Registered Nurse Staffing Research Articles

The Relationship between Nursing Home Staffing and Health Outcomes Revisited

ObjectiveNursing homes make staffing decisions in conjunction with choosing quality goals, potentially leading to endogeneity bias between staffing and quality. We use instrumental variables (IVs) to explore it. DesignRetrospective statistical analysis of 2017–2019 Payroll-Based Journal, Minimum Data Set, Nursing Home Care Compare, and Long-Term Care Focus. Settings and ParticipantsA total of 11,261 nursing homes nationally. MethodsWe estimated separate models for each of 6 quality measures as dependent variables, and registered nurses (RNs), certified nurse assistants (CNAs), and licensed practical nurses (LPNs) as independent variables, including other control variables associated with quality. The models were estimated using both ordinary least squares (OLS) and 2-stage least squares (2SLS) methods, the latter accounting for endogeneity. The IVs were defined as the average staffing of competing nursing homes in the same market as the index facility. ResultsEstimated coefficients for the quality measures in the 2SLS models were up to 5 times larger than in the OLS models. The 2SLS estimates for antipsychotic medications use increased with higher RN staffing [0.279 (0.004 to 0.553)] and decreased with higher CNAs [−0.125 (−0.198 to −0.052)]. Hospitalizations decreased with more RNs [−1.328 (−1.673 to −0.983)] and LPN staffing [−0.483 (−0.755 to −0.211])] and increased with CNA [0.201 (0.109 to 0.293)] staffing. Emergency room visits decreased with higher RNs [−1.098 (−1.500 to −0.696)] and increased with CNAs [0.191 (0.084 to 0.298)]. Long-stay activities of daily living [−0.313 (−0.416 to −0.209)] and short-stay functioning [−0.481 (−0.598 to −0.364)] improved only with higher CNA staffing and pressure sores improved only with increased RN staffing [−0.436 (−0.836 to −0.035)]. Conclusions and ImplicationsOur findings demonstrate the importance of accounting for endogeneity in studies of staffing and quality. Endogeneity changes conclusions about significance, direction, and magnitude of the relationship between staffing and specific quality measures. These findings highlight the need to further study and understand the nuanced relationship between different staffing types and different health outcomes such as the difference between the relationship of RN and CNA hours per resident day to antipsychotic quality measures.

Workforce thresholds and the non-linear association between registered nurse staffing and care quality in long-term residential care: A retrospective longitudinal study of English care homes with nursing

BackgroundCare needs amongst 425,000 dependent older residents in English care homes are becoming more complex. The quality of care in these homes is influenced by staffing levels, especially the presence of registered nurses (RNs). Existing research on this topic, often US-focused and relying on linear assumptions, has limitations. This study aims to investigate the non-linear relationship between RN staffing and care quality in English care homes using machine learning and administrative data from two major care home providers. MethodsA retrospective observational study was conducted using data from two English care home providers. Each was analysed separately due to variations in data reporting and care processes. Various care quality indicators and staffing metrics were collected for a 3.5-year period. Regression analysis and machine learning (random forest) were employed to identify non-linear relationships. Ethical approval was obtained for the study. ResultsUsing linear methods, higher skill mix – more care provided by RNs – was associated with lower incidence of adverse outcomes, such as urinary tract infections and hospitalisations. However, non-linear skill mix–outcome relationship modelling revealed both low and high skill mix levels were linked to higher risks. The effects of agency RN usage varied between providers, increasing risks in one but not the other. DiscussionThe study highlights the cost implications of increasing RN staffing establishments to improve care quality, suggesting a non-linear relationship and an optimal staffing threshold of around one-quarter of care provided by nurses. Alternative roles, such as care practitioners, merit exploration for meeting care demands whilst maintaining quality. This research underscores the need for a workforce plan for social care in England. It advocates for the incorporation of machine learning models alongside traditional regression-based methods. Our results may have limited generalisability to smaller providers and experimental research to redesign care processes effectively may be needed. ConclusionRNs are crucial for quality in care homes. Contrary to the assumption that higher nurse staffing necessarily leads to better care quality, this study reveals a nuanced, non-linear relationship between RN staffing and care quality in English care homes. It suggests that identifying an optimal staffing threshold, beyond which increasing nursing inputs may not significantly enhance care quality may necessitate reconsidering care system design and (human) resource allocation. Further experimental research is required to elucidate resource-specific thresholds and further strengthen evidence for care home staffing. Tweetable abstractHow much nursing care is needed to assure quality in care homes? Evidence from 2 English care home providers shows that nurse sensitive outcomes (an indicator of quality) are better when ~25 % of care is provided by nurses. Nurse shortages increase risks for residents.

