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The long-term care of hematopoietic stem cell transplantation (HSCT) survivors poses special challenges owing to a myriad of possible chronic and/or late complications. Survivorship care plans (SCPs) have been proposed as tools to communicate information on the late effects of treatment and recommended follow-up care to clinicians and survivors. The primary aims of this study were to determine SCP content and format, as well as to assess the preferred timing of SCP provision following HSCT. HSCT survivors and nontransplantation clinicians (oncologists and primary care physicians) were invited to participate in a survey evaluating the usefulness and utility of a sample HSCT-specific SCP with a treatment summary generated by autopopulation from an electronic health record (EHR). All participating HSCT survivors (n = 29) and clinicians (n = 18) indicated a desire to receive an SCP. More than 85% of the participants perceived information about treatments received, recommended follow-up and health maintenance including vaccinations, survivor and clinician resources, and graft-versus-host disease and other late/chronic side effects to be useful. The majority of survivors also believed that care team contact information was useful. In addition, >85% of survivors and clinicians agreed that the SCP increased their understanding of treatments and chronic/late side effects, improved health care provided, and were satisfied with the SCP and found it understandable and easy to use. The majority of survivors indicated that additional information should be added to the SCP, whereas some clinicians deemed the SCP too long. Survivors preferred to receive the SCP as a paper document at the end of a regular follow-up visit and review it with a cancer clinician, whereas clinicians preferred to receive the SCP through the EHR. These findings will help improve the design of future SCPs for use by HSCT survivors and clinicians. Future work will include leveraging the EHR to ease the burden of creating user-centered documents.

Just under half of the 85.7 million US adults with hypertension have uncontrolled blood pressure using a hypertension threshold of systolic pressure ≥ 140 or diastolic pressure ≥ 90. Uncontrolled hypertension increases risks of death, stroke, heart failure, and myocardial infarction. Guidelines on hypertension management include lifestyle modification such as diet and exercise. In order to improve hypertension control, it is important to identify predictors of lifestyle modification assessment or advice to tailor future interventions using these effective, low-risk interventions. Electronic health record data from 14,360 adult hypertension patients at an academic medical center were analyzed using statistical and machine learning methods to identify predictors and timing of lifestyle modification. Multiple variables were statistically significant in analysis of lifestyle modification documentation at multiple time points. Random Forest was the best machine learning method to classify lifestyle modification documentation at any time with Area Under the Receiver Operator Curve (AUROC) 0.831. Logistic regression was the best machine learning method for classifying lifestyle modification documentation at ≤3 months with an AUROC of 0.685. Analyzing narrative and coded data from electronic health records can improve understanding of timing of lifestyle modification and patient, clinic and provider characteristics that are correlated with or predictive of documentation of lifestyle modification for hypertension. This information can inform improvement efforts in hypertension care processes, treatment implementation, and ultimately hypertension control.

Objectives To evaluate the utility of routinely collected Hendrich II fall scores in predicting returns to the emergency department (ED) for falls within 6 months. Design Retrospective electronic record review. Setting Academic medical center ED. Participants Individuals aged 65 and older seen in the ED from January 1, 2013, through September 30, 2015. Measurements We evaluated the utility of routinely collected Hendrich II fall risk scores in predicting ED visits for a fall within 6 months of an all‐cause index ED visit. Results For in‐network patient visits resulting in discharge with a completed Hendrich II score (N = 4,366), the return rate for a fall within 6 months was 8.3%. When applying the score alone to predict revisit for falls among the study population the resultant receiver operating characteristic (ROC) plot had an area under the curve (AUC) of 0.64. In a univariate model, the odds of returning to the ED for a fall in 6 months were 1.23 times as high for every 1‐point increase in Hendrich II score (odds ratio (OR)=1.23 (95% confidence interval (CI)=1.19–1.28). When included in a model with other potential confounders or predictors of falls, the Hendrich II score is a significant predictor of a return ED visit for fall (adjusted OR=1.15, 95% CI=1.10–1.20, AUC=0.75). Conclusion Routinely collected Hendrich II scores were correlated with outpatient falls, but it is likely that they would have little utility as a stand‐alone fall risk screen. When combined with easily extractable covariates, the screen performs much better. These results highlight the potential for secondary use of electronic health record data for risk stratification of individuals in the ED. Using data already routinely collected, individuals at high risk of falls after discharge could be identified for referral without requiring additional screening resources.

About 99,000 people are waiting for a kidney in the US, and many will die waiting. The concept of “imminent death” donation, a type of living donation, has been gaining attention among physicians, patients, and ethicists. We estimated the number of potential imminent death kidney donors at the University of Wisconsin Hospital and Clinics by estimating the number of annual deaths in individuals with normal kidney function. Based on a previous survey suggesting that 1/3 of patients might be willing to donate at imminent death, we estimate that between 76 and 396 people in the state of Wisconsin would be medically eligible and willing to donate each year at the time of imminent death. We extrapolated these numbers to all transplant centers in the US, estimating that between 5925 and 31,097 people might be eligible and willing to donate. Our results suggest that allowing donation at imminent death and including discussions about organ donation in end-of-life planning could substantially reduce the nation's kidney waiting list while providing many more donors the opportunity to give this gift. This article is protected by copyright. All rights reserved.

