Diverse perspectives on unit-level nurse staffing ratios in medical-surgical units: A Delphi policy analysis.

BACKGROUND: Appropriate staffing is essential to acute care delivery. Staffing ratio policy generates controversy. PURPOSE: This study examines perspectives on unit-level nurse-to-patient ratio policy in adult medical-surgical units. METHOD: Delphi methodology uses an invited diverse panel to analyze a policy's effects. Panelists completed iterative surveys about the impact they expect from unit-level ratio policy. FINDINGS: Panelists demonstrated moderate agreement that the proposed policy could increase staffing levels, decrease patient length of stay, and reduce nurse attrition. Other potential outcomes included reducing staffing in units above the minimum and increasing short-term costs. Panelists agreed that the policy could increase patient safety and nurse satisfaction and did not agree about the effect on long-term cost and innovation. Panelists also anticipated a mostly positive effect on patients and nurses. DISCUSSION: Policies that set unit-level nurse-to-patient ratios offer a potential strategy to improve medical-surgical staffing. Policy design should consider the range of expected outcomes.

Comparing Factors Associated with Increased Stimulant Use in Relation to HIV Status Using a Machine Learning and Prediction Modeling Approach.

Stimulant use is an important driver of HIV/STI transmission among men who have sex with men (MSM). Evaluating factors associated with increased stimulant use is critical to inform HIV prevention programming efforts. This study seeks to use machine learning variable selection techniques to determine characteristics associated with increased stimulant use and whether these factors differ by HIV status. Data from a longitudinal cohort of predominantly Black/Latinx MSM in Los Angeles, CA was used. Every 6 months from 8/2014-12/2020, participants underwent STI testing and completed surveys evaluating the following: demographics, substance use, sexual risk behaviors, and last partnership characteristics. Least absolute shrinkage and selection operator (lasso) was used to select variables and create predictive models for an interval increase in self-reported stimulant use across study visits. Mixed-effects logistic regression was then used to describe associations between selected variables and the same outcome. Models were also stratified based on HIV status to evaluate differences in predictors associated with increased stimulant use. Among 2095 study visits from 467 MSM, increased stimulant use was reported at 20.9% (n = 438) visits. Increased stimulant use was positively associated with unstable housing (adjusted [a]OR 1.81; 95% CI 1.27-2.57), STI diagnosis (1.59; 1.14-2.21), transactional sex (2.30; 1.60-3.30), and last partner stimulant use (2.21; 1.62-3.00). Among MSM living with HIV, increased stimulant use was associated with binge drinking, vaping/cigarette use (aOR 1.99; 95% CI 1.36-2.92), and regular use of poppers (2.28; 1.38-3.76). Among HIV-negative MSM, increased stimulant use was associated with participating in group sex while intoxicated (aOR 1.81; 95% CI 1.04-3.18), transactional sex (2.53; 1.40-2.55), and last partner injection drug use (1.96; 1.02-3.74). Our findings demonstrate that lasso can be a useful tool for variable selection and creation of predictive models. These results indicate that risk behaviors associated with increased stimulant use may differ based on HIV status and suggest that co-substance use and partnership contexts should be considered in the development of HIV prevention/treatment interventions.

Examining the Relative Contributions of Methamphetamine Use, Depression, and Sexual Risk Behavior on Rectal Gonorrhea/Chlamydia Among a Cohort of Men Who Have Sex With Men in Los Angeles, California.

