Health IT Security: An Examination of Modern Challenges in Maintaining HIPAA and HITECH Compliance

This work describes an undergraduate honors research project into some of the challenges modern healthcare providers face in maintaining compliance with the Health Insurance Portability and Accountability Act (HIPAA) and HITECH (Health Information Technology for Economic and Clinical Health) Act. An overview of the pertinent sections of both the HIPAA and HITECH Acts regarding health information security is provided, along with a discussion of traditionally weak points in information security, including: people susceptible to social engineering, software that is not or cannot be regularly updated, and targeted attacks (including advanced persistent threats, or APTs). Further, the paper examines potential violations of HIPAA involving vulnerabilities in commonly-used enterprise health records systems. Finally, we compare these challenges to the challenges of the United States healthcare system prior to 1995, specifically looking at information handling procedures, how procedures have changed, and how effective those changes have been

Dynamic range and mass accuracy of wide-scan direct infusion nanoelectrospray fourier transform ion cyclotron resonance mass spectrometry-based metabolomics increased by the spectral stitching method

Direct infusion nanoelectrospray Fourier transform ion cyclotron resonance mass spectrometry (DI nESI FT-ICR MS)offers high mass accuracy and resolution for analyzing complex metabolite mixtures. High dynamic range across a wide mass range, however, can only be achieved at the expense of mass accuracy, since the large numbers of ions entering the ICR detector induce adverse spacecharge effects. Here we report an optimized strategy for wide-scan DI nESI FT-ICR MS that increases dynamic range but maintains high mass accuracy. It comprises the collection if multiple adjacent selected ion monitoring (SIM) windows that are stitched together using novel algorithms. The final SIM-stitching method, derived from several optimization experiments, comprises 21 adjoining SIM windows each of width m/z 30 (from m/z 70 to 500; adjacent windows overlap by m/z 10) with an automated gain control (AGC) target of 1 105 charges. SIMstitching and wide-scan range (WSR; Thermo Electron)were compared using a defined standard to assess mass accuracy and a liver extract to assess peak count and dynamic range. SIM-stitching decreased the maximum mass error by 1.3- and 4.3-fold, and increased the peak count by 5.3- and 1.8-fold, versus WSR (AGC targets of 1 x 105 and 5 x 105, respectively). SIM-stitching achieved an rms mass error of 0.18 ppm and detected over 3000 peaks in liver extract. This novel approach increases metabolome coverage, has very high mass accuracy, and at 5.5 min/sample is conducive for high- throughput metabolomics

Short-Term Effects of Thin-Layer Sand Placement on Salt Marsh Grasses: A Marsh Organ Field Experiment

Salt marshes can build in elevation with sea-level rise through accumulation of inorganic sediment and organic matter, but marshes worldwide are under threat of drowning due to rapid rates of sea-level rise that outpace natural marsh building rates. The application of a thin layer of sediment to the marsh surface (thin-layer placement [TLP]) is a tool to build elevation and decrease flooding stress, but its effects on marsh plants are understudied, especially in New England. In a novel application of a marsh organ experiment (i.e. rows of pots at different elevations), the addition of 10 cm of sand to pots planted with Spartina alterniflora and Spartina patens resulted in fewer stems than controls for S. patens but not S. alterniflora after 2 months. However, total biomass and root mass were not significantly impacted for either species, suggesting plants will fully recover from TLP over longer timescales. Effects of TLP on biomass and stem density did not vary significantly by elevation. Although long-term research is still needed, short-term equivalency in biomass between TLP treatments and controls suggests TLP of 10 cm is a promising strategy to enhance the ability of marshes to build vertically as sea level rises in New England

Effects of a large-scale, natural sediment deposition event on plant cover in a Massachusetts salt marsh

In mid-winter 2018, an unprecedented sediment deposition event occurred throughout portions of the Great Marsh in Massachusetts. Evaluation of this event in distinct marsh areas spanning three towns (Essex, Ipswich, and Newbury) revealed deposition covering 29.2 hectares with an average thickness of 30.1±2.1 mm measured shortly after deposition. While sediment deposition helps marshes survive sea level rise by building elevation, effects of such a large-scale deposition on New England marshes are unknown. This natural event provided an opportunity to study effects of large-scale sediment addition on plant cover and soil chemistry, with implications for marsh resilience. Sediment thickness did not differ significantly between winter and summer, indicating sediment is not eroding or compacting. The deposited sediment at each site had similar characteristics to that of the adjacent mudflat (e.g., texture, bivalve shells), suggesting that deposited materials resulted from ice rafting from adjacent flats, a natural phenomenon noted by other authors. Vegetative cover was significantly lower in plots with rafted sediment (75.6±2.3%) than sediment-free controls (93.1±1.6%) after one growing season. When sorted by sediment thickness categories, the low thickness level (1–19 mm) had significantly greater percent cover than medium (20–39 mm) and high (40–90 mm) categories. Given that sediment accretion in the Great Marsh was found to average 2.7 mm per year, the sediment thickness documented herein represents ~11 years of sediment accretion with only a 25% reduction in plant cover, suggesting this natural sediment event will likely increase long-term marsh resilience to sea level rise

