Current Topics in Nursing Informatics Blog

                                         EHR and developing a staffing acuity tool

Staffing is one of the most challenging and tedious decision-making roles a nurse leader fulfills as preparing for the next shift. There are rules and regulations set by the organization in determining how many nurses will be assigned to the unit and how the patient rooms will be delegated. It is estimated that current nursing staffing rates comprises 40% of hospital budgets (Meyer et al., 2020). In this essence, creating optimal nurse assignments is desired to continue to meet standards of quality care, limit incidences and improve patient outcomes (Meyer et al., 2020). Nursing assignments have multiple factors implemented into the decision-making process. These dynamics would include budgeting, operational costs, staff satisfaction rates and patient safety concerns (Meyer et al., 2020) Nursing assignments can also be determined in relation to room proximity, predetermined nurse-to-patient ratios, medical complexities, and continuity of care from shift to shift (Meyer et al., 2020). Admissions, transfers, discharges and other unit activities should also be considered in the creation of a shift assignment. Nursing care will change during a patient's length of stay based on a combination of ordered tasks including education, nursing interventions, skill level, compliance, psychosocial needs and the patient’s medical diagnosis (Meyer et al, 2020). 

Unfortunately, the Covid-19 pandemic has really set a precedence for the need of nursing staff. There has been a huge shift in nurses leaving the bedside and seeking travel contract nursing opportunities. This is in regards to the higher pay scales and incentives. Improving the assignment acuity can adjust how the staff views their units and can promote providing quality care to their patients essentially decreasing mortality rates and length of stay. There is a definite change of attitudes towards leadership when the assignments are populated and viewed as fair and the nurses feel as if they have access to support and care from administration.  

The current practice at Lakeland Regional Health with staffing assignments is designed and dictated by the House Supervisor. The house supervisor gathers staffing ratio numbers and designates how many nurses will be assigned to each unit according to the budgeted ratios. When there is a critical shortage, units are left below their ratios and more often than not, the Team Leader is in staffing with their own patients. The supervisor is made aware of special circumstances such as Baker Act patients requiring sitters, special needs such as trachs and vents and is informed of any employee absence. These numbers are submitted in a workflow excel spreadsheet and sent out to the different departments. The formulation does not calculate other special indications for each unit and does not take the nursing skill level or experience into consideration. Unfortunately, there is a vast majority of nurses that have left the organization to seek other opportunities for higher pay or decreased nursing ratios. The current way of creating nursing assignments is destructive to our retention rates and only contributes to added reasons of why nurses are leaving the bedside. This can be detrimental to the safety of the staff and patients. Change is necessary in order to benefit nursing needs and to improve patient outcomes (Eastman & Kernan, 2022). 

Proposed Interventions

The purpose of patient classification systems or applying acuity application programs are to assess the care needs of the patients for careful staffing decisions (Sewell, 2019). In general, patient acuity systems gather data to calculate the number of full-time equivalents (FTEs) needed for the entire unit and patient volume (Sewell, 2019). Certain applications identify self-care deficits such as those related to activities of daily living, treatments, medications, special requirements and patient teaching needs (Sewell, 2019). Other systems assign time specifications to each task based on hospital requirements and predetermined measures (Sewell, 2019). Another process of these applications is the use of certain nursing diagnoses based on the patient’s condition and dependency on staffing care (Sewell, 2019). The primary nursing care provider forms the final decisions for this method. All patient classification systems depend on accurate and timely data input. There are some patient classification systems that use computer-based entry modules especially relying heavily on the EHR. This requires the nurse to enter precise data, special criteria measures or the appropriate tasks to generate the scoring of the patient’s acuity (Sewell, 2019). Other applications pull information from nurses’ documentation into the computerized record creating a fair, standardized scoring process. This technique prevents the nurses from adding the additional step of data entry for patient classification.

Recommendations

In order to allow this type of technological advancement in the organization, new upgrades would have to occur in Cerner. These upgrades will be costly in the beginning of the operation but could alter the overall financial state of the hospital by improving staff satisfaction of their assignments, improving patient satisfaction scores and the overall health outcomes. This new upgrade would have to be reviewed by the entire management team of the organization. There would be numerous committees that would have to review this type of program implementation and identify the benefits and barriers to the system. The informatics team would be essential to learn about the new patient acuity software, gather appropriate data and be fully involved with the implementation and evaluation process. Staff cooperation would be essential for the success of the venture. The financial aspects of upgrading the software package would have to be determined beneficial by the investors and business liaisons. 

To solve the acuity issue expanding across the medical-surgical units, it is proposed that this organization seek out additional resources from their current provider, Cerner. Cerner (2022) offers the ability for health care organizations to calculate patient acuity, specifically the care hours needed based on information documented in the electronic health record. This has created a balance of the high acuity patients between nurses, therefore dispersing a fair and manageable workload among the shift (Cerner, 2022). Currently, this practice is only offered among the critical care environment. The program, Cerner APACHE, relies on effective measurements and the accurate reporting of outcomes (Cerner, 2022). This application allows a nurse to objectively evaluate the specifics and performance of care delivered in an ICU setting (Cerner, 2022). Process improvement has become a major focus along with resource optimization in the organizations across the nation. APACHE gives the accessibility to the one of the largest outcomes databases in the world and provides an optimum capability to ensure fair acuity levels and therefore increasing the level of quality care provided (Cerner, 2022). Current data has not been issued for medical-surgical units or step-down units. This is a program that would be very beneficial with upgraded design aspects to handle these acute care settings. This type of program would have to be tested in these trial med-surg environments to see the appropriateness of the patient populations and successfully executing it to different organizations across the nation. 

