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Modifications to Fried’s frailty phenotype (FFP) are common. We evaluated a self-reported modified frailty phenotype (Mod-FP) used among people with HIV (PWH). Among 522 PWH engaged in two longitudinal studies, we assessed validity of the four-item Mod-FP compared with the five-item FFP. We compared the phenotypes via receiver operator characteristic curves, agreement in classifying frailty, and criterion validity via association with having experienced falls. Mod-FP classified 8% of PWH as frail, whereas FFP classified 9%. The area under the receiver operator characteristic curve for Mod-FP classifying frailty was 0.93 (95% CI = 0.91–0.96). We observed kappa ranging from 0.64 (unweighted) to 0.75 (weighted) for categorizing frailty status. Both definitions found frailty associated with a greater odds of experiencing a fall; FFP estimated a slightly greater magnitude (i.e., OR) for the association than Mod-FP. The Mod-FP has good performance in measuring frailty among PWH and is reasonable to use when the gold standards of observed assessments (i.e., weakness and slowness) are not feasible.

ObjectiveDigital exposure notifications (DEN) systems were an emergency response to the coronavirus disease 2019 (COVID-19) pandemic, harnessing smartphone-based technology to enhance conventional pandemic response strategies such as contact tracing. We identify and describe performance measurement constructs relevant to the implementation of DEN tools: (1) reach (number of users enrolled in the intervention); (2) engagement (utilization of the intervention); and (3) effectiveness in preventing transmissions of COVID-19 (impact of the intervention). We also describe WA State’s experience utilizing these constructs to design data-driven evaluation approaches.MethodsWe conducted an environmental scan of DEN documentation and relevant publications. Participation in multidisciplinary collaborative environments facilitated shared learning. Compilation of available data sources and their relevance to implementation and operation workflows were synthesized to develop implementation evaluation constructs.ResultsWe identified 8 useful performance indicators within reach, engagement, and effectiveness constructs.DiscussionWe use implementation science to frame the evaluation of DEN tools by linking the theoretical constructs with the metrics available in the underlying disparate, deidentified, and aggregate data infrastructure. Our challenges in developing meaningful metrics include limited data science competencies in public health, validation of analytic methodologies in the complex and evolving pandemic environment, and the lack of integration with the public health infrastructure.ConclusionContinued collaboration and multidisciplinary consensus activities can improve the utility of DEN tools for future public health emergencies.

CONTEXT: Documented goals-of-care discussions are an important quality metric for patients with serious illness. Natural language processing (NLP) is a promising approach for identifying goals-of-care discussions in the electronic health record (EHR). OBJECTIVES: To compare three NLP modeling approaches for identifying EHR documentation of goals-of-care discussions and generate hypotheses about differences in performance. METHODS: We conducted a mixed-methods study to evaluate performance and misclassification for three NLP featurization approaches modeled with regularized logistic regression: bag-of-words (BOW), rule-based, and a hybrid approach. From a prospective cohort of 150 patients hospitalized with serious illness over 2018–2020, we collected 4,391 inpatient EHR notes; 99 (2.3%) contained documented goals-of-care discussions. We used leave-one-out cross-validation to estimate performance by comparing pooled NLP predictions to human abstractors with receiver-operating-characteristic (ROC) and precision-recall (PR) analyses. We qualitatively examined a purposive sample of 70 NLP-misclassified notes using content analysis to identify linguistic features that allowed us to generate hypotheses underpinning misclassification. RESULTS: All three modeling approaches discriminated between notes with and without goals-of-care discussions (AUC(ROC): BOW, 0.907; rule-based, 0.948; hybrid, 0.965). Precision and recall were only moderate (precision at 70% recall: BOW, 16.2%; rule-based, 50.4%; hybrid, 49.3%; AUC(PR): BOW, 0.505; rule-based, 0.579; hybrid, 0.599). Qualitative analysis revealed patterns underlying performance differences between BOW and rule-based approaches. CONCLUSION: NLP holds promise for identifying EHR-documented goals-of-care discussions. However, the rarity of goals-of-care content in EHR data limits performance. Our findings highlight opportunities to optimize NLP modeling approaches, and support further exploration of different NLP approaches to identify goals-of-care discussions.

Background and Objective Care partners of people living with dementia require support to knowledgeably navigate decision making about how and when to use monitoring technologies for care purposes. We conducted a pilot study of a novel self-administered intervention, “Let’s Talk Tech,” for people living with mild dementia and their care partners. This paper presents preliminary efficacy findings of this intervention designed to educate and facilitate dyadic communication about a range of technologies used in dementia care and to document the preferences of the person living with dementia. It is the first-of-its-kind decision-making and planning tool with a specific focus on technology use. Research Design and Methods We used a 1-group pretest–post-test design and paired t tests to assess change over 2 time periods in measures of technology comprehension, care partner knowledge of the participant living with mild Alzheimer’s disease’s (AD) preferences, care partner preparedness to make decisions about technology use, and mutual understanding. Thematic analysis was conducted on postintervention interview transcripts to elucidate mechanisms and experiences with Let’s Talk Tech. Results Twenty-nine mild AD dementia care dyads who live together completed the study. There was statistically significant improvement with medium and large effect sizes on outcome measures of care partners’ understanding of each technology, care partners’ perceptions of the person living with dementia’s understanding of each technology, knowledge of the person living with dementia’s preferences, decision-making preparedness, and care partners’ feelings of mutual understanding. Participants reported that it helped them have important and meaningful conversations about using technology. Discussion and Implications Let’s Talk Tech demonstrated promising preliminary efficacy on targeted measures that can lead to informed, shared decision making about technologies used in dementia care. Future studies should assess efficacy with larger samples and more diverse sample populations in terms of race, ethnicity, and dementia type.

Making EHR Data More Available for Research and Public Health (MedMorph) is a Centers for Disease Control and Prevention-led initiative developing and demonstrating a reference architecture (RA) and implementation, including Health Level Seven International Fast Healthcare Interoperability Resources (HL7 FHIR) implementation guides (IGs), describing how to leverage FHIR for aligned research and public health access to clinical data for automated data exchange. MedMorph engaged a technical expert panel of more than 100 members to model representative use cases, develop IGs (architectural and content), align with existing efforts in the FHIR community, and demonstrate the RA in research and public health uses. The RA IG documents common workflows needed to automatically send research data to Research Patient Data Repositories for multiple use cases. Sharing a common RA and canonical data model will improve data sharing for research and public health needs and generate evidence. MedMorph delivers a robust, reusable method to utilize data from electronic health records addressing multiple research and public health needs.

