Provide Decision Support Tools Research Articles

Taking Shared Decision Making from Concept to Clinical Practice: What Do Sickle Cell Healthcare Providers Need?

Introduction:The landscape of therapies for sickle cell disease (SCD) is rapidly evolving. While hydroxyurea remains the gold standard treatment, since 2017 the FDA has approved three additional drugs (i.e., L-glutamine, voxelotor, crizanlizumab), and many others are under investigation. Thus, new therapies and multi-agent treatment approaches for SCD are on the horizon, along with increasingly complex treatment decisions for patients, caregivers, and clinicians. Best practice SCD guidelines recommend shared decision making (SDM; NHLBI, 2014) and SCD patients and caregivers strongly prefer a SDM approach when considering disease-modifying therapies (Jabour et al., 2019; Ross et al., 2016). SDM is a collaborative process in which patients, caregivers, and clinicians work in partnership to reach healthcare decisions based on scientific evidence and the patient's/caregiver's values, preferences, and treatment goals (Stiggelbout et al., 2012). SDM enhances patient and parent knowledge, engagement in the decision making process, and satisfaction with care (Stacey et al., 2014; Wyatt et al., 2015) and is particularly beneficial for marginalized groups (Durand et al., 2014). Evidence also suggests positive impacts of SDM on more distal outcomes, including adherence to the selected treatment (Hauser et al., 2015; Joosten et al., 2008) and health outcomes (Hauser et al., 2015; Tapp et al., 2017). However, few tools are available to facilitate SDM for SCD therapies (Crosby et al., 2019), and most healthcare providers who care for youth with SCD have not had specific training in SDM (Yawn et al., 2014). This study examined clinician perspectives on resources needed to foster SDM in the context of disease-modifying treatment decisions for SCD. Methods:SCD providers were recruited from across the United States using maximum variation purposeful sampling to ensure diversity in provider characteristics (age, sex, race, discipline, years in profession) and clinics (region, patient volume). After electronic consent, providers completed a demographics survey and joined a private online “crowd” on Slack. There were five waves of data collection; during each wave, a series of 4-5 questions were posed to the crowd. Providers were paid for each question they answered and encouraged to view and respond to others' posts. Thematic content analysis was used to summarize perspectives on resources needed to help healthcare providers better engage patients and caregivers in SDM for sickle cell therapies. Two raters independently coded each provider's responses; coding discrepancies were resolved via group discussion to consensus. Results:Of the 59 SCD providers who enrolled, approximately two-thirds were female (67%) and 61% were White; the remainder of the sample identified as Asian (20%), Black or African American (10%), or Middle Eastern (3%). Most were non-Hispanic or Latino (95%). Providers included physicians (73%), nurse practitioners or advanced practice nurses (22%), and nurses (5%) with a wide range of years in practice (2 - 57, M=12.8, SD=10.6). Providers were employed at care centers serving pediatric patients (37%), adult patients (29%), or both pediatric and adult patients with SCD (34%), with annual patient volume ranging from 16 to 2200 (M=420.5, SD=405.1). Across the waves of data collection, response rates ranged from 53-59%. These clinicians identified five resources necessary to optimize SDM for disease-modifying therapies: 1) well-staffed multidisciplinary care teams; 2) high quality patient education materials; 3) billing and reimbursement policies that incentivize SDM; 4) resources to address social determinants of health barriers; and, 5) peer mentoring and support programs for patients. See Table 1 for illustrative quotes. Conclusions:Providers identified several supports and resources to facilitate SDM with individuals with SCD. Findings from this study will inform the development of a multi-component SDM intervention, including decision support tools for patients, caregivers, and healthcare providers and clinic-based implementation tools. Acknowledgements: This research was supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number P20GM109021. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Abstract B049: Perceptions of gastric cancer screening in Asian Americans

