Machine learning-based donor permission extraction from informed consent documents.

BACKGROUND: With more clinical trials are offering optional participation in the collection of bio-specimens for biobanking comes the increasing complexity of requirements of informed consent forms. The aim of this study is to develop an automatic natural language processing (NLP) tool to annotate informed consent documents to promote biorepository data regulation, sharing, and decision support. We collected informed consent documents from several publicly available sources, then manually annotated them, covering sentences containing permission information about the sharing of either bio-specimens or donor data, or conducting genetic research or future research using bio-specimens or donor data. RESULTS: We evaluated a variety of machine learning algorithms including random forest (RF) and support vector machine (SVM) for the automatic identification of these sentences. 120 informed consent documents containing 29,204 sentences were annotated, of which 1250 sentences (4.28%) provide answers to a permission question. A support vector machine (SVM) model achieved a F-1 score of 0.95 on classifying the sentences when using a gold standard, which is a prefiltered corpus containing all relevant sentences. CONCLUSIONS: This study provides the feasibility of using machine learning tools to classify permission-related sentences in informed consent documents.

Tolerance to oral anticancer agent treatment in older adults with cancer: a secondary analysis of data from electronic health records and a pilot study of patient-reported outcomes.

BACKGROUND: More than 60% of cancer cases occur in older adults, and many are treated with oral anticancer agents. Yet, the treatment tolerability in older adults has not been fully understood due to their underrepresentation in oncology clinical trials, creating challenges for treatment decision-making and symptom management. The objective of this study was to investigate the tolerance of capecitabine, an example of oral chemotherapy, among older adults with cancer and explore factors associated with capecitabine-related side effects and treatment changes, to enhance supportive care. METHODS: A secondary analysis used combined data from electronic health records and a pilot study of patient-reported outcomes, with a total of 97 adult patients taking capecitabine during 2016-2017, including older adult patients aged 65 years or older (n = 43). The data extracted included patient socio-demographics, capecitabine information, side effects, and capecitabine treatment changes (dose reductions and dose interruptions). Bivariate correlations, negative binomial regression, and multiple linear regression were conducted for data analysis. RESULTS: Older adults were more likely to experience fatigue (86% vs. 51%, p = .001) and experienced more severe fatigue (ß = 0.44, p = 0.03) and hand-foot syndrome (HFS) (ß = 1.15, p = 0.004) than younger adults. The severity of fatigue and HFS were associated with the number of outpatient medications (ß = 0.06, p = 0.006) and the duration of treatment (ß = 0.50, p = 0.009), respectively. Correlations among side effects presented different patterns between younger and older adults. Although more older adults experienced dose reductions (21% vs. 13%) and dose interruptions (33% vs. 28%) than younger adults, the differences were not statistically different. Female sex, breast cancer diagnosis, capecitabine monotherapy, and severe HFS were found to be associated with dose reductions (p-values < 0.05). CONCLUSIONS: Older adults were less likely to tolerate capecitabine treatment and had different co-occurring side effects compared to younger adults. While dose reductions are common among older adults, age 65 years or older may not be an independent factor of treatment changes. Other socio-demographic and clinical factors may be more likely to be associated. Future studies can be conducted to further explore older adults' tolerance to a variety of oral anticancer agents to generate more evidence to support optimal treatment decision-making and symptom management.

Sagittal abdominal diameter and its socioeconomic correlates: perspective of sex differences.

BACKGROUND: Sagittal abdominal diameter (SAD) is an anthropometric index associated with visceral adiposity. It remains unclear whether SAD and its socio-economic correlates differ in women and men, which limits the epidemiological and clinical applications of the SAD measurement. The aims of this study are to examine the sex differences in SAD and its socio-economic correlates. METHODS: A complex stratified multistage clustered sampling design was used to select 6975 men and 7079 women aged 18 years or more from the National Health Nutrition and Examination Survey 2011-2016, representative of the US civilian non-institutionalized population. SAD was measured in accordance to the standard protocols using a two-arm abdominal caliper. The sex differences in SAD and its socio-economic correlates were evaluated by performing weighted independent t tests and weighted multiple regression. RESULTS: SAD was lower in women than in men in the entire sample, as well as in all the subgroups characterized by age, race, birth place, household income, and body mass index except for non-Hispanic blacks and those with household income < $20,000. Adjusted for other characteristics, age, birth place, household income, and body mass index were associated with SAD in both women and men. Black women were associated with higher SAD then white women (p < .0001), and Hispanic and Asian men were associated with lower SAD than white men (both p < .01). Women born in other countries were more likely to have lower SAD than women born in the US (p < .0001), and so were men (p = .0118). Both women and men with a household income of <$75,000 had higher SAD than those with an income of over $75,000. The associations of age, race, and household income with SAD differed in women and men. CONCLUSION: SAD is lower in women than in men, in the general population as well as in the most socio-economic subgroups. While socio-economic correlates of SAD are similar in women and men, the associations of age, race, and household income with SAD vary across sex.