ObjectiveClinical research involving humans is critically important, but it is a lengthy and expensive process. Most studies require institutional review board (IRB) approval. Our objective is to identify predictors of delays or accelerations in the IRB review process and apply this knowledge to inform process change in an effort to improve IRB efficiency, transparency, consistency and communication.MethodsWe analyzed timelines of protocol submissions to determine protocol or IRB characteristics associated with different processing times. Our evaluation included single variable analysis to identify significant predictors of IRB processing time and machine learning methods to predict processing times through the IRB review system. Based on initial identified predictors, changes to IRB workflow and staffing procedures were instituted and we repeated our analysis.ResultsOur analysis identified several predictors of delays in the IRB review process including type of IRB review to be conducted, whether a protocol falls under Veteran’s Administration purview and specific staff in charge of a protocol's review.ConclusionsWe have identified several predictors of delays in IRB protocol review processing times using statistical and machine learning methods. Application of this knowledge to process improvement efforts in two IRBs has led to increased efficiency in protocol review. The workflow and system enhancements that are being made support our four-part goal of improving IRB efficiency, consistency, transparency, and communication.

The purpose of this article is to describe the association between initial CT for atraumatic headache and repeat emergency department (ED) visitation within 30 days of ED discharge.A retrospective observational study was performed at an academic urban ED with more than 85,000 annual visits. All adult patients with a chief complaint of headache from January through December 2010 who were discharged after ED evaluation were included in the analysis. Patients were excluded if they were transferred, died in the ED, or had a diagnosis indicating a traumatic mechanism. A propensity score-matched logistic regression model was used to determine whether the use of brain CT was associated with the primary outcome of ED revisitation within 30 days, controlling for potential confounding variables.Of 80,619 total patient visits to the ED during the study period, 922 ED discharges with a chief complaint of headache were included. A total of 139 (15.1%) patients revisited within 30 days. The return rate was 11.2% among patients who underwent CT at their initial visit and 21.1% among those who did not. In the adjusted analysis, controlling for age, race, sex, insurance status, triage vital signs, laboratory values, and triage pain level, the odds ratio for revisitation given CT performance was 0.49 (95% CI, 0.27-0.86).After adjustment for clinical factors, we found that patients who underwent a brain CT examination for atraumatic headache at an initial ED visit were less likely to return to the ED within 30 days. Future appropriate use quality metrics regarding ED imaging use may need to incorporate downstream health care use.

Given the importance of clinical trials (CT) for the approval of new drugs, and the many current obstacles to CT execution, there is an urgent need for CT improvement. This chapter discusses pragmatic trials and other informatics-enabled enhancements to Phase IV CT that completely change the original definitions of CT and may be seen as full replacements to Phase IVs. These developments are important for reducing costs and time-lines for the CT process, reducing risk of withdrawal from the market, and they are also useful for drug repurposing. Importantly, the future of Phase IV CTs is one that relies heavily on data collected via the EHR enabling a continuous and individualized Phase IV trial model. The EHR thus is a foundation to a continuous pragmatic Phase IV registry and a key tool in support of precision medicine.

Background Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, emergency department encounters in order to deliver appropriate care and referrals. Unfortunately, falls are difficult to identify without manual chart review, a time intensive process infeasible for many applications including surveillance and quality reporting. Here we describe a pragmatic NLP approach to automating fall identification. Methods In this single center retrospective review, 500 emergency department provider notes from older adult patients (age 65 and older) were randomly selected for analysis. A simple, rules-based NLP algorithm for fall identification was developed and evaluated on a development set of 1084 notes, then compared with identification by consensus of trained abstractors blinded to NLP results. Results The NLP pipeline demonstrated a recall (sensitivity) of 95.8%, specificity of 97.4%, precision of 92.0%, and F1 score of 0.939 for identifying fall events within emergency physician visit notes, as compared to gold standard manual abstraction by human coders. Conclusions Our pragmatic NLP algorithm was able to identify falls in ED notes with excellent precision and recall, comparable to that of more labor-intensive manual abstraction. This finding offers promise not just for improving research methods, but as a potential for identifying patients for targeted interventions, quality measure development and epidemiologic surveillance. Electronic supplementary material The online version of this article (10.1186/s12911-019-0843-7) contains supplementary material, which is available to authorized users.

Background The ECOG-ACRIN Cancer Research Group evaluated rituximab treatment schedules for patients with newly-diagnosed low-tumor-burden follicular-lymphoma (FL). All patients received 4-weekly rituximab treatments as induction therapy. Clinically-responding patients were randomized to receive rituximab every 13 weeks (“maintenance”) vs. no additional rituximab until progression (“non-maintenance”). Based on “time-to-rituximab-failure (TTRF)”, the study-committee reported there was no overall-benefit for maintenance rituximab in this setting. Tumor-reactive mAbs, like rituximab, trigger natural killer (NK) cells. NK-cell responses are regulated, in part, by interactions between killer immunoglobulin-like receptors (KIRs) on NK cells and their interactions with KIR-ligands. In a separate study of children with neuroblastoma treated with a different mAb, we found certain KIR/KIR-ligand genotypes associated with improved outcome. Here, we assessed whether a subset of FL patients show improved outcome from the maintenance rituximab based on these same KIR/KIR-ligand genotypes. Methods Genotypes for KIR/KIR-ligand were determined and assessed for associations with outcome [duration of response, TTRF and % tumor shrinkage] as a post-hoc analysis of this phase III trial. Our primary objective was to assess specific KIR/KIR-ligand genotype associations, followed by separate prespecified KIR/KIR-ligand genotype associations in follow-up analyses. Statistical analyses for association of genotype with clinical outcome included: Log-rank tests and Cox proportional hazards regression models to assess duration of response and TTRF; analysis of variance (ANOVA) was used for assessment of % tumor shrinkage. Results We found that patients inheriting KIR2DL2 and its ligand (HLA-C1) along with KIR3DL1 and its ligand (HLA-Bw4) had improved outcome over patients without this genotype. In addition, patients with KIR2DL2 and HLA-C1 along with KIR3DL1 and HLA-Bw4 also showed improved duration of response and tumor shrinkage if they received maintenance, while patients without this genotype showed no such improvement when receiving maintenance. Conclusions The data presented here indicate that a subset of FL patients, identified by certain KIRs/KIR-ligands, have improved outcome and may benefit from additional rituximab treatment. Taken together, this suggests that the efficacy of tumor-reactive mAb treatment for some patients is influenced by KIRs on NK cells. However, prior to considering these genotypes in a clinically-actionable manner, these findings need independent validation in other studies. Electronic supplementary material The online version of this article (10.1186/s40425-019-0538-8) contains supplementary material, which is available to authorized users.

