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Leaders from national nursing organizations, nursing schools, and health care simulation vendors convened in early 2019 to discuss simulation in nurse practitioner (NP) education. Nurse practitioner clinical education needs a more standardized, efficient, and sustainable model to prepare NPs to provide quality care in complex health care systems. Currently, a major shortage of clinical sites and preceptors to educate students creates challenges for NP programs and nursing faculty. One strategy used by nursing programs to overcome this challenge is using simulation to provide clinical training for NP students in a safe, controlled environment. There remains, however, a lack of evidence linking these simulation experiences with clinical skills acquisition and program outcomes. Implementing competency-based education through standardized simulations has the potential to demonstrate quality, safety, and accountability across NP education programs. Ultimately, the expansion and acceptance of simulation hours in NP education is dependent on strong and favorable evidence from rigorous, high-quality studies.

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A core project team was able to identify essential implementation components for a successful dual-care program aimed at improving communication and collaboration with non-VA health care providers.

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Women Veterans enrolled in Veterans Affairs (VA) health care almost always use non-VA hospitals for childbirth, making it more likely they will use non-VA hospitals for other needs, as well. We compared VA and non-VA hospitalizations obtained by VA enrollees in seven states from 2004 through 2007 to determine whether women aged 18 to 44 were more likely to use VA or non-VA care for diagnoses in certain major categories, and how this use differed between women who did or did not have any pregnancy/childbirth admissions during the 4 years. We found that women were hospitalized much more in non-VA than in VA hospitals, though they were relatively more likely to use VA hospitals for mental illness, digestive system diseases, and neoplasms than other diagnoses. Women who gave birth during the time interval had very few VA admissions for any diagnosis, and compared to other women they were also less likely to be hospitalized for mental health or cancer, but more likely to be hospitalized for infectious and parasitic diseases. VA hospitals were used more by women who were slightly older, sicker, poorer, and living nearer to them. VA-using women tend to have different and greater medical needs than those having children.

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OBJECTIVE: To assess use and quality of care at a new 1-day-per-week Veterans Administration Outreach Clinic in remote northern Maine. METHODS: Veterans Administration electronic medical records were abstracted to compare outreach clinic patients seen in its first year to patients seen at the nearest outpatient treatment sites, a small-staff, full-time VA clinic 81 miles away and a community-based outpatient clinic 55 miles away. Chart abstractions (N = 1251) yielded counts of visits, patients newly enrolled in VA care, patients transferring to the outreach clinic, and patients who had and maintained a local non-VA primary care physician, as well as multiple quality of care performance measures using standard VA criteria. RESULTS: The outreach clinic enrolled very few patients new to VA; 96% of its patients were transfers from other sites. For transfers, the average one-way driving burden to reach primary care was reduced by 52.9 miles and 58.1 minutes to reach. Compared to community-based outpatient clinic patients, outreach clinic patients were more likely to have three or more provider visits during the year. Some quality of care measures were lower at the outreach clinic: obesity screenings, referrals to smoking cessation services, diabetes management, and hypertension control. At all three sites, most patients had health insurance coverage and kept a local, non-VA doctor throughout the year. CONCLUSIONS: A part-time outreach clinic improved the convenience of primary care for rural VA outpatients, though quality of care was reduced for some measures related to equipment and staffing limitations. Most patients at any VA site had a local, non-VA medical doctor with whom they remained in care while using VA services.

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This multimethod pilot study examined patient and practitioner perspectives on the influence of spatial barriers to healthcare access and the role of health information technology in overcoming these barriers. The study included a survey administered to patients attending a Department of Veterans Affairs (VA) health visit, and a focus group with VA care providers. Descriptive results and focus group findings are presented. Spatial distance is a significant factor for many rural veterans when seeking healthcare. For this sample of rural veterans, a range of telephone, computer, and Internet technologies may become more important for accessing care as Internet access becomes more ubiquitous and as younger veterans begin using the VA health system. The focus group highlighted the negative impact of distance, economic considerations, geographic barriers, and specific medical conditions on access to care. Lack of adequate technology infrastructure was seen as an obstacle to utilization. This study discusses the need to consider distance, travel modes, age, and information technology infrastructure and adoption when designing health information technology to care for rural patients.

