Showing papers by "Regenstrief Institute published in 2019"
TL;DR: A narrative review of measurement-based care, informed by implementation science, offers a 10-point research agenda to improve the integration of MBC into clinical practice.
Abstract: Importance Measurement-based care (MBC) is the systematic evaluation of patient symptoms before or during an encounter to inform behavioral health treatment. Despite MBC’s demonstrated ability to enhance usual care by expediting improvements and rapidly detecting patients whose health would otherwise deteriorate, it is underused, with typically less than 20% of behavioral health practitioners integrating it into their practice. This narrative review addresses definitional issues, offers a concrete and evaluable operationalization of MBC fidelity, and summarizes the evidence base and utility of MBC. It also synthesizes the extant literature’s characterization of barriers to and strategies for supporting MBC implementation, sustainment, and scale-up. Observations Barriers to implementing MBC occur at multiple levels: patient (eg, concerns about confidentiality breach), practitioner (eg, beliefs that measures are no better than clinical judgment), organization (eg, no resources for training), and system (eg, competing requirements). Implementation science—the study of methods to integrate evidence-based practices such as MBC into routine care—offers strategies to address barriers. These strategies include using measurement feedback systems, leveraging local champions, forming learning collaboratives, training leadership, improving expert consultation with clinical staff, and generating incentives. Conclusions and Relevance This narrative review, informed by implementation science, offers a 10-point research agenda to improve the integration of MBC into clinical practice: (1) harmonize terminology and specify MBC’s core components; (2) develop criterion standard methods for monitoring fidelity and reporting quality of implementation; (3) develop algorithms for MBC to guide psychotherapy; (4) test putative mechanisms of change, particularly for psychotherapy; (5) develop brief and psychometrically strong measures for use in combination; (6) assess the critical timing of administration needed to optimize patient outcomes; (7) streamline measurement feedback systems to include only key ingredients and enhance electronic health record interoperability; (8) identify discrete strategies to support implementation; (9) make evidence-based policy decisions; and (10) align reimbursement structures.
246 citations
TL;DR: An institutional ethnography of three closely related research partnerships that used participatory methods with autistic adults over the years 2006–2018 is conducted to create practice-based guidelines for the inclusion of autistic adults, both as research team members and as study participants.
Abstract: As interest in autism in adulthood grows, so does the need for methods to promote the inclusion of autistic adults in research. Our objective was to create practice-based guidelines for the inclusion of autistic adults, both as research team members and as study participants. We conducted an institutional ethnography of three closely related research partnerships that used participatory methods with autistic adults over the years 2006-2018. We used an iterative approach which combined discussions with community and academic partners and artifact review. Guidelines to promote the inclusion of autistic adults as co-researchers focus on being transparent about partnership goals, clearly defining roles and choosing partners, creating processes for effective communication and power-sharing, building and maintaining trust, disseminating findings, encouraging community capacitation, and fairly compensating partners. Guidelines to promote the inclusion of autistic adults as study participants focus on maximizing autonomy and inclusion, creating an accessible consent process, offering multiple modes of participation, adapting survey instruments for use with autistic adults, creating accessible qualitative interview guides, and handling data from proxy reporters. Although these practice-based guidelines may not apply to all research teams, we hope that other researchers can capitalize on these practical lessons when including autistic adults in research.
146 citations
TL;DR: SALMON as discussed by the authors is a deep learning-based method for predicting Cox regression survival in breast cancer. But it is not suitable for the use of gene expression values as model inputs, instead of using eigengene modules from the result of gene co-expression network analysis, and the results revealed improved performance when more omics data were used in model construction.
Abstract: Improved cancer prognosis is a central goal for precision health medicine. Though many models can predict differential survival from data, there is a strong need for sophisticated algorithms that can aggregate and filter relevant predictors from increasingly complex data inputs. In turn, these models should provide deeper insight into which types of data are most relevant to improve prognosis. Deep Learning-based neural networks offer a potential solution for both problems because they are highly flexible and account for data complexity in a non-linear fashion. In this study, we implement Deep Learning-based networks to determine how gene expression data predicts Cox regression survival in breast cancer. We accomplish this through an algorithm called SALMON (Survival Analysis Learning with Multi-Omics Neural Networks), which aggregates and simplifies gene expression data and cancer biomarkers to enable prognosis prediction. The results revealed improved performance when more omics data were used in model construction. Rather than use raw gene expression values as model inputs, we innovatively use eigengene modules from the result of gene co-expression network analysis. The corresponding high impact co-expression modules and other omics data are identified by feature selection technique, then examined by conducting enrichment analysis and exploiting biological functions, escalated the interpretation of input feature from gene level to co-expression modules level. Our study shows the feasibility of discovering breast cancer related co-expression modules, sketch a blueprint of future endeavors on Deep Learning-based survival analysis. SALMON source code is available at https://github.com/huangzhii/SALMON/.