There's No Substitute for Adequate Registered Nurse Staffing.

There's No Substitute for Adequate Registered Nurse Staffing.

Taking New Approaches to Coaching and Care Can Lift Nursing Numbers.

Nurses are the backbone of healthcare. Their retention and recruitment are essential to the success and sustainability of healthcare providers. For many years, Portland, Oregon-based Legacy Health enjoyed the luxury of a registered nurse (RN) turnover rate consistently as low as 7.6 percent and a vacancy rate of 2.49 percent. Suddenly, COVID-19 and a confounding exodus of nurses from the profession overran this excellent track record. Today, Legacy Health is rebuilding its RN workforce and staff resilience through new initiatives. Even with a dwindling RN talent pool and vacancy rates rapidly growing into the double digits, the leadership is closing the gap. For example, a coach model for precepting new graduate nurses has allowed the RN residency program to grow by more than 300 percent. Programs such as Schwartz Rounds, Code Lavender, and an inpatient throughput initiative are also improving RN wellness, reducing stress, and increasing retention.

Licensed Practical Nurses in Team Triage: A Safe Way to Address Nursing Shortages in the Emergency Department.

Background There is a Registered Nurse (RN) shortage across the United States that is predicted to intensify in the upcoming years. RNs are an integral part of Emergency Departments (EDs) and perform many vital tasks, including IV placement, blood draws, medication administration, acute assessments, and patient hand-offs. Thus, RN staffing is a crucial part of ED operations, and ED initiatives should account for RN workforce shortages. Given the increase in ED visits and crowding, throughput initiatives that can expedite patient care are integral to the functioning of an ED. Team Triage is a throughput initiative that has been shown to improve ED time to provider, length of stay, and left without being seen rates. In our institution, we created a Team Triage model where advanced practice providers (APPs) perform a patient's initial evaluation in triage and place orders for labs, intravenous (IV) catheters, and imaging. Given the RN staffing shortage, we incorporated Licensed Practical Nurses (LPNs) in Team Triage to place IV catheters and draw blood work for laboratory tests. The objective of this investigation was to describe a Team Triage model that incorporated LPNs and to report the patient safety and productivity of this model. Methods This was a single-site retrospective study at a large, academic, tertiary care center with over 100,000 annual visits. Adult patients who self-presented to the ED and went through Team Triage (11 am-11 pm) between Jan 1, 2020, and Jan 31, 2020, were included in this study. LPNs staffed the Team Triage, along with APPs. LPNs placed IV catheters and drew blood specimens for the Team Triage patients. The primary outcomes studied were the proportion of specimens mislabeled by LPNs, the proportion of patients receiving IV catheters, the proportion of patients receiving blood work, blood tubes drawn per hour, and IVs inserted per hour in Team Triage. Results During the study period, 1355 patients went through Team Triage. Of these patients, 1075 (79%) were ordered for blood work, and 1017 (75%) were ordered for an IV catheter. All Team Triage blood work and IV catheter placements were completed by LPNs, who staffed 372 hours of Team Triage. A total of 2558 blood tubes were collected by LPNs. The LPNs cared for 2.9 patients per hour, collected 6.9 blood tubes per hour, inserted 2.7 IV catheters per hour, and collected 2.4 blood tubes per patient. The LPNs had a 0% specimen mislabeling rate. Conclusion Due to the significant RN workforce shortage impacting Emergency Medicine coupled with increased ED crowding, there is a significant need to evaluate the integration of LPNs into Team Triage to place IV catheters and perform blood draws. This study shows that incorporating LPNs in Team Triage is a productive and safe way to address nursing shortages in Emergency Medicine.

Quality Matters: Examining the Impact of Nurse Staffing Challenges on Clinical Outcomes.

