Patient-powered research networks aim to improve patient care and health research

Public Involvement and Engagement in Big Data Research: Scoping Review

BACKGROUND

The success of big data initiatives depends on public support. Public involvement and engagement could be a way of establishing public support for big data research.

OBJECTIVE

This review aims to synthesize the evidence on public involvement and engagement in big data research.

METHODS

This scoping review mapped the current evidence on public involvement and engagement activities in big data research. We searched 5 electronic databases, followed by additional manual searches of Google Scholar and gray literature. In total, 2 public contributors were involved at all stages of the review.

RESULTS

A total of 53 papers were included in the scoping review. The review showed the ways in which the public could be involved and engaged in big data research. The papers discussed a broad range of involvement activities, who could be involved or engaged, and the importance of the context in which public involvement and engagement occur. The findings show how public involvement, engagement, and consultation could be delivered in big data research. Furthermore, the review provides examples of potential outcomes that were produced by involving and engaging the public in big data research.

CONCLUSIONS

This review provides an overview of the current evidence on public involvement and engagement in big data research. While the evidence is mostly derived from discussion papers, it is still valuable in illustrating how public involvement and engagement in big data research can be implemented and what outcomes they may yield. Further research and evaluation of public involvement and engagement in big data research are needed to better understand how to effectively involve and engage the public in big data research.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-https://doi.org/10.1136/bmjopen-2021-050167.

Towards conceptualizing patients as partners in health systems: a systematic review and descriptive synthesis

BACKGROUND

With the sharp increase in the involvement of patients (including family and informal caregivers) as active participants, collaborators, advisors and decision-makers in health systems, a new role has emerged: the patient partner. The role of patient partner differs from other forms of patient engagement in its longitudinal and bidirectional nature. This systematic review describes extant work on how patient partners are conceptualized and engaged in health systems. In doing so, it furthers the understanding of the role and activities of patient partners, and best practices for future patient partnership activities.

METHODS

A systematic review was conducted of peer-reviewed literature published in English or French that describes patient partner roles between 2000 and 2021 in any country or sector of the health system. We used a broad search strategy to capture descriptions of longitudinal patient engagement that may not have used words such as "partner" or "advisor".

RESULTS

A total of 506 eligible papers were identified, representing patient partnership activities in mostly high-income countries. These studies overwhelmingly described patient partnership in health research. We identified clusters of literature about patient partnership in cancer and mental health. The literature is saturated with single-site descriptive studies of patient partnership on individual projects or initiatives. There is a lack of work synthesizing impacts, facilitating factors and outcomes of patient partnership in healthcare.

CONCLUSIONS

There is not yet a consolidated understanding of the role, activities or impacts of patient partners. Advancement of the literature has been stymied by a lack of consistently used terminology. The literature is ready to move beyond single-site descriptions, and synthesis of existing pockets of high-quality theoretical work will be essential to this evolution.

AGREEMENT BETWEEN UDD APPTM & PROVIDER EVALUATION OF ESOPHAGECTOMY SYMPTOMS IN A MOBILE APP TOOL

BACKGROUND

The objective of this study was to assess the criterion validity of score thresholds for Upper Digestive Disease (UDD) App^TM.

METHODS

From 12/15/2017-12/15/2020, patients presenting after esophagectomy were offered the UDD App^TM concurrent with a provider visit. This tool consists of 67 questions including five novel domains. Score thresholds were used to classify patient as good, moderate, or poor based on domain scores. Providers were given performance descriptions for each domain and asked to classify patients based on their clinical evaluation. The weighted kappa statistic was used to determine the magnitude of agreement between classifications based on the patients' UDD App^TM scores and providers' clinical evaluation.

RESULTS

Fifty-nine patients in the study (76% male), median age 63 [IQR 57, 72] reported outcomes utilizing the UDD app. Providers reviewed between 1-10 patients at a median time of 296.5 days [IQR 50, 975] post-esophagectomy. The magnitude of agreement between patients and providers was moderate for dysphagia (κ= 0.52, p<0.001) and reflux (κ= 0.42, p<0.001). Dumping-related hypoglycemia (κ= 0.03, p=0.148), gastrointestinal complaints (κ= 0.02, p=0.256) and pain (κ= 0.05, p<0.184), showed minimal agreement, with providers underestimating the symptoms and problems reported by patients in these domains.

CONCLUSIONS

Although there was agreement between UDD App^TM assessment and provider evaluation of dysphagia and reflux following esophagectomy, there was discordance of scoring for dumping-related symptoms and pain. Future research is needed to determine whether thresholds for pain and dumping domains need to be revised and/or whether additional provider education on performance descriptions is needed.

A Guide to Selecting Participatory Research Methods Based on Project and Partnership Goals

Participatory research engages community stakeholders in the research process, from problem identification and developing the research question, to dissemination of results. There is increasing recognition in the field of health research that community-engaged methods can be used throughout the research process. The volume of guidance for engaging communities and conducting participatory research has grown steadily in the past 40+ years, in many countries and contexts. Further, some institutions now require stakeholder engagement in research as a condition of funding. Interest in collaborating in the research process is also growing among patients and the public. This article provides an overview for selecting participatory research methods based on project and partnerships goals.

Patient Education and Engagement through Social Media

This review addresses the demographics of social media users and their relative health literacy. Means of overcoming health inequities via social media and the role of social media in patient education and engagement are explored. This review discusses forms of appropriate patient engagement, including the pitfalls of social media use.

Patient-Powered Research Networks of the Autoimmune Research Collaborative: Rationale, Capacity, and Future Directions

Patient-Powered Research Networks (PPRNs) are US-based registry infrastructures co-created by advocacy groups, patient research partners, academic investigators, and other healthcare stakeholders. Patient-Powered Research Networks collect information directly from patients to conduct and disseminate the results of patient-centered/powered research that helps patients make more informed decisions about their healthcare. Patient-Powered Research Networks gather and utilize real-world data and patient-reported outcomes to conduct comparative effectiveness, safety, and other research, and leverage the Internet to accomplish this effectively and efficiently. Four PPRNs focused on autoimmune and immune-mediated conditions formed the Autoimmune Research Collaborative: ArthritisPower (rheumatoid arthritis, spondyloarthritis, and other rheumatic and musculoskeletal diseases), IBD Partners (inflammatory bowel disease), iConquerMS (multiple sclerosis), and the Vasculitis PPRN (vasculitis). The Autoimmune Research Collaborative aims to inform the healthcare decision making of patients, care partners, and other stakeholders, such as clinicians, regulators, and payers. Illustrated by practical applications from the Autoimmune Research Collaborative and its constituent PPRNs, this article discusses the shared capacities and challenges of the PPRN model, and the opportunities presented by collaborating across autoimmune conditions to design, conduct, and disseminate patient-centered outcomes research.