Duncan Short,1 Xueqi Wang,2 Shivali Suri,3 Thomas K Hsu,2 Bryn Jones,1 Rob J Fredericksen,4 Heidi M Crane,4 Alexandra Musten,5 Jean Bacon,5 Yongwei Wang,2 Kevin A Gough,3 Moti Ramgopal,6 Jeff Berry,7 William B Lober4 1ViiV Healthcare, Brentford, UK; 2ViiV Healthcare, Durham, NC, USA; 3St Michael’s Hospital, Toronto, ON, Canada; 4Center for AIDS Research, University of Washington, Seattle, WA, USA; 5Ontario HIV Treatment Network, Toronto, ON, Canada; 6Midway Specialty Care Center, Fort Pierce, FL, USA; 7TPAN, Chicago, IL, USACorrespondence: Duncan Short, ViiV Healthcare, 980 Great West Road, Brentford, Middlesex, TW8 9GS, UK, Tel +44 7827 282971, Email duncan.x.short@viivhealthcare.comPurpose: Use of patient-reported outcomes assessments (PROs) can improve patient–provider communication and focus provider attention on current health issues. This analysis examines the association between suboptimal antiretroviral therapy (ART) adherence and factors obtained through PROs among people with HIV (PWH) at 2 North American outpatient clinics.Patients and Methods: Immediately before a clinic visit, PWH completed self-administered PROs. Unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated from logistic regression models to identify sociodemographic and health-related factors (satisfaction with ART, difficulty meeting housing costs, depression, intimate partner violence, risk of malnutrition, smoking status, alcohol use, and substance use) associated with suboptimal adherence (defined as self-reporting < 95% or < 80% adherence). Multiple imputation was performed to account for missing data in the multivariate analyses.Results: Of 1632 PWH, 1239 (76%) responded to the adherence assessment; of these, 268 (22%) and 106 (9%) reported < 95% and < 80% adherence, respectively. Of 1580 PWH who responded, 354 (22%) were dissatisfied with their HIV medication. Of responding PWH, 19% reported moderate-to-severe depression, 23% indicated they were at risk of malnutrition, 34% were current smokers, and 62% reported substance use in the past 3 months. Dissatisfaction with ART was significantly associated with < 95% and < 80% adherence in the unadjusted analysis (unadjusted OR [95% CI], 3.38 [2.51– 4.56] and 4.26 [2.82– 6.42], respectively) and adjusted analysis (adjusted OR [95% CI], 2.76 [1.91– 4.00] and 3.28 [1.95– 5.52], respectively); significance remained after multiple imputation. In adjusted analyses, no risk of malnutrition was significantly associated with reduced odds of < 95% adherence after multiple imputation (adjusted OR [95% CI], 0.714 [0.511– 0.997]); no other factors were associated with < 95% or < 80% adherence.Conclusion: These results suggest that implementation of PROs evaluating treatment satisfaction may provide value to adherence management in routine HIV care.Keywords: patient satisfaction, antiretroviral therapy, highly active, treatment adherence, implementation science, quality of life

Substance use in the U.S. varies by geographic region. Opioid prescribing practices and marijuana, heroin, and methamphetamine availability are evolving differently across regions. We examined self-reported substance use among people living with HIV (PLWH) in care at seven sites from 2017-2019 to understand current regional substance use patterns. We calculated the percentage and standardized percentage of PLWH reporting current drug use and at-risk and binge alcohol use by U.S. Census Bureau geographic region and examined associations in adjusted logistic regression analyses. Among 7,686 PLWH, marijuana use was the most prevalent drug (30%), followed by methamphetamine/crystal (8%), cocaine/crack (7%), and illicit opioids (3%). One-third reported binge alcohol use (32%). Differences in percent of current use by region were seen for marijuana (24-41%) and methamphetamine/crystal (2-15%), with more use in the West and Northeast, and binge alcohol use (26-40%). In adjusted analyses, PLWH in the Midwest were significantly less likely to use methamphetamine/crystal (aOR: 0.13;0.06-0.25) or illicit opioids (aOR:0.16;0.05-0.53), and PLWH in the Northeast were more likely to use cocaine/crack (aOR:1.59;1.16-2.17), compared to PLWH in the West. Understanding differences in substance use patterns in the current era, as policies continue to evolve, will enable more targeted interventions in clinical settings among PLWH.

Objective Lung transplant (LTx) saves lives in cystic fibrosis (CF). However, many potential candidates express uncertainty about LTx and die before receiving this treatment. CF guidelines recommend LTx education and clinical discussions well before the need for LTx arises, but limited patient resources exist. Materials and Methods We engaged people with CF and CF physicians in human-centered design of “Take On Transplant” (TOT), a web-based education tool to prepare patients for LTx discussions. Across 3 phases, needs assessment, design groups, and iterative user testing of TOT, we refined TOT from wireframe prototypes, to an interactive website, to a fully functional intervention ready for clinical trials. Results Fifty-five people with CF and 105 physicians identified information needs to prepare for LTx discussions. Design groups (n = 14 participants) then established core requirements: didactic education (“Resource Library”), patient narratives (“CF Stories”), frequently asked questions (“FAQ”), and self-assessment to tailor content (“My CF Stage”). Iterative usability testing (n = 39) optimized the design of CF Stories and prototype layout. We then developed the TOT website and demonstrated feasibility and preliminary efficacy of use through 2-week field testing (n = 9). Discussion Our human-centered design process provided guidance for educational tools to serve the evolving needs of potential LTx candidates. Our findings support the process of patient deliberation as a foundation for shared decision-making in CF, and inform educational tools that could potentially translate beyond LTx. Conclusion TOT fills a critical gap in preparing people with CF for shared decision-making about LTx and may serve as a model for educational tools for other preference-sensitive decisions.

We assessed acceptability/usability of tablet-based patient-reported outcome (PRO) assessments among patients in HIV care, and relationships with health outcomes using a modified version of the 6-item Acceptability E-Scale (AES) within a self-administered PRO assessment. Using multivariable linear regression, we measured associations between patient characteristics and continuous combined AES score. Among 786 patients (median age=48; 91% male; 49% white; 17% Spanish-speaking) overall mean score was 26/30 points (SD: 4.4). Mean scores per dimension (max 5, 1=lowest acceptability, 5=highest): ease of use 4.7, understandability 4.7, time burden 4.3, overall satisfaction 4.3, helpfulness describing symptoms/behaviors 4.2, and enjoyability 3.8. Higher overall score was associated with race/ethnicity (+1.3 points/African-American patients (95%CI:0.3-2.3); +1.6 points/Latino patients (95%CI:0.9-2.3) compared to white patients). Patients completing PROs in Spanish scored +2.4 points on average (95%CI:1.6-3.3). Higher acceptability was associated with better quality of life (0.3 points (95%CI:0.2-0.5)) and adherence (0.4 points (95%CI:0.2-0.6)). Lower acceptability was associated with: higher depression symptoms (−0.9 points (95%CI:-1.4 to −0.4)); recent illicit opioid use (−2.0 points (95%CI:-3.9 to −0.2)); multiple recent sex partners (−0.8 points (95%CI:−1.5 to −0.1)). While patients endorsing depression symptoms, recent opioid use, condomless sex, or multiple sex partners found PROs to be less acceptable, overall, patients found self-administered, tablet-based PRO assessments to be highly acceptable and easy to use.

Introduction: Many patients use mobile devices to track health conditions by recording patient-generated health data. However, patients and clinicians may disagree how to use these data. Objective: To systematically review the literature to identify how patient-generated health data and patient-reported outcomes collected outside of clinical settings can affect patient–clinician relationships within surgery and primary care. Methods: Six research databases were queried for publications documenting the effect of patient-generated health data or patient-reported outcomes on patient–clinician relationships. We conducted thematic synthesis of the results of the included publications. Results: Thirteen of the 3204 identified publications were included for synthesis. Three main themes were identified: patient-generated health data supported patient–clinician communication and health awareness, patients desired for their clinicians to be involved with their patient-generated health data, which clinicians had difficulty accommodating, and patient-generated health data platform features may support or hinder patient–clinician collaboration. Conclusion: Patient-generated health data and patient-reported outcomes may improve patient health awareness and communication with clinicians but may negatively affect patient–clinician relationships.

BackgroundPeople with HIV (PWH) are at increased risk of cardiovascular comorbidities and substance use is a potential predisposing factor. We evaluated associations of tobacco smoking and alcohol use with venous thromboembolism (VTE) in PWH.MethodsWe assessed incident, centrally adjudicated VTE among 12957 PWH within the Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) cohort between January 2009 and December 2018. Using separate Cox proportional hazards models, we evaluated associations of time-updated alcohol and cigarette use with VTE, adjusting for demographic and clinical characteristics. Smoking was evaluated as pack-years and never, former, or current use with current cigarettes per day. Alcohol use was parameterized using categorical and continuous alcohol use score, frequency of use, and binge frequency.ResultsDuring a median of 3.6years of follow-up, 213 PWH developed a VTE. One-third of PWH reported binge drinking and 40% reported currently smoking. In adjusted analyses, risk of VTE was increased among both current (HR: 1.44, 95% CI: 1.02-2.03) and former (HR: 1.44, 95% CI: 0.99-2.07) smokers compared to PWH who never smoked. Additionally, total pack-years among ever-smokers (HR: 1.10 per 5 pack-years; 95% CI: 1.03-1.18) was associated with incident VTE in a dose-dependent manner. Frequency of binge drinking was associated with incident VTE (HR: 1.30 per 7days/month, 95% CI: 1.11-1.52); however, alcohol use frequency was not. Severity of alcohol use was not significantly associated with VTE.ConclusionsCurrent smoking and pack-year smoking history were dose-dependently associated with incident VTE among PWH in CNICS. Binge drinking was also associated with VTE. Interventions for smoking and binge drinking may decrease VTE risk among PWH.