Abstract Background: Endoscopy of the upper gastrointestinal tract is an effective way to screen for gastric cancer (GC) and benefits of screening are evident in countries that have implemented nationwide screening. Despite being disproportionately affected by GC, Asian Americans lack knowledge of GC risk factors and resources to make informed decision on GC screening. Experts recommend shared decision making between providers and patients regarding endoscopy for GC screening. However, we lack decision support tools for providers and patients at high risk for GC. Objective: This qualitative study aims to 1) explore patient experiences and perspectives on GC screening with endoscopy on concepts such as perceived GC risk, risk factors, early detection methods, and healthcare navigation, 2) explore provider knowledge, beliefs, and practice patterns regarding GC screening and GC prevention, and 3) develop a decision aid to support shared decision making for GC screening in the Asian American population. Methods: We interviewed primary care providers [PCP] and gastroenterologists in medical networks in Southern California that primarily serve Asian American communities, and patient populations in these medical networks with an initial focus on Korean and Vietnamese Americans who face the highest risk of GC among Asian Americans. Qualitative data was collected using one-on-one interviews with patients and providers. The interview was then transcribed and coded following reflexive thematic analysis. Results: To date, we have interviewed 6 patients and 5 providers and data collection continues. Several key themes were identified during the interviews: Among patients there is a lack of understanding of Helicobacter pylori (H. pylori) as a risk factor for GC, while dietary factors were frequently perceived as risk factors. Providers found GC screening to be beneficial for Korean and Vietnamese populations, and recommended GC screening simultaneous to screening colonoscopy, to reduce patient burden and cost. Patients who had experience with upper endoscopy found it to be acceptable. On the other hand, patients’ desired costs for upper endoscopy were much lower than market out-of-pocket costs of endoscopy. A preliminary decision aid was developed and edited in response to the results. The decision aid presents educational information including risk of GC in Korean and Vietnamese American relative to the general U.S. population, risk factors of GC, GC screening procedures, and risks and benefits of screening. The decision aid offers opportunity to assess personal attitudes towards GC screening, and allows for patients to indicate their intentions for GC screening for discussion with their providers. The decision aid will be further refined with additional qualitative data. Conclusion: Perceptions towards GC screening is generally positive among Asian patients and providers, but the costs of screening are a concern. Patients need education on H. pylori as a risk factor for GC. Citation Format: Simon Kim, Christie Y. Jeon, Celina Shirazipour. Perceptions of gastric cancer screening in Asian Americans [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr B049.

Split Liver Transplantation: An Analytical Decision Support Model

Split liver transplantation (SLT) is a procedure that can potentially save two lives using one liver, thus increasing the total utility derived from the limited number of donated livers available. It also can potentially improve equity, by giving transplant candidates who are physically smaller (including children) increased access to liver transplants. However, SLT is rarely used in the US. To help quantify the benefits of increased utilization of SLT and provide decision support tools, we introduce a deceased-donor liver allocation model with both efficiency and fairness objectives. In this model we formulate a multi-queue fluid system, incorporating the specifics of donor-recipient size matching and patients’ dynamically changing Model for End-Stage Liver Disease scores. Leveraging a novel decomposition result we find the optimal matching, enabling us to benchmark the performance of different allocation policies. Numerical results, utilizing data from UNOS, show that SLT can significantly increase total quality-adjusted life years, reduce patient deaths, and improve fairness among different patient groups.

Abstract PS8-05: Randomized controlled trial of decision support tools for patients and providers to increase breast cancer chemoprevention

