Nurse Practitioner Care, Scope of Practice, and End-of-Life Outcomes for Nursing Home Residents With Dementia.

Importance: Nursing home residents with Alzheimer disease and related dementias (ADRD) often receive burdensome care at the end of life. Nurse practitioners (NPs) provide an increasing share of primary care in nursing homes, but how NP care is associated with end-of-life outcomes for this population is unknown. Objectives: To examine the association of NP care with end-of-life outcomes for nursing home residents with ADRD and assess whether these associations differ according to state-level NP scope of practice regulations. Design, Setting, and Participants: This cohort study using fee-for-service Medicare claims included 334 618 US nursing home residents with ADRD who died between January 1, 2016, and December 31, 2018. Data were analyzed from April 6, 2015, to December 31, 2018. Exposures: Share of nursing home primary care visits by NPs, classified as minimal (<10% of visits), moderate (10%-50% of visits), and extensive (>50% of visits). State NP scope of practice regulations were classified as full vs restrictive in 2 domains: practice authority (authorization to practice and prescribe independently) and do-not-resuscitate (DNR) authority (authorization to sign DNR orders). Main Outcomes and Measures: Hospitalization within the last 30 days of life and death with hospice. Linear probability models with hospital referral region fixed effects controlling for resident characteristics, visit volume, and geographic factors were used to estimate whether the associations between NP care and outcomes varied across states with different scope of practice regulations. Results: Among 334 618 nursing home decedents (mean [SD] age at death, 86.6 [8.2] years; 69.3% female), 40.5% received minimal NP care, 21.4% received moderate NP care, and 38.0% received extensive NP care. Adjusted hospitalization rates were lower for residents with extensive NP care (31.6% [95% CI, 31.4%-31.9%]) vs minimal NP care (32.3% [95% CI, 32.1%-32.6%]), whereas adjusted hospice rates were higher for residents with extensive (55.6% [95% CI, 55.3%-55.9%]) vs minimal (53.6% [95% CI, 53.3%-53.8%]) NP care. However, there was significant variation by state scope of practice. For example, in full practice authority states, adjusted hospice rates were 2.88 percentage points higher (95% CI, 1.99-3.77; P < .001) for residents with extensive vs minimal NP care, but the difference between these same groups was 1.77 percentage points (95% CI, 1.32-2.23; P < .001) in restricted practice states. Hospitalization rates were 1.76 percentage points lower (95% CI, -2.52 to -1.00; P < .001) for decedents with extensive vs minimal NP care in full practice authority states, but the difference between these same groups in restricted practice states was only 0.43 percentage points (95% CI, -0.84 to -0.01; P < .04). Similar patterns were observed in analyses focused on DNR authority. Conclusions and Relevance: The findings of this cohort study suggest that NPs appear to be important care providers during the end-of-life period for many nursing home residents with ADRD and that regulations governing NP scope of practice may have implications for end-of-life hospitalizations and hospice use in this population.

Feasibility of an image planning system for kilovoltage image-guided radiation therapy.

PURPOSE: Image guidance has become a standard of care for many treatment scenarios in radiation therapy. This is most typically accomplished by use of kV x-ray devices mounted onto the linear accelerator (Linac) gantry that yield planar, fluoroscopic, and cone-beam computed tomography (CBCT) images. Image acquisition parameters are chosen via preset techniques that rely on broad categorizations in patient anatomy and imaging goal. However, the optimal imaging technique results in detectability of the features of interest while exposing the patient to minimum dose. Herein, the authors present an investigation into the feasibility of developing an image planning system (IPS) for radiotherapy. METHODS: In this first phase, the authors focused on developing an algorithm to predict tissue contrast produced by a common radiotherapy planar imaging chain. Input parameters include a CT dataset and simulated planar imaging technique settings that include kV and mAs. Energy-specific attenuation through each voxel of the CT dataset was calculated in the algorithm to derive a net transmitted intensity. The response of the flat panel detector was integrated into the image simulation algorithm. Verification was conducted by comparing simulated and measured images using four phantoms. Comparisons were made in both high and low contrast settings, as well as changes in the geometric appearance due to image saturation. RESULTS: The authors studied a lung nodule test object to assess the planning system's ability to predict object contrast and detectability. Verification demonstrated that the slope of the pixel intensities is similar, the presence of the nodule is evident, and image saturation at high mAs values is evident in both images. The appearance of the lung nodule is a function of the image detector saturation. The authors assessed the dimensions of the lung nodule in measured and simulated images. Good quantitative agreement affirmed the algorithm's predictive capabilities. The invariance of contrast with kVp and mAs prior to saturation was predicted, as well as the gradual loss of object detectability as saturation was approached. Small changes in soft tissue density were studied using a mammography step wedge phantom. Data were acquired at beam qualities of 80 and 120 kVp and over exposure values ranging from 0.04 to 500 mAs. The data showed good agreement in terms of the absolute value of pixel intensities predicted, as well as small variations across the step wedge pattern. The saturation pixel intensity was consistent between the two beam qualities studied. Boney tissue contrast was assessed using two abdominal phantoms. Measured and calculated values agree in terms of predicting the mAs value at which detector saturation, and subsequent loss of contrast occurs. The lack of variation in contrast over mAs values lower than 10 suggests that there is wide latitude for minimizing patient dose. CONCLUSIONS: The authors developed and tested an algorithm that can be used to assist in kV imaging technique selection during localization for radiotherapy. Phantom testing demonstrated the algorithm's predictive accuracy for both low and high contrast imaging scenarios. Detector saturation with subsequent loss of imaging detail, both in terms of object size and contrast were accurately predicted by the algorithm.