Evidence-based Decision Support Tool Research Articles

Preventing Eviction-Caused Homelessness through ML-Informed Distribution of Rental Assistance

Rental assistance programs provide individuals with financial assistance to prevent housing instabilities caused by evictions and avert homelessness. Since these programs operate under resource constraints, they must decide who to prioritize. Typically, funding is distributed by a reactive allocation process that does not systematically consider risk of future homelessness. We partnered with Anonymous County (PA) to explore a proactive and preventative allocation approach that prioritizes individuals facing eviction based on their risk of future homelessness. Our ML models, trained on state and county administrative data accurately identify at-risk individuals, outperforming simpler prioritization approaches by at least 20% while meeting our equity and fairness goals across race and gender. Furthermore, our approach would reach 28% of individuals who are overlooked by the current process and end up homeless. Beyond improvements to the rental assistance program in Anonymous County, this study can inform the development of evidence-based decision support tools in similar contexts, including lessons about data needs, model design, evaluation, and field validation.

QLTI-09. INTEGRATION OF NEURO-ONCOLOGY CLINICAL PATHWAYS IN PROVIDENCE SOUTHERN CALIFORNIA CLINICAL RESEARCH NETWORK: UPDATED INFO AFTER 17 MONTHS OF UTILIZATION

Abstract INTRODUCTION ClinicalPath is an evidence-based oncology decision support and analytics tool for cancer care. ClinicalPath’s treatment recommendations are prioritized based on efficacy, toxicity, and cost, by a nationwide committee of oncologists. The pathways are updated quarterly with the most recent evidenced-based treatment options that healthcare providers choose for adoption to help standardize therapy, improve quality, and decrease cost. The pathway system also allows for local clinical trial mapping to promote clinical trial awareness and help increase enrollment. ClinicalPath provides clinical pathways delivering personalized, evidence-based oncology guidance at the point of care. ClinicalPath’s network in North America serves more than 2,000 cancer physicians, within 54 practices in 31 states (15 academic medical centers, 29 hospital systems, and 9 community practices). Population: Our population is derived from multiple hospitals in Southern California within the Providence Health System. Methodology: Medical oncologists and Advanced Practice Providers received training on ClinicalPath before go-live. ClinicalPath was integrated into the Epic EHR in multiple Southern CA hospitals in a single month in Jan 2022. RESULTS On reviewing the utilization data within our Southern California region from Jan 2022-May 2023, 2681 treatment decisions were made across all cancers, with 86.7% of cancer patients treated on pathway. Of these decisions, 114 were made within the neuro-oncology specialty, and 70.2% of those cancer patients were treated on pathway. CONCLUSION We successfully integrated and initiated ClinicalPath in a multiple hospital-affiliated community oncology clinical trial network which included a strong neuro-oncology presence. We are actively working across our Southern California Region to map locally available clinical trials to promote awareness and increase enrollment. Provider utilization and patient on-pathway rates are actively monitored and will be updated.

Integration of breast-oncology clinical pathways in Providence Southern California clinical research network.

e18710 Background: ClinicalPath is an evidence-based oncology decision support and analytics tool for cancer care. ClinicalPath’s treatment recommendations are prioritized based on efficacy, toxicity, and cost by a nationwide committee of oncologists. The pathways are updated quarterly and are expected to speed the integration of new treatments into practice, standardize therapy, improve quality, and decrease cost. The pathway system also allows for local clinical trial mapping to promote clinical trial awareness and increase enrollment. ClinicalPath provides clinical pathways delivering personalized, evidence-based oncology guidance at the point of care. ClinicalPath’s network in North America serves more than 2,000 cancer physicians, within 54 practices in 31 states (15 academic medical centers, 29 hospital systems, and 9 community practices). Methods: Providence’s Population: Our population is derived from multiple hospitals in Southern California within the Providence Health System. Methodology: Medical oncologists and Advanced Practice Providers received training on ClinicalPath before go-live. ClinicalPath was integrated into the Epic EHR in multiple Southern CA hospitals in a single month. Results: After 4 months of utilization within our Southern California region, 342 treatment decisions were made across all cancers, and 85.1% of cancer patients were treated on pathway. Of which, 103 treatment decisions were made within the breast-oncology specialty, and 93.2% of those cancer patients were treated on pathway. Conclusions: We successfully integrated and initiated ClinicalPath in a multiple hospital-affiliated community oncology clinical trial network. We are actively working across our Southern California Region to map locally available clinical trials to promote awareness and increase enrollment. Provider utilization and patient on-pathway rates are actively monitored.