Abstract Background: Breast cancer chemoprevention with selective estrogen receptor modulators (SERMs) and aromatase inhibitors (AIs) have been shown in randomized controlled trials to reduce breast cancer incidence by 50-65% among high-risk women. However, chemoprevention is still underutilized with fewer than 5% of high-risk women offered chemoprevention agreeing to take the medications. Reasons for low chemoprevention uptake include inadequate knowledge about chemoprevention among patients and healthcare providers, concerns about side effects, competing comorbidities, and time constraints during the clinical encounter. To address these barriers to chemoprevention uptake, we developed decision support tools for patients and providers. Methods: We conducted a randomized controlled trial of standard educational materials alone or combined with web-based decision support tools, RealRisks and BNAV, among 300 high-risk women and 50 healthcare providers, respectively. Patient eligibility criteria included: 1) women, age 35-75 years; 2) high-risk for breast cancer, defined as a 5-year invasive breast cancer risk ≥1.67% according to the Gail model or history of lobular carcinoma in situ (LCIS); 3) no prior use of a SERM or AI; 4) No personal history of breast cancer; 5) Access to the internet. Providers included primary care providers, such as internists, family practitioners, gynecologists, and nurse practitioners, and specialists, such as breast surgeons and medical oncologists. The RealRisks decision aid (DA) is available in English and Spanish and includes interactive modules to communicate personalized breast cancer risk and the risks and benefits of chemoprevention. The BNAV tool includes self-paced learning modules on breast cancer risk factors and chemoprevention and was made available to all providers through the electronic health record (EHR) dashboard. The primary endpoint was chemoprevention uptake at 6 months as assessed via the EHR. Secondary outcomes included validated measures of perceived breast cancer risk, breast cancer worry, chemoprevention knowledge, self-efficacy, decision conflict, chemoprevention attitudes, intention, and informed choice, which were administered to patients at baseline, 1 month, and 6 months after randomization. Results: Among 282 evaluable high-risk women enrolled from November 2016 to March 2020, mean age was 57 years (SD, 9.9), including 59% white, 14% black, 21% Hispanic, and 6% other. Mean 5-year invasive breast cancer risk was 2.98% (SD, 1.42), including 67% of women with benign breast disease and 64% with a first-degree family history of breast cancer. Comparing the intervention and control arms at 1 month, there were significant differences among high-risk women in accurate breast cancer risk perceptions (56% vs. 39%, p=0.017), adequate chemoprevention knowledge (49% vs. 27%, p<0.001), informed choice (41% vs. 23%, p=0.003), and mean decision conflict (34.0 vs. 47.0, p<0.001). There were no significant differences between the two groups in other patient-reported outcomes. Among patients who completed their 6-month follow-up, only 2.3% of high-risk women in the intervention arm and 3.8% in the control arm initiated a SERM or AI for breast cancer chemoprevention. Conclusions: With short-term follow-up, exposure to our decision support tools was associated with improvement in decision antecedents (accurate breast cancer risk perceptions, adequate chemoprevention knowledge) and decision quality (increased informed choice, reduced decision conflict). However, actual chemoprevention uptake in both arms remained low at less than 5%. Future research should focus on targeting high-risk women with LCIS or atypical hyperplasia and better incorporating decision support into clinic workflow through EHRs and patient portals. Citation Format: Katherine D Crew, Gauri Bhatkhande, Thomas Silverman, Tarsha Jones, Jennie Mata, Ashlee Guzman, Ting He, Jill Dimond, Rita Kukafka. Randomized controlled trial of decision support tools for patients and providers to increase breast cancer chemoprevention [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS8-05.

Effectiveness and safety of interventions to manage childhood overweight and obesity: An Overview of Cochrane systematic reviews.

Childhood overweight and obesity are associated with adverse physical, social, and psychological outcomes. We conducted an overview of Cochrane systematic reviews on the effectiveness and risks of interventions to treat overweight and obesity in children and adolescents. In June 2019, we searched the Cochrane Database of Systematic Reviews for eligible reviews. The primary outcomes were change in adiposity (body mass and body mass index [BMI] z-score) and adverse events. Two reviewers screened studies and one reviewer extracted and another verified data. Two reviewers assessed methodological quality and reached consensus. Data were synthesized narratively. We included seven Cochrane reviews published between 2011 and 2017 containing evidence from 167 randomized controlled trials with 21,050 participants. Lifestyle and behavioural interventions more effectively reduced weight compared with no intervention, usual care, or another behavioural treatment (three reviews, low-to-moderate certainty). Parent-child lifestyle and behavioural interventions more effectively reduced BMI z-score compared with no intervention (one review, low certainty). Decision support tools for healthcare providers more effectively limited increases in BMI z-score compared with usual care (one review, moderate certainty). Pharmacologic treatments combined with behavioural modification more effectively reduced adiposity compared with placebo or usual care (one review, low certainty), but the risk of adverse events was greater than non-pharmacologic therapy. Surgical interventions (e.g., LAP-BAND) combined with behavioural modification more effectively reduced adiposity compared with behavioural modification alone (one review, low certainty). Those who underwent surgery reported a higher number of adverse events compared with those treated with lifestyle modification. There is low-certainty evidence that lifestyle and behavioural interventions, pharmacologic interventions, and surgical interventions are effective in weight management for children with overweight and obesity. Safety data remain lacking across all intervention modalities. Future research should focus on implementation strategies. Further, a focus on overall well-being may be more beneficial than weight management specifically.