ImportanceMany clinical trial outcomes are documented in free-text electronic health records (EHRs), making manual data collection costly and infeasible at scale. Natural language processing (NLP) is a promising approach for measuring such outcomes efficiently, but ignoring NLP-related misclassification may lead to underpowered studies.ObjectiveTo evaluate the performance, feasibility, and power implications of using NLP to measure the primary outcome of EHR-documented goals-of-care discussions in a pragmatic randomized clinical trial of a communication intervention.Design, Setting, and ParticipantsThis diagnostic study compared the performance, feasibility, and power implications of measuring EHR-documented goals-of-care discussions using 3 approaches: (1) deep-learning NLP, (2) NLP-screened human abstraction (manual verification of NLP-positive records), and (3) conventional manual abstraction. The study included hospitalized patients aged 55 years or older with serious illness enrolled between April 23, 2020, and March 26, 2021, in a pragmatic randomized clinical trial of a communication intervention in a multihospital US academic health system.Main Outcomes and MeasuresMain outcomes were natural language processing performance characteristics, human abstractor-hours, and misclassification-adjusted statistical power of methods of measuring clinician-documented goals-of-care discussions. Performance of NLP was evaluated with receiver operating characteristic (ROC) curves and precision-recall (PR) analyses and examined the effects of misclassification on power using mathematical substitution and Monte Carlo simulation.ResultsA total of 2512 trial participants (mean [SD] age, 71.7 [10.8] years; 1456 [58%] female) amassed 44 324 clinical notes during 30-day follow-up. In a validation sample of 159 participants, deep-learning NLP trained on a separate training data set identified patients with documented goals-of-care discussions with moderate accuracy (maximal F1 score, 0.82; area under the ROC curve, 0.924; area under the PR curve, 0.879). Manual abstraction of the outcome from the trial data set would require an estimated 2000 abstractor-hours and would power the trial to detect a risk difference of 5.4% (assuming 33.5% control-arm prevalence, 80% power, and 2-sided α = .05). Measuring the outcome by NLP alone would power the trial to detect a risk difference of 7.6%. Measuring the outcome by NLP-screened human abstraction would require 34.3 abstractor-hours to achieve estimated sensitivity of 92.6% and would power the trial to detect a risk difference of 5.7%. Monte Carlo simulations corroborated misclassification-adjusted power calculations.Conclusions and RelevanceIn this diagnostic study, deep-learning NLP and NLP-screened human abstraction had favorable characteristics for measuring an EHR outcome at scale. Adjusted power calculations accurately quantified power loss from NLP-related misclassification, suggesting that incorporation of this approach into the design of studies using NLP would be beneficial.

Background Digital health interventions (DHI) have the potential to improve the management and utilization of health information to optimize health care worker performance and provision of care. Despite the proliferation of DHI projects in low-and middle-income countries, few have been evaluated in an effort to understand their impact on health systems and health-related outcomes. Although more evidence is needed on their impact and effectiveness, the use of DHIs among immunization programs has become more widespread and shows promise for improving vaccination uptake and adherence to immunization schedules. Methods Our aim was to assess the impact of an electronic immunization registry (EIR) using an interrupted time-series analysis to analyze the effect on proportion of on-time vaccinations following introduction of an EIR in Tanzania. We hypothesized that the introduction of the EIR would lead to statistically significant changes in vaccination timeliness at 3, 6, and > 6 months post-introduction. Results For our primary analysis, we observed a decrease in the proportion of on-time vaccinations following EIR introduction. In contrast, our sensitivity analysis estimated improvements in timeliness among those children with complete vaccination records. However, we must emphasize caution interpreting these findings as they are likely affected by implementation challenges. Conclusions This study highlights the complexities of using digitized individual-level routine health information system data for evaluation and research purposes. EIRs have the potential to improve vaccination timeliness, but analyses using EIR data can be complicated by data quality issues and inconsistent data entry leading to difficulties interpreting findings.

Background: An optimal adherence to antiretroviral therapy (ART) is fundamental for suppression of HIV viral load and favourable treatment outcomes. Patient-reported outcomes (PROs) are effective tools for improving patient–provider communication and focusing providers’ awareness on current health problems. The objectives of this analysis were (1) to determine the feasibility of implementing an electronic screening tool to measure PROs in a Canadian HIV clinic to obtain information on ART adherence and related factors and (2) to determine the factors related to sub-optimal adherence. Methods: This implementation research with a convenience sample of 600 people living with HIV (PLWH) was conducted in a busy, academic, urban HIV clinic in Toronto, Canada. PLWH were approached to participate in PRO assessments just prior to their in-clinic appointments, including health-related domains such as mental health, housing, nutrition, financial stress and medication adherence, and responses were summarized on a single sheet available for providers to review. Feasibility of implementing PROs was assessed by quantifying response rate, completion rate, time taken and participation rate. Medication adherence was elicited by self-report of the percentage of prescribed HIV medications taken in the last month. Unadjusted and adjusted odds ratios were estimated from logistic regression models to identify factors associated with adherence of

Background: Emerging technologies such as smartphones and wearable sensors have enabled the paradigm shift to new patient-centered healthcare, together with recent mobile health (mHealth) app development. One such promising healthcare app is incision monitoring based on patient-taken incision images. In this review, challenges and potential solution strategies are investigated for surgical site infection (SSI) detection and evaluation using surgical site images taken at home. Methods: Potential image quality issues, feature extraction, and surgical site image analysis challenges are discussed. Recent image analysis and machine learning solutions are reviewed to extract meaningful representations as image markers for incision monitoring. Discussions on opportunities and challenges of applying these methods to derive accurate SSI prediction are provided. Conclusions: Interactive image acquisition as well as customized image analysis and machine learning methods for SSI monitoring will play critical roles in developing sustainable mHealth apps to achieve the expected outcomes of patient-taken incision images for effective out-of-clinic patient-centered healthcare with substantially reduced cost.

Background: As the use of patient-owned devices, including smartphones and tablets, to manage day-to-day activities grows, so does healthcare industry's interest to better leverage technology to engage patients. For surgical care, a unique opportunity exists to capture patient-generated health data (PGHD) including photographs. As part of a broader initiative to evaluate PGHD for surgical site infection (SSI) surveillance, we sought evidence regarding patient involvement and experience with PGHD for SSI monitoring and surveillance. Methods: Through a scoping review of the literature and semi-structured stakeholder interviews we gathered evidence on what is currently known about patient perspectives of and experiences with mobile health (mHealth) interventions for post-operative recovery. We presented findings to and discussed with the ASSIST PGHD Stakeholder Advisory Group (PSAG) to generate priorities for further examination. Results: Our scoping review yielded 34 studies that addressed post-discharge use of PGHD for monitoring and surveillance of SSI. Of these, 16 studies addressed at least one outcome regarding patient experience; the most commonly measured outcome was patient satisfaction. Only three studies reported on patient involvement in the development of PGHD tools and interventions. We conducted interviews (n = 24) representing a range of stakeholder perspectives. Interviewees stressed the importance of patient involvement in tool and program design, noting patient involvement ensures the “work” that patients do in their daily lives to manage their health and healthcare is recognized. Discussion of evidence with the ASSIST PSAG resulted in formal recommendations for direct involvement of patients and caregivers for future work. Conclusions: While mHealth initiatives to advance post-operative management offer the ability to improve patient engagement, work is needed to ensure the patient voice is reflected. Active engagement with patients and caregivers in the development of new technology, the design of new workflows, and the conduct of research and evaluation ensures that the patient experiences and values are incorporated.