Integrating Stakeholder Engagement With Claims-Based Research on Health Insurance Design and Bipolar Disorder

Researchers increasingly recognize that stakeholder involvement enhances research relevance and validity. However, reports of patient engagement in research that relies on administrative records data are rare. The authors' collaborative project combined quantitative and qualitative studies of costs and access to care among U.S. adults with employer-sponsored insurance. The authors analyzed insurance claims to estimate the impacts on enrollee costs and utilization after patients with bipolar disorder were switched from traditional coverage to high-deductible health plans. In parallel, in-depth interviews explored people's experiences accessing treatment for bipolar disorder. Academic investigators on the research team partnered with the Depression and Bipolar Support Alliance (DBSA), a national advocacy organization for people with mood disorders. Detailed personal stories from DBSA-recruited volunteers informed and complemented the claims analyses. Several DBSA audience forums and a stakeholder advisor panel contributed regular feedback on study issues. These multiple engagement modes drew inputs of varying intensity from diverse community segments. Efforts to include new voices must acknowledge individuals' distinct interests and barriers to research participation. Strong engagement leadership roles ensure productive communication between researchers and stakeholders. The involvement of people with direct experience of care is especially necessary in research that uses secondary data. Longitudinal, adaptable partnerships enable colearning and higher-quality research that captures the manifold dimensions of patient experiences.

Developments in evidence creation for treatments of inborn errors of metabolism

Inborn errors of metabolism (IEM) represent the first group of genetic disorders, amenable to causal therapies. In addition to traditional medical diet and cofactor treatments, new treatment strategies such as enzyme replacement and small molecule therapies, solid organ transplantation, and cell-and gene-based therapies have become available. Inherent to the rare nature of the single conditions, generating high-quality evidence for these treatments in clinical trials and under real-world conditions has been challenging. Guidelines developed with standardized methodologies have contributed to improve the practice of care and long-term clinical outcomes. Adaptive trial designs allow for changes in sample size, group allocation and trial duration as the trial proceeds. n-of-1 studies may be used in small sample sized when participants are clinically heterogeneous. Multicenter observational and registry-based clinical trials are promoted via international research networks. Core outcome and standard data element sets will enhance comparative analysis of clinical trials and observational studies. Patient-centered outcome-research as well as patient-led research initiatives will further accelerate the development of therapies for IEM.

Data linkages between patient-powered research networks and health plans: a foundation for collaborative research

OBJECTIVE

Patient-powered research networks (PPRNs) are a valuable source of patient-generated information. Diagnosis code-based algorithms developed by PPRNs can be used to query health plans' claims data to identify patients for research opportunities. Our objective was to implement privacy-preserving record linkage processes between PPRN members' and health plan enrollees' data, compare linked and nonlinked members, and measure disease-specific confirmation rates for specific health conditions.

MATERIALS AND METHODS

This descriptive study identified overlapping members from 4 PPRN registries and 14 health plans. Our methods for the anonymous linkage of overlapping members used secure Health Insurance Portability and Accountability Act-compliant, 1-way, cryptographic hash functions. Self-reported diagnoses by PPRN members were compared with claims-based computable phenotypes to calculate confirmation rates across varying durations of health plan coverage.

RESULTS

Data for 21 616 PPRN members were hashed. Of these, 4487 (21%) members were linked, regardless of any expected overlap with the health plans. Linked members were more likely to be female and younger than nonlinked members were. Irrespective of duration of enrollment, the confirmation rates for the breast or ovarian cancer, rheumatoid or psoriatic arthritis or psoriasis, multiple sclerosis, or vasculitis PPRNs were 72%, 50%, 75%, and 67%, increasing to 91%, 67%, 93%, and 80%, respectively, for members with ≥5 years of continuous health plan enrollment.

CONCLUSIONS

This study demonstrated that PPRN membership and health plan data can be successfully linked using privacy-preserving record linkage methodology, and used to confirm self-reported diagnosis. Identifying and confirming self-reported diagnosis of members can expedite patient selection for research opportunities, shorten study recruitment timelines, and optimize costs.

Landscape of Participant-Centric Initiatives for Medical Research in the United States, the United Kingdom, and Japan: Scoping Review

BACKGROUND

Information and communication technology (ICT) has made remarkable progress in recent years and is being increasingly applied to medical research. This technology has the potential to facilitate the active involvement of research participants. Digital platforms that enable participants to be involved in the research process are called participant-centric initiatives (PCIs). Several PCIs have been reported in the literature, but no scoping reviews have been carried out. Moreover, detailed methods and features to aid in developing a clear definition of PCIs have not been sufficiently elucidated to date.

OBJECTIVE

The objective of this scoping review is to describe the recent trends in, and features of, PCIs across the United States, the United Kingdom, and Japan.

METHODS

We applied a methodology suggested by Levac et al to conduct this scoping review. We searched electronic databases-MEDLINE (Medical Literature Analysis and Retrieval System Online), Embase (Excerpta Medica Database), CINAHL (Cumulative Index of Nursing and Allied Health Literature), PsycINFO, and Ichushi-Web-and sources of grey literature, as well as internet search engines-Google and Bing. We hand-searched through key journals and reference lists of the relevant articles. Medical research using ICT was eligible for inclusion if there was a description of the active involvement of the participants.

RESULTS

Ultimately, 21 PCIs were identified that have implemented practical methods and modes of various communication activities, such as patient forums and use of social media, in the field of medical research. Various methods of decision making that enable participants to become involved in setting the agenda were also evident.

CONCLUSIONS

This scoping review is the first study to analyze the detailed features of PCIs and how they are being implemented. By clarifying the modes and methods of various forms of communication and decision making with patients, this review contributes to a better understanding of patient-centric involvement, which can be facilitated by PCIs.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/resprot.7407.

