Improving the quality of cancer care in America through health information technology

Randomized Trial of a Volunteer-Led Symptom Assessment Intervention on Documentation, Patient-Reported Outcomes, and Health Care Use Among Veterans With Lung Cancer

PURPOSE

Identification and documentation of Veterans' symptoms are crucial for optimal lung cancer care delivery. The objective of this study was to determine whether a volunteer-led proactive telephone symptom assessment intervention could improve comprehensive symptom documentation.

METHODS

Veterans with lung cancer were randomly assigned to usual care (control group) or usual care with proactive symptom assessment in which a peer volunteer made weekly phone calls to assess patient symptoms under nurse practitioner supervision. The primary outcome was oncologist documentation of symptoms in the electronic health record at all clinical visits within 6 months after enrollment. Secondary outcomes included patient satisfaction with decision, patient activation, health-related quality of life (HRQOL), and symptom burden, measured at baseline, and 3, 6, and 9 months after enrollment, and acute care use within 9 months after enrollment.

RESULTS

Among 60 Veterans randomly assigned, median (range) age was 70.2 (50-86) years; 57 (95.0%) were male. More intervention participants had oncologist documentation of symptoms than control group participants (24 [77.4%] v seven [24.1%], respectively; odds ratio, 16.46 [95% CI, 4.58 to 59.16]). Intervention group participants had greater improvements over time in HRQOL (expected mean difference, 25.3 [95% CI, 15.00 to 35.70]) and patient activation (expected mean difference, 13.6 [95% CI, 3.79 to 23.39]), lower symptom burden (expected mean difference, -6.39 [95% CI, -15.21 to -2.46]), lower rates of emergency room visits (incidence rate ratio, 0.48 [95% CI, 0.30 to 0.75]), and hospitalizations (incidence rate ratio, 0.47 [95% CI, 0.28 to 0.77]) than control group participants.

CONCLUSION

This symptom assessment intervention is an effective strategy for Veterans with lung cancer.

How can we discover the most valuable types of big data and artificial intelligence-based solutions? A methodology for the efficient development of the underlying analytics that improve care

BACKGROUND

Much has been invested in big data and artificial intelligence-based solutions for healthcare. However, few applications have been implemented in clinical practice. Early economic evaluations can help to improve decision-making by developers of analytics underlying these solutions aiming to increase the likelihood of successful implementation, but recommendations about their use are lacking. The aim of this study was to develop and apply a framework that positions best practice methods for economic evaluations alongside development of analytics, thereby enabling developers to identify barriers to success and to select analytics worth further investments.

METHODS

The framework was developed using literature, recommendations for economic evaluations and by applying the framework to use cases (chronic lymphocytic leukaemia (CLL), intensive care, diabetes). First, the feasibility of developing clinically relevant analytics was assessed and critical barriers to successful development and implementation identified. Economic evaluations were then used to determine critical thresholds and guide investment decisions.

RESULTS

When using the framework to assist decision-making of developers of analytics, continuing development was not always feasible or worthwhile. Developing analytics for progressive CLL and diabetes was clinically relevant but not feasible with the data available. Alternatively, developing analytics for newly diagnosed CLL patients was feasible but continuing development was not considered worthwhile because the high drug costs made it economically unattractive for potential users. Alternatively, in the intensive care unit, analytics reduced mortality and per-patient costs when used to identify infections (- 0.5%, - €886) and to improve patient-ventilator interaction (- 3%, - €264). Both analytics have the potential to save money but the potential benefits of analytics that identify infections strongly depend on infection rate; a higher rate implies greater cost-savings.

CONCLUSIONS

We present a framework that stimulates efficiency of development of analytics for big data and artificial intelligence-based solutions by selecting those applications of analytics for which development is feasible and worthwhile. For these applications, results from early economic evaluations can be used to guide investment decisions and identify critical requirements.

An Analysis of the Learning Health System in Its First Decade in Practice: Scoping Review

Background

In the past decade, Lynn Etheredge presented a vision for the Learning Health System (LHS) as an opportunity for increasing the value of health care via rapid learning from data and immediate translation to practice and policy. An LHS is defined in the literature as a system that seeks to continuously generate and apply evidence, innovation, quality, and value in health care.

Objective

This review aimed to examine themes in the literature and rhetoric on the LHS in the past decade to understand efforts to realize the LHS in practice and to identify gaps and opportunities to continue to take the LHS forward.