Background The updated Veterans Aging Cohort Study (VACS) Index 2.0 combines general and human immunodeficiency virus (HIV)–specific biomarkers to generate a continuous score that accurately discriminates risk of mortality in diverse cohorts of persons with HIV (PWH), but a score alone is difficult to interpret. Using data from the North American AIDS Cohort Collaboration (NA-ACCORD), we translate VACS Index 2.0 scores into validated probability estimates of mortality. Methods Because complete mortality ascertainment is essential for accurate calibration, we restricted analyses to cohorts with mortality from the National Death Index or equivalent sources. VACS Index 2.0 components were ascertained from October 1999 to April 2018. Mortality was observed up to March 2019. Calibration curves compared predicted (estimated by fitting a gamma model to the score) to observed mortality overall and within subgroups: cohort (VACS/NA-ACCORD subset), sex, age 500 copies/mL, CD4 count Results Among 37230 PWH in VACS and 8061 PWH in the NA-ACCORD subset, median age was 53 and 44 years; 3% and 19% were women; and 48% and 39% were black. Discrimination in NA-ACCORD (C-statistic = 0.842 [95% confidence interval {CI}, .830–.854]) was better than in VACS (C-statistic = 0.813 [95% CI, .809–.817]). Predicted and observed mortality largely overlapped in VACS and the NA-ACCORD subset, overall and within subgroups. Conclusions Based on this validation, VACS Index 2.0 can reliably estimate probability of all-cause mortality, at various follow-up times, among PWH in North America.

As the COVID-19 pandemic continues to unfold and states experience the impacts of reopened economies, it is critical to efficiently manage new outbreaks through widespread testing and monitoring of both new and possible cases. Existing labor-intensive public health workflows may benefit from information collection directly from individuals through patient-reported outcomes (PROs) systems. Our objective was to develop a reusable, mobile-friendly application for collecting PROs and experiences to support COVID-19 symptom self-monitoring and data sharing with appropriate public health agencies, using Fast Healthcare Interoperability Resources (FHIR) for interoperability. We conducted a needs assessment and designed and developed StayHome, a mobile PRO administration tool. FHIR serves as the primary data model and driver of business logic. Keycloak, AWS, Docker, and other technologies were used for deployment. Several FHIR modules were used to create a novel “FHIR-native” application design. By leveraging FHIR to shape not only the interface strategy but also the information architecture of the application, StayHome enables the consistent standards-based representation of data and reduces the barrier to integration with public health information systems. FHIR supported rapid application development by providing a domain-appropriate data model and tooling. FHIR modules and implementation guides were referenced in design and implementation. However, there are gaps in the FHIR specification which must be recognized and addressed appropriately. StayHome is live and accessible to the public at https://stayhome.app. The code and resources required to build and deploy the application are available from https://github.com/uwcirg/stayhome-project.

Introduction Foundational to a learning health system (LHS) is the presence of a data infrastructure that can support continuous learning and improve patient outcomes. To advance their capacity to drive patient‐centered care, health systems are increasingly looking to expand the electronic capture of patient data, such as electronic patient‐reported outcome (ePRO) measures. Yet ePROs bring unique considerations around workflow, measurement, and technology that health systems may not be poised to navigate. We report on our effort to develop generalizable learnings that can support the integration of ePROs into clinical practice within an LHS framework. Methods Guided by action research methodology, we engaged in iterative cycles of planning, acting, observing, and reflecting around ePRO use with two primary goals: (1) mobilize an ePRO community of practice to facilitate knowledge sharing, and (2) establish guidelines for ePRO use in the context of LHS practice. Multiple, emergent data collection activities generated generalizable guidelines that document the tangible best practices for ePRO use in clinical care. We organized guidelines around thematic areas that reflect LHS structures and stakeholders. Results Three core thematic areas (and 24 guidelines) emerged. The theme of governance reflects the importance of leadership, knowledge management, and facilitating organizational learning around best practice models for ePRO use. The theme of integration considers the intersection of workflow, technology, and human factors for ePROs across areas of care delivery. Lastly, the theme of reporting reflects critical considerations for curating data and information, designing system functions and interactions, and presentation of ePRO data to support the translation of knowledge to action. Conclusions The guidelines produced from this work highlight the complex, multidisciplinary nature of implementing change within LHS contexts, and the value of action research approaches to enable rapid, iterative learning that leverages the knowledge and experience of communities of practice.

Background Most studies of stroke in people living with HIV (PLWH) do not use verified stroke diagnoses, are small, and/or do not differentiate stroke types and subtypes. Setting CNICS, a U.S. multisite clinical cohort of PLWH in care. Methods We implemented a centralized adjudication stroke protocol to identify stroke type, subtype, and precipitating conditions identified as direct causes including infection and illicit drug use in a large diverse HIV cohort. Results Among 26,514 PLWH, there were 401 strokes, 75% of which were ischemic. Precipitating factors such as sepsis or same-day cocaine use were identified in 40% of ischemic strokes. Those with precipitating factors were younger, had more severe HIV disease, and fewer traditional stroke risk factors such as diabetes and hypertension. Ischemic stroke subtypes included cardioembolic (20%), large vessel atherosclerosis (13%), and small vessel (24%) ischemic strokes. Individuals with small vessel strokes were older, were more likely to have a higher current CD4 cell count than those with cardioembolic strokes and had the highest mean blood pressure of the ischemic stroke subtypes. Conclusion Ischemic stroke, particularly small vessel and cardioembolic subtypes, were the most common strokes among PLWH. Traditional and HIV-related risk factors differed by stroke type/subtype. Precipitating factors including infections and drug use were common. These results suggest that there may be different biological phenomena occurring among PLWH and that understanding HIV-related and traditional risk factors and in particular precipitating factors for each type/subtype may be key to understanding, and therefore preventing, strokes among PLWH.

Background Electronic patient-reported outcome (ePRO) systems can improve health outcomes by detecting health issues or risk behaviors that may be missed when relying on provider elicitation. Objective This study aimed to implement an ePRO system that administers key health questionnaires in an urban community health center in Boston, Massachusetts. Methods An ePRO system that administers key health questionnaires was implemented in an urban community health center in Boston, Massachusetts. The system was integrated with the electronic health record so that medical providers could review and adjudicate patient responses in real-time during the course of the patient visit. This implementation project was accomplished through careful examination of clinical workflows and a graduated rollout process that was mindful of patient and clinical staff time and burden. Patients responded to questionnaires using a tablet at the beginning of their visit. Results Our program demonstrates that implementation of an ePRO system in a primary care setting is feasible, allowing for facilitation of patient-provider communication and care. Other community health centers can learn from our model in terms of applying technological innovation to streamline clinical processes and improve patient care. Conclusions Our program demonstrates that implementation of an ePRO system in a primary care setting is feasible, allowing for facilitation of patient-provider communication and care. Other community health centers can learn from our model for application of technological innovation to streamline clinical processes and improve patient care.