Harnessing health plan enrollee data to boost membership in patient-powered research networks

BACKGROUND

Patient-powered research networks (PPRNs) have been employing and exploring different methods to engage patients in research activities specific to their conditions. One way to intensify patient engagement is to partner with payer stakeholders. The objective of this study was to evaluate the effectiveness of two common payer-initiated outreach methods (postal mail versus email) for inviting prospective candidates to participate in their initiatives.

METHODS

This descriptive study linked members of a nationally-representative private insurance network to four disease-specific PPRN registries. Eligible members meeting diagnostic criteria who were not registered in any of the four PPRNs by 02/28/2018 were identified, and randomly assigned to either the mail or email group. They were contacted in two outreach efforts: first on 04/23/2018, and one follow-up on 05/23/2018. New registration rates by outreach method as of 8/31/2018 were determined by relinking. We compared registrants and non-registrants using bivariate analysis.

RESULTS

A total of 14,571 patients were assigned to the mail group, and 14,574 to the email group. Invitations were successfully delivered to 13,834 (94.9%) mail group and 10,205 (70.0%) email group members. A small but significantly larger proportion of mail group members, (n = 78; 0.54, 95% Confidence Interval [CI] {0.42-0.67%}) registered in PPRNs relative to the email group (n = 24; 0.16, 95% CI {0.11-0.25%}), p < 0.001. Members who registered had more comorbidities, were more likely to be female, and had marginally greater medical utilization, especially emergency room visits, relative to non-registrants (52.0% vs. 42.5%, p = 0.05).

CONCLUSION

A health plan outreach to invite members to participate in PPRNs was modestly effective. Regular mail outperformed less costly email. Providing more value-add to participants may be a possible way to increase recruitment success.

Digital Interventions to Build a Patient Registry for Rheumatology Research

This article aims to describe key issues, processes, and outcomes related to development of a patient registry for rheumatology research using a digital platform where patients track useful data about their condition for their own use while contributing to research. Digital interventions are effective to build a patient research registry for people with rheumatoid arthritis and other rheumatic and musculoskeletal diseases. ArthritisPower provides evidence of the value of digital interventions to build community support for research and to transform patient engagement and patient-generated data capture.

Interdisciplinary Models for Research and Clinical Endeavors in Genomic Medicine: A Scientific Statement From the American Heart Association

The completion of the Human Genome Project has unleashed a wealth of human genomics information, but it remains unclear how best to implement this information for the benefit of patients. The standard approach of biomedical research, with researchers pursuing advances in knowledge in the laboratory and, separately, clinicians translating research findings into the clinic as much as decades later, will need to give way to new interdisciplinary models for research in genomic medicine. These models should include scientists and clinicians actively working as teams to study patients and populations recruited in clinical settings and communities to make genomics discoveries-through the combined efforts of data scientists, clinical researchers, epidemiologists, and basic scientists-and to rapidly apply these discoveries in the clinic for the prediction, prevention, diagnosis, prognosis, and treatment of cardiovascular diseases and stroke. The highly publicized US Precision Medicine Initiative, also known as All of Us, is a large-scale program funded by the US National Institutes of Health that will energize these efforts, but several ongoing studies such as the UK Biobank Initiative; the Million Veteran Program; the Electronic Medical Records and Genomics Network; the Kaiser Permanente Research Program on Genes, Environment and Health; and the DiscovEHR collaboration are already providing exemplary models of this kind of interdisciplinary work. In this statement, we outline the opportunities and challenges in broadly implementing new interdisciplinary models in academic medical centers and community settings and bringing the promise of genomics to fruition.

Current status of use of big data and artificial intelligence in RMDs: a systematic literature review informing EULAR recommendations

Objective

To assess the current use of big data and artificial intelligence (AI) in the field of rheumatic and musculoskeletal diseases (RMDs).

Methods

A systematic literature review was performed in PubMed MEDLINE in November 2018, with key words referring to big data, AI and RMDs. All original reports published in English were analysed. A mirror literature review was also performed outside of RMDs on the same number of articles. The number of data analysed, data sources and statistical methods used (traditional statistics, AI or both) were collected. The analysis compared findings within and beyond the field of RMDs.

Results

Of 567 articles relating to RMDs, 55 met the inclusion criteria and were analysed, as well as 55 articles in other medical fields. The mean number of data points was 746 million (range 2000–5 billion) in RMDs, and 9.1 billion (range 100 000–200 billion) outside of RMDs. Data sources were varied: in RMDs, 26 (47%) were clinical, 8 (15%) biological and 16 (29%) radiological. Both traditional and AI methods were used to analyse big data (respectively, 10 (18%) and 45 (82%) in RMDs and 8 (15%) and 47 (85%) out of RMDs). Machine learning represented 97% of AI methods in RMDs and among these methods, the most represented was artificial neural network (20/44 articles in RMDs).

Conclusions

Big data sources and types are varied within the field of RMDs, and methods used to analyse big data were heterogeneous. These findings will inform a European League Against Rheumatism taskforce on big data in RMDs.

Consumer-Mediated Data Exchange for Research: Current State of US Law, Technology, and Trust

A compendium of US laws and regulations offers increasingly strong support for the concept that researchers can acquire the electronic health record data that their studies need directly from the study participants using technologies and processes called consumer-mediated data exchange. This data acquisition method is particularly valuable for studies that need complete longitudinal electronic records for all their study participants who individually and collectively receive care from multiple providers in the United States. In such studies, it is logistically infeasible for the researcher to receive necessary data directly from each provider, including providers who may not have the capability, capacity, or interest in supporting research. This paper is a tutorial to inform the researcher who faces these data acquisition challenges about the opportunities offered by consumer-mediated data exchange. It outlines 2 approaches and reviews the current state of provider- and consumer-facing technologies that are necessary to support each approach. For one approach, the technology is developed and estimated to be widely available but could raise trust concerns among research organizations or their institutional review boards because of the current state of US law applicable to consumer-facing technologies. For the other approach, which does not elicit the same trust concerns, the necessary technology is emerging and a pilot is underway. After reading this paper, the researcher who has not been following these developments should have a good understanding of the legal, regulatory, technology, and trust issues surrounding consumer-mediated data exchange for research, with an awareness of what is potentially possible now, what is not possible now, and what could change in the future. The researcher interested in trying consumer-mediated data exchange will also be able to anticipate and respond to an anticipated barrier: the trust concerns that their own organizations could raise.

