A Person-Centered, Registry-Based Learning Health System for Palliative Care: A Path to Coproducing Better Outcomes, Experience, Value, and Science

Evaluation of the Concept of Value-Based Healthcare Applied to an Integrated Palliative Care Program in Colombia

OBJECTIVE

This study aimed to evaluate the "Value-Based Healthcare" concept of an integrated palliative care (PC) program in Bogotá, Colombia, through the measurement of health outcomes and care costs in the last 3 months of life.

METHODS

A multicenter, retrospective cohort study that included patients ≥18 years old who died in 2020 due to medical conditions amenable to PC. The measured health outcomes included pain, wellbeing, comfort, quality of life (QOL), and satisfaction. We analyzed the behavior of overall care costs during the last 3 months of the patients' lives and controlled for the effect of exposure to the program, considering the disease type and insurance coverage, using a linear regression model, nearest-neighbor matching, and sensitivity analysis.

RESULTS

Among patients exposed to the program, the mean pain score was 2.1/10 (± 1.3) and wellbeing was rated at 3.5/10 (± 1.0), comfort at 1.6/24 (± 1.3), QOL at 3.6/5.0 (± 0.17), and satisfaction at 9.3/100 (± 0.15). The positive changes in these scores were greater for patients who remained in the program for over 3 months. Cost reduction was demonstrated in the last 90 days of life, with statistically significant and chronologically progressive savings during the last 30 days of life exceeding 5 million pesos per patient (P < .05).

CONCLUSIONS

This study demonstrated the success of PC in reducing pain, improving wellbeing and QOL, providing comfort, and ensuring high levels of satisfaction. Moreover, PC is an effective value-based healthcare strategy and can significantly enhance the efficiency of healthcare services by reducing end-of-life healthcare costs.

The speech neuroprosthesis

Loss of speech after paralysis is devastating, but circumventing motor-pathway injury by directly decoding speech from intact cortical activity has the potential to restore natural communication and self-expression. Recent discoveries have defined how key features of speech production are facilitated by the coordinated activity of vocal-tract articulatory and motor-planning cortical representations. In this Review, we highlight such progress and how it has led to successful speech decoding, first in individuals implanted with intracranial electrodes for clinical epilepsy monitoring and subsequently in individuals with paralysis as part of early feasibility clinical trials to restore speech. We discuss high-spatiotemporal-resolution neural interfaces and the adaptation of state-of-the-art speech computational algorithms that have driven rapid and substantial progress in decoding neural activity into text, audible speech, and facial movements. Although restoring natural speech is a long-term goal, speech neuroprostheses already have performance levels that surpass communication rates offered by current assistive-communication technology. Given this accelerated rate of progress in the field, we propose key evaluation metrics for speed and accuracy, among others, to help standardize across studies. We finish by highlighting several directions to more fully explore the multidimensional feature space of speech and language, which will continue to accelerate progress towards a clinically viable speech neuroprosthesis.

Using Patient-Centered Dissemination and Implementation Frameworks and Strategies in Palliative Care Settings for Improved Quality of Life and Health Outcomes: A Scoping Review

BACKGROUND

There is a need for patient-provider dissemination and implementation frameworks, strategies, and protocols in palliative care settings for a holistic approach when it comes to addressing pain and other distressing symptoms affecting the quality of life, function, and independence of patients with chronic illnesses. The purpose of this scoping review is to explore patient-centered D&I frameworks and strategies that have been adopted in PC settings to improve behavioral and environmental determinants influencing health outcomes through evidence-based programs and protocols.

METHODS

The five step Arksey and O'Malley's (2005) York methodology was adopted as a guiding framework: (1) identifying research questions; (2) searching for relevant studies; (3) selecting studies relevant to the research questions; (4) charting the data; and (5) collating, summarizing, and reporting results.

