A Symphony of Evidence-Based Staffing (2)

A Symphony of Evidence-Based Staffing

By Barry P. Chaiken, MD, MPH

For more than 100 years, the Boston Symphony Orchestra (BSO) has entertained audiences in Symphony Hall, one of the finest musical halls in the world. As information technology advanced, the BSO deployed numerous systems to manage ticketing, payroll, and personnel management in an effort to automate processes and lower costs. In spite of these efforts, the budget for the BSO has risen every year, leading to progressively higher ticket prices and greater need for grants and donations. Like other orchestras around the world, playing Beethoven’s “Symphony No. 9” requires a conductor and a minimum number of violinists, cellists, horn players, percussionists, and other musicians. No amount of information technology deployment can reduce the number of people required to play instruments to deliver the music.

In many ways healthcare is like a symphony orchestra. Although information technology can enhance care planning, assist in medication administration, and reduce duplicative testing, it cannot replace the people required to deliver care services to patients. Nurses are needed to administer medications, therapists are needed to provide treatments, and physicians are needed to diagnose illnesses and provide treatment plans.

On average, hospitals devote close to 70% of their budgets to labor costs. Until robots replace humans in the delivery of patient care, selection of the proper skill mix and number of professionals remains a significant factor that determines cost in provider organizations.

Although information technology cannot replace the staff delivering care to patients, it can assist organizations in choosing the best talent available, help develop that talent, and determine the best way to utilize the skills of these professionals.

To identify the best talent, information technology tools can identify an employee’s “behavioral DNA”—his or her behavioral, cognitive, and cultural traits. Organizations then compare this prospective employee’s “DNA” to the “DNA” of existing high-performing employees within the organization in an effort to identify individuals who possess a high probability of exceling.

These tools leverage the big data research of behavioral science PhDs in human traits that include ambition, discipline, energy, acceptance of authority, attention to detail, flexibility, conscientiousness, and empathy. By combining the behavioral and performance data, organizations generate a performance profile for a specific position, providing a consistent structure and a common language for evaluation.

Once organizations create and validate a unique position profile, prospective hiring managers compare a candidate’s a pre-employment assessment generated “DNA” to the “DNA” of an ideal candidate for the position. Reports include recommended levels indicative of how well the candidate’s assessment score matches established parameters related to the open position.

Each report explains why a score was earned and creates customized guidelines for each candidate covering best-fit scores, career path planning, interview questions, onboarding, coaching, and feedback. This allows the hiring managers to consider any potential disconnects, and evaluate a candidate before the first interview, resulting in better employee selection. By comparing specific traits of existing employees to their job-related performance data such as safety records, healthcare organizations can create a custom blueprint for each open position and assign employees to departments where their traits are best suited.

Unlike unscientific profiling that slots prospective or current employees into qualified or unqualified job applicant categories based upon intrinsic, biased, and subjective criteria, utilizing “behavioral DNA” evaluations encourages the use of extrinsic criteria that deliver reproducible results. In addition, the process demands the input of less scientific but no less valuable human evaluation that together delivers better results than either method deployed on its own. Finally, rather than providing a binary result of qualified/unqualified, the methodology offers a range of options for managers that includes options for employee development through education and training. This enhances opportunities for the employee and employer while delivering caregivers best suited to serve patients.

Staffing to Patient Needs

Once proper staff members are identified, recruited, and placed in their appropriate roles, organizations must identify the proper tasks for these caregivers so that they are utilized efficiently to deliver the required patient care. Initially, the healthcare industry focused on nurse staffing as a key criteria driving patient care as evidenced by legislation targeting nurse to patient ratios.

For more than a decade, the federal government required hospitals accepting Medicare funding to, “have adequate numbers of licensed registered nurses, licensed practical (vocational) nurses, and other personnel to provide nursing care to all patients as needed. (U.S. National Archives, 2011)”

In 2004, California became the first and only state to date to require minimum nurse-to-patient ratios that must be maintained at all times by every care unit within a hospital. Seven other states require hospitals to maintain standing staffing committees responsible for plans and staffing policy—Connecticut, Illinois, Nevada, Ohio, Oregon, Texas, and Washington—while five states require some form of disclosure and/or public reporting—Illinois, New Jersey, New York, Rhode Island, and Vermont (McEwen & Furillo, 2014).

Although staffing to patient census provides a blunt instrument to identifying the nursing needs of patients, it ignores the availability of valuable evidence-based guidelines that link patient care delivery requirements with a patient’s diagnosis and related acuity. In addition, patient data, newly available from the HITECH Act-driven implementation of electronic medical records (EMRs), allows for a refined evaluation of patient care delivery needs and the staffing skills required. EMR data utilized in patient acuity evaluation produces a robust, accurate assessment of patients and their care requirements, allowing for more accurate clinical staffing.

Although information technology will never replace patient care staff, it offers a means to intelligently recruit and retain skilled caregivers and deploy them in the most efficient way possible to help patients. Unlike other industries that may cut staffing in ways that may negatively impact the consumer experience, healthcare providers must consistently deliver exceptional service to patients who rely upon them for their wellbeing. Utilizing newly available information technology tools offers a way to honor patient needs efficiently and effectively.


Barry Chaiken is the chief medical information officer of Infor. With more than 20 years of experience in medical research, epidemiology, clinical information technology, and patient safety, Chaiken is board certified in general preventive medicine and public health and is a Fellow, former Board member, and chair of HIMSS. As founder of DocsNetwork, Ltd., he worked on quality improvement studies, health IT clinical transformation projects, and clinical investigations for the National Institutes of Health, UK National Health Service, and Boston University Medical School. He is currently an adjunct professor of informatics at Boston University’s School of Management. Chaiken may be contacted at barry.chaiken@infor.com.

 

References

American Nurses Association (2013). Nurse staffing plans and ratios. Retrieved September 18, 2014, from http://www.nursingworld.org/mainmenucategories/policy-advocacy/state/legislative-agenda-reports/state-staffingplansratios

McEwen, D., & Furillo, J. (2014, August 13). State-mandated nurse staffing levels alleviate workloads, leading to lower patient mortality and higher nurse satisfaction. AHRQ Health Care Innovations Exchange. Retrieved September 12, 2014, from http://innovations.ahrq.gov/content.aspx?id=3708&tab=1

U.S. National Archives and Records Administration. (2011, October 1). Title 42. Public health, part 482 to end. Code of Federal Regulations. Retrieved September 12, 2014, from http://www.gpo.gov/fdsys/pkg/CFR-2011-title42-vol5/pdf/CFR-2011-title42-vol5.pdf