Best Practices for Staffing: Acuity vs. Census
Level of Evidence/ Citation
BACKGROUND
Key Measures
Orthopedic surgical unit
Sample, n=34:
-FTE RNs
Level VI Evidence
Harper & McCully. (2007). Acuity systems dialogue and
patient classification system essentials. Nursing
Administration Quarterly, 31(4), 284-299
IV:
DV:
Medical-surgical unit
Descriptive
Sample, n=15:
-RNs
-5 Criteria of patient classification:
medications, complicated procedures,
education, psychosocial issues,
complicated IV medications.
-Yielded: 1-4 patient acuity rating
Level IV Evidence
Twigg, D.I., Duffield, C., Bremner, A., Rapley, P., & Finn, J.
(2011). The impact of the nursing hours per patient day
(NHPPD) staffing method on patient outcomes: A
retrospective analysis of patient and staffing data.
International Journal of Nursing Studies, 48(5), 540-548.
IV: Mandatory staffing levels: Western Australian hospitals.
Nursing hours per patient day Sample, n= 235,454:
(NHPPD)
-patient records
Sample, n=150,925:
DV: Patient outcomes
-staffing records
Level IV Evidence
Non-Experimental
Mark, B. A., & Harless, D. W. (2011, March/April). Adjusting
for patient acuity in measurement of nurse staffing. Nursing
Research, 60(2), 107-113.
13 states from 2000 - 2006
Non-Experimental
Sample, n=579:
- Cross-sectional
Hospitals
- Longitudinal study
Included were: three measures of nurse
staffing and hospital characteristics
(ownership, geographic location,
teaching status, hospital size, and
percent Medicare inpatient days).
Level IV Evidence
Non-Experimental
Heede, K. V., Diya, L., Lesaffre, E., Vleugels, A., & Sermeus,
W. (2008). Benchmarking nurse staffing levels: The
development of a nationwide feedback tool. Journal of
Advanced Nursing, 63, 607-618.
1637 acute care nursing units in 115
Non-Experimental
hospitals
Sample, -Retrospective analysis of crossn=690,258:
sectional data
inpatient days for 298,691 patients
IV: Acuity; distance traveled by Single adult medical/oncology unit
RN per shift (each based on
(general medical unit)
detailed scoring system)
Sample, n=40:
-RNs
DV: Total workload
-Approximately 100, 12-hour shifts
were observed.
Level IV Evidence
IV: Organizational
Bacon, C.T. & Mark, B. (2009). Organizational effects on
characteristics, nursing unit
patient satisfaction in hospital medical surgical units. Journal characteristics, patient
of Nursing Administration, 39(5), 220-227.
characteristics
SEARCHABLE QUESTION
286 Medical-surgical units in 146
hospitals
Sample, n=3718 RNs; 2720 patients:
-Randomly selected
Level V Evidence
Lang, T.A., Hodge, M., Olson, V., Romano, P.S., & Kravitz,
R.L. (2004). A systematic review on the effects of nurse
staffing on patient, nurse employee, and hospital outcomes.
JONA, 34(7/8), 326-337.
IV: Nurse staffing
DV: Patient, nurse employee,
and hospital outcomes
Acute care, rehabilitation, or
psychiatric hospitals
Sample, n=43:
-research studies
Level VI Evidence
IV: Nurse staffing levels
Hayes, N. & Ball, J. (2012). Achieving safe staffing for older
people in hospital. Nursing Older People 24(4), 20-24.
DV: Quality of care
This study found an association between implementing the NHPPD
staffing method and improvements in patient safety. Specifically,
there have been significant reductions in the rates of nine nursingsensitive patient outcome indicators following the implementation of
the NHPPD staffing method.
Strengths:
-Themes dominated conversations and were
interrelated
Weaknesses:
-Group size was preselected
-No mention of data saturation
Detailed analysis of transcripts revealed three key themes: patient
acuity, workload, and understaffing. Workload and understaffing
dominated the narrative and showed a strong link to patient acuity.
