Nurse Staffing Ratio Impact on Patient Outcomes

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Table of Contents

Abstract
Introduction
Review of Relevant Literature
Methods
Data Analysis
Discussion and Findings
References

Abstract

The purpose of this research proposal is to analyze interventions aimed at reducing the risk of adverse events associated with poor hospital staffing ratios. Inadequate nursing staff ratios have been an ongoing concern in the nursing field. The author asked, if nursing errors can be attributed to (C) unsafe nurse patient ratios, will a reduction in (I) nurse patient ratio result in better patient outcomes (O) for patients (P) in (S) hospital settings. The authors conducted a literature review that examines the standing knowledge of the question. The authors located more than 20 journal articles, including systematic reviews and articles from nursing journals. In sum, the authors conclude that most published studies demonstrate a relationship between improved nursing staffing ratios and patient outcomes, however, systematic analysis of the data reveals that controlled studies are necessary to provide the highest quality evidence to demonstrate how increased staffing can affect patient outcomes.

Introduction

Nurse patient ratio is a hot topic these days, its in the news, and even politicians are getting involved. Nurses around the country are rallying for better patient outcomes about safe staffing levels in hospitals. There is a call for nurses in America to join in the campaign for safer staffing ratios (National Nurse United, 2016). Politicians are involved with the campaign to ensure that patient outcomes are positive with safe staffing. Presidential candidate Bernie Sanders supports the Patient Advocacy Act, which would limit the number of patients each nurse can care for, to provide better outcomes for patients (Bernie, 2016).

Representative Lois Capps (CA-24) and former nurse, along with Representative David Joyce (OH-14) have sponsored a bill to ensure safe nurse staffing, and to reduce nurse fatigue, to lead to better health outcomes for patients (Capps, 2015). Many studies report when nurse patient ratio is limited the patients have a better outcome. When nurses work at unsafe nurse patient ratios, patients suffer for it. Nurses are on the frontlines of healthcare. Nurses are qualified to determine what safe practice for their patients are. Often nurses are overworked, tired, have not taken adequate breaks, or even have time for bathroom breaks (Haines, 2012). If nurses are foregoing their health this is not good for patients (The Oncology Nurse Community, 2012).

Nursing errors can be attributed to unsafe nurse patient ratios, if nurse patient ratio is decreased, there will be fewer nurse related errors, improving patient outcomes. This paper will explore some ways nursing errors have harmed patients through unsafe staffing, and why nurses have missed nursing duties related to a patients well-being. This paper will determine if nurse staffing ratios are reduced, that there will be less fatigue for nurses, less missed nursing duties, and increased survival for patients, resulting in better outcomes for the patients. Research shows that nurses have missed nursing duties because of an unexpected rise in patient volume, or acuity of patients, an inadequate number of staff, heavy admissions and discharges, and medication not available (Maloney, Fencl & Hardin, 2015). Research also has shown that improved nurse work conditions increase the survival of patients (McHugh et al., 2016).

Review of Relevant Literature

Improved nurse patient ratios have a relationship with reductions in negative patient outcomes such as hospital-related mortality and morbidity in most published studies.

Silber et al. (2016) found that hospitals with above-average staffing levels were associated with lower mortality compared with hospitals without nursing environment recognition and with below-average staffing. The study showed that the patients undergoing general surgery at hospitals with better nursing staff ratios received higher quality care.

Moreover, nursing patient ratios negatively affect nurse sensitive patient outcomes such as failure-to-rescue (FTR). Ghaferi & Friese (2016) noted that hospitals with better staffing ratios have a nearly 20% lower FTR rate than control hospitals with poorer staffing. The same study noted that poor ratios negatively impact higher risk patients, Better nursing environments was associated with lower ICU length of stay (Sakr et al., 2015).

Furthermore, evidence suggests critically ill patients suffer most. It was found that an increase of a nurse to patient ratio over 1:2 in ICU was associated with an increased risk of hospital death. Furthermore, Aiken et al. (2014) linked nurse workload with patient survival rate in common surgeries such as hip/knee replacement, appendectomy, gall bladder surgery, and vascular procedures. Furthermore, pediatric patients are particularly vulnerable to poor nurse-patient ratios.

Inadequate RN staffing levels adversely affect patients through missed nursing duties that lead to reduced quality care and poor outcomes. Dabney & Kalisch (2015) found that activities such as delivering timely medications, repositioning patients, helping the patient to ambulate, patient education, and assessing the effectiveness of interventions are missed or delayed because of inadequate staffing.

Do reduced ratios produce less fatigue/burnout, less missed duties, increased survival for patients, and better outcomes?

McHugh et al. (2016) found evidence that better nurse staff ratios result in better outcomes for patients. The study found that adequate nurse patient ratios were associated with survival following in hospital cardiac arrest. Variable staffing levels in medical surgical units are associated with lower odds of survival, noting that units with staffing standards, such as ICU, have stabilized patients odds of survival. The study shows a direct link between the nurses workload and patient safety.