Intelligent Maintenance Systems and Predictive Manufacturing

Abstract With continued global market growth and an increasingly competitive environment, manufacturing industry is facing challenges and desires to seek continuous improvement. This effect is forcing manufacturers to squeeze every asset for maximum value and thereby calls for high-equipment effectiveness, and at the same time flexible and resilient manufacturing systems. Maintenance operations are essential to modern manufacturing systems in terms of minimizing unplanned down time, assuring product quality, reducing customer dissatisfaction, and maintaining advantages and competitiveness edge in the market. It has a long history that manufacturers struggle to find balanced maintenance strategies without significantly compromising system reliability or productivity. Intelligent maintenance systems (IMS) are designed to provide decision support tools to optimize maintenance operations. Intelligent prognostic and health management tools are imperative to identify effective, reliable, and cost-saving maintenance strategies to ensure consistent production with minimized unplanned downtime. This article aims to present a comprehensive review of the recent efforts and advances in prominent methods for maintenance in manufacturing industries over the last decades, identifying the existing research challenges, and outlining directions for future research.

Location of facilities and network design for reverse logistics of lithium-ion batteries in Sweden

Estimations of the amount of lithium-ion batteries reaching their end-of-life in 2025 and the amount being recycled indicates large deviations. To enable an efficient recycling process a well-defined and efficient supply chain network for the recovery of discarded lithium-ion batteries must be put in place. This includes analyzing the needs and restrictions of such a network. The aim of this paper is to provide decision support tools, to analyze input, and optimize a future supply chain for discarded lithium-ion batteries. A mixed integer programming model is developed and applied to the Swedish market. The findings show that several aspects will affect a reverse supply chain for discarded lithium-ion batteries, many of which are still uncertain and hard to predict.

Should We Wait Before Outsourcing? Analysis of a Revenue-Generating Blended Contact Center

Problem definition : We consider a revenue-generating call center with inbound and outbound calls, where service and sales activities are blended. For maximizing the call center’s revenue, the call center manager exercises two levels of control: agent reservation for inbound calls and call outsourcing. Given the influence of waits on purchase probability, we investigate the strategy of outsourcing customers who have waited already as opposed to outsourcing customers directly at arrival. Academic/practical relevance : The main novelty of this article arises from the use of a single framework to investigate both the combination of agent reservation with outsourcing decisions, and a waiting time–based outsourcing strategy. The existing literature only considers these two strategies in isolation and is restricted to quantity-based decisions. From a practical viewpoint, our results aim to provide decision support tools that are directly implementable in a call center’s routing software. Methodology : We apply a Markov decision process approach to optimize the manager’s decisions. The particularity of our approach is that we use the experienced waiting time as a decision variable. Results : We prove that the optimal policy for reservation and outsourcing is of threshold type. Our main conclusion is that outsourcing customers after letting them wait in-house generates higher revenue than outsourcing calls at arrival. However, it is also detrimental to service quality. In addition, we identify contexts in which the difference between the two outsourcing strategies is significant. Managerial implications : Contrary to standard call center practices, which either consist of specialized teams for one type of call or only exercise one specific level of decision-making (reservation or outsourcing), we demonstrate the potential of partial outsourcing with partial reservation. Our study shows that the benefits of implementing our results are greatest in small congested call centers.

Spatial conservation planning under uncertainty using modern portfolio theory and Nash bargaining solution

In recent years, researchers from interdisciplinary teams involving ecologists, economists and operations researchers collaborated to provide decision support tools to address the challenges of preserving biodiversity by optimizing the design of reserves. The goal of this paper is to further advance this area of research and provide new solutions to solve complex Spatial Conservation Planning (SCP) problems under uncertainty that consider risk preferences of decision makers. Our approach employs modern portfolio theory to address uncertainties in SCP problems, and involves two conflicting objectives: maximizing return and minimizing risk. We apply concepts from game theory such as the Nash bargaining solution to directly compute a desirable Pareto-optimal solution for the proposed bi-objective optimization formulation in natural resource management problems. We demonstrate with numerical examples that by directly computing a Nash bargaining solution, a Binary Quadratically Constrained Quadratic Program (BQCQP) can be solved. We show that our approach (implementable with commercial solvers such as CPLEX) can effectively solve the proposed BQCQP for much larger problems than previous approaches published in the ecological literature. Optimal solutions for problems with less than 400 parcels can be computed within a minute. Near optimal solutions (within at most 0.2% gap from an optimal solution) for high-dimensional problems involving up to 800 parcels can be computed within 8 h on a standard computer. We have presented a new approach to solve SCP optimization problems while considering uncertainty and risk tolerance of decision makers. Our new approach expands considerably the applicability of such SCP optimization methods to address real conservation problems.

