Author Correction: Additive manufacturing of ultrafine-grained high-strength titanium alloys.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Additive manufacturing of ultrafine-grained high-strength titanium alloys.

Additive manufacturing, often known as three-dimensional (3D) printing, is a process in which a part is built layer-by-layer and is a promising approach for creating components close to their final (net) shape. This process is challenging the dominance of conventional manufacturing processes for products with high complexity and low material waste1. Titanium alloys made by additive manufacturing have been used in applications in various industries. However, the intrinsic high cooling rates and high thermal gradient of the fusion-based metal additive manufacturing process often leads to a very fine microstructure and a tendency towards almost exclusively columnar grains, particularly in titanium-based alloys1. (Columnar grains in additively manufactured titanium components can result in anisotropic mechanical properties and are therefore undesirable2.) Attempts to optimize the processing parameters of additive manufacturing have shown that it is difficult to alter the conditions to promote equiaxed growth of titanium grains3. In contrast with other common engineering alloys such as aluminium, there is no commercial grain refiner for titanium that is able to effectively refine the microstructure. To address this challenge, here we report on the development of titanium-copper alloys that have a high constitutional supercooling capacity as a result of partitioning of the alloying element during solidification, which can override the negative effect of a high thermal gradient in the laser-melted region during additive manufacturing. Without any special process control or additional treatment, our as-printed titanium-copper alloy specimens have a fully equiaxed fine-grained microstructure. They also display promising mechanical properties, such as high yield strength and uniform elongation, compared to conventional alloys under similar processing conditions, owing to the formation of an ultrafine eutectoid microstructure that appears as a result of exploiting the high cooling rates and multiple thermal cycles of the manufacturing process. We anticipate that this approach will be applicable to other eutectoid-forming alloy systems, and that it will have applications in the aerospace and biomedical industries.

Ultrastrong nanotwinned titanium alloys through additive manufacturing.

Titanium alloys, widely used in the aerospace, automotive and energy sectors, require complex casting and thermomechanical processing to achieve the high strengths required for load-bearing applications. Here we reveal that additive manufacturing can exploit thermal cycling and rapid solidification to create ultrastrong and thermally stable titanium alloys, which may be directly implemented in service. As demonstrated in a commercial titanium alloy, after simple post-heat treatment, adequate elongation and tensile strengths over 1,600 MPa are achieved. The excellent properties are attributed to the unusual formation of dense, stable and internally twinned nanoprecipitates, which are rarely observed in traditionally processed titanium alloys. These nanotwinned precipitates are shown to originate from a high density of dislocations with a dominant screw character and formed from the additive manufacturing process. The work here paves the way to fabricate structural materials with unique microstructures and excellent properties for broad applications.

Crystallographic and Compositional Evolution of Ordered B2 and Disordered BCC Phases During Isothermal Annealing of Refractory High-Entropy Alloys.

Refractory high-entropy alloys (RHEAs) are promising candidates for next-generation high-temperature materials. RHEAs containing Al, often exhibit a checkered pattern microstructure comprising a combination of disordered BCC and ordered B2 phases. Since the ordered B2 phase is based on the BCC parent matrix, distinguishing these two phases can be rather challenging. Advanced characterization techniques are necessary for a reliable qualitative and quantitative analysis of BCC and B2 phases in RHEAs. Additionally, there is a tendency for transformation of the ordered B2 phase into more complex ordered-omega type phases that are usually deleterious to mechanical properties. The current study focuses on the phase stability of a candidate RHEA, Al0.5Mo0.5NbTa0.5TiZr. Correlative transmission electron microscopy (TEM) and atom probe tomography (APT) have been employed to investigate the phase stability and transformation pathway of this RHEA when isothermally annealed at 800°C. The results show that a metastable two-phase BCC + B2 microstructure formed at the early stages of decomposition, eventually transforming into a three-phase BCC + B2 + hP18 microstructure. The hP18 phase is an ordered omega derivative of the ordered B2 phase. The correlative microscopy techniques (TEM and APT) reveal a very interesting interplay of compositional partitioning between the different phases and their respective stability.