RESULTS

Only 6 out of the 38 (16%) included studies applied a D&I theory and/or framework. The RE-AIM framework was the most prominently cited (n = 3), followed by the Diffusion of Innovation Model (n = 2), the CONNECT framework (n = 1), and the Transtheoretical Stages of Change Model (n = 1). The most frequently reported ERIC strategy was strategy #6 "Develop and organize quality monitoring systems", as it identified in all 38 of the included studies.

CONCLUSION

This scoping review identifies D&I efforts to translate research into practice in U.S. palliative care settings. Results may contribute to enhancing future D&I initiatives for dissemination/adaptation, implementation, and sustainability efforts aiming to improve patient health outcomes and personal satisfaction with care received.

The use and role of digital technology in learning health systems: A scoping review

OBJECTIVE

The review aimed to identify which digital technologies are proposed or used within learning health systems (LHS) and to analyze the extent to which they support learning processes in LHS.

MATERIALS AND METHODS

Multiple databases and grey literature were searched with terms related to LHS. Manual searches and backward searches of reference lists were also undertaken. The review considered publications from 2007 to 2022. Records focusing on LHS, referring to one or more digital technologies, and describing how at least one digital technology could be used in LHS were included.

RESULTS

2046 records were screened for inclusion and 154 records were included in the analysis. Twenty categories of digital technology were identified. The two most common ones across records were data recording and processing and electronic health records. Digital technology was primarily leveraged to support data access and aggregation and data analysis, two of the seven recognized learning processes within LHS learning cycles.

DISCUSSION

The results of the review show that a wide array of digital technologies is being leveraged to support learning cycles within LHS. Nevertheless, an over-reliance on a narrow set of technologies supporting knowledge discovery, a lack of direct evaluation of digital technologies and ambiguity in technology descriptions are hindering the realization of the LHS vision.

CONCLUSION

Future LHS research and initiatives should aim to integrate digital technology to support practice change and impact evaluation. The use of recognized evaluation methods for health information technology and more detailed descriptions of proposed technologies are also recommended.

Maintaining High-Touch in High-Tech Digital Health Monitoring and Multi-Omics Prognostication: Ethical, Equity, and Societal Considerations in Precision Health for Palliative Care

Advances in digital health, systems biology, environmental monitoring, and artificial intelligence (AI) continue to revolutionize health care, ushering a precision health future. More than disease treatment and prevention, precision health aims at maintaining good health throughout the lifespan. However, how can precision health impact care for people with a terminal or life-limiting condition? We examine here the ethical, equity, and societal/relational implications of two precision health modalities, (1) integrated systems biology/multi-omics analysis for disease prognostication and (2) digital health technologies for health status monitoring and communication. We focus on three main ethical and societal considerations: benefits and risks associated with integration of these modalities into the palliative care system; inclusion of underrepresented and marginalized groups in technology development and deployment; and the impact of high-tech modalities on palliative care's highly personalized and "high-touch" practice. We conclude with 10 recommendations for ensuring that precision health technologies, such as multi-omics prognostication and digital health monitoring, for palliative care are developed, tested, and implemented ethically, inclusively, and equitably.

Patient-Reported Quality Measures for Palliative Care: The Time is now

CONTEXT

While progress has been made in the ability to measure the quality of hospice and specialty palliative care, there are notable gaps. A recent analysis conducted by Center for Medicare and Medicaid Services (CMS) revealed a paucity of patient-reported measures, particularly in palliative care domains such as symptom management and communication.

OBJECTIVES

The research team, consisting of quality measure and survey developers, psychometricians, and palliative care clinicians, used established state-of-the art methods for developing and testing patient-reported measures.

METHODS

We applied a patient-centered, patient-engaged approach throughout the development and testing process. This sequential process included 1) an information gathering phase; 2) a pre-testing phase; 3) a testing phase; and 4) an endorsement phase.