Context Goals-of-care discussions are an important quality metric in palliative care. However, goals-of-care discussions are often documented as free text in diverse locations. It is difficult to identify these discussions in the electronic health record (EHR) efficiently. Objectives To develop, train, and test an automated approach to identifying goals-of-care discussions in the EHR, using natural language processing (NLP) and machine learning (ML). Methods From the electronic health records of an academic health system, we collected a purposive sample of 3183 EHR notes (1435 inpatient notes and 1748 outpatient notes) from 1426 patients with serious illness over 2008–2016, and manually reviewed each note for documentation of goals-of-care discussions. Separately, we developed a program to identify notes containing documentation of goals-of-care discussions using NLP and supervised ML. We estimated the performance characteristics of the NLP/ML program across 100 pairs of randomly partitioned training and test sets. We repeated these methods for inpatient-only and outpatient-only subsets. Results Of 3183 notes, 689 contained documentation of goals-of-care discussions. The mean sensitivity of the NLP/ML program was 82.3% (SD 3.2%), and the mean specificity was 97.4% (SD 0.7%). NLP/ML results had a median positive likelihood ratio of 32.2 (IQR 27.5–39.2) and a median negative likelihood ratio of 0.18 (IQR 0.16–0.20). Performance was better in inpatient-only samples than outpatient-only samples. Conclusion Using NLP and ML techniques, we developed a novel approach to identifying goals-of-care discussions in the EHR. NLP and ML represent a potential approach toward measuring goals-of-care discussions as a research outcome and quality metric.

Background People living with human immunodeficiency virus (HIV; PLWH) have a markedly elevated anal cancer risk, largely due to loss of immunoregulatory control of oncogenic human papillomavirus infection. To better understand anal cancer development and prevention, we determined whether recent, past, cumulative, or nadir/peak CD4+ T-cell count (CD4) and/or HIV-1 RNA level (HIV RNA) best predict anal cancer risk. Methods We studied 102 777 PLWH during 1996–2014 from 21 cohorts participating in the North American AIDS Cohort Collaboration on Research and Design. Using demographics-adjusted, cohort-stratified Cox models, we assessed associations between anal cancer risk and various time-updated CD4 and HIV RNA measures, including cumulative and nadir/peak measures during prespecified moving time windows. We compared models using the Akaike information criterion. Results Cumulative and nadir/peak CD4 or HIV RNA measures from approximately 8.5 to 4.5 years in the past were generally better predictors for anal cancer risk than their corresponding more recent measures. However, the best model included CD4 nadir (ie, the lowest CD4) from approximately 8.5 years to 6 months in the past (hazard ratio [HR] for Conclusions Our results are consistent with anal cancer promotion by severe, prolonged HIV-induced immunosuppression. Nadir and cumulative CD4 may represent useful markers for identifying PLWH at higher anal cancer risk.

Context Recent analyses of Medicare data show decreases over time in intensity of end-of-life care. Few studies exist regarding trends in intensity of end-of-life care for those under 65 years of age. Objectives To examine recent temporal trends in place of death, and both hospital and intensive care unit (ICU) utilization, for age-stratified decedents with chronic, life-limiting diagnoses ( Methods Retrospective cohort using death certificates and electronic health records for 22,068 patients with chronic illnesses who died between 2010 and 2015. We examined utilization overall and stratified by age using multiple regression. Results The proportion of deaths at home did not change, but hospital admissions in the last 30 days of life decreased significantly from 2010 to 2015 (hospital b = −0.026; CI = −0.041, −0.012). ICU admissions in the last 30 days also declined over time for the full sample and for patients aged 65 years or older (overall b = −0.023; CI = −0.039, −0.007), but was not significant for younger decedents. Length of stay (LOS) did not decrease for those using the hospital or ICU. Conclusion From 2010 to 2015, we observed a decrease in hospital admissions for all age groups and in ICU admissions for those over 65 years. As there were no changes in the proportion of patients with chronic illness who died at home nor in hospital or ICU LOS in the last 30 days, hospital and ICU admissions in the last 30 days may be a more responsive quality metric than site of death or LOS for palliative care interventions.

Background Persons with human immunodeficiency virus (HIV) have higher risks for myocardial infarction (MI) than the general population. This is driven in part by higher type 2 MI (T2MI, due to coronary supply-demand mismatch) rates among persons with HIV (PWH). In the general population, T2MI has higher mortality than type 1 MI (T1MI, spontaneous and generally due to plaque rupture and thrombosis). PWH have a greater burden of comorbidities and may therefore have an even greater excess risk for complication and death in the setting of T2MI. However, mortality patterns after T1MI and T2MI in HIV are unknown. Methods We analyzed mortality after MI among PWH enrolled in the multicenter, US-based Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) cohort (N = 28,186). Incident MIs occurring between January 1, 1996, and December 31, 2014, were centrally adjudicated and classified as T1MI or T2MI. We first compared mortality following T1MI vs. T2MI among PWH. Cox survival analyses and Bayesian model averaging were then used to evaluate pre-MI covariates associated with mortality following T1MI and T2MI. Results Among the 596 out of 28,186 PWH who experienced MI (2.1%; 293 T1MI and 303 T2MI), mortality rates were significantly greater after T2MI (22.2/100 person-years; 1-, 3-, and 5-year mortality 39%, 52%, and 62%) than T1MI (8.2/100 person-years; 1-, 3-, and 5-year mortality 15%, 22%, and 30%). Significant mortality predictors after T1MI were higher HIV viral load, renal dysfunction, and older age. Significant predictors of mortality after T2MI were low body-mass index (BMI) and detectable HIV viral load. Conclusions Mortality is high following MI for PWH and substantially greater after T2MI than T1MI. Predictors of death after MI differed by type of MI, reinforcing the different clinical scenarios associated with each MI type and the importance of considering MI types separately. Electronic supplementary material The online version of this article (10.1186/s12916-019-1385-7) contains supplementary material, which is available to authorized users.

CONTEXT. Advance care planning (ACP) is difficult in the setting of a life-threatening trauma but may be equally important in this context, especially with increasing numbers of trauma victims being elderly or having multimorbidity. OBJECTIVES. Identify predictors of absent ACP documentation in the electronic health records of patients with underlying chronic illness who died of traumatic injury. METHODS. We used death records and electronic health records to identify decedents with chronic life-limiting illness who died of traumatic injury between 2010 and 2015 and to evaluate factors associated with documentation of living wills, durable powers of attorney, or physician orders for life-sustaining treatment. RESULTS. Only 22% of decedents had ACP documentation at time of injury. Among those without preinjury ACP documentation, 4% completed ACP documentation after injury. In multipredictor analyses, patients were less likely to have ACP documentation at the time of injury if they were younger (P < 0.001), had fewer chronic illnesses (P = 0.002), and had fewer nonsurgical hospitalizations (P = 0.042) in the year before injury. Among patients without ACP documentation before injury, those with fewer postinjury nonsurgical hospitalizations were less likely to complete ACP documentation after injury (P = 0.019). CONCLUSIONS. Our findings suggest that patient characteristics play an important role in the completion of ACP among patients with chronic life-limiting illness and who died from sudden severe injury. Interventions to improve ACP completion by patients with serious chronic conditions have the potential for increasing goal-concordant care in the event of traumatic injury.

