Overregulation of Health Care: Musings on Disruptive Innovation Theory

Disruptive innovation theory provides one lens through which to describe how regulations may stifle innovation and increase costs. Basing their discussion on this theory, Curtis and Schulman consider some of the effects that regulatory controls may have on innovation in the health sector

Launching PCORnet, a national patient-centered clinical research network

The Patient-Centered Outcomes Research Institute (PCORI) has launched PCORnet, a major initiative to support an effective, sustainable national research infrastructure that will advance the use of electronic health data in comparative effectiveness research (CER) and other types of research. In December 2013, PCORI's board of governors funded 11 clinical data research networks (CDRNs) and 18 patient-powered research networks (PPRNs) for a period of 18 months. CDRNs are based on the electronic health records and other electronic sources of very large populations receiving healthcare within integrated or networked delivery systems. PPRNs are built primarily by communities of motivated patients, forming partnerships with researchers. These patients intend to participate in clinical research, by generating questions, sharing data, volunteering for interventional trials, and interpreting and disseminating results. Rapidly building a new national resource to facilitate a large-scale, patient-centered CER is associated with a number of technical, regulatory, and organizational challenges, which are described here

Applying Patient-Reported Outcome Methodology to Capture Patient-Reported Health Data: Report From an NIH Collaboratory Roundtable

Patient-reported health data provide information for pragmatic clinical trials that may not be readily available from electronic health records or administrative claims data. In this report, we present key considerations for collecting patient-reported health information in pragmatic clinical trials, which are informed by best practices from patient-reported outcome research. We focus on question design and administration via electronic data collection platforms with respect to 3 types of patient-reported health data: medication use, utilization of health care services, and comorbid conditions. We summarize key scientific literature on the accuracy of these patient-reported data compared with electronic health record data. We discuss question design in detail, specifically defining the concept to be measured, patient understanding of the concept, recall periods of the question, and patient willingness to report. In addition, we discuss approaches for question administration and data collection platforms, which are key aspects of successful patient-reported data collection

Long‐Term Outcomes Among Elderly Survivors of Out‐of‐Hospital Cardiac Arrest

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139093/1/jah31396_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139093/2/jah31396.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139093/3/jah31396-sup-0001-SupInfo.pd

Electronic health records to facilitate clinical research

Electronic health records (EHRs) provide opportunities to enhance patient care, embed performance measures in clinical practice, and facilitate clinical research. Concerns have been raised about the increasing recruitment challenges in trials, burdensome and obtrusive data collection, and uncertain generalizability of the results. Leveraging electronic health records to counterbalance these trends is an area of intense interest. The initial applications of electronic health records, as the primary data source is envisioned for observational studies, embedded pragmatic or post-marketing registry-based randomized studies, or comparative effectiveness studies. Advancing this approach to randomized clinical trials, electronic health records may potentially be used to assess study feasibility, to facilitate patient recruitment, and streamline data collection at baseline and follow-up. Ensuring data security and privacy, overcoming the challenges associated with linking diverse systems and maintaining infrastructure for repeat use of high quality data, are some of the challenges associated with using electronic health records in clinical research. Collaboration between academia, industry, regulatory bodies, policy makers, patients, and electronic health record vendors is critical for the greater use of electronic health records in clinical research. This manuscript identifies the key steps required to advance the role of electronic health records in cardiovascular clinical research

Differences in health care use and outcomes by the timing of in-hospital worsening heart failure