Strengths:
-Random selection of patients data
Weaknesses:
-Data assumes units within hospitals are
correlated
-Aim of study to report, not predict staffing
-Feedback tool only available online
Quantitative
- Strengths:
After-only, comparative design,
Measurement tools demonstrated validity and
looking at two models developed to
reliability, and may be useful for a future
balance total workload of RN's.
workload measurement system.
-Model(1): focused on acuity and
Weaknesses:
distance
- -The population of the study was handModel(2): considered total workload of selected, lending to some possible internal
nurses
bias.
-A single-hospital study may have limited
generalizability.
-Scoring measures were designed specifically
for this study and have not been tested
elsewhere.
Descriptive/correlational study
-3 questionnaires, over 6-month period
(RNs)
-1
questionnaire (patients)
Systematic review of
descriptive/correlational studies
-assessed relationship between some
measure of nurse staffing and patient,
nurse employee, or hospital outcomes.
Databases Searched
CINAL & PUBMED
Strengths:
Extensive patient and nurse staffing records.
Weaknesses:
California hospitals did not have similar
findings following mandatory staffing ratio
implementation.
- Strengths:
- The study used descriptive statistics and simple correlation analysis
- Large sample size
and found no statistically significant relationship between NIWWeaknesses:
- adjusted and CMI adjusted staffing.
NIWs provide a true estimate of patient needs
-CMI doesn’t reflect acuity
- This study suggests one way to start addressing staffing based on
CMI only for Medicare patients
patient acuity is to have a “standardized acuity system developed,
tested, implemented widely in hospitals, and adopted by researchers”.
DV: Patient satisfaction
What are the best practices for staffing adult inpatient acute
care units regarding patient census and patient acuity?
Results
Strengths:
The PCS tool was well received by nurses with
-Use of staff nurses input to develop PCS tool. 77% rating it as an effective voice for nurses in
-5 rating concepts evaluate time and frequency communicating about their patients.
required for interventions
-Includes
education and psychosocial considerations
Weaknesses:
-Small sample size
-No clear recommendation on how to use the
tool to make specific assignments
Interrupted time series, retrospective
analysis of patient and staffing data
throughout the implementation of the
mandated staffing level.
8 acute care, publicly funded,
Qualitative
Canadian hospitals (randomly
-Detailed analysis of transcripts
selected)
Sample,
n=8:
-nurses
-selected by purposive sampling
• Low nurse-to-patient ratios are related to lower rates of
adverse patient outcomes (Harper & McCully, 2007).
Key Strengths/Weaknesses
Retrospective Exploratory
Strengths:
-Admissions increased response times more than discharges.
-Convenience, non-randomised sample -Readily available data & use of existing
-Tracking call light study demonstrated the busiest times of the day.
technology
-Nurse staffing was adjusted accordingly.
-Application to clinical practice
Weaknesses:
-All patient calls (needs) were assumed equally
important
Level VI Evidence
McGillis Hall, L., & Kiesners, D. (2005). A narrative
approach to understanding the nursing work environment in
Canada. Social Science & Medicine, 61(12), 2482-2491. doi:
10.1016/j.socscimed.2005.05.002
Level IV Evidence
Acar, I. (2010). A decision model for nurse-to-patient
assignment. Western Michigan University.
• “Patient classification systems and acuity tools allow
managers and administrators to predict staffing needs
and more accurately control nurse-to-patient ratios”
(Harper & McCully 2007)
Research Design
IV:
DV:
• Patient Classification Systems have been utilized since
the 1960’s without standardization or consensus
(Harper & McCully, 2007).
• With a combination of increasing health costs,
decreasing nurse satisfaction, a lack of communication
tools, and staffing shortages; acuity tools can
appropriately coordinate staff with patient needs
(Twigg, Duffield, Bremner, Rapley, & Finn 2011).
Settings and sample
Level IV Evidence
Lucero, R.J., Ji, H., de Cordova, P.B., & Stone, P. (2011).
Information technology, nurse staffing, and patient needs.
Nursing Economics, 29(4), 189-194.
NHS hospitals in the United Kingdom Descriptive
Sample, n=240:
-Mixed Methods
-nurses working on older people’s
-quantitative, yet from a 2 survey
wards
method
-focus groups, though no mention of
qualitative method
The study found that variability in nurse staffing levels occurs within
a specific unit and not the whole hospital.