Building Meaningful Patient Engagement in Research: Case Study From ADVANCE Clinical Data Research Network

BACKGROUND

Strategies to engage patients to improve and enhance research and clinical care are increasingly being implemented in the United States, yet little is known about best practices for or the impacts of meaningful patient engagement.

OBJECTIVE

We describe and reflect on our patient stakeholder groups, engagement framework, experiences, and lessons learned in engaging patients in research, from generating proposal ideas to disseminating findings.

SETTING

The ADVANCE (Accelerating Data Value Across a National Community Health Center Network) clinical data research network is the nation's largest clinical dataset on the safety net, with outpatient clinical data from 122 health systems (1109 clinics) in 23 states.

RESULTS

Patients stakeholders codeveloped the ADVANCE engagement framework and its implementation in partnership with network leaders. In phase I of ADVANCE, patients were involved with designing studies (input on primary outcome measures and methods) and usability testing (of the patient portal). In phase II, the network is prioritizing research training, dissemination opportunities, an "ambassador" program to pair more experienced patient stakeholders with those less experienced, and evaluation of engagement activities and impacts.

DISCUSSION

The ADVANCE framework for patient engagement has successfully involved a diverse group of patients in the design, implementation, and interpretation of comparative effectiveness research. Our experience and framework can be used by other organizations and research networks to support patient engagement activities.

Removing the Mask of Average Treatment Effects in Chronic Lyme Disease Research Using Big Data and Subgroup Analysis

Lyme disease is caused by the bacteria borrelia burgdorferi and is spread primarily through the bite of a tick. There is considerable uncertainty in the medical community regarding the best approach to treating patients with Lyme disease who do not respond fully to short-term antibiotic therapy. These patients have persistent Lyme disease symptoms resulting from lack of treatment, under-treatment, or lack of response to their antibiotic treatment protocol. In the past, treatment trials have used small restrictive samples and relied on average treatment effects as their measure of success and produced conflicting results. To provide individualized care, clinicians need information that reflects their patient population. Today, we have the ability to analyze large data bases, including patient registries, that reflect the broader range of patients more typically seen in clinical practice. This allows us to examine treatment variation within the sample and identify groups of patients that are most responsive to treatment. Using patient-reported outcome data from the MyLymeData online patient registry, we show that sub-group analysis techniques can unmask valuable information that is hidden if averages alone are used. In our analysis, this approach revealed treatment effectiveness for up to a third of patients with Lyme disease. This study is important because it can help open the door to more individualized patient care using patient-centered outcomes and real-world evidence.

Crohn's and Colitis Foundation of America Partners Patient-Powered Research Network: Patient Perspectives on Facilitators and Barriers to Building an Impactful Patient-Powered Research Network

BACKGROUND

To build a Patient-Powered Research Networks (PPRN) that prioritizes the needs of its members who have inflammatory bowel diseases (IBD), we sought to better understand patients' preferences for what are the essential features that will facilitate and sustain engagement.

METHODS

We conducted a two-phase qualitative study. Seven focus groups involving 62 participants with IBD were conducted (phase 1). Focus group results informed the phase 2 cognitive interviews, which included 13 phone interviews. Topics included experiences with IBD and research, PPRN engagement, patient-generated health data, and resources/tools to facilitate self-management. All focus groups and interviews were digitally recorded, transcribed verbatim, and analyzed in ATLAS.ti 7.5. Thematic categories were derived from the data, and codes were grouped into emergent themes and relationships.

RESULTS

Four major themes emerged through inductive coding: (1) the impact of knowing; (2) participation barriers and challenges; (3) engagement and collaboration; and (4) customizable patient portal features/functionalities. Participants were motivated to participate in the PPRN because the knowledge gained from research studies would benefit both society and the individual. Main concerns included credibility of online resources, pharmaceutical industry profiting from their data, data security, and participation expectations. Participants wanted a true and equal partnership in every phase of building a PPRN. Participants felt it was important to have access to personal health records and be able to track health status and symptoms.

CONCLUSION

Partnering with participants throughout PPRN development was critical to understanding the needs and preferences of patients with IBDs and for shaping engagement strategies and the portal's design.

Phelan-McDermid syndrome data network: Integrating patient reported outcomes with clinical notes and curated genetic reports

The heterogeneity of patient phenotype data are an impediment to the research into the origins and progression of neuropsychiatric disorders. This difficulty is compounded in the case of rare disorders such as Phelan-McDermid Syndrome (PMS) by the paucity of patient clinical data. PMS is a rare syndromic genetic cause of autism and intellectual deficiency. In this paper, we describe the Phelan-McDermid Syndrome Data Network (PMS_DN), a platform that facilitates research into phenotype-genotype correlation and progression of PMS by: a) integrating knowledge of patient phenotypes extracted from Patient Reported Outcomes (PRO) data and clinical notes-two heterogeneous, underutilized sources of knowledge about patient phenotypes-with curated genetic information from the same patient cohort and b) making this integrated knowledge, along with a suite of statistical tools, available free of charge to authorized investigators on a Web portal https://pmsdn.hms.harvard.edu. PMS_DN is a Patient Centric Outcomes Research Initiative (PCORI) where patients and their families are involved in all aspects of the management of patient data in driving research into PMS. To foster collaborative research, PMS_DN also makes patient aggregates from this knowledge available to authorized investigators using distributed research networks such as the PCORnet PopMedNet. PMS_DN is hosted on a scalable cloud based environment and complies with all patient data privacy regulations. As of October 31, 2016, PMS_DN integrates high-quality knowledge extracted from the clinical notes of 112 patients and curated genetic reports of 176 patients with preprocessed PRO data from 415 patients.

Applying a community-based participatory research framework to patient and family engagement in the development of patient-centered outcomes research and practice

There has been increasing recognition of the need to engage patients, families, and other patient stakeholders in research. This article seeks to provide understanding and examples of how to apply core principles of community-based participatory research (CBPR) in developing patient-centered outcomes research (PCOR) that can impact clinical and public health practice. Authors review CBPR principles and demonstrate how to translate them into effective PCOR strategies. Common themes of CBPR principles and PCOR strategies are related to: (a) fostering joint ownership in the identification of health priorities, the development and evaluation of research strategies and their design, and the dissemination of findings; (b) a keen recognition and appreciation for the importance of stakeholder-driven priorities, research, and solutions; (c) building capacity of both stakeholders and researchers to engage in research collaboratively; and (d) recognizing that conducting the research is not the endpoint but continues on with a commitment to dissemination, spread, adoption and sustainability. The authors highlight the specific strategies in which these CBPR principles can be translated for use in engaging patients and families, and including other stakeholders such as care providers, community partner organizations, health systems, and insurers, in the research process to ensure the development of PCOR.