Methods

We conducted a thematic analysis in 2018 to analyze progress and opportunities over time as compared with the initial Knowledge Gaps and Uncertainties proposed in 2007.

Results

We found that the literature on the LHS has increased over the past decade, with most articles focused on theory and implementation; articles have been increasingly concerned with policy.

Conclusions

There is a need for attention to understanding the ethical and social implications of the LHS and for exploring opportunities to ensure that these implications are salient in implementation, practice, and policy efforts.

Oncologists' Views Regarding the Role of Electronic Health Records in Care Coordination

BACKGROUND

Electronic health records (EHRs) play a significant role in complex health care processes, especially in information transfer with patients and care coordination among providers. EHRs may also generate unintended consequences, introducing new patient safety risks. To date, little investigation has been performed in oncology settings, despite the need for quality provider-patient communication and information transfer during oncology visits. In this qualitative study, we focused on oncology providers' perceptions of EHRs for supporting communication with patients and coordination of care with other providers.

METHODS

We conducted semistructured interviews with oncologists from an urban academic medical center to learn their perceptions of the use of EHRs before, during, and after clinic visits with patients. Our interview guide was developed on the basis of the work system model. We coded transcripts using inductive content analysis.

RESULTS

Data analysis yielded four main themes regarding oncologists' practices in using the EHR and perceptions about EHRs: (1) EHR use for care coordination (eg, timeliness of receiving information, SmartSet documentation); (2) EHR use in the clinic visit (eg, educating patients, using as a reinforcement tool); (3) safety hazards in care coordination associated with EHRs (eg, incomplete documentation, error propagating, no filtering mechanism to capture errors); and (4) suggestions for improvements (eg, improved SmartSet functionalities, simplification of user interface).

CONCLUSION

Current EHRs do not adequately support teamwork of oncology providers, which could lead to potential hazards in the care of patients with cancer. Redesigning EHR features that are tailored to support oncology care and addressing the concerns regarding information overload, improved organization of flagging abnormal results, and documentation-related workload are needed to minimize potential safety hazards.

A framework for analysing learning health systems: Are we removing the most impactful barriers?

INTRODUCTION

Learning health systems (LHS) are one of the major computing advances in health care. However, no prior research has systematically analysed barriers and facilitators for LHS. This paper presents an investigation into the barriers, benefits, and facilitating factors for LHS in order to create a basis for their successful implementation and adoption.

METHODS

First, the ITPOSMO-BBF framework was developed based on the established ITPOSMO (information, technology, processes, objectives, staffing, management, and other factors) framework, extending it for analysing barriers, benefits, and facilitators. Second, the new framework was applied to LHS.

RESULTS

We found that LHS shares similar barriers and facilitators with electronic health records (EHR); in particular, most facilitator effort in implementing EHR and LHS goes towards barriers categorised as human factors, even though they were seen to carry fewer benefits. Barriers whose resolution would bring significant benefits in safety, quality, and health outcomes remain.LHS envisage constant generation of new clinical knowledge and practice based on the central role of collections of EHR. Once LHS are constructed and operational, they trigger new data streams into the EHR. So LHS and EHR have a symbiotic relationship. The implementation and adoption of EHRs have proved and continues to prove challenging, and there are many lessons for LHS arising from these challenges.

CONCLUSIONS

Successful adoption of LHS should take account of the framework proposed in this paper, especially with respect to its focus on removing barriers that have the most impact.

The Heimdall Framework for Supporting Characterisation of Learning Health Systems

BACKGROUND

Learning Health Systems (LHS) can focus population medicine and Evidence Based Practice; smart technology delivering the next generation of improved healthcare described as Precision Medicine, and yet researchers in the LHS domain presently lack the ability to recognise their relevant works as falling within this domain.

OBJECTIVE

To review LHS literature and develop a framework describing the domain that can be used as a tool to analyse the literature and support researchers to identify health informatics investigations as falling with the domain of LHS.

METHOD

A scoping review is used to identify literature on which analysis was performed. This resolved the ontology and framework. The ontology was applied to quantify the distribution of classifications of LHS solutions. The framework was used to analyse and characterise the various works within the body of LHS literature.