Clinicians perceptions of a telemedicine system: a mixed method study of Makassar City, Indonesia.

BACKGROUND: This case study in Makassar City, Indonesia aims to investigate the clinicians' perceptions, including both satisfaction and barriers in using telemedicine in a large, established program which supported 3974 consultations in 2017. METHODS: A mixed methodology was used in this research utilizing a questionnaire with 12 questions, and semi-structured interviews. A purposeful sample of clinicians using the telemedicine system at the 39 primary care clinics in Makassar City were surveyed. A total of 100 clinicians participated in this study. All of them completed the questionnaires (76.9% response rate) and 15 of them were interviewed. RESULTS: The result showed that 78% of the clinicians were satisfied with the telemedicine system. In free text responses 69% said that telemedicine allowed quicker diagnosis and treatment, 47% said poor internet connectivity was a significant obstacle in using the system, and 40% suggested improvement to the infrastructure including internet connection and electricity. CONCLUSION: Overall, the clinicians were satisfied with the system, with the main benefit of rendering the diagnosis faster and easier for patients. However, poor internet connectivity was indicated as the main barrier. Most of the clinicians suggested improving the infrastructure especially the internet network.

Digital health Systems in Kenyan Public Hospitals: a mixed-methods survey.

BACKGROUND: As healthcare facilities in Low- and Middle-Income Countries adopt digital health systems to improve hospital administration and patient care, it is important to understand the adoption process and assess the systems' capabilities. This survey aimed to provide decision-makers with information on the digital health systems landscape and to support the rapidly developing digital health community in Kenya and the region by sharing knowledge. METHODS: We conducted a survey of County Health Records Information Officers (CHRIOs) to determine the extent to which digital health systems in public hospitals that serve as internship training centres in Kenya are adopted. We conducted site visits and interviewed hospital administrators and end users who were at the facility on the day of the visit. We also interviewed digital health system vendors to understand the adoption process from their perspective. Semi-structured interview guides adapted from the literature were used. We identified emergent themes using a thematic analysis from the data. RESULTS: We obtained information from 39 CHRIOs, 58 hospital managers and system users, and 9 digital health system vendors through semi-structured interviews and completed questionnaires. From the survey, all facilities mentioned purchased a digital health system primarily for administrative purposes. Radiology and laboratory management systems were commonly standalone systems and there were varying levels of interoperability within facilities that had multiple systems. We only saw one in-patient clinical module in use. Users reported on issues such as system usability, inadequate training, infrastructure and system support. Vendors reported the availability of a wide range of modules, but implementation was constrained by funding, prioritisation of services, users' lack of confidence in new technologies and lack of appropriate data sharing policies. CONCLUSION: Public hospitals in Kenya are increasingly purchasing systems to support administrative functions and this study highlights challenges faced by hospital users and vendors. Significant work is required to ensure interoperability of systems within hospitals and with other government services. Additional studies on clinical usability and the workflow fit of digital health systems are required to ensure efficient system implementation. However, this requires support from key stakeholders including the government, international donors and regional health informatics organisations.

Development and Deployment of the OpenMRS-Ebola Electronic Health Record System for an Ebola Treatment Center in Sierra Leone.