113 citations
TL;DR: An algorithm trained on half a million electronic medical records predicts chronic kidney disease in diabetic patients using a small set of defined clinical features, outperforming predictions derived from clinical trial data.
Abstract: Diagnostic procedures, therapeutic recommendations, and medical risk stratifications are based on dedicated, strictly controlled clinical trials. However, a plethora of real-world medical data exists, whereupon the increase in data volume comes at the expense of completeness, uniformity, and control. Here, a case-by-case comparison shows that the predictive power of our real world data-based model for diabetes-related chronic kidney disease outperforms published algorithms, which were derived from clinical study data.
113 citations
TL;DR: An updated summary of FIT performance for CRC is provided, how FIT sensitivity and specificity in asymptomatic, average-risk adults is evaluated is evaluated, and whether variation in reported performance characteristics among studies is a function of the threshold used to define a positive test result or the test brand is evaluated.
Abstract: Background Studies report inconsistent performance of fecal immunochemical tests (FITs) for colorectal cancer (CRC) and advanced adenomas. Purpose To summarize performance characteristics of FITs for CRC and advanced adenomas in average-risk persons undergoing screening colonoscopy (reference standard) and to identify factors affecting these characteristics. Data sources Ovid MEDLINE, PubMed, Embase, and the Cochrane Library from inception through October 2018; reference lists of studies and reviews. Study selection Two reviewers independently screened records to identify published English-language prospective or retrospective observational studies that evaluated FIT sensitivity and specificity for colonoscopic findings in asymptomatic, average-risk adults. Data extraction Two authors independently extracted data and evaluated study quality. Data synthesis Thirty-one studies (120 255 participants; 18 FITs) were included; all were judged to have low to moderate risk of bias. Performance characteristics depended on the threshold for a positive result. A threshold of 10 µg/g resulted in sensitivity of 0.91 (95% CI, 0.84 to 0.95) and a negative likelihood ratio of 0.10 (CI, 0.06 to 0.19) for CRC, whereas a threshold of greater than 20 µg/g resulted in specificity of 0.95 (CI, 0.94 to 0.96) and a positive likelihood ratio of 15.49 (CI, 9.82 to 22.39). For advanced adenomas, sensitivity was 0.40 (CI, 0.33 to 0.47) and the negative likelihood ratio was 0.67 (CI, 0.57 to 0.78) at 10 µg/g, and specificity was 0.95 (CI, 0.94 to 0.96) and the positive likelihood ratio was 5.86 (CI, 3.77 to 8.97) at greater than 20 µg/g. Studies had low to high heterogeneity, depending on the threshold. Although several FITs had adequate performance, sensitivity and specificity for CRC for 1 qualitative FIT were 0.90 and 0.91, respectively, at its single threshold of 10 µg/g; positive and negative likelihood ratios were 10.13 and 0.11, respectively. Comparison of 3 FITs at 3 thresholds was inconclusive: CIs overlapped, and the comparisons were across rather than within studies. Limitations Only English-language studies were included. Incomplete reporting limited quality assessment of some evidence. Performance characteristics are for 1-time rather than serial testing. Conclusion Single-application FITs have moderate to high sensitivity and specificity for CRC, depending on the positivity threshold. Sensitivity of 1-time testing for advanced adenomas is low, regardless of the threshold. Primary funding source Department of Medicine, Indiana University School of Medicine.
109 citations
TL;DR: BERMUDA (Batch Effect ReMoval Using Deep Autoencoders), a novel transfer-learning-based method for batch effect correction in scRNA-seq data, is presented.
Abstract: To fully utilize the power of single-cell RNA sequencing (scRNA-seq) technologies for identifying cell lineages and bona fide transcriptional signals, it is necessary to combine data from multiple experiments. We present BERMUDA (Batch Effect ReMoval Using Deep Autoencoders), a novel transfer-learning-based method for batch effect correction in scRNA-seq data. BERMUDA effectively combines different batches of scRNA-seq data with vastly different cell population compositions and amplifies biological signals by transferring information among batches. We demonstrate that BERMUDA outperforms existing methods for removing batch effects and distinguishing cell types in multiple simulated and real scRNA-seq datasets.
100 citations
TL;DR: Despite its popularity, little is known about the measurement invariance of the Patient Health Questionnaire‐9 (PHQ‐9) across U.S. sociodemographic groups, and it is found that use of a screener shown not to possess measurement invariant could result in under/over‐detection of depression.