RESULTS

The ontology and framework developed was shown to be easily applicable to the literature, consistently describing and representing the goals, intentions and solutions of each LHS investigation in the literature. More proposed or potential solutions are described in the literature than implemented LHS. This suggests immaturity in the domain and points to the existence of barriers preventing LHS realisation.

CONCLUSION

The lack of an ontology and framework may have been one of the causes for the failure to describe research works as falling within the LHS domain. Using our ontology and framework, LHS research works could be easily classified, demonstrating the comprehensiveness of our approach in contrast to earlier efforts.

'Because I Don't know': uncertainty and ambiguity in closed-ended reports of perceived discrimination in US health care

Objective Surveys often ask respondents to assess discrimination in health care. Yet, patients' responses to one type of widely used measure of discrimination (single-item, personally mediated) tend to reveal prevalence rates lower than observational studies would suggest. This study examines the meaning behind respondents' closed-ended self-reports on this specific type of measure, paying special attention to the frameworks and references used within the medical setting. Design Twenty-nine respondents participated in this study. They were asked the widely used question: 'Within the past 12 months, when seeking health care do you feel your experiences were worse than, the same as, or better than people of other races?' We then conducted qualitative interviews focusing on their chosen response and past experiences. Descriptive analyses focus on both the quantitative and qualitative data, including a comparison of conveyed perceived discrimination according to the different sources of data. Results To identify discrimination, respondents drew upon observations of dynamics in the waiting room or the health providers' communication style. Our respondents were frequently ambivalent and uncertain about how their personal treatment in health care compared to people of other races. When participants were unable to make observable comparisons, they tended to assume equal treatment and report 'same as' in the close-ended reports. Conclusion Respondents' responses to single-item, closed-ended questions may be influenced by characteristics specific to the health care realm. An emphasis on privacy and assumptions about the health care field (both authority and benevolence of providers) may limit opportunities for comparison and result in assumptions of racial parity in treatment.

How do organisational characteristics influence teamwork and service delivery in lung cancer diagnostic assessment programmes? A mixed-methods study

OBJECTIVES

Diagnostic assessment programmes (DAPs) can reduce wait times for cancer diagnosis, but optimal DAP design is unknown. This study explored how organisational characteristics influenced multidisciplinary teamwork and diagnostic service delivery in lung cancer DAPs.

DESIGN

A mixed-methods approach integrated data from descriptive qualitative interviews and medical record abstraction at 4 lung cancer DAPs. Findings were analysed with the Integrated Team Effectiveness Model.

SETTING

4 DAPs at 2 teaching and 2 community hospitals in Canada.

PARTICIPANTS

22 staff were interviewed about organisational characteristics, target service benchmarks, and teamwork processes, determinants and outcomes; 314 medical records were reviewed for actual service benchmarks.

RESULTS

Formal, informal and asynchronous team processes enabled service delivery and yielded many perceived benefits at the patient, staff and service levels. However, several DAP characteristics challenged teamwork and service delivery: referral volume/workload, time since launch, days per week of operation, rural-remote population, number and type of full-time/part-time human resources, staff colocation, information systems. As a result, all sites failed to meet target benchmarks (from referral to consultation median 4.0 visits, median wait time 35.0 days). Recommendations included improved information systems, more staff in all specialties, staff colocation and expanded roles for patient navigators. Findings were captured in a conceptual framework of lung cancer DAP teamwork determinants and outcomes.

CONCLUSIONS

This study identified several DAP characteristics that could be improved to facilitate teamwork and enhance service delivery, thereby contributing to knowledge of organisational determinants of teamwork and associated outcomes. Findings can be used to update existing DAP guidelines, and by managers to plan or evaluate lung cancer DAPs. Ongoing research is needed to identify ideal roles for navigators, and staffing models tailored to case volumes.

Cancer Prevention in the Survivorship Setting

OBJECTIVES

To describe how nurses can use risk reduction and health promotion activities to facilitate surveillance of late effects and secondary cancers in long-term cancer survivors.

DATA SOURCES

Literature review on survivorship, nursing practice, cancer prevention, and survivorship; articles published in peer-reviewed scientific journals; and Web-based or professional organization resources.

CONCLUSION

Appropriate participation in screening activities, early detection of cancer, and further advances in treatment have contributed to the rise in cancer survivors. A demand for nurses with clinical experience and competence in survivorship care will follow.