OC-0602 Development of an evidence-based adjuvant treatment decision support tool for endometrial cancer

OC-0602 Development of an evidence-based adjuvant treatment decision support tool for endometrial cancer

Decision Analysis in SHared decision making for Thromboprophylaxis during Pregnancy (DASH-TOP): a sequential explanatory mixed-methods pilot study

ObjectivesTo gain insight into formal methods of integrating patient preferences and clinical evidence to inform treatment decisions, we explored patients’ experience with a personalised decision analysis intervention, for prophylactic low-molecular-weight...

A Novel Approach to Delivering Evidence-based, High-quality Care in Psychiatry Through an Electronic Integrated Care Pathway (eICP) Pilot.

Integrated care pathways (ICPs) are evidence-based decision support tools intended to reduce variation and improve quality of care. Historically, adoption of ICPs has been difficult to measure, as the pathways were outside of the electronic health record (EHR), where care delivery documentation and orders were completed. This Technology Column describes the innovative development and implementation of a diagnosis specific electronic ICP that directly embeds pathway steps into an EHR to facilitate order sets, clinical decision-making, and usage tracking. The pathway was implemented at a seven-hospital academic medical center, and details the technology, team structure, early adoption results, and future directions. As such, the importance of investing and organizing resources to create an eICP (e.g., time, technology, and specialized teams) to provide a user-friendly experience to support early adoption is underscored. Preliminary findings show that the eICP had consistent use in the first year of implementation. This manuscript is intended to serve as a practical guide to build eICPs within behavioral health service areas across institutions.

QLTI-26. INTEGRATION OF NEURO-ONCOLOGY CLINICAL PATHWAYS IN PROVIDENCE SOUTHERN CALIFORNIA CLINICAL RESEARCH NETWORK

Abstract INTRODUCTION ClinicalPath is an evidence-based oncology decision support and analytics tool for cancer care. ClinicalPath’s treatment recommendations are prioritized based on efficacy, toxicity, and cost by a nationwide committee of oncologists. The pathways are updated quarterly and are expected to speed the integration of new treatments into practice, standardize therapy, improve quality, and decrease cost. The pathway system also allows for local clinical trial mapping to promote clinical trial awareness and increase enrollment. ClinicalPath provides clinical pathways delivering personalized, evidence-based oncology guidance at the point of care. ClinicalPath’s network in North America serves more than 2,000 cancer physicians, within 54 practices in 31 states (15 academic medical centers, 29 hospital systems, and 9 community practices). Population: Our population is derived from multiple hospitals in Southern California within the Providence Health System. Methodology: Medical oncologists and Advanced Practice Providers received training on ClinicalPath before go-live. ClinicalPath was integrated into the Epic EHR in multiple Southern CA hospitals in a single month. RESULTS After 3 months of utilization within our Southern California region, 342 treatment decisions were made across all cancers, and 85.1% of cancer patients were treated on pathway. Of which, 7 treatment decisions were made within the neuro-oncology specialty, and 85.7% of those cancer patients were treated on pathway. CONCLUSION We successfully integrated and initiated ClinicalPath in a multiple hospital-affiliated community oncology clinical trial network. We are actively working across our Southern California Region to map locally available clinical trials to promote awareness and increase enrollment. Provider utilization and patient on-pathway rates are actively monitored and will be updated.