Abstract: BACKGROUND Despite its popularity, little is known about the measurement invariance of the Patient Health Questionnaire-9 (PHQ-9) across US sociodemographic groups Use of a screener shown not to possess measurement invariance could result in under/over-detection of depression, potentially exacerbating sociodemographic disparities in depression Therefore, we assessed the factor structure and measurement invariance of the PHQ-9 across major US sociodemographic groups METHODS US population representative data came from the 2005-2016 National Health and Nutrition Examination Survey (NHANES) cohorts We conducted a measurement invariance analysis of 31,366 respondents across sociodemographic factors of sex, race/ethnicity, and education level RESULTS Considering results of single-group confirmatory factor analyses (CFAs), depression theory, and research utility, we justify a two-factor structure for the PHQ-9 consisting of a cognitive/affective factor and a somatic factor (RMSEA = 0034, TLI = 0985, CFI = 0989) On the basis of multiple-group CFAs testing configural, scalar, and strict factorial invariance, we determined that invariance held for sex, race/ethnicity, and education level groups, as all models demonstrated close model fit (RMSEA = 0025-0025, TLI = 0985-0992, CFI = 0986-0991) Finally, for all steps ΔCFI was <-0004, and ΔRMSEA was <001 CONCLUSIONS We demonstrate that the PHQ-9 is acceptable to use in major US sociodemographic groups and allows for meaningful comparisons in total, cognitive/affective, and somatic depressive symptoms across these groups, extending its use to the community This knowledge is timely as medicine moves towards alternative payment models emphasizing high-quality and cost-efficient care, which will likely incentivize behavioral and population health efforts We also provide a consistent, evidence-based approach for calculating PHQ-9 subscale scores
90 citations
08 Mar 2019
TL;DR: This study implements Deep Learning-based networks to determine how gene expression data predicts Cox regression survival in breast cancer through an algorithm called SALMON (Survival Analysis Learning with Multi-Omics Neural Networks), which aggregates and simplifies gene expressionData and cancer biomarkers to enable prognosis prediction.
Abstract: Improved cancer prognosis is a central goal for precision health medicine. Though many models can predict differential survival from data, there is a strong need for sophisticated algorithms that can aggregate and filter relevant predictors from increasingly complex data inputs. In turn, these models should provide deeper insight into which types of data are most relevant to improve prognosis. Deep Learning-based neural networks offer a potential solution for both problems because they are highly flexible and account for data complexity in a non-linear fashion. In this study, we implement Deep Learning-based networks to determine how gene expression data predicts Cox regression survival in breast cancer. We accomplish this through an algorithm called SALMON (Survival Analysis Learning with Multi-Omics Neural Networks), which aggregates and simplifies gene expression data and cancer biomarkers to enable prognosis prediction. The results revealed improved performance when more omics data were used in model construction. Rather than use raw gene expression values as model inputs, we innovatively use eigengene modules from the result of gene co-expression network analysis. The corresponding high impact co-expression modules and other omics data are identified by feature selection technique, then examined by conducting enrichment analysis and exploiting biological functions, escalated the interpretation of input feature from gene level to co-expression modules level. Our study shows the feasibility of discovering breast cancer related co-expression modules, sketch a blueprint of future endeavors on Deep Learning-based survival analysis. SALMON source code is available at https://github.com/huangzhii/SALMON/.
88 citations
TL;DR: Among adults with pain catastrophizing undergoing knee arthroplasty, cognitive behaviorally based pain coping skills training did not confer pain or functional benefit beyond the large improvements achieved with usual surgical and postoperative care.
Abstract: Background:Pain catastrophizing has been identified as a prognostic indicator of poor outcome following knee arthroplasty. Interventions to address pain catastrophizing, to our knowledge, have not been tested in patients undergoing knee arthroplasty. The purpose of this study was to determine whethe
63 citations
TL;DR: A meta‐analysis of published studies that reported age‐specific incidence rates of dementia and AD was conducted to determine whether dementia andAD incidence rates are changing over time.
Abstract: Background/objectives Population-based incidence estimates of dementia and Alzheimer disease (AD) provide important information for public health policy and resource allocation. We conducted a meta-analysis of published studies that reported age-specific incidence rates of dementia and AD to determine whether dementia and AD incidence rates are changing over time. Design PubMed and MEDLINE were searched for publications through June 30, 2017, using key words "dementia", "Alzheimer", and "incidence." Inclusion criteria for the meta-analysis are: (1) population-based studies using personal interviews and direct examinations of the study subjects, (2) standardized clinical diagnosis criteria, (3) reporting age-specific incidence rates, (4) published in English, and (5) sample size of 500 or greater and length of follow-up of 2 years or greater. Mixed-effects models were used to determine the association between birth year and incidence rates. Measurements Age-specific dementia/AD incidence rates and their standard errors reported in each study. Results Thirty-eight articles with 53 cohorts on dementia incidence and 31 articles with 35 cohorts on AD incidence met the inclusion criteria. There were significant associations between later birth years and decreased dementia incidence rates in all three age groups (65-74, 75-84, and 85 years and older). There were no significant associations between birth year and AD incident rates in any of the three age groups. In particular, AD incidence rates reported from Western countries stayed steady in all age groups, while studies in non-Western countries showed significantly increased AD incidence rates for the 65 to 74 years age group (odds ratio = 2.78; P = .04), but a nonsignificant association for the 75 to 84 or 85 years and older groups. Conclusion Dementia incidence declined over the past four decades, but AD incidence did not decline. Further research, especially from non-Western countries, is needed to elucidate the mechanism underlying the trends in dementia and AD incidence over time.