Lifestyle modification, including diet, exercise, and tobacco cessation, is the first-line treatment of many disorders including hypertension, obesity, and diabetes. Lifestyle modification data are not easily retrieved or used in research due to their textual nature. This study addresses this knowledge gap using natural language processing to automatically identify lifestyle modification documentation from electronic health records. Electronic health record notes from hypertension patients were analyzed using an open-source natural language processing tool to retrieve assessment and advice regarding lifestyle modification. These data were classified as lifestyle modification assessment or advice and mapped to a coded standard ontology. Combined lifestyle modification (advice and assessment) recall was 99.27 percent, precision 94.44 percent, and correct classification 88.15 percent. Through extraction and transformation of narrative lifestyle modification data to coded data, this critical information can be used in research, metric development, and quality improvement efforts regarding care delivery for multiple medical conditions that benefit from lifestyle modification.

Objectives The Patient, Intervention, Control/Comparison, and Outcome (PICO) framework is an effective technique for framing a clinical question. We aim to develop the counterpart of PICO to structure clinical research data needs. Methods We use a data-driven approach to abstracting key concepts representing clinical research data needs by adapting and extending an expert-derived framework originally developed for defining cancer research data needs. We annotated clinical trial eligibility criteria, EHR data request logs, and data queries to electronic health records (EHR), to extract and harmonize concept classes representing clinical research data needs. We evaluated the class coverage, class preservation from the original framework, schema generalizability, schema understandability, and schema structural correctness through a semi-structured interview with eight multidisciplinary domain experts. We iteratively refined the schema based on the evaluations. Results Our data-driven schema preserved 68% of the 63 classes from the original framework and covered 88% (73/82) of the classes proposed by evaluators. Class coverage for participants of different backgrounds ranged from 60% to 100% with a median value of 95% agreement among the individual evaluators. The schema was found understandable and structurally sound. Conclusions Our proposed schema may serve as the counterpart to PICO for improving the research data needs communication between researchers and informaticians.

New vocabularies are rapidly evolving in the literature relative to the practice of clinical medicine and translational research. To provide integrated access to new terms, we developed a mobile and desktop online reference—Marshfield Dictionary of Clinical and Translational Science (MD-CTS). It is the first public resource that comprehensively integrates Wiktionary (word definition), BioPortal (ontology), Wiki (image reference), and Medline abstract (word usage) information. MD-CTS is accessible at http://spellchecker.mfldclin.edu/. The website provides a broadened capacity for the wider clinical and translational science community to keep pace with newly emerging scientific vocabulary. An initial evaluation using 63 randomly selected biomedical words suggests that online references generally provided better coverage (73%-95%) than paper-based dictionaries (57–71%).

To evaluate the utility of routinely collected Hendrich II fall scores in predicting returns to the emergency department (ED) for falls within 6 months.Retrospective electronic record review.Academic medical center ED.Individuals aged 65 and older seen in the ED from January 1, 2013, through September 30, 2015.We evaluated the utility of routinely collected Hendrich II fall risk scores in predicting ED visits for a fall within 6 months of an all-cause index ED visit.For in-network patient visits resulting in discharge with a completed Hendrich II score (N = 4,366), the return rate for a fall within 6 months was 8.3%. When applying the score alone to predict revisit for falls among the study population the resultant receiver operating characteristic (ROC) plot had an area under the curve (AUC) of 0.64. In a univariate model, the odds of returning to the ED for a fall in 6 months were 1.23 times as high for every 1-point increase in Hendrich II score (odds ratio (OR)=1.23 (95% confidence interval (CI)=1.19-1.28). When included in a model with other potential confounders or predictors of falls, the Hendrich II score is a significant predictor of a return ED visit for fall (adjusted OR=1.15, 95% CI=1.10-1.20, AUC=0.75).Routinely collected Hendrich II scores were correlated with outpatient falls, but it is likely that they would have little utility as a stand-alone fall risk screen. When combined with easily extractable covariates, the screen performs much better. These results highlight the potential for secondary use of electronic health record data for risk stratification of individuals in the ED. Using data already routinely collected, individuals at high risk of falls after discharge could be identified for referral without requiring additional screening resources.