Improved nursing staff ratio reduced preventable admissions. McHugh et al. (2016) found that hospitals with higher nursing staff ratios had 25 percent lower odds of preventable admissions in contrast with hospitals with poor nurse patient staffing.

Methods

Many clinical reports were reviewed to determine if higher nurse patient ratios improve patient outcomes. Many reports support the evidence. McHugh et al. (2016) concluded that patients who had in-hospital cardiac arrests (IHCA) had a better chance of survival if there were better work conditions and decreased patient to nurse ratios. Initially, 91 hospitals and 14,001 patients were included in the study. Finally, a total of 11,160 patients in 75 hospitals in Pennsylvania, Florida, California, and New Jersey were included in a cross-sectional study between 2005 and 2007. Those excluded did not fit the criteria for the study. 9 hospitals had less than 10 IHCAs, 7 hospitals were missing staffing information, 2,567 patients omitted because IHCA did not occur in medical cardiac, ICU, medical-surgical, or telemetry unit, 15 patients were under 18years, 209 patients had implanted cardioverter defibrillators.

Data were obtained from 3 sources, The American Heart Associations (AHA) Get with the Guidelines In-Hospital Cardiac Arrest-Resuscitation (GWTG-R) database, University of Pennsylvania Multi-State Nursing Care and Patient Safety Survey, and the AHAs annual survey of hospitals. Standardized software used by data abstractors that are certified as a 2.4% error rate. Outcome Services is a data collection and coordination center for GWTG-R. Cases were identified by cardiac arrest flow sheets, hospital paging system log review, routine code cart checks, pharmacy drug records, and hospital billing for resuscitation medications. Previous nursing survey data collected for Pennsylvania, California, New Jersey, and Florida were used. 100,000 nurses responded to the survey from all 4 states. Nurses were asked to report the number of patients and nurses on the last shift.

They found from a direct survey measure of staffing to be superior to other data resources in predicting patient outcomes. The 31 item Practice Environment Scale of the Nursing Work Index (PES-NWI) measures the nurse work environment and has widely been used in research, which has established reliability and validity. A risk-adjustment approach includes controls for age, select conditions present before IHCA, pre-IHCA critical care interventions, and initial IHCA rhythm all associated with IHCA survival. Also included were variables indicating if the IHCA was in the ICU, or witnessed. The study concluded that patients who had IHCA were more likely to survive when the work environment was better and had a decreased nurse patient ratio (McHugh et al., 2016).

Studies have shown that nurses miss care of patients when they have an unexpected rise in patient volume or acuity, inadequate staffing, not enough assistive personnel, heavy admissions and discharges, and medications not available. Missed care for patients are, ambulation, turning every 2 hours, giving medication on time, mouth care, and feeding while food is still warm are the top missed care functions (Dabney & Kalisch, 2015). The method for this descriptive study is a convenience sample of nursing staff from 16 inpatient units from 3 hospitals in North Carolina. They were asked to complete a MISSCARE survey which was developed to measure missed care. MISSCARE tool met standards for validity and reliability, and acceptable rates were high.

MISSCARE survey contains 17 multiple choice and open-ended questions. The questions focus on staff and work environment characteristics and job satisfaction. It asked to rank frequency of care missed, there were 24 choices with 17 reasons care was missed. Full time and part time nurses participated along with licensed practical nurses and nurse technicians. 750 nursing staff was recruited, and 205 completed the survey. Staff was able to participate in the survey after consent for participation was given, and went online to complete the survey. Those participating were entered into a drawing for a gift certificate towards continuing education activities. This study identifies frequency and reasons for missed care which has a relationship to patient outcomes (Maloney, Fencl & Hardin, 2015).

Patrician et al. (2011) completed a study that demonstrated the association between nurse staffing and adverse events at the shift lever. The results of this survey found that adverse events occurred where fewer personnel were staffed and especially fewer nurses on staff. The data for this analysis comes from the Military Nursing Outcome Database (MilNOD). 13 military hospitals participated chosen for military affiliation and nearness to study hub sites, with a total of 115,062 shifts from 2003 to 2006. Staffing measures used were total nursing care hours per patient per shift, skill mix, and shift interval which used 8 hour shifts. Adverse event measures were sourced from incident reports. Covariates are continuous control variables that are observed (Dictionary.com, 2016).