Acceptance and Use of Home-Based Electronic Symptom Self-Reporting Systems in Patients With Cancer: Systematic Review.

BACKGROUND: Electronic symptom self-reporting systems (e-SRS) have been shown to improve symptoms and survival in patients with cancer. However, patient engagement in using e-SRS for voluntary symptom self-reporting is less optimal. Multiple factors can potentially affect patients' acceptance and engagement in using home-based e-SRS. However, such factors have not been fully explored in cancer populations. OBJECTIVE: The aim of this study is to understand the acceptance and use of home-based e-SRS by patients with cancer and identify associated facilitators and barriers. METHODS: PubMed, CINAHL, Scopus, and PsycINFO (January 2010 to March 2020) were searched using a combination of Medical Subject Headings (MeSH) terms and keywords such as symptom self-reporting, electronic/technology, cancer, and their synonyms. Included studies focused on the use of home-based e-SRS by patients with cancer and their families. Studies on patients' use of e-SRS in clinical settings only were excluded. Of the 3740 papers retrieved, 33 were included in the final review. Factors associated with patient acceptance and use of e-SRS were extracted and synthesized. RESULTS: Most e-SRS were web based (22/33, 66%) or mobile app based (9/33, 27%). The e-SRS initial acceptance, represented by patient enrollment rates, ranged from 40% (22/55) to 100% (100/100). High e-SRS acceptance was rated by 69% (59/85) to 77.6% (337/434) of the patients after they used the system. The e-SRS use, measured by patients' response rates to questionnaires (ranging from 1596/3521, 45.33% to 92%) or system log-on rates (ranging from 4/12, 33% to 99/100, 99%), declined over time in general patterns. Few studies (n=7) reported e-SRS use beyond 6 months, with the response rates ranging from 62% (40/64) to 85.1% (541/636) and the log-on rates ranging from 63.6% (103/162) to 77% (49/64). The availability of compatible devices and technical support, interactive system features, information accessibility, privacy, questionnaire quality, patient physical/psychosocial status, and age were associated with patient acceptance and use of home-based e-SRS. CONCLUSIONS: Acceptance and use of home-based e-SRS by patients with cancer varied significantly across studies, as assessed by a variety of approaches. The lack of access to technology has remained a barrier to e-SRS adoption. Interactive system features and personalized questionnaires may increase patient engagement. More studies are needed to further understand patients' long-term use of home-based e-SRS behavior patterns to develop personalized interventions to support symptom self-management and self-reporting of patients with cancer for optimal health outcomes.

Architecture and usability of OntoKeeper, an ontology evaluation tool.

BACKGROUND: The existing community-wide bodies of biomedical ontologies are known to contain quality and content problems. Past research has revealed various errors related to their semantics and logical structure. Automated tools may help to ease the ontology construction, maintenance, assessment and quality assurance processes. However, there are relatively few tools that exist that can provide this support to knowledge engineers. METHOD: We introduce OntoKeeper as a web-based tool that can automate quality scoring for ontology developers. We enlisted 5 experienced ontologists to test the tool and then administered the System Usability Scale to measure their assessment. RESULTS: In this paper, we present usability results from 5 ontologists revealing high system usability of OntoKeeper, and use-cases that demonstrate its capabilities in previous published biomedical ontology research. CONCLUSION: To the best of our knowledge, OntoKeeper is the first of a few ontology evaluation tools that can help provide ontology evaluation functionality for knowledge engineers with good usability.

Do Patient-Centered Medical Home Access and Care Coordination Measures Reflect the Contribution of All Team Members? A Systematic Review.