Another finding was the feedback tool develops accurate reflection of
staffing in the past, but “the figures generated do not indicate the
optimal or evidence-based nurse staffing level.”
Strengths:
-Large sample size
Weaknesses:
-Sampling bias
-Possible threat to internal validity
-Questionnaires have limited reliability
Measures to reduce work complexity, such as regulation of nursing
assignments based on patient acuity and improved support services,
positively influence patient satisfaction.
Strengths:
-former nurse with 15 years experience as a
medical reference librarian performed the
literature search
Weaknesses:
-49% of studies analyzed hospital-level data,
rather than nursing-unit-level data.
-include data from ICUs, which have different
staffing patterns and different patient
characteristics
A minimum nurse-patient ratio alone is likely not appropriate to
ensure quality of care. Patient acuity, skill mix, nurse competence,
nursing process variables, technological sophistication, and
institutional support of nursing should also be taken into consideration
when establishing minimum staffing requirements.
Strengths:
-Royal College of Nursing’s (2012) guidance
and recommendations can be used by nurses at
all levels
Multiple focus groups with front-line nurses
-Workshops & discussions with invited
gerontological nurses
-The use of acuity tools alone is not sufficient to determine adequate
staffing requirements. During periods of high patient acuity, charge
nurses must have instant access to additional nursing resources. They
should also have access to senior clinical support and leadership from
nurse experts.
-Further work is needed to
develop suitable metrics and measures that include all aspects of
complex care.
•Nurse tracking call light systems are an underutilized tool that can
be used to effectively communicate patient needs among the
interdisciplinary team, (Lucero, Ji, Cordova, & Stone, 2011)
•There is a need to have a universal acuity tool, (Harper & McCully,
2007).
•There is an association between acuity based staffing and
improvements in patient safety, (Twigg, Duffield, Bremner, Rapley,
& Finn, 2011).
•Nursing satisfaction is related to patient acuity, nursing workload,
and understaffing (McGillis & Kiesners, 2005).
•Universal system for collection of nurses involved in patient care
(Mark & Harless, 2011).
•A standardized acuity system needs to be developed, tested, and
implemented widely in hospitals and adopted by researchers (Mark
& Harless, 2011)
•Patient satisfaction is related to nurse staffing and the availability
of hospital support services. (Bacon & Mark, 2009)
•High acuity increases workload due to understaffing. Fixing
staffing would decrease the workload per patient (Acar, 2010).
•Patient acuity scoring systems and distance scoring systems can
be used to estimate total workload of nurses, (Acar, 2010).
•Units cannot use a minimum nurse patient ratio alone, a number of
factors must be incorporated to determine an appropriate patient to
nurse ratio, including patient acuity, skill mix, nurse competence,
nursing process variables, technological sophistication (Lang,
Hodge, Olson, Romano, & Kravitz, 2004).
•There is a lack of support offered in the literature for specific
minimum nurse patient ratios ,(Lang, Hodge, Olson, Romano,
Kravitz, 2004).
•The use of acuity tools alone is not sufficient to determine
adequate staffing requirements, (Hayes & Ball, 2012)
RESULTS
Evidence Answers Original Question
•Research was inconclusive related to our original question. At
this time there is a continued need for establishing a universal
acuity rating tool. Additional experimentation, and possibly a metaanalysis of previous research is needed.
Not Found in Evidence
•There was no universal tool for patient acuity measurement found
in the literature search.
Suggestions for Future Research
•Meta-analysis of all currently available acuity tools.
CONCLUSIONS
•Nurse leadership should pay careful attention to seeking buy in from staff nurses and other
interdisciplinary members (Harper and McCully, 2007).
•Unit specific measures of acuity should be
considered in development of future acuity staffing
tools.
•Each unit should seek out workable acuity tools, and implement them within their specific
environment (Heede, Diya, Lesaffre, Vleugels, & Sermeus, 2008).
•A patient acuity tool should be developed, and
measured against patient outcomes.
University of Anchorage
School of Nursing (907) 786-4550
Summary of Evidence
What does it all mean?