BACKGROUND: Methamphetamine use, sexual risk behaviors, and depression contribute to ongoing human immunodeficiency virus (HIV) and sexually transmitted infection (STI) disparities among men who have sex with men (MSM). The relative contributions of these effects longitudinally are not well understood. METHODS: This analysis used visit-level data from a longitudinal cohort of MSM, half with HIV, in Los Angeles, CA. From August 2014 to March 2020, participants completed follow-up visits every 6 months and underwent testing for rectal gonorrhea/chlamydia (GC/CT) and completed questionnaires including depressive symptoms, number of receptive anal intercourse (RAI) partners, and methamphetamine use. Path analysis with structural equation modeling using concurrent and lagged covariates was used to identify relative contributions of methamphetamine use and depression on number of RAI partners and rectal GC/CT across time. RESULTS: Five hundred fifty-seven MSM with up to 6 visits (3 years) were included for a total of 2437 observations. Methamphetamine use and depressive symptoms were positively associated with number of RAI partners (ß = 0.28, P < 0.001; ß = 0.33, P = 0.018, respectively), which was positively associated with rectal GC/CT (ß = 0.02, P < 0.001). When stratified by HIV status, depressive symptoms were positively associated with RAI partners for HIV-negative MSM (ß = 0.50, P = 0.007) but were not associated for MSM living with HIV (ß = 0.12, P = 0.57). Methamphetamine use was positively associated with RAI partners in both strata. CONCLUSIONS: Factors and patterns, which contribute to risk behaviors associated with rectal GC/CT, may differ by HIV status. Our findings demonstrate the importance of combined treatment and prevention efforts that link screening and treatment of stimulant use and depression with STI prevention and treatment.

Risk Behaviors Associated with Patterns of Sexualized Stimulant and Alcohol Use among Men Who Have Sex with Men: a Latent Class Analysis.

Substance use during sexual encounters (sexualized substance use) is an important driver of HIV and sexually transmitted infection (STI) disparities that are experienced by men who have sex with men (MSM). This analysis aimed to identify patterns of sexualized substance use and their associations with HIV risk behaviors. We utilized visit-level data from a longitudinal cohort of predominantly Black/Latinx MSM, half with HIV and half with substance use in Los Angeles, California. Every 6 months from 8/2014 to 3/2020, participants underwent STI testing and completed surveys on demographics, sexualized substance use (stimulant and/or alcohol intoxication during oral sex, receptive anal intercourse [RAI] and/or insertive anal intercourse [IAI]), transactional sex, biomedical HIV prevention (pre-/post-exposure prophylaxis use or undetectable viral load), and depressive symptoms. Latent class analysis was used to identify patterns of sexualized substance use. Multinomial logit models evaluated risk behaviors associated with latent classes. Among 2386 study visits from 540 participants, 5 classes were identified: no substance use, sexualized stimulant use, sexualized alcohol use, sexualized stimulant and alcohol use, and stimulant/alcohol use during oral sex and RAI. Compared to the no sexualized substance use class, sexualized stimulant use was associated with transactional sex, current diagnosis of STIs, not using HIV biomedical prevention, and depressive symptoms. Sexualized alcohol use had fewer associations with HIV risk behaviors. Patterns of sexual activities, and the substances that are used during those activities, confer different risk behavior profiles for HIV/STI transmission and demonstrate the potential utility of interventions that combine substance use treatment with HIV prevention.

A sequence analysis of hospitalization patterns and service utilization in patients with major psychiatric disorders in China.

BACKGROUND: Understanding the long-term inpatient service cost and utilization of psychiatric patients may provide insight into service demand for these patients and guide the design of targeted mental health programs. This study assesses 3-year hospitalization patterns and quantifies service utilization intensity of psychiatric patients in Beijing, China. METHODS: We identified patients admitted for one of three major psychiatric disorders (schizophrenia, bipolar and depressive disorders) between January 1 and December 31, 2013 in Beijing, China. Inpatient admissions during the following 3 years were extracted and analyzed using sequence analysis. Clinical characteristics, psychiatric and non-psychiatric service use of included patients were analyzed. RESULTS: The study included 3443 patients (7657 hospitalizations). The patient hospitalization sequences were grouped into 4 clusters: short stay (N = 2741 (79.61% of patients), who had 126,911 or 26.82% of the hospital days within the sample), repeated long stay (N = 404 (11.73%), 76,915 (16.26%) days), long-term stay (N = 101 (2.93%), 59,909 (12.66%) days) and permanent stay (N = 197 (5.72%), 209,402 (44.26%) days). Length and frequency of hospitalization, as well as readmission rates were significantly different across the 4 clusters. Over the 3-year period, hospitalization days per year decreased for patients in the short stay and repeated long stay clusters. Patients with schizophrenia (1705 (49.52%)) had 78.4% of cumulative psychiatric stays, with 11.14% of them in the permanent stay cluster. Among patients with depression, 23.11% had non-psychiatric hospitalizations, and on average 46.65% of their total inpatient expenses were for non-psychiatric care, the highest among three diagnostic groups. CONCLUSION: Hospitalization patterns varied significantly among psychiatric patients and across diagnostic categories. The high psychiatric care service use of the long-term and permanent stay patients underlines the need for evidence-based interventions to reduce cost and improve care quality.