RESULTS

To fill quality measure gaps identified during the information gathering phase, we selected two draft measures ("Feeling Heard and Understood" and "Receiving Desired Help for Pain") for testing with patients receiving palliative care in clinic-based settings. In the pre-testing phase, we used an iterative process of cognitive interviews to refine draft items and corresponding response options for the proposed measures. The alpha pilot test supported establishment of protocols for the national beta field test. Measures met conventional criteria for reliability, had strong face and construct validity, and there was diversity in program level scores. The measures received National Quality Forum (NQF) endorsement.

CONCLUSION

These measures highlight the key role of patient voices in palliative care and fill a much-needed gap for patient-reported experience measures in our field.

Top Ten Tips Palliative Care Clinicians Should Know About Leveraging the Electronic Health Record for Data Collection and Quality Improvement

As palliative care (PC) programs rapidly grow and expand across settings, the need to measure, improve, and standardize high-quality PC has also grown. The electronic health record (EHR) is a key component of these efforts as a central hub of care delivery and a repository of patient and system data. Deliberate efforts to leverage the EHR for PC quality improvement (QI) can help PC programs and health systems improve care for patients with serious illnesses. This article, written by clinicians with experience in QI, informatics, and clinical program development, provides practical tips and guidance on EHR strategies and tools for QI and quality measurement.

Psychometric assessment of the consideRATE questions, a new measure of serious illness experience, with an online simulation study

OBJECTIVE

To assess the psychometric properties of the consideRATE questions, a measure of serious illness experience.

METHODS

We recruited people at least 50 years old via paid panels online, with US-Census-based quotas. We randomized participants to a patient experience story at two time points. Participants completed a series of measures, including the consideRATE questions. We assessed convergent (Pearson's correlation), discriminative (one-way ANOVA with Tukey's test for multiple comparisons) and divergent (Pearson's correlation) validity. We also assessed intra-rater reliability (intra-class correlation) and responsiveness to change (t-tests).

RESULTS

We included 809 individuals in our analysis. We established convergent validity (r = 0.77; p < 0.001); discriminative validity (bad/neutral stories [mean diff=0.4; p < 0.001]; neutral/ good stories [mean diff=1.3; p < 0.001]) and moderate divergent validity (r = 0.57; p < 0.001). We established sensitivity to change in all stories (bad/good [mean diff=1.52; p < 0.001]; good/bad [mean diff= -1.68; p < 0.001]; neutral/bad [mean diff= -0.57; p < 0.001]; good/neutral [mean diff= -1.11; p < 0.001]; neutral/good [mean diff= 1.1; p < 0.001]) but one (bad/neutral [mean diff= 0.4; p < 0.07]). Intra-rater reliability was demonstrated between time points (r = 0.77; p < 0.001).

CONCLUSIONS

the consideRATE questions were reliable and valid in a simulated online test.

PRACTICE IMPLICATIONS

the consideRATE questions may be a practical way to measure serious illness experience and the effectiveness of interventions to improve it.

Conceptualizing learning health systems: A mapping review

Introduction

Health systems worldwide face the challenge of increasing population health with high-quality care and reducing health care expenditure growth. In pursuit for a solution, regional cross-sectoral partnerships aim to reorganize and integrate services across public health, health care and social care. Although the complexity of regional partnerships demands an incremental strategy, it is yet not known how learning works within these partnerships. To understand learning in regional cross-sectoral partnerships for health, this study aims to map the concept Learning Health System (LHS).

Methods

This mapping review used a qualitative text analysis approach. A literature search was conducted in Embase and was limited to English-language papers published in the period 2015-2020. Title-abstract screening was performed using established exclusion criteria. During full-text screening, we combined deductive and inductive coding. The concept LHS was disentangled into aims, design elements, and process of learning. Data extraction and analysis were performed in MAX QDA 2020.

Results

In total, 155 articles were included. All articles used the LHS definition of the Institute of Medicine. The interpretation of the concept LHS varied widely. The description of LHS contained 25 highly connected aims. In addition, we identified nine design elements. Most elements were described similarly, only the interpretation of stakeholders, data infrastructure and data varied. Furthermore, we identified three types of learning: learning as 1) interaction between clinical practice and research; 2) a circular process of converting routine care data to knowledge, knowledge to performance; and performance to data; and 3) recurrent interaction between stakeholders to identify opportunities for change, to reveal underlying values, and to evaluate processes. Typology 3 was underrepresented, and the three types of learning rarely occurred simultaneously.