Screening for Lung Cancer - 10 States, 2017.

Lung cancer is the leading cause of cancer death in the United States; 148,869 lung cancer-associated deaths occurred in 2016 (1). Mortality might be reduced by identifying lung cancer at an early stage when treatment can be more effective (2). In 2013, the U.S. Preventive Services Task Force (USPSTF) recommended annual screening for lung cancer with low-dose computed tomography (CT) for adults aged 55-80 years who have a 30 pack-year* smoking history and currently smoke or have quit within the past 15 years (2).† This was a Grade B recommendation, which required health insurance plans to cover lung cancer screening as a preventive service.§ To assess the prevalence of lung cancer screening by state, CDC used Behavioral Risk Factor Surveillance System (BRFSS) data¶ collected in 2017 by 10 states.** Overall, 12.7% adults aged 55-80 years met the USPSTF criteria for lung cancer screening. Among those meeting USPSTF criteria, 12.5% reported they had received a CT scan to check for lung cancer in the last 12 months. Efforts to educate health care providers and provide decision support tools might increase recommended lung cancer screening.

Spatial Multicriteria Evaluation for Mapping the Risk of Occurrence of Peste des Petits Ruminants in Eastern Africa and the Union of the Comoros.

Peste des petits ruminants virus (PPRV), responsible for peste des petits ruminants (PPR), is widely circulating in Africa and Asia. The disease is a huge burden for the economy and development of the affected countries. In Eastern Africa, the disease is considered endemic. Because of the geographic proximity and existing trade between eastern African countries and the Comoros archipelago, the latter is at risk of introduction and spread, and the first PPR outbreaks occurred in the Union of the Comoros in 2012. The objective of this study was to map the areas suitable for PPR occurrence and spread in the Union of the Comoros and four eastern African countries, namely Ethiopia, Uganda, Kenya, and Tanzania. A Geographic Information System (GIS)-based Multicriteria Evaluation (MCE) was developed. Risk factors for PPR occurrence and spread, and their relative importance, were identified using literature review and expert-based knowledge. Corresponding geographic data were collected, standardized, and combined based on a weighted linear combination to obtain PPR suitability maps. The accuracy of the maps was assessed using outbreak data from the EMPRES database and a ROC curve analysis. Our model showed an excellent ability to distinguish between absence and presence of outbreaks in Eastern Africa (AUC = 0.907; 95% CI [0.820–0.994]), and a very good performance in the Union of the Comoros (AUC = 0.889, 95% CI: [0.694–1]). These results highlight the efficiency of the GIS-MCE method, which can be applied at different geographic scales: continental, national and local. The resulting maps provide decision support tools for implementation of disease surveillance and control measures, thus contributing to the PPR eradication goal of OIE and FAO by 2030.

Study protocol: Randomized controlled trial of web-based decision support tools for high-risk women and healthcare providers to increase breast cancer chemoprevention

BackgroundChemoprevention using selective estrogen receptor modulators and aromatase inhibitors has been shown to reduce invasive breast cancer incidence in high-risk women. Despite this evidence, few high-risk women who are eligible for chemoprevention utilize it as a risk-reducing strategy. Reasons for low uptake include inadequate knowledge about chemoprevention among patients and healthcare providers, concerns about side effects, time constraints during the clinical encounter, and competing comorbidities. Methods/designWe describe the study design of a randomized controlled trial examining the effect of two web-based decision support tools on chemoprevention decision antecedents and quality, referral for specialized counseling, and chemoprevention uptake among women at an increased risk for breast cancer. The trial is being conducted at a large, urban medical center. A total of 300 patients and 50 healthcare providers will be recruited and randomized to standard educational materials alone or in combination with the decision support tools. Patient reported outcomes will be assessed at baseline, one and six months after randomization, and after their clinic visit with their healthcare provider. DiscussionWe are conducting this trial to provide evidence on how best to support personalized breast cancer risk assessment and informed and shared decision-making for chemoprevention. We propose to integrate the decision support tools into clinical workflow, which can potentially expand quality decision-making and chemoprevention uptake. Trial registrationNCT03069742.