The Community and Patient Partnered Research Network (CPPRN): Application of Patient-Centered Outcomes Research to Promote Behavioral Health Equity

Objective

We describe the rationale, development, and progress on the Community and Patient Partnered Research Network (CPPRN). The CPPRN builds on more than a decade of partnered work and is designed to promote health equity by developing partnered research on behavioral health and social risk factors in Los Angeles and New Orleans.

Setting

A community-academic partnership across Los Angeles County and New Orleans.

Methods

Review of rationale, history, structure, activities and progress in applying community partnered participatory research (CPPR) to CPPRN.

Findings

Patient and community stakeholders participated in all phases of development, including local and national activities. Key developments include partnered planning efforts, progress on aggregating a large, de-identified dataset across county agencies, and development of an information technology-supported screening approach for behavioral and social determinants in health care, social, and community-based settings.

Conclusion

The CPPRN represents a promising approach for research data networks, balancing the potential benefit of information technology and data analytic approaches while addressing potential risks and priorities of relevant stakeholders.

Defining Future Research Priorities in Donation and Organ and Stem Cell Transplantation With Patients, Families, Caregivers, Healthcare Providers and Researchers Within the Canadian National Transplant Research Program

Supplemental digital content is available in the text.

Background

Patients, families, and caregivers have a unique understanding of the diseases they live with and provide care for every day. Their experience and expertise are important and should be taken into consideration when determining research priorities. The aim of this study was to gather the perspectives of Canadian patients, families, caregivers, researchers, and healthcare professionals on what research priorities were important to them in the field of organ and hematopoietic cell transplantation (HCT) and donation within the Canadian National Transplant Research Program (CNTRP).

Methods

The CNTRP developed a national consultation process, which included a Web-based survey and in-person workshop, to ascertain and validate the viewpoints of the Canadian donation and transplant community. The Web-based survey identified 3 principal research priorities (increasing donation, developing better antirejection drugs and developing tolerance), which were further refined and prioritized during the one-and-a-half day national workshop held in Toronto in November 2015.

Results

A total of 505 participants answered the Web-based survey, and 46 participants (28 patients, 12 researchers and 6 healthcare professionals) participated in the in-person workshop. Workshop participants ranked the following 2 priorities as the most important in the fields of donation, HCT, and solid organ transplantation: methods for developing a culture of donation (within healthcare organizations and throughout society); and methods for improving graft survival and antirejection therapy.

Conclusion

The CNTRP will use these results to prioritize future research projects and studies in donation, HCT, and solid organ transplantation in the years to come.

Possible Sources of Bias in Primary Care Electronic Health Record Data Use and Reuse

BACKGROUND

Enormous amounts of data are recorded routinely in health care as part of the care process, primarily for managing individual patient care. There are significant opportunities to use these data for other purposes, many of which would contribute to establishing a learning health system. This is particularly true for data recorded in primary care settings, as in many countries, these are the first place patients turn to for most health problems.

OBJECTIVE

In this paper, we discuss whether data that are recorded routinely as part of the health care process in primary care are actually fit to use for other purposes such as research and quality of health care indicators, how the original purpose may affect the extent to which the data are fit for another purpose, and the mechanisms behind these effects. In doing so, we want to identify possible sources of bias that are relevant for the use and reuse of these type of data.

METHODS

This paper is based on the authors' experience as users of electronic health records data, as general practitioners, health informatics experts, and health services researchers. It is a product of the discussions they had during the Translational Research and Patient Safety in Europe (TRANSFoRm) project, which was funded by the European Commission and sought to develop, pilot, and evaluate a core information architecture for the learning health system in Europe, based on primary care electronic health records.

RESULTS

We first describe the different stages in the processing of electronic health record data, as well as the different purposes for which these data are used. Given the different data processing steps and purposes, we then discuss the possible mechanisms for each individual data processing step that can generate biased outcomes. We identified 13 possible sources of bias. Four of them are related to the organization of a health care system, whereas some are of a more technical nature.

CONCLUSIONS

There are a substantial number of possible sources of bias; very little is known about the size and direction of their impact. However, anyone that uses or reuses data that were recorded as part of the health care process (such as researchers and clinicians) should be aware of the associated data collection process and environmental influences that can affect the quality of the data. Our stepwise, actor- and purpose-oriented approach may help to identify these possible sources of bias. Unless data quality issues are better understood and unless adequate controls are embedded throughout the data lifecycle, data-driven health care will not live up to its expectations. We need a data quality research agenda to devise the appropriate instruments needed to assess the magnitude of each of the possible sources of bias, and then start measuring their impact. The possible sources of bias described in this paper serve as a starting point for this research agenda.

Prevalence of Multiple Chronic Conditions Among Older Adults in Florida and the United States: Comparative Analysis of the OneFlorida Data Trust and National Inpatient Sample

Background

Older patients with multiple chronic conditions are often faced with increased health care needs and subsequent higher medical costs, posing significant financial burden to patients, their caregivers, and the health care system. The increasing adoption of electronic health record systems and the proliferation of clinical data offer new opportunities for prevalence studies and for population health assessment. The last few years have witnessed an increasing number of clinical research networks focused on building large collections of clinical data from electronic health records and claims to make it easier and less costly to conduct clinical research.

Objective

The aim of this study was to compare the prevalence of common chronic conditions and multiple chronic conditions in older adults between Florida and the United States using data from the OneFlorida Clinical Research Consortium and the Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS).

Methods

We first analyzed the basic demographic characteristics of the older adults in 3 datasets—the 2013 OneFlorida data, the 2013 HCUP NIS data, and the combined 2012 to 2016 OneFlorida data. Then we analyzed the prevalence of each of the 25 chronic conditions in each of the 3 datasets. We stratified the analysis of older adults with hypertension, the most prevalent condition. Additionally, we examined trends (ie, overall trends and then by age, race, and gender) in the prevalence of discharge records representing multiple chronic conditions over time for the OneFlorida (2012-2016) and HCUP NIS cohorts (2003-2013).

