What Is ONS’s Perspective on the Ambulatory Staffing Dilemma?

Despite that knowledge, much of staffing in the outpatient setting is not grounded in evidence, and an astounding number of variables contribute to the problem. In the 2016 ONS member survey (http://chapter.vc.ons.org/file_depot/0-10000000/0-10000/1337/folder/14081/2016+MEMBER+SURVEY+SUMMARY+FOR+CHAPTER+LEADERS.pdf), 64% of respondents identified staffing as the top concern in response to, “What are the most pressing challenges you face today in your practice?” Staffing in the outpatient setting has had less attention in than in the inpatient setting that, for many years, has used acuity tools to determine staffing.

Setting-Based Variables

Standardization of staffing in the outpatient care setting is a challenge because many variables need to be considered in a staffing model.

• Physical space, presence of an electronic health record, capacity, and hours of operation
• Type and volume of patients and the care to be given (from simple intramuscular injection to complex chemotherapy regimens; from blood transfusions to management of adverse reactions)
• Lack of a standardized methodology for counting patient encounters (number of patients only, minutes of interaction, number of tasks per patient, or a combination of these)
• Many institutions use home-grown staffing or acuity models that recognize assumptions included in the development of their institution-specific model but that may not be reproducible in all outpatient settings.
  • For example, levels of acuity are often cited but all are uniquely developed (https://doi.org/10.1188/15.CJON.332-337), with some being population specific and others institutionally specific. (See Figure 2 for additional reading.)
• Many staffing decisions are not evidence based (http://dx.doi.org/10.1097/NAQ.0000000000000138) and rely on assumption and opinion.

Personnel-Based Variables

Personnel variables contribute (http://dx.doi.org/10.1097/NAQ.0000000000000138) to whether staffing is appropriate, including:

• Level of education, licensure, certification, and training of nursing staff
• Nurse demographics (e.g., years of experience in setting)
• Degree to which nurses are performing non-nurse duties (e.g., booking appointments, testing)
• Availability of assistive personnel, including volunteers, and appropriate delegation by nurses
• Accurately identifying all of nurses’ direct and indirect care activities
• Alignment of the most appropriate skill set and nursing assignment for each patient patient requires better documentation of actionable interventions or decision making based on evidence rather than opinion
• Evidence-based interventions for unplanned variances in care and staffing.

State of the Knowledge

Most traditional staffing models use a case-mix index (a proxy for acuity) that is calculated from an average of all hospitalized patients, and therefore is not as accurate for higher acuity areas (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3291170/), such as oncology. More innovative approaches use a combination of forecasting of patient populations and mathematical calculations (e.g., x chairs multiplied by y patients) but assume an adequate number of nurses (http://www.nxtbook.com/nxtbooks/accc/oncologyissues_20170506/index.php#/70) in the calculation. Some U.S. states have mandated ratios that focus on nurse-patient ratios but do not include ratio of patients to assistive personnel, which is a known contributor to effective staffing models (https://doi.org/10.1188/12.ONF.166-172). (See Figure 3 for additional reading.) To complicate the issue further, the concept of adequate staffing can be a subjective experience. It may be poorly associated not only with case mix index but also with nursing variables. Finally, the availability of educational and practical support (e.g., advanced practice nurses and manager support) contributes to a perception of staffing adequacy (https://doi.org/10.1097/NCC.0b013e31825e4293).

Despite the overwhelming variables, we do have data to begin benchmarking best practices, including:

• National infusion hour per type of cancer benchmarks (http://oncologymgmt.com/proofa/wp-content/uploads/2014/01/2014NHOBSSlides.pdf) have been established.
• Workflow analysis and redistribution of non-nursing duties from RNs to assistive personnel can maximize efficiency and decrease RN staffing requirements (https://onf.ons.org/onf.ons.org/onf/43/2/podium-poster-and-research-abstracts) without compromising quality and safety.
• The number of assistive personnel as part of overall nurse staffing and patient outcomes is under recorded and may lead to overemphasizing the RN staffing (https://doi.org/10.1188/12.ONF.166-172) rather than overall staffing as it relates to quality outcomes. (See Figure 3 for additional reading.)
• Process analysis and reorganization using existing resources (https://www.ncbi.nlm.nih.gov/pubmed/24953809) can result in improved efficiencies, increased patient volume, decreased wait times, and more predictability in scheduling.
• Pilot data have shown (https://onf.ons.org/onf.ons.org/onf/43/2/podium-poster-and-research-abstracts) that many nonclinical, non-nurse duties are being performed by RNs, supporting the need to analyze and revise current processes. Such analysis may support a decrease in RN full-time equivalents from 14 to 5, maximizing efficiency while maintaining quality.

How You Can Contribute to the Evidence

In response to these challenges, ONS is collaborating with expert members to more fully understand the unique nature of outpatient oncology nursing staffing, and this is where you can help. A new online community, the ONS Ambulatory Staffing Initiative (http://communities.ons.org/communities/community-home?communitykey=3feca5e0-2f68-40b2-8667-01620f8b7446), is now available, with targeted questions designed to gather member-driven data and fully analyze and develop strategies to address outpatient staffing needs.

Excellence in staffing combines what we already know, such as historical member survey data (http://dx.doi.org/10.1188/04.ONF.E147-E156), with innovative use of technologies to gather current evidence to guide decision-making. If you are responsible for staffing or scheduling, visit the community and share your best practices for staffing outpatient centers.