Abstract 13: Evaluation of a FHIR-based Clinical Decision Support Tool for Calculating CHA2DS2-VASc Scores

Background: Oral anticoagulants reduce stroke risk among atrial fibrillation (AF) patients, yet treatment rates remain low. A technology known as SMART on FHIR allows third party apps to integrate with electronic medical records (EMR) and provide decision support tools. University of Utah Health implemented an alpha version of an integrated MDCalc app - MDCalc on FHIR (MoF) - in the Epic EHR using a SMART on FHIR interface to enable multiple calculations, one of which was the CHA2DS2-VASc calculation. While MDCalc on FHIR is designed to automate inputs that are then reviewed by the practicing clinician with an opportunity to override with clinical judgment, we prospectively compared the automated app score - without physician oversight - with the clinician score, as an early measurement to evaluate accuracy and identify areas for improvement. Methods: We identified outpatient AF patients who were seen in the University of Utah’s cardiovascular clinics between 11/5/2018 and 12/7/2018. We used the MoF app to automatically calculate the CHA2DS2-VASc score within 24 hours of the identified clinic visit - without the MoF feature of allowing clinician interaction - and compared these values to the score documented by the clinician. We also categorized patients as either low risk of stroke or high risk of stroke and calculated the net reclassification index (NRI) using the app compared to documentation. Patients with an app score ≥2 were considered high risk, while patients with a documented score of ≥2 or were prescribed an oral anticoagulant were considered high risk. Results: We identified 200 AF patients, of whom 111 had a documented clinician score. The mean MoF app score was 3.79 (SD 1.86) compared to a mean clinician score of 3.25 (SD 1.63; p=0.02). The NRI was 13.5% (27 of 200) using the app compared to documentation. Ten percent (19 of 200) of patients were “up-classified” by the app, meaning they were high risk by app and low risk by the clinician. Four percent (8 of 200) of patients were “down-classified” by the app, meaning they were low risk by the app and high risk by the clinician. Upon review of these cases, and after accounting for patients who were or were not anticoagulated for a clinically relevant reason (history of bleeding, recent cardioversion, or patient preference), we found that three percent (5 of 200) of patients were “up-classified” by the app, and two percent (3 of 200) of patients were “down-classified” by the app, making the adjusted NRI 4% (8 of 200). Conclusion: SMART on FHIR enables third party vendors to create EMR-based apps, which could provide decision support and improve care. We found that our FHIR-app based approach tended to identify more comorbidities by using medication data to assign conditions, resulting in a higher CHA2DS2-VASc score compared to clinicians. These differences would have had a 4% effect on the actual decision to anticoagulate.

Toward the Advancement of Decision Support Tools for Industrial Facilities: Addressing Operation Metrics, Visualization Plots, and Alarm Floods

The objective of this paper is to facilitate the improvement of the control and operation of industrial facilities, by providing decision support tools. More specifically, this paper has three main contributions. First, this paper presents the definition of operation metrics that provide insight into the behavior of: 1) annunciated alarms, 2) alarm floods, and 3) operator actions in industrial facilities. Second, this paper presents visualization plots named multilayered radar plots that can present information in an elegant, dense, and comprehensive fashion. Three types of plots are proposed, which collectively compare the behavior of metrics, variables, and operation times in industrial facilities. Third, this paper presents a ranking method and a reordering design procedure of displayed alarms during an alarm flood to reorder the alarms based on the proposed alarm-flood criticality index . The purpose is to provide additional assistance to operators to focus on more critical issues. As the operation metrics, visualization plots, and the ranking in alarm floods heavily utilize historized data and given the industrial-oriented application of these decision support tools, this paper also addresses the extraction of information and the integration of the tools into industrial automation platforms. Note to Practitioners —In a control system used for an industrial facility, a large amount of data is collected and historized. The data include sensor measurements, status of actuators, alarms, and operator actions, and it therefore contains valuable information. The information can be extracted and utilized to assist in the improvement of the control and operation of the industrial facility. The objective of this paper is to provide decision support tools by: 1) defining operation metrics that can characterize the information extracted from the historized data; 2) presenting visualization plots that allow for a clear presentation and comparison of the metrics, where three types of plots are proposed for different purposes of comparison; and 3) a ranking method and a reordering design procedure of displayed alarms during an alarm flood. Furthermore, this paper discusses how the information is extracted from the historized data and how to integrate the proposed decision support tools into existing industrial automation platforms.