BackgroundResearch is needed to better understand relations between immunosuppression and HIV viraemia and risk for non-Hodgkin lymphoma, a common cancer in people living with HIV. We aimed to identify key CD4 count and HIV RNA (viral load) predictors of risk for non-Hodgkin lymphoma, overall and by subtype.MethodsWe studied people living with HIV during 1996-2014 from 21 Canadian and US cohorts participating in the North American AIDS Cohort Collaboration on Research and Design. To determine key independent predictors of risk for non-Hodgkin lymphoma, we assessed associations with time-updated recent, past, cumulative, and nadir or peak measures of CD4 count and viral load, using demographics-adjusted, cohort-stratified Cox models, and we compared models using Akaike's information criterion.FindingsOf 102 131 people living with HIV during the study period, 712 people developed non-Hodgkin lymphoma. The key independent predictors of risk for overall non-Hodgkin lymphoma were recent CD4 count (ie, lagged by 6 months

Background At-risk alcohol use is important to identify in clinical settings to facilitate interventions. The Patient-Reported Outcomes Measurement Information System (PROMIS) Alcohol Use Short Form was developed through an item response theory process, but its utility as a screening instrument in clinical care has not been reported. Objective To determine the ability of the PROMIS Alcohol Use Short Form to identify people with current or future at-risk alcohol use defined by the Alcohol Use Disorders Identification Test consumption (AUDIT-C) instrument. Methods Observational study of people living with HIV (PLWH) in clinical care at four sites across the US. Patients completed a tablet-based clinical assessment prior to seeing their providers at clinic appointments. We used 3 definitions of clinically-relevant at-risk alcohol use and determined the proportion of PLWH with current or future at-risk drinking identified by the PROMIS instrument. Results Of 2497 PLWH who endorsed ≥1 drink in the prior 12 months, 1500 PLWH (60%) endorsed “never” for all PROMIS items. In that group, 26% had clinically-relevant at-risk alcohol use defined by one or more AUDIT-C definitions. At follow-up (N = 1608), high baseline PROMIS scores had 55% sensitivity for at-risk drinking among those with at-risk drinking at baseline, and 22% sensitivity among those without baseline risk. Conclusions The PROMIS Alcohol Use Short Form cannot be used alone to identify PLWH with clinically-relevant at-risk alcohol use. Optimal assessment of problem drinking behavior is not clear, but there does not seem to be an important role for the PROMIS instrument in this clinical setting.

Importance Patients with chronic illness frequently use Physician Orders for Life-Sustaining Treatment (POLST) to document treatment limitations. Objectives To evaluate the association between POLST order for medical interventions and intensive care unit (ICU) admission for patients hospitalized near the end of life. Design, Setting, and Participants Retrospective cohort study of patients with POLSTs and with chronic illness who died between January 1, 2010, and December 31, 2017, and were hospitalized 6 months or less before death in a 2-hospital academic health care system. Exposures POLST order for medical interventions (“comfort measures only” vs “limited additional interventions” vs “full treatment”), age, race/ethnicity, education, days from POLST completion to admission, histories of cancer or dementia, and admission for traumatic injury. Main Outcomes and Measures The primary outcome was the association between POLST order and ICU admission during the last hospitalization of life; the secondary outcome was receipt of a composite of 4 life-sustaining treatments: mechanical ventilation, vasopressors, dialysis, and cardiopulmonary resuscitation. For evaluating factors associated with POLST-discordant care, the outcome was ICU admission contrary to POLST order for medical interventions during the last hospitalization of life. Results Among 1818 decedents (mean age, 70.8 [SD, 14.7] years; 41% women), 401 (22%) had POLST orders for comfort measures only, 761 (42%) had orders for limited additional interventions, and 656 (36%) had orders for full treatment. ICU admissions occurred in 31% (95% CI, 26%-35%) of patients with comfort-only orders, 46% (95% CI, 42%-49%) with limited-interventions orders, and 62% (95% CI, 58%-66%) with full-treatment orders. One or more life-sustaining treatments were delivered to 14% (95% CI, 11%-17%) of patients with comfort-only orders and to 20% (95% CI, 17%-23%) of patients with limited-interventions orders. Compared with patients with full-treatment POLSTs, those with comfort-only and limited-interventions orders were significantly less likely to receive ICU admission (comfort only: 123/401 [31%] vs 406/656 [62%], aRR, 0.53 [95% CI, 0.45-0.62]; limited interventions: 349/761 [46%] vs 406/656 [62%], aRR, 0.79 [95% CI, 0.71-0.87]). Across patients with comfort-only and limited-interventions POLSTs, 38% (95% CI, 35%-40%) received POLST-discordant care. Patients with cancer were significantly less likely to receive POLST-discordant care than those without cancer (comfort only: 41/181 [23%] vs 80/220 [36%], aRR, 0.60 [95% CI, 0.43-0.85]; limited interventions: 100/321 [31%] vs 215/440 [49%], aRR, 0.63 [95% CI, 0.51-0.78]). Patients with dementia and comfort-only orders were significantly less likely to receive POLST-discordant care than those without dementia (23/111 [21%] vs 98/290 [34%], aRR, 0.44 [95% CI, 0.29-0.67]). Patients admitted for traumatic injury were significantly more likely to receive POLST-discordant care (comfort only: 29/64 [45%] vs 92/337 [27%], aRR, 1.52 [95% CI, 1.08-2.14]; limited interventions: 51/91 [56%] vs 264/670 [39%], aRR, 1.36 [95% CI, 1.09-1.68]). In patients with limited-interventions orders, older age was significantly associated with less POLST-discordant care (aRR, 0.93 per 10 years [95% CI, 0.88-1.00]). Conclusions and Relevance Among patients with POLSTs and with chronic life-limiting illness who were hospitalized within 6 months of death, treatment-limiting POLSTs were significantly associated with lower rates of ICU admission compared with full-treatment POLSTs. However, 38% of patients with treatment-limiting POLSTs received intensive care that was potentially discordant with their POLST.

IMPORTANCE: Surgeons are increasingly interested in using mobile and online applications with wound photography to monitor patients after surgery. Early work using remote care to diagnose surgical site infections (SSIs) demonstrated improved diagnostic accuracy using wound photographs to augment patients’ electronic reports of symptoms, but it is unclear whether these findings are reproducible in real-world practice. OBJECTIVE: To determine how wound photography affects surgeons’ abilities to diagnose SSIs in a pragmatic setting. DESIGN, SETTING, AND PARTICIPANTS: This prospective study compared surgeons’ paired assessments of postabdominal surgery case vignettes with vs without wound photography for detection of SSIs. Data for case vignettes were collected prospectively from May 1, 2007, to January 31, 2009, at Erasmus University Medical Center, Rotterdam, the Netherlands, and from July 1, 2015, to February 29, 2016, at Vanderbilt University Medical Center, Nashville, Tennessee. The surgeons were members of the American Medical Association whose self-designated specialty is general, abdominal, colorectal, oncologic, or vascular surgery and who completed internet-based assessments from May 21 to June 10, 2016. INTERVENTION: Surgeons reviewed online clinical vignettes with or without wound photography. MAIN OUTCOMES AND MEASURES: Surgeons’ diagnostic accuracy, sensitivity, specificity, confidence, and proposed management with respect to SSIs. RESULTS: A total of 523 surgeons (113 women and 410 men; mean [SD] age, 53 [10] years) completed a mean of 2.9 clinical vignettes. For the diagnosis of SSIs, the addition of wound photography did not change accuracy (863 of 1512 [57.1%] without and 878 of 1512 [58.1%] with photographs). Photographs decreased sensitivity (from 0.58 to 0.50) but increased specificity (from 0.56 to 0.63). In 415 of 1512 cases (27.4%), the addition of wound photography changed the surgeons’ assessment (215 of 1512 [14.2%] changed from incorrect to correct and 200 of 1512 [13.2%] changed from correct to incorrect). Surgeons reported greater confidence when vignettes included a wound photograph compared with vignettes without a wound photograph, regardless of whether they correctly identified an SSI (median, 8 [interquartile range, 6-9] vs median, 8 [interquartile range, 7-9]; P

Background: Although racial/ethnic minorities receive more intense, nonbeneficial healthcare at the end of life, the role of race/ethnicity independent of other social determinants of health is not well understood. Objectives: Examine the association between race/ethnicity, other key social determinants of health, and healthcare intensity in the last 30 days of life for those with chronic, life-limiting illness. Subjects: We identified 22,068 decedents with chronic illness cared for at a single healthcare system in Washington State who died between 2010 and 2015 and linked electronic health records to death certificate data. Design: Binomial regression models were used to test associations of healthcare intensity with race/ethnicity, insurance status, education, and median income by zip code. Path analyses tested direct and indirect effects of race/ethnicity with insurance, education, and median income by zip code used as mediators. Measurements: We examined three measures of healthcare intensity: (1) intensive care unit admission, (2) use of mechanical ventilation, and (3) receipt of cardiopulmonary resuscitation. Results: Minority race/ethnicity, lower income and educational attainment, and Medicaid and military insurance were associated with higher intensity care. Socioeconomic disadvantage accounted for some of the higher intensity in racial/ethnic minorities, but most of the effects were direct effects of race/ethnicity. Conclusions: The effects of minority race/ethnicity on healthcare intensity at the end of life are only partly mediated by other social determinants of health. Future interventions should address the factors driving both direct and indirect effects of race/ethnicity on healthcare intensity.

