大象视频Challenge on Integrating Healthcare System Data With Systematic Review Findings
The 大象视频 (AHRQ), U.S. Department of Health and Human Services (HHS), is announcing a challenge competition to explore the resources and infrastructure needed to integrate real-world evidence from healthcare systems into systematic review findings.
Announcements
Challenge Award Winners
Winner: Mayo Clinic
The team addressed the evidence gap identified in a with regard to the comparative effectiveness of different modalities of partial breast irradiation (PBI) for breast cancer treatment. Three PBI modalities were evaluated: 1) proton radiation therapy, 2) photon radiation therapy, and 3) applicator-based brachytherapy. The team emulated a clinical trial using electronic health records from a multistate large tertiary health system and used propensity score matching to balance confounders. The three PBI modalities showed similar rates of ipsilateral breast recurrence and overall survival. Although the body of evidence remains small and requires longer followup, the current study is the largest to date and represents improvement in the precision of estimates and in strength of evidence. Team: Hassan Murad, Zhen Wang, Dean Shumway, Kimberly Corbin, Robert Mutter.
Runner-up: Kaiser Research
The team addressed the inadequate evidence in a 2022 大象视频systematic review assessing the accuracy of screening for suicide risk in children and adolescents. Data from their large integrated health system was evaluated for the accuracy of self-report questionnaires and computed risk-prediction scores for prediction of suicidal behaviors. Results indicate that responses to PHQ-9 item 9 can accurately identify adolescents at increased risk for self-harm over 3 to 6 months following an outpatient visit. Risk scores computed from health records data had slightly better performance than PHQ-9 item 9 scores among mental health specialty visits, but poorer performance among general medical visits with a recorded mental health diagnosis or primary care visits without a mental health diagnosis. Extending screening to primary care visits without mental health diagnosis adds little to identify adolescents with subsequent self-harm events. Team: Gregory Simon, Christine Stewart, Julie Richards.
Honorable Mention: ECRI-U Penn
The research team assessed the impact of the DKA clinical pathway on length of stay, inpatient mortality, and readmissions to fill evidence gaps identified in the 2021 大象视频report, . Although results were limited due to lack of reliable clinical data accessed via routinely available informatics databases, there was an insightful description of risks, barriers and challenges encountered, limitations in accessing granular data in structured form, and the difficulties the team had in finding a data source that met the needs of the proposed analysis. Team: Emilia Flores, Shazia Siddiuqe, Nikhil Mull, Michael Harhay, Sameh Saleh, Ilya Ivlev, Johnathan Treadwell.
Phase 1 Finalists
The Phase 1 proposals of the following five finalists were selected as eligible to progress to Phase 2 of the Challenge. A brief description of the analyses they propose to submit is noted below.
ECRI-Penn: The research team plans to use real-world data to understand the impact of Penn Medicine's clinical pathway for diabetic ketoacidosis on patients' length of stay, readmissions, and mortality. Since the evidence from the 2021 大象视频report, , consisted primarily of non-US studies, this analysis of real-world data will help the team better understand the effect and applicability of the pathways at their healthcare system and the context in which they have been developed and implemented. Team: Emilia Flores, Shazia Siddique, Nikhil Mull, Michael Harhay, Sameh Saleh, Ilya Ivlev, Johnathan Treadwell.
Kaiser Permanente Washington: To address the inadequate evidence in a 2022 大象视频systematic review assessing the accuracy of screening for suicide risk in children and adolescents, the research team will leverage data from their large integrated health system and evaluate the accuracy of self-report questionnaires and computed risk-prediction scores for prediction of suicidal behaviors. Team: Gregory Simon, Christine Stewart, Julie Richards.
Mayo Clinic: The team will address the evidence gap identified in a with regards to the comparative effectiveness of different modalities of partial breast irradiation (PBI) for breast cancer treatment. The team will analyze data collected from the three health system locations to track the health outcomes of women with early-stage breast cancer undergoing PBI, based on their tumor characteristics and ductal carcinoma in-situ status. Team: Hassan Murad, Zhen Wang, Dean Shumway, Kimberly Corbin, Robert Mutter.