The purpose of this study was to examine nurse staffing while describing the relationships that exist in staffing and quality associated with nursing care during the COVID-19 pandemic, a significantly challenging time for nurse staffing. We examined the relationship between permanent registered nurse (RN) and travel RN staffing during the pandemic and the nursing-sensitive outcomes of catheter-associated urinary tract infections (CAUTIs), central line-associated bloodstream infections (CLABSIs), falls, and hospital-acquired pressure injuries (HAPIs) and length of stay and compared the cost of CAUTIs, CLABSIs, falls, and HAPIs in fiscal years 2021 and 2022. We used a descriptive, observational design to retrospectively examine permanent nurse staffing volume and CAUTI, CLABSI, HAPI, and fall counts from October 1, 2019, to February 28, 2022, and travel nurse volume for the most current 12 months, April 1, 2021, to March 31, 2022. Descriptive statistics, Pearson correlation, and statistical process control analyses were completed. Pearson correlation showed a statistically significant, moderately strong negative correlation (r = -0.568, p = .001) between the active registered nurse full-time equivalents (RN FTEs) and average length of stay (ALOS), and a moderately strong positive correlation (r = 0.688, p = .013) between the travel RN FTEs and ALOS. Pearson correlations were not statistically significant, with low to moderate negative correlations for CAUTIs (r = -0.052, p = .786), CLABSIs (r = -0.207, p = .273), and falls (r = -0.056, p = .769). Pearson correlation for active RN and HAPI showed a moderately strong, statistically significant positive correlation (r = 0.499, p = .003). We observed common cause variation in CAUTIs and CLABSIs, with HAPIs and falls showing special cause variation via statistical process control. Despite the challenges associated with the lack of available nurse staffing accompanied by increasing responsibilities including unlicensed tasks, positive clinical outcomes can be maintained by staff adherence to evidence-based quality improvement.

Authentic Leadership: Pearls of Wisdom

Authentic Leadership: Pearls of Wisdom

The Role Of Real Estate Investment Trusts In Staffing US Nursing Homes.

In 2021 real estate investment trusts (REITs) held investments in 1,806 US nursing homes. REITs are for-profit public or private corporations that invest in income-producing properties. We created a novel database of REIT investments in US nursing homes, merged it with Medicare cost report data (2013-19), and used a difference-in-differences approach within an event study framework to compare staffing before and after a nursing home received REIT investment with staffing in for-profit nursing homes that did not receive REIT investment. REIT investment was associated with average relative staffing increases of 2.15percent and 1.55percent for licensed practical nurses (LPNs) and certified nursing assistants (CNAs), respectively. During the postinvestment period, registered nurse (RN) staffing was unchanged, but event study results showed a 6.25percent decrease in years 2 and 3 after REIT investment. After the three largest REIT deals were excluded, REIT investments were associated with an overall 6.25percent relative decrease in RN staffing and no changes in LPN and CNA staffing. Larger deals resulted in increases in LPN and CNA staffing, with no changes in RN staffing; smaller deals appeared to replace more expensive and skilled RN staffing with less expensive and skilled staff.

STAFFING DIFFERENCES IN NURSING HOME SPECIAL FOCUS FACILITIES AND SPECIAL FOCUS FACILITY CANDIDATES

Abstract Introduction Centers for Medicare and Medicaid Services designates “Special Focus Facilities” (SFF), which are nursing homes receiving special oversight for persistent quality problems. “Special Focus Facility Candidates” (SFFc) are nursing homes with quality problems that are designated as candidates to be future SFFs. Recent academic literature has not examined if SFF and SFFc have significant differences in staffing hours per resident day (HPRD). Methods Nursing homes that were SFF or SFFc in 2020 were matched to 5-star nursing homes. Monthly staffing averages were aggregated, and two-way ANOVAs with Tukey Post Hoc were conducted to detect level differences in HPRD across the three facility groups. Gross and Case-Mix staffing HPRD were analyzed, along with daily resident census. Results The final sample was n=197 SFFc, and n= 50 SFF, which were matched with n=247 5-star nursing homes for a total sample of Nf494. Over 2020, daily census for 5-star nursing homes was lower (M=72.36, SD=52.5) than SFFc (M=93.77, SD=68.34) or SFFs (M=97.88, SD=44.06). There was a significant difference between SFF and SFFc HPRD in Case-Mix Aide F(2, 5748)=187.6, p= < .005, and Registered Nurse (RN), F(2,5748)=323,p=.003 care. There were no significant differences between SFF and SFFc in HPRD Aide F(2,5748)=380,p=.63, Practical Nurse F(2,5748)=1.1, p=.211, Case-Mix Practical Nurse F(2,5748)=19.57,p=.39, Case-Mix RN F(2,5748)=9.51,p=.91 or Total HPRD F(2,5748)=472.6,p=.16, care. Discussion: There is only a significant difference in staffing levels observed between SFF and SFFc for Aide staffing and RN staffing. This information supports researchers and policymakers in delineating the differences and similarities between SFF and SFFcs.