Results

The rankings of the top 10 prevalent conditions are the same across the OneFlorida and HCUP NIS datasets. The most prevalent multiple chronic conditions of 2 conditions among the 3 datasets were—hyperlipidemia and hypertension; hypertension and ischemic heart disease; diabetes and hypertension; chronic kidney disease and hypertension; anemia and hypertension; and hyperlipidemia and ischemic heart disease. We observed increasing trends in multiple chronic conditions in both data sources.

Conclusions

The results showed that chronic conditions and multiple chronic conditions are prevalent in older adults across Florida and the United States. Even though slight differences were observed, the similar estimates of prevalence of chronic conditions and multiple chronic conditions across OneFlorida and HCUP NIS suggested that clinical research data networks such as OneFlorida, built from heterogeneous data sources, can provide rich data resources for conducting large-scale secondary data analyses.

Patient engagement in type 2 diabetes mellitus research: what patients want

BACKGROUND

As patients are the ultimate stakeholder in their health, their perspectives should be included along with researchers, providers, and funders of research design, execution, and interpretation. Despite the high prevalence of type 2 diabetes mellitus (T2DM), patients are rarely directly included in these decisions.

PURPOSE

We sought to determine areas of research most important to patients with T2DM, identify ways through which patients with T2DM want to engage in research, and evaluate online patient research networks as a source for obtaining patient perspectives on research engagement.

PATIENTS AND METHODS

This study used an online patient community forum (PatientsLikeMe) to host two asynchronous moderated discussions, each with three to four prompted discussion posts. A qualitative summary of themes was derived from the posts.

RESULTS

Eighty-eight participants with T2DM took part. Participants were mostly white (86%), averaged 58.6 years of age, half were female (50%), and over half (62%) resided in the US. Research priorities included managing T2DM with comorbidities, controlling blood sugar levels, finding a cure, and understanding causes of T2DM. Participants wanted to see direct applications of research to their lives. Clinical research was perceived to have overly restrictive eligibility criteria and to measure outcome sets that do not adequately address patient health concerns. Participants indicated broad interest in partnering in research and a willingness to apply their skills and educational background to specific stages in the research process.

CONCLUSION

Patients with T2DM would like researchers to address outcomes that have meaning in patients' daily lives. Initiatives to involve patients in research should leverage and enable patients to contribute as participants, advisors, or co-investigators, going beyond research topic prioritization to full participation throughout the research process based on their abilities and interest. This study provides support for the use of online patient research network discussions to generate rich qualitative data to engage patients in research.

Exploring patient and family involvement in the lifecycle of an orphan drug: a scoping review

BACKGROUND

Patients and their families have become more active in healthcare systems and research. The value of patient involvement is particularly relevant in the area of rare diseases, where patients face delayed diagnoses and limited access to effective therapies due to the high level of uncertainty in market approval and reimbursement decisions. It has been suggested that patient involvement may help to reduce some of these uncertainties. This review explored existing and proposed roles for patients, families, and patient organizations at each stage of the lifecycle of therapies for rare diseases (i.e., orphan drug lifecycle).

METHODS

A scoping review was conducted using methods outlined by Arksey and O'Malley. To validate the findings from the literature and identify any additional opportunities that were missed, a consultative webinar was conducted with members of the Patient and Caregiver Liaison Group of a Canadian research network.

RESULTS

Existing and proposed opportunities for involving patients, families, and patient organizations were reported throughout the orphan drug lifecycle and fell into 12 themes: research outside of clinical trials; clinical trials; patient reported outcomes measures; patient registries and biorepositories; education; advocacy and awareness; conferences and workshops; patient care and support; patient organization development; regulatory decision-making; and reimbursement decision-making. Existing opportunities were not described in sufficient detail to allow for the level of involvement to be assessed. Additionally, no information on the impact of involvement within specific opportunities was found. Based on feedback from patients and families, documentation of existing opportunities within Canada is poor.

CONCLUSIONS

Opportunities for patient, family, and patient organization involvement exist throughout the orphan drug lifecycle. However, based on the information found, it is not possible to determine which opportunities would be most effective at each stage.

A Research Agenda for Communication Scholars in the Precision Medicine Era

The 2015 announcement of the Precision Medicine Initiative (PMI) galvanized and energized efforts to reconsider medical practice through tailoring of prevention and treatment recommendations based on genetics, environment, and lifestyle. Numerous disciplines contributed white papers identifying challenges associated with PMI and calling for discipline-specific research that might provide solutions to such challenges. Throughout these white papers, the prominence of communication in achieving the PMI's goals is obviously apparent. In this article, we highlight opportunities for communication scholars' contributions to the PMI based on challenges identified in white papers from other disciplines and work already conducted by research teams in the field of communication.

Building a learning health system using clinical registers: a non-technical introduction

Purpose The purpose of this paper is to describe how clinical registers were designed and used to serve multiple purposes in three health systems, in order to contribute practical experience for building learning healthcare systems. Design/methodology/approach Case description and comparison of the development and use of clinical registries, drawing on participants' experience and published and unpublished research. Findings Clinical registers and new software systems enable fact-based decisions by patients, clinicians, and managers about better care, as well as new and more economical research. Designing systems to present the data for users' daily work appears to be the key to effective use of the potential afforded by digital data. Research limitations/implications The case descriptions draw on the experience of the authors who were involved in the development of the registers, as well as on published and unpublished research. There is limited data about outcomes for patients or cost-effectiveness. Practical implications The cases show the significant investments which are needed to make effective use of clinical register data. There are limited skills to design and apply the digital systems to make the best use of the systems and to reduce their disadvantages. More use can be made of digital data for quality improvement, patient empowerment and support, and for research. Social implications Patients can use their data combined with other data to self-manage their chronic conditions. There are challenges in designing and using systems so that those with lower health and computer literacy and incomes also benefit from these systems, otherwise the digital revolution may increase health inequalities. Originality/value The paper shows three real examples of clinical registers which have been developed as part of their host health systems' strategies to develop learning healthcare systems. The paper gives a simple non-technical introduction and overview for clinicians, managers, policy-advisors and improvers of what is possible and the challenges, and highlights the need to shape the design and implementation of digital infrastructures in healthcare services to serve users.

