Data-Driven Diffusion Of Innovations: Successes And Challenges In 3 Large-Scale Innovative Delivery Models

Abstract

Failed diffusion of innovations may be linked to an inability to use and apply data, information, and knowledge to change perceptions of current practice and motivate change. Using qualitative and quantitative data from three large-scale health care delivery innovations-accountable care organizations, advanced primary care practice, and EvidenceNOW-we assessed where data-driven innovation is occurring and where challenges lie. We found that implementation of some technological components of innovation (for example, electronic health records) has occurred among health care organizations, but core functions needed to use data to drive innovation are lacking. Deficits include the inability to extract and aggregate data from the records; gaps in sharing data; and challenges in adopting advanced data functions, particularly those related to timely reporting of performance data. The unexpectedly high costs and burden incurred during implementation of the innovations have limited organizations' ability to address these and other deficits. Solutions that could help speed progress in data-driven innovation include facilitating peer-to-peer technical assistance, providing tailored feedback reports to providers from data aggregators, and using practice facilitators skilled in using data technology for quality improvement to help practices transform. Policy efforts that promote these solutions may enable more rapid uptake of and successful participation in innovative delivery system reforms.

Longitudinal participation in delivery and payment reform programs among US Primary Care Organizations

“…We created measures of organizational characteristics and characteristics of the county in which organizations were located using MD‐PPAS data along with data from the Area Health Resource File (AHRF) and the American Community Survey. We selected characteristics that have been shown in prior work to be related to participation in individual primary care practice transformation efforts 19‐21 . These variables included organizations size (both number of providers and number of Medicare beneficiaries per provider), proportion of primary care specialties of providers in the organization, and provider age (see Appendix : Table A2 for details on these measures).…”

“…We selected characteristics that have been shown in prior work to be related to participation in individual primary care practice transformation efforts. [19][20][21] These variables included organizations size (both number of providers and number of Medicare beneficiaries per provider), proportion of primary care specialties of providers in the organization, and provider age (see Appendix S1: Table A2 for details on these measures).…”

Developing an Evidence-Based Technical Assistance Model: a Process Evaluation of the National Training and Technical Assistance Center for Child, Youth, and Family Mental Health

“…8,21 In recent years, there has been movement towards data-driven TA, in which relevant data points are identified and reviewed to guide TA efforts. 22,23 Such data-driven approaches help ensure that TA is delivered to those who need it, not only to those who make a formal request for support. Furthermore, such a systematic approach helps TA providers tailor their support to the unique goals, strengths, and needs of recipients.…”

Lessons Learned in Providing Claims-Based Data to Participants in Health Care Innovation Models

“…The study team conducted a study across a wide range of innovation models to learn what approaches have worked well to provide claims-based data to model participants and what could be improved going forward. Prior literature addressing confidential feedback data have tended to focus on reporting to physicians, [5][6][7][8][9][10][11] especially primary care physicians, [8][9][10][11] and, more recently, accountable care organizations (ACOs). 11,12 This study makes an important contribution by evaluating the provision of claims-based data to a much broader range of organizations participating in 18 CMS models.…”

“…Prior literature addressing confidential feedback data have tended to focus on reporting to physicians, [5][6][7][8][9][10][11] especially primary care physicians, [8][9][10][11] and, more recently, accountable care organizations (ACOs). 11,12 This study makes an important contribution by evaluating the provision of claims-based data to a much broader range of organizations participating in 18 CMS models. By studying a mix of model types and data recipients, cross-cutting lessons were identified in 4 major areas: The findings should be of interest to multiple stakeholders involved in health care innovation models, including organizations designing or evaluating such models, payers providing claims-based data to model participants, and the organizations receiving such data.…”