Display Omitted We compared ILP to propositional machine learning approaches for EHR phenotyping.Training subject selection for machine learning was automated using ICD-9 codes.ILP out-performed propositional machine learning approaches in AUROC.Relational learning using ILP offers a viable approach to EHR-driven phenotyping. ObjectiveElectronic health records (EHR) offer medical and pharmacogenomics research unprecedented opportunities to identify and classify patients at risk. EHRs are collections of highly inter-dependent records that include biological, anatomical, physiological, and behavioral observations. They comprise a patient's clinical phenome, where each patient has thousands of date-stamped records distributed across many relational tables. Development of EHR computer-based phenotyping algorithms require time and medical insight from clinical experts, who most often can only review a small patient subset representative of the total EHR records, to identify phenotype features. In this research we evaluate whether relational machine learning (ML) using inductive logic programming (ILP) can contribute to addressing these issues as a viable approach for EHR-based phenotyping. MethodsTwo relational learning ILP approaches and three well-known WEKA (Waikato Environment for Knowledge Analysis) implementations of non-relational approaches (PART, J48, and JRIP) were used to develop models for nine phenotypes. International Classification of Diseases, Ninth Revision (ICD-9) coded EHR data were used to select training cohorts for the development of each phenotypic model. Accuracy, precision, recall, F-Measure, and Area Under the Receiver Operating Characteristic (AUROC) curve statistics were measured for each phenotypic model based on independent manually verified test cohorts. A two-sided binomial distribution test (sign test) compared the five ML approaches across phenotypes for statistical significance. ResultsWe developed an approach to automatically label training examples using ICD-9 diagnosis codes for the ML approaches being evaluated. Nine phenotypic models for each ML approach were evaluated, resulting in better overall model performance in AUROC using ILP when compared to PART (p=0.039), J48 (p=0.003) and JRIP (p=0.003). DiscussionILP has the potential to improve phenotyping by independently delivering clinically expert interpretable rules for phenotype definitions, or intuitive phenotypes to assist experts. ConclusionRelational learning using ILP offers a viable approach to EHR-driven phenotyping.

Research on mobile health decision support systems (mHealth DSS) is limited, and few studies have focused on nurses or nurse practitioners (NPs). This study compared diagnostic rates and care planning by nurses in NP training randomized to mHealth DSS versus a control group for obesity and overweight, tobacco use, and depression. The patient encounter (N = 34,349) was the unit of analysis in the randomized controlled trial. NP students were assigned within specialty to receive mHealth DSS for 1 of 3 conditions. There was a significant effect (P

Purpose: In 2010, a Children's Oncology Group (COG) phase III randomized trial for patients with high-risk neuroblastoma (ANBL0032) demonstrated improved event-free survival (EFS) and overall survival (OS) following treatment with an immunotherapy regimen of dinutuximab, GM-CSF, IL2, and isotretinoin compared with treatment with isotretinoin alone. Dinutuximab, a chimeric anti-GD2 monoclonal antibody, acts in part via natural killer (NK) cells. Killer immunoglobulin-like receptors (KIR) on NK cells and their interactions with KIR-ligands can influence NK cell function. We investigated whether KIR/KIR-ligand genotypes were associated with EFS or OS in this trial. Experimental Design: We genotyped patients from COG study ANBL0032 and evaluated the effect of KIR/KIR-ligand genotypes on clinical outcomes. Cox regression models and log-rank tests were used to evaluate associations of EFS and OS with KIR/KIR-ligand genotypes. Results: In this trial, patients with the “all KIR-ligands present” genotype as well as patients with inhibitory KIR2DL2 with its ligand (HLA-C1) together with inhibitory KIR3DL1 with its ligand (HLA-Bw4) were associated with improved outcome if they received immunotherapy. In contrast, for patients with the complementary KIR/KIR-ligand genotypes, clinical outcome was not significantly different for patients who received immunotherapy versus those receiving isotretinoin alone. Conclusions: These data show that administration of immunotherapy is associated with improved outcome for neuroblastoma patients with certain KIR/KIR-ligand genotypes, although this was not seen for patients with other KIR/KIR-ligand genotypes. Further investigation of KIR/KIR-ligand genotypes may clarify their role in cancer immunotherapy and may enable KIR/KIR-ligand genotyping to be used prospectively for identifying patients likely to benefit from certain cancer immunotherapy regimens. Clin Cancer Res; 24(1); 189–96. ©2017 AACR. See related commentary by Cheung and Hsu, p. 3

Palivizumab was licensed in June 1998 by the Food and Drug Administration for the reduction of serious lower respiratory tract infection caused by respiratory syncytial virus (RSV) in children at increased risk of severe disease. Since that time, the American Academy of Pediatrics has updated its guidance for the use of palivizumab 4 times as additional data became available to provide a better understanding of infants and young children at greatest risk of hospitalization attributable to RSV infection. The updated recommendations in this policy statement reflect new information regarding the seasonality of RSV circulation, palivizumab pharmacokinetics, the changing incidence of bronchiolitis hospitalizations, the effect of gestational age and other risk factors on RSV hospitalization rates, the mortality of children hospitalized with RSV infection, the effect of prophylaxis on wheezing, and palivizumab-resistant RSV isolates. This policy statement updates and replaces the recommendations found in the 2012 Red Book.