Conclusion

To understand learning within regional cross-sectoral partnerships for health, we suggest to specify LHS-aim(s), operationalize design elements, and choose deliberately appropriate learning type(s).

Prioritizing Measures that Matter Within a Person-Centered Oncology Learning Health System

Background

Despite progress in developing learning health systems (LHS) and associated metrics of success, a gap remains in identifying measures to guide the implementation and assessment of the impact of an oncology LHS. Our aim was to identify a balanced set of measures to guide a person-centered oncology LHS.

Methods

A modified Delphi process and clinical value compass framework were used to prioritize measures for tracking LHS performance. A multidisciplinary group of 77 stakeholders, including people with cancer and family members, participated in 3 rounds of online voting followed by 50-minute discussions. Participants rated metrics on perceived importance to the LHS and discussed priorities.

Results

Voting was completed by 94% of participants and prioritized 22 measures within 8 domains. Patient and caregiver factors included clinical health (Eastern Cooperative Oncology Group Performance Status, survival by cancer type and stage), functional health and quality of life (Patient Reported Outcomes Measurement Information System [PROMIS] Global-10, Distress Thermometer, Modified Caregiver Strain Index), experience of care (advance care planning, collaboRATE, PROMIS Self-Efficacy Scale, access to care, experience of care, end-of-life quality measures), and cost and resource use (avoidance and delay in accessing care and medications, financial hardship, total cost of care). Contextual factors included team well-being (Well-being Index; voluntary staff turnover); learning culture (Improvement Readiness, compliance with Commission on Cancer quality of care measures); scholarly engagement and productivity (institutional commitment and support for research, academic productivity index); and diversity, equity, inclusion, and belonging (screening and follow-up for social determinants of health, inclusivity of staff and patients).

Conclusions

The person-centered LHS value compass provides a balanced set of measures that oncology practices can use to monitor and evaluate improvement across multiple domains.

The role of co-production in Learning Health Systems

Background

Co-production of health is defined as ‘the interdependent work of users and professionals who are creating, designing, producing, delivering, assessing, and evaluating the relationships and actions that contribute to the health of individuals and populations’. It can assume many forms and include multiple stakeholders in pursuit of continuous improvement, as in Learning Health Systems (LHSs). There is increasing interest in how the LHS concept allows integration of different knowledge domains to support and achieve better health. Even if definitions of LHSs include engaging users and their family as active participants in aspects of enabling better health for individuals and populations, LHS descriptions emphasize technological solutions, such as the use of information systems. Fewer LHS texts address how interpersonal interactions contribute to the design and improvement of healthcare services.

Objective

We examined the literature on LHS to clarify the role and contributions of co-production in LHS conceptualizations and applications.

Method

First, we undertook a scoping review of LHS conceptualizations. Second, we compared those conceptualizations to the characteristics of LHSs first described by the US Institute of Medicine. Third, we examined the LHS conceptualizations to assess how they bring four types of value co-creation in public services into play: co-production, co-design, co-construction and co-innovation. These were used to describe core ideas, as principles, to guide development.

Result

Among 17 identified LHS conceptualizations, 3 qualified as most comprehensive regarding fidelity to LHS characteristics and their use in multiple settings: (i) the Cincinnati Collaborative LHS Model, (ii) the Dartmouth Coproduction LHS Model and (iii) the Michigan Learning Cycle Model. These conceptualizations exhibit all four types of value co-creation, provide examples of how LHSs can harness co-production and are used to identify principles that can enhance value co-creation: (i) use a shared aim, (ii) navigate towards improved outcomes, (iii) tailor feedback with and for users, (iv) distribute leadership, (v) facilitate interactions, (vi) co-design services and (vii) support self-organization.