61 citations
TL;DR: Convergent and construct validity was supported and strong correlations of the composite depression-anxiety measures with one another and moderate correlations with health-related quality of life measures, respectively.
TL;DR: In a cluster randomized trial, an intervention used to target parents of adolescents (11-17 years) eligible for a dose of HPV vaccine, was tested in pediatric clinics part of an urban health system as discussed by the authors.
Abstract: BACKGROUND: Human papillomavirus (HPV) infection can lead to serious health issues and remains the most common sexually transmitted infection. Despite availability of effective vaccines, HPV vaccination rates are suboptimal. METHODS: In a cluster randomized trial, an intervention used to target parents of adolescents (11–17 years) eligible for a dose of HPV vaccine, was tested in pediatric clinics part of an urban health system. Parents watched a digital video outlining the risks and benefits of vaccine using a tablet in the examination room. The primary outcome was change in HPV vaccine status 2 weeks after the clinic visit. An intention-to-treat analysis for the primary outcome used generalized estimating equations to accommodate the potential cluster effect of clinics. RESULTS: A total of 1596 eligible adolescents were observed during the 7-month trial. One-third of adolescents visited an intervention clinic. Adolescents who attended an intervention clinic were more likely to be younger (11–12 years) than those who attended a control clinic (72.4% vs 49.8%; P CONCLUSIONS: Educational interventions delivered within a clinical setting hold promise to improve vaccination behaviors.
TL;DR: It is found that cancer-specific patient-centered technologies seem to be effective, especially when tailored, in improving patient and care-related outcomes.
Abstract: Background: In the United States, more than 16 million new cases of cancer are estimated to be diagnosed each year However, the burden of cancer among the US population is not shared equally, with racial and ethnic minorities and lower-income populations having a higher cancer burden compared with their counterparts For example, African Americans have the highest mortality rates and shortest survival rates for most cancers compared with other racial or ethnic groups in the United States A wide range of technologies (eg, internet-based [electronic health, eHealth] technologies, mobile [mobile health, mHealth] apps, and telemedicine) available to patients are designed to improve their access to care and empower them to participate actively in their care, providing a means to reduce health care disparities; however, little is known of their use among underserved populations Objective: The aim of this study was to systematically review the current evidence on the use of cancer-specific patient-centered technologies among various underserved populations Methods: Computer-based search was conducted in the following academic databases: (1) PubMed (cancer subset), (2) MEDLINE, (3) PsycINFO, and (4) CINAHL We included studies that were peer-reviewed, published in the English language, and conducted in the United States Each study was individually assessed for relevance, with any disagreements being reconciled by consensus We used a 3-step inclusion process in which we examined study titles, abstracts, and full-text papers for assessment of inclusion criteria We systematically extracted information from each paper meeting our inclusion criteria Results: This review includes 71 papers that use patient-centered technologies that primarily targeted African Americans (n=31), rural populations (n=14), and Hispanics (n=12) A majority of studies used eHealth technologies (n=41) finding them to be leading sources of cancer-related health information and significantly improving outcomes such as screening among nonadherent individuals and increasing knowledge about cancer and cancer screening Studies on mHealth found that participants reported overall favorable responses to receiving health information via short message service (SMS) text message; however, challenges were experienced with respect to lack of knowledge of how to text among some participants More complex mobile technologies (eg, a tablet-based risk assessment tool) were also found favorable to use and acceptable among underserved populations; however, they also resulted in more significant barriers, for example, participants expressed concerns regarding security and unfamiliarity with the technology and preferred further instruction and assistance in its use Conclusions: There is a growing body of literature exploring patient-centered technology and its influence on care of underserved populations In this review, we find that these technologies seem to be effective, especially when tailored, in improving patient and care-related outcomes Despite the potential of patient-centered technologies and the receptivity of underserved populations, challenges still exist with respect to their effective use and usability
TL;DR: Six commonly used anxiety scales demonstrate similar responsiveness, and estimated MIDs can be used to gauge anxiety change in clinical research and practice.
Abstract: Background:Anxiety is one of the most prevalent mental disorders and accounts for substantial disability as well as increased health care costs. This study examines the minimally important difference (MID) and responsiveness of 6 commonly used anxiety scales.Methods:The sample comprised 294 patients
05 Jun 2019
TL;DR: In this paper, the authors identify changes in demographic and clinical characteristics and outcomes in patients with newly diagnosed cirrhosis, and support investment in the prevention and treatment of alcoholic liver disease and nonalcoholic steatohepatitis.