Catheter-associated urinary tract infection (CAUTI) is a common and costly healthcare-associated infection, yet measuring it accurately is challenging and resource-intensive. Electronic surveillance promises to make this task more objective and efficient in an era of new financial and regulatory imperatives, but previous surveillance approaches have used a simplified version of the definition. We applied a complete definition, including subjective elements identified through natural language processing of clinical notes. Through examination of documentation practices, we defined a set of rules that identified positively and negatively asserted symptoms of CAUTI. Our algorithm was developed on a training set of 1421 catheterizedpatients and prospectively validated on 1567 catheterizedpatients. Compared to gold standard chart review, our tool had a sensitivity of 97.1%, specificity of 94.5% PPV of 66.7% and NPV of 99.6% for identifying CAUTI. We discuss sources of error and suggestions for more computable future definitions.

Context: Obesity is a significant health issue in the United States that both clinical and public health systems struggle to address. Electronic health record data could help support multi-sectoral interventions to address obesity. Standards have been identified and created to support the electronic exchange of weight-related data across many stakeholder groups.Case Description: The Centers for Disease Control and Prevention initiated a public-private partnership including government, industry, and academic technology partners to develop workflow scenarios and supporting systems to exchange weight-related data through standard transactions. This partnership tested the transmission of data using this newly-defined Healthy Weight (HW) profile at multiple health data interoperability demonstration events.Findings: Five transaction types were tested by 12 partners who demonstrated how the standards and related systems support end-to-end workflows around managing weight-related issues in the community. The standard transactions were successfully tested at two Integrating the Healthcare Enterprise (IHE) Connectathon events through 86 validated tests encompassing 38 multi-partner transactions.Discussion: We have successfully demonstrated the transactions defined in the HW profile with a public-private partnership. These tested IT products and HW standards could be used to support a continuum of care around health related issues encompassing both health care and public health functions.Conclusion: The use of the HW profile, including a set of transactions and identified standards to implement those transactions, in IT products is a helpful first step in leveraging health information technology to address weight-related issues in the United States. Future work is needed to expand the use of these standards and to assess their use in real world settings.

As our population ages and the burden of chronic illness rises, there is increasing need to implement quality metrics that measure and benchmark care of the seriously ill, including the delivery of both primary care and specialty palliative care. Such metrics can be used to drive quality improvement, value-based payment, and accountability for population-based outcomes.In this article, we examine use of the electronic health record (EHR) as a tool to assess quality of serious illness care through narrative review and description of a palliative care quality metrics program in a large healthcare system.In the search for feasible, reliable, and valid palliative care quality metrics, the EHR is an attractive option for collecting quality data on large numbers of seriously ill patients. However, important challenges to using EHR data for quality improvement and accountability exist, including understanding the validity, reliability, and completeness of the data, as well as acknowledging the difference between care documented and care delivered. Challenges also include developing achievable metrics that are clearly linked to patient and family outcomes and addressing data interoperability across sites as well as EHR platforms and vendors. This article summarizes the strengths and weakness of the EHR as a data source for accountability of community- and population-based programs for serious illness, describes the implementation of EHR data in the palliative care quality metrics program at the University of Washington, and, based on that experience, discusses opportunities and challenges. Our palliative care metrics program was designed to serve as a resource for other healthcare systems.Although the EHR offers great promise for enhancing quality of care provided for the seriously ill, significant challenges remain to operationalizing this promise on a national scale and using EHR data for population-based quality and accountability.

The objective of this study was to develop and pilot test a chronic pain empowerment and self-management platform, derived from acceptance and commitment therapy, in a pain specialty setting. A controlled, sequential, nonrandomized study design was used to accommodate intervention development and to test the efficacy of the PainTracker Self-Manager (PTSM) intervention (Web-based educational modules and outcome tracking combined with tailored patient coaching sessions and provider guidance). Generalized estimating equations evaluated changes over time (baseline, 3 months, 6 months) in pain self-efficacy (primary outcome), chronic pain acceptance (activity engagement and pain willingness), perceived efficacy in patient–provider interactions, pain intensity and interference, and overall satisfaction with pain treatment (secondary outcomes) between intervention (n = 48) and usual care control groups (n = 51). The full study sample (N = 99) showed greater improvements over time (significant Group × Time interactions) in pain self-efficacy and satisfaction with pain treatment. Among study completers (n = 82), greater improvement in activity engagement as well as pain intensity and interference were also observed. These preliminary findings support the efficacy of the PTSM intervention in a pain specialty setting. Further research is needed to refine and expand the PTSM intervention and to test it in a randomized trial in primary care settings. Perspective We developed a Web-based patient empowerment platform that combined acceptance and commitment therapy-based educational modules and tailored coaching sessions with longitudinal tracking of treatments and patient-reported outcomes, named PTSM. Pilot controlled trial results provide preliminary support for its efficacy in improving pain self-efficacy, activity engagement, pain intensity and interference, and satisfaction with pain treatment.

BACKGROUND: Patient-provider sexual risk behavior discussions occur infrequently but may be facilitated by high-quality sexual risk screening tools. OBJECTIVE: To develop the Sexual Risk Behavior Inventory (SRBI), a brief computer-administered patient-reported measure. DESIGN: Qualitative item development/quantitative instrument validation. PARTICIPANTS: We developed SRBI items based on patient interviews (n = 128) at four geographically diverse US primary care clinics. Patients were diverse in gender identity, sex, sexual orientation, age, race/ethnicity, and HIV status. We compared sexual risk behavior identified by the SRBI and the Risk Assessment Battery (RAB) among patients (n = 422). APPROACH: We constructed an item pool based on validated measures of sexual risk, developed an in-depth interview guide based on pool content, and used interviews to elicit new sexual risk concepts. We coded concepts, matched them to item pool content, and developed new content where needed. A provider team evaluated item clinical relevance. We conducted cognitive interviews to assess item comprehensibility. We administered the SRBI and the RAB to patients. KEY RESULTS: Common, clinically relevant concepts in the SRBI included number of sex partners; partner HIV status; partner use of antiretroviral medication (ART)/pre-exposure prophylaxis (PrEP); and recent sex without barrier protection, direction of anal sex, and concern regarding HIV/STI exposure. While 90% reported inconsistent condom use on the RAB, same-day SRBI administration revealed that for over one third, all their partners were on ART/PrEP. CONCLUSION: The SRBI is a brief, skip-patterned, clinically relevant measure that ascertains sexual risk behavior across sex, sexual orientation, gender identity, partner HIV serostatus, and partner treatment status, furnishing providers with context to determine gradations of risk for HIV/STI.

We compared same-day provider medical record documentation and interventions addressing depression and risk behaviors before and after delivering point-of-care patient-reported outcomes (PROs) feedback for patients who self-reported clinically relevant levels of depression or risk behaviors. During the study period (1 January 2006–15 October 2010), 2289 PRO assessments were completed by HIV-infected patients. Comparing the 8 months before versus after feedback implementation, providers were more likely to document depression (74% before vs. 87% after feedback, p = 0.02) in patients with moderate-to-severe depression (n = 317 assessments), at-risk alcohol use (41 vs. 64%, p = 0.04, n = 155) and substance use (60 vs. 80%, p = 0.004, n = 212). Providers were less likely to incorrectly document good adherence among patients with inadequate adherence after feedback (42 vs. 24%, p = 0.02, n = 205). While PRO feedback of depression and adherence were followed by increased provider intervention, other domains were not. Further investigation of factors associated with the gap between awareness and intervention are needed in order to bridge this divide.