Conclusions

The LHS conceptualizations have common features and harness co-production to generate value for individual patients as well as for health systems. They facilitate learning and improvement by integrating supportive technologies into the sociotechnical systems that make up healthcare. Further research on LHS applications in real-world complex settings is needed to unpack how LHSs are grown through coproduction and other types of value co-creation.

Aiming for quality: a global compass for national learning systems

INTRODUCTION

Transforming a health system into a learning one is increasingly recognized as necessary to support the implementation of a national strategic direction on quality with a focus on frontline experience. The approach to a learning system that bridges the gap between practice and policy requires active exploration.

METHODS

This scoping review adapted the methodological framework for scoping studies from Arksey and O'Malley. The central research question focused on common themes for learning to improve the quality of health services at all levels of the national health system, from government policy to point-of-care delivery.

RESULTS

A total of 3507 records were screened, resulting in 101 articles on strategic learning across the health system: health professional level (19%), health organizational level (15%), subnational/national level (26%), multiple levels (35%), and global level (6%). Thirty-five of these articles focused on learning systems at multiple levels of the health system. A national learning system requires attention at the organizational, subnational, and national levels guided by the needs of patients, families, and the community. The compass of the national learning system is centred on four cross-cutting themes across the health system: alignment of priorities, systemwide collaboration, transparency and accountability, and knowledge sharing of real-world evidence generated at the point of care.

CONCLUSION

This paper proposes an approach for building a national learning system to improve the quality of health services. Future research is needed to validate the application of these guiding principles and make improvements based on the findings.

What constitutes a palliative care need in people with serious illnesses across Africa? A mixed-methods systematic review of the concept and evidence

BACKGROUND

Clarity on what constitutes a palliative care need is essential to ensure that health systems and clinical services deliver an appropriate response within Universal Health Coverage.

AIM

To synthesise primary evidence from Africa for palliative care needs among patients and families with serious illness.

DESIGN

We conducted a mixed methods systematic review with sequential synthesis design. The protocol was registered with PROSPERO (CRD42019136606) and included studies were quality assessed using Mixed Method Appraisal Tool.

DATA SOURCES

Six global literature databases and Three Africa-specific databases were searched up to October 2020 for terms related to palliative care, serious illnesses and Africa. Palliative care need was defined as multidimensional problems, symptoms, distress and concerns which can benefit from palliative care.

RESULTS

Of 7810 papers screened, 159 papers met eligibility criteria. Palliative care needs were mostly described amongst patients with HIV/AIDS (n = 99 studies) or cancer (n = 59), from East (n = 72) and Southern (n = 89) Africa. Context-specific palliative care needs included managing pregnancy and breastfeeding, preventing infection transmission (physical); health literacy needs, worry about medical bills (psychological); isolation and stigma, overwhelmed families needing a break, struggling to pay children's school fees and selling assets (social and practical needs); and rites associated with cultural and religious beliefs (spiritual).

CONCLUSIONS

Palliative care assessment and care must reflect the context-driven specific needs of patients and families in Africa, in line with the novel framework. Health literacy is a crucial need in this context that must be met to ensure that the benefits of palliative care can be achieved at the patient-level.

The work of having a chronic condition: development and psychometric evaluation of the distribution of co-care activities (DoCCA) scale

BACKGROUND

Chronic care involves multiple activities that can be performed by individuals and healthcare staff as well as by other actors and artifacts, such as eHealth services. Thus, chronic care management can be viewed as a system where the individual interacts with people and eHealth services performing activities to maintain or improve health and functioning, called co-care. Yet, the system perspective is not reflected in concepts such as person-centered care and shared decision making. This limits the understanding of individuals' global experience of chronic care management and subsequently the ability to optimize chronic care. The aim of this study was threefold: (1) to propose a theory-based operationalization of co-care for chronic care management, (2) to develop a scale to measure co-care as a distributed system of activities, and (3) to evaluate the scale's psychometric properties. With the theory of distributed cognition as a theoretical underpinning, co-care was operationalized along three dimensions: experience of activities, needs support, and goal orientation.