Census, acuity, hospital size, temporal covariates (shift time, day, and year) correlates to adverse events or staffing. After approval from the institutional review board, the study was introduced to major stockholders. Staff proficiency was implemented in the data collection process. 12 hour shifts were separated into 8 hours and 4 hours. Shift hours were (7:00 am to 2:59) pm, (3:00 pm to 10:59 pm), and 11:00 pm to 6:59 am), at the end of the shift, entered hours worked by each provider type, and staff category into a Microsoft database. For adverse events, incident reports were reviewed by trained nurses, and a 3 month wait to ensure all incidents were captured for review. Reliability and validity were built in the early phase of the project. Study staff was available to verify data entry and coding practices. Outliers were reconciled with managers (Patrician et al., 2011).

Aiken et al., (2010) studied California mandated minimum nurse patient ratio with hospitals in New Jersey and Pennsylvania to determine if there is a difference in patient outcomes. Primary survey data sourced from 22,336 hospitals in 2006 and state hospital discharge databases were studied. Nurses with active licenses were asked to participate. Only those who worked in a hospital were chosen. Hospital staff nurses were the target population. They were asked about where they worked, their work environment, patient loads, and the number of nurses and patients at the end of their last shift.

They determined this method of data collection eliminates bias which is a threat to validity. Survey mailings were sent out with a 35.4% response. Non responders received incentives to respond and a second mailing went out with a 91% response rate. There were differences in demographics, ages, race/ethnicity, and experience were varied. Logistic regression models to estimate the effects of nurse staffing on 30-day inpatient mortality and FTR. Self-reports of workloads may have some bias, however, prior work with self-reports have had predictive validity. This report concludes that lower nurse patient ratios have lower mortality, nurse burnout, and job dissatisfaction was lower (Aiken et al., 2010).

Data Analysis

A critique of the relevant literature reveals moderate quality evidence that unsafe nurse patient ratios negatively impact patient outcomes. Nurses miss out on nursing duties because of poor staffing or changes in patient volumes that result in unsafe nurse patient ratios. Furthermore, improving nursing working conditions such as nurse patient ratios improves patient outcomes.

How does it adversely affect outcomes?

i.e. Missed duties?

Do reduced ratios produce less fatigue/burnout, less missed duties, increased survival for patients, and better outcomes?

Narrative critique analyzes the quality of evidence with attention to quality of design, the relevance of research study to overall questions, strength of intervention effects)

Identify evidence and relation to client and family values, clinicians factors, and internal/external research to make an informed clinical decision about treatment

Discussion and Findings

It is imperative to note that the results of the research were expected because most scholars have reached a consensus on this topic and regard it as a significant problem, but several fascinating aspects should be highlighted. Inadequate staffing levels can lead to severe complications most of the time. The sample size is sufficient in this case to state that the results of the research are statistically significant. Moreover, the knowledge that has been gained in previous studies can be expanded in this case. Findings support the idea that such interventions are needed to reduce the possibility of occurrence of adverse events in a health care facility. For instance, McHugh, Berez, & Small (2013) have researched the way nursing staffing affects readmission penalties, and the results suggest that hospitals are capable of providing much more efficient care when the number of professionals is higher. Also, it is necessary to consider the experience of other countries in this area.

Cho, Kim, Yeon, You, & Lee (2015) suggest that an increase in the number of patients per nurse has reduced the level of quality of services in South Korea. Such results indicate that this is a common problem all over the globe, and such aspects as techniques and guidelines that are utilized do not play a significant role as believed by many. The difference in health care approaches between these two regions is enormous, but the problem remains. A study by Ersek et al. (2013) suggests that staffing levels affect aid interventions because nurses are much more likely to participate in discussions, and it would lead to positive outcomes. Another aspect that should be highlighted is that it has been noted that a relationship between the numbers of other professionals is also present. Moreover, such data should not be overlooked, and the results of this research expand on the information because it has been proven that nursing staffing may lead to many other critical issues.

Further research is required because it would be beneficial to improve an understanding of how the performance of nurses is affected by other health care professionals. Another problem that is worthy of a discussion is that many institutions have to deal with limited funding, and it complicates the situation. Moreover, it is not possible to increase the number of health care professionals without making sacrifices in other areas. Another aspect that should be mentioned is that the number of such professionals is limited in some regions, and they cannot be substituted because it would lead to additional expenses. Furthermore, much more attention should be devoted to education and training (Yang, Hung, & Chen 2015).

Also, it would be beneficial to study the correlations between problematic events that may occur because of staffing numbers because it is evident that this problem has an enormous impact on positive outcomes. Also, it may be necessary to research the way modern technologies can be utilized to increase the efficiency of operations. The correct proportion of staff members should be selected individually based on various factors such as the needs of the population and available resources. Understandably, health care professionals have to deal with numerous tasks, and they should not overwork, but techniques that could be used to increase the level of productivity without affecting quality would be quite helpful. Overall, it is possible to state that these results support the hypothesis that staffing ratios have an enormous impact on patient outcomes.

