JONA Volume 44, Number 10, pp 507-516 Copyright B 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins
THE JOURNAL OF NURSING ADMINISTRATION
Analyzing Staffing Trade-Offs on Acute Care Hospital Units Steven Berkow, JD Kate Vonderhaar, AB Jennifer Stewart, BA
Katherine Virkstis, ND Anne Terry, ScB
Given today’s resource-limited environment, nurse leaders must make judicious staffing decisions to deliver safe, cost-effective care. Investing in 1 element of staffing often requires scaling back in another. A national cross section of acute care hospital unit leaders was surveyed regarding staffing resources, including nurse workload, education, specialty certification, experience, and level of support staff. The authors report findings from the survey and discuss the trade-offs observed among units regarding nurse-to-patient ratios and the proportion of baccalaureate-prepared nurses.
leaders balance the demands on staffing resources have not been widely available. This study aimed to demonstrate how nurse leaders prioritize competing staffing needs and resources at the individual unit level. For example, when leaders enhance nurse-to-patient ratios, where do they scale back with other resources? Understanding how changes in a single staffing variable can impact other elements of the care team can help nurse leaders make more informed staffing decisions. In this article, the authors highlight the evidence supporting the importance of several individual staffing variables on patient outcomes and discuss the challenges nurse leaders face in applying these findings to their units and organizations. The study design is described, and early findings at the unit level are reported. This article discusses a subset of findings from a more comprehensive report, 360-Degree Nurse Staffing Benchmarks: Unit- and SiteSpecific Snapshots.1 In the comprehensive report,1 5 staffing variables were explored: RN-to-patient ratio, RN-to-assistant ratio, nurse education, certification, and experience.
Nurse leaders routinely make difficult decisions about how to structure care teams to deliver safe and costeffective care. These decisions inherently involve tradeoffs among multiple elements of a care team based on various constraints. In making these decisions, historically, nurse leaders have relied on findings in the literature or staffing benchmarks that focus on a single variable such as the ratio of nurses to patients, or the percentage of nurses with a BSN degree. These data can provide helpful information about how to optimize single elements of the care team, but few organizations have the resources to simultaneously enhance the unit’s nurse-to-patient ratio, level of support staff, and RN educational preparation. Unfortunately, reliable benchmarking data on how peer nurse Author Affiliations: Executive Director (Mr Berkow), Consultant (Ms Vonderhaar), Managing Director (Ms Stewart), Practice Manager (Dr Virkstis), Senior Consultant (Ms Terry), Nursing Executive Center, The Advisory Board Company, Washington, DC. The authors are employed by The Advisory Board Company. The authors declare no other conflicts of interest. Correspondence: Ms Vonderhaar, The Advisory Board Company, 2445 M St NW, Washington, DC 20037 ([email protected]). Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.jonajournal.com). DOI: 10.1097/NNA.0000000000000109
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The Effect of Individual Staffing Variables on Patient Outcomes Several studies have examined the effect of nurse-topatient ratios on patient outcomes.2-4 Aiken and colleagues2 reported that an increase of 1 surgical patient in the mean patient load of all surveyed frontline RNs at a hospital was associated with a 7% increase in the probability of mortality and a 7% increase in the probability of failure to rescue. A subsequent study showed that decreasing nurses’ workload by 1 patient per nurse had a particularly strong effect at hospitals with the best working environments, decreasing the odds of 30-day inpatient mortality by 9% and failure to rescue by 10%.3 Kane and colleagues4 conducted a systematic review and metaanalysis of 28 studies examining nurse staffing. The
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studies had different designs, but all reported adjusted odds ratios of patient outcomes. The authors pooled the data and found an increase by 1 RN full-time equivalent (FTE) per patient day was associated with a 9% reduction in odds of death in ICUs, 16% reduction for surgical patients, and 6% for medical patients.4 They also found that an increase by 1 RN FTE per patient day in ICUs was associated with a 30% decrease in the odds of hospital-acquired pneumonia, 51% decrease in the odds of unplanned extubation, 60% decrease in the odds of respiratory failure, and 28% decrease in the odds of cardiac arrest.4 An increase by 1 RN FTE per patient day reduced the odds of failure to rescue by 16% for surgical patients.4 Researchers have studied the impact of the proportion of RNs on the care team.5-8 For medical patients, an increase in the proportion of a hospital’s RN hours from the 25th to the 75th percentile was associated with a decrease in 6 of 11 outcomes potentially sensitive to nursing, including a 3.5% decrease in length of stay, 9.4% decrease in shock or cardiac arrest, 2.5% decrease in failure to rescue, and 6.4% decrease in hospital-acquired pneumonia.5 A 10% increase in a hospital’s proportion of RNs was associated with a 9.5% decrease in the probability of a surgical patient developing pneumonia.6 A 10% increase in a hospital’s proportion of RNs has also been associated with 6 fewer deaths for every 1000 discharged medical patients.7 Several studies suggest better outcomes are associated with a greater proportion of BSN RNs.3,8-11 A 10% increase in the proportion of RNs with BSN degrees across an entire institution has been associated with a 4% to 6% decrease in the probability of mortality and failure to rescue in surgical patients.3,9,10 Across a hospital, a 10-point increase in the % of BSNs has been associated with an average reduction of 2.12 deaths per 1000 surgical patients and 7.47 deaths per 1000 surgical patients with complications.11 The impact of nurse experience on patient outcomes is unclear. One study showed lower rates of reported medication errors were associated with higher mean RN experience on a unit,12 but others have found no significant impact of mean years of RN experience at a hospital on mortality and failure to rescue in surgical patients.9,10 Findings on the impact of specialty certification are also mixed. Kendall-Gallagher and colleagues10 found no independent effect of certification on mortality or failure to rescue, but a 10% increase in a hospital’s proportion of RNs with a BSN degree and specialty certification was associated with a 2% decrease in the probability of both outcomes.
Facing Inherent Trade-Offs With Every Staffing Decision Nurse leaders must incorporate these evidence-based findings into the staffing decisions they make for their
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organization or unit, while also considering the potential costs of enhancing the care team. RNs cost more than nursing assistants (NAs); according to the Bureau of Labor Statistics’ 2013 estimate, the mean hourly wage is $33.94 for RNs and $13.53 for NAs in hospitals.13 BSN RNs can cost more than RNs with an associate’s degree in nursing (ADN); 37.9% of urban hospitals and 24.4% of rural hospitals pay RNs a higher salary once they complete their BSN14; 25.8% of urban hospitals and 17.0% of rural hospitals pay a salary differential, usually less than $3,000 per year, between BSN and ADN RNs.14 Organizations may also pay more for specialty-certified RNs. In a survey of perioperative staff nurses, leaders, and educators, about 40% of respondents indicated their facility pays RNs more for holding a certification, most typically in the form of an addition to base pay.15 Few nurse leaders can invest in all elements of the care team at once, so where should they begin? The literature suggests enhancing nurse-to-patient ratios and the proportion of BSN nurses may lead to improved patient outcomes. But the findings do not describe the trade-offs these investments may require. In other words, in which elements of the care team may leaders need to scale back, so they can invest in another area of the team, such as richer staffing ratios? To date, the best quantitative data for understanding staffing trade-offs have come from California, where the state legislature implemented minimum nurse staff ing ratios in 2004. Across the state, the number of patients assigned per nurse decreased following implementation of the minimum staffing law, but the use of unlicensed personnel also dropped.16-18 One study found that 42% of surveyed California nurses reported a decrease in patients assigned per nurse, but 34% also reported a decrease in the use of unlicensed personnel.16 Twenty-seven percent reported a decrease in nonnursing support services, such as housekeeping and unit clerks, following implementation of the law.16 Another study found the number of patients per RN decreased by an average of 1.5 patients on medical-surgical units between 2002 and 2006.17 During the same time, the percentage of care delivered by unlicensed personnel on medical-surgical units decreased from 33% to 24%.17 These findings suggest California nurse leaders likely had to shift some of their budget away from support staff in order to invest in more favorable nurse-to-patient ratios. As noted by Donaldson and Shapiro,18 lower levels of support staff may mean RNs are spending more time on work that could be safely accomplished by someone elseVand less time on work that requires RN skills. Existing research based on California’s experience provides insight into staffing trade-offs nurse leaders made over time in 1 state. However, data have not been published quantifying trade-offs among care team elements at the individual unit level. The Nursing Executive
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Center (NEC ) assembled the 360-degree nurse benchmarking database to fill this gap. A
A
Methods Survey Instruments In spring 2013, the NEC conducted an online survey of nurse leaders with the aim of creating a database of nurse staffing data and outcomes across a variety of settings: acute care hospital units, outpatient ancillary departments, physician offices, ambulatory centers, and postYacute care organizations. Two thousand six hundred thirty-three nurse leaders from 617 current or former member institutions submitted data via an online survey. The database contains staffing data from 19 different types of acute care hospital units: 2 214 individual units in total. The authors analyzed multiple variables from each unit to quantify the trade-offs nurse leaders make regarding nurse workload, education, specialty certification, experience, and level of support staff. There were 3 versions of the survey based on respondents’ main work site: acute care hospital unit, outpatient site (including outpatient ancillary departments, physician offices, and ambulatory centers), and postY acute care organization (see Documents, Supplemental Digital Contents 1 [http://links.lww.com/JONA/A336] 2, [http://links.lww.com/JONA/A337], and 3 [http://links.lww .com/JONA/A338], for the surveys). Researchers developed the survey instruments using an iterative process. They began by consulting with data and staffing experts to create the initial survey drafts. These drafts were reviewed by nurse leaders and other experts in a variety of leadership roles and care settings for content validity. Researchers repeatedly revised the survey instruments until all recommendations had been considered and typically incorporated. The survey for acute care hospital units (see Document, Supplemental Digital Content 1, http:// links.lww.com/JONA/A336) included 27 questions about respondents’ role, main work site characteristics (including unit type, teaching status, Magnet status, bed size, union representation, and requirements for RNs to have a BSN degree), work intensity (including the unit’s nurse-to-patient ratio; starting census; and number of admissions, transfers, and discharges), level of support (including the unit’s number of dedicated nurse aides, pharmacists, environmental service staff, patient transport technicians, and secretaries), nurse education and experience (including the % of staff RNs with a BSN degree, the % of staff RNs with G1 year of experience, and the % of staff RNs with 95 years of experience), and unit performance (including the unit’s number of patient falls, number of pressure ulcers, and average ‘‘willingness to recommend’’ patient satisfaction score). The survey for outpatient sites (see Document, Supplemental Digital Content 2, http://links.lww.com/JONA/ A