METHODS

Informed by the literature on patient experiences and work psychology, a scale denoted Distribution of Co-Care Activities (DoCCA) was developed with the three conceptualized dimensions, the activities dimension consisting of three sub-factors: demands, unnecessary tasks, and role clarity. It was tested with 113 primary care patients with chronic conditions in Sweden at two time points.

RESULTS

A confirmatory factor analysis showed support for a second-order model with the three conceptualized dimensions, with activities further divided into the three sub-factors. Cronbach's alpha values indicated a good to excellent reliability of the subscales, and correlations across time points with panel data indicated satisfactory test-retest reliability. Convergent, concurrent and predictive validity of the scale were, overall, satisfactory.

CONCLUSIONS

The psychometric evaluation supports a model consisting of activities (demands, unnecessary tasks, and role clarity), needs support and goal orientation that can be reliably measured with the DoCCA scale. The scale provides a way to assess chronic care management as a system, considering the perspective of the individuals with the chronic condition and how they perceive the work that must be done, across situations, either by themselves or through healthcare, eHealth, or other means.

Content comparison and person-centeredness of standards for quality improvement in cardiovascular health care

Background

Quality standards are important for improving health care by providing compelling evidence for best practice. High quality person-centered health care requires information on patients' experience of disease and of functioning in daily life.

Objective

To analyze and compare the content of five Swedish National Quality Registries (NQRs) and two standard sets of the International Consortium of Health Outcomes Measurement (ICHOM) related to cardiovascular diseases.

Materials and methods

An analysis of 2588 variables (= data items) of five NQRs—the Swedish Registry of Congenital Heart Disease, Swedish Cardiac Arrest Registry, Swedish Catheter Ablation Registry, Swedish Heart Failure Registry, SWEDEHEART (including four sub-registries) and two ICHOM standard sets–the Heart Failure Standard Set and the Coronary Artery Disease Standard Set. According to the name and definition of each variable, the variables were mapped to Donabedian’s quality criteria, whereby identifying whether they capture health care processes or structures or patients’ health outcomes. Health outcomes were further analyzed whether they were clinician- or patient-reported and whether they capture patients’ physiological functions, anatomical structures or activities and participation.

Results

In total, 606 variables addressed process quality criteria (31%), 58 structure quality criteria (3%) and 760 outcome quality criteria (38%). Of the outcomes reported, 85% were reported by clinicians and 15% by patients. Outcome variables addressed mainly ‘Body functions’ (n = 392, 55%) or diseases (n = 209, 29%). Two percent of all documented data captured patients’ lived experience of disease and their daily activities and participation (n = 51, 3% of all variables).

Conclusions

Quality standards in the cardiovascular field focus predominately on processes (e.g. treatment) and on body functions-related outcomes. Less attention is given to patients’ lived experience of disease and their daily activities and participation. The results can serve as a starting-point for harmonizing data and developing a common person-centered quality indicator set.

Identification of important factors in an inpatient fall risk prediction model to improve the quality of care using EHR and electronic administrative data: A machine-learning approach

BACKGROUND

Inpatient falls, many resulting in injury or death, are a serious problem in hospital settings. Existing falls risk assessment tools, such as the Morse Fall Scale, give a risk score based on a set of factors, but don't necessarily signal which factors are most important for predicting falls. Artificial intelligence (AI) methods provide an opportunity to improve predictive performance while also identifying the most important risk factors associated with hospital-acquired falls. We can glean insight into these risk factors by applying classification tree, bagging, random forest, and adaptive boosting methods applied to Electronic Health Record (EHR) data.

OBJECTIVE

The purpose of this study was to use tree-based machine learning methods to determine the most important predictors of inpatient falls, while also validating each via cross-validation.