Patient-Centered Medical Home (PCMH) evaluations have primarily focused on primary care providers and not on the primary care team. This systematic literature review examined the extent to which access and care coordination measures in PCMH reflect the involvement of associate care providers (ACPs), which include registered and licensed practical nurses, nursing and medical assistants, clerks, pharmacists, social workers, and dietitians. Among 42 studies, few measures specified ACP roles or linked ACP care to outcomes. Increasing attention on team-based care emphasizes a vital need to reframe measures within a team context.

Nurse staffing and inpatient hospital mortality.

BACKGROUND: Cross-sectional studies of hospital-level administrative data have shown an association between lower levels of staffing of registered nurses (RNs) and increased patient mortality. However, such studies have been criticized because they have not shown a direct link between the level of staffing and individual patient experiences and have not included sufficient statistical controls. METHODS: We used data from a large tertiary academic medical center involving 197,961 admissions and 176,696 nursing shifts of 8 hours each in 43 hospital units to examine the association between mortality and patient exposure to nursing shifts during which staffing by RNs was 8 hours or more below the staffing target. We also examined the association between mortality and high patient turnover owing to admissions, transfers, and discharges. We used Cox proportional-hazards models in the analyses with adjustment for characteristics of patients and hospital units. RESULTS: Staffing by RNs was within 8 hours of the target level for 84% of shifts, and patient turnover was within 1 SD of the day-shift mean for 93% of shifts. Overall mortality was 61% of the expected rate for similar patients on the basis of modified diagnosis-related groups. There was a significant association between increased mortality and increased exposure to unit shifts during which staffing by RNs was 8 hours or more below the target level (hazard ratio per shift 8 hours or more below target, 1.02; 95% confidence interval [CI], 1.01 to 1.03; P<0.001). The association between increased mortality and high patient turnover was also significant (hazard ratio per high-turnover shift, 1.04; 95% CI, 1.02 to 1.06; P<0.001). CONCLUSIONS: In this retrospective observational study, staffing of RNs below target levels was associated with increased mortality, which reinforces the need to match staffing with patients' needs for nursing care. (Funded by the Agency for Healthcare Research and Quality.).

Using present-on-admission coding to improve exclusion rules for quality metrics: the case of failure-to-rescue.

BACKGROUND: The Agency for Healthcare Research and Quality (AHRQ) patient safety indicator "death among surgical inpatients with serious treatable complications" (failure-to-rescue) uses rules to exclude complications presumed to be present-on-admission (POA). Like other administrative data-based quality measures, exclusion rules were developed with limited information on whether complications were POA. We examine whether the accuracy of failure-to-rescue exclusion rules can be improved with data with good POA indicators. METHODS: POA-coded data from 243,825 discharges from a large academic medical center were used to develop 3 failure-to-rescue exclusion rules. Data from 82,871 discharges from California hospitals screened for good POA coding practices was used as a validation sample. The AHRQ failure-to-rescue measure and 3 new measures based on alternative exclusion rules were compared on sensitivity, specificity, and C-statistics for prediction of POA status. Using data from the AHRQ HCUP National Inpatient Sample, the alternative specifications were tested for sensitivity to nurse staffing. RESULTS: The AHRQ exclusion rules had sensitivity of 18.5%, specificity 92.1%, and a C-statistic of 0.553. All POA-informed specifications of exclusion rules improved the C-statistic of the failure-to-rescue measure and its sensitivity, with modest losses of specificity. For all tested specifications, higher licensed hours and proportions of registered nurse were statistically significant and associated with lower risk of death. CONCLUSIONS: Failure-to-rescue is a robust quality measure, sensitive to nursing across alternative exclusion rule specifications. Despite expanded POA coding, exclusion-based rules are needed to analyze datasets not coded for POA, legacy datasets, and datasets with poor POA coding. POA-informed construction of exclusions significantly improves rules identifying POA complications.

The case for expressing nursing theories using ontologies.