Many bioinformatics programming tasks can be automated with ChatGPT

Computer programming is a fundamental tool for life scientists, allowing them to carry out many essential research tasks. However, despite a variety of educational efforts, learning to write code can be a challenging endeavor for both researchers and students in life science disciplines. Recent advances in artificial intelligence have made it possible to translate human-language prompts to functional code, raising questions about whether these technologies can aid (or replace) life scientists' efforts to write code. Using 184 programming exercises from an introductory-bioinformatics course, we evaluated the extent to which one such model -- OpenAI's ChatGPT -- can successfully complete basic- to moderate-level programming tasks. On its first attempt, ChatGPT solved 139 (75.5%) of the exercises. For the remaining exercises, we provided natural-language feedback to the model, prompting it to try different approaches. Within 7 or fewer attempts, ChatGPT solved 179 (97.3%) of the exercises. These findings have important implications for life-sciences research and education. For many programming tasks, researchers no longer need to write code from scratch. Instead, machine-learning models may produce usable solutions. Instructors may need to adapt their pedagogical approaches and assessment techniques to account for these new capabilities that are available to the general public.Comment: 13 pages, 4 figures, to be submitted for publicatio

Successional dynamics of a 35 year old freshwater mitigation wetland in southeastern New Hampshire

The long-term ecological success of compensatory freshwater wetland projects has come into question based on follow-up monitoring studies over the past few decades. Given that wetland restoration may require many years to decades to converge to desired outcomes, long-term monitoring of successional patterns may increase our ability to fully evaluate success of wetland mitigation projects or guide adaptive management when needed. In Portsmouth, New Hampshire a 4 ha wetland was constructed in an abandoned gravel quarry as off-site compensatory mitigation for impacts to a scrub-shrub swamp associated with property expansion. Building upon prior evaluations from 1992 and 2002, we conducted a floral survey in 2020 to compare results with prior surveys to document vegetation successional trends over time. In addition, we monitored the avian community throughout the growing season as a measure of habitat quality. The plant community mirrored documented successional trends of freshwater wetland restoration projects as native hydrophytes dominated species composition. Plant species composition stabilized as the rate of turnover, the measurement of succession, declined by nearly half after 17 years. Researchers should consider long-term monitoring of specific sites to better understand successional patterns of created wetlands as we documented long time frames required for the development of scrub-shrub swamps, red maple swamps, and sedge meadows. High species richness was attributed to beaver activity, topographic heterogeneity from Carex stricta tussocks, and the seed bank from the application of peat from the original wetland. Habitat heterogeneity of open water, herbaceous cover, and woody vegetation supports a diverse avian community including 11 wetland dependent species. Although the mitigation project has not created the full area of lost scrub-shrub swamp after 35 years, it has developed a structurally complex habitat and diverse avian community that effectively provides the functions and values of the impacted system

Investigations of Hail Damage Swaths Using Various Satellite Remote Sensing Platforms

Severe thunderstorms that bring damaging winds and large hail can cause significant damage to agricultural crops. Severe thunderstorms can cause upwards of several hundreds of millions of dollars in damage to agricultural areas. Formal ground surveys are not conducted on these areas of damage, like they are for suspected tornado damaged areas. IF ground surveys were conducted, they would likely be time and resources consuming due to their large spatial extent. Satellite remote sensing has been frequently used in identification and analysis of these hail damage swaths. Previous analysis have looked at the simple change in damaged vegetation to looking at the damage areas in satellite imagery with varying spatial resolutions. One study has even looked at the impacts that these damage swaths can have on the land surface, associated fluxes and how they affect numerical weather prediction. Previous studies have focused on using optical remote (VIS, NIR, SWIR) sensing instruments and derived indices, such as Normalized Difference Vegetation Index (NDVI) for analysis. NDVI is used to monitor the health (greenness) of the vegetation. Optical sensors however are limited by sky conditions over the areas they are imaging and certain bands are further limited by the diurnal cycle. These limitations can lead to sometimes upwards of 7 to 10 day gaps of the surface not being imaged, especially during the height of summer convection. One way to obtain more views of the surface, regardless of the sky conditions or time of day is through the use of synthetic aperture radar (SAR). SAR sensors are active instruments that transmit in the microwave portion of the EM spectrum. The surface and its characteristics will determine the amount of energy scattered back to the sensor. The SAR sensors then measure amplitude and phase of wavelength coming back from surface

OpenSep: A generalizable open source pipeline for SOFA score calculation and Sepsis-3 classification

EHR-based sepsis research often uses heterogeneous definitions of sepsis leading to poor generalizability and difficulty in comparing studies to each other. We have developed OpenSep, an open-source pipeline for sepsis phenotyping according to the Sepsis-3 definition, as well as determination of time of sepsis onset and SOFA scores. The Minimal Sepsis Data Model was developed alongside the pipeline to enable the execution of the pipeline to diverse sources of electronic health record data. The pipeline\u27s accuracy was validated by applying it to the MIMIC-IV version 1.0 data and comparing sepsis onset and SOFA scores to those produced by the pipeline developed by the curators of MIMIC. We demonstrated high reliability between both the sepsis onsets and SOFA scores, however the use of the Minimal Sepsis Data model developed for this work allows our pipeline to be applied to more broadly to data sources beyond MIMIC