Untapped Potential of Observational Research to Inform Clinical Decision Making: American Society of Clinical Oncology Research Statement

ASCO believes that high-quality observational studies can advance evidence-based practice for cancer care and are complementary to randomized controlled trials (RCTs). Observational studies can generate hypotheses by evaluating novel exposures or biomarkers and by revealing patterns of care and relationships that might not otherwise be discovered. Researchers can then test these hypotheses in RCTs. Observational studies can also answer or inform questions that either have not been or cannot be answered by RCTs. In addition, observational studies can be used for postmarketing surveillance of new cancer treatments, particularly in vulnerable populations. The incorporation of observational research as part of clinical decision making is consistent with the position of many leading institutions. ASCO identified five overarching recommendations to enhance the role of observational research in clinical decision making: (1) improve the quality of electronic health data available for research, (2) improve interoperability and the exchange of electronic health information, (3) ensure the use of rigorous observational research methodologies, (4) promote transparent reporting of observational research studies, and (5) protect patient privacy.

Improving Recruitment and Retention Rates in a Randomized Controlled Trial

High recruitment and retention rates in randomized controlled trials are essential to ensure validity and broad generalizability. We used quality improvement methods, including run charts and intervention cycles, to achieve and sustain high recruitment and retention rates during the Hospital-To-Home Outcomes randomized controlled trial. This study is examining the effects of a single nurse-led home health care visit after discharge for an acute pediatric hospitalization. A total of 1500 participants were enrolled in the 15-month study period. For study recruitment, we assessed the percentage of patients who enrolled in the study among those randomly selected to approach (goal ≥50%) and the percentage of patients who refused to enroll from those randomly selected to approach (goal ≤30%). For intervention completion, we examined the percentage of patients who completed the home visit intervention among those randomized to receive the intervention (goal ≥95%) were examined. Follow-up rates were tracked as the percentage of patients who completed the 14-day follow-up telephone survey (goal ≥95%). The study goals for 2 of the 4 metrics were met and sustained, with statistically significant improvements over time in 3 metrics. The median enrollment rate increased from 50% to 59%, and the median refusal rate decreased from 37% to 32%. The median intervention completion rate remained unchanged at 88%. The 14-day follow-up completion median rate increased from 94% to 96%. These results indicate that quality improvement methods can be used within the scope of a large research study to achieve and sustain high recruitment and retention rates.

Anticipated Ethics and Regulatory Challenges in PCORnet: The National Patient-Centered Clinical Research Network

PCORnet, the National Patient-Centered Clinical Research Network, seeks to establish a robust national health data network for patient-centered comparative effectiveness research. This article reports the results of a PCORnet survey designed to identify the ethics and regulatory challenges anticipated in network implementation. A 12-item online survey was developed by leadership of the PCORnet Ethics and Regulatory Task Force; responses were collected from the 29 PCORnet networks. The most pressing ethics issues identified related to informed consent, patient engagement, privacy and confidentiality, and data sharing. High priority regulatory issues included IRB coordination, privacy and confidentiality, informed consent, and data sharing. Over 150 IRBs and five different approaches to managing multisite IRB review were identified within PCORnet. Further empirical and scholarly work, as well as practical and policy guidance, is essential if important initiatives that rely on comparative effectiveness research are to move forward.

Four health data networks illustrate the potential for a shared national multipurpose big-data network

Information in electronic health data that are drawn from large populations of patients is transforming health care, public health practice, and clinical research. This article describes our experience in developing data networks that repurpose electronic health records and administrative data. The four programs we feature are the Food and Drug Administration's Mini-Sentinel program (which focuses on medical product safety), the National Patient-Centered Clinical Research Network (PCORnet, comparative effectiveness research), the National Institutes of Health's Health Care Systems Research Collaboratory Distributed Research Network (biomedical research), and ESPnet (public health surveillance). Challenges to these uses of electronic health data include understanding the factors driving the collection, coding, and preservation of the data; the extensive customization of different systems that collect similar data; the fragmentation of the US health care delivery system and its records; and privacy and proprietary considerations. We view these four programs as examples of the first stage in the development of a shared national big-data resource that leverages the investments of many agencies and organizations for the benefit of multiple networks and users.

Software-Enabled Distributed Network Governance: The PopMedNet Experience

Introduction:

The expanded availability of electronic health information has led to increased interest in distributed health data research networks.

Distributed Research Network Model:

The distributed research network model leaves data with and under the control of the data holder. Data holders, network coordinating centers, and researchers have distinct needs and challenges within this model.

Software Enabled Governance: PopMedNet:

The concerns of network stakeholders are addressed in the design and governance models of the PopMedNet software platform. PopMedNet features include distributed querying, customizable workflows, and auditing and search capabilities. Its flexible role-based access control system enables the enforcement of varying governance policies.

Selected Case Studies:

Four case studies describe how PopMedNet is used to enforce network governance models.

Issues and Challenges:

Trust is an essential component of a distributed research network and must be built before data partners may be willing to participate further. The complexity of the PopMedNet system must be managed as networks grow and new data, analytic methods, and querying approaches are developed.

Conclusions:

The PopMedNet software platform supports a variety of network structures, governance models, and research activities through customizable features designed to meet the needs of network stakeholders.

Big data analytics to improve cardiovascular care: promise and challenges

The potential for big data analytics to improve cardiovascular quality of care and patient outcomes is tremendous. However, the application of big data in health care is at a nascent stage, and the evidence to date demonstrating that big data analytics will improve care and outcomes is scant. This Review provides an overview of the data sources and methods that comprise big data analytics, and describes eight areas of application of big data analytics to improve cardiovascular care, including predictive modelling for risk and resource use, population management, drug and medical device safety surveillance, disease and treatment heterogeneity, precision medicine and clinical decision support, quality of care and performance measurement, and public health and research applications. We also delineate the important challenges for big data applications in cardiovascular care, including the need for evidence of effectiveness and safety, the methodological issues such as data quality and validation, and the critical importance of clinical integration and proof of clinical utility. If big data analytics are shown to improve quality of care and patient outcomes, and can be successfully implemented in cardiovascular practice, big data will fulfil its potential as an important component of a learning health-care system.

Bidirectional Data Collaborations in Distributed Research

Introduction:

The need for collaborations with bidirectional data exchange within and across distributed research networks has increased.

Currently Existing Activities:

This commentary will present currently publically available activities including the Sentinel Initiative, the Patient-Centered Outcomes Research Network (PCORnet), and the NIH Research Collaboratory.