Of the two models tested, the model with a focus on patient acuity and
distance traveled by the RN resulted in a more balanced total
workload, reducing the variability between the workload of all nurses
on the unit per shift.
Weaknesses:
-focused on older people’s wards in the UK
-focus groups not randomized, may introduce
bias
For addition information please contact:
Lauren Bachman, Heath Chrisianson, Sylvia Davis,
Heidi Kidd, Eric Stuemke
Heidi Kidd, Sylvia Davis, Eric Stuemke, Heath
Christianson, and Lauren Bachman
Background & Significance
 Patient Classification Systems have been utilized since the 1960’s
without standardization or consensus (Harper & McCully, 2007).
 With a combination of increasing health costs, decreasing nurse
satisfaction, a lack of communication tools, and staffing
shortages; acuity tools can appropriately coordinate staff with
patient needs (Twigg, Duffield, Bremner, Rapley, & Finn 2011).
 Low nurse-to-patient ratios are related to lower rates of adverse
patient outcomes (Harper & McCully, 2007).
 “Patient classification systems and acuity tools allow managers
and administrators to predict staffing needs and more accurately
control nurse-to-patient ratios” (Harper & McCully 2007)
Searchable Question
 What are the best practices for staffing
adult inpatient acute care units
regarding patient census and patient
acuity?
Information Technology, Nurse Staffing, and
Patient Needs (Lucero, Ji, Cordova, & Stone,
2011)






Retrospective Exploratory, Level IV
FTE RN’s on an orthopedic surgical unit N=34
Convenience Non-Random Sample
Admissions increased response times more than discharges
Tracking call light study demonstrated the busiest times of day
Nurse staffing was adjusted accordingly
Strengths
Readily available data & use of existing technology
Application to clinical practice
Weaknesses
All patient calls (needs) were assumed equally important
Acuity Systems Dialogue and Patient
Classification System Essentials (Harper &
McCully, 2007)
 Descriptive Level VI Evidence
 N = 15 RN’s on a Medical-Surgical Unit
 Author’s Patient Classification System Employed 5 Criteria
 Medications, Complicated Procedures, Education, Psychosocial Issues, and
Complicated IV Medications.
 Criteria yielded a level 1-4 patient acuity rating
 The PCS tool was well received by nurses with 77% rating it as an effective
voice for nurses in communicating about their patients
Strengths
Use of staff nurses input to develop PCS tool
5 rating concepts evaluate time & frequency required for interventions
Includes education & psychosocial considerations
Weaknesses
Small Sample Size
No clear recommendation on how to use tool to make specific assignments
The impact of the nursing hours per patient day (NHPPD)
staffing method on patient outcomes: A retrospective
analysis of patient and staffing data. (Twigg et al., 2011)
• Interrupted time series using retrospective analysis. Level IV
• Three adult tertiary teaching hospitals that received 88.9% of the
staffing increases
• All patient records (N = 236,454) and nurse staffing records (N =
150,925) .
• Measurements taken pre implementation, transitional period and post
implementation.
• Significant decreases in the rates of nine nursing-sensitive outcomes
following implementation of NHPPD
Strengths
Large sample size
Extensive patient and nurse staffing records
Weaknesses
DRG’s not consistent through time
California did not produce similar results
A narrative approach to understanding the
nursing work environment in Canada (McGillis et
al., 2005)
• Qualitative . Level VI.
• Purposive sampling from eight randomly selected
hospitals.