How do contraindications to non-opioid analgesics and opioids affect the likelihood that patients with back pain diagnoses in the primary care setting receive an opioid prescription? An observational cross-sectional study.

BACKGROUND: Given the risks of opioids, clinicians are under growing pressure to treat pain with non-opioid medications. Yet non-opioid analgesics such as non-steroidal anti-inflammatory drugs (NSAIDs) have their own risks: patients with kidney disease or gastrointestinal diseases can experience serious adverse events. We examined the likelihood that patients with back pain diagnoses and contraindications to NSAIDs and opioids received an opioid prescription in primary care. METHODS: We identified office visits for back pain from 2012 to 2017 and sampled the first office visit per patient per year (N = 24,543 visits). We created indicators reflecting contraindications for NSAIDs (kidney, liver, cardiovascular/cerebrovascular, and gastrointestinal diseases; concurrent or chronic use of anticoagulants/antiplatelets, chronic corticosteroid use) and opioids (depression, anxiety, substance use (SUD) and bipolar disorders, and concurrent benzodiazepines) and estimated four logistic regression models, with the one model including all patient visits and models 2-4 stratifying for previous opioid use. We estimated the population attributable risk for each contraindication. RESULTS: In our model with all patients-visits, patients received an opioid prescription at 4% of visits. The predicted probability (PP) of receiving an opioid was 4% without kidney disease vs. 7% with kidney disease; marginal effect (ME): 3%; 95%CI: 1-4%). For chronic or concurrent anticoagulant/antiplatelet prescriptions, the PPs were 4% vs. 6% (ME: 2%; 95%CI: 1-3%). For concurrent benzodiazepines, the PPs were 4% vs. 11% (ME: 7%, 95%CI: 5-9%) and for SUD, the PPs were 4% vs. 5% (ME: 1%, 95%CI: 0-3%). For the model including patients with previous long-term opioid use, the PPs for concurrent benzodiazepines were 25% vs. 24% (ME: -1%; 95%CI: - 18-16%). The population attributable risk (PAR) for NSAID and opioid contraindications was small. For kidney disease, the PAR was 0.16% (95%CI: 0.08-0.23%), 0.44% (95%CI: 0.30-0.58%) for anticoagulants and antiplatelets, 0.13% for substance use (95%CI: 0.03-0.22%) and 0.20% for concurrent benzodiazepine use (95%CI: 0.13-0.26%). CONCLUSIONS: Patients with diagnoses of kidney disease and concurrent use of anticoagulants/antiplatelet medications had a higher probability of receiving an opioid prescription at a primary care visit for low back pain, but these conditions do not explain a large proportion of the opioid prescriptions.

How Do Clinicians of Different Specialties Perceive and Use Opioid Risk Mitigation Strategies? A Qualitative Study.

BACKGROUND: In response to the opioid crisis, states and health systems are encouraging clinicians to use risk mitigation strategies aimed at assessing a patient's risk for opioid misuse or abuse: opioid agreements, prescription drug monitoring programs (PDMPs), and urine drug tests (UDT). Objective: The objective of this qualitative study was to understand how clinicians perceived and used risk mitigation strategies for opioid abuse/misuse and identify barriers to implementation. Methods: We interviewed clinicians who prescribe opioid medications in the outpatient setting from 2016-2018 and analyzed the data using Constructivist Grounded Theory methodology. Results: We interviewed 21 primary care clinicians and 12 specialists. Nearly all clinicians reported using the PDMP. Some clinicians (adopters) found the opioid agreement and UDTs to be valuable, but most (non-adopters) did not. Adopters found the agreements and UDTs helpful in treating patients equitably, setting limits, and having objective evidence of misuse; protocols and workflows facilitated the use of the strategies. Non-adopters perceived the strategies as awkward, disruptive to the clinician-patient relationship, and introducing a power differential; they also cited lack of time and resources as barriers to use. Conclusions: Our study demonstrates that clinicians in certain settings have found effective ways to implement and use the PDMP, opioid agreements, and UDT but that other clinicians are less comfortable with their use. Administrators and policymakers should ensure that the strategies are designed in a way that strengthens the clinician-patient relationship while maximizing safety for patients and that clinicians are adequately trained and supported when introducing the strategies.