TEXAS NURSING HOMES INCREASED DIRECT-CARE STAFFING LEVELS DURING WINTER STORM URI

Abstract Prior work suggests that nursing homes (NHs) increase their registered nurse (RN), licensed practical nurse (LPN), and certified nursing assistant (CNA) staffing levels in anticipation of a major hurricane. However, less is known about NHs’ ability to increase staffing levels during a winter storm. We examined RN, LPN, and CNA staffing levels in 1,170 Texas NHs during Winter Storm Uri from February 13-20, 2021. This storm was characterized by cold temperatures and snow/ice accretion that affected the Texas power grid. Linear mixed effects models were adjusted for profit status, continuing-care retirement community status, resident census, overall star rating, a weighted deficiency score, number of citations for infection control, number of substantiated complaints, and county fixed-effects. After adjustment, Texas NHs decreased RN (β=-0.005;b=-0.002;p=.004) but increased LPN (β=0.022;b=0.009;p<.001) and CNA (β=0.044;b=0.026;p<.001) staffing levels. NHs face unprecedented challenges during winter storms, including maintaining adequate staffing levels to meet the needs of their residents.

Skilled Nursing Facility Participation in Bundled Payments Was Related to Small Increases in Nurse Staffing Levels.

Medicare implemented Bundled Payments for Care Improvement (BPCI) Model 3 in 2013, in which participating skilled nursing facilities (SNFs) were accountable for episode costs. We performed comparative interrupted time series analyses to evaluate associations between SNF BPCI participation and nurse staffing levels, using Medicare claims, resident assessments, and facility-level and market-level files of 2010-2017. For persistent-participating SNFs, BPCI was associated with improved certified nursing assistant (CNA) staffing levels (differential change = .03hours, p = .025). However, BPCI was not related to changes in registered nurse (RN) and all licensed nurse hours, and nurse skill mix. Among drop-out SNFs, BPCI was associated with increased RN staffing levels (differential change = .02hours, p = .009), leading to a higher nurse skill ratio (0.51 percentage points, p = .016) than control SNFs. Bundled payments for care improvement had no impact on CNA and all licensed nurse staffing levels. In conclusion, BPCI was associated with statistically significant but small increases in nurse staffing levels.

HRM Practices, Organizational Culture and Nurse Staffing Turnover among High-Medicaid Nursing Homes

Nurse staffing turnover has been associated with nursing home quality, such as worse resident outcomes, higher rates of infection, and hospitalizations. Nurse staffing turnover can be worse in under-resourced nursing homes, such as those with a high proportion of Medicaid residents. These organizations may lack the resources to attract and retain nurse staff, and this could contribute to higher nurse turnover. However, even within this group of under-resourced nursing homes, we observe variations in nurse turnover rates. Using the resource-based view of the firm (RBV), we explored the role that both human resource management (HRM) practices and organizational culture may have in explaining the variations in nursing staff turnover among high Medicaid nursing homes. Data consisted of survey and secondary data sources for 2017-2018. Survey data comprised 348 responses (33% response rate) from a national mailer of US nursing home administrators in high-Medicaid (85% or higher) facilities. Survey data were merged with secondary datasets including Long-Term Care Focus (LTCFocus) and the Area Health Resource File (AHRF). The dependent variables (nurse staffing turnover rates) consisted of the percentages of registered nurses (RNs)/licensed practical nurses (LPNs)/certified nurse aides (CNAs) that had voluntarily quit the organization during the past year. The first independent variable, HRM practices, consisted of three sub-scales: traditional, employee-centered, and high involvement practices. The second independent variable consisted of nursing homes’ classification into one of four organizational cultures: clan, market, hierarchical, and non-dominant. Organizational and market variables were controlled for. Data were modeled using Poisson log-linear regression, and propensity score weights were used to adjust for potential survey non-response bias. Results show that high involvement HRM practices and having a clan culture (compared to a market, hierarchical, and non-dominant culture) are associated with lower RN, LPN, and CNA staffing turnover. The findings of this study highlight the importance of organizational culture as well as HRM practices for practitioners and policy makers to more effectively target their efforts to reduce nurse turnover in high Medicaid nursing homes. By reducing turnover, these under-resourced facilities may be able to lower costs and improve their financial performance, which may ultimately reduce the likelihood of closure with implications for access to long-term care. Similarly, lower nurse staffing turnover rates may improve quality of care for a particularly vulnerable nursing home population, i.e. those with lower SES and racial/ethnic minorities.