Abstract: Importance Changes in the characteristics of patients with cirrhosis are likely to affect future outcomes and are important to understand in planning for the care of this population. Objective To identify changes in demographic and clinical characteristics and outcomes in patients with newly diagnosed cirrhosis. Design, Setting, and Participants A retrospective cohort study of patients with a new diagnosis of cirrhosis was conducted using the Indiana Network for Patient Care, a large statewide regional health information exchange, between 2004 and 2014. Patients with at least 1 year of continuous follow-up before the cirrhosis diagnosis were followed up through August 1, 2015. The analysis was conducted from December 2018 to January 2019. Exposures Age, cause of cirrhosis, and year of diagnosis. Main Outcomes and Measures Overall rates for mortality, liver transplant, hepatocellular carcinoma, and hepatic decompensation (composite of ascites, hepatic encephalopathy, or variceal bleeding). Results A total of 9261 patients with newly diagnosed cirrhosis were identified (mean [SD] age, 57.9 [12.6] years; 5109 [55.2%] male). A 69% increase in new diagnoses occurred over the course of the study period (620 in 2004 vs 1045 in 2014). The proportion of those younger than 40 years increased by 0.20% per year (95% CI, 0.04% to 0.36%;Pfor trend = .02), and the proportion of those aged 65 years and older increased by 0.81% per year (95% CI, 0.51% to 1.11%;Pfor trend Conclusions and Relevance The population of patients with newly diagnosed cirrhosis in Indiana has experienced changes in the age distribution and cause of cirrhosis, with decreasing mortality rates. These findings support investment in the prevention and treatment of alcoholic liver disease and nonalcoholic steatohepatitis, particularly in younger and older patients. Additional study is needed to identify the reasons for decreasing mortality rates.
01 Mar 2019
TL;DR: In this article, the authors report inconsistent performance of FITs for colorectal cancer (CRC) and advanced adenomas, and identify factors affecting these characteristics.
Abstract: Background Studies report inconsistent performance of fecal immunochemical tests (FITs) for colorectal cancer (CRC) and advanced adenomas. Purpose To summarize performance characteristics of FITs for CRC and advanced adenomas in average-risk persons undergoing screening colonoscopy (reference standard) and to identify factors affecting these characteristics. Data sources Ovid MEDLINE, PubMed, Embase, and the Cochrane Library from inception through October 2018; reference lists of studies and reviews. Study selection Two reviewers independently screened records to identify published English-language prospective or retrospective observational studies that evaluated FIT sensitivity and specificity for colonoscopic findings in asymptomatic, average-risk adults. Data extraction Two authors independently extracted data and evaluated study quality. Data synthesis Thirty-one studies (120 255 participants; 18 FITs) were included; all were judged to have low to moderate risk of bias. Performance characteristics depended on the threshold for a positive result. A threshold of 10 µg/g resulted in sensitivity of 0.91 (95% CI, 0.84 to 0.95) and a negative likelihood ratio of 0.10 (CI, 0.06 to 0.19) for CRC, whereas a threshold of greater than 20 µg/g resulted in specificity of 0.95 (CI, 0.94 to 0.96) and a positive likelihood ratio of 15.49 (CI, 9.82 to 22.39). For advanced adenomas, sensitivity was 0.40 (CI, 0.33 to 0.47) and the negative likelihood ratio was 0.67 (CI, 0.57 to 0.78) at 10 µg/g, and specificity was 0.95 (CI, 0.94 to 0.96) and the positive likelihood ratio was 5.86 (CI, 3.77 to 8.97) at greater than 20 µg/g. Studies had low to high heterogeneity, depending on the threshold. Although several FITs had adequate performance, sensitivity and specificity for CRC for 1 qualitative FIT were 0.90 and 0.91, respectively, at its single threshold of 10 µg/g; positive and negative likelihood ratios were 10.13 and 0.11, respectively. Comparison of 3 FITs at 3 thresholds was inconclusive: CIs overlapped, and the comparisons were across rather than within studies. Limitations Only English-language studies were included. Incomplete reporting limited quality assessment of some evidence. Performance characteristics are for 1-time rather than serial testing. Conclusion Single-application FITs have moderate to high sensitivity and specificity for CRC, depending on the positivity threshold. Sensitivity of 1-time testing for advanced adenomas is low, regardless of the threshold. Primary funding source Department of Medicine, Indiana University School of Medicine.
TL;DR: This study conducted a study to test if the frequency of suspected DILI from prescription agents is higher in individuals with chronic liver disease suggestive of NAFLD.
01 Jan 2019
TL;DR: In a cluster randomized trial, an intervention used to target parents of adolescents (11-17 years) eligible for a dose of HPV vaccine, was tested in pediatric clinics part of an urban health system as discussed by the authors.