Comorbidity Assessment Is Uneven Across Veterans Health Administration and Medicare for the Same Patient: Implications for Risk Adjustment.

OBJECTIVE: Compare comorbidity identification in Medicare and Veterans Health Administration (VA) data for the purposes of risk adjustment. DATA SOURCES: Analysis of Medicare and VA datasets for dually-enrolled Veterans receiving care in both settings, fiscal years 2010-2014. STUDY DESIGN: A retrospective analysis of administrative data for a national sample of cancer decedents. DATA EXTRACTION METHODS: Comorbidities were evaluated using Elixhauser and Charlson coding algorithms. PRINCIPAL FINDINGS: Clinical comorbidities were more likely to be recorded in Medicare than in VA datasets. Of 42 comorbidities, 36 (86%) were recorded at a different frequency. For example, congestive heart failure was recorded for 22.0% of patients in Medicare data and for 11.3% of patients in VA data (P<0.001). CONCLUSION: There are large differences in comorbidity assessment across VA and Medicare administrative data for the same patient, posing challenges for risk adjustment.

Adherence to the SEP-1 Sepsis Bundle in Hospital-Onset v. Community-Onset Sepsis: a Multicenter Retrospective Cohort Study.

BACKGROUND: Sepsis is the leading cause of in-hospital death. The SEP-1 sepsis bundle is a protocol for early sepsis care that requires providers to diagnose and treat sepsis quickly. Limited evidence suggests that adherence to the sepsis bundle is lower in cases of hospital-onset sepsis. OBJECTIVE: To compare sepsis bundle adherence in hospital-onset vs. community-onset sepsis. DESIGN: Retrospective cohort study using multivariable analysis of clinical data. PARTICIPANTS: A total of 4658 inpatients age 18 or older were identified by diagnosis codes consistent with sepsis or disseminated infection. SETTING: Four university hospitals in California between 2014 and 2016. MAIN OUTCOMES AND MEASURES: The primary outcome was adherence to key components of the sepsis bundle defined by the Centers for Medicare and Medicaid Services in their core measure, SEP-1. Covariates included clinical characteristics related to the patient, infection, and pathogen. KEY RESULTS: Compared with community-onset, cases of hospital-onset sepsis were less likely to receive SEP-1 adherent care (relative risk 0.33, 95% confidence interval 0.29-0.38, p < 0.001). With the exception of vasopressors (RR 1.11, p = 0.002), each component of SEP-1 evaluated-blood cultures (RR 0.76, p < 0.001), serum lactate (RR 0.51, p < 0001), broad-spectrum antibiotics (RR 0.62, p < 0.001), intravenous fluids (0.47, p < 0.001), and follow-up lactate (RR 0.71, p < 0.001)-was less likely to be performed within the recommended time frame in hospital-onset sepsis. Within the hospital, cases of hospital-onset sepsis arising on the ward were less likely to receive SEP-1-adherent care than were cases arising in the intensive care unit (RR 0.68, p = 0.004). CONCLUSIONS: Inpatients with hospital-onset sepsis receive different management than individuals with community-onset sepsis. It remains to be determined whether system-level factors, provider-level factors, or factors related to measurement explain the observed variation in care or whether variation in care affects outcomes.

Understanding Clinicians' Decisions to Assume Prescriptions for Inherited Patients on Long-term Opioid Therapy: A Qualitative Study.