The Relationship of Registered Nurse Staffing and Nursing Home Quality Measure Star Ratings

The Relationship of Registered Nurse Staffing and Nursing Home Quality Measure Star Ratings

Association of Registered Nurse Staffing With Mortality Risk of Medicare Beneficiaries Hospitalized With Sepsis

Sepsis is a major physiologic response to infection that if not managed properly can lead to multiorgan failure and death. The US Centers for Medicare & Medicaid Services (CMS) requires that hospitals collect data on core sepsis measure Severe Sepsis and Septic Shock Management Bundle (SEP-1) in an effort to promote the early recognition and treatment of sepsis. Despite implementation of the SEP-1 measure, sepsis-related mortality continues to challenge acute care hospitals nationwide. To determine if registered nurse workload was associated with mortality in Medicare beneficiaries admitted to an acute care hospital with sepsis. This cross-sectional study used 2018 data from the American Hospital Association Annual Survey, CMS Hospital Compare, and Medicare claims on Medicare beneficiaries age 65 to 99 years with a primary diagnosis of sepsis that was present on admission to 1 of 1958 nonfederal, general acute care hospitals that had data on CMS SEP-1 scores and registered nurse workload (indicated by registered nurse hours per patient day [HPPD]). Patients with sepsis were identified based on 29 International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes. Data were analyzed throughout 2021. SEP-1 score and registered nurse staffing. The patient outcome of interest was mortality within 60 days of admission. Hospital characteristics included number of beds, ownership, teaching status, technology status, rurality, and region. Patient characteristics included age, sex, transfer status, intensive care unit admission, palliative care, do-not-resuscitate order, and a series of 29 comorbid diseases based on the Elixhauser Comorbidity Index. In total, 702 140 Medicare beneficiaries (mean [SD] age, 78.2 [8.7] years; 360 804 women [51%]) had a diagnosis of sepsis. The mean SEP-1 score was 56.1, and registered nurse HPPD was 6.2. In a multivariable regression model, each additional registered nurse HPPD was associated with a 3% decrease in the odds of 60-day mortality (odds ratio, 0.97; 95% CI 0.96-0.99) controlling for SEP-1 score and hospital and patient characteristics. The results of this cross-sectional study suggest that hospitals that provide more registered nurse hours of care could likely improve SEP-1 bundle compliance and decrease the likelihood of mortality in Medicare beneficiaries with sepsis.

요양병원 간호인력 확보수준과 요양병원 등급에 따른 입원환자 간호결과

Purpose: This study was conducted to examine the relationship between nursing outcomes of the elderly and the staffing level of registered nurses and nurse aids to enhance the quality of care in long-term care hospitals. Methods: A secondary data analysis was performed using a long-term care hospitals database collected by the Health Insurance Review and Assessment Services from October to December 2015. The database was collected from 1056 long-term care hospitals and includes variables such as Registered Nurse (RN), Nurse Aid (NA), RN and NA staffing; grade of hospitals; and 8 nursing outcome indicators. Results: Findings showed that the number of patients per RN & NA was a significant indicator of the ratio of patients with pressure ulcer improvement in the high-risk group, the decline in ADL of patients without dementia, and transfer abilities in both dementia and non-dementia groups. The nursing outcomes were closely related to the hospital grade. The better grade, the better nursing outcomes. Conclusion: Enhance nursing outcomes in elderly patients; it is required to reconsider the policies on the RN staffing ratio as a way to enhance the RN staffing ratio in long-term care hospitals.