BACKGROUND: Patients hospitalized with acute heart failure may experience worsening symptoms requiring escalation of therapy. In-hospital worsening heart failure is associated with worse in-hospital and postdischarge outcomes, but associations between the timing of worsening heart failure and outcomes are unknown. METHODS: Using data from a large clinical registry linked to Medicare claims, we examined characteristics, outcomes, and costs of patients hospitalized for acute heart failure. We defined in-hospital worsening heart failure by the use of inotropes or intravenous vasodilators or initiation of mechanical circulatory support, hemodialysis, or ventilation. The study groups were early worsening heart failure (n = 1,990), late worsening heart failure (n = 4,223), complicated presentation (n = 15,361), and uncomplicated hospital course (n = 41,334). RESULTS: Among 62,908 patients, those with late in-hospital worsening heart failure had higher in-hospital and postdischarge mortality than patients with early worsening heart failure or complicated presentation. Those with early or late worsening heart failure had more frequent all-cause and heart failure readmissions at 30 days and 1 year, with resultant higher costs, compared with patients with an uncomplicated hospital course. CONCLUSION: Although late worsening heart failure was associated with the highest mortality, both early and late worsening heart failures were associated with more frequent readmissions and higher health care costs compared to uncomplicated hospital course. Prevention of worsening heart failure may be an important focus in the care of hospitalized patients with acute heart failure

The Emergence of Population Health in US Academic Medicine

Importance In response to rapidly growing interest in population health, academic medical centers are launching department-level initiatives that focus on this evolving discipline. This trend, with its potential to extend the scope of academic medicine, has not been well characterized. Objective To describe the emergence of departments of population health at academic medical centers in the United States, including shared areas of focus, opportunities, and challenges. Design, Setting, and Participants This qualitative study was based on a structured in-person convening of a working group of chairs of population health–oriented departments on November 13 and 14, 2017, complemented by a survey of core characteristics of these and additional departments identified through web-based review of US academic medical centers. United States medical school departments with the word population in their name were included. Centers, institutes, and schools were not included. Main Outcomes and Measures Departments were characterized by year of origin, areas of focus, organizational structure, faculty size, teaching programs, and service engagement. Opportunities and challenges faced by these emerging departments were grouped thematically and described. Results Eight of 9 population health–oriented departments in the working group were launched in the last 6 years. The 9 departments had 5 to 97 full-time faculty. Despite varied organizational structures, all addressed essential areas of focus spanning the missions of research, education, and service. Departments varied significantly in their relationships with the delivery of clinical care, but all engaged in practice-based and/or community collaboration. Common attributes include core attention to population health–oriented research methods across disciplines, emphasis on applied research in frontline settings, strong commitment to partnership, interest in engaging other sectors, and focus on improving health equity. Tensions included defining boundaries with other academic units with overlapping areas of focus, identifying sources of sustainable extramural funding, and facilitating the interface between research and health system operations. Conclusions and Relevance Departments addressing population health are emerging rapidly in academic medical centers. In supporting this new framing, academic medicine affirms and strengthens its commitment to advancing population health and health equity, to improving the quality and effectiveness of care, and to upholding the social mission of medicine

Leveraging electronic health records for clinical research

Electronic health records (EHRs) can be a major tool in the quest to decrease costs and timelines of clinical trial research, generate better evidence for clinical decision making, and advance health care. Over the past decade, EHRs have increasingly offered opportunities to speed up, streamline, and enhance clinical research. EHRs offer a wide range of possible uses in clinical trials, including assisting with prestudy feasibility assessment, patient recruitment, and data capture in care delivery. To fully appreciate these opportunities, health care stakeholders must come together to face critical challenges in leveraging EHR data, including data quality/completeness, information security, stakeholder engagement, and increasing the scale of research infrastructure and related governance. Leaders from academia, government, industry, and professional societies representing patient, provider, researcher, industry, and regulator perspectives convened the Leveraging EHR for Clinical Research Now! Think Tank in Washington, DC (February 18-19, 2016), to identify barriers to using EHRs in clinical research and to generate potential solutions. Think tank members identified a broad range of issues surrounding the use of EHRs in research and proposed a variety of solutions. Recognizing the challenges, the participants identified the urgent need to look more deeply at previous efforts to use these data, share lessons learned, and develop a multidisciplinary agenda for best practices for using EHRs in clinical research. We report the proceedings from this think tank meeting in the following paper

Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers

Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]-positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2 x 10(53)). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2 x 10(-20)). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management