Abstract OT3-01-02: Randomized controlled trial of web-based decision support tools for high-risk women and primary care providers to increase breast cancer chemoprevention

Abstract Background: Breast cancer chemoprevention with selective estrogen receptor modulators (SERMs) and aromatase inhibitors (AIs) is under-utilized despite several randomized controlled trials demonstrating a 40-65% decrease in breast cancer incidence among high-risk women. Reasons for low chemoprevention uptake include inadequate time for counseling, insufficient knowledge about SERMs and AIs, and concerns about side effects. Intervention trials of clinical decision support tools designed to increase chemoprevention uptake have been met with limited success. We have developed web-based decision aids (DAs), RealRisks for high-risk women and BNAV for primary care providers (PCPs). Our intervention differs from the prior literature in that we are targeting both patients and PCPs with personalized risk reports and education about the risks and benefits of chemoprevention. Our patient-centered decision aid is available in English and Spanish and has been rigorously tested in multi-ethnic women with varying health literacy. We hypothesize that standard educational materials combined with RealRisks and BNAV will increase uptake of SERMs or AIs among high-risk women in the primary care setting. Trial Design: We are conducting a randomized controlled trial at Columbia University Medical Center (CUMC) in New York, NY, consisting of standard educational materials combined with RealRisks and BNAV or standard educational materials alone among 300 high-risk women stratified by Hispanic ethnicity and menopausal status. Women in the intervention arm are given access to the RealRisks DA, and, based on their responses, an action plan is generated summarizing their breast cancer risk profile, risks/benefits of SERMs and AIs, and personal preferences for chemoprevention. PCPs are given their patient's tailored risk report, which is the providers' view of the action plan, and are invited to access the BNAV tool. Eligibility Criteria: 1) Women, aged 35-75 years; 2) 5-year invasive breast cancer risk ≥1.67% or lifetime risk ≥20% according to the Gail model (Breast Cancer Risk Assessment Tool) or history of lobular carcinoma in situ; 3) No prior use of SERM or AI; 4) No prior history of breast cancer; 5) PCP at CUMC; 6) English- or Spanish-speaking. Specific Aims: The primary endpoint is chemoprevention uptake of a SERM or AI at 6 months based upon documentation in the electronic health record. Secondarily, we use validated surveys to assess breast cancer and chemoprevention knowledge, accuracy of perceived breast cancer risk and worry, decision self-efficacy, and informed choice at baseline, 1 month, 6 months, and post-clinical encounter with the patients' PCP. PCPs will complete a 1-time survey on personal and professional characteristics and practice patterns. Statistical Methods: With a total sample size of 300 (150 per arm), assuming a Type 1 error of 5% and a 10% drop-out rate (effective sample size of 270), we will have >80% power to detect a difference in chemoprevention uptake of 1% in the control arm and 10% in the active intervention arm. Target Accrual: 300. Seventy-eight participants accrued as of June 2017. Accrual completion expected November 2018. Contact: Katherine Crew, CUMC, kd59@cumc.columbia.edu Citation Format: Vanegas A, Vargas JM, Kukafka R, Crew KD. Randomized controlled trial of web-based decision support tools for high-risk women and primary care providers to increase breast cancer chemoprevention [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr OT3-01-02.

Inventory models for joint pricing and greening effort decisions with discounts

PurposeThis paper aims to develop efficient decision support tools for a firm’s environment protection by using greening effort while yet improving profitability by utilizing pricing and inventory decisions with discount consideration.Design/methodology/approachThis study proposed a mathematical model for price- and greening effort-dependent demand rate with discount considerations. Later, the mathematical model is extended to the situation in which the demand rate is also dependent on the stock level, in addition to the price and greening effort. Efficient solution methodologies are developed for finding the optimal solution to the proposed models.FindingsSimple yet elegant models are proposed to mimic real-life applications. Structural properties of the models are explored to outline efficient algorithms with quantity discounts.Research limitations/implicationsThe paper considers monopoly and assumes deterministic demand. Only a more commonly observed all-units discount scheme is studied.Practical implicationsThe models provide decision support tools for firms in pursuit of joint profit maximization and environment consciousness goals.Social implicationsThe study develops environment-friendly approaches for inventory management and improving the profitability alike.Originality/valueThis study is among the first to consider environmental protection with an investment in greening effort along with inventory management and pricing decision. The study also explored the effect of all-unit quantity discounts.