BACKGROUND: Stringent infection control requirements at Ebola treatment centers (ETCs), which are specialized facilities for isolating and treating Ebola patients, create substantial challenges for recording and reviewing patient information. During the 2014-2016 West African Ebola epidemic, paper-based data collection systems at ETCs compromised the quality, quantity, and confidentiality of patient data. Electronic health record (EHR) systems have the potential to address such problems, with benefits for patient care, surveillance, and research. However, no suitable software was available for deployment when large-scale ETCs opened as the epidemic escalated in 2014. OBJECTIVE: We present our work on rapidly developing and deploying OpenMRS-Ebola, an EHR system for the Kerry Town ETC in Sierra Leone. We describe our experience, lessons learned, and recommendations for future health emergencies. METHODS: We used the OpenMRS platform and Agile software development approaches to build OpenMRS-Ebola. Key features of our work included daily communications between the development team and ground-based operations team, iterative processes, and phased development and implementation. We made design decisions based on the restrictions of the ETC environment and regular user feedback. To evaluate the system, we conducted predeployment user questionnaires and compared the EHR records with duplicate paper records. RESULTS: We successfully built OpenMRS-Ebola, a modular stand-alone EHR system with a tablet-based application for infectious patient wards and a desktop-based application for noninfectious areas. OpenMRS-Ebola supports patient tracking (registration, bed allocation, and discharge); recording of vital signs and symptoms; medication and intravenous fluid ordering and monitoring; laboratory results; clinician notes; and data export. It displays relevant patient information to clinicians in infectious and noninfectious zones. We implemented phase 1 (patient tracking; drug ordering and monitoring) after 2.5 months of full-time development. OpenMRS-Ebola was used for 112 patient registrations, 569 prescription orders, and 971 medication administration recordings. We were unable to fully implement phases 2 and 3 as the ETC closed because of a decrease in new Ebola cases. The phase 1 evaluation suggested that OpenMRS-Ebola worked well in the context of the rollout, and the user feedback was positive. CONCLUSIONS: To our knowledge, OpenMRS-Ebola is the most comprehensive adaptable clinical EHR built for a low-resource setting health emergency. It is designed to address the main challenges of data collection in highly infectious environments that require robust infection prevention and control measures and it is interoperable with other electronic health systems. Although we built and deployed OpenMRS-Ebola more rapidly than typical software, our work highlights the challenges of having to develop an appropriate system during an emergency rather than being able to rapidly adapt an existing one. Lessons learned from this and previous emergencies should be used to ensure that a set of well-designed, easy-to-use, pretested health software is ready for quick deployment in future.

A Small Spot, Inert Gas, Ion Milling Process as a Complementary Technique to Focused Ion Beam Specimen Preparation.

This paper reports on the substantial improvement of specimen quality by use of a low voltage (0.05 to ~1 keV), small diameter (~1 µm), argon ion beam following initial preparation using conventional broad-beam ion milling or focused ion beam. The specimens show significant reductions in the amorphous layer thickness and implanted artifacts. The targeted ion milling controls the specimen thickness according to the needs of advanced aberration-corrected and/or analytical transmission electron microscopy applications.

Factors Influencing Data Quality in Electronic Health Record Systems in 50 Health Facilities in Rwanda and the Role of Clinical Alerts: Cross-Sectional Observational Study.

BACKGROUND: Electronic health records (EHRs) play an increasingly important role in delivering HIV care in low- and middle-income countries. The data collected are used for direct clinical care, quality improvement, program monitoring, public health interventions, and research. Despite widespread EHR use for HIV care in African countries, challenges remain, especially in collecting high-quality data. OBJECTIVE: We aimed to assess data completeness, accuracy, and timeliness compared to paper-based records, and factors influencing data quality in a large-scale EHR deployment in Rwanda. METHODS: We randomly selected 50 health facilities (HFs) using OpenMRS, an EHR system that supports HIV care in Rwanda, and performed a data quality evaluation. All HFs were part of a larger randomized controlled trial, with 25 HFs receiving an enhanced EHR with clinical decision support systems. Trained data collectors visited the 50 HFs to collect 28 variables from the paper charts and the EHR system using the Open Data Kit app. We measured data completeness, timeliness, and the degree of matching of the data in paper and EHR records, and calculated concordance scores. Factors potentially affecting data quality were drawn from a previous survey of users in the 50 HFs. RESULTS: We randomly selected 3467 patient records, reviewing both paper and EHR copies (194,152 total data items). Data completeness was >85% threshold for all data elements except viral load (VL) results, second-line, and third-line drug regimens. Matching scores for data values were close to or >85% threshold, except for dates, particularly for drug pickups and VL. The mean data concordance was 10.2 (SD 1.28) for 15 (68%) variables. HF and user factors (eg, years of EHR use, technology experience, EHR availability and uptime, and intervention status) were tested for correlation with data quality measures. EHR system availability and uptime was positively correlated with concordance, whereas users' experience with technology was negatively correlated with concordance. The alerts for missing VL results implemented at 11 intervention HFs showed clear evidence of improving timeliness and completeness of initially low matching of VL results in the EHRs and paper records (11.9%-26.7%; P<.001). Similar effects were seen on the completeness of the recording of medication pickups (18.7%-32.6%; P<.001). CONCLUSIONS: The EHR records in the 50 HFs generally had high levels of completeness except for VL results. Matching results were close to or >85% threshold for nondate variables. Higher EHR stability and uptime, and alerts for entering VL both strongly improved data quality. Most data were considered fit for purpose, but more regular data quality assessments, training, and technical improvements in EHR forms, data reports, and alerts are recommended. The application of quality improvement techniques described in this study should benefit a wide range of HFs and data uses for clinical care, public health, and disease surveillance.