Current Technical and Governance Challenges:

Even with the advances made in this arena, several technical and governance challenges remain including the evolution of clinically rich data sources and modes of care, availability of longitudinal data resources through data linkage, and the processes to share data and link data resources while ensuring privacy and proprietary control of data.

Perspective:

These activities will require enhanced levels of trust between entities involved in the delivery of healthcare (Trust 2.0) in addition to the trust health plans and health systems have with patients (Trust 1.0). Recent public funding announcements and public access to data resources will likely improve the landscape of bidirectional data collaborations in distributed research.

Optimizing Enrollment of Patients into Nephrology Research Studies

Advances in medical care and biomedical research depend on the participation of human subjects. Poor patient enrollment in research has limited past clinical and translational research endeavors in nephrology. Simultaneously, patients and their caregivers are seeking better diagnostic, monitoring, and therapeutic approaches to improve or restore kidney and overall health. This manuscript will discuss a framework and strategies to optimize patient enrollment within nephrology research and provide examples of success from existing nephrology research programs.

Improving care delivery and outcomes in pediatric rheumatic diseases

PURPOSE OF REVIEW

This article highlights efforts in pediatric rheumatology related to optimizing the care provided to patients with pediatric rheumatic diseases and describes various approaches to improve health outcomes.

RECENT FINDINGS

Recent studies report low rates of remission, frequent occurrence of comorbidities, disease damage, and decreased health-related quality of life in pediatric rheumatic diseases. The Pediatric Rheumatology Care and Outcomes Improvement Network is a quality improvement learning network that has demonstrated improvement in the process of care measures through use of a centralized patient registry, and interventions, including previsit planning, population management, shared decision making, and patient/parent engagement. A pediatric rheumatology patient-powered research network was established to enable patient and caregiver participation in setting research priorities and to facilitate data sharing to answer research questions. Quality measure development and benchmarking are proceeding in multiple pediatric rheumatic diseases.

SUMMARY

The review summarizes the current efforts to improve care delivery and outcomes in pediatric rheumatic diseases through a learning health system approach that harnesses knowledge from the clinical encounter to serve quality improvement, research, and discovery. Incorporating standard approaches to medication treatment plans may reduce variation in care, including using the patient voice to design research studies to bring focus on more patient relevant outcomes.

VIDEO ABSTRACT

http://links.lww.com/COR/A28.

Caring for patients with kidney disease: shifting the paradigm from evidence-based medicine to patient-centered care

The last several decades have witnessed the emergence of evidence-based medicine as the dominant paradigm for medical teaching, research and practice. Under an evidence-based approach, populations rather than individuals become the primary focus of investigation. Treatment priorities are largely shaped by the availability, relevance and quality of evidence and study outcomes and results are assumed to have more or less universal significance based on their implications at the population level. However, population-level treatment goals do not always align with what matters the most to individual patients-who may weigh the risks, benefits and harms of recommended treatments quite differently. In this article we describe the rise of evidence-based medicine in historical context. We discuss limitations of this approach for supporting real-world treatment decisions-especially in older adults with confluent comorbidity, functional impairment and/or limited life expectancy-and we describe the emergence of more patient-centered paradigms to address these limitations. We explain how the principles of evidence-based medicine have helped to shape contemporary approaches to defining, classifying and managing patients with chronic kidney disease. We discuss the limitations of this approach and the potential value of a more patient-centered paradigm, with a particular focus on the care of older adults with this condition. We conclude by outlining ways in which the evidence-base might be reconfigured to better support real-world treatment decisions in individual patients and summarize relevant ongoing initiatives.

The evolution of healthcare quality measurement in the United States

Quality measurement is fundamental to systematic improvement of the healthcare system. Whilst the United States has made significant investments in healthcare quality measurement and improvement, progress has been somewhat limited. Public and private payers in the United States increasingly mandate measurement and reporting as part of pay-for-performance programmes. Numerous issues have limited improvement, including lack of alignment in the use of measures and improvement strategies, the fragmentation of the U.S. healthcare system, and the lack of national electronic systems for measurement, reporting, benchmarking and improvement. Here, we provide an overview of the evolution of U.S. quality measurement efforts, including the role of the National Quality Forum. Important contextual changes such as the growing shift towards electronic data sources and clinical registries are discussed together with international comparisons. In future, the U.S. healthcare system needs to focus greater attention on the development and use of measures that matter. The three-part aim of effective care, affordable care and healthy communities in the U.S. National Quality Strategy focuses attention on population health and reduction in healthcare disparities. To make significant improvements in U.S. health care, a closer connection between measurement and both evolving national data systems and evidence-based improvement strategies is needed.

Research participation registers can increase opportunities for patients and the public to participate in health services research

Members of the public and patients repeatedly indicate their willingness to take part in research, but current United Kingdom research governance involves complex rules about gaining consent. Research participation registers that seek consent from participants to be approached about future studies have several potential benefits, including: increased research participation across clinical and healthy populations; simplified recruitment to health care research; support for people's autonomy in decision making; and improved efficiency and generalizability of research. These potential benefits have to be balanced against ethical and governance considerations. With appropriate processes in place, seeking prospective consent from patients and members of the public to be approached about future studies could potentially increase public participation in health research without compromising informed consent and other ethical principles.

Using e-technologies in clinical trials

Clinical trials have been slow to incorporate e-technology (digital and electronic technology that utilizes mobile devices or the Internet) into the design and execution of studies. In the meantime, individuals and corporations are relying more on electronic platforms and most have incorporated such technology into their daily lives. This paper provides a general overview of the use of e-technologies in clinical trials research, specifically within the last decade, marked by rapid growth of mobile and Internet-based tools. Benefits of and challenges to the use of e-technologies in data collection, recruitment and retention, delivery of interventions, and dissemination are provided, as well as a description of the current status of regulatory oversight of e-technologies in clinical trials research. As an example of ways in which e-technologies can be used for intervention delivery, a summary of e-technologies for treatment of substance use disorders is presented. Using e-technologies to design and implement clinical trials has the potential to reach a wide audience, making trials more efficient while also reducing costs; however, researchers should be cautious when adopting these tools given the many challenges in using new technologies, as well as threats to participant privacy/confidentiality. Challenges of using e-technologies can be overcome with careful planning, useful partnerships, and forethought. The role of web- and smartphone-based applications is expanding, and the increasing use of those platforms by scientists and the public alike make them tools that cannot be ignored.