A conceptual framework for patient-centered fertility treatment

BackgroundPatient-centered care is a pillar of quality health care and is important to patients experiencing infertility. In this study we used empirical, in-depth data on couples’ experiences of infertility treatment decision making to inform and revise a conceptual framework for patient-centered fertility treatment that was developed based on health care professionals’ conceptualizations of fertility treatment, covering effectiveness, burden, safety, and costs.MethodsIn this prospective, longitudinal mixed methods study, we collected data from both members (separately) of 37 couples who scheduled an initial consult with a reproductive specialist. Data collection occurred 1 week before the initial consultation, 1 week after the initial consultation, and then roughly 2, 4, 8, and 12 months later. Data collection included semi-structured qualitative interviews, self-reported questionnaires, and medical record review. Interviews were recorded, transcribed, and content analyzed in NVivo. A single coder analyzed all transcripts, with > 25% of transcripts coded by a second coder to ensure quality control and consistency.ResultsContent analysis of the interview transcripts revealed 6 treatment dimensions: effectiveness, physical and emotional burden, time, cost, potential risks, and genetic parentage. Thus, the revised framework for patient-centered fertility treatment retains much from the original framework, with modification to one dimension (from safety to potential risks) and the addition of two dimensions (time and genetic parentage). For patients and their partners making fertility treatment decisions, tradeoffs are explicitly considered across dimensions as opposed to each dimension being considered on its own.ConclusionsPatient-centered fertility treatment should account for the dimensions of treatment that patients and their partners weigh when making decisions about how to add a child to their family. Based on the lived experiences of couples seeking specialist medical care for infertility, this revised conceptual framework can be used to inform patient-centered treatment and research on infertility and to develop decision support tools for patients and providers.

Asthma management programs for primary care providers: increasing adherence to asthma guidelines.

This article reviews new approaches, facilitators, barriers, and opportunities to increasing guideline-adherent care for children with asthma by primary care clinicians. Primary care clinicians are challenged by the volume of guidelines and want transparent guidelines that are easy to use and that can be used in complex patients with multiple comorbidities. Programs that use decision support tools and electronic technologies and provide support from individuals new to the medical home such as panel management assistants, community health workers, patient advocates, practice facilitators, school nurses, and pharmacists may enhance use of guidelines by primary care clinicians and reduce asthma morbidity. Primary care clinician burnout and difficulty incorporating electronic asthma decision tools into current workflow are recently recognized barriers to guideline integration and improved asthma outcomes. In addition, many of these interventions are labor intensive, costly and may not be capable of being widely disseminated. Programs that simplify guidelines, provide decision support tools and use electronic technologies and an expanded medical team may improve the quality of asthma care provided by the primary care community to children and their families with asthma.

Provider perspectives on barriers and facilitators to adjuvant endocrine therapy-related symptom management.

155 Background: Adjuvant endocrine therapy (AET)-related symptom management (SM) among breast cancer survivors (BCS) typically involves a multidisciplinary team of health care providers; yet few studies have examined provider perspectives on AET-related SM. The purpose of this study was to examine provider perspectives on the barriers and facilitators to AET-related SM among BCS and opportunities for improvement. Methods: We conducted 3 focus groups (FGs) with a multidisciplinary group of health care providers (n = [6] physician; n = [7] non-physician) experienced in caring for BCS undergoing AET. We utilized semi-structured discussion guides to elicit provider perspectives on AET-related SM and its barriers and facilitators as well as recommendations for improvement. All FGs were held at the University of Pittsburgh, audiotaped, and transcribed. We analyzed FG transcripts using qualitative software to identify key themes. Results: Providers described patient-, provider-, and system- level facilitators and barriers to AET-related SM. At the patient-level, facilitators included social support and provider communication about symptoms while cancer-related distress, misinformation and misinterpretation of online information were identified as barriers. Provider-level facilitators included strong relationships with other providers and ongoing communication with patients; however, lack of time, insufficient resources, and challenges distinguishing AET-related symptoms from other conditions were key provider-level barriers. Finally, at the system-level, electronic health records were described as both a facilitator and barrier to SM. Moreover, poor care coordination among different providers and lack of clear guidelines on which provider “owns” AET-related SM emerged as key system-level barriers. Conclusions: Findings suggest that efforts to improve AET-related SM should span multiple levels, in order to address patient-, provider-, and system-level barriers to SM. Recommendations include increased education for patients, greater access to clinical decision support tools for providers, and improved coordination of survivorship resources within hospitals.

How does evidence affect clinical decision-making?

In 1998, the ‘Evidence Cart’ was introduced to provide decision support tools at the point of care. A recent study showed that a majority of doctors who previously stated that...