Background Survivors of hematopoietic stem cell transplants (HSCTs) face many chronic and late complications that pose challenges to future survivorship care. The provision and review of Survivorship Care Plans (SCPs) has been proposed as a method to improve knowledge of these complications as well as screening and treatment recommendations among survivors and their non-transplant clinicians. Creating SCPs can be work intensive, however, using the electronic health record (EHR) can reduce the time and personnel resources required to generate SCPs and complement efforts to discretely capture HSCT data. Objectives Our objectives were to determine what content should be included in HSCT-focused SCPs for these diverse users as well as format and preferred timing of SCP provision. Results will be used to create HSCT-focused SCP templates generated by and integrated with an EHR. Methods Eligible HSCT survivors were ≥18 years and received a HSCT > 12 months ago. Non-transplant primary care and oncology clinicians were eligible if they provided care to HSCT patients. Those eligible were invited to complete a survey evaluating a HSCT-focused SCP with treatment summary data generated by an EHR. The usefulness of content, format and utility of the document, and timing of provision were considered especially pertinent. The survey utilized both 5-point Likert scales and open-ended questions. Results Survey response rate exceeded 80% (n=29/36 survivors; n=18/22 clinicians). Our survivor respondents were a median age of 59 (range 32-73), White (100%), mostly female (52%) and educated (52% held an associate degree or higher). Clinician respondents were predominately female (67%), White (78%) and providing primary care (56%). Over 85% of survivors and clinicians perceived information about treatments received, recommended follow-up and health maintenance including vaccinations, survivor and clinician resources, graft versus host disease and other late/chronic side effects to be useful or very useful. The majority of survivors also found care team contact information useful or very useful. Additionally, over 85% of survivors and clinicians agreed or strongly agreed that the SCP would improve follow-up care and increase their understanding of treatments and chronic/late side effects. Overall, 88% were satisfied with the SCP and found it understandable and easy to use. All respondents indicated a desire to receive SCPs. Survivors (93%) prefer to receive the SCP as a paper document at the end of a regular follow-up, and most would like to receive the SCP immediately after transplant (70%) or two to three months after transplant (67%). Clinicians (89%) would prefer to receive the SCP through the EHR. Conclusion These results will help improve future HSCT-focused SCP templates to meet the needs of these users. Future work will include leveraging the EHR for creation and provision of SCPs with ease.

Decreasing the incidence of nonmelanoma skin cancer (NMSC) is of great importance in regards to future healthcare services. Given the previously reported preventive effects of α-difluoromethylornithine (DFMO) in skin and colon cancer trials, we determined appropriate cause to update the clinical data on the subjects from the recently reported randomized, double-blind, placebo-controlled phase III skin cancer prevention study of DFMO. Our intention was to retrospectively assess the further incidence of skin cancer, other malignancies, and adverse events of patients accrued to our phase III skin cancer prevention study of DFMO. Clinical records of 209 University of Wisconsin (UW) Health subjects were reviewed, and 2,092.7 person years of on study (884.3 person years) and poststudy (1,208.4 person years) follow-up for these patients were assessed for new NMSC events and recurrence rates from the on study period, the poststudy period, and the two study periods combined. No evidence of increased significant diagnoses or serious adverse events was observed in the DFMO participants. The initially observed, marginally significant reduction (P = 0.069) in NMSC rates for DFMO subjects relative to placebo continued without evidence of rebound. Event rates after discontinuation from study for total NMSCs (DFMO 0.236 NMSC/person/year, placebo 0.297, P = 0.48) or the subtypes of basal cell carcinomas (BCC; DFMO 0.179 BCC/person/year, placebo 0.190, P = 0.77) and squamous cell carcinomas (SCC; DFMO 0.057 SCC/person/year, placebo 0.107, P = 0.43) are listed. Follow-up data revealed a persistent but insignificant reduction in new NMSCs occurring in DFMO subjects without evidence of latent or cumulative toxicity relative to placebo subjects. Cancer Prev Res; 5(12); 1368–74. ©2012 AACR.

Purpose: Fc-gamma receptors (FCGRs) are expressed on immune cells, bind to antibodies, and trigger antibody-induced cell-mediated antitumor responses when tumor-reactive antibodies are present. The affinity of the FCGR/antibody interaction is variable and dependent upon FCGR polymorphisms. Prior studies of patients with cancer treated with immunotherapy indicate that FCGR polymorphisms can influence antitumor response for certain immunotherapies that act via therapeutically administered mAbs or via endogenous tumor-reactive antibodies induced from tumor antigen vaccines. The previously published “SELECT” trial of high-dose aldesleukin (HD-IL2) for metastatic renal cell carcinoma resulted in an objective response rate of 25%. We evaluated the patients in this SELECT trial to determine whether higher-affinity FCGR polymorphisms are associated with outcome. Experimental Design: SNPs in FCGR2A, FCGR3A, and FCGR2C were analyzed, individually and in combination, for associations between genotype and clinical outcome. Results: When higher-affinity genotypes for FCGR2A, FCGR3A, and FCGR2C were considered together, they were associated with significantly increased tumor shrinkage and prolonged survival in response to HD-IL2. Conclusions: Although associations of higher-affinity FCGR genotype with clinical outcome have been demonstrated with mAb therapy and with idiotype vaccines, to our knowledge, this is the first study to show associations of FCGR genotypes with outcome following HD-IL2 treatment. We hypothesize that endogenous antitumor antibodies may engage immune cells through their FCGRs, and HD-IL2 may enhance antibody-induced tumor destruction, or antibody-enhanced tumor antigen presentation, via augmented activation of innate or adaptive immune responses; this FCGR-mediated immune activity would be augmented through immunologically favorable FCGRs. Clin Cancer Res; 23(9); 2159–68. ©2016 AACR.