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BACKGROUND: Brief motivational interventions that have been provided in addition to routine primary care have changed adolescent health behaviors. Whether health screening and motivational-interviewing-based counseling provided by clinicians during routine care can change behaviors is unknown. METHODS: Healthy Teens was a primary care, office-system intervention to support efficient, patient-centered counseling at well visits. Healthy Teens utilized a personal digital assistant (PDA)-based screener that provided the clinician with information about a teen's health risks and motivation to change. Changes in adolescent self-report of diet and activity health behaviors 6 months later were assessed in two cross-sectional samples of teens from five rural practices in 2005 and 2006. Usual-care subjects (N=148) were recruited at well visits prior to the intervention, and the Healthy Teens subjects (N=136) were recruited at well visits after the Healthy Teens system was well established. RESULTS: At 6-month follow-up, the Healthy Teens group had significantly increased self-reported exercise levels and milk-product intake. In the models exploring covariates, the only significant predictors for improvement in exercise levels were intervention-group status (p=0.009) and post-visit interest in making a change (p=0.015). Interest in changing predicted increased milk intake (p=0.028) in both groups. When teens planned an action related to nutrition, physical activity, or both after a well visit, Healthy Teens participants were more likely to report multiple planned actions (68% Healthy Teens vs 32% usual care, p<0.05). CONCLUSIONS: Changes in office systems using low-cost technology to screen adolescents and promote patient-centered counseling appear to influence teens to increase exercise and milk intake.

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Identifying active regions of the brain that are task-related is important in fMRI study. Current methods of determining functional Regions of Interest (ROIs) are unsatisfactory because they either reduce the effect size or bias the statistical results. We propose a spectral clustering method for assessing those voxels within an ROI that are suitable for further task-activation analysis. Different similarity functions are studied and the correlation index is chosen based on the simulation study. In real fMRI study, further group analysis employing regression is investigated to identify different brain activation patterns between groups in order to reveal the effects of disease and medicine. A real fMRI case study in Parkinson's disease suggests that the technique is promising, warranting further study.

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BACKGROUND: Re-Engineering Systems for Primary Care Treatment of Depression (RESPECT-D) sought to improve patient outcomes by disseminating the 3-component model of depression management. The purpose of this study was to determine whether an integrated model of depression management continued to be used by primary care clinicians after the end of a randomized controlled trial (RCT). METHODS: A descriptive evaluation was conducted at 2 time points. First, during a 12-month period after the end of the RESPECT-D RCT when referrals to care management were determined for each of the 5 participating health care organizations. Second, 3 years after the RCT ended, when clinicians were surveyed about use of the 3-component model. RESULTS: Three organizations continued to support the model with minimal modification. One made a major modification to it and one did not continue to support it. In the 12 months after the RCT, 1039 care management referrals were made. Seventy-one percent of RCT clinicians (n=92) completed the follow-up survey. Of these, 87% reported using the Patient Health Questionnaire-9; 58.9% reported availability of care management and 45.1% reported availability of informal psychiatry consultation. CONCLUSION: Practical clinical interventions can be sustained in primary care practice after the completion of an RCT. Additional resources may be needed to sustain and spread the program.