Abstract: BACKGROUND: Human papillomavirus (HPV) infection can lead to serious health issues and remains the most common sexually transmitted infection. Despite availability of effective vaccines, HPV vaccination rates are suboptimal. METHODS: In a cluster randomized trial, an intervention used to target parents of adolescents (11–17 years) eligible for a dose of HPV vaccine, was tested in pediatric clinics part of an urban health system. Parents watched a digital video outlining the risks and benefits of vaccine using a tablet in the examination room. The primary outcome was change in HPV vaccine status 2 weeks after the clinic visit. An intention-to-treat analysis for the primary outcome used generalized estimating equations to accommodate the potential cluster effect of clinics. RESULTS: A total of 1596 eligible adolescents were observed during the 7-month trial. One-third of adolescents visited an intervention clinic. Adolescents who attended an intervention clinic were more likely to be younger (11–12 years) than those who attended a control clinic (72.4% vs 49.8%; P CONCLUSIONS: Educational interventions delivered within a clinical setting hold promise to improve vaccination behaviors.
TL;DR: In this article, the authors evaluated the responsiveness of the Patient-Reported Outcomes Measurement Information System Pain Interference (PROMIS-PI) scales and compared their responsiveness with legacy pain measures.
TL;DR: Broad information sources, which are reflective of patients' reliance on multiple organizations for care, better support risk prediction modeling in the emergency department.
TL;DR: A pragmatic trial is designed to test the efficacy of a pharmacological management of delirium (PMD) bundle in improvingDelirium/coma‐free days and reducing deliria severity among ICU patients.
Abstract: Background/objective Delirium in the intensive care units (ICUs) is prevalent, with both delirium duration and delirium severity associated with adverse outcomes. We designed a pragmatic trial to test the efficacy of a pharmacological management of delirium (PMD) bundle in improving delirium/coma-free days and reducing delirium severity among ICU patients. Design A randomized pragmatic clinical trial. Setting Medical, surgical, and progressive ICUs of three tertiary care hospitals. Participants A total of 351 critically ill patients. Intervention A multicomponent PMD bundle consisting of reducing the exposure to 20 definite anticholinergic medications and benzodiazepines and prescribing low-dose haloperidol. Measurements The primary outcomes were delirium/coma-free days, measured through the Richmond Agitation-Sedation Scale and the Confusion Assessment Method for the ICU (CAM-ICU), and delirium severity, measured through Delirium Rating Scale-Revised-98 and the CAM-ICU-7. Secondary outcomes were in-hospital and posthospital discharge 30-day mortality, ICU and hospital lengths of stay, and delirium-related hospital complications. Results We randomized 351 critically ill delirious patients (mean age = 59.3 years [SD = 16.9 years]; 52% female, 42% African Americans) to receive the PMD bundle or usual care. There were no significant differences in median delirium/coma-free days at day 8 (PMD vs usual care = 4 [interquartile range {IQR} = 2-7] days vs 5 [IQR = 1-7] days; P = .888) or at day 30 (PMD vs usual care = 26 [IQR 19-29] days vs 26 [IQR, 14-29] days; P = .991). There were no significant differences for decrease in delirium severity at day 8, but at hospital discharge, the intervention group showed a greater reduction in delirium severity (mean decrease in CAM-ICU-7 score for PMD vs usual care = 3.2 [SD = 3.3] vs 2.5 [SD = 3.2]; P = .046). No differences were observed between groups for ICU and hospital lengths of stay, mortality, and delirium-related hospital complications. Similar results were observed when analyses were limited to patients 65 years or older and 75 years or older. Conclusion and relevance Implementing the PMD bundle in the ICU did not reduce delirium duration or severity among critically ill patients. Trial registration clinicaltrials.gov Identifier: NCT00842608. J Am Geriatr Soc 67:1057-1065, 2019.
TL;DR: In this paper, the authors evaluated the minimally important difference (MID) of Patient-Reported Outcomes Measurement Information System (PROMIS) measures and their correspondence with other brief measures to assess SPADE symptoms.
Oregon Health & Science University1, University of Colorado Boulder2, Lawrence Berkeley National Laboratory3, University of North Carolina at Chapel Hill4, Geisinger Health System5, Johns Hopkins University6, Humboldt University of Berlin7, Oregon State University8, National Institutes of Health9, Regenstrief Institute10, Indiana University11, University of Colorado Denver12, University of Connecticut13
TL;DR: This work provides a method for mapping LOINC-encoded laboratory test results transmitted in FHIR standards to Human Phenotype Ontology (HPO) terms and annotated the medical implications of 2923 commonly used laboratory tests with HPO terms.
Abstract: Electronic Health Record (EHR) systems typically define laboratory test results using the Laboratory Observation Identifier Names and Codes (LOINC) and can transmit them using Fast Healthcare Interoperability Resource (FHIR) standards. LOINC has not yet been semantically integrated with computational resources for phenotype analysis. Here, we provide a method for mapping LOINC-encoded laboratory test results transmitted in FHIR standards to Human Phenotype Ontology (HPO) terms. We annotated the medical implications of 2923 commonly used laboratory tests with HPO terms. Using these annotations, our software assesses laboratory test results and converts each result into an HPO term. We validated our approach with EHR data from 15,681 patients with respiratory complaints and identified known biomarkers for asthma. Finally, we provide a freely available SMART on FHIR application that can be used within EHR systems. Our approach allows readily available laboratory tests in EHR to be reused for deep phenotyping and exploits the hierarchical structure of HPO to integrate distinct tests that have comparable medical interpretations for association studies.