NK cells play a role in many cancer immunotherapies. NK cell activity is tightly regulated by killer immunoglobulin-like receptor (KIR) and KIR–ligand interactions. Inhibitory KIR–ligands have been identified as HLA molecules, while activating KIR–ligands are largely unknown. Individuals that have not inherited the corresponding KIR–ligand for at least one inhibitory KIR gene are termed the “KIR–ligand missing” genotype, and they are thought to have a subset of NK cells that express inhibitory KIRs for which the corresponding KIR–ligand is missing on autologous tissue, and thus will not be inhibited through KIR–ligand recognition. In some settings where an anticancer immunotherapeutic effect is likely mediated by NK cells, individuals with a KIR–ligand missing genotype have shown improved clinical outcome compared to individuals with an “all KIR–ligands present” genotype. In addition, patients receiving hematopoietic stem cell transplants for leukemia may do better if their donor has more activating KIR genes (i.e., KIR haplotype-B). In a recent multi-institution clinical trial of patients with metastatic renal cell carcinoma receiving high-dose IL2 (HD-IL2), 25 % of patients showed a complete or partial tumor response to this therapy. We genotyped KIR and KIR–ligand genes for these patients (n = 107) and tested whether KIR/KIR–ligand genotypes correlated with patient clinical outcomes. In these analyses, we did not find any significant association of KIR/KIR–ligand genotype (either KIR–ligand missing or the presence of KIR haplotype-B) with patient outcome in response to the HD-IL2 therapy.

HD-IL2 was given to patients with mRCC in a prospective trial (ClinicalTrials.gov ID: NCT00554515) that demonstrated an overall response rate of 25%. To identify predictors of response, we genotyped patients for single nucleotide polymorphisms (SNPs) in FcgR genes: FcgR2a, FcgR3a, and FcgR2c. These FcgRs are variably expressed on immune cells, and bind to the IgG portion of antibodies, triggering activation. FcgR2a [SNP = histidine/arginine (H/R); expressed on neutrophils, monocytes-macrophages and antigen-presenting cells (APCs)] and FcgR3a [SNP = valine/phenylalanine (V/F); expressed on NK cells and some APCs] impact patient response to immunotherapy [mainly monoclonal antibody-based (mAb) therapies] in several malignancies, as both FcgR2a-H and FcgR3a-V have higher antibody binding affinity than FcgR2a-R or FcgR3a-F, respectively. FcgR2c, also expressed on NK cells, has a SNP that regulates its expression [C nucleotide = expression; T nucleotide = non-expression (C/T)]. About 20-40% of individuals express FcgR2c; little is known about the role of FcgR2c expression in cytokine-based immunotherapy. We found associations of FcgR genotypes with patient response to HD-IL2. Dual combination analyses of FcgR3a with FcgR2a genotypes revealed significantly improved %Tumor Shrinkage in patients with either FcgR3a-VV and/or FcgR2a-HH (n=34) as compared to those patients genotyped as FcgR3a-VF or FF with FcgR2a-HR or RR (n=70) (p=0.047). For analyses including both FcgR3a and FcgR2c genotypes, significantly improved OS was seen in those with ≥2 alleles of either FcgR3a-V and/or FcgR2c-C (n=27) vs. those with < 2 alleles of either FcgR3a-V and/or FcgR2c-C (n=79) (p=0.013). We further considered combinations that included the genotypes of all 3 genes; we identified 42 patients with “favorable” genotypes and 64 with “unfavorable”. We saw significant improvement in the %Tumor shrinkage (p = 0.033) and a trend for improvement in OS (p = 0.071) in the “favorable genotype” group. As reported previously by others, some cancer patients make endogenous anti-tumor Ab. The association of these “favorable” FcgR genotypes with outcome suggests there may be a beneficial interaction of “favorable” FcR genotypes with endogenous anti-tumor Ab. Favorable FcgRs may support the induction of in vivo antibody-dependent cell-mediated cytotoxicity (ADCC) or antibody-dependent cellular phagocytosis (ADCP). In addition, ADCP by APC with a favorable pattern of FcgRs, may be playing a role in enhancing induction of effective adaptive immunity, via augmented antigen presentation. Further analyses are needed to validate these exploratory findings and clarify the mechanisms by which these favorable FcgR genotypes are associated with improved outcome in these patients with mRCC treated with HD-IL2.

Background and Methods: Previous studies identifying risk factors for catheter related blood stream infections (BSI) have relied on labor-intensive paper chart review. The electronic medical record (EMR) can provide real-time data for profiling patients at risk for BSI. Our study’s aim was to use our hospital EMR to identify risk factors and develop a clinical predictive model for catheter related BSI from June 2001-June 2002. Using a modified CDC definition for BSI, we retrospectively extracted a number of variables from the EMR data repository including demographics, medications, nutritional status, presence of diabetes (DM), skin/wound status, use of a mechanical ventilator, and presence of a urinary catheter or central/arterial/PICC catheter. We developed a Cox Proportional Hazards model using half the cohort (14,977 controls and 123 BSI cases), and validated the model using the other half. Final variables in the multivariate model were chosen by clinical relevance, significance on univariate analysis and by step-wise automated selection. Results: The final model contained: use of antibiotics (HR 4.6), central venous catheter for 0-6 days (HR 1.8), central venous catheter for greater or equal to 7 days (HR 1.3), tunneled central venous port (HR 9.3) and DM (HR 2.1). Variables from multivariate analysis were used for the predictive index; points were derived from the respective HR of the Cox model. A cutoff value that maximized sensitivity (75%) and specificity (89%) had a positive predictive value (PPV) of .05. This model was validated on the second half of the cohort (122 BSI, 14,977 ‘non-cases’) with resultant sensitivity of 69%, specificity of 88% and PPV of 0.05. Comparison of the two models revealed no significant differences in the sensitivity, specificity and PPV. Conclusion: We successfully used a hospital-based EMR in developing a Cox Proportional Hazards model for catheter related BSI. This model was used to derive a predictive index. At a cutoff point providing a sensitivity of 75% and specificity of 89% for finding patients who develop catheter related BSI, the index had a PPV 0.05. When applied to a predictive index, real time data gathered from the EMR may assist in identifying patients at risk for a catheter related BSI and may be further utilized as part of a protocol driven, preventive strategy for catheter related BSI risk reduction.