Importance The Second Universal Definition of Myocardial Infarction (MI) divides MIs into different types. Type 1 MIs result spontaneously from instability of atherosclerotic plaque, whereas type 2 MIs occur in the setting of a mismatch between oxygen demand and supply, as with severe hypotension. Type 2 MIs are uncommon in the general population, but their frequency in human immunodeficiency virus (HIV)–infected individuals is unknown. Objectives To characterize MIs, including type; identify causes of type 2 MIs; and compare demographic and clinical characteristics among HIV-infected individuals with type 1 vs type 2 MIs. Design, Setting, and Participants This longitudinal study identified potential MIs among patients with HIV receiving clinical care at 6 US sites from January 1, 1996, to March 1, 2014, using diagnoses and cardiac biomarkers recorded in the centralized data repository. Sites assembled deidentified packets, including physician notes and electrocardiograms, procedures, and clinical laboratory tests. Two physician experts adjudicated each event, categorizing each definite or probable MI as type 1 or type 2 and identifying the causes of type 2 MI. Main Outcomes and Measures The number and proportion of type 1 vs type 2 MIs, demographic and clinical characteristics among those with type 1 vs type 2 MIs, and the causes of type 2 MIs. Results Among 571 patients (median age, 49 years [interquartile range, 43-55 years]; 430 men and 141 women) with definite or probable MIs, 288 MIs (50.4%) were type 2 and 283 (49.6%) were type 1. In analyses of type 1 MIs, 79 patients who underwent cardiac interventions, such as coronary artery bypass graft surgery, were also included, totaling 362 patients. Sepsis or bacteremia (100 [34.7%]) and recent use of cocaine or other illicit drugs (39 [13.5%]) were the most common causes of type 2 MIs. A higher proportion of patients with type 2 MIs were younger than 40 years (47 of 288 [16.3%] vs 32 of 362 [8.8%]) and had lower current CD4 cell counts (median, 230 vs 383 cells/µL), lipid levels (mean [SD] total cholesterol level, 167 [63] vs 190 [54] mg/dL, and mean (SD) Framingham risk scores (8% [7%] vs 10% [8%]) than those with type 1 MIs or who underwent cardiac interventions. Conclusions and Relevance Approximately half of all MIs among HIV-infected individuals were type 2 MIs caused by heterogeneous clinical conditions, including sepsis or bacteremia and recent use of cocaine or other illicit drugs. Demographic characteristics and cardiovascular risk factors among those with type 1 and type 2 MIs differed, suggesting the need to specifically consider type among HIV-infected individuals to further understand MI outcomes and to guide prevention and treatment.

Phone-based unannounced pill counts to measure medication adherence are much more practical and less expensive than home-based unannounced pill counts, but their validity has not been widely assessed. We examined the validity of phone versus home-based pill counts using a simplified protocol streamlined for studies embedded in clinical care settings. A total of 100 paired counts were used to compare concordance between unannounced phone and home-based pill counts using interclass correlations. Discrepancy analyses using χ(2) tests compared demographic and clinical characteristics across patients who were concordant between phone and home-based pill counts and patients who were not concordant. Concordance was high for phone-based and home-based unannounced total pill counts, as well as individual medication counts and calculated adherence. This study demonstrates that a simplified phone-based pill count protocol can be implemented among patients from a routine clinical care setting and is a feasible means of monitoring medication adherence.

In this paper, we develop a novel formulation for contemporaneous patient risk monitoring by exploiting the emerging data-rich environment in many healthcare applications, where an abundance of longitudinal data that reflect the degeneration of the health condition can be continuously collected. Our objective, and the developed formulation, is fundamentally different from many existing risk score models for different healthcare applications, which mostly focus on predicting the likelihood of a certain outcome at a pre-specified time. Rather, our formulation translates multivariate longitudinal measurements into a contemporaneous health index (CHI) that captures patient condition changes over the course of progression. Another significant feature of our formulation is that, CHI can be estimated with or without label information, different from other risk score models strictly based on supervised learning. To develop this formulation, we focus on the degenerative disease conditions, for which we could utilize the monotonic progression characteristic (either towards disease or recovery) to learn CHI. Such a domain knowledge leads us to a novel learning formulation, and on top of that, we further generalize this formulation with a capacity to incorporate label information if available. We further develop algorithms to mitigate the challenges associated with the nonsmooth convex optimization problem by first identifying its dual reformulation as a constrained smooth optimization problem, and then, using the block coordinate descent algorithm to iteratively solve the optimization with a derived efficient projection at each iteration. Extensive numerical studies are performed on both synthetic datasets and real-world applications on Alzheimer's disease and Surgical Site Infection, which demonstrate the utility and efficacy of the proposed method on degenerative conditions that include a wide range of applications.

Little is known about psychiatric illness and utilization of end-of-life care.We hypothesized that preexisting psychiatric illness would increase hospital utilization at end of life among patients with chronic medical illness due to increased severity of illness and care fragmentation.We reviewed electronic health records to identify decedents with one or more of eight chronic medical conditions based on International Classification of Diseases-9 codes. We used International Classification of Diseases-9 codes and prescription information to identify preexisting psychiatric illness. Regression models compared hospital utilization among patients with and without psychiatric illness. Path analyses examined the effect of severity of illness and care fragmentation.Eleven percent of 16,214 patients with medical illness had preexisting psychiatric illness, which was associated with increased risk of death in nursing homes (P = 0.002) and decreased risk of death in hospitals (P 0.001). In the last 30 days of life, psychiatric illness was associated with reduced inpatient and intensive care unit utilization but increased emergency department utilization. Path analyses confirmed an association between psychiatric illness and increased hospital utilization mediated by severity of illness and care fragmentation, but a stronger direct effect of psychiatric illness decreasing hospitalizations.Our findings differ from the increased hospital utilization for patients with psychiatric illness in circumstances other than end-of-life care. Path analyses confirmed hypothesized associations between psychiatric illness and increased utilization mediated by severity of illness and care fragmentation but identified more powerful direct effects decreasing hospital use. Further investigation should examine whether this effect represents a disparity in access to preferred care.

Postoperative surgical site infections (SSI) are common and costly. Most occur post discharge, and can result in potentially preventable readmission or unnecessary urgent evaluation. Mobile health approaches incorporating patient-generated wound photos are being implemented in an attempt to optimize triage and management. We assessed how adding wound photos to existing data sources modifies provider decision making.We used a web-based simulation survey using a convenience sample of providers with expertise in surgical infections. Participants viewed a range of scenarios, including surgical history, physical exam, and description of wound appearance. All participants reported SSI diagnosis, diagnostic confidence, and management recommendations (main outcomes) first without, and then with, accompanying wound photos. At each step, participants ranked the most important features contributing to their decision.Eighty-three participants completed a median of 5 scenarios (interquartile range 4 to 7). Most participants were physicians in academic surgical specialties (n = 70 [84%]). The addition of photos improved overall diagnostic accuracy from 67% to 76% (p0.001), and increased specificity from 77% to 92% (p0.001), but did not significantly increase sensitivity (55% to 65%; p = 0.16). Photos increased mean confidence in diagnosis from 5.9 of 10 to 7.4 of 10 (p0.001). Overtreatment recommendations decreased from 48% to 16% (p0.001), and undertreatment did not change (28% to 23%; p = 0.20) with the addition of photos.The addition of wound photos to existing data as available via chart review and telephone consultation with patients significantly improved diagnostic accuracy and confidence, and prevented proposed overtreatment in scenarios without SSI. Post-discharge mobile health technologies have the potential to facilitate patient-centered care, decrease costs, and improve clinical outcomes.