TL;DR: Preliminary evidence is provided that risk-stratification interventions to identify patients in need of wraparound services to address social determinants can increase referrals and uptake of services that may address social drivers of disease burden.
TL;DR: A conceptual model of OTC medication purchase and use depicts dual processes for OTC medications decision making – habit‐based and deliberation‐based – as well as the antecedents and consequences of decision making.
Abstract: Background Older adults purchase and use over-the-counter (OTC) medications with potentially significant adverse effects. Some OTC medications, such as those with anticholinergic effects, are relatively contraindicated for use by older adults due to evidence of impaired cognition and other adverse effects. Objective To inform the design of future OTC medication safety interventions for older adults, this study investigated consumers' decision making and behavior related to OTC medication purchasing and use, with a focus on OTC anticholinergic medications. Methods The study had a cross-sectional design with multiple methods. A total of 84 adults participated in qualitative research interviews (n = 24), in-store shopper observations (n = 39), and laboratory-based simulated OTC shopping tasks (n = 21). Simulated shopping participants also rank-ordered eight factors on their importance for OTC decision making. Results Findings revealed that many participants had concerns about medication adverse effects, generally, but were not aware of age-related risk associated with the use of anticholinergic medications. Analyses produced a map of the workflow of OTC-related behavior and decision making as well as related barriers such as difficulty locating medications or comparing them to an alternative. Participants reported effectiveness, adverse effects or health risks, and price as most important to their OTC medication purchase and use decisions. A persona analysis identified two types of consumers: the habit follower, who frequently purchased OTC medications and considered them safe; and the deliberator, who was more likely to weigh their options and consider alternatives to OTC medications. Conclusion A conceptual model of OTC medication purchase and use is presented. Drawing on study findings and behavioral theories, the model depicts dual processes for OTC medication decision making – habit-based and deliberation-based – as well as the antecedents and consequences of decision making. This model suggests several design directions for consumer-oriented interventions to promote OTC medication safety.
TL;DR: A participatory design session was held with seven adult patients with HF and CRT device implants, who were presently undergoing RM, along with two informal caregivers, to design a prototype for a patient-facing dashboard with which they could engage with their device data.
Abstract: Patients with heart failure (HF) are commonly implanted with cardiac resynchronization therapy (CRT) devices as part of their treatment. Presently, they cannot directly access the remote monitoring (RM) data generated from these devices, representing a missed opportunity for increased knowledge and engagement in care. However, electronic health data sharing can create information overload issues for both clinicians and patients, and some older patients may not be comfortable using the technology (i.e., computers and smartphones) necessary to access this data. To mitigate these problems, patients can be directly involved in the creation of data visualization tailored to their preferences and needs, allowing them to successfully interpret and act upon their health data. We held a participatory design (PD) session with seven adult patients with HF and CRT device implants, who were presently undergoing RM, along with two informal caregivers. Working in three teams, participants used drawing supplies and design cards to design a prototype for a patient-facing dashboard with which they could engage with their device data. Information that patients rated as a high priority for the “Main Dashboard” screen included average percent pacing with alerts for abnormal pacing, other device information such as battery life and recorded events, and information about who to contact with for data-related questions. Preferences for inclusion in an “Additional Information” display included a daily pacing chart, health tips, aborted shocks, a symptom list, and a journal. These results informed the creation of an actual dashboard prototype which was later evaluated by both patients and clinicians. Additionally, important insights were gleaned regarding the involvement of older patients in PD for health technology.
05 Jun 2019
TL;DR: The population of patients with newly diagnosed cirrhosis is facing changes in demographic characteristics, clinical features, and outcomes that may affect future care.
Abstract: Importance Changes in the characteristics of patients with cirrhosis are likely to affect future outcomes and are important to understand in planning for the care of this population. Objective To identify changes in demographic and clinical characteristics and outcomes in patients with newly diagnosed cirrhosis. Design, Setting, and Participants A retrospective cohort study of patients with a new diagnosis of cirrhosis was conducted using the Indiana Network for Patient Care, a large statewide regional health information exchange, between 2004 and 2014. Patients with at least 1 year of continuous follow-up before the cirrhosis diagnosis were followed up through August 1, 2015. The analysis was conducted from December 2018 to January 2019. Exposures Age, cause of cirrhosis, and year of diagnosis. Main Outcomes and Measures Overall rates for mortality, liver transplant, hepatocellular carcinoma, and hepatic decompensation (composite of ascites, hepatic encephalopathy, or variceal bleeding). Results A total of 9261 patients with newly diagnosed cirrhosis were identified (mean [SD] age, 57.9 [12.6] years; 5109 [55.2%] male). A 69% increase in new diagnoses occurred over the course of the study period (620 in 2004 vs 1045 in 2014). The proportion of those younger than 40 years increased by 0.20% per year (95% CI, 0.04% to 0.36%;Pfor trend = .02), and the proportion of those aged 65 years and older increased by 0.81% per year (95% CI, 0.51% to 1.11%;Pfor trend Conclusions and Relevance The population of patients with newly diagnosed cirrhosis in Indiana has experienced changes in the age distribution and cause of cirrhosis, with decreasing mortality rates. These findings support investment in the prevention and treatment of alcoholic liver disease and nonalcoholic steatohepatitis, particularly in younger and older patients. Additional study is needed to identify the reasons for decreasing mortality rates.
