Characteristics of primary care office visits to nurse practitioners, physician assistants and physicians in United States Veterans Health Administration facilities, 2005 to 2010: a retrospective cross-sectional analysis.

UNLABELLED: BACKGROUND: Primary care, an essential determinant of health system equity, efficiency, and effectiveness, is threatened by inadequate supply and distribution of the provider workforce. The Veterans Health Administration (VHA) has been a frontrunner in the use of nurse practitioners (NPs) and physician assistants (PAs). Evaluation of the roles and impact of NPs and PAs in the VHA is critical to ensuring optimal care for veterans and may inform best practices for use of PAs and NPs in other settings around the world. The purpose of this study was to characterize the use of NPs and PAs in VHA primary care and to examine whether their patients and patient care activities were, on average, less medically complex than those of physicians. METHODS: This is a retrospective cross-sectional analysis of administrative data from VHA primary care encounters between 2005 and 2010. Patient and patient encounter characteristics were compared across provider types (PA, NP, and physician). RESULTS: NPs and PAs attend about 30% of all VHA primary care encounters. NPs, PAs, and physicians fill similar roles in VHA primary care, but patients of PAs and NPs are slightly less complex than those of physicians, and PAs attend a higher proportion of visits for the purpose of determining eligibility for benefits. CONCLUSIONS: This study demonstrates that a highly successful nationwide primary care system relies on NPs and PAs to provide over one quarter of primary care visits, and that these visits are similar to those of physicians with regard to patient and encounter characteristics. These findings can inform health workforce solutions to physician shortages in the USA and around the world. Future research should compare the quality and costs associated with various combinations of providers and allocations of patient care work, and should elucidate the approaches that maximize quality and efficiency.

Caring for Alaska Native prostate cancer survivors in primary care: a survey of Alaska Tribal Health System providers.

BACKGROUND: Little is known about the constraints of optimizing health care for prostate cancer survivors in Alaska primary care. OBJECTIVE: To describe the experiences and attitudes of primary care providers within the Alaska Tribal Health System (ATHS) regarding the care of prostate cancer survivors. DESIGN: In late October 2011, we emailed a 22-item electronic survey to 268 ATHS primary care providers regarding the frequency of Prostate Specific Antigen (PSA) monitoring for a hypothetical prostate cancer survivor; who should be responsible for the patient's life-long prostate cancer surveillance; who should support the patient's emotional and medical needs as a survivor; and providers' level of comfort addressing recurrence monitoring, erectile dysfunction, urinary incontinence, androgen deprivation therapy, and emotional needs. We used simple logistic regression to examine the association between provider characteristics and their responses to the survivorship survey items. RESULTS: Of 221 individuals who were successfully contacted, a total of 114 responded (52% response rate). Most ATHS providers indicated they would order a PSA test every 12 months (69%) and believed that, ideally, the hypothetical patient's primary care provider should be responsible for his life-long prostate cancer surveillance (60%). Most providers reported feeling either "moderately" or "very" comfortable addressing topics such as prostate cancer recurrence (59%), erectile dysfunction (64%), urinary incontinence (63%), and emotional needs (61%) with prostate cancer survivors. These results varied somewhat by provider characteristics including female sex, years in practice, and the number of prostate cancer survivors seen in their practice. CONCLUSIONS: These data suggest that most primary care providers in Alaska are poised to assume the care of prostate cancer survivors locally. However, we also found that large minorities of providers do not feel confident in their ability to manage common issues in prostate cancer survivorship, implying that continued access to specialists with more expert knowledge would be beneficial.

Specialist and primary care physicians' views on barriers to adequate preparation of patients for renal replacement therapy: a qualitative study.

BACKGROUND: Early preparation for renal replacement therapy (RRT) is recommended for patients with advanced chronic kidney disease (CKD), yet many patients initiate RRT urgently and/or are inadequately prepared. METHODS: We conducted audio-recorded, qualitative, directed telephone interviews of nephrology health care providers (n = 10, nephrologists, physician assistants, and nurses) and primary care physicians (PCPs, n = 4) to identify modifiable challenges to optimal RRT preparation to inform future interventions. We recruited providers from public safety-net hospital-based and community-based nephrology and primary care practices. We asked providers open-ended questions to assess their perceived challenges and their views on the role of PCPs and nephrologist-PCP collaboration in patients' RRT preparation. Two independent and trained abstractors coded transcribed audio-recorded interviews and identified major themes. RESULTS: Nephrology providers identified several factors contributing to patients' suboptimal RRT preparation, including health system resources (e.g., limited time for preparation, referral process delays, and poorly integrated nephrology and primary care), provider skills (e.g., their difficulty explaining CKD to patients), and patient attitudes and cultural differences (e.g., their poor understanding and acceptance of their CKD and its treatment options, their low perceived urgency for RRT preparation; their negative perceptions about RRT, lack of trust, or language differences). PCPs desired more involvement in preparation to ensure RRT transitions could be as "smooth as possible", including providing patients with emotional support, helping patients weigh RRT options, and affirming nephrologist recommendations. Both nephrology providers and PCPs desired improved collaboration, including better information exchange and delineation of roles during the RRT preparation process. CONCLUSIONS: Nephrology and primary care providers identified health system resources, provider skills, and patient attitudes and cultural differences as challenges to patients' optimal RRT preparation. Interventions to improve these factors may improve patients' preparation and initiation of optimal RRTs.