MATERIALS AND METHODS

A case-control study was designed using EHR and electronic administrative data collected between January 1, 2013 to October 31, 2013 in 14 medical surgical units. The data contained 38 predictor variables which comprised of patient characteristics, admission information, assessment information, clinical data, and organizational characteristics. Classification tree, bagging, random forest, and adaptive boosting methods were used to identify the most important factors of inpatient fall-risk through variable importance measures. Sensitivity, specificity, and area under the ROC curve were computed via ten-fold cross validation and compared via pairwise t-tests. These methods were also compared to a univariate logistic regression of the Morse Fall Scale total score.

RESULTS

In terms of AUROC, bagging (0.89), random forest (0.90), and boosting (0.89) all outperformed the Morse Fall Scale (0.86) and the classification tree (0.85), but no differences were measured between bagging, random forest, and adaptive boosting, at a p-value of 0.05. History of Falls, Age, Morse Fall Scale total score, quality of gait, unit type, mental status, and number of high fall risk increasing drugs (FRIDs) were considered the most important features for predicting inpatient fall risk.

CONCLUSIONS

Machine learning methods have the potential to identify the most relevant and novel factors for the detection of hospitalized patients at risk of falling, which would improve the quality of patient care, and to more fully support healthcare provider and organizational leadership decision-making. Nurses would be able to enhance their judgement to caring for patients at risk for falls. Our study may also serve as a reference for the development of AI-based prediction models of other iatrogenic conditions. To our knowledge, this is the first study to report the importance of patient, clinical, and organizational features based on the use of AI approaches.

Role of Hospice Care at the End of Life for People With Cancer

Patient-defined factors that are important at the end of life include being physically independent for as long as possible, good symptom control, and spending quality time with friends and family. Hospice care adds to the quality of care and these patient-centered priorities for people with cancer and their families in the last weeks and days of life. Evidence from large observational studies demonstrate that hospice care can improve outcomes directly and support better and more appropriate health care use for people in the last stages of cancer.

Team-based community hospice care has measurable benefits for patients, their family caregivers, and health services. In addition to improved symptom control for patients and a greater likelihood of time spent at home, caregiver outcomes are better when hospice care is accessed: informational needs are better met, and caregivers have an improved ability to move on with life after the patient’s death compared with people who did not have access to these services.

Hospice care continues to evolve as its reach expands and the needs of patients continue to broaden. This is reflected in the transition from hospice being based on excellence in nursing to teams with a broad range of health professionals to meet the complex and changing needs of patients and their families. Additional integration of cancer services with hospice care will help to provide more seamless care for patients and supporting family caregivers during their caregiving and after the death of the patient.

Characteristics and Trends Among Patients With Cardiovascular Disease Referred to Palliative Care

IMPORTANCE

Use of palliative care (PC) for patients with cardiovascular disease (CVD) has increased recently. However, it is unknown if patients are receiving earlier referrals to PC.

OBJECTIVE

To assess characteristics and trends of patients with CVD referred to PC.

DESIGN, SETTING, AND PARTICIPANTS

Cohort study in which analysis of data from the multicenter Quality Data Collection Tool for Palliative Care registry from January 2, 2015, through December 29, 2017, included patients with CVD 18 years or older referred to initial PC consultation who had a documented palliative performance score (PPS) .

EXPOSURES

Patients with CVD who presented for an initial PC visit.

MAIN OUTCOMES AND MEASURES

The primary outcome was PPS. Secondary outcomes included symptoms and end-of-life documentation.

