Best Practices for Staffing: Acuity vs. Census BACKGROUND • 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 Lauren Bachman, Heath Chrisianson, Sylvia Davis, Heidi Kidd, Eric Stuemke SEARCHABLE QUESTION What are the best practices for staffing adult inpatient acute care units regarding patient census and patient acuity? Databases Searched CINAL & PUBMED CONCLUSIONS Nurse leadership should pay careful attention to seeking buy in from staff nurses and other interdisciplinary members (Harper and McCully, Each unit should seek out workable acuity tools, and implement them within their specific environment (Heede, Diya, Lesaffre, Vleugels, & Sermeus, 2008). 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.  For addition information please contact: University of Anchorage School of Nursing (907) 786-4550 Suggestions for 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 Summary of Evidence What does it all mean? •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) Level of Evidence/ Citation Key Measures Settings and sample Research Design Key Strengths/Weaknesses Results 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. IV: DV: Orthopedic surgical unit Sample, n=34: -FTE RNs Retrospective Exploratory - Convenience, non- randomised sample Strengths: -Readily available data & use of existing technology - Application to clinical practice Weaknesses: -Admissions increased response times more than discharges. -Tracking call light study demonstrated the busiest times of the day. -Nurse staffing was adjusted accordingly. 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 Sample, n=15: -RNs -5 Criteria of patient classification: medications, complicated procedures, education, psychosocial issues, complicated IV medications. -Yielded: 1-4 patient acuity rating Descriptive Strengths: -Use of staff nurses input to develop PCS tool. -5 rating concepts evaluate time and frequency required for interventions -Includes education and psychosocial considerations Weaknesses: -Small sample size -No clear The PCS tool was well received by nurses with 77% rating it as an effective voice for nurses in communicating about their patients. 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: Nursing hours per patient day (NHPPD) DV: Patient outcomes Western Australian hospitals. Sample, n= 235,454: -patient records Sample, n=150,925: -staffing records Interrupted time series, retrospective analysis of patient and staffing data throughout the implementation of the mandated staffing level. Strengths: Extensive patient and nurse staffing records. Weaknesses: California hospitals did not have similar findings following mandatory staffing ratio implementation. 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 nursing-sensitive patient outcome indicators following the implementation of the NHPPD staffing method. 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 8 acute care, publicly funded, Canadian hospitals (randomly selected) Sample, n=8: -nurses -selected by purposive Qualitative -Detailed analysis of transcripts 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. Level IV Evidence Mark, B. A., & Harless, D. W. (2011, March/April). Adjusting for patient acuity in measurement of nurse staffing. Nursing Research, 60(2), 107-113. Non-Experimental 13 states from 2000 - 2006 Sample, n=579: -Hospitals - Included were: three measures of nurse staffing and hospital characteristics (ownership, geographic location, teaching status, Non-Experimental - Cross-sectional - Longitudinal study Strengths: -Large sample size Weaknesses: - NIWs provide a true estimate of patient needs -CMI doesn’t reflect acuity -CMI only for Medicare patients The study used descriptive statistics and simple correlation analysis and found no statistically significant relationship between NIW-adjusted and CMI adjusted staffing. This study suggests one way to start addressing staffing based on patient acuity is to have a “standardized acuity system developed, tested, implemented widely in hospitals, and adopted by researchers”. Level IV Evidence 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. Non-Experimental 1637 acute care nursing units in 115 hospitals Sample, n=690,258: -inpatient days for 298,691 patients Non-Experimental - Retrospective analysis of cross-sectional data 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 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.” Level IV Evidence Acar, I. (2010). A decision model for nurse-to-patient assignment. Western