Improving collection and use of interprofessional health workforce data: Progress and peril

Abstract

a b s t r a c tBackground: Policymakers and other stakeholders need robust data to understand how health care system changes affect the health care workforce and the care it provides, evaluate the effectiveness of health care finance and delivery innovations, and build an adequate supply of nurses and other health professionals to care for an aging and diverse population of patients. In 2011, the Institute of Medicine released a report that called for the creation of an infrastructure to collect and analyze interprofessional health workforce data and issued specific recommendations to reach that overarching goal. Purpose: This paper examines progress toward each of the main data-related recommendations of the Institute of Medicine Committee on the Future of Nursing, and identifies strategies that can achieve further gains in health workforce data collection. Methods: Multiple documents and websites were reviewed to identify the extent to which each of the Institute of Medicine's recommendations have been implemented. Discussion: There has been little progress toward the Institute of Medicine recommendations regarding data collection, with a few exceptions related to improvements in national data on ambulatory care. This can largely be attributed to a lack of funding. Conclusion: Although there are active and strong collaborative relationships across many key stakeholders, there have not been sufficient resources dedicated to ensuring that new programs advance. More leadership, advocacy, and resources will be needed to build the robust data infrastructure called for by the Institute of Medicine.

Rural And Nonrural Primary Care Physician Practices Increasingly Rely On Nurse Practitioners

“…In general, data limitations for conducting NP- focused research include lack of longitudinal information and the inability to identify individual NPs. 35,36 Commonly used publicly available data provide national and regional counts of NPs 33 or pool NPs with other providers. 23,34 Thus, these features of the SK&A data advance research focused on NPs.…”

Surveying Primary Care Nurse Practitioners: An Overview of National Sampling Frames

“…There is currently no national file with comprehensive NP specialty information. Barriers to collecting this data include lack of funding and lack of coordination across federal, state, and local organizations to standardize collection of nursing workforce data (Barnes & Novosel, 2018; Spetz et al., 2016; University of North Carolina [UNC], n.d.). The National Academy of Medicine’s (formerly the Institute of Medicine, 2011) Future of Nursing Report recommended that the National Health Workforce Commission and HRSA collaborate with state licensing boards to standardize collection of minimum health care workforce data sets at the state level, to be collected during license renewal.…”

“…To address this issue, specialty information could potentially be self-reported by NPs or determined by an algorithm that includes a combination of self-reported specialty, certifications, and employment setting (UNC, n.d.). More consistent and comprehensive data collection for NPs and other APRNs, including specialty information, education and training, certification and licensure, and practice characteristics, can inform nursing workforce planning and policies (Barnes & Novosel, 2018; Spetz et al., 2016). In particular, better data collection using unique NP identifiers would enable linkage of NP workforce data to other data sources to evaluate the impact of NPs on patient outcomes (Barnes & Novosel, 2018; Campaign for Action, 2016).…”

Improving Data for Behavioral Health Workforce Planning: Development of a Minimum Data Set

“…Despite support for MDS adoption, nearly half of states do not yet use a workforce MDS, and those that do cite data collection limitations. 39 Widespread MDS implementation may require cultivation of partnerships and development of new policies. State and federal government agencies and policy makers can advocate for the adoption of standards in data collection for human resources planning, as well as provide incentives for implementing ongoing data collection.…”