Planning, Implementation and Evaluation

Hawkins et al., (2019) recommends the need for further research that could analyze several different regions of the United States and to assess the distinct patient populations, such as cardiac, orthopedic, and neurologic patient populations in those regions. Hawkins et al., (2019) expresses that nurse leaders, nursing staff, patients, and their families can benefit from what an interfaced EHR acuity tool offers. This type of application is expected to aid in cost reduction, staff retention, increased patient satisfaction scores, decreased adverse events, and increased reimbursement cost by implementing the acuity tool in order to balance the nurse-to-patient assignments (Hawkins et al., 2019) This type of acuity tool will need to be compatible with EHR and show a fluent trend in cost savings and staffing satisfaction levels. Hawkins et al., (2019) conveys that applying an electronic acuity tool interfaced with the EHR can be costly upfront due to the initiation costs, the training of team members, and the continued annual education (Hawkins et al., 2019). The desired outcome of such instillation may be that future costs may be improved with an increase in nursing satisfaction and therefore decreasing turnover rates and current marketing costs (Hawkins et al., 2019). This can also deter the extreme financial burden of paying for contract nurses to fill in the current staffing gaps. 

Nurses play a vital role in providing patient safety measures, promoting quality of care, and patient outcome measures. Annual education and formal training must occur with the current nursing staff and onboarding nurses on the importance of the acuity tool and how the information is accumulated from the EHR (Hawkins et al., 2019). The importance of real-time and accurate documentation will need to be to executed in order to ensure the desired effect of balancing nurse workloads (Hawkins et al., 2019). Nursing administration and the leadership team is ultimately responsible for ensuring that nurses have an appropriate and safe work environment to warrant quality care to patients and their families. The development of the software system is necessary especially in the acute-care units to obtain the appropriate resource planning and staffing for high acuity settings (Hawkins et al., 2019). Promoting the implementation of utilizing this type of tool will impact logistical cost savings, improving patient approval and nurse satisfaction, and decreasing turnover rates among nurses (Hawkins et al., 2019). 

In order to prove that this type of system is precise, the patient's workload score will have to be updated numerous times per shift to adjust to real-time documentation and newly entered orders. Producing the most reliable score will be dependent on nursing documentation, complete and real-time documentation of patient care tasks and updated order sets. The components of the scoring would have to be standardized and set on a specific score. The scores should be determined appropriately by assessments, braden scores, fall or flight risks, medications, wound care orders, activities of daily living, turning and repositioning requirements, lines/tubes/drains/airway management and admission, transfer or discharge orders. These requirements can give a better outlook that can be calculated into a concise result to be reviewed and considered when assigning nurses (Meyer et al, 2020). If nurses delay entering the documentation, the patient’s acuity score is altered because the documentation of vital signs, education, dressing changes and other nursing activities are not properly populated in order to reflect the patient’s true acuity (Sewell, 2019). Bedside charting should be enforced by the leadership teams in order for this type of practice to be successful and accurate. 

 

Conclusion

Current evidence shows that there is a manner to predict a patient's acuity by utilizing an electronic acuity tool that pulls data straight from the EHR (Hawkins et al., 2019). Further research should be conducted in order to produce a broad range of data among the different specialties and regions of the United States. Unfortunately, due to the Covid-19 pandemic and from the continuous nursing shortage crisis, patients’ rising acuity levels have created the means necessary to examine and place operations to combat nursing turnover rates and increase optimal patient outcomes. Patient health data within the EHR should be utilized to predict staffing in a formulated manner (Hawkins et al., 2019). This specialized software system incorporated amongst the EHR can escalate the operation of determining an acuity-based staffing assignment and ensure tactical decision-making efforts from the leadership team. This eliminates the need for creating assignments based off the former paper sheets. This acuity tool can accurately predict patient acuity and help to balance the nurse workload for the upcoming shift. Technology can essentially create a better patient workload for the nurse altering the sense of care, reducing staff departures and encouraging healthy patient outcomes (Hawkins et al., 2019).  

 

 

References

Cerner. (2022). Nursing: Advancing care delivery to support care teams across the continuum of care.https://www.cerner.com/solutions/nursing

Eastman, D. & Kernan, K.  (2022).  A New Patient Acuity Tool to Support Equitable Patient Assignments in a Progressive Care Unit.  Critical Care Nursing Quarterly, 45 (1), 54-61.  doi: 10.1097/CNQ.0000000000000388.

Hawkins, M., Messier, A., Myers, K., Nihsen, A., & Kniewel, M. (2019). Using an Acuity Tool that Interfaces with the Electronic Health Record to Balance Nursing Workload. I-Manager's Journal on Nursing, 9(2), 36-42. http://dx.doi.org/10.26634/jnur.9.2.16250

Meyer, K., Fraser, P. & Emeny, R.  (2020).  Development of a Nursing Assignment Tool Using Workload Acuity Scores.  JONA: The Journal of Nursing Administration, 50 (6),  322-327.  doi: 10.1097/NNA.0000000000000892.

Sewell, J. (2019). Informatics and nursing: Opportunities and challenges (6th ed.). Philadelphia, PA: Wolters Kluwer.