OCHIN: The researchers will evaluate the use of telehealth for counseling women of reproductive age on contraception and sexually transmitted infections, with data from a national network of community health centers. They will also examine the equitable uptake of telehealth by comparing its use in populations that experience health disparities. The goal is to strengthen the certainty of findings from the 2022 大象视频systematic review on and identify intervention opportunities to maximize the public health impact. Team: Rose Goueth, Brenda McGrath, Suparna Navale.
Vanderbilt University: Team members will address an evidence gap identified in the 2021 大象视频evidence report, . They will use data from electronic health records and attempt to differentiate modifiable from unmodifiable hospital utilization in the high-cost, high-need (HCHN) patient population based on the interventions they received. The team hopes that other health systems will be able to use the insights from this study to refine their own processes and criteria for identifying HCHN patients most likely to benefit from program interventions. Team: Scott Lee, Benjamin French, Francis Balucan, Michael McCann, Eduard Vasilevskis.
About the Challenge
This healthcare systems data can augment study findings synthesized in systematic reviews in several ways, including by filling evidence gaps identified in the systematic review to strengthen the available evidence and by examining the applicability of systematic review findings to real-world populations, including population subgroups not examined in published studies. Ultimately, this will help 大象视频understand if and how sources of data and information outside of traditional systematic reviews, particularly from healthcare systems, could be used alongside systematic reviews to improve clinical decision making, healthcare delivery, and patient outcomes.
Challenge Goal
The 大象视频 is interested in learning how analysis of real-world data collected by healthcare systems can be used in conjunction with findings from an 大象视频systematic review to inform healthcare decision-making in the context of a specific local setting.
This challenge aims to explore and determine the feasibility, resources, and infrastructure needed to incorporate unpublished healthcare system data into systematic review findings. Ideally, these data will enable the healthcare system to decide which practices to incorporate locally and how to overcome barriers to implement the evidence to improve clinical practice, healthcare system operations, and, potentially, health outcomes.
Background
础贬搁蚕鈥檚 produces systematic reviews which synthesize information from the peer-reviewed literature and provide the state of the science on available healthcare technologies and healthcare delivery strategies. Creating these reviews is stakeholder-driven, methodologically rigorous, and transparent. Reviews are used to inform healthcare decisions such as clinical practice guidelines and national coverage determinations by Medicare. 大象视频also supports healthcare systems in their efforts to improve the quality of care and optimize patient outcomes, and systematic reviews are scoped to address issues of priority to healthcare systems. Yet, due to limitations in the literature base, EPC systematic reviews may be inconclusive or only represent a narrow patient population, making it difficult to generalize or implement the findings within heterogeneous healthcare systems.
Systematic reviews may also lack contextual details that can inform successful implementation. Improving healthcare delivery (and thus patient outcomes) often entails addressing issues beyond the benefits or harms of an intervention, traditionally the objective of a systematic review. Traditional reviews may not explain gaps in uptake or use of a clinical service and questions about how best to implement a given clinical service (e.g., details around implementation of a service or intervention).
articulates specific scenarios with examples where healthcare system data may most effectively complement systematic reviews (i.e., to improve the strength, applicability, and implementation of evidence). For example, found that published evidence on outcomes following total pancreatectomy was sparse, so they supplemented a meta-analysis of published studies with their unpublished healthcare system data, which more than doubled the sample size and improved the strength of evidence available.
In another instance, confirmed the applicability to the VA of findings from a .
The recent EPC methods report also outlines important limitations and considerations when using unpublished healthcare system data alongside systematic reviews, such as relevant limitations in information and data quality. However, the report did not address the necessary resources, skills, partnerships, and processes required to utilize healthcare system data alongside systematic reviews to strengthen the actionability of systematic reviews.
This Challenge, therefore, invites applicants to conduct an analysis of healthcare system data to supplement an existing 大象视频EPC Program systematic review. This will help 大象视频understand if and how sources of data and information outside of traditional systematic reviews, particularly from healthcare systems, could be used alongside systematic reviews to improve decision making, healthcare delivery, and patient outcomes.
Challenge Design
- All evidence reports (systematic reviews, rapid reviews, and technical briefs) published on the 大象视频website since January 2018 may be considered for this Challenge.