OBJECTIVE: Given the changing political and social climate around opioids, we examined how clinicians in the outpatient setting made decisions about managing opioid prescriptions for new patients already on long-term opioid therapy. METHODS: We conducted in-depth interviews with 32 clinicians in Southern California who prescribed opioid medications in the outpatient setting for chronic pain. The study design, interview guides, and coding for this qualitative study were guided by constructivist grounded theory methodology. RESULTS: We identified three approaches to assuming a new patient's opioid prescriptions. Staunch Opposers, mostly clinicians with specialized training in pain medicine, were averse to continuing opioid prescriptions for new patients and often screened outpatients seeking opioids. Cautious and Conflicted Prescribers were wary about prescribing opioids but were willing to refill prescriptions if they perceived the patient as trustworthy and the medication fell within their comfort zone. Clinicians in the first two groups felt resentful about other clinicians "dumping" patients on opioids on them. Rapport Builders, mostly primary care physicians, were the most willing to assume opioid prescriptions and were strategic in their approach to transitioning patients to safer doses. CONCLUSIONS: Clinicians with the most training in pain management were the least willing to assume responsibility for opioid prescriptions for patients already on long-term opioid therapy. In contrast, primary care clinicians were the most willing to assume this responsibility. However, primary care clinicians face barriers to providing high-quality care for patients with complex pain conditions, such as short visit times and less specialized training.

Factors associated with 30-day and 1-year readmission among psychiatric inpatients in Beijing China: a retrospective, medical record-based analysis.

BACKGROUND: Psychiatric readmissions negatively impact patients and their families while increasing healthcare costs. This study aimed at investigating factors associated with psychiatric readmissions within 30 days and 1 year of the index admissions and exploring the possibilities of monitoring and improving psychiatric care quality in China. METHODS: Data on index admission, subsequent admission(s), clinical and hospital-related factors were extracted in the inpatient medical record database covering 10 secondary and tertiary psychiatric hospitals in Beijing, China. Logistic regressions were used to examine the associations between 30-day and 1-year readmissions plus frequent readmissions (≥3 times/year), and clinical variables as well as hospital characteristics. RESULTS: The 30-day and 1-year psychiatric readmission rates were 16.69% (1289/7724) and 33.79% (2492/7374) respectively. 746/2492 patients (29.34%) were readmitted 3 times or more within a year (frequent readmissions). Factors significantly associated with the risk of both 30-day and 1-year readmission were residing in an urban area, having medical comorbidities, previous psychiatric admission(s), length of stay > 60 days in the index admission and being treated in tertiary hospitals (p < 0.001). Male patients were more likely to have frequent readmissions (OR 1.30, 95%CI 1.04-1.64). Receiving electroconvulsive therapy (ECT) was significantly associated with a lower risk of 30-day readmission (OR 0.72, 95%CI 0.56-0.91) and frequent readmissions (OR 0.60, 95%CI 0.40-0.91). CONCLUSION: More than 30% of the psychiatric inpatients were readmitted within 1 year. Urban residents, those with medical comorbidities and previous psychiatric admission(s) or a longer length of stay were more likely to be readmitted, and men are more likely to be frequently readmitted. ECT treatment may reduce the likelihood of 30-day readmission and frequent admissions. Targeted interventions should be designed and piloted to effectively monitor and reduce psychiatric readmissions.

Hospitalization Pattern, Inpatient Service Utilization and Quality of Care in Patients With Alcohol Use Disorder: A Sequence Analysis of Discharge Medical Records.