Risk-based decision-making related to preprocedural coronavirus disease 2019 testing in the setting of GI endoscopy: management of risks, evidence, and behavioral health economics

Background and AimsControversies exist regarding the benefits and most appropriate approach for preprocedural coronavirus disease 2019 (COVID-19) testing (eg, rapid antigen test, polymerase chain reaction, or real-time polymerase chain reaction) for outpatients undergoing diagnostic and therapeutic procedures, such as GI endoscopy, to prevent COVID-19 infections among staff. Guidelines for protecting healthcare workers (HCWs) from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection from outpatient procedures varies across medical professional organizations. This study provides an evidence-based decision support tool for key decision-makers (eg, clinicians) to respond to COVID-19 transmission risks and reduce the effect of personal biases.MethodsA scoping review was used to identify relevant factors influencing COVID-19 transmission risk relevant for GI endoscopy. From 12 relevant publications, 8 factors were applicable: test sensitivity, prevalence of SARS-CoV-2 in the population, age-adjusted SARS-CoV-2 prevalence in the patient cohort, proportion of asymptomatic patients, risk of transmission from asymptomatic carriers, risk reduction by personal protective equipment (PPE), vaccination rates of HCWs, and risk reduction of SAE by vaccination. The probability of a serious adverse event (SAE), such as workplace-acquired infection resulting in HCW death, under various scenarios with preprocedural testing was determined to inform decision-makers of expected costs of reductions in SAEs.ResultsIn a setting of high community transmission, without testing and PPE, 117.5 SAEs per million procedures were estimated to occur, and this was reduced to between .079 and 2.35 SAEs per million procedures with the use of PPE and preprocedural testing. When these variables are used and a range of scenarios are tested, the probability of an SAE was low even without testing but was reduced by preprocedural testing.ConclusionsUnder all scenarios tested, preprocedural testing reduced the SAE risk for HCWs regardless of the SARS-CoV-2 variant. Benefits of preprocedural testing are marginal when community transmission is low (eg, below 10 infections a day per 100,000 population). The proposed decision support tool can assist in developing rational preprocedural testing policies.

Human factors applications in the design of decision support systems for population health: a scoping review

IntroductionPublic health professionals engage in complex cognitive tasks, often using evidence-based decision support tools to bolster their decision-making. Human factors methods take a user-centred approach to improve the design of...

Patient Perspective: We have embraced digital technologies to support arrhythmia patients during the COVID-19 pandemic

Patient Perspective: We have embraced digital technologies to support arrhythmia patients during the COVID-19 pandemic

Development of the Exercise in Cancer Evaluation and Decision Support (EXCEEDS) algorithm

Participation in exercise or rehabilitation services is recommended to optimize health, functioning, and well-being across the cancer continuum of care. However, limited knowledge of individual needs and complex decision-making are barriers to connect the right survivor to the right exercise/rehabilitation service at the right time. In this article, we define the levels of exercise/rehabilitation services, provide a conceptual model to improve understanding of individual needs, and describe the development of the Exercise in Cancer Evaluation and Decision Support (EXCEEDS) algorithm. From literature review, we synthesized defining characteristics of exercise/rehabilitation services and individual characteristics associated with safety and efficacy for each service. We developed a visual model to conceptualize the need for each level of specialized care, then organized individual characteristics into a risk-stratified algorithm. Iterative review with a multidisciplinary expert panel was conducted until consensus was reached on algorithm content and format. We identified eight defining features of the four levels of exercise/rehabilitation services and provide a conceptual model of to guide individualized navigation for each service across the continuum of care. The EXCEEDS algorithm includes a risk-stratified series of eleven dichotomous questions, organized in two sections and ten domains. The EXCEEDS algorithm is an evidence-based decision support tool that provides a common language to describe exercise/rehabilitation services, a practical model to understand individualized needs, and step-by-step decision support guidance. The EXCEEDS algorithm is designed to be used at point of care or point of need by multidisciplinary users, including survivors. Thus, implementation may improve care coordination for cancer exercise/rehabilitation services.

Triaging online child abuse material: testing a decision support tool to enhance law enforcement and investigative prioritisation

PurposeOnline production and transmission of child abuse material (CAM) is a complex and growing global problem. The exponential increase in the volume of CyberTips of CAM offending is placing information processing and decision-making strains on law enforcement. This paper presents the outcomes of a project that reviewed an existing risk assessment tool and then developed a new tool for CAM triaging and investigative prioritisation.Design/methodology/approachUsing a mixed method approach, the authors first explored the capacity of an existing risk assessment tool for predicting a police action. The authors then used these findings to design and implement a replacement CAM decision support tool. Using a random sample of CyberTip alert cases from 2018, the authors then tested the efficiency of the new tool.FindingsThe existing risk assessment tool was not fit for CAM triaging purposes. Just six questions from the old tool were found to be statistically and significantly associated with law enforcement agents achieving a police action. The authors found that an immediate threat of abuse/endangering a child, potential case solvability, CAM image assessment, chat assessment, criticality and some weighting for professional judgement were significant in being associated with a police action. The new decision support tool is more efficient to complete and achieved a 93.6% convergence of risk ratings with the old tool using 2018 case data.Originality/valueThis research is unique in its development of an evidence-based decision support tool that enhances the ability of law enforcement agents to objectively and efficiently triage and prioritise increasing numbers of CyberTip alerts.

Cultivating our urban forest future: a value-chain perspective

For cities to grow their urban forest canopy the formula appears rather straightforward: the right trees, plus the right conditions, plus the right care equals success. These simplified “tree chain of custody” steps, however, represent activities within a complex value-chain in Canada. Given that there is heightened demand for urban tree planting as natural climate solutions become the norm, how can we prepare the value-chain to meet these demands? To answer this question, we outline the pathways by which trees presently go from nurseries into urban and peri-urban areas. Delineating the actors, roles, and present barriers to success exposes the complexity of the process and relationships in the value-chain, as there are distinct phases with multiple actor groups involved who influence, and are influenced, by one another. We explore the issues that pose prominent challenges to, as well as opportunities for, the value-chain. Emergent themes include communication, forecasting demand and timing, underpricing and undervaluing tree establishment, lack of awareness on the importance of soils, juvenile tree health, species selection, and gaps in evidence-based decision support tools. The touchstones of science and innovation, collaboration, and knowledge mobilization are pertinent for the value-chain in Canada to draw upon to navigate the future.

Prosilience trajectories of phoenix regions: a narrative on intelligent transformation of old mining areas

This paper departs from the regional resilience concept - as part of a broad strand of literature on non-linear dynamic systems in a space-economy - and introduces the notion of prosilience to highlight the policy challenge of developing radically new and innovative strategies for regions in decline. The mining industry will be used as an illustrative case. The notion of phoenix regions is put forward to argue that an external disruption or shock in an established industrial sector in a region necessitates unconventional survival strategies oriented towards entirely new market demands and based on totally different product packages. Ansoff's model on product diversification in competitive markets forms an inspiration source for the Schumpeterian 'creative destruction' proposition advocated in this study. An illustrative case study is concisely described in the present paper, viz. the South-Limburg coal mining region in the Southern part of the Netherlands. Smart prosilience trajectories supported in particular by evidence-based decision support tools are sketched for such depressed regions, based on the so-called Pentagon intervention model. The paper is concluded with some general policy lessons for an intelligent transformation of regions in decline.