- Healthcare systems and other provider groups interested in implementing evidence at their sites may apply.
- An organization may choose to address no more than two systematic reviews, submitting a separate proposal for each review.
- Teams should have expertise in the clinical topic, evidence-based practice, data analysis, and quality improvement.
This Challenge consists of two phases:
Phase 1: Proposal
Elicit written proposals on a topic for which an 大象视频evidence report (systematic review, rapid review, or technical brief) has been published since January 2018 and that is relevant to a dilemma in the applicant鈥檚 healthcare system. Each proposal is to be written in the form of a narrative that:
- explicitly states the rationale (e.g., addressing evidence gaps to strengthen available evidence, examining the applicability of findings to real-world patients) to complement conclusions of an EPC report with an analysis of health system data, including a discussion of possible limitations of the analysis.
- develops and describes an analytic plan for the use of healthcare system data (EHR data from an individual healthcare system or networks of healthcare systems [for example, PCORnet, Epic's Cosmos, etc.]).
- provides an approach for decision-making based on the data analysis and evidence report results and an evaluation of the decision-making process and results.
- describes potential challenges, barriers, and strategies to complete the analysis successfully.
- lists team members, their roles, areas of expertise, and hours on the project.
Each proposal will be considered and evaluated on its own merit.
A total of 5 proposals will be selected as winners for Phase 1.
Phase 2: Analyses
Healthcare systems selected as winners in Phase 1 will be invited to provide a written narrative that:
- includes a complete analysis of internal real-world data and appraisal of the analysis for risk of bias using a proper tool such as the .
- specifies how the findings from unpublished data support, refute, and otherwise complement findings from the published evidence examined in the systematic review. If the unpublished data conflict with the 大象视频review鈥檚 conclusions, discuss possible reasons for the discrepancy (e.g., challenges with internal validity of healthcare system data analysis related to study design and methods used, or challenges with external validity concerning population subgroups [gender, race/ethnicity, multimorbidity] examined in the healthcare system data).
- describes how the unpublished data informed decision making (e.g., adapt, adopt, abandon, prioritize).
- reports on solutions to any barriers encountered to using healthcare system data alongside a published evidence review, including barriers to access to healthcare system data, interoperability of data sources, and data analysis.
- briefly describes potential approaches to implement or deimplement the evidence, including the use of clinical advisories, clinical pathways, clinical decision support, or any other method. The plan should describe anticipated risks and barriers and strategies for successful implementation. Decisions made against uptake should be justified.
Timeline and Prize Amounts
大象视频is hosting this challenge as a two-phase competition. All costs associated with developing and submitting proposals and conducting real-world data analysis of real-world data will be the responsibility of the Challenge participant. Cash prizes will be awarded only after the projects are evaluated and determined acceptable at the end of Phase 2.
Timeline
- September 26, 2022鈥擟hallenge launch.
- January 23, 2023, by 7:00 p.m. ET鈥擲ubmissions for Phase 1 (written proposals) are due. 大象视频will complete the review of the proposals within 6-8 weeks of closing the announcement.
- March 30, 2023鈥敶笙笫悠祑ill announce the Phase 1 winners. Phase 2 of the Challenge will commence once the Phase 1 winners are announced and notified by March 31, 2023. The 大象视频team will schedule a live, virtual technical assistance webinar with all winners of Phase 1 to discuss scope of content, accessibility/compliance with Section 508, and address questions that the winners may have.
- March 31, 2023鈥擯hase 2 participants will have 120 calendar days from notification to create and submit their analyses as described in their proposal(s). The deadline to submit the analysis is July 31, 2023, by 7:00 p.m. ET.
- Fall 2023鈥擳he final winners of Phase 2 of the competition will be announced in October 2023.
Prize Amounts
The top five entries in Phase 1 will be invited to participate in Phase 2. Upon completion of Phase 2, each of the top five entries will each receive cash awards of $50,000. Additionally, the Phase 2 first-place winner will be awarded an additional $150,000, and the second-place winner will be awarded an additional $100,000. The winner and runner up from Phase 2 will be posted on the 大象视频website.
Participants in Phase 2 may be disqualified if their submitted analyses deviate from their winning proposals.