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A337) included 19 questions about respondents’ role, main work site characteristics (including type of outpatient site, number of days open per week, number of days open past 6 PM, number and type of staff usually present on a typical weekday, nurse reporting relationships, and union representation), work intensity (including the number of patients seen during a typical weekday), nurse education and experience, and the average ‘‘willingness to recommend’’ patient satisfaction score. The survey for postYacute care organizations (see Document, Supplemental Digital Content 3, http://links .lww.com/JONA/A338) included 2 sets of questions depending on whether the survey respondent worked at a postYacute care facility (skilled nursing facility or longterm acute care hospital) or at a postYacute care service provider (home health agency or hospice provider). The questions for postYacute care facilities mirrored the questions asked for acute care hospital units. The questions for postYacute care service providers included main work site characteristics (including site type and nurse reporting relationships), work intensity (including the number of patients cared for on a typical weekday), nurse education and experience, and the average ‘‘willingness to recommend’’ patient satisfaction score. Survey respondents received the appropriate survey version after answering an initial question about their main work site (acute care hospital unit, outpatient site, or postYacute care organization). Survey respondents managing multiple sites (such as a nurse director overseeing 91 unit) were instructed to select the site they oversee with the largest number of staff nurses as their main work site. Survey Respondent Demographics The list of survey recipients included nurse managers and directors at organizations that currently hold or formerly held membership with 1 or more programs at The Advisory Board Company. These leaders had shared their e-mail addresses to access the company’s Web site and receive periodic updates via e-mail. An institutional review board did not review the study, but nurse executives at each organization included in the survey list were alerted via e-mail that the NEC planned to invite nurse managers from their organization to complete an online staffing survey. Nurse executives were given the option to remove their organization’s nurse managers from the center’s e-mail list for the survey. Only 1 organization exercised this option. The authors e-mailed a single survey link to 26 662 healthcare leaders from 1178 facilities. Survey recipients were informed that responses would be reported in aggregate for confidentiality. Four thousand four hundred ninety-five unique respondents (16.9% of the sample) began the survey. To be included in the database, survey responses had to be submitted by a nurse manager, assistant nurse manager, or nurse director. Nurse executives have more formal responsibility for allocating staffing resources across the
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organization, but nurse managers and directors can provide a more accurate picture of staffing variables at the unit level. Responses also had to include the respondent’s main work site type, state, number of nurses providing care at the main work site, and the typical weekday nurse-topatient ratio (for units) or the average number of patients seen at the site each workday (for nonYacute care sites). Two thousand six hundred thirty-three nurse leaders submitted data meeting these criteria (9.9% of the sample). Of these responses, 2 214 were submitted by nurse managers or directors of 19 different types of acute care units. Medicalsurgical unit leaders comprised the largest number of acute care respondents at 19.0%, followed by critical care respondents at 14.4%. The respondents represent all 50 states, with the largest number from the North Central and New England/Middle Atlantic regions; 27.4% of respondents
work on units where RNs are unionized, and 38.6% of respondents work at Magnet-designated hospitals. Table 1 contains additional demographic information about the acute care respondents, their units, and their institutions. Data Analysis The authors performed 2-sided t tests (assuming unequal sample variances) to detect differences in staffing variables between units with different RN-to-patient ratios and levels of BSN preparation. The tests were performed on the data submitted for individual units. For example, a t test was performed to determine if the mean RN-toassistant ratio on medical-surgical units with a 1:4 RN-to-patient ratio was significantly different from the mean RN-to-assistant ratio on medical-surgical units with a 1:6 RN-to-patient ratio.
Table 1. Demographic Information About Acute Care Unit Respondents (Key Demographic Information About the 2,214 Acute Care Respondents Who Submitted Data) % of Total Acute Care Respondents
1 460 338 416
65.9 15.3 18.8
515
23.3
417
18.8
528
23.8
387
17.5
Respondents’ roles
Nurse manager Assistant nurse manager/supervisor Nurse director
Respondents’ geographical distribution
New England/Middle Atlantic (Connecticut, Massachusetts, Maine, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont) South Atlantic (DC, Delaware, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia) North Central (Iowa, Illinois, Indiana, Kansas, Michigan, Minnesota, Missouri, North Dakota, Nebraska, Ohio, South Dakota, Wisconsin) South Central (Alabama, Arkansas, Kentucky, Louisiana, Mississippi, Oklahoma, Tennessee, Texas) Mountain/Pacific (Alaska, Arizona, Colorado, Hawaii, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, Wyoming) California
187
8.4
180
8.1
Cardiac Critical care Emergency department Interventional procedure Medical Medical/surgical Neurology/neurosurgery Nursery/neonatal ICU Obstetrics-gynecology/labor and delivery Observation/short-stay Oncology Operating room Pediatrics PostYacute care unit Psychiatric/behavioral health Rehab Step-down Surgical Telemetry
76 319 138 42 68 421 57 81 169 21 92 125 73 76 121 31 83 94 127
3.4 14.4 6.2 1.9 3.1 19.0 2.6 3.7 7.6 0.9 4.2 5.6 3.3 3.4 5.5 1.4 3.7 4.2 5.7
% of Respondents at unionized sites
603
27.4
% of Respondents at Magnet-designated hospitals
843
38.6
Respondent Main Unit Type
510
n
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Results In September 2013, the NEC published 360-Degree Nurse Staffing Benchmarks: Unit- and Site-Specific Snapshots, a report with comprehensive benchmarks for 19 different types of acute care units and several types of outpatient and postYacute care sites.1 The complete report is available to NEC members, but leaders from nonmember organizations interested in specific unit or site data can contact the corresponding author. The following section describes high-level insights based on the authors’ observations of the data. Developing a Tool for Nurse Leaders: Staffing Trade-Off Analysis Table 2 displays the NEC’s staffing trade-off analysis for medical-surgical units, the acute care unit type with the
largest number of respondents. The table has 2 sections. In the 1st 3 rows of the table, the RN-to-patient ratio is the independent variable, indicated by bold formatting. In the last 3 rows of the table, the percentage of staff RNs with a BSN degree is the independent variable. Each row shows how the value of the independent variable impacts other elements of the care team. For example, the 1st row in Table 2 displays staffing data for medicalsurgical units with a 1:4 RN-to-patient ratio. The 2nd row shows data for medical-surgical units with a 1:5 RN-topatient ratio. Each column shows how a particular element of the care team changes as the independent variable changes. The RN-to-patient ratios shown in the 1st 3 rows of Table 2V1:4, 1:5, and 1:6Vwere the most common ratios in the medical-surgical unit data. The percentage of staff RNs with BSN degrees varied considerably across unit
Table 2. Staffing Trade-Off Analysis for Medical-Surgical Unitsa RN-to-Patient RN-to-Assistant BSN Specialty G1 y of 95 y of Ratiob Ratioc Degreed Certificatione Experiencef Experienceg For units with a 1:4 RN-to-patient ratio, what are the median values of other key nurse staffing variables?h (n = 70)
1:4.0
1:0.43
50%
15%
10%
60%
For units with a 1:5 RN-to-patient ratio, what are the median values of other key nurse staffing variables? (n = 192)
1:5.0
1:0.48
50%
10%
10%
60%
For units with a 1:6 RN-to-patient ratio, what are the median values of other key nurse staffing variables? (n = 69)
1:6.0
1:0.55
40%
10%
15%
60%
For units on which 20% or less of staff RNs have a BSN degree, what are the median values of other key nurse staffing variables?i (n = 68)
1:5.0
1:0.50
15%
5%
10%
65%
For units on which 50% of staff RNs have a BSN degree, what are the median values of other key nurse staffing variables? (n = 55)
1:5.0
1:0.45
50%
10%
10%
60%
For units on which 80% or more of staff RNs have a BSN degree, what are the median values of other key nurse staffing variables? (n = 51)
1:5.0
1:0.43
85%
15%
10%
70%
In the 1st 3 rows of the table, the RN-to-patient ratio is the independent variable, indicated by bold formatting. In the last 3 rows of the table, the percentage of staff RNs with a BSN degree is the independent variable. Reading across each row shows how the value of the independent variable impacts other key elements of the care team. Reading down a column shows how a particular element of the care team changes as the independent variable changes. We selected the RN-to-patient ratios to include in the table based on the most common ratios we found in the data. If you do not see your unit’s RN-to-patient ratio listed in the table, the ratio was not common in our sample. a Nurse managers, assistant nurse managers/supervisors, and nurse directors reported data for the single unit they oversee that has the largest number of staff nurses. b Based on the survey question, ‘‘During a typical weekday shift on this unit, how many patients is each RN usually responsible for?’’ c Based on the survey questions, ‘‘During a typical weekday shift on this unit, approximately how many RNs provide patient care?’’ and ‘‘During a typical weekday shift on this unit, approximately how many unit-based nurse aides or techs (eg, CNAs, PCAs, PCTs) are dedicated to the unit?’’ d Based on the survey question, ‘‘On this unit, approximately what percentage of staff nurses have a BSN degree?’’ e Based on the survey question, ‘‘On this unit, approximately what percentage of RNs hold a national specialty certification directly related to the type of work they do?’’ f Based on the survey question, ‘‘On this unit, approximately what percentage of RNs have less than 1 year of nursing experience?’’ g Based on the survey question, ‘‘On this unit, approximately what percentage of RNs have more than 5 years of nursing experience?’’ h Based on the survey question, ‘‘During a typical weekday shift on this unit, how many patients is each RN usually responsible for?’’ i Based on the survey question, ‘‘On this unit, approximately what percentage of staff nurses have a BSN degree?’’ For the sake of consistency across unit types, we show how 20% or less BSN preparation, 50% preparation, and 80% or more BSN preparation impact other key care team elements.