Long-term prognostic counselling in people with multiple sclerosis using an online analytical processing tool

Background: Prognostic counselling is a sensitive issue in medicine and especially so in MS due to the highly heterogeneous disease course. However, people with MS (pwMS) seek prognostic information. The web-based ‘Evidence-Based Decision Support Tool in Multiple Sclerosis’ (EBDiMS) uses data of 717 patients from the London/Ontario cohort to calculate personalized long-term prognostic information. Objective: The aim of this study was to investigate the feasibility and effect of long-term prognostic counselling in pwMS using EBDiMS. Methods: Ninety consecutive pwMS were provided with personalized estimations of expected time to reach Expanded Disability Status Scale (EDSS) scores of 6 and 8 and time to conversion to secondary-progressive MS. Participants gave estimates on their own putative prognosis and rated the tool’s acceptability on six-step Likert-type scales. Results: Participants rated EBDiMS as highly understandable, interesting and relevant for patient–physician encounters, coping and therapy decisions. Although it provoked a certain degree of worry in some participants, 95% would recommend using the tool. Participants’ own prognosis estimates did not change significantly following EBDiMS. Conclusion: Long-term prognostic counselling using an online tool has been shown to be feasible in a clinical setting. EBDiMS provides pwMS with relevant, easy-to-understand, long-term prognostic information without causing relevant anxiety.

Anaphylaxis in primary care: Systematic review to support quality of management and optimization of health-care pathways

Anaphylaxis is a severe, life-threatening systemic hypersensitivity reaction characterized by rapid onset and the potential to endanger life. Most of cases of anaphylaxis are first seen by general practitioners (GPs) or emergency doctors. This systematic review is intended to provide evidence-based decision support tools to GPs confronted with anaphylactic patients. We searched MEDLINE, EMBASE, Cochrane Controlled Register of Trials, Lilacs databases from inception from 1988, for manuscripts concerning anaphylaxis and primary care, without language restrictions. We screened studies, extracted data, and assessed risk of bias independently in duplicate. The manual review was performed by two independent ratters. The degree of inter-rater agreement was assessed using Cohen’s kappa. Main outcomes included clinical history, clinical examination, treatment, use of epinephrine and timing to refer the patient to the specialist. We selected 56 studies, comprising 37 original articles, 15 reviews and 4 guidelines. Twenty-three (41%) were focused on specific aetiology: food-induced anaphylaxis (FA) (52%), drug allergy (DA) (35%) and venom allergy (VA) (13%). With a kappa value of 0.67, there was a high agreement on the classification procedures between the two raters. Data showed that in the presence of respiratory and/or cardiovascular symptoms, patients should be promptly treated and sent to the emergency room. Structured clinical history was reported as being mandatory for the diagnosis of anaphylaxis, mainly based on 5 key points: type of manifestations, type of trigger, chronology between reaction and suspected allergen, reproducibility and risk factors. Most documents (44%) covered food-induced anaphylaxis occurring in childhood, with suspected IgE-mediated reaction. Most anaphylaxis in adults were related to DA or VA (48%). Data still stress lack of the recognition of manifestations (48%), treatment with anti-histamines and systemic corticosteroids (26%), delayed application of epinephrine (35%) and highlight the need of decision aids to support diagnosis and anaphylaxis by GPs (38%). GPs should advise an emergency plan and prescribe adrenaline auto-injectors. Reasons for referring to specialists based on the literature are: to investigate aetiology, to undergo specific treatment, such as allergen immunotherapy, severe cases or in suspicion of underlying condition, such as mastocytosis. Evidence presented supports the construction of a decision tree in order to improve management of anaphylaxis. This intends to optimize the life-time of these patients across the health care pathways and prevent avoidable deaths. It is intended that the resultant decision support tool will undergo field-testing for validation.

Evidence-Synthesis Tools to Inform Evidence-Based Physiatry.

Evidence-Synthesis Tools to Inform Evidence-Based Physiatry.

More data, more questions: No simple answer about which children should undergo screening neuroimaging for clinically occult abusive head trauma

Abusive head trauma (AHT) is the leading cause of fatal child physical abuse. Victims may initially present with clinically occult AHT without overt signs of head trauma or with only subtle, nonspecific symptoms, which can make timely recognition of AHT challenging. Research has shown missed opportunities for early detection of AHT in the medical setting are common and can lead to repeated injury. Neuroimaging is needed to diagnose clinically occult AHT but is not without risk. Researchers have worked to understand the yield of neuroimaging in detection of clinically occult AHT and to identify risk factors, yet findings have varied widely across studies. Identifying which children undergoing physical abuse evaluations are at highest risk of clinically occult AHT is key to development of evidence-based imaging decision support tools for clinicians. Here we discuss the recent literature, identify potential reasons for variation across studies, and offer opportunities for future research.