57 Background: BMT survivors are underrepresented in survivorship research, yet are at high risk for complications. Practice guidelines are vague, non-BMT clinicians are inadequately informed, and communication between BMT and non-BMT clinicians is inconsistent. Our objective is to develop EHR-integrated survivorship care planning that is user-centered, supports non-BMT clinician and survivor needs, but does not adversely impact clinical workflow. Methods: A multidisciplinary team of clinicians (primary care, oncology, BMT), engineers, and EHR analysts used a systems engineering approach to identify barriers and facilitators to BMT survivorship care planning. The team identified patient data categories to include in BMT survivorship care plan (SCP) templates, as well as examined tasks, technology, workflows and individual roles and responsibilities necessary to support care planning. Results: Facilitators include: potential for EHR to discretely capture individual diagnosis and treatment data to create accurate SCPs addressing survivor and primary care information needs. Barriers are: lack of EHR inter-operability which prevents sharing of patient data outside the BMT center’s EHR system, reliance on manual entry of critical data elements into the SCP (i.e. majority of the 88 patient data categories, identified by the team, are non-discrete in the EHR), inefficient or absent survivorship workflows, lack of resources (including time, dedicated clinical staff, space, SCP content), poorly defined roles and responsibilities for survivorship care provision, and lack of evidence-based BMT survivorship guidelines. Conclusions: Work system barriers impede use of the EHR to support survivorship care planning. Steps to overcome barriers: design discrete fields in the EHR to support patient-level data capture, re-engineer existing workflows to support survivorship care planning, obtain BMT program consensus on SCP content, and evaluate user-centeredness of SCPs. This research has the potential to improve feasibility and sustainability of survivorship care planning activities, resulting in improved communication and care coordination for BMT survivors.

Summary Objective: Rigorous human-computer interaction (HCI) design methodologies have not traditionally been applied to the development of clinical trial participant tracking (CTPT) tools. Given the frequent use of iconic HCI models in CTPTs, and prior evidence of usability problems associated with the use of ambiguous icons in complex interfaces, such approaches may be problematic. Presentation Discovery (PD), a knowledge-anchored HCI design method, has been previously demonstrated to improve the design of iconic HCI models. In this study, we compare the usability of a CTPT HCI model designed using PD and an intuitively designed CTPT HCI model. Methods: An iconic CPTP HCI model was created using PD. The PD-generated and an existing iconic CTPT HCI model were subjected to usability testing, with an emphasis on task accuracy and completion times. Study participants also completed a qualitative survey instrument to evaluate subjective satisfaction with the two models. Results: CTPT end-users reliably and reproducibly agreed on the visual manifestation and semantics of prototype graphics generated using PD. The performance of the PD-generated iconic HCI model was equivalent to an existing HCI model for tasks at multiple levels of complexity, and in some cases superior. This difference was particularly notable when tasks required an understanding of the semantic meanings of multiple icons. Conclusion: The use of PD to design an iconic CTPT HCI model generated beneficial results and improved end-user subjective satisfaction, while reducing task completion time. Such results are desirable in information and time intensive domains, such as clinical trials management. Citation: Payne PRO, Embi PJ, Johnson SB, Mendonca E, Starren J. Improving clinical trial participant tracking tools using knowledge-anchored design methodologies. Appl Clin Inf 2010; 1: 177–196 http://dx.doi.org/10.4338/ACI-2010-02-RA-0012

Objective: To identify some of the challenges that medical residents face in addressing their information needs in an inpatient setting, by examining how voice capture in natural language of clinical questions fits into workflow, and by characterizing the focus, format, and semantic content and complexity of their questions. Design: Internal medicine residents captured information needs on a digital recorder while on a hospital inpatient service and then participated in semi-structured interviews. Measurements: Interviews were analyzed to identify emergent themes. Recorded questions were analyzed for focus (diagnosis, treatment, or epidemiology) and format, either foreground (specific knowledge relating to an individual patient) or background (general knowledge about a condition). Semantic concepts and types were identified using MetaMap (UMLS - Unified Medical Language System) and manually. Results: Voice recording of questions appeared to unmask residents' latent information needs. Although residents were able to record questions during workflow, there was a delay from the time questions materialized to when they were recorded. Question focus was distributed among diagnosis (32%), treatment (40%), and epidemiology (28%), and the majority of questions were background (69%). Questions were semantically complex; foreground and background questions averaged 12.6 (SD 6.0) and 9.1 (SD 6.0) UMLS concepts, respectively. MetaMap failed to recognize concepts when residents used acronyms or abbreviations or omitted key terms. Conclusions: We found that it is feasible for residents to capture their clinical questions in natural language during workflow and that recording questions may prompt awareness of previously unrecognized information needs. However, the semantic complexity of typical questions and mapping failures due to residents' use of acronyms and abbreviations present challenges to machine-based extraction of semantic content.