Michigan University. IV: Acuity; distance traveled by RN per shift (each based on detailed scoring system) DV: Total workload Single adult medical/oncology unit (general medical unit) Sample, n=40: -RNs -Approximately 100, 12- hour shifts were observed. Quantitative -After-only, comparative design, looking at two models developed to balance total workload of RN's. -Model(1): focused on acuity and distance - Model(2): considered total workload of nurses Strengths: -Measurement tools demonstrated validity and reliability, and may be useful for a future workload measurement system. Weaknesses: -The population of the study was hand-selected, lending to some possible internal bias. -A single-hospital study may have limited generalizability. -Scoring measures were designed 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. Level IV Evidence Bacon, C.T. & Mark, B. (2009). Organizational effects on patient satisfaction in hospital medical surgical units. Journal of Nursing Administration, 39(5), 220-227. IV: Organizational characteristics, nursing unit characteristics, patient characteristics DV: Patient satisfaction 286 Medical-surgical units in 146 hospitals Sample, n=3718 RNs; 2720 patients: -Randomly selected Descriptive/correlational study -3 questionnaires, over 6- month period (RNs) -1 questionnaire (patients) Strengths: -Large sample size Weaknesses: -Sampling bias -Possible threat to internal validity -Questionnaires have Measures to reduce work complexity, such as regulation of nursing assignments based on patient acuity and improved support services, positively influence patient satisfaction. 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 Systematic review of descriptive/correlational studies -assessed relationship between some measure of nurse staffing and patient, nurse employee, or hospital outcomes. 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. Level VI Evidence Hayes, N. & Ball, J. (2012). Achieving safe staffing for older people in hospital. Nursing Older People 24(4), 20- IV: Nurse staffing levels NHS hospitals in the United Kingdom Sample, n=240: Descriptive -Mixed Methods -quantitative, yet from a 2 survey method Strengths: -Royal College of Nursing’s (2012) guidance and -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
1. Best Practices for Staffing: Acuity vs. Census BACKGROUND
Patient Classification Systems have been utilized since the 1960s
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) Lauren
Bachman, Heath Chrisianson, Sylvia Davis, Heidi Kidd, Eric Stuemke
SEARCHABLE QUESTION What are the best practices for staffing adult
inpatient acute care units regarding patient census and patient
acuity? Databases Searched CINAL & PUBMED 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). 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. For addition
information please contact: University of Anchorage School of
Nursing (907) 786-4550 Suggestions for 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. Summary of
Evidence What does it all mean? 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) Level of Evidence/ Citation
Key Measures Settings and sample Research Design Key
Strengths/Weaknesses Results Level IV Evidence Lucero, R.J., Ji,
H., de Cordova, P.B., & Stone, P. (2011). Information
technology, nurse staffing, and patient needs.
NursingEconomics,29(4), 189-194. IV: DV: Orthopedic surgical unit
Sample, n=34: -FTE RNs Retrospective Exploratory -Convenience,
non-randomised sample Strengths: -Readily available data & use
of existing technology -Application to clinical practice
Weaknesses: -All patient calls (needs) were assumed equally
important -Admissions increased response times more than
discharges. -Tracking call light study demonstrated the busiest
times of the day. -Nurse staffing was adjusted accordingly. Level
VI Evidence Harper & McCully. (2007). Acuity systems dialogue
and patient classification system essentials. Nursing
AdministrationQuarterly, 31(4), 284-299 IV: DV: Medical-surgical
unit Sample, n=15: -RNs -5 Criteria of patient classification:
medications, complicated procedures, education, psychosocial
issues, complicated IV medications. -Yielded: 1-4 patient acuity
rating Descriptive Strengths: -Use of staff nurses input to develop
PCS tool. -5 rating concepts evaluate time and frequency 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
The PCS tool was well received by nurses with 77% rating it as an
effective voice for nurses in communicating about their patients.
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 NursingStudies,48(5), 540-548. IV: Mandatory staffing
levels: Nursing hours per patient day (NHPPD) DV: Patient outcomes
Western Australian hospitals. Sample, n= 235,454: -patient records
Sample, n=150,925: -staffing records Interrupted time series,
retrospective analysis of patient and staffing data throughout the
implementation of the mandated staffing level. Strengths: Extensive
patient and nurse staffing records. Weaknesses: California
hospitals did not have similar findings following mandatory
staffing ratio implementation. 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 nursing- sensitive patient outcome
indicators following the implementation of the NHPPD staffing
method. 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 8 acute care,
publicly funded, Canadian hospitals (randomly selected) Sample,
n=8: -nurses -selected by purposive sampling Qualitative -Detailed
analysis of transcripts 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. Level IV Evidence Mark,
B. A., & Harless, D. W. (2011, March/April). Adjusting for
patient acuity in measurement of nurse staffing. Nursing Research,
60(2), 107-113. Non-Experimental 13 states from 2000 - 2006 Sample,
n=579: - Hospitals - Included were: three measures of nurse
staffing and hospital characteristics (ownership, geographic
location, teaching status, hospital size, and percent Medicare
inpatient days). Non-Experimental - Cross-sectional - Longitudinal
study Strengths: - Large sample size Weaknesses: - NIWs provide a
true estimate of patient needs -CMI doesnt reflect acuity - CMI
only for Medicare patients The study used descriptive statistics
and simple correlation analysis and found no statistically
significant relationship between NIW- adjusted and CMI adjusted
staffing. This study suggests one way to start addressing staffing
based on patient acuity is to have a standardized acuity system
developed, tested, implemented widely in hospitals, and adopted by
researchers. Level IV Evidence 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. Non-Experimental 1637
acute care nursing units in 115 hospitals Sample, n=690,258: -
inpatient days for 298,691 patients Non-Experimental -Retrospective
analysis of cross- sectional data 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 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. Level IV Evidence Acar, I. (2010). A decision model
for nurse-to-patient assignment. Western Michigan University. IV:
Acuity; distance traveled by RN per shift (each based on detailed
scoring system) DV: Total workload Single adult medical/oncology
unit (general medical unit) Sample, n=40: -RNs -Approximately 100,
12-hour shifts were observed. Quantitative - After-only,
comparative design, looking at two models developed to balance
total workload of RN's. -Model(1): focused on acuity and distance -
Model(2): considered total workload of nurses Strengths: -
Measurement tools demonstrated validity and reliability, and may be
useful for a future workload measurement system. Weaknesses: -The
population of the study was hand- selected, lending to some
possible internal bias. -A single-hospital study may have limited
generalizability. -Scoring measures were designed specifically for
this study and have not been tested elsewhere. 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. Level IV Evidence Bacon, C.T. & Mark, B.
(2009). Organizational effects on patient satisfaction in hospital
medical surgical units. Journal of NursingAdministration,39(5),
220-227. IV: Organizational characteristics, nursing unit
characteristics, patient characteristics DV: Patient satisfaction
286 Medical-surgical units in 146 hospitals Sample, n=3718 RNs;
2720 patients: -Randomly selected Descriptive/correlational study
-3 questionnaires, over 6-month period (RNs) -1 questionnaire
(patients) 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. 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 Systematic review of
descriptive/correlational studies -assessed relationship between
some measure of nurse staffing and patient, nurse employee, or
hospital outcomes. 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. Level VI Evidence Hayes, N. & Ball, J.
(2012). Achieving safe staffing for older people in hospital.
NursingOlder People 24(4), 20-24. IV: Nurse staffing levels DV:
Quality of care NHS hospitals in the United Kingdom Sample, n=240:
-nurses working on older peoples wards Descriptive -Mixed Methods
-quantitative, yet from a 2 survey method -focus groups, though no
mention of qualitative method Strengths: -Royal College of Nursings
(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 Weaknesses:
-focused on older peoples wards in the UK -focus groups not
randomized, may introduce bias -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.
2. Heidi Kidd, Sylvia Davis, Eric Stuemke, Heath Christianson,
and Lauren Bachman
3. Background & Significance Patient Classification Systems
have been utilized since the 1960s 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)
4. Searchable Question What are the best practices for staffing
adult inpatient acute care units regarding patient census and
patient acuity?
5. Information Technology, Nurse Staffing, and Patient Needs
(Lucero, Ji, Cordova, & Stone, 2011) Retrospective Exploratory,
Level IV FTE RNs 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
6. Acuity Systems Dialogue and Patient Classification System
Essentials (Harper & McCully, 2007) Descriptive Level VI
Evidence N = 15 RNs on a Medical-Surgical Unit Authors 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
7. 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 DRGs not consistent through time
California did not produce similar results
8. 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
9. 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 doesnt reflect acuity. CMI only for Medicare patients No
distinction between inpatient and outpatient employee Level IV
Study
10. 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
11. 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.
12. A Decision Model for Nurse-To-Patient Assignment (Acar, I.,
2010) After-only Comparative Design, level IV. 40 RNs 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 Nurses
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.
13. 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
14. 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 peoples 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 Nursings (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 peoples wards in the U.K. Focused
groups not randomized, may introduce bias
15. Stake Holders Facility Administration/Accounting Insurance
Companies/Third Party Payer Nurse Leadership Nurse Educators Staff
Nurses Patient Care Technicians/CNAs Patients-(Outcomes)
16. 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)
17. 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).
18. 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.
19. 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.
20. 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.
21. 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).
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