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types. For the sake of consistency across unit types, researchers analyzed the impact of 20% or less BSN preparation, 50% BSN preparation, and 80% or more BSN preparation. Researchers created similar staffing trade-off analysis tables for several unit and site types (see Document, Supplemental Digital Content 4, http://links.lww.com/ JONA/A339). Although the working conditions, salaries and benefits may vary from acute care, staffing tradeoffs were noted in other care settings as well. Table 3 is a representative analysis from a nonYacute care site:
physician practices. To examine the workload of RNs at nonYacute care sites, the authors compared the number of patients seen at a site during a typical weekday with the number of RNs staffed to the site during a typical weekday. The ratios shown in the 1st 3 rows of Table 3Vsites with 5 to 15 patients daily per RN, sites with 20 to 35 patients daily per RN, and sites with 40 to 55 patients daily per RNVwere the most common ratios in the physician practice data. Because of smaller sample sizes at nonYacute care sites, researchers analyzed the impact of 20% or less BSN
Table 3. Staffing Trade-Off Analysis for Physician Practicesa RN-to-Patient RN-to-LPN RN-to-Assistant BSN Specialty G1 y of 95 y of Ratiob Ratioc Ratioc Degreed Certificatione Experiencef Experienceg For sites with 5-15 patients daily per RN, what are the median values of other key nurse staffing variables?h (n = 24)
1:10.4
1:0.33
1:0.15
55%
8%
0%
88%
For sites with 20 to 35 patients daily per RN, what are the median values of other key nurse staffing variables? (n = 22)
1:27.1
1:0.67
1:0.50
50%
10%
0%
90%
For sites with 40-55 patients daily per RN, what are the median values of other key nurse staffing variables? (n = 18)
1:48.3
1:1.17
1:1.67
63%
8%
0%
100%
For sites at which e20% of staff RNs have a BSN degree, what are the median values of other key nurse staffing variables?i (n = 23)
1:40.0
1:1.25
1:1.00
5%
0%
0%
100%
For sites at which 40%-60% of staff RNs have a BSN degree, what are the median values of other key nurse staffing variables? (n = 23)
1:22.2
1:0.50
1:0.50
50%
5%
0%
90%
For sites at which Q80% of staff RNs have a BSN degree, what are the median values of other key nurse staffing variables? (n = 32)
1:46.3
1:0.75
1:1.00
100%
20%
0%
100%
To examine the workload of RNs at nonYacute care sites, the authors compared the number of patients seen at a site during a typical weekday with the number of RNs staffed to the site during a typical weekday. In the 1st 3 rows of the table, this ratio is the independent variable, indicated by bold formatting. In the last 3 rows of the table, the % of staff RNs with a BSN degree is the independent variable. We selected the RN-to-patient ratios to include in the table based on the most common ratios we found in the data. If you do not see your site’s RN-to-patient ratio listed in the table, the ratio was not common in our sample. a Nurse managers, assistant nurse managers/supervisors, and nurse directors reported data for the single physician practice where they work that has the largest number of staff nurses. b Based on the survey questions, ‘‘During a typical weekday at this site, approximately how many RNs are present?’’ and ‘‘During a typical weekday at this site, approximately how many patients are seen?’’ c Based on the survey questions, ‘‘During a typical weekday at this site, approximately how many RNs are present?’’ and ‘‘During a typical weekday at this site, approximately how many of the following staff are present: licensed practical nurses (LPNs)/licensed vocational nurses (LVNs); assistants (eg, CNAs, PCAs, PCTs, MAs, NAs)?’’ d Based on the survey question, ‘‘At this site, approximately what % of RNs have a BSN degree?’’ e Based on the survey question, ‘‘At this site, approximately what % of RNs hold a national specialty certification directly related to the type of work they do?’’ f Based on the survey question, ‘‘At this site, approximately what % of RNs have less than 1 year of nursing experience?’’ g Based on the survey question, ‘‘At this site, approximately what % of RNs have more than 5 years of nursing experience?’’ h Based on the survey questions, ‘‘During a typical weekday at this site, approximately how many RNs are present?’’ and ‘‘During a typical weekday at this site, approximately how many patients are seen?’’ i Based on the survey question, ‘‘At this site, approximately what % of staff nurses have a BSN degree?’’ For the sake of consistency across site types, we show how 20% or less BSN preparation, 40% to 60% BSN preparation, and 80% or more BSN preparation impact other key care team elements.
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preparation, 40% to 60% BSN preparation, and 80% or more BSN preparation. One-Quarter of Respondents Reported Their Hospital Requires RNs to Earn a BSN Degree Within 5 Years of Hire As shown in Table 4, 24.7% of acute care respondents reported their organization requires new RN hires to earn a BSN degree within 5 years. This % was relatively consistent among different types of hospitals. Respondents at specialty hospitals reported 22.5% of their organizations have the requirement; respondents at teaching hospitals, 24.2%; and respondents at nonteaching hospitals, 25.6%. The percentage was higher (32.3%) for respondents at Magnet-designated organizations and lower (19.7%) for non-Magnet organizations. Compared with 27.4% of respondents at nonunionized organizations, 17.4% of respondents at hospitals where nurses are unionized reported their organizations require new RNs to earn a BSN within 5 years.
More than 1-in-6 Respondents Reported Their Hospital Hires Only RNs With BSN Degrees Of all acute care respondents, 15.3% reported their organizations hire only RNs who already have a BSN degree. This % varied considerably across hospital types, as shown in Table 4. Respondents at nonteaching hospitals reported 8.7% of their organizations hire only BSNs; respondents at specialty hospitals, 14.1%; and respondents at teaching hospitals, 20.9%. The % rose with hospital bed size: only 6.8% of respondents at hospitals with G 200 beds reported their organizations hire only BSNs, but the % rose to 13.3% for respondents at hospitals with 201 to 400 beds, 20.0% for hospitals with 401 to 600 beds, and 23.4% for hospitals with 9 600 beds. Of respondents at Magnet-designated hospitals, 24.9% reported their organizations hire only BSNs, compared with 9.2% of respondents at nonMagnet organizations. Of respondents at hospitals
Table 4. BSN Requirements at Respondents’ Hospitals No: Organization Yes: Organization Organization Hires Does Not Require Requires New RN Only RNs New RNs to Earn to Earn a BSN Who Already a BSN Within 5 y Within 5 y Have a BSN Entire Cohort
n = 2,123
60.0%
24.7%
15.3%
Hospital type
Teaching Community (nonteaching) Specialty
n =1,111 n = 906 n = 71
54.9% 65.7% 63.4%
24.2% 25.6% 22.5%
20.9% 8.7% 14.1%
Region
New England/Middle Atlantic (Connecticut, Massachusetts, Maine, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont) South Atlantic (DC, Delaware, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia) North Central (Iowa, Illinois, Indiana, Kansas, Michigan, Minnesota, Missouri, North Dakota, Nebraska, Ohio, South Dakota, Wisconsin) South Central (Alabama, Arkansas, Kentucky, Louisiana, Mississippi, Oklahoma, Tennessee, Texas) Mountain/Pacific (Alaska, Arizona, Colorado, Hawaii, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, Wyoming) California
n = 497
50.7%
19.7%
29.6%
n = 398
65.3%
29.1%
5.5%
n = 505
59.0%
31.3%
9.7%
n = 369
56.4%
30.1%
13.6%
n = 181
74.6%
16.6%
8.8%
n = 173
69.9%
6.4%
23.7%
n n n n
70.3% 61.6% 56.6% 49.1%
22.9% 25.1% 23.4% 27.4%
6.8% 13.3% 20.0% 23.4%
Hospital bed size
0-200 Beds 201-400 Beds 401-600 Beds 9600 Beds
= = = =
441 825 454 401
Hospital Magnet Magnet designated status Not Magnet designated
n = 810 n = 1,288
42.7% 71.0%
32.3% 19.7%
24.9% 9.2%
Hospital union status
n = 576 n = 1,540
63.7% 58.6%
17.4% 27.4%
18.9% 14.0%
Unionized Not unionized
The percentage of respondents selecting the indicated option for the question, ‘‘If new RN hires do not currently have a BSN degree, does your organization require them to earn one within 5 years?’’
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with unionized nurses, 18.9% reported their organizations hire only BSNs, compared with 14.0% of respondents at nonunionized organizations. Units in Teaching Hospitals and Larger Hospitals Had a Greater Proportion of Staff RNs With a BSN Degree As shown in Table 5, the median % of staff RNs with a BSN degree was 50% across all acute care hospital units. This % was higher (60%) for units in teaching hospitals and lower (45%) for units in nonteaching community hospitals. Likewise, the median was 65% for units at hospitals with more than 600 beds, but only 40% for units in hospitals with 200 beds or fewer.