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BACKGROUND: Two instruments commonly used in primary care research to measure depressive severity are the Patient Health Questionnaire-9 (PHQ-9) and the Hopkins Symptom Checklist-20 (HSCL-20). However, there is little information regarding the relationship between clinical information derived from these scales. The present study investigates the psychometric properties of the PHQ-9 and HSCL-20, determines the degree of instrument concordance, and describes the factor structure of the HSCL-20. METHODS: A secondary data analysis from a randomized controlled trial was performed. A total of 405 primary care patients with major depressive disorder and/or dysthymia were administered the PHQ-9 and the HSCL-20 when recruited for the study. RESULTS: Good internal consistency reliability estimates were obtained for both scales (PHQ-9 alpha=0.803; HSCL-20 alpha=0.837). All PHQ-9 inter-item and corrected item-total correlations showed that no item detracted from overall scale functioning. HSCL-20 items assessing overeating, poor appetite, and sexual interest were poorly correlated with other items and with the total scale score. A positive, moderate strength relationship was found between the instruments (r=0.54, p<0.0001). Exploratory factor analysis of the HSCL-20 yielded a six-factor structure, which accounted for almost 63% of the variance in total score. The largest contribution to common variance in the scale was provided by an "anxiety and self-reproach" factor. CONCLUSIONS: PHQ-9 and HSCL-20 total scores were moderately correlated. Although the HSCL-20 is utilized as a measure of depression severity, it may lack sufficient specificity to be an accurate reflection of depression status per se.

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PURPOSE: We investigated the prevalence, severity, and course of passive and active suicidal ideation occurring in primary care patients with an uncomplicated depressive disorder. METHODS: We studied suicidal ideation experienced by patients recruited in 60 primary care practices participating in a randomized controlled trial of depression management. Risk levels associated with suicidal ideation and plans were determined by a 2-stage procedure using pertinent items of the Patient Health Questionnaire-9, the Hopkins Symptom Checklist-20, and the Cornell structured assessment interview and management algorithm. RESULTS: Of the 761 patients whom physicians judged in need of treatment for a clinical depression, 405 (53%) were experiencing uncomplicated dysthymia, major depression, or both. Among these depressed patients, about 90% had no risk or a low risk of self-harm based on the presence and nature of suicidal ideation; the rest had an intermediate risk. Almost all patients who were initially classified at the no or low risk levels remained at these levels during the subsequent 6 months. The incidence of suicidal ideation at a risk level requiring the physician's immediate attention in this no- or low-risk subgroup was 1.1% at 3 months and 2.6% at 6 months. CONCLUSIONS: Almost all patients with uncomplicated dysthymia, major depression, or both acknowledging suicidal ideation of the minimal risk type when initially assessed maintained this minimal risk status during the subsequent 6 months.

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Suicide is a critical public health problem that primary care physicians potentially can help address given that distressed patients frequently visit them in the weeks and months preceding the successful suicide. This article considers factors placing the patient at high risk for successful suicide and clinical assessment techniques available to the primary care physician. Patients who wish to harm themselves but still lack an articulated plan for doing so can be treated by the primary care physician with the monitoring assistance of a depression care manager and appropriate consultation by a mental health specialist.

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OBJECTIVE: To test the effectiveness of an evidence based model for management of depression in primary care with support from quality improvement resources. DESIGN: Cluster randomised controlled trial. SETTING: Five healthcare organisations in the United States and 60 affiliated practices. PATIENTS: 405 patients, aged > or = 18 years, starting or changing treatment for depression. INTERVENTION: Care provided by clinicians, with staff providing telephone support under supervision from a psychiatrist. MAIN OUTCOME MEASURES: Severity of depression at three and six months (Hopkins symptom checklist-20): response to treatment (> or = 50% decrease in scores) and remission (score of < 0.5). RESULTS: At six months, 60% (106 of 177) of patients in intervention practices had responded to treatment compared with 47% (68 of 146) of patients in usual care practices (P = 0.02). At six months, 37% of intervention patients showed remission compared with 27% for usual care patients (P = 0.014). 90% of intervention patients rated their depression care as good or excellent at six months compared with 75% of usual care patients (P = 0.0003). CONCLUSION: Resources such as quality improvement programmes can be used effectively in primary care to implement evidence based management of depression and improve outcomes for patients with depression.

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