AIMS: To identify and group hospitalization trajectory of alcohol use disorder (AUD) patients and its associations with service utilization, healthcare quality and hospital-level variations. METHODS: Inpatients with AUD as the primary diagnosis from 2012 to 2014 in Beijing, China, were identified. Their discharge medical records were extracted and analyzed using the sequence analysis and the cluster analysis. RESULTS: Eight-hundred thirty-one patients were included, and their hospitalization patterns were grouped into four clusters: short stay (n = 565 (67.99%)), mean psychiatric length of stay in 3 years: (32.25 ± 18.69), repeated short stay (n = 211 (25.39%), 137.76 ± 88.8 days), repeated long stay (n = 41 (4.93%), 405.44 ± 146.54 days), permanent stay (n = 14 (1.68%), 818.14 ± 225.22 days). The latter two clusters (6.61% patients) used 37.26% of the total psychiatric hospital days and 33.65% of the total psychiatric hospitalization expenses. All the patients in the permanent stay cluster and 41.77% of the patients in the short stay cluster were readmitted at least once within 3 years. Two-hundred thirty-four patients (28.16%) were admitted at least once for non-psychiatric reasons, primarily for diseases of circulatory and digestive systems. Cluster composition varied significantly among different hospitals. CONCLUSION: Hospitalization pattern of patients with AUD varies greatly, and while most (>2/3) hospitalizations were short stay, those with repeated long stay and permanent stay used more than one third of the hospital days and expenses. Our findings suggest interventions targeting at certain patients may be more effective in reducing resource utilization.

Primary Care Physicians in the Merit-Based Incentive Payment System (MIPS): a Qualitative Investigation of Participants' Experiences, Self-Reported Practice Changes, and Suggestions for Program Administrators.

BACKGROUND: While both administrators of pay-for-performance programs and practicing physicians strive to improve healthcare quality, they sometimes disagree on the best approach. The Medicare Access and CHIP Reauthorization Act of 2015 mandated the creation of the Merit-Based Incentive Payment System (MIPS), a program that incentivizes more than 700,000 physician participants to report on four domains of care, including healthcare quality. While MIPS performance scores were recently released, little is known about how primary care physicians (PCPs) and their practices are being affected by the program and what actions they are taking in response to MIPS. OBJECTIVES: To (1) describe PCP perspectives and self-reported practice changes related to quality measurement under MIPS and (2) disseminate PCP suggestions for improving the program. DESIGN: Qualitative study employing semi-structured interviews. PARTICIPANTS: Twenty PCPs trained in internal medicine or family medicine who were expected to report under MIPS for calendar year 2017 were interviewed between October 2017 and June 2018. Eight PCPs self-reported to be knowledgeable about MIPS. Seven PCPs worked in small practices. KEY RESULTS: Most PCPs identified advantages of quality measurement under MIPS, including the creation of practice-level systems for quality improvement. However, they also cited disadvantages, including administrative burdens and fears that practices serving vulnerable patients could be penalized. Many participants reported using technology or altering staffing to help with data collection and performance improvement. A few participants were considering selling small practices or joining larger ones to avoid administrative tasks. Suggestions for improving MIPS included simplifying the program to reduce administrative burdens, protecting practices serving vulnerable populations, and improving communication between program administrators and PCPs. CONCLUSIONS: MIPS is succeeding in nudging PCPs to develop quality measurement and improvement systems, but PCPs are concerned that administrative burdens are leading to the diversion of clinical resources away from patient-centered care and negatively impacting patient and clinician satisfaction. Program administrators should improve communication with participants and consider simplifying the program to make it less burdensome. Future work should be done to investigate how technical assistance programs can target PCPs that serve vulnerable patient populations and are having difficulty adapting to MIPS.

Nurse Staffing and Healthcare-Associated Infection, Unit-Level Analysis.

OBJECTIVE: To examine whether healthcare-associated infections (HAIs) and nurse staffing are associated using unit-level staffing data. BACKGROUND: Previous studies of the association between HAIs and nurse staffing are inconsistent and limited by methodological weaknesses. METHODS: Cross-sectional data between 2007 and 2012 from a large urban hospital system were analyzed. HAIs were diagnosed using the Centers for Disease Control and Prevention's National Healthcare Safety Network definitions. We used Cox proportional-hazards regression model to examine the association of nurse staffing (2 days before HAI onset) with HAIs after adjusting for individual risks. RESULTS: Fifteen percent of patient-days had 1 shift understaffed, defined as staffing below 80% of the unit median for a shift, and 6.2% had both day and night shifts understaffed. Patients on units with both shifts understaffed were significantly more likely to develop HAIs 2 days later. CONCLUSIONS: Understaffing is associated with increased risk of HAIs.