University of Massachusetts Medical School1, VA Boston Healthcare System2, Brown University3, University of Texas Health Science Center at San Antonio4, University of Michigan5, Roy J. and Lucille A. Carver College of Medicine6, Boston University7, University of Utah8, Regenstrief Institute9, Indiana University – Purdue University Indianapolis10, Veterans Health Administration11, Yale University12
TL;DR: Recommendations are provided about how to evaluate cross-system care coordination between VA and community health systems and the role of multiple individuals coordinating VA and non-VA care, and how these coordinators work together to optimize coordination.
Abstract: In response to widespread concerns regarding Veterans' access to VA care, Congress enacted the Veterans Access, Choice and Accountability Act of 2014, which required VA to establish the Veterans Choice Program (VCP). Since the inception of VCP, more than two million Veterans have received care from community providers, representing approximately 25% of Veterans enrolled in VA care. However, expanded access to non-VA care has created challenges in care coordination between VA and community health systems. In March 2018, the VA Health Services Research & Development Service hosted a VA State of the Art conference (SOTA) focused on care coordination. The SOTA convened VA researchers, program directors, clinicians, and policy makers to identify knowledge gaps regarding care coordination within the VA and between VA and community systems of care. This article provides a summary and synthesis of relevant literature and provides recommendations generated from the SOTA about how to evaluate cross-system care coordination. Care coordination is typically evaluated using health outcomes including hospital readmissions and death; however, in cross-system evaluations of care coordination, measures such as access, cost, Veteran/patient and provider satisfaction (including with cross-system communication), comparable quality metrics, context (urban vs. rural), and patient complexity (medical and mental health conditions) need to be included to fully evaluate care coordination effectiveness. Future research should examine the role of multiple individuals coordinating VA and non-VA care, and how these coordinators work together to optimize coordination.
TL;DR: This work tested the impact of a deprescribing intervention on short‐term delirium outcomes in the intensive care unit (ICU) and found that benzodiazepines and anticholinergics are risk factors for delirity in the ICU.
Abstract: Objective Benzodiazepines and anticholinergics are risk factors for delirium in the intensive care unit (ICU). We tested the impact of a deprescribing intervention on short-term delirium outcomes. Design Multisite randomized clinical trial. Setting ICUs of three large hospitals. Participants Two hundred adults aged 18 years or older and admitted to an ICU with delirium, according to the Richmond Agitation-Sedation Scale and the Confusion Assessment Method for the ICU (CAM-ICU). Participants had a contraindication to haloperidol (seizure disorder or prolonged QT interval) or preference against haloperidol as a treatment for delirium, and were excluded for serious mental illness, stroke, pregnancy, or alcohol withdrawal. Participants were randomized to a deprescribing intervention or usual care. The intervention included electronic alerts combined with pharmacist support to deprescribe anticholinergics and benzodiazepines. Measurements Primary outcomes were delirium duration measured by the CAM-ICU and severity measured by the Delirium Rating Scale Revised-98 (DRS-R-98) and the CAM-ICU-7; secondary outcomes included adverse events and mortality. Results Participants had a mean age of 61.8 (SD = 14.3) years, 59% were female, and 52% were African American, with no significant differences in baseline characteristics between groups. No differences between groups were identified in the number exposed to anticholinergics (P = .219) or benzodiazepines (P = .566), the median total anticholinergic score (P = .282), or the median total benzodiazepine dose in lorazepam equivalents (P = .501). Neither median delirium/coma-free days (P = .361) nor median change in delirium severity scores (P = .582 for DRS-R-98; P = .333 for CAM-ICU-7) were different between groups. No differences in adverse events or mortality were identified. Conclusions When added to state-of-the-art clinical services, this deprescribing intervention had no impact on medication use in ICU participants. Given the age of the population, results of clinical outcomes may not be easily extrapolated to older adults. Nonetheless, improved approaches for deprescribing or preventing anticholinergics and benzodiazepines should be developed to determine the impact on delirium outcomes. J Am Geriatr Soc 67:695-702, 2019.
TL;DR: The majority of patients with X-linked hypophosphatemia develop secondary hyperparathyroidism during treatment with phosphate and active vitamin D and most have recurrence or persistence of hypercalcemia after surgery.