Units at Magnet-designated hospitals had a median of 60%, compared with 50% for units at non-Magnet hospitals. The median % was 50% regardless of the organization’s unionization status. Units at hospitals in the South Central states had a higher median at 55%, as did units in California hospitals, 53%. On Medical-Surgical Units, RNs Caring for More Patients Tended to Have More Assistants As shown in Table 2, medical-surgical units with a greater number of patients assigned per nurse had a greater number of support staff per nurse. The RN-toassistant ratio on units where RNs cared for 6 patients was significantly different (P G .01) than on units where
Table 5. Percentage of Staff RNs With a BSN Degree BSN Degree
Entire Cohort Hospital type
Teaching Community (nonteaching) Specialty
Region
Hospital bed size
New England/Middle Atlantic (Connecticut, Massachusetts, Maine, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont) South Atlantic (DC, Delaware, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia) North Central (Iowa, Illinois, Indiana, Kansas, Michigan, Minnesota, Missouri, North Dakota, Nebraska, Ohio, South Dakota, Wisconsin) South Central (Alabama, Arkansas, Kentucky, Louisiana, Mississippi, Oklahoma, Tennessee, Texas) Mountain/Pacific (Alaska, Arizona, Colorado, Hawaii, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, Wyoming) California 0-200 Beds 201-400 Beds 401-600 Beds 9600 Beds
Hospital Magnet status
Magnet designated Not Magnet designated
Hospital union status
Unionized Not unionized
n
2 126
Median
50%
n Median n Median n Median
1 115 60% 904 45% 72 50%
n Median
501 50%
n Median n Median n Median n Median
399 50% 506 50% 368 55% 180 50%
n Median
172 53%
n Median n Median n Median n Median
441 40% 825 50% 455 55% 403 65%
n Median n Median
815 60% 1 286 50%
n Median n Median
577 50% 1 542 50%
Based on the survey question, ‘‘On this unit, approximately what percentage of staff nurses have a BSN degree?’’ Responses were collected in 5% increments.
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RNs cared for 5 patients and on units where RNs cared for 4 patients. Medical-Surgical Units on Which RNs Cared for More Patients Tended to Have More RNs With Less Than 1 Year of Experience On medical-surgical units, the % of staff RNs with G 1 year of experience was significantly higher (P G .05) on units where RNs cared for 6 patients than on units where RNs cared for 4 patients. The % of staff RNs with a BSN degree, specialty certification, and 9 5 years of experience did not change significantly among medicalsurgical units with the different RN-to-patient ratios analyzed. Medical-Surgical Units With More BSN-Prepared RNs Tended to Have More Specialty-Certified RNs As shown in Table 2, medical-surgical units with a greater % of staff RNs with a BSN degree tended to have a greater % of staff RNs with a national specialty certification. The % of staff RNs with a specialty certification on medical-surgical units where 80% or more of staff RNs had a BSN degree was significantly greater (P G .01) than that on units where 20% or less of staff RNs had a BSN degree. Medical-Surgical Units With More BSN-Prepared RNs Tended to Have Fewer Patients per RN The number of patients per RN on medical-surgical units with 20% or less BSN preparation was significantly different (P G .01) than on medical-surgical units with 80% or more BSN preparation. The median number of patients per RN was the same on both types of units, but the 25th and 75th percentiles were not. For units with 20% or less BSN preparation, the 25th percentile was 5.0 patients per RN; the 75th percentile was 6.0 patients. For units with 80% or more BSN preparation, the 25th percentile was 4.0 patients per RN; the 75th percentile was 5.0. Medical-surgical units with different levels of BSN preparation did not have significantly different RN-to-assistant ratios or levels of staff experience.
Discussion Study Limitations All survey participants work at organizations that are current or former members of The Advisory Board Company. While the sample represents a broad cross section of organization types and sizes, it may not be representative of all healthcare organizations across the country. The modest number of respondents also limits the strength of the conclusions, particularly for the unit types and nonYacute care settings with the smallest numbers of respondents. The largest number of sur-
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vey participants oversaw medical-surgical units, so much of the preceding analysis focused on this acute care unit type. To allow nurse leaders to complete the benchmarking survey easily, several survey questions asked respondents to estimate the % of staff RNs at their main work site who met particular criteria (eg, the percentage of staff RNs with a BSN degree and the percentage of staff RNs with G1 year of experience). This method of collecting data may not be as accurate as aggregating responses from staff RNs themselves or analyzing personnel records. For these same questions, nurse leaders were asked to estimate percentage to the nearest 5%, which limits the accuracy of the data. The NEC’s Staffing Trade-Off Analysis ToolB enables nurse leaders to see how peers are allocating scarce staffing resources across 5 elements of a care team: nurse workload, education, specialty certification, experience, and level of support staff. However, the tool does not capture several other elements impacting the safety and effectiveness of a care team such as unit-based ancillary staff, educators, and management support. The tool also does not reflect important unit characteristics such as the admission, discharge, transfer index; acuity or patient population characteristics that nurse leaders should consider when making staffing decisions.
Implications for Nurse Leaders Discussions about nurse staffing are often reduced to a single variable, such as the number of patients per nurse or the percentage of BSN RNs. But staffing a unit safely and cost-effectively requires balancing investment across multiple elements of a care team. The NEC’s 360-Degree Nurse Staffing Benchmarks1 provides nurse leaders with quantitative analysis about the trade-offs accompanying changes to a unit’s RN-to-patient ratio or level of BSN preparation. For example, a more favorable RN-to-patient ratio may require decreasing the level of support staff to maintain a consistent labor budget. But fewer support staff on the unit may limit RNs’ ability to practice to the full extent of their skills and training. Reliable support staff can protect nurses’ time for patient education, care coordination, and other work requiring RN skills.19 The benchmarks described here can equip nurse leaders to provide safe, cost-effective patient care by making more informed staffing decisions. Further analysis evaluating the relationships between these different characteristics and patient outcomes including experience and clinical data is indicated. To hear more about the benchmarks and learn how to apply them at your care site, join Kate Vonderhaar for a webconference on Oct. 29 (http://ns.advisory.com/ Nursing-Executive-Center-360-Degree-BenchmarksWebconference).
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References 1. Berkow S, Vonderhaar K, Virkstis K, et al. 360-Degree Nurse Staffing Benchmarks: Unit- and Site-Specific Snapshots. Washington, DC: The Nursing Executive Center, The Advisory Board Company; 2013. 2. Aiken LH, Clarke SP, Sloane DM, Sochalski J, Silber JH. Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA. 2002;288(16):1987-1993. 3. Aiken LH, Cimiotti JP, Sloane DM, Smith HL, Flynn L, Neff DF. Effects of nurse staffing and nurse education on patient deaths in hospitals with different nurse work environments. Med Care. 2011; 49(12):1047-1053. 4. Kane RL, Shamliyan TA, Mueller C, Duval S, Wilt TJ. The association of registered nurse staffing levels and patient outcomes: systematic review and meta-analysis. Med Care. 2007;45(12):1195-1204. 5. Needleman J, Buerhaus P, Mattke S, Stewart M, Zelevinsky K. Nurse-staffing levels and the quality of care in hospitals. N Engl J Med. 2002;346(22):1715-1722. 6. Cho S, Ketefian S, Barkauskas VH, Smith DG. The effects of nurse staffing on adverse events, morbidity, mortality, and medical costs. Nurs Res. 2003;52(2):71-79. 7. Tourangeau AE, Doran DM, McGillis Hall L, et al. Impact of hospital nursing care on 30-day mortality for acute medical patients. J Adv Nurs. 2007;57(1):32-44. 8. Estabrooks CA, Midodzi WK, Cummings GG, Ricker KL, Giovannetti P. The impact of hospital nursing characteristics on 30-day mortality. Nurs Res. 2005;54(2):74-84. 9. Aiken LH, Clarke SP, Cheung RB, Sloane DM, Silber JH. Educational levels of hospital nurses and surgical patient mortality. JAMA. 2003;290(12):1617-1623. 10. Kendall-Gallagher D, Aiken LH, Sloane DM, Cimiotti JP. Nurse specialty certification, inpatient mortality, and failure to rescue. J Nurs Scholarsh. 2011;43(2):188-194.
11. Kutney-Lee A, Sloane DM, Aiken LH. An increase in the number of nurses with baccalaureate degrees is linked to lower rates of postsurgery mortality. Health Aff. 2013;32(3):579-586. 12. Blegen MA, Vaughn TE, Goode CJ. Nurse experience and education: effect on quality of care. J Nurs Adm. 2001;31(1):33-39. 13. Bureau of Labor Statistics. US Department of Labor. May 2013 national industry-specific occupational employment and wage estimates. NAICS 622100Vgeneral medical and surgical hospitals (including private, state, and local government hospitals). http://www.bls.gov/ current/naics4_622100.htm. Accessed May 25, 2014. 14. Pittman P, Herrera CS, Horton K, Thompson PA, Ware JM, Terry M. Healthcare employers’ policies on nurse education. J Healthc Manage. 2013;58(6):399-410. 15. Bacon DR, Stewart KA. Results of the 2013 AORN salary and compensation survey. AORN J. 2013;98(6):569-584. 16. Aiken LH, Sloane DM, Cimiotti JP, et al. Implications of the California nurse staffing mandate for other states. Health Serv Res. 2010;45(4):904-921. 17. Burnes Bolton L, Aydin CE, Donaldson N, et al. Mandated nurse staffing ratios in California: a comparison of staffing and nursingsensitive outcomes pre- and postregulation. Policy Polit Nurs Pract. 2007;8(4):238-250. 18. Donaldson N, Shapiro S. Impact of California mandated acute care hospital nurse staffing ratios: a literature synthesis. Policy Polit Nurs Pract. 2010;11(3):184-201. 19. Berkow S, Virkstis K, Stewart J, Vonderhaar K, Forman A, Katz M. Achieving Top-of-License Nursing Practice: Best Practices for Elevating the Impact of the Frontline Nurse. Washington, DC: The Nursing Executive Center, The Advisory Board Company; 2013.