Segmentation of High-Cost Adults in an Integrated Healthcare System Based on Empirical Clustering of Acute and Chronic Conditions.

BACKGROUND: High-cost patients are a frequent focus of improvement projects based on primary care and other settings. Efforts to characterize high-cost, high-need patients are needed to inform care planning, but such efforts often rely on a priori assumptions, masking underlying complexities of a heterogenous population. OBJECTIVE: To define recognizable subgroups of patients among high-cost adults based on clinical conditions, and describe their survival and future spending. DESIGN: Retrospective observational cohort study. PARTICIPANTS: Within a large integrated delivery system with 2.7 million adult members, we selected the top 1% of continuously enrolled adults with respect to total healthcare expenditures during 2010. MAIN MEASURES: We used latent class analysis to identify clusters of alike patients based on 53 hierarchical condition categories. Prognosis as measured by healthcare spending and survival was assessed through 2014 for the resulting classes of patients. RESULTS: Among 21,183 high-cost adults, seven clinically distinctive subgroups of patients emerged. Classes included end-stage renal disease (12% of high-cost population), cardiopulmonary conditions (17%), diabetes with multiple comorbidities (8%), acute illness superimposed on chronic conditions (11%), conditions requiring highly specialized care (14%), neurologic and catastrophic conditions (5%), and patients with few comorbidities (the largest class, 33%). Over 4 years of follow-up, 6566 (31%) patients died, and survival in the classes ranged from 43 to 88%. Spending regressed to the mean in all classes except the ESRD and diabetes with multiple comorbidities groups. CONCLUSIONS: Data-driven characterization of high-cost adults yielded clinically intuitive classes that were associated with survival and reflected markedly different healthcare needs. Relatively few high-cost patients remain persistently high cost over 4 years. Our results suggest that high-cost patients, while not a monolithic group, can be segmented into few subgroups. These subgroups may be the focus of future work to understand appropriateness of care and design interventions accordingly.

Building the foundation to generate a fundamental care standardised data set.

AIM AND OBJECTIVES: This paper provides an overview of the current state of performance measurement, key trends and a methodological approach to leverage in efforts to generate a standardised data set for fundamental care. BACKGROUND: Considerable transformation is occurring in health care globally with organisations focusing on achieving the quadruple aim of improving the experience of care, the health of populations, and the experience of providing care while reducing per capita costs of health care. In response, healthcare organisations are employing performance measurement and quality improvement methods to achieve the quadruple aim. Despite the plethora of measures available to health managers, there is no standardised data set and virtually no indicators reflecting how patients actually experience the delivery of fundamental care, such as nutrition, hydration, mobility, respect, education and psychosocial support. CONCLUSIONS: Given the linkages of fundamental care to safety and quality metrics, efforts to build the evidence base and knowledge that captures the impact of enacting fundamental care across the healthcare continuum and lifespan should include generating a routinely collected data set of relevant measures. RELEVANCE TO CLINICAL PRACTICE: This paper provides an overview of the current state of performance measurement, key trends and a methodological approach to leverage in efforts to generate a standardised data set for fundamental care. Standardised data sets enable comparability of data across clinical populations, healthcare sectors, geographic locations and time and provide data about care to support clinical, administrative and health policy decision-making.

Interprofessional training and team function in patient-centred medical home: Findings from a mixed method study of interdisciplinary provider perspectives.

Transitioning from profession-specific to interprofessional (IP) models of care requires major change. The Veterans Assessment and Improvement Laboratory (VAIL), is an initiative based in the United States that supports and evaluates the Veterans Health Administration's (VAs) transition of its primary care practices to an IP team based patient-centred medical home (PCMH) care model. We postulated that modifiable primary care practice organizational climate factors impact PCMH implementation. VAIL administered a survey to 322 IP team members in primary care practices in one VA administrative region during early implementation of the PCMH and interviewed 79 representative team members. We used convergent mixed methods to study modifiable organizational climate factors in relationship to IP team functioning. We found that leadership support and job satisfaction were significantly positively associated with team functioning. We saw no association between team functioning and either role readiness or team training. Qualitative interview data confirmed survey findings and explained why the association with IP team training might be absent. In conclusion, our findings demonstrate the importance of leadership support and individual job satisfaction in producing highly functioning PCMH teams. Based on qualitative findings, we hypothesize interprofessional training is important, however, inconsistencies in IP training delivery compromise its potential benefit. Future implementation efforts should improve standardization of training process and train team members together. Interprofessional leadership coordination of interprofessional training is warranted.