Medical logic modules are a procedural representation for sharing task-specific knowledge for decision support systems. Based on the premise that clinicians may perceive object-oriented expressions as easier to read than procedural rules in Arden Syntax-based medical logic modules, we developed a method for improving the readability of medical logic modules. Two approaches were applied: exploiting the concept-oriented features of the Medical Entities Dictionary and building an executable Java program to replace Arden Syntax procedural expressions. The usability evaluation showed that 66% of participants successfully mapped all Arden Syntax rules to Java methods. These findings suggest that these approaches can play an essential role in the creation of human readable medical logic modules and can potentially increase the number of clinical experts who are able to participate in the creation of medical logic modules. Although our approaches are broadly applicable, we specifically discuss the relevance to concept-oriented nursing terminologies and automated processing of task-specific nursing knowledge.

Clinical decision-support systems (CDSSs) are computer programs that are designed to provide expert support for health professionals making clinical decisions. The goal of these systems is to help health professionals analyze patient data and make decisions regarding diagnosis, prevention, and treatment of health problems. This article discusses the characteristics of such systems, addresses the challenges in developing them, identifies potential barriers for their use in clinical practice, and provides perspectives for the future.

Wireless handheld technology provides new ways to deliver and present information. As with any technology, its unique features must be taken into consideration and its applications designed accordingly. In the clinical setting, availability of needed information can be crucial during the decision-making process. Preliminary studies performed at New York Presbyterian Hospital (NYPH) determined that there are inadequate access to information and ineffective communication among clinicians (potential proximal causes of medical errors). In response to these findings, the authors have been developing extensions to their Web-based clinical information system including PalmCIS, an application that provides access to needed patient information via a wireless personal digital assistant (PDA). The focus was on achieving end-to-end security and developing a highly usable system. This report discusses the motivation behind PalmCIS, design and development of the system, and future directions.

Background/Aims New terms are rapidly appearing in the literature and practice of clinical medicine and translational research. To catalog real-world usage of medical terms, we report the first construction of an online dictionary of clinical and translational medicinal terms, which are computationally generated in near real-time using a big data approach. This project is NIH CTSA-funded and developed by the Marshfield Clinic Research Foundation in conjunction with University of Wisconsin - Madison. Currently titled Marshfield Dictionary of Clinical and Translational Science (MD-CTS), this application is a Google-like word search tool. By entering a term into the search bar, MD-CTS will display that term’s definition, usage examples, contextual terms, related images, and ontological information. A prototype is available for public viewing at http://spellchecker.mfldclin.edu/.

Only 38 % of young adults with hypertension have controlled blood pressure. Lifestyle education is a critical initial step for hypertension control. Previous studies have not assessed the type and frequency of lifestyle education in young adults with incident hypertension. The purpose of this study was to determine patient, provider, and visit predictors of documented lifestyle education among young adults with incident hypertension. We conducted a retrospective analysis of manually abstracted electronic health record data. A random selection of adults 18–39 years old (n = 500), managed by a large academic practice from 2008 to 2011 and who met JNC 7 clinical criteria for incident hypertension, participated in the study. The primary outcome was the presence of any documented lifestyle education during one year after meeting criteria for incident hypertension. Abstracted topics included documented patient education for exercise, tobacco cessation, alcohol use, stress management/stress reduction, Dietary Approaches to Stop Hypertension (DASH) diet, and weight loss. Clinic visits were categorized based upon a modified established taxonomy to characterize patients’ patterns of outpatient service. We excluded patients with previous hypertension diagnoses, previous antihypertensive medications, or pregnancy. Logistic regression was used to identify predictors of documented education. Overall, 55 % (n = 275) of patients had documented lifestyle education within one year of incident hypertension. Exercise was the most frequent topic (64 %). Young adult males had significantly decreased odds of receiving documented education. Patients with a previous diagnosis of hyperlipidemia or a family history of hypertension or coronary artery disease had increased odds of documented education. Among visit types, chronic disease visits predicted documented lifestyle education, but not acute or other/preventive visits. Among young adults with incident hypertension, only 55 % had documented lifestyle education within one year. Knowledge of patient, provider, and visit predictors of education can help better target the development of interventions to improve young adult health education and hypertension control.

Objective The completion of sequencing the human genome in 2003 has spurred the production and collection of genetic data at ever increasing rates. Genetic data obtained for clinical purposes, as is true for all results of clinical tests, are expected to be included in patients’ medical records. With this explosion of information, questions of what, when, where and how to incorporate genetic data into electronic health records (EHRs) have reached a critical point. In order to answer these questions fully, this paper addresses the ethical, logistical and technological issues involved in incorporating these data into EHRs. Materials and methods This paper reviews journal articles, government documents and websites relevant to the ethics, genetics and informatics domains as they pertain to EHRs. Results and discussion The authors explore concerns and tasks facing health information technology (HIT) developers at the intersection of ethics, genetics, and technology as applied to EHR development. Conclusions By ensuring the efficient and effective incorporation of genetic data into EHRs, HIT developers will play a key role in facilitating the delivery of personalized medicine.