The Journal of Nursing Administration Instructions for Authors Instructions for Authors can be found online at the address below. To ensure that your manuscript is in compliance with new submission procedures, you should read this document carefully before manuscript preparation. All manuscripts must be submitted electronically through this system.
Please visit http://JONA.EdMgr.com.
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THE JOURNAL OF NURSING ADMINISTRATION
Analyzing Staffing Trade-Offs on Acute Care Hospital Units Steven Berkow, JD Kate Vonderhaar, AB Jennifer Stewart, BA
Katherine Virkstis, ND Anne Terry, ScB
Given today’s resource-limited environment, nurse leaders must make judicious staffing decisions to deliver safe, cost-effective care. Investing in 1 element of staffing often requires scaling back in another. A national cross section of acute care hospital unit leaders was surveyed regarding staffing resources, including nurse workload, education, specialty certification, experience, and level of support staff. The authors report findings from the survey and discuss the trade-offs observed among units regarding nurse-to-patient ratios and the proportion of baccalaureate-prepared nurses.
leaders balance the demands on staffing resources have not been widely available. This study aimed to demonstrate how nurse leaders prioritize competing staffing needs and resources at the individual unit level. For example, when leaders enhance nurse-to-patient ratios, where do they scale back with other resources? Understanding how changes in a single staffing variable can impact other elements of the care team can help nurse leaders make more informed staffing decisions. In this article, the authors highlight the evidence supporting the importance of several individual staffing variables on patient outcomes and discuss the challenges nurse leaders face in applying these findings to their units and organizations. The study design is described, and early findings at the unit level are reported. This article discusses a subset of findings from a more comprehensive report, 360-Degree Nurse Staffing Benchmarks: Unit- and SiteSpecific Snapshots.1 In the comprehensive report,1 5 staffing variables were explored: RN-to-patient ratio, RN-to-assistant ratio, nurse education, certification, and experience.
Nurse leaders routinely make difficult decisions about how to structure care teams to deliver safe and costeffective care. These decisions inherently involve tradeoffs among multiple elements of a care team based on various constraints. In making these decisions, historically, nurse leaders have relied on findings in the literature or staffing benchmarks that focus on a single variable such as the ratio of nurses to patients, or the percentage of nurses with a BSN degree. These data can provide helpful information about how to optimize single elements of the care team, but few organizations have the resources to simultaneously enhance the unit’s nurse-to-patient ratio, level of support staff, and RN educational preparation. Unfortunately, reliable benchmarking data on how peer nurse Author Affiliations: Executive Director (Mr Berkow), Consultant (Ms Vonderhaar), Managing Director (Ms Stewart), Practice Manager (Dr Virkstis), Senior Consultant (Ms Terry), Nursing Executive Center, The Advisory Board Company, Washington, DC. The authors are employed by The Advisory Board Company. The authors declare no other conflicts of interest. Correspondence: Ms Vonderhaar, The Advisory Board Company, 2445 M St NW, Washington, DC 20037 ([email protected]). Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.jonajournal.com). DOI: 10.1097/NNA.0000000000000109
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The Effect of Individual Staffing Variables on Patient Outcomes Several studies have examined the effect of nurse-topatient ratios on patient outcomes.2-4 Aiken and colleagues2 reported that an increase of 1 surgical patient in the mean patient load of all surveyed frontline RNs at a hospital was associated with a 7% increase in the probability of mortality and a 7% increase in the probability of failure to rescue. A subsequent study showed that decreasing nurses’ workload by 1 patient per nurse had a particularly strong effect at hospitals with the best working environments, decreasing the odds of 30-day inpatient mortality by 9% and failure to rescue by 10%.3 Kane and colleagues4 conducted a systematic review and metaanalysis of 28 studies examining nurse staffing. The
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studies had different designs, but all reported adjusted odds ratios of patient outcomes. The authors pooled the data and found an increase by 1 RN full-time equivalent (FTE) per patient day was associated with a 9% reduction in odds of death in ICUs, 16% reduction for surgical patients, and 6% for medical patients.4 They also found that an increase by 1 RN FTE per patient day in ICUs was associated with a 30% decrease in the odds of hospital-acquired pneumonia, 51% decrease in the odds of unplanned extubation, 60% decrease in the odds of respiratory failure, and 28% decrease in the odds of cardiac arrest.4 An increase by 1 RN FTE per patient day reduced the odds of failure to rescue by 16% for surgical patients.4 Researchers have studied the impact of the proportion of RNs on the care team.5-8 For medical patients, an increase in the proportion of a hospital’s RN hours from the 25th to the 75th percentile was associated with a decrease in 6 of 11 outcomes potentially sensitive to nursing, including a 3.5% decrease in length of stay, 9.4% decrease in shock or cardiac arrest, 2.5% decrease in failure to rescue, and 6.4% decrease in hospital-acquired pneumonia.5 A 10% increase in a hospital’s proportion of RNs was associated with a 9.5% decrease in the probability of a surgical patient developing pneumonia.6 A 10% increase in a hospital’s proportion of RNs has also been associated with 6 fewer deaths for every 1000 discharged medical patients.7 Several studies suggest better outcomes are associated with a greater proportion of BSN RNs.3,8-11 A 10% increase in the proportion of RNs with BSN degrees across an entire institution has been associated with a 4% to 6% decrease in the probability of mortality and failure to rescue in surgical patients.3,9,10 Across a hospital, a 10-point increase in the % of BSNs has been associated with an average reduction of 2.12 deaths per 1000 surgical patients and 7.47 deaths per 1000 surgical patients with complications.11 The impact of nurse experience on patient outcomes is unclear. One study showed lower rates of reported medication errors were associated with higher mean RN experience on a unit,12 but others have found no significant impact of mean years of RN experience at a hospital on mortality and failure to rescue in surgical patients.9,10 Findings on the impact of specialty certification are also mixed. Kendall-Gallagher and colleagues10 found no independent effect of certification on mortality or failure to rescue, but a 10% increase in a hospital’s proportion of RNs with a BSN degree and specialty certification was associated with a 2% decrease in the probability of both outcomes.
Facing Inherent Trade-Offs With Every Staffing Decision Nurse leaders must incorporate these evidence-based findings into the staffing decisions they make for their
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organization or unit, while also considering the potential costs of enhancing the care team. RNs cost more than nursing assistants (NAs); according to the Bureau of Labor Statistics’ 2013 estimate, the mean hourly wage is $33.94 for RNs and $13.53 for NAs in hospitals.13 BSN RNs can cost more than RNs with an associate’s degree in nursing (ADN); 37.9% of urban hospitals and 24.4% of rural hospitals pay RNs a higher salary once they complete their BSN14; 25.8% of urban hospitals and 17.0% of rural hospitals pay a salary differential, usually less than $3,000 per year, between BSN and ADN RNs.14 Organizations may also pay more for specialty-certified RNs. In a survey of perioperative staff nurses, leaders, and educators, about 40% of respondents indicated their facility pays RNs more for holding a certification, most typically in the form of an addition to base pay.15 Few nurse leaders can invest in all elements of the care team at once, so where should they begin? The literature suggests enhancing nurse-to-patient ratios and the proportion of BSN nurses may lead to improved patient outcomes. But the findings do not describe the trade-offs these investments may require. In other words, in which elements of the care team may leaders need to scale back, so they can invest in another area of the team, such as richer staffing ratios? To date, the best quantitative data for understanding staffing trade-offs have come from California, where the state legislature implemented minimum nurse staff ing ratios in 2004. Across the state, the number of patients assigned per nurse decreased following implementation of the minimum staffing law, but the use of unlicensed personnel also dropped.16-18 One study found that 42% of surveyed California nurses reported a decrease in patients assigned per nurse, but 34% also reported a decrease in the use of unlicensed personnel.16 Twenty-seven percent reported a decrease in nonnursing support services, such as housekeeping and unit clerks, following implementation of the law.16 Another study found the number of patients per RN decreased by an average of 1.5 patients on medical-surgical units between 2002 and 2006.17 During the same time, the percentage of care delivered by unlicensed personnel on medical-surgical units decreased from 33% to 24%.17 These findings suggest California nurse leaders likely had to shift some of their budget away from support staff in order to invest in more favorable nurse-to-patient ratios. As noted by Donaldson and Shapiro,18 lower levels of support staff may mean RNs are spending more time on work that could be safely accomplished by someone elseVand less time on work that requires RN skills. Existing research based on California’s experience provides insight into staffing trade-offs nurse leaders made over time in 1 state. However, data have not been published quantifying trade-offs among care team elements at the individual unit level. The Nursing Executive
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Center (NEC ) assembled the 360-degree nurse benchmarking database to fill this gap. A
A
Methods Survey Instruments In spring 2013, the NEC conducted an online survey of nurse leaders with the aim of creating a database of nurse staffing data and outcomes across a variety of settings: acute care hospital units, outpatient ancillary departments, physician offices, ambulatory centers, and postYacute care organizations. Two thousand six hundred thirty-three nurse leaders from 617 current or former member institutions submitted data via an online survey. The database contains staffing data from 19 different types of acute care hospital units: 2 214 individual units in total. The authors analyzed multiple variables from each unit to quantify the trade-offs nurse leaders make regarding nurse workload, education, specialty certification, experience, and level of support staff. There were 3 versions of the survey based on respondents’ main work site: acute care hospital unit, outpatient site (including outpatient ancillary departments, physician offices, and ambulatory centers), and postY acute care organization (see Documents, Supplemental Digital Contents 1 [http://links.lww.com/JONA/A336] 2, [http://links.lww.com/JONA/A337], and 3 [http://links.lww .com/JONA/A338], for the surveys). Researchers developed the survey instruments using an iterative process. They began by consulting with data and staffing experts to create the initial survey drafts. These drafts were reviewed by nurse leaders and other experts in a variety of leadership roles and care settings for content validity. Researchers repeatedly revised the survey instruments until all recommendations had been considered and typically incorporated. The survey for acute care hospital units (see Document, Supplemental Digital Content 1, http:// links.lww.com/JONA/A336) included 27 questions about respondents’ role, main work site characteristics (including unit type, teaching status, Magnet status, bed size, union representation, and requirements for RNs to have a BSN degree), work intensity (including the unit’s nurse-to-patient ratio; starting census; and number of admissions, transfers, and discharges), level of support (including the unit’s number of dedicated nurse aides, pharmacists, environmental service staff, patient transport technicians, and secretaries), nurse education and experience (including the % of staff RNs with a BSN degree, the % of staff RNs with G1 year of experience, and the % of staff RNs with 95 years of experience), and unit performance (including the unit’s number of patient falls, number of pressure ulcers, and average ‘‘willingness to recommend’’ patient satisfaction score). The survey for outpatient sites (see Document, Supplemental Digital Content 2, http://links.lww.com/JONA/ A