Nursing and informatics share a common strength in their use of structured representations of domains, specifically the underlying notion of 'things' (ie, concepts, constructs, or named entities) and the relationships among those things. Accurate representation of nursing knowledge in machine-interpretable formats is a necessary next step for leveraging contemporary technologies. Expressing validated nursing theories in ontologies, and in particular formal ontologies, would serve not only nursing, but also investigators from other domains, clinical information system developers, and the users of advanced technologies such as artificial intelligence that seek to learn from the real-world data and evidence generated by nurses and others. Such efforts will enable sharing knowledge and conceptualizations about phenomena across the domains of nursing and generating, testing, revising, and providing theoretically-based perspectives when leveraging contemporary technologies. Nursing is well situated for this work, leveraging intentional and focused collaborations among nurse informaticists, scientists, and theorists.

CRENO: An ontology to model concepts relating to culture, race, ethnicity, and nationality for health data.

Generating categories and classifications is a common function in life science research; however, categorizing the human population based on "race" remains controversial. There is an awareness and recognition of social-economic disparities with respect to health which are sometimes impacted by someone's ethnicity or race. This work describes an endeavor to develop a computable ontology model to represent a standardization of the concepts surrounding culture, race, ethnicity, and nationality - concepts misrepresented widely. We constructed an OWL ontology based on reliable resources with iterative human expert evaluations and aligned it to existing biomedical ontological models. The effort produced a preliminary ontology that expresses concepts related to classes of ethnic, racial, national, and cultural identities and showcases how health disparity data can be linked and expressed within our ontological framework. Future work will explore automated methods to expand the ontology and its utilization for clinical informatics.

Leveraging EHR data for outcomes and comparative effectiveness research in oncology.

Along with the increasing adoption of electronic health records (EHRs) are expectations that data collected within EHRs will be readily available for outcomes and comparative effectiveness research. Yet the ability to effectively share and reuse data depends on implementing and configuring EHRs with these goals in mind from the beginning. Data sharing and integration must be planned both locally as well as nationally. The rich data transmission and semantic infrastructure developed by the National Cancer Institute (NCI) for research provides an excellent example of moving beyond paper-based paradigms and exploiting the power of semantically robust, network-based systems, and engaging both domain and informatics expertise. Similar efforts are required to address current challenges in sharing EHR data.

A Concept Analysis of Oral Anticancer Agent Self-management.

BACKGROUND: The rapid development and adoption of oral anticancer agents (OAAs) for cancer management have shifted patients' roles from recipient to owner of their care delivery, assuming their responsibilities for self-managing their OAA treatments at home, while the concept of oral anticancer agent self-management (OAA-SM) has not been well clarified and defined. OBJECTIVE: This study was to clarify the concept of OAA-SM and identify major components, influential factors, and consequences of OAA-SM, as well as propose a representative conceptual model of OAA-SM. METHODS: A literature review was conducted concerning the concept and application of OAA-SM. The Walker and Avant method for concept analysis was utilized to guide the examination of OAA-SM. RESULTS: OAA-SM is a multifaceted and dynamic process that requires continuous adaptation by patients as multiple self-management challenges can emerge throughout OAA treatments. The defining attributes of OAA-SM include OAA adherence, adverse-effect self-management, patient-provider communication, and OAA safe storage, handling, and administration practices. Oral anticancer agent-SM is potentially influenced by a variety of patient-related, OAA-related, and healthcare system factors. Effective OAA-SM is associated with better patient and healthcare outcomes. CONCLUSIONS: The clarification of the concept of OAA-SM and the identification of attributes of OAA-SM and their interrelationships contribute to the body of knowledge in OAA-SM. IMPLICATIONS FOR PRACTICE: This concept analysis provides the foundation to increase healthcare providers' understanding of patients' needs for OAA-SM support and guides the development of patient-centered interventions to empower and engage patients and their families in effective OAA-SM, and improve patients' quality of life and care.

Technologies for Medication Adherence Monitoring and Technology Assessment Criteria: Narrative Review.

