Developing the knowledge base of family practice

Fam Med. 2001 Apr;33(4):286-97.

Abstract

Borrowed and adapted knowledge is insufficient to optimize the potential of a comprehensive, integrative, relationship-centered generalist approach to improve the health of individuals, families, and communities. The knowledge base for family practice must be expanded by integrating multiple ways of knowing. This involves (1) self-reflective practice by clinicians, (2) involving the patient voice in generating research questions and interpreting data, (3) inquiry into the systems affecting health care, and (4) investigation of disease phenomena and treatment effects in patients over time. A multimethod, transdisciplinary, participatory approach is needed to create knowledge that retains connections with its meaning and context and therefore is readily translated into practice. This research integrates quantitative and qualitative traditions and involves the active participation of both clinicians and patients. The generation of relevant knowledge should be supported through (a) developing a culture of reflective practice among clinicians, (b) expanding the infrastructure for practice-based research, (c) developing a multimethod, transdisciplinary, participatory research paradigm, (d) longitudinal study of the process and outcomes of broad, integrative, relationship-centered care, and (e) incorporating pursuit of new knowledge as a central feature of training programs and policy. The time has come for the generalist disciplines to commit to the generation of new knowledge based on the needs of patients, families, and communities for relationship-centered, integrated, prioritized health care. Development of a culture of learning and inquiry, and the necessary research methods and skills will require a long-term commitment, creation of partnerships, and a focus on core principles by individuals and organizations.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Algorithms*
  • Clinical Competence*
  • Family Practice*
  • Humans
  • Research