IMPLICATIONS FOR NURSING PRACTICE

Oncology nurses have an essential role in providing safe and high-quality care throughout the survivorship experience, which can contribute to better long-term outcomes.

The influence of health-specific social network site use on the psychological well-being of cancer-affected people

OBJECTIVE

We aimed to explore and examine how and in what ways the use of social network sites (SNSs) can improve health outcomes, specifically better psychological well-being, for cancer-affected people.

METHODS

Qualitative semi-structured interviews were conducted with users of the Ovarian Cancer Australia Facebook page (OCA Facebook), the exemplar SNS used in this study. Twenty-five women affected by ovarian cancer who were users of OCA Facebook were interviewed. A multi-theory perspective was employed to interpret the data.

RESULTS

Most of the study participants used OCA Facebook daily. Some users were passive and only observed created content, while other users actively posted content and communicated with other members. Analysis showed that the use of this SNS enhanced social support for users, improved the users' experiences of social connectedness, and helped users learn and develop social presence, which ultimately improved their psychological well-being.

DISCUSSION

The strong theoretical underpinning of our research and empirically derived results led to a new understanding of the capacity of SNSs to improve psychological well-being. Our study provides evidence showing how the integration of these tools into existing health services can enhance patients' psychological well-being. This study also contributes to the body of knowledge on the implications of SNS use for improving the psychological well-being of cancer-affected people.

CONCLUSION

This research assessed the relationship between the use of SNSs, specifically OCA Facebook, and the psychological well-being of cancer-affected people. The study confirmed that using OCA Facebook can improve psychological well-being by demonstrating the potential value of SNSs as a support service in the healthcare industry.

Integrating Patient-Reported Outcome Measures into Routine Cancer Care: Cancer Patients' and Clinicians' Perceptions of Acceptability and Value

INTRODUCTION

Despite growing interest in integrating patient-reported outcome (PRO) measures of symptoms and functional status into routine cancer care, little attention has been paid to patients' and clinicians' perceptions of acceptability and value.

METHODS

A two-phase qualitative study was conducted to develop a web-based PRO screening system with 21 items assessing symptoms (e.g., nausea) and functional status. Phase 1 involved cognitive interviews with 35 cancer outpatients (n=9 breast chemotherapy, radiation for prostate (n=8) or head and neck cancer (n=10), and n=8 bone marrow transplant [BMT]). In Phase 2, we evaluated the acceptability and perceived value of reviewing a PRO measure during real-time clinical encounters with 39 additional outpatients (n=10 breast, n=9 head and neck, n=10 prostate, n=10 BMT) and 12 clinicians (n=3 breast, n=2 head and neck, n=4 prostate, n=3 BMT). At least 20% of patients were ≥60 years, African American, or ≤ high school.

RESULTS

Patients felt that their PRO summary of symptoms and functional status was helpful in discussing health issues with clinicians (92%), wanted to review their results with clinicians during future visits (82%), and would recommend it to other patients (87%). Clinicians found the PRO summary to be easy to interpret (83%), most helpful for documenting the Review of Symptoms (92%), and would recommend it to future patients (92%). Over 90% of clinicians reported that consultation time did not increase.

CONCLUSION

Both cancer patients and clinicians reported that discussing a PRO summary of symptoms and functional status during an outpatient visit was useful, acceptable, and feasible.

An integrated, ontology-driven approach to constructing observational databases for research

The electronic health record (EHR) contains a diverse set of clinical observations that are captured as part of routine care, but the incomplete, inconsistent, and sometimes incorrect nature of clinical data poses significant impediments for its secondary use in retrospective studies or comparative effectiveness research. In this work, we describe an ontology-driven approach for extracting and analyzing data from the patient record in a longitudinal and continuous manner. We demonstrate how the ontology helps enforce consistent data representation, integrates phenotypes generated through analyses of available clinical data sources, and facilitates subsequent studies to identify clinical predictors for an outcome of interest. Development and evaluation of our approach are described in the context of studying factors that influence intracranial aneurysm (ICA) growth and rupture. We report our experiences in capturing information on 78 individuals with a total of 120 aneurysms. Two example applications related to assessing the relationship between aneurysm size, growth, gene expression modules, and rupture are described. Our work highlights the challenges with respect to data quality, workflow, and analysis of data and its implications toward a learning health system paradigm.