BACKGROUND: Accurate measurement and monitoring of patient medication adherence is a global challenge because of the absence of gold standard methods for adherence measurement. Recent attention has been directed toward the adoption of technologies for medication adherence monitoring, as they provide the opportunity for continuous tracking of individual medication adherence behavior. However, current medication adherence monitoring technologies vary according to their technical features and data capture methods, leading to differences in their respective advantages and limitations. Overall, appropriate criteria to guide the assessment of medication adherence monitoring technologies for optimal adoption and use are lacking. OBJECTIVE: This study aims to provide a narrative review of current medication adherence monitoring technologies and propose a set of technology assessment criteria to support technology development and adoption. METHODS: A literature search was conducted on PubMed, Scopus, CINAHL, and ProQuest Technology Collection (2010-present) using the combination of keywords medication adherence, measurement technology, and monitoring technology. The selection focused on studies related to medication adherence monitoring technology and its development and use. The technological features, data capture methods, and potential advantages and limitations of the identified technology applications were extracted. Methods for using data for adherence monitoring were also identified. Common recurring elements were synthesized as potential technology assessment criteria. RESULTS: Of the 3865 articles retrieved, 98 (2.54%) were included in the final review, which reported a variety of technology applications for monitoring medication adherence, including electronic pill bottles or boxes, ingestible sensors, electronic medication management systems, blister pack technology, patient self-report technology, video-based technology, and motion sensor technology. Technical features varied by technology type, with common expectations for using these technologies to accurately monitor medication adherence and increase adoption in patients' daily lives owing to their unobtrusiveness and convenience of use. Most technologies were able to provide real-time monitoring of medication-taking behaviors but relied on proxy measures of medication adherence. Successful implementation of these technologies in clinical settings has rarely been reported. In all, 28 technology assessment criteria were identified and organized into the following five categories: development information, technology features, adherence to data collection and management, feasibility and implementation, and acceptability and usability. CONCLUSIONS: This narrative review summarizes the technical features, data capture methods, and various advantages and limitations of medication adherence monitoring technology reported in the literature and the proposed criteria for assessing medication adherence monitoring technologies. This collection of assessment criteria can be a useful tool to guide the development and selection of relevant technologies, facilitating the optimal adoption and effective use of technology to improve medication adherence outcomes. Future studies are needed to further validate the medication adherence monitoring technology assessment criteria and construct an appropriate technology assessment framework.

Regulations and Norms for Reuse of Residual Clinical Biospecimens and Health Data.

Nurse scientists are increasingly interested in conducting secondary research using real world collections of biospecimens and health data. The purposes of this scoping review are to (a) identify federal regulations and norms that bear authority or give guidance over reuse of residual clinical biospecimens and health data, (b) summarize domain experts' interpretations of permissions of such reuse, and (c) summarize key issues for interpreting regulations and norms. Final analysis included 25 manuscripts and 23 regulations and norms. This review illustrates contextual complexity for reusing residual clinical biospecimens and health data, and explores issues such as privacy, confidentiality, and deriving genetic information from biospecimens. Inconsistencies make it difficult to interpret, which regulations or norms apply, or if applicable regulations or norms are congruent. Tools are necessary to support consistent, expert-informed consent processes and downstream reuse of residual clinical biospecimens and health data by nurse scientists.

Evaluating and Extending the Informed Consent Ontology for Representing Permissions from the Clinical Domain.

The purpose of this study was to evaluate, revise, and extend the Informed Consent Ontology (ICO) for expressing clinical permissions, including reuse of residual clinical biospecimens and health data. This study followed a formative evaluation design and used a bottom-up modeling approach. Data were collected from the literature on US federal regulations and a study of clinical consent forms. Eleven federal regulations and fifteen permission-sentences from clinical consent forms were iteratively modeled to identify entities and their relationships, followed by community reflection and negotiation based on a series of predetermined evaluation questions. ICO included fifty-two classes and twelve object properties necessary when modeling, demonstrating appropriateness of extending ICO for the clinical domain. Twenty-six additional classes were imported into ICO from other ontologies, and twelve new classes were recommended for development. This work addresses a critical gap in formally representing permissions clinical permissions, including reuse of residual clinical biospecimens and health data. It makes missing content available to the OBO Foundry, enabling use alongside other widely-adopted biomedical ontologies. ICO serves as a machine-interpretable and interoperable tool for responsible reuse of residual clinical biospecimens and health data at scale.

Infrastructuring an organizational node for a federated research and data network: A case study from a sociotechnical perspective.

