturbances. Flood flow connectivities across the landscape create buffer zones through replenishing soil moisture and reducing flood energy, which in turn support multiple functions. This study developed a decision support tool, the Flood Flow Connectivity to the Landscape (FlowCon) framework that quantifies the most efficient management efforts to increase the key watershed buffering functions of increasing infiltration and reducing flow energy. FlowCon links three spatially explicit, process-based, and predictive models to answer two critical management questions: what key processes acting in what optimal areas are drivers of infiltration dynamics and what roles do peak flows of differing scales of energy play. The spatial models delineated the buffer zone to characterize the heterogeneous and optimal infiltration dynamics across the landscape. The hydrologic process model, using a curve number technique, identified the key ecohydrologic processes that affect infiltration and characterized peak flows and flow regime variability. The predictive flood routing model quantified the potential management benefits. We calibrated the models with measured runoff and the corresponding rainfall events for a six-year period, which included thirty-six flow events. The synthesized ecohydrologic indicators provided critical calibrations, improving the relationship between the hydrologic modeling results and observed data by 12% for the linear regression R2 and 69% for the root mean square error (RMSE). Implementation of prioritized management is estimated to reduce peak flow by half, with interventions focused on 24% of floodplains that infiltrate three times the flow volume per area than the floodplain average. FlowCon provides an efficient assessment framework that integrates watershed process understanding in an accessible decision support tool to achieve tangible improvements in dryland watershed management.