• 8 nurses from 8 different acute care units
• Revealed three key themes: patient acuity, workload, and
understaffing as effecting quality of work environment
Strengths
Themes dominated conversations and were interrelated
Weaknesses
Group size was preselected & no mention of data saturation
Adjusting for Patient Acuity in Measurement
of Nurse Staffing (Mark and Harless, 2011)





Cross Sectional and Longitudinal, Level IV
Sample 579 hospitals in 13 states from 2000 to 2006
Purpose to examine if CMI can substitute for NIW
CMI=Case Mix Index High CMI =more care
NIW = Nursing Intensity Workload
Strengths
Descriptive Statistics with simple correlation analysis
Large sample size
Weakness
NIWs provide a true estimate of Patient needs
CMI doesn’t reflect acuity. CMI only for Medicare patients
No distinction between inpatient and outpatient employee
Level IV Study
Benchmarking nurse staffing levels: the
development of a nationwide feedback tool (Heede
et al., 2008)
 Retrospective analysis of cross-sectional data, Level IV
 Sample 690,258 inpatient days for 298,691 patients from 1637 acute care
nursing units in 115 hospitals
 Feedback tool developed based on satistical model
 Spearman rank correlations from 0.91-0.99
 High reliability and validity for tool developed
Strengths
Inter-rater reliability 78.8 %
Random selection of patients data
Weakness
Data assumes units within hospitals are correlated
Aim of study to report not predict staffing
Feedback tool only available online
Level IV evidence
Organizational Effects On Patient Satisfaction In
Hospital Medical Surgical Units (Bacon, C.T. &
Mark, B., 2009)
Single, correlation study, level IV
 Random sample
 Included 2720 patients and 3718 RNs in 286 medical-surgical
units in 146 hospitals
 Investigated the relationship of patient satisfaction with floor
staffing and support services.
Strengths
Patient acuity is used as a variable
Weaknesses
Sampling bias is a potential problem.
Variables used (patient acuity and work complexity) are difficult to
operationalize.

A Decision Model for Nurse-To-Patient
Assignment (Acar, I., 2010)
After-only Comparative Design, level IV.
 40 RN’s on General Medical Unit. Approximately 100 12-hour shifts
observed.
 Models for staff assignment included maximizing patient acuity and
minimizing RN distance traveled during a shift, or minimizing the
maximum workload assigned to a nurse. Results compared to the
Charge Nurse’s manual assignments’ resulting workload
Strengths
Initially planned to study nurses in NICU, and realized generalizability
may be limited.
Switched the study to a General Medical Unit.
Weaknesses
Study took place in one hospital, which may limit generalizability.

Nurse-patient ratios: A systematic review on the effects of
nurse staffing on patient, nurse employee, and hospital
outcomes (Lang et al., 2004)
•
•
•
•
Level V
Systematic review of descriptive/correlational studies
Sample: 43 research studies on acute care, rehabilitation, or psychiatric
hospitals
Patient acuity, skill mix, nurse competence, nursing process variables,
technological sophistication, and institutional support of nursing should
be considered when setting minimum nurse staffing requirements, and
not a minimum nurse-patient ratio alone.
Strengths
Former nurse with 15 years experience as a medical reference librarian
performed the literature search
Weaknesses
49% of studies analyzed hospital-level data, rather than nursing-unit-level
data.
Include data from ICUs, which have different staffing patterns and different
patient characteristics
Achieving safe staffing for older people in hospital
(Hayes & Ball, 2012)
• Level VI
• Mixed Methods (quantitative from a 2 survey method)
• Nurses who worked on older people’s wards (n=240)
• The use of acuity tools alone is not sufficient to determine adequate
staffing requirements.
During periods of high patient acuity, charge nurses must have instant
access to additional nursing resources.
Charge nurses should also have access to senior clinical support and
leadership from nurse experts.
Strengths
Royal college of Nursing’s (2012) guidance and recommendations can be used
by nurses at all levels
Multiple focus groups with front-line nurses
Workshops & discussions w/ invited gerontological nurses
Weaknesses
Focused on older people’s ward’s in the U.K.
Focused groups not randomized, may introduce bias
•
•
Stake Holders
 Facility Administration/Accounting
 Insurance Companies/Third Party Payer
 Nurse Leadership
 Nurse Educators
 Staff Nurses
 Patient Care Technicians/CNA’s
 Patients-(Outcomes)
Summary of Evidence
 Nurse tracking call light systems are an underutilized tool that





can be used to effectively communicate patient needs among the
interdisciplinary team (Lucero, Ji, Cordova, & Stone, 2011).
There is a need to have a universal acuity tool (Harper &
McCully, 2007).
There is an association between acuity based staffing and
improvements in patient safety (Twigg, Duffield, Bremner,
Rapley, & Finn, 2011).