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A337) included 19 questions about respondents’ role, main work site characteristics (including type of outpatient site, number of days open per week, number of days open past 6 PM, number and type of staff usually present on a typical weekday, nurse reporting relationships, and union representation), work intensity (including the number of patients seen during a typical weekday), nurse education and experience, and the average ‘‘willingness to recommend’’ patient satisfaction score. The survey for postYacute care organizations (see Document, Supplemental Digital Content 3, http://links .lww.com/JONA/A338) included 2 sets of questions depending on whether the survey respondent worked at a postYacute care facility (skilled nursing facility or longterm acute care hospital) or at a postYacute care service provider (home health agency or hospice provider). The questions for postYacute care facilities mirrored the questions asked for acute care hospital units. The questions for postYacute care service providers included main work site characteristics (including site type and nurse reporting relationships), work intensity (including the number of patients cared for on a typical weekday), nurse education and experience, and the average ‘‘willingness to recommend’’ patient satisfaction score. Survey respondents received the appropriate survey version after answering an initial question about their main work site (acute care hospital unit, outpatient site, or postYacute care organization). Survey respondents managing multiple sites (such as a nurse director overseeing 91 unit) were instructed to select the site they oversee with the largest number of staff nurses as their main work site. Survey Respondent Demographics The list of survey recipients included nurse managers and directors at organizations that currently hold or formerly held membership with 1 or more programs at The Advisory Board Company. These leaders had shared their e-mail addresses to access the company’s Web site and receive periodic updates via e-mail. An institutional review board did not review the study, but nurse executives at each organization included in the survey list were alerted via e-mail that the NEC planned to invite nurse managers from their organization to complete an online staffing survey. Nurse executives were given the option to remove their organization’s nurse managers from the center’s e-mail list for the survey. Only 1 organization exercised this option. The authors e-mailed a single survey link to 26 662 healthcare leaders from 1178 facilities. Survey recipients were informed that responses would be reported in aggregate for confidentiality. Four thousand four hundred ninety-five unique respondents (16.9% of the sample) began the survey. To be included in the database, survey responses had to be submitted by a nurse manager, assistant nurse manager, or nurse director. Nurse executives have more formal responsibility for allocating staffing resources across the
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organization, but nurse managers and directors can provide a more accurate picture of staffing variables at the unit level. Responses also had to include the respondent’s main work site type, state, number of nurses providing care at the main work site, and the typical weekday nurse-topatient ratio (for units) or the average number of patients seen at the site each workday (for nonYacute care sites). Two thousand six hundred thirty-three nurse leaders submitted data meeting these criteria (9.9% of the sample). Of these responses, 2 214 were submitted by nurse managers or directors of 19 different types of acute care units. Medicalsurgical unit leaders comprised the largest number of acute care respondents at 19.0%, followed by critical care respondents at 14.4%. The respondents represent all 50 states, with the largest number from the North Central and New England/Middle Atlantic regions; 27.4% of respondents
work on units where RNs are unionized, and 38.6% of respondents work at Magnet-designated hospitals. Table 1 contains additional demographic information about the acute care respondents, their units, and their institutions. Data Analysis The authors performed 2-sided t tests (assuming unequal sample variances) to detect differences in staffing variables between units with different RN-to-patient ratios and levels of BSN preparation. The tests were performed on the data submitted for individual units. For example, a t test was performed to determine if the mean RN-toassistant ratio on medical-surgical units with a 1:4 RN-to-patient ratio was significantly different from the mean RN-to-assistant ratio on medical-surgical units with a 1:6 RN-to-patient ratio.
Table 1. Demographic Information About Acute Care Unit Respondents (Key Demographic Information About the 2,214 Acute Care Respondents Who Submitted Data) % of Total Acute Care Respondents
1 460 338 416
65.9 15.3 18.8
515
23.3
417
18.8
528
23.8
387
17.5
Respondents’ roles
Nurse manager Assistant nurse manager/supervisor Nurse director
Respondents’ geographical distribution
New England/Middle Atlantic (Connecticut, Massachusetts, Maine, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont) South Atlantic (DC, Delaware, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia) North Central (Iowa, Illinois, Indiana, Kansas, Michigan, Minnesota, Missouri, North Dakota, Nebraska, Ohio, South Dakota, Wisconsin) South Central (Alabama, Arkansas, Kentucky, Louisiana, Mississippi, Oklahoma, Tennessee, Texas) Mountain/Pacific (Alaska, Arizona, Colorado, Hawaii, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, Wyoming) California
187
8.4
180
8.1
Cardiac Critical care Emergency department Interventional procedure Medical Medical/surgical Neurology/neurosurgery Nursery/neonatal ICU Obstetrics-gynecology/labor and delivery Observation/short-stay Oncology Operating room Pediatrics PostYacute care unit Psychiatric/behavioral health Rehab Step-down Surgical Telemetry
76 319 138 42 68 421 57 81 169 21 92 125 73 76 121 31 83 94 127
3.4 14.4 6.2 1.9 3.1 19.0 2.6 3.7 7.6 0.9 4.2 5.6 3.3 3.4 5.5 1.4 3.7 4.2 5.7
% of Respondents at unionized sites
603
27.4
% of Respondents at Magnet-designated hospitals
843
38.6
Respondent Main Unit Type
510
n
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Results In September 2013, the NEC published 360-Degree Nurse Staffing Benchmarks: Unit- and Site-Specific Snapshots, a report with comprehensive benchmarks for 19 different types of acute care units and several types of outpatient and postYacute care sites.1 The complete report is available to NEC members, but leaders from nonmember organizations interested in specific unit or site data can contact the corresponding author. The following section describes high-level insights based on the authors’ observations of the data. Developing a Tool for Nurse Leaders: Staffing Trade-Off Analysis Table 2 displays the NEC’s staffing trade-off analysis for medical-surgical units, the acute care unit type with the
largest number of respondents. The table has 2 sections. In the 1st 3 rows of the table, the RN-to-patient ratio is the independent variable, indicated by bold formatting. In the last 3 rows of the table, the percentage of staff RNs with a BSN degree is the independent variable. Each row shows how the value of the independent variable impacts other elements of the care team. For example, the 1st row in Table 2 displays staffing data for medicalsurgical units with a 1:4 RN-to-patient ratio. The 2nd row shows data for medical-surgical units with a 1:5 RN-topatient ratio. Each column shows how a particular element of the care team changes as the independent variable changes. The RN-to-patient ratios shown in the 1st 3 rows of Table 2V1:4, 1:5, and 1:6Vwere the most common ratios in the medical-surgical unit data. The percentage of staff RNs with BSN degrees varied considerably across unit
Table 2. Staffing Trade-Off Analysis for Medical-Surgical Unitsa RN-to-Patient RN-to-Assistant BSN Specialty G1 y of 95 y of Ratiob Ratioc Degreed Certificatione Experiencef Experienceg For units with a 1:4 RN-to-patient ratio, what are the median values of other key nurse staffing variables?h (n = 70)
1:4.0
1:0.43
50%
15%
10%
60%
For units with a 1:5 RN-to-patient ratio, what are the median values of other key nurse staffing variables? (n = 192)
1:5.0
1:0.48
50%
10%
10%
60%
For units with a 1:6 RN-to-patient ratio, what are the median values of other key nurse staffing variables? (n = 69)
1:6.0
1:0.55
40%
10%
15%
60%
For units on which 20% or less of staff RNs have a BSN degree, what are the median values of other key nurse staffing variables?i (n = 68)
1:5.0
1:0.50
15%
5%
10%
65%
For units on which 50% of staff RNs have a BSN degree, what are the median values of other key nurse staffing variables? (n = 55)
1:5.0
1:0.45
50%
10%
10%
60%
For units on which 80% or more of staff RNs have a BSN degree, what are the median values of other key nurse staffing variables? (n = 51)
1:5.0
1:0.43
85%
15%
10%
70%
In the 1st 3 rows of the table, the RN-to-patient ratio is the independent variable, indicated by bold formatting. In the last 3 rows of the table, the percentage of staff RNs with a BSN degree is the independent variable. Reading across each row shows how the value of the independent variable impacts other key elements of the care team. Reading down a column shows how a particular element of the care team changes as the independent variable changes. We selected the RN-to-patient ratios to include in the table based on the most common ratios we found in the data. If you do not see your unit’s RN-to-patient ratio listed in the table, the ratio was not common in our sample. a Nurse managers, assistant nurse managers/supervisors, and nurse directors reported data for the single unit they oversee that has the largest number of staff nurses. b Based on the survey question, ‘‘During a typical weekday shift on this unit, how many patients is each RN usually responsible for?’’ c Based on the survey questions, ‘‘During a typical weekday shift on this unit, approximately how many RNs provide patient care?’’ and ‘‘During a typical weekday shift on this unit, approximately how many unit-based nurse aides or techs (eg, CNAs, PCAs, PCTs) are dedicated to the unit?’’ d Based on the survey question, ‘‘On this unit, approximately what percentage of staff nurses have a BSN degree?’’ e Based on the survey question, ‘‘On this unit, approximately what percentage of RNs hold a national specialty certification directly related to the type of work they do?’’ f Based on the survey question, ‘‘On this unit, approximately what percentage of RNs have less than 1 year of nursing experience?’’ g Based on the survey question, ‘‘On this unit, approximately what percentage of RNs have more than 5 years of nursing experience?’’ h Based on the survey question, ‘‘During a typical weekday shift on this unit, how many patients is each RN usually responsible for?’’ i Based on the survey question, ‘‘On this unit, approximately what percentage of staff nurses have a BSN degree?’’ For the sake of consistency across unit types, we show how 20% or less BSN preparation, 50% preparation, and 80% or more BSN preparation impact other key care team elements.