End-of-life care practices in Korean nursing homes: A national survey

BackgroundBoth globally and nationally, determinants of end-of-life care practices in nursing homes, such as laws and workforce, vary widely, resulting in a huge disparity in the quality of such practices. Despite the rapid growth in the number of nursing homes and increasing social attention being paid to end-of-life care in South Korea, little is known about these practices and how they differ because of nursing home-related regulations and nurse staffing. ObjectivesTo examine end-of-life care practices in nursing homes and compare them between nursing homes with 30 beds or more and those with fewer than 30 beds (the cut-point where nursing home-related regulations differ) and between nursing homes with and without registered nurses. DesignA cross-sectional exploratory study using data from a national survey conducted by the National Health Insurance Service. SettingsNursing homes certified by the national long-term care insurance in South Korea. ParticipantsNursing representatives from 836 nursing homes. MethodsMeasures of end-of-life care practices included the identification of residents’ (or families’) preferences for the place of death and a do-not-resuscitate order, the provision of end-of-life care on-site, and the presence of end-of-life care protocols. Descriptive statistics and logistic regression were used to compare end-of-life care practices by bed size and registered-nurse staffing. ResultsOf the 836 nursing homes, 85% and 84.1% identified the preference for the place of death and a do-not-resuscitate order mostly from surrogates, respectively. The most preferred places of death were nursing homes (53.3%) and hospitals (46.0%). Approximately, 72% responded that on-site end-of-life care protocols were present, and 50.8% reported providing end-of-life care on-site. Compared to nursing homes with 10–29 beds, those with 30 beds or more were more likely to identify the preference for a do-not-resuscitate order (OR 2.392, 95% CI 1.643–3.482); have in place end-of-life care protocols (OR 1.829, 95% CI 1.341–2.496); and provide end-of-life care on-site (OR 1.556, 95% CI 1.169–2.072). Compared to nursing homes without registered nurses, those with registered nurses were also more likely to identify the preference for a do-not-resuscitate order (OR 1.717, 95% CI 1.142–2.583) and provide end-of-life care on-site (OR 1.663, 95% CI 1.254–2.206). ConclusionsThe findings indicate a huge disparity in end-of-life care practices in nursing homes across South Korea by bed size-based nursing-home regulations and registered-nurse staffing. Law/regulation- and policy-level changes are needed to promote robust end-of-life care in nursing homes. Study registrationNot registered.

Using the Electronic Health Record Patient Census and Acuity Data to Determine Acuity-Based Staffing in the Labor and Delivery Unit

In 2010, The Association of Women’s Health, Obstetric and Neonatal Nurses (AWHONN) published Guidelines for Professional Registered Nurse Staffing for Perinatal Units to address the challenges of staffing in perinatal units. This quality improvement project was initiated with the goal of developing an electronic report within the electronic health record system to quantify registered nurse (RN) hourly staffing needs based on patient census and acuity. These data would then be analyzed to determine trends and RN staffing needs for each 24-hour period and each day of the week and identify staffing patterns to meet AWHONN’s staffing guidelines.

AWHONN Members’ Recommendations on What to Include in Updated Standards for Professional Registered Nurse Staffing for Perinatal Units

ObjectiveTo solicit advice from members of the Association of Women’s Health, Obstetric, and Neonatal Nurses (AWHONN) on what to include in an update of nurse staffing standards. DesignOnline, single-question survey with thematic analysis of responses. SettingElectronic survey link sent via e-mail. ParticipantsAWHONN members who shared their e-mail with the association and who responded to the survey (n = 1,813). MeasuresParticipants were asked to answer this single question: “The AWHONN (2010) Guidelines for Professional Registered Nurse Staffing for Perinatal Units are being updated. During their initial development, feedback from nearly 900 AWHONN members was extremely helpful in providing specific details for the nurse staffing guidelines. We’d really like to hear from you again. Please give the writing team your input. What should AWHONN consider when updating the AWHONN nurse staffing guidelines?” ResultsThe e-mail was successfully delivered to 20,463 members; 8,050 opened the e-mail, and 3,050 opened the link to the survey. There were 1,892 responses. After removing duplicate and blank responses, 1,813 responses were available for analysis. They represented all hospital practice settings for maternity and newborn care and included nurses from small-volume and rural hospitals. Primary concerns of respondents centered on two aspects of patient acuity—the increasing complexity of clinical cases and the need to link nurse staffing standards to patient acuity. Other themes included maintaining current nurse-to-patient ratios, needing help with implementation in the context of economic challenges, and changing wording from “guidelines” to “standards” to promote widespread adoption. ConclusionIn a single-question survey, AWHONN members offered rich, detailed recommendations that were used in the updating of the AWHONN nurse staffing standards.