McHugh et al. (2016) researched what would happen to patients if increased nurse to patient ratio were implemented, specifically the association with nurse staffing, work environments and in-hospital cardiac arrest (IHCA) survival. A cross-sectional study conducted included data from 3 sources, The American Heart Associations (AHA) Get with the Guidelines In-Hospital Cardiac Arrest-Resuscitation (GWTG-R) database, University of Pennsylvania Multi-State Nursing Care and Patient Safety Survey, and the AHAs annual survey of hospitals. Data was collected from 2005 through 2007. The AHAs survey was implemented in 4 states, Pennsylvania, New Jersey, California, and Florida. These hospitals are representative of hospitals nationwide, and represent over 20% of hospital admissions. Data for the IHCA came from the GWTG-R. The GWTG-R is a large prospective national quality-improvement registry

Aiken et al. (2010) wanted to determine the patient outcomes from California with mandated minimum nurse patient ratios with hospitals in New Jersey and Pennsylvania which do not have mandates minimum nurse patient ratios. The methods used were from surveys from primary data completed in 2006. Large random samples were chosen from nurses with active licenses but the research was limited nurses working in hospitals. This was to eliminate response bias. A Dilman approach was used for the survey. Surveys were mailed and used along with telephone reminders, and financial incentives to encourage responses, 91% response was obtained. A sample of 22,336 nurses was surveyed from California, New Jersey, and Pennsylvania. The researchers made sure that the nurses in New Jersey and Philadelphia had workloads that were below levels mandated by California laws.

References

Aiken, L. H., Sloane, D. M., Bruyneel, L., Van den Heede, K., Griffiths, P., Busse, R.,&Sermeus, W. (2014). Nurse staffing and education and hospital mortality in nine European countries: a retrospective observational study. Lancet, 383(4), 1824-1830. Web.

Aiken, L. H., Sloane, D. M., Cimiotti, J., Clarke, S., Flynn, L., Seago, J. A.,&Smith, H. (2010). Implications of the California nurse staffing mandates for other states. Health Services Research, 45(4), 904-921. Web.

Bernie. (2016). Fighting for nurses. Web.

Capps, L. (2015). Capps, Joyce reintroduce bipartisan legislature to improve patient care and support nurses. Web.

Cho, S., Kim, Y., Yeon, K., You, S., & Lee, I. (2015). Effects of increasing nurse staffing on missed nursing care. International Nursing Review, 62(2), 267-274.

Dabney, B. W., & Kalisch, B. J. (2015). Nurse staffing levels and patient-reported missed nursing care. Journal of Nursing Care Quality, 30(4), 306-312.

Dictionary.com. (2016). Covariate.

Ersek, M., Sefcik, J. S., Lin, F., Lee, T. J., Gilliam, R., & Hanson, L. C. (2013). Provider staffing effect on a decision aid intervention. Clinical Nursing Research, 23(1), 36-53. Web.

Ghaferi, A. A., & Friese, C. R. (2016). Revisiting nursings effect on surgical quality and cost. JAMA Surgery.

Haines, N. (2012). The healthy nurse pees. The Oncology Nurse Community.

Maloney, S., Fencl, J. L., & Hardin, S. R. (2015). Is nursing care missed? A comparative study of three North Carolina pospitals. MEDSURG Nursing 24(4), 229-235.

McHugh, M. D., Berez, J., & Small, D. S. (2013). Hospitals with higher nurse staffing had lower odds of readmissions penalties than hospitals with lower staffing. Health Affairs, 32(10), 1740-7.

McHugh, M., Rochman, M., Sloane, D., Berg, R., Mancini, M., Nadkarni, V., & Merchant, R. (2016). Better nurse staffing and nurse work environments associated with increased survival of in-hospital cardiac arrest patients. Medical Care. 54(1), 74-80.

National Nurse United. (2016). National campaign for sate RN-to-patient safety ratios.

Patrician, P., Loan, L., McCarthy, M., Friedman, M., Donaldson, N., Bingham, M., & Brosch, L. (2011). The association of shift level nurse staffing with adverse patient events. Journal of Nursing Administration. 41(2). 64-70. Web.

Sakr, Y., Moreira, C. L., Rhodes, A., Ferguson, N. D., Kleinpell, R., Pickkers, P.,&Vincent, J. (2015). The impact of hospital and ICU organizational factors on outcome in critically ill patients: Results from the extended prevalence of infection in intensive care study. Critical Care Medicine, 43(3), 519-526.

Silber, J. H., Rosenbaum, P. R., McHugh, M. D., Ludwig, J. M., Smith, H. L., Niknam, B. A.,&Aiken, L. H. (2016). Comparison of the value of nursing work environments in hospitals across different levels of patient risk. JAMA Surgery.

Yang, P., Hung, C., & Chen, Y. (2015). The impact of three nursing staffing models on nursing outcomes. Journal of Advanced Nursing, 71(8), 1847-1856.

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