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types. For the sake of consistency across unit types, researchers analyzed the impact of 20% or less BSN preparation, 50% BSN preparation, and 80% or more BSN preparation. Researchers created similar staffing trade-off analysis tables for several unit and site types (see Document, Supplemental Digital Content 4, http://links.lww.com/ JONA/A339). Although the working conditions, salaries and benefits may vary from acute care, staffing tradeoffs were noted in other care settings as well. Table 3 is a representative analysis from a nonYacute care site:
physician practices. To examine the workload of RNs at nonYacute care sites, the authors compared the number of patients seen at a site during a typical weekday with the number of RNs staffed to the site during a typical weekday. The ratios shown in the 1st 3 rows of Table 3Vsites with 5 to 15 patients daily per RN, sites with 20 to 35 patients daily per RN, and sites with 40 to 55 patients daily per RNVwere the most common ratios in the physician practice data. Because of smaller sample sizes at nonYacute care sites, researchers analyzed the impact of 20% or less BSN
Table 3. Staffing Trade-Off Analysis for Physician Practicesa RN-to-Patient RN-to-LPN RN-to-Assistant BSN Specialty G1 y of 95 y of Ratiob Ratioc Ratioc Degreed Certificatione Experiencef Experienceg For sites with 5-15 patients daily per RN, what are the median values of other key nurse staffing variables?h (n = 24)
1:10.4
1:0.33
1:0.15
55%
8%
0%
88%
For sites with 20 to 35 patients daily per RN, what are the median values of other key nurse staffing variables? (n = 22)
1:27.1
1:0.67
1:0.50
50%
10%
0%
90%
For sites with 40-55 patients daily per RN, what are the median values of other key nurse staffing variables? (n = 18)
1:48.3
1:1.17
1:1.67
63%
8%
0%
100%
For sites at which e20% of staff RNs have a BSN degree, what are the median values of other key nurse staffing variables?i (n = 23)
1:40.0
1:1.25
1:1.00
5%
0%
0%
100%
For sites at which 40%-60% of staff RNs have a BSN degree, what are the median values of other key nurse staffing variables? (n = 23)
1:22.2
1:0.50
1:0.50
50%
5%
0%
90%
For sites at which Q80% of staff RNs have a BSN degree, what are the median values of other key nurse staffing variables? (n = 32)
1:46.3
1:0.75
1:1.00
100%
20%
0%
100%
To examine the workload of RNs at nonYacute care sites, the authors compared the number of patients seen at a site during a typical weekday with the number of RNs staffed to the site during a typical weekday. In the 1st 3 rows of the table, this ratio is the independent variable, indicated by bold formatting. In the last 3 rows of the table, the % of staff RNs with a BSN degree is the independent variable. We selected the RN-to-patient ratios to include in the table based on the most common ratios we found in the data. If you do not see your site’s RN-to-patient ratio listed in the table, the ratio was not common in our sample. a Nurse managers, assistant nurse managers/supervisors, and nurse directors reported data for the single physician practice where they work that has the largest number of staff nurses. b Based on the survey questions, ‘‘During a typical weekday at this site, approximately how many RNs are present?’’ and ‘‘During a typical weekday at this site, approximately how many patients are seen?’’ c Based on the survey questions, ‘‘During a typical weekday at this site, approximately how many RNs are present?’’ and ‘‘During a typical weekday at this site, approximately how many of the following staff are present: licensed practical nurses (LPNs)/licensed vocational nurses (LVNs); assistants (eg, CNAs, PCAs, PCTs, MAs, NAs)?’’ d Based on the survey question, ‘‘At this site, approximately what % of RNs have a BSN degree?’’ e Based on the survey question, ‘‘At this site, approximately what % of RNs hold a national specialty certification directly related to the type of work they do?’’ f Based on the survey question, ‘‘At this site, approximately what % of RNs have less than 1 year of nursing experience?’’ g Based on the survey question, ‘‘At this site, approximately what % of RNs have more than 5 years of nursing experience?’’ h Based on the survey questions, ‘‘During a typical weekday at this site, approximately how many RNs are present?’’ and ‘‘During a typical weekday at this site, approximately how many patients are seen?’’ i Based on the survey question, ‘‘At this site, approximately what % of staff nurses have a BSN degree?’’ For the sake of consistency across site types, we show how 20% or less BSN preparation, 40% to 60% BSN preparation, and 80% or more BSN preparation impact other key care team elements.
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preparation, 40% to 60% BSN preparation, and 80% or more BSN preparation. One-Quarter of Respondents Reported Their Hospital Requires RNs to Earn a BSN Degree Within 5 Years of Hire As shown in Table 4, 24.7% of acute care respondents reported their organization requires new RN hires to earn a BSN degree within 5 years. This % was relatively consistent among different types of hospitals. Respondents at specialty hospitals reported 22.5% of their organizations have the requirement; respondents at teaching hospitals, 24.2%; and respondents at nonteaching hospitals, 25.6%. The percentage was higher (32.3%) for respondents at Magnet-designated organizations and lower (19.7%) for non-Magnet organizations. Compared with 27.4% of respondents at nonunionized organizations, 17.4% of respondents at hospitals where nurses are unionized reported their organizations require new RNs to earn a BSN within 5 years.
More than 1-in-6 Respondents Reported Their Hospital Hires Only RNs With BSN Degrees Of all acute care respondents, 15.3% reported their organizations hire only RNs who already have a BSN degree. This % varied considerably across hospital types, as shown in Table 4. Respondents at nonteaching hospitals reported 8.7% of their organizations hire only BSNs; respondents at specialty hospitals, 14.1%; and respondents at teaching hospitals, 20.9%. The % rose with hospital bed size: only 6.8% of respondents at hospitals with G 200 beds reported their organizations hire only BSNs, but the % rose to 13.3% for respondents at hospitals with 201 to 400 beds, 20.0% for hospitals with 401 to 600 beds, and 23.4% for hospitals with 9 600 beds. Of respondents at Magnet-designated hospitals, 24.9% reported their organizations hire only BSNs, compared with 9.2% of respondents at nonMagnet organizations. Of respondents at hospitals
Table 4. BSN Requirements at Respondents’ Hospitals No: Organization Yes: Organization Organization Hires Does Not Require Requires New RN Only RNs New RNs to Earn to Earn a BSN Who Already a BSN Within 5 y Within 5 y Have a BSN Entire Cohort
n = 2,123
60.0%
24.7%
15.3%
Hospital type
Teaching Community (nonteaching) Specialty
n =1,111 n = 906 n = 71
54.9% 65.7% 63.4%
24.2% 25.6% 22.5%
20.9% 8.7% 14.1%
Region
New England/Middle Atlantic (Connecticut, Massachusetts, Maine, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont) South Atlantic (DC, Delaware, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia) North Central (Iowa, Illinois, Indiana, Kansas, Michigan, Minnesota, Missouri, North Dakota, Nebraska, Ohio, South Dakota, Wisconsin) South Central (Alabama, Arkansas, Kentucky, Louisiana, Mississippi, Oklahoma, Tennessee, Texas) Mountain/Pacific (Alaska, Arizona, Colorado, Hawaii, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, Wyoming) California
n = 497
50.7%
19.7%
29.6%
n = 398
65.3%
29.1%
5.5%
n = 505
59.0%
31.3%
9.7%
n = 369
56.4%
30.1%
13.6%
n = 181
74.6%
16.6%
8.8%
n = 173
69.9%
6.4%
23.7%
n n n n
70.3% 61.6% 56.6% 49.1%
22.9% 25.1% 23.4% 27.4%
6.8% 13.3% 20.0% 23.4%
Hospital bed size
0-200 Beds 201-400 Beds 401-600 Beds 9600 Beds
= = = =
441 825 454 401
Hospital Magnet Magnet designated status Not Magnet designated
n = 810 n = 1,288
42.7% 71.0%
32.3% 19.7%
24.9% 9.2%
Hospital union status
n = 576 n = 1,540
63.7% 58.6%
17.4% 27.4%
18.9% 14.0%
Unionized Not unionized
The percentage of respondents selecting the indicated option for the question, ‘‘If new RN hires do not currently have a BSN degree, does your organization require them to earn one within 5 years?’’
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with unionized nurses, 18.9% reported their organizations hire only BSNs, compared with 14.0% of respondents at nonunionized organizations. Units in Teaching Hospitals and Larger Hospitals Had a Greater Proportion of Staff RNs With a BSN Degree As shown in Table 5, the median % of staff RNs with a BSN degree was 50% across all acute care hospital units. This % was higher (60%) for units in teaching hospitals and lower (45%) for units in nonteaching community hospitals. Likewise, the median was 65% for units at hospitals with more than 600 beds, but only 40% for units in hospitals with 200 beds or fewer.