Teaching neuraxial anesthesia techniques for obstetric care in a Ghanaian referral hospital: achievements and obstacles.

Anesthesia providers in low-income countries may infrequently provide regional anesthesia techniques for obstetrics due to insufficient training and supplies, limited manpower, and a lack of perceived need. In 2007, Kybele, Inc. began a 5-year collaboration in Ghana to improve obstetric anesthesia services. A program was designed to teach spinal anesthesia for cesarean delivery and spinal labor analgesia at Ridge Regional Hospital, Accra, the second largest obstetric unit in Ghana. The use of spinal anesthesia for cesarean delivery increased significantly from 6% in 2006 to 89% in 2009. By 2012, >90% of cesarean deliveries were conducted with spinal anesthesia, despite a doubling of the number performed. A trial of spinal labor analgesia was assessed in a small cohort of parturients with minimal complications; however, protocol deviations were observed. Although subsequent efforts to provide spinal analgesia in the labor ward were hampered by anesthesia provider shortages, spinal anesthesia for cesarean delivery proved to be practical and sustainable.

Bioburden after Staphylococcus aureus inoculation in type 1 diabetic rats undergoing internal fixation.

SUMMARY: Fracture stabilization in the diabetic patient is associated with higher complication rates, particularly infection and impaired wound healing, which can lead to major tissue damage, osteomyelitis, and higher amputation rates. With an increasing prevalence of diabetes and an aging population, the risks of infection of internal fixation devices are expected to grow. Although numerous retrospective clinical studies have identified a relationship between diabetes and infection, currently there are few animal models that have been used to investigate postoperative surgical-site infections associated with internal fixator implantation and diabetes. The authors therefore refined the protocol for inducing hyperglycemia and compared the bacterial burden in controls to pharmacologically induced type 1 diabetic rats after undergoing internal fracture plate fixation and Staphylococcus aureus surgical-site inoculation. Using an initial series of streptozotocin doses, followed by optional additional doses to reach a target blood glucose range of 300 to 600 mg/dl, the authors reliably induced diabetes in 100 percent of the rats (n = 16), in which a narrow hyperglycemic range was maintained 14 days after onset of diabetes (mean ± SEM, 466 ± 16 mg/dl; coefficient of variation, 0.15). With respect to their primary endpoint, the authors quantified a significantly higher infectious burden in inoculated diabetic animals (median, 3.2 × 10 colony-forming units/mg dry tissue) compared with inoculated nondiabetic animals (7.2 × 10 colony-forming units/mg dry tissue). These data support the authors' hypothesis that uncontrolled diabetes adversely affects the immune system's ability to clear Staphylococcus aureus associated with internal hardware.

Micro-Anatomical Quantitative Imaging Towards Enabling Automated Diagnosis of Thick Tissues at the Point of Care

Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.

Understanding the Context for Long-Term Care Planning.

Evolving family structure and economic conditions may affect individuals' ability and willingness to plan for future long-term care (LTC) needs. We applied life course constructs to analyze focus group data from a study of family decision making about LTC insurance. Participants described how past exposure to caregiving motivated them to engage in LTC planning; in contrast, child rearing discouraged LTC planning. Perceived institutional and economic instability drove individuals to regard financial LTC planning as either a wise precaution or another risk. Perceived economic instability also shaped opinions that adult children are ill-equipped to support parents' LTC. Despite concerns about viability of social insurance programs, some participants described strategies to maximize gains from them. Changing norms around aging and family roles also affected expectations of an active older age, innovative LTC options, and limitations to adult children's involvement. Understanding life course context can inform policy efforts to encourage LTC planning.

Thinking Outside the Box: Treating Acute Heart Failure Outside the Hospital to Improve Care and Reduce Admissions.

The management of acute heart failure is shifting toward treatment approaches outside of a traditional hospital setting. Many heart failure providers are now treating patients in less familiar health care settings, such as acute care clinics, emergency departments, and skilled nursing facilities. In this review we describe the current pressures driving change in the delivery of acute heart failure and summarize the evidence regarding treatments for acute heart failure outside of the inpatient setting. We also provide considerations for the design of future treatment strategies to be implemented in alternative care settings.