BACKGROUND: Local nodes on federated research and data networks (FR&DNs) provide enabling infrastructure for collaborative clinical and translational research. Studies in other fields note that infrastructuring, that is, work to identify and negotiate relationships among people, technologies, and organizations, is invisible, unplanned, and undervalued. This may explain the limited literature on nodes in FR&DNs in health care. METHODS: A retrospective case study of one PCORnet® node explored 3 questions: (1) how were components of infrastructure assembled; (2) what specific work was required; and (3) what theoretically grounded, pragmatic questions should be considered when infrastructuring a node for sustainability. Artifacts, work efforts, and interviews generated during node development and implementation were reviewed. A sociotechnical lens was applied to the analysis. Validity was established with internal and external partners. RESULTS: Resources, services, and expertise needed to establish the node existed within the organization, but were scattered across work units. Aligning, mediating, and institutionalizing for sustainability among network and organizational teams, governance, and priorities consumed more work efforts than deploying technical aspects of the node. A theoretically based set of questions relevant to infrastructuring a node was developed and organized within a framework of infrastructuring emphasizing enacting technology, organizing work, and institutionalizing; validity was established with internal and external partners. CONCLUSIONS: FR&DNs are expanding; we provide a sociotechnical perspective on infrastructuring a node. Future research should evaluate the applicability of the framework and questions to other node and network configurations, and more broadly the infrastructuring required to enable and support federated clinical and translational science.

Expressing and Executing Informed Consent Permissions Using SWRL: The All of Us Use Case.

The informed consent process is a complicated procedure involving permissions as well a variety of entities and actions. In this paper, we discuss the use of Semantic Web Rule Language (SWRL) to further extend the Informed Consent Ontology (ICO) to allow for semantic machine-based reasoning to manage and generate important permission-based information that can later be viewed by stakeholders. We present four use cases of permissions from the All of Us informed consent document and translate these permissions into SWRL expressions to extend and operationalize ICO. Our efforts show how SWRL is able to infer some of the implicit information based on the defined rules, and demonstrate the utility of ICO through the use of SWRL extensions. Future work will include developing formal and generalized rules and expressing permissions from the entire document, as well as working towards integrating ICO into software systems to enhance the semantic representation of informed consent for biomedical research.

Lessons Learned for Identifying and Annotating Permissions in Clinical Consent Forms.

BACKGROUND: The lack of machine-interpretable representations of consent permissions precludes development of tools that act upon permissions across information ecosystems, at scale. OBJECTIVES: To report the process, results, and lessons learned while annotating permissions in clinical consent forms. METHODS: We conducted a retrospective analysis of clinical consent forms. We developed an annotation scheme following the MAMA (Model-Annotate-Model-Annotate) cycle and evaluated interannotator agreement (IAA) using observed agreement (A o), weighted kappa (κw ), and Krippendorff's α. RESULTS: The final dataset included 6,399 sentences from 134 clinical consent forms. Complete agreement was achieved for 5,871 sentences, including 211 positively identified and 5,660 negatively identified as permission-sentences across all three annotators (A o = 0.944, Krippendorff's α = 0.599). These values reflect moderate to substantial IAA. Although permission-sentences contain a set of common words and structure, disagreements between annotators are largely explained by lexical variability and ambiguity in sentence meaning. CONCLUSION: Our findings point to the complexity of identifying permission-sentences within the clinical consent forms. We present our results in light of lessons learned, which may serve as a launching point for developing tools for automated permission extraction.

Nurses' ratings of their health and professional work environments.

Interactions between nursing work environments and nurses' health are of growing significance, given the aging work force, nursing shortage, and workplace health risks. This study examined relationships among nurses' ratings of health behaviors, health status, and professional work environments. Registered nurses (N = 3,132) from five multi-state settings completed an electronic survey. Participants' general health ratings were good, yet stress levels remained the one consistent predictor of poorer health ratings and work environment ratings in regression models. Additionally, more than half of the participants reported being overweight, only 50% met physical activity standards, more than two thirds reported a history of back or needlestick injuries, and 44% and 62% reported experiencing verbal abuse by colleagues and patients, respectively. Contrary to other studies, professional work environment as measured in this study did not predict nurses' health ratings. Further study of the impact of stress on long-term health outcomes and work force retention, as well as on worksite health strategies, is needed.

Nursing-sensitive safety and quality outcomes: the taming of a wicked problem?

There are tremendous opportunities associated with the increasing interest in outcomes that are sensitive to the effects of nursing. However, the challenges in realizing these opportunities are significant, and can be characterized as "wicked". Taming these challenges requires that we manage highly interdependent processes and techniques, including health information technologies.