Dataset Information

Pre-Visit Prioritization for complex patients with diabetes: Randomized trial design and implementation within an integrated health care system.

ABSTRACT: Despite robust evidence to guide clinical care, most patients with diabetes do not meet all goals of risk factor control. Improved patient-provider communication during time-limited primary care visits may represent one strategy for improving diabetes care.We designed a controlled, cluster-randomized, multi-site intervention (Pre-Visit Prioritization for Complex Patients with Diabetes) that enables patients with poorly controlled type 2 diabetes to identify their top priorities prior to a scheduled visit and sends these priorities to the primary care physician progress note in the electronic medical record. In this paper, we describe strategies to address challenges to implementing our health IT-based intervention study within a large health care system.This study is being conducted in 30 primary care practices within a large integrated care delivery system in Northern California. Over a 12-week period (3/1/2015-6/6/2015), 146 primary care physicians consented to enroll in the study (90.1%) and approved contact with 2496 of their patients (97.6%). Implementation challenges included: (1) navigating research vs. quality improvement requirements; (2) addressing informed consent considerations; and (3) introducing a new clinical tool into a highly time-constrained workflow. Strategies for successfully initiating this study included engagement with institutional leaders, Institutional Review Board members, and clinical stakeholders at multiple stages both before and after notice of Federal funding; flexibility by the research team in study design; and strong support from institutional leadership for "self-learning health system" research.By paying careful attention to identifying and collaborating with a wide range of key clinical stakeholders, we have shown that researchers embedded within a learning care system can successfully apply rigorous clinical trial methods to test new care innovations.

SUBMITTER: Grant RW

PROVIDER: S-EPMC4818191 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Pre-Visit Prioritization for complex patients with diabetes: Randomized trial design and implementation within an integrated health care system.

Grant Richard W RW Uratsu Connie S CS Estacio Karen R KR Altschuler Andrea A Kim Eileen E Fireman Bruce B Adams Alyce S AS Schmittdiel Julie A JA Heisler Michele M

Contemporary clinical trials 20160126

<h4>Background/aims</h4>Despite robust evidence to guide clinical care, most patients with diabetes do not meet all goals of risk factor control. Improved patient-provider communication during time-limited primary care visits may represent one strategy for improving diabetes care.<h4>Methods</h4>We designed a controlled, cluster-randomized, multi-site intervention (Pre-Visit Prioritization for Complex Patients with Diabetes) that enables patients with poorly controlled type 2 diabetes to identif ...[more]

PMID: 26820612

Similar Datasets

Project description:BACKGROUND:Group-based Diabetes Prevention Programs (DPP), aligned with recommendations from the Centers for Disease Control and Prevention, promote clinically significant weight loss and reduce cardio-metabolic risks. Studies have examined implementation of the DPP in community settings, but less is known about its integration in healthcare systems. In 2010, a group-based DPP known as the Group Lifestyle Balance (GLB) was implemented within a large healthcare delivery system in Northern California, across three geographically distinct regional administration divisions of the organization within 12 state counties, with varying underlying socio-demographics. The regional divisions implemented the program independently, allowing for natural variation in its real-world integration. We leveraged this natural experiment to qualitatively assess the implementation of a DPP in this healthcare system and, especially, its fidelity to the original GLB curriculum and potential heterogeneity in implementation across clinics and regional divisions. METHODS:Using purposive sampling, we conducted semi-structured interviews with DPP lifestyle coaches. Data were analyzed using mixed-method techniques, guided by an implementation outcomes framework consisting of eight constructs: acceptability, adoption, appropriateness, cost, feasibility, fidelity, penetration, and sustainability. RESULTS:We conducted 33 interviews at 20 clinics across the three regional administrative divisions. Consistencies in implementation of the program were found across regions in terms of satisfaction with the evidence base (acceptability), referral methods (adoption), eligibility criteria (fidelity), and strategies to increase retention and effectiveness (sustainability). Heterogeneity in implementation across regions were found in all categories, including: the number and frequency of sessions (fidelity); program branding (adoption); lifestyle coach training (adoption), and patient-facing cost (cost). Lifestyle coaches expressed differing attitudes about curriculum content (acceptability) and suitability of educational level (appropriateness). While difficulties with recruitment were common across regions (feasibility), strategies used to address these challenges differed (sustainability). CONCLUSIONS:Variation exists in the implementation of the DPP within a large multi-site healthcare system, revealing a dynamic and important tension between retaining fidelity to the original program and tailoring the program to meet the local needs. Moreover, certain challenges across sites may represent opportunities for considering alternative implementation to anticipate these barriers. Further research is needed to explore how differences in implementation domains impact program effectiveness.

Project description:BackgroundThe rapid spread of severe acute respiratory syndrome coronavirus-2 or SARS-CoV-2 necessitated a scaled treatment response to the novel coronavirus disease 2019 (COVID-19).ObjectiveThis study aimed to characterize the design and rapid implementation of a complex, multimodal, technology response to COVID-19 led by the Intermountain Healthcare's (Intermountain's) Care Transformation Information Systems (CTIS) organization to build pandemic surge capacity.MethodsIntermountain has active community-spread cases of COVID-19 that are increasing. We used the Centers for Disease Control and Prevention Pandemic Intervals Framework (the Framework) to characterize CTIS leadership's multimodal technology response to COVID-19 at Intermountain. We provide results on implementation feasibility and sustainability of health information technology (HIT) interventions as of June 30, 2020, characterize lessons learned and identify persistent barriers to sustained deployment.ResultsWe characterize the CTIS organization's multimodal technology response to COVID-19 in five relevant areas of the Framework enabling (1) incident management, (2) surveillance, (3) laboratory testing, (4) community mitigation, and (5) medical care and countermeasures. We are seeing increased use of traditionally slow-to-adopt technologies that create additional surge capacity while sustaining patient safety and care quality. CTIS leadership recognized early that a multimodal technology intervention could enable additional surge capacity for health care delivery systems with a broad geographic and service scope. A statewide central tracking system to coordinate capacity planning and management response is needed. Order interoperability between health care systems remains a barrier to an integrated response.ConclusionThe rate of future pandemics is estimated to increase. The pandemic response of health care systems, like Intermountain, offers a blueprint for the leadership role that HIT organizations can play in mainstream care delivery, enabling a nimbler, virtual health care delivery system that is more responsive to current and future needs.

Dataset Information

Pre-Visit Prioritization for complex patients with diabetes: Randomized trial design and implementation within an integrated health care system.

Publications

Pre-Visit Prioritization for complex patients with diabetes: Randomized trial design and implementation within an integrated health care system.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets