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Best Practices for Staffing: Acuity vs. CensusBACKGROUNDPatient 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 QUESTIONWhat are the best practices for staffing adult inpatient acute care units regarding patient census and patient acuity?

Databases SearchedCINAL & PUBMED

CONCLUSIONSNurse 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).

RESULTSEvidence Answers Original QuestionResearch 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 ResearchMeta-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 EvidenceWhat 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/ CitationKey MeasuresSettings and sampleResearch DesignKey Strengths/WeaknessesResultsLevel 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 RNsRetrospective 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 Administration Quarterly, 31(4), 284-299IV: 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 ratingDescriptiveStrengths: -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 assignmentsThe PCS tool was well received by nurses with77% rating it as an effective voice for nurses incommunicating about their patients.Level IV EvidenceTwigg, 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 outcomesWestern Australian hospitals. Sample, n= 235,454: -patient records Sample, n=150,925: -staffing recordsInterrupted 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 EvidenceMcGillis 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.2005.05.0028 acute care, publicly funded, Canadian hospitals (randomly selected) Sample, n=8: -nurses -selected by purposive sampling Qualitative-Detailed analysis of transcriptsStrengths:-Themes dominated conversations and were interrelatedWeaknesses:-Group size was preselected-No mention of data saturationDetailed 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-Experimental13 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 studyStrengths: -Large sample sizeWeaknesses: -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-Experimental1637 acute care nursing units in 115 hospitals Sample, n=690,258: -inpatient days for 298,691 patientsNon-Experimental -Retrospective analysis of cross-sectional dataStrengths: -Random selection of patients dataWeaknesses: -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 EvidenceAcar, 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 nursesStrengths: -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 Nursing Administration, 39(5), 220-227.IV: Organizational characteristics, nursing unit characteristics, patient characteristics DV: Patient satisfaction286 Medical-surgical units in 146 hospitals Sample, n=3718 RNs; 2720 patients: -Randomly selectedDescriptive/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 reliabilityMeasures to reduce work complexity, such as regulation of nursing assignments based on patient acuity and improved support services, positively influence patient satisfaction. Level V EvidenceLang, 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 outcomesAcute 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 characteristicsA 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 EvidenceHayes, N. & Ball, J. (2012). Achieving safe staffing for older people in hospital. Nursing Older People 24(4), 20-24. IV: Nurse staffing levels DV: Quality of careNHS 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 methodStrengths: -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.

Best Practices for StaffingAcuity vs. CensusUniversity of Alaska Anchorage NS400Heidi Kidd, Sylvia Davis, Eric Stuemke, Heath Christianson, and Lauren Bachman

2Background & SignificancePatient 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)

3Searchable QuestionWhat are the best practices for staffing adult inpatient acute care units regarding patient census and patient acuity?

4Information Technology, Nurse Staffing, and Patient Needs (Lucero, Ji, Cordova, & Stone, 2011)Retrospective Exploratory, Level IVFTE RNs on an orthopedic surgical unit N=34Convenience Non-Random SampleAdmissions increased response times more than dischargesTracking call light study demonstrated the busiest times of dayNurse staffing was adjusted accordinglyStrengthsReadily available data & use of existing technologyApplication to clinical practiceWeaknessesAll patient calls (needs) were assumed equally important

Lucero, Ji, Cordova, & Stone (2011) performed a retrospective level IV study to determine how patient needs, seen as using the call light, influenced nurse response time as monitored by an RN tracking system.

The population consisted of 34 FTE RNs on an orthopedic surgical unit at a magnet hospital over one year. Variations in data were accounted for in this one group study without randomization.

Findings indicate that admissions increased response times more than discharges, and increased staffing during periods of increased patient needs may have been due to proactive nurse management. Call light tracking systems are an underutilized way to assist in staffing adjustments, yet there was no significant relationship between nurse staffing and call light response times.

Strengths include inexpensive study as existing technology was used, and recommendations for clinical practice.Weaknesses include that there was no differentiation regarding needs that could be met by aids vs RNs thus all calls were assumed equally important. 5Acuity Systems Dialogue and Patient Classification System Essentials (Harper & McCully, 2007)Descriptive Level VI EvidenceN = 15 RNs on a Medical-Surgical UnitAuthors Patient Classification System Employed 5 CriteriaMedications, Complicated Procedures, Education, Psychosocial Issues, and Complicated IV Medications.Criteria yielded a level 1-4 patient acuity ratingThe PCS tool was well received by nurses with 77% rating it as an effective voice for nurses in communicating about their patientsStrengthsUse of staff nurses input to develop PCS tool5 rating concepts evaluate time & frequency required for interventionsIncludes education & psychosocial considerationsWeaknessesSmall Sample SizeNo clear recommendation on how to use tool to make specific assignments

Harper & McCully, (2007) used a descriptive study yielding Level VI Evidence. The authors developed a Patient Classification System or PCS around 5 criteria; medications, complicated procedures, education, psychosocial issues, and complicated IV medications.

After developing the tool with bedside nurses, two questionnaires were sent out and responded to voluntarily and anonymously by 15 RNs functioning either as unit staff, charge/coordinators, or nurse educators at a small rural hospital on a medical-surgical unit. One questionnaire asked the nurse to evaluate the effectiveness of the PCS, while the other assessed the nurses expert opinion of the 5 criteria used. 77% rated the tool as effective in serving as a voice, 64% believed it accurately discriminated between patients, and 55% rated the representation of patient needs as accurate while 45% were neutral on this point. Additionally 5 patients were evaluated with the PCS by 3 different RNs yielding 87% interrater reliability.

Strengths included the use of bedside nurses in PCS development, validity of 5 criteria, & high interrater reliability.Weaknesses include small sample size, and a lack of clear indication regarding how to use the tool in making specific assignments. 6The 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 IVThree adult tertiary teaching hospitals that received 88.9% of the staffing increasesAll 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 NHPPDStrengthsLarge sample sizeExtensive patient and nurse staffing recordsWeaknessesDRGs not consistent through timeCalifornia did not produce similar results

Twigg, Duffield, Bremner, Rapley, and Finn (2011) investigated the impact of the nursing hours per patient day (NHPPD) staffing method on nursing sensitive patient outcomes in Western Australian hospitals. They performed an interrupted time series, retrospective analysis of patient and staffing data throughout the implementation of the mandated staffing level. This study yielded level IV evidence.

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 NHPPD staffing method.

This study was strengthened by the fact that extensive patient and nurse staffing records from NHPPD wards were included for the entire Western Australia region. One possible weakness was that similar results in California hospitals were not found following mandatory staffing ratio implementation, but there were differences in data collection and completeness.

7A 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 unitsRevealed three key themes: patient acuity, workload, and understaffing as effecting quality of work environmentStrengthsThemes dominated conversations and were interrelatedWeaknessesGroup size was preselected & no mention of data saturation

McGillis Hall and Kiesners (2005) used a narrative approach in an attempt to understand the nursing work environment in Canadian hospitals. This study yielded level VI evidence. Purposive sampling was used to select eight nurses from eight different acute care, publicly funded hospitals that were randomly selected. 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.

8Adjusting for Patient Acuity in Measurement of Nurse Staffing (Mark and Harless, 2011)Cross Sectional and Longitudinal, Level IVSample 579 hospitals in 13 states from 2000 to 2006Purpose to examine if CMI can substitute for NIW CMI=Case Mix Index High CMI =more careNIW = Nursing Intensity WorkloadStrengthsDescriptive Statistics with simple correlation analysisLarge sample sizeWeaknessNIWs provide a true estimate of Patient needsCMI doesnt reflect acuity. CMI only for Medicare patients No distinction between inpatient and outpatient employeeLevel IV Study

Mark and Harless (2011) conducted a cross sectional and longitudinal study to determine the correlation between case mix index (CMI) and nursing intensity workload (NIW). This Level IV study collected data from 579 hospitals in 13 states from 2000 to 2006.

A higher CMI is correlated with patients that require more resources and have a more severe illness. NIW reflects the staffing hours of nurses. A higher NIW reflects the need for more personal.

The study used descriptive statistics and simple correlation analysis and found no statistically significant relationship between NIW-adjusted and CMI adjusted staffing.

This study suggest 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 researches (2011).

Mark, B. A., & Harless, D. W. (2011, March/April). Adjusting for Patient Acuity in Measurement of Nurse Staffing. Nursing Research, 60, No 2, 107-113.

9Benchmarking nurse staffing levels: the development of a nationwide feedback tool (Heede et al., 2008)Retrospective analysis of cross-sectional data, Level IVSample 690,258 inpatient days for 298,691 patients from 1637 acute care nursing units in 115 hospitalsFeedback tool developed based on satistical modelSpearman rank correlations from 0.91-0.99High reliability and validity for tool developedStrengthsInter-rater reliability 78.8 %Random selection of patients dataWeaknessData assumes units within hospitals are correlatedAim of study to report not predict staffingFeedback tool only available onlineLevel IV evidence

Heede et al. (2011) conducted a Retrospective analysis of cross-sectional data that was used to develop a feedback tool. The level of evidence for this study was IV. The sample for the study was gathered from data of 690,258 inpatient days for 298,691 patients from 1637 acute care nursing units in 115 hospitals.

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.

One important suggestion that the article makes is One possible way to determine whether a unit is under- or over-staffed is to survey nurses.

Finally there are things that this tool can not predict and that is the type of staff and the experience that that staff has in a particular hospital.

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.

10Organizational Effects On Patient Satisfaction In Hospital Medical Surgical Units (Bacon, C.T. & Mark, B., 2009)Single, correlation study, level IVRandom sampleIncluded 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.StrengthsPatient acuity is used as a variable WeaknessesSampling bias is a potential problem. Variables used (patient acuity and work complexity) are difficult to operationalize.

Bacon and Mark (2009) conducted a correlation study, providing level IV evidence. The study involved 2720 patients and 3718 RNs in 286 medical surgical units in 146 hospitals.

Study coordinators assisted with data collection to include 2 different questionnaires, completed by the nurses, and 1 questionnaire completed by patients. The relationship between organizational, nursing unit, and patient characteristics on patient satisfaction was observed, collecting information about support services using a 21-item checklist, and patient acuity, using a 24-item Likert-type questionnaire. Patients completed questionnaires detailing their satisfaction with their care, with response ranges from excellent to poor, or always to never.

The study demonstrated a clear association between work engagement and availability of support services with patient satisfaction.

Study measures included patient acuity and work complexity. These variables are difficult to operationalize, and the measures used may have lacked sensitivity to adequately capture the full range of patient acuity and work complexity.

11A 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. WeaknessesStudy took place in one hospital, which may limit generalizability.

Acar, I (2010) conducted an after-only, comparative design study, resulting in level IV evidence. The study involved direct observation of 40 RNs working on the General Medical Unit of a single hospital, observing about 100 12 hour shifts. Patient acuity scoring system and distance scoring systems were developed for the study, used to estimate total workload.2 models for unit staffing using Analytical Hierarchy Process were implemented, with patient acuity and RN distances traveled as objectives. Total workloads were compared to Charge Nurses manual assignments. Based on a scale estimating the quality and variability of the workload of nurses, staffing which focused on patient acuity and total distance per shift traveled by the nurse, resulted in more balanced staffing assignments in the workload of the unit.12Nurse-patient ratios: A systematic review on the effects of nurse staffing on patient, nurse employee, and hospital outcomes (Lang et al., 2004)Level VSystematic review of descriptive/correlational studiesSample: 43 research studies on acute care, rehabilitation, or psychiatric hospitalsPatient 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.StrengthsFormer nurse with 15 years experience as a medical reference librarian performed the literature search Weaknesses49% 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

Lang et al. (2004) conducted a systematic review of 43 descriptive/correlational studies to determine the effects of nurse staffing on patient, nurse employee, and hospital outcomes. It had a level V of evidence. The most important finding is that 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. One of this studys strengths was that a former nurse with 15 years experience as a medical reference librarian performed the literature search and collected the data. Some weaknesses were that 49% of the studies analyzed hospital level data, rather than nursing-unit level data. Also, it included data from ICUs, which have different staffing patterns and different patient characteristics.

13Achieving safe staffing for older people in hospital(Hayes & Ball, 2012)Level VIMixed 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.StrengthsRoyal college of Nursings (2012) guidance and recommendations can be used by nurses at all levelsMultiple focus groups with front-line nursesWorkshops & discussions w/ invited gerontological nurses WeaknessesFocused on older peoples wards in the U.K.Focused groups not randomized, may introduce bias

Hayes and Ball (2012) conducted a mixed-method, double survey study of 240 nurses who worked directly on older peoples wards in the UK. The most important findings with respect to the question being asked to the group were that 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. Strengths of this study were: The Royal College of Nursings (2012) guidance and recommendations can be used by nurses at all levels, and the study had focus groups with front-line nurses and workshops with invited gerontological nurses. Weaknesses of this study were that it focused on older peoples wards in the U.K. and the focus group methods may introduce bias because they were not randomized.14Stake HoldersFacility Administration/AccountingInsurance Companies/Third Party PayerNurse LeadershipNurse EducatorsStaff NursesPatient Care Technicians/CNAs Patients-(Outcomes)

15Summary of EvidenceNurse 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)

16Summary of EvidenceHigh 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).

17Results Evidence Answers Original QuestionResearch 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.

18Future ResearchMeta-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.

Future research projects include a meta-anlysis of all currently available acuity tools; the development of future acuity staffing tools to include unit specific measures of acuity; a relational study of patient outcomes measured against a patient acuity tool.19Plan of ImplementationA 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.

After a meta analysis is performed, focus groups comprised of stake holders, should conduct a literature review. Once the best acuity rating tool for that unit is determined, it should systematically be implemented. Finally, 20ConclusionsNurse 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).

21ReferencesAcar, 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), 284-299Hayes, 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.

22ReferencesLang, 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), 107-113.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.2005.05.002Twigg, 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.

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