Units at Magnet-designated hospitals had a median of 60%, compared with 50% for units at non-Magnet hospitals. The median % was 50% regardless of the organization’s unionization status. Units at hospitals in the South Central states had a higher median at 55%, as did units in California hospitals, 53%. On Medical-Surgical Units, RNs Caring for More Patients Tended to Have More Assistants As shown in Table 2, medical-surgical units with a greater number of patients assigned per nurse had a greater number of support staff per nurse. The RN-toassistant ratio on units where RNs cared for 6 patients was significantly different (P G .01) than on units where
Table 5. Percentage of Staff RNs With a BSN Degree BSN Degree
Entire Cohort Hospital type
Teaching Community (nonteaching) Specialty
Region
Hospital bed size
New England/Middle Atlantic (Connecticut, Massachusetts, Maine, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont) South Atlantic (DC, Delaware, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia) North Central (Iowa, Illinois, Indiana, Kansas, Michigan, Minnesota, Missouri, North Dakota, Nebraska, Ohio, South Dakota, Wisconsin) South Central (Alabama, Arkansas, Kentucky, Louisiana, Mississippi, Oklahoma, Tennessee, Texas) Mountain/Pacific (Alaska, Arizona, Colorado, Hawaii, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, Wyoming) California 0-200 Beds 201-400 Beds 401-600 Beds 9600 Beds
Hospital Magnet status
Magnet designated Not Magnet designated
Hospital union status
Unionized Not unionized
n
2 126
Median
50%
n Median n Median n Median
1 115 60% 904 45% 72 50%
n Median
501 50%
n Median n Median n Median n Median
399 50% 506 50% 368 55% 180 50%
n Median
172 53%
n Median n Median n Median n Median
441 40% 825 50% 455 55% 403 65%
n Median n Median
815 60% 1 286 50%
n Median n Median
577 50% 1 542 50%
Based on the survey question, ‘‘On this unit, approximately what percentage of staff nurses have a BSN degree?’’ Responses were collected in 5% increments.
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RNs cared for 5 patients and on units where RNs cared for 4 patients. Medical-Surgical Units on Which RNs Cared for More Patients Tended to Have More RNs With Less Than 1 Year of Experience On medical-surgical units, the % of staff RNs with G 1 year of experience was significantly higher (P G .05) on units where RNs cared for 6 patients than on units where RNs cared for 4 patients. The % of staff RNs with a BSN degree, specialty certification, and 9 5 years of experience did not change significantly among medicalsurgical units with the different RN-to-patient ratios analyzed. Medical-Surgical Units With More BSN-Prepared RNs Tended to Have More Specialty-Certified RNs As shown in Table 2, medical-surgical units with a greater % of staff RNs with a BSN degree tended to have a greater % of staff RNs with a national specialty certification. The % of staff RNs with a specialty certification on medical-surgical units where 80% or more of staff RNs had a BSN degree was significantly greater (P G .01) than that on units where 20% or less of staff RNs had a BSN degree. Medical-Surgical Units With More BSN-Prepared RNs Tended to Have Fewer Patients per RN The number of patients per RN on medical-surgical units with 20% or less BSN preparation was significantly different (P G .01) than on medical-surgical units with 80% or more BSN preparation. The median number of patients per RN was the same on both types of units, but the 25th and 75th percentiles were not. For units with 20% or less BSN preparation, the 25th percentile was 5.0 patients per RN; the 75th percentile was 6.0 patients. For units with 80% or more BSN preparation, the 25th percentile was 4.0 patients per RN; the 75th percentile was 5.0. Medical-surgical units with different levels of BSN preparation did not have significantly different RN-to-assistant ratios or levels of staff experience.
Discussion Study Limitations All survey participants work at organizations that are current or former members of The Advisory Board Company. While the sample represents a broad cross section of organization types and sizes, it may not be representative of all healthcare organizations across the country. The modest number of respondents also limits the strength of the conclusions, particularly for the unit types and nonYacute care settings with the smallest numbers of respondents. The largest number of sur-
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vey participants oversaw medical-surgical units, so much of the preceding analysis focused on this acute care unit type. To allow nurse leaders to complete the benchmarking survey easily, several survey questions asked respondents to estimate the % of staff RNs at their main work site who met particular criteria (eg, the percentage of staff RNs with a BSN degree and the percentage of staff RNs with G1 year of experience). This method of collecting data may not be as accurate as aggregating responses from staff RNs themselves or analyzing personnel records. For these same questions, nurse leaders were asked to estimate percentage to the nearest 5%, which limits the accuracy of the data. The NEC’s Staffing Trade-Off Analysis ToolB enables nurse leaders to see how peers are allocating scarce staffing resources across 5 elements of a care team: nurse workload, education, specialty certification, experience, and level of support staff. However, the tool does not capture several other elements impacting the safety and effectiveness of a care team such as unit-based ancillary staff, educators, and management support. The tool also does not reflect important unit characteristics such as the admission, discharge, transfer index; acuity or patient population characteristics that nurse leaders should consider when making staffing decisions.
Implications for Nurse Leaders Discussions about nurse staffing are often reduced to a single variable, such as the number of patients per nurse or the percentage of BSN RNs. But staffing a unit safely and cost-effectively requires balancing investment across multiple elements of a care team. The NEC’s 360-Degree Nurse Staffing Benchmarks1 provides nurse leaders with quantitative analysis about the trade-offs accompanying changes to a unit’s RN-to-patient ratio or level of BSN preparation. For example, a more favorable RN-to-patient ratio may require decreasing the level of support staff to maintain a consistent labor budget. But fewer support staff on the unit may limit RNs’ ability to practice to the full extent of their skills and training. Reliable support staff can protect nurses’ time for patient education, care coordination, and other work requiring RN skills.19 The benchmarks described here can equip nurse leaders to provide safe, cost-effective patient care by making more informed staffing decisions. Further analysis evaluating the relationships between these different characteristics and patient outcomes including experience and clinical data is indicated. To hear more about the benchmarks and learn how to apply them at your care site, join Kate Vonderhaar for a webconference on Oct. 29 (http://ns.advisory.com/ Nursing-Executive-Center-360-Degree-BenchmarksWebconference).
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References 1. Berkow S, Vonderhaar K, Virkstis K, et al. 360-Degree Nurse Staffing Benchmarks: Unit- and Site-Specific Snapshots. Washington, DC: The Nursing Executive Center, The Advisory Board Company; 2013. 2. Aiken LH, Clarke SP, Sloane DM, Sochalski J, Silber JH. Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA. 2002;288(16):1987-1993. 3. Aiken LH, Cimiotti JP, Sloane DM, Smith HL, Flynn L, Neff DF. Effects of nurse staffing and nurse education on patient deaths in hospitals with different nurse work environments. Med Care. 2011; 49(12):1047-1053. 4. Kane RL, Shamliyan TA, Mueller C, Duval S, Wilt TJ. The association of registered nurse staffing levels and patient outcomes: systematic review and meta-analysis. Med Care. 2007;45(12):1195-1204. 5. Needleman J, Buerhaus P, Mattke S, Stewart M, Zelevinsky K. Nurse-staffing levels and the quality of care in hospitals. N Engl J Med. 2002;346(22):1715-1722. 6. Cho S, Ketefian S, Barkauskas VH, Smith DG. The effects of nurse staffing on adverse events, morbidity, mortality, and medical costs. Nurs Res. 2003;52(2):71-79. 7. Tourangeau AE, Doran DM, McGillis Hall L, et al. Impact of hospital nursing care on 30-day mortality for acute medical patients. J Adv Nurs. 2007;57(1):32-44. 8. Estabrooks CA, Midodzi WK, Cummings GG, Ricker KL, Giovannetti P. The impact of hospital nursing characteristics on 30-day mortality. Nurs Res. 2005;54(2):74-84. 9. Aiken LH, Clarke SP, Cheung RB, Sloane DM, Silber JH. Educational levels of hospital nurses and surgical patient mortality. JAMA. 2003;290(12):1617-1623. 10. Kendall-Gallagher D, Aiken LH, Sloane DM, Cimiotti JP. Nurse specialty certification, inpatient mortality, and failure to rescue. J Nurs Scholarsh. 2011;43(2):188-194.
11. Kutney-Lee A, Sloane DM, Aiken LH. An increase in the number of nurses with baccalaureate degrees is linked to lower rates of postsurgery mortality. Health Aff. 2013;32(3):579-586. 12. Blegen MA, Vaughn TE, Goode CJ. Nurse experience and education: effect on quality of care. J Nurs Adm. 2001;31(1):33-39. 13. Bureau of Labor Statistics. US Department of Labor. May 2013 national industry-specific occupational employment and wage estimates. NAICS 622100Vgeneral medical and surgical hospitals (including private, state, and local government hospitals). http://www.bls.gov/ current/naics4_622100.htm. Accessed May 25, 2014. 14. Pittman P, Herrera CS, Horton K, Thompson PA, Ware JM, Terry M. Healthcare employers’ policies on nurse education. J Healthc Manage. 2013;58(6):399-410. 15. Bacon DR, Stewart KA. Results of the 2013 AORN salary and compensation survey. AORN J. 2013;98(6):569-584. 16. Aiken LH, Sloane DM, Cimiotti JP, et al. Implications of the California nurse staffing mandate for other states. Health Serv Res. 2010;45(4):904-921. 17. Burnes Bolton L, Aydin CE, Donaldson N, et al. Mandated nurse staffing ratios in California: a comparison of staffing and nursingsensitive outcomes pre- and postregulation. Policy Polit Nurs Pract. 2007;8(4):238-250. 18. Donaldson N, Shapiro S. Impact of California mandated acute care hospital nurse staffing ratios: a literature synthesis. Policy Polit Nurs Pract. 2010;11(3):184-201. 19. Berkow S, Virkstis K, Stewart J, Vonderhaar K, Forman A, Katz M. Achieving Top-of-License Nursing Practice: Best Practices for Elevating the Impact of the Frontline Nurse. Washington, DC: The Nursing Executive Center, The Advisory Board Company; 2013.
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