Clinical Effectiveness and Cost of a Hospital-Based Fall Prevention Intervention: The Importance of Time Nurses Spend on the Front Line of Implementation.

OBJECTIVE: The aim of this study is to evaluate the clinical effectiveness and incremental net cost of a fall prevention intervention that involved hourly rounding by RNs at 2 hospitals. BACKGROUND: Minimizing in-hospital falls is a priority, but little is known about the value of fall prevention interventions. METHODS: We used an uncontrolled before-after design to evaluate changes in fall rates and time use by RNs. Using decision-analytical models, we estimated incremental net costs per hospital per year. RESULTS: Falls declined at 1 hospital (incidence rate ratio [IRR], 0.47; 95% confidence interval [CI], 0.26-0.87; P = .016), but not the other (IRR, 0.83; 95% CI, 0.59-1.17; P = .28). Cost analyses projected a 67.9% to 72.2% probability of net savings at both hospitals due to unexpected declines in the time that RNs spent in fall-related activities. CONCLUSIONS: Incorporating fall prevention into hourly rounds might improve value. Time that RNs invest in implementing quality improvement interventions can equate to sizable opportunity costs or savings.

Expanding the Role of Registered Nurses in Primary Care: A Business Case Analysis.

Primary care is evolving in response to payment reform, changes in the primary care workforce, and development of new models of work emphasizing team care. The role of registered nurses in these new models is being reexamined and reimagined, with increased registered nurse engagement in chart review prior to visits, histories and physicals, preliminary patient assessment, patient education and coaching in ordered care, delivery of care under standardized orders and protocols, transition planning, and care coordination. The business case for employing registered nurses in these new roles has not been fully addressed. This article examines the business case and financial issues in this expansion of practice. Under both fee-for-service and value-based, capitated, or shared saving models of reimbursement, there are strategies for increasing the number of registered nurses in primary care practices, and expanding the engagement of registered nurses that can increase net revenues for primary care practices, even when the costs of the additional staffing are taken into account.

Engaging Frontline Staff in Performance Improvement: The American Organization of Nurse Executives Implementation of Transforming Care at the Bedside Collaborative.

BACKGROUND: Process improvement stresses the importance of engaging frontline staff in implementing new processes and methods. Yet questions remain on how to incorporate these activities into the workday of hospital staff or how to create and maintain its commitment. In a 15-month American Organization of Nurse Executives collaborative involving frontline medical/surgical staff from 67 hospitals, Transforming Care at the Bedside (TCAB) was evaluated to assess whether participating units successfully implemented recommended change processes, engaged staff, implemented innovations, and generated support from hospital leadership and staff. METHODS: In a mixed-methods analysis, multiple data sources, including leader surveys, unit staff surveys, administrative data, time study data, and collaborative documents were used. RESULTS: All units reported establishing unit-based teams, of which >90% succeeded in conducting tests of change, with unit staff selecting topics and making decisions on adoption. Fifty-five percent of unit staff reported participating in unit meetings, and 64%, in tests of change. Unit managers reported substantial increase in staff support for the initiative. An average 36 tests of change were conducted per unit, with 46% of tested innovations sustained, and 20% spread to other units. Some 95% of managers and 97% of chief nursing officers believed that the program had made unit staff more likely to initiate change. Among staff, 83% would encourage adoption of the initiative. CONCLUSIONS: Given the strong positive assessment of TCAB, evidence of substantial engagement of staff in the work, and the high volume of innovations tested, implemented, and sustained, TCAB appears to be a productive model for organizing and implementing a program of frontline-led improvement.