Use of a Decision Support Tool on Prognosis of Work Ability in Work Disability Assessments: An Experimental Study Among Insurance Physicians

Purpose Assessment of prognosis of work disability is a challenging task for occupational health professionals. An evidence-based decision support tool, based on a prediction model, could aid professionals in the decision-making process. This study aimed to evaluate the efficacy of such a tool on Dutch insurance physicians’ (IPs) prognosis of work ability and their prognostic confidence, and assess IPs’ attitudes towards use of the tool. Methods We conducted an experimental study including six case vignettes among 29 IPs. For each vignette, IPs first specified their own prognosis of future work ability and prognostic confidence. Next, IPs were informed about the outcome of the prediction model and asked whether this changed their initial prognosis and prognostic confidence. Finally, respondents reported their attitude towards use of the tool in real practice. Results The concordance between IPs’ prognosis and the outcome of the prediction model was low: IPs’ prognosis was more positive in 72 (41%) and more negative in 20 (11%) cases. Using the decision support tool, IPs changed their prognosis in only 13% of the cases. IPs prognostic confidence decreased when prognosis was discordant, and remained unchanged when it was concordant. Concerning attitudes towards use, the wish to know more about the tool was considered as the main barrier. Conclusion The efficacy of the tool on IPs’ prognosis of work ability and their prognostic confidence was low. Although the perceived barriers were overall limited, only a minority of the IPs indicated that they would be willing to use the tool in practice.

Systematic screening as a tool for individualized rehabilitation following primary breast cancer treatment: study protocol for the ReScreen randomized controlled trial

BackgroundIt is well known that women suffer from negative consequences following breast cancer (BC) treatment and that their largely varying needs for rehabilitation are often unmet. Up to 43% of these women are at risk of developing chronic distress requiring complex interventions; however, how to early identify and meet these women’s needs is unknown, leaving them with suboptimal chances of rehabilitation. The aim of the ReScreen study is to develop a model for and evaluate the effect of screening-based, individualized rehabilitation following primary BC treatment.MethodsThe ReScreen study is designed as a complex intervention. Women with newly diagnosed BC are consecutively included in a three-armed randomized controlled trial. At inclusion, patients score their distress level on the Distress Thermometer (scale of 0–10) aiming to identify patients with extended rehabilitation needs. Patients scoring ≥5 are randomized to the intervention or control group while patients scoring ≤4 are followed longitudinally as an observational group. Patients in the intervention group, in conjunction with a dedicated research nurse, create an individualized rehabilitation plan based on an evidence-based decision support tool that was developed to create a solid base for the intervention. The research nurse will act as a continuous health care contact and be responsible for proactively and systematically evaluating patients’ needs to ensure that potential new problems or changed rehabilitation needs are identified throughout the 1-year follow-up period. The intervention will be evaluated through self-reported data focusing on physical and psychological outcomes as well as evaluation of satisfaction with care at baseline, 2 weeks and 3, 6, 9 and 12 months. Evaluation will also include health economic aspects based on register data and patients’ and relatives’ experiences of the rehabilitation process. In addition, optimal cut-off levels for distress as an indicator for extended rehabilitation needs will be investigated.DiscussionThis study will provide important knowledge related to effectiveness of screening-based identification of rehabilitation needs and standardized evidence-based, individualized rehabilitation after primary BC treatment. With a complex intervention design, this study has the potential to form a comprehensive knowledge base which includes tools and guidelines for implementation into clinical practice.Trial registrationClinicalTrials.gov NCT03434717. Registered February 15, 2018.