Alternative Approaches to Ensuring Adequate Nurse Staffing: The Effect of State Legislation on Hospital Nurse Staffing.

The objective of this study was to addresses the basic question of whether alternative legislative approaches are effective in encouraging hospitals to increase nurse staffing. Using 16 years of nationally representative hospital-level data from the American Hospital Association (AHA) annual survey, we employed a difference-in-difference design to compare changes in productive hours per patient day for registered nurses (RNs), licensed practical/vocational nurses (LPNs), and nursing assistive personnel (NAP) in the state that mandated staffing ratios, states that legislated staffing committees, and states that legislated public reporting, to changes in states that did not implement any nurse staffing legislation before and after the legislation was implemented. We constructed multivariate linear regression models to assess the effects with hospital and year fixed effects, controlling for hospital-level characteristics and state-level factors. Compared with states with no legislation, the state that legislated minimum staffing ratios had an 0.996 (P<0.01) increase in RN hours per patient day and 0.224 (P<0.01) increase in NAP hours after the legislation was implemented, but no statistically significant changes in RN or NAP hours were found in states that legislated a staffing committee or public reporting. The staffing committee approach had a negative effect on LPN hours (difference-in-difference=-0.076, P<0.01), while the public reporting approach had a positive effect on LPN hours (difference-in-difference=0.115, P<0.01). There was no statistically significant effect of staffing mandate on LPN hours. When we included California in the comparison, our model suggests that neither the staffing committee nor the public reporting approach alone are effective in increasing hospital RN staffing, although the public reporting approach appeared to have a positive effect on LPN staffing. When we excluded California form the model, public reporting also had a positive effect on RN staffing. Future research should examine patient outcomes associated with these policies, as well as potential cost savings for hospitals from reduced nurse turnover rates.

Value of Nurse Practitioner Inpatient Hospital Staffing.

Evidence indicates hospitals with better registered nurse (RN) staffing have better patient outcomes. Whether involving more nurse practitioners (NPs) in inpatient care produces better outcomes is largely unknown. The objective of this study was to determine whether the presence of more NPs produces better inpatient outcomes net of RN staffing. This was a 2015-2016 cross-sectional data on 579 hospitals linked from: (1) RN4CAST-US nurse surveys; (2) Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) patient surveys; (3) surgical patient discharge abstracts; (4) Medicare Spending per Beneficiary (MSPB) reports; (5) American Hospital Association (AHA) Annual Survey. Hospitals were grouped according to their NP/beds ratios [<1 NP/100 beds (N=132), 1-2.99 NPs/100 beds (N=279), and 3+ NPs/100 beds (N=168)]. RNs randomly sampled nurses from licensure lists yielded 22,273 RNs in study hospitals; discharge data for 1.4 million surgical patients; HCAHPS data for 86% of study hospitals. Mortality, readmissions, lengths of stay, MSPB, patient experience, and quality reported by patients and nurses. After adjustments, patients in hospitals with 3+ NPs/100 beds had lower odds than patients in hospitals with <1 NP/100 beds of 30-day mortality [odds ratio (OR)2=0.76; 95% confidence interval (CI)=0.67-0.82; P<0.001] and 7-day readmissions (OR2=0.90; 95% CI=0.86-0.96; P<0.001), shorter average length of stay (incident rate ratio2=0.92; 95% CI=0.88-0.96; P<0.001) and 5.4% lower average MSPB (95% CI=3.8%-7.1%). Patients and nurses in the hospitals with higher NP/bed ratios were significantly more likely to report better care quality and safety, and nurses reported lower burnout, higher job satisfaction, greater intentions of staying in their jobs. Having more NPs in hospitals has favorable effects on patients, staff nurse satisfaction, and efficiency. NPs add value to existing labor resources.