RESULTS

Among 1801 patients (mean [SD] age, 77.7 [13.7] years) from 16 sites in the analysis, 875 (48.6%) were women and 1339 (74.3%) were white. A low PPS score (0%-30%), consistent with bedbound status, was recorded for 521 patients (28.9%), with no change through time. The most common moderate to severe symptoms were poor well-being, tiredness, anorexia, and dyspnea. Year of encounter was associated with improved symptoms of pain (odds ratio, 1.25; 95% CI, 1.05-1.50) and with constipation (odds ratio, 1.32; 95% CI, 1.03-1.69). No change through time was noted in other symptoms or end-of-life documentation. Although the proportion of referrals from general medicine increased from 43.2% (167 of 387) in 2015 to 52.9% (410 of 775) in 2017, the proportion of referrals from cardiologists decreased from 16.5% (64 of 387) in 2015 to 10.5% (81 of 775) in 2017. The proportion of patients referred to PC who were black decreased from 11.9% (46 of 387) in 2015 to 6.3% (49 of 775) in 2017. While 69.5% of all patients with CVD (1252 of 1801) had a primary diagnosis of heart failure, the proportion of non-heart failure CVD diagnoses, such as coronary artery disease and valvular heart disease, increased from 25.6% (99 of 387) in 2015 to 30.1% (233 of 775) in 2017.

CONCLUSIONS AND RELEVANCE

Patients with CVD demonstrated significant symptom burden, and there was no evidence in the registry of change in the PPSs of patients with CVD referred to PC through time. Cardiologists provided comparatively fewer referrals to PC for patients with CVD, and this proportion decreased through time. The proportion of racial and ethnic minorities referred to PC was small and decreased through time. These findings reinforce the need for cardiologists to be more engaged with PC and consider referring appropriate patients with CVD sooner.

Implementation of Patient-Reported Outcomes in Routine Medical Care

There is increasing interest to integrate collection of patient-reported outcomes (PROs) in routine practice to enhance clinical care. Multiple studies show that systematic monitoring of patients using PROs improves patient-clinician communication, clinician awareness of symptoms, symptom management, patient satisfaction, quality of life, and overall survival. The general approach includes a brief electronic survey, administered via the Web or an app or an automated telephone system, with alerts to clinicians for concerning or worsening issues. Patients have generally been asked to self-report on a regular basis (remotely between visits and/or at visits), with reminders prompting patients to self-report that are sent via email, text, or automated phone message. More recently, care management pathways for patients and clinicians have been triggered by PRO system alerts. PRO systems may be free-standing, integrated into electronic health record systems or patient portals, or native functionality of an electronic health record. Despite potential benefits, there are challenges with integrating PROs into practice for monitoring patient status, as there are with any modifications to existing clinical processes. These challenges range from administrative to technical to workflow. A session at the 2018 ASCO Annual Meeting was dedicated to the implementation of PROs in clinical practice. The session focused on practical examples of PRO implementations, with honest reflections on barriers and strategies that may be generalizable to other systems looking to implement PROs. Panelists for that session are the authors of this paper, which describes their respective experiences implementing PROs in practice settings.

Palliation in pediatric otorhinolaryngology

Palliation in pediatric otorhinolaryngology is a rarely discussed but important aspect of care. This review encapsulates current thinking on pediatric palliative care (PC) and demonstrates, through one case, the impact of integrating PC into clinical care. We encourage early consideration of pediatric palliative care approaches for children with complex otorhinolaryngologic disorders.

Accountability for Community-Based Programs for the Seriously Ill

Innovation is needed to improve care of the seriously ill, and there are important opportunities as we transition from a volume- to value-based payment system. Not all seriously ill are dying; some recover, while others are persistently functionally impaired. While we innovate in service delivery and payment models for the seriously ill, it is important that we concurrently develop accountability that ensures a focus on high-quality care rather than narrowly focusing on cost containment. The Gordon and Betty Moore Foundation convened a meeting of 45 experts to arrive at guiding principles for measurement, create a starter measurement set, specify a proposed definition of the denominator and its refinement, and identify research priorities for future implementation of the accountability system. A series of articles written by experts provided the basis for debate and guidance in formulating a path forward to develop an accountability system for community-based programs for the seriously ill, outlined in this article. As we innovate in existing population-based payment programs such as Medicare Advantage and develop new alternative payment models, it is important and urgent that we develop the foundation for accountability along with actionable measures so that the healthcare system ensures high-quality person- and family-centered care for persons who are seriously ill.