Creating pragmatic, rapid-cycle, evidence-based innovation: The Kaiser Permanente Northern California Delivery Science and Applied Research (DARE) program

Abstract

Introduction

Ongoing crises in the quality, affordability, sustainability, value, and equity of U.S. healthcare call for rapid, massive-scale innovations across multiple specialties. Physician groups and healthcare organizations commit significant monetary and personnel investments for innovation and improvement efforts, but most lack over-arching systems theory-supported conceptual frameworks for efficiently coordinating the timely, large-volume idea generation, refinement, prioritization, evidence development, implementation, and re-evaluation strategies needed for rapid-cycle improvements in health care delivery, outcomes, and value.

Methods

This article describes one large-scale, generalizable model: The Permanente Medical Group's (TPMG) Delivery Science and Applied Research (DARE) program within Kaiser Permanente Northern California. This organization-level initiative was designed to: (1) elicit clinical innovation and quality concerns across clinical specialties; (2) prioritize these questions for next-step evaluations; (3) create dedicated analytic, research, and clinical expertise to rapidly study the questions generated; (4) develop communities of clinician-researchers, embedded within their specialties' clinical operations, who gather ideas for evaluation, generate evidence, and facilitate implementation of research results (a.k.a. evidence-based innovators); and (5) broadly disseminate findings, to connect results with potential next-step implementation.

Results

The DARE program and its components rapidly led to more than 200 recently completed or ongoing projects, informed care changes, influenced national guidelines, developed communities of evidence-based clinician innovators in 15 specialties, and empowered new paths for career diversity and physician wellness. Key factors in the DARE program's success include explicitly defining high-impact ideas; engaging researchers with analysts experienced with large clinical data systems; developing several research funding mechanisms scaled to project size; prioritizing rapid and efficient project completion; supporting clinician-investigators embedded within their specialties; and structured organization-wide dissemination of findings for informing potential implementation.

Conclusions

High-volume, evidence-based innovation programs can be important, scale-able, reproducible models for different settings for increasing quality, affordability, sustainability, value, and equity in healthcare and furthering the difficult-to-achieve concept of developing sustainable learning healthcare systems.