Nursing satisfaction is related to patient acuity, nursing
workload, and understaffing (McGillis & Kiesners, 2005).
A standardized acuity system needs to be developed, tested, and
implemented widely in hospitals and adopted by researchers
(Mark & Harless, 2011)
Patient satisfaction is related to nurse staffing and the
availability of hospital support services. (Bacon & Mark, 2009)
Summary of Evidence
 High acuity increases workload due to understaffing. Fixing staffing




would decrease the workload per patient (Acar, 2010).
Patient acuity scoring systems and distance scoring systems can be
used to estimate total workload of nurses (Acar, 2010).
Units cannot use a minimum nurse patient ratio alone, a number of
factors must be incorporated to determine an appropriate patient to
nurse ratio, including patient acuity, skill mix, nurse competence,
nursing process variables, technological sophistication (Lang,
Hodge, Olson, Romano, & Kravitz, 2004).
There is a lack of support offered in the literature for specific
minimum nurse patient ratios (Lang, Hodge, Olson, Romano,
Kravitz, 2004).
The use of acuity tools alone is not sufficient to determine adequate
staffing requirements (Hayes & Ball, 2012).
Results
Evidence Answers Original Question
 Research was inconclusive related to our original
question. At this time there is a continued need for
establishing a universal acuity rating tool. Additional
experimentation, and possibly a meta-analysis of
previous research is needed.
Not Found in Evidence
 There was no universal tool for patient acuity
measurement found in the literature search.
Future Research
 Meta-analysis of all currently available acuity tools.
 Unit specific measures of acuity should be considered
in development of future acuity staffing tools.
 A patient acuity tool should be developed, and
measured against patient outcomes.
Plan of Implementation
 A meta analysis should be performed.
 Focus groups, comprised of stake holders, should
conduct a literature review.
 Unit specific acuity tools would then be implemented.
 Pre-implementation data should be measured against
post-implementation data in relation to pre-defined
patient outcomes.
Conclusions
 Nurse leadership should pay careful attention to
seeking buy in from staff nurses and other
interdisciplinary members (Harper and McCully,
2007).
 Each unit should seek out workable acuity tools, and
implement them within their specific environment
(Heede, Diya, Lesaffre, Vleugels, & Sermeus, 2008).
References
Acar, I. (2010). A decision model for nurse-to-patient assignment.
Western Michigan University.
Bacon, C.T. & Mark, B. (2009). Organizational effects on patient
satisfaction in hospital medical surgical units. Journal of Nursing
Administration, 39(5), 220-227.
Harper & McCully. (2007). Acuity systems dialogue and patient
classification system essentials. Nursing Administration Quarterly,
31(4), 284-299
Hayes, N. & Ball, J. (2012). Achieving safe staffing for older people in
hospital. Nursing Older People 24(4), 20-24.
Heede, K. V., Diya, L., Lesaffre, E., Vleugels, A., & Sermeus, W. (2008).
Benchmarking nurse staffing levels: The development of a nationwide
feedback tool. Journal of Advanced Nursing, 63, 607-618.
References
Lang, T.A., Hodge, M., Olson, V., Romano, P.S., & Kravitz, R.L. (2004). A
systematic review on the effects of nurse staffing on patient, nurse
employee, and hospital outcomes. JONA, 34(7/8), 326-337.
Lucero, R.J., Ji, H., de Cordova, P.B., & Stone, P. (2011). Information
technology, nurse staffing, and patient needs. Nursing Economics,
29(4), 189-194.
Mark, B. A., & Harless, D. W. (2011, March/April). Adjusting for patient
acuity in measurement of nurse staffing. Nursing Research, 60(2), 107113.
McGillis Hall, L., & Kiesners, D. (2005). A narrative approach to
understanding the nursing work environment in Canada. Social
Science & Medicine, 61(12), 2482-2491. doi:
10.1016/j.socscimed.2005.05.002
Twigg, D.I., Duffield, C., Bremner, A., Rapley, P., & Finn, J. (2011). The
impact of the nursing hours per patient day (NHPPD) staffing method
on patient outcomes: A retrospective analysis of patient and staffing
data. International Journal of Nursing Studies, 48(5), 540-548.