Open Source Software in Healthcare: International Case Series from the IMIA Open Source Working Group.

In this case series, we demonstrate how open-source software has been widely adopted as the primary health information system in many low- and middle-income countries, and for government-developed applications in high-income settings. We discuss the concept of Digital Global Goods and how the general approach of releasing software developed through public funding under open-source licences could improve the delivery of healthcare in all settings through increased transparency and collaboration as well as financial efficiency.

The impact of culture medium on the development and physiology of biofilms of Pseudomonas fluorescens formed on polyurethane paint.

Microbial biofilms cause the deterioration of polymeric coatings such as polyurethanes (PUs). In many cases, microbes have been shown to use the PU as a nutrient source. The interaction between biofilms and nutritive substrata is complex, since both the medium and the substratum can provide nutrients that affect biofilm formation and biodeterioration. Historically, studies of PU biodeterioration have monitored the planktonic cells in the medium surrounding the material, not the biofilm. This study monitored planktonic and biofilm cell counts, and biofilm morphology, in long-term growth experiments conducted with Pseudomonas fluorescens under different nutrient conditions. Nutrients affected planktonic and biofilm cell numbers differently, and neither was representative of the system as a whole. Microscopic examination of the biofilm revealed the presence of intracellular storage granules in biofilms grown in M9 but not yeast extract salts medium. These granules are indicative of nutrient limitation and/or entry into stationary phase, which may impact the biodegradative capability of the biofilm.

Barriers, Priorities and Lessons Learned in Achieving Electronic Health Records Interoperability in Low- and Middle-Income Countries: Workshop Findings.

Electronic health records (EHR) interoperability is a complex topic that continues to gain traction in the digital health landscape. We facilitated a qualitative workshop consisting of domain experts in EHR implementation and health IT managers. The workshop aimed to identify critical barriers to achieving interoperability, priorities for new EHR implementations and lessons learned from managing existing implementations. The workshop highlighted that data modelling and interoperability standards are vital priorities for maternal and child health data services in low- and middle-income countries (LMICs).

The Global Health Informatics landscape and JAMIA.

Global Health Informatics (GHI) as a branch of health informatics has been established for 2 decades now. During that time, great strides have been made in the creation and implementation of informatics tools to improve healthcare delivery and outcomes in the most vulnerable and remote communities worldwide. In many of the most successful projects, innovation has been shared between teams in high- and low- or middle-income countries (LMICs). In this perspective, we review the state of the academic field of GHI and the work published in JAMIA in the last 6 1/2 years. We apply criteria for articles about LMICs, those on international health, and on indigenous and refugee population, and subtypes of research. For comparison, we apply those criteria to JAMIA Open and 3 other health informatics journals which publish articles on GHI. We make recommendations for future directions and the role that journals like JAMIA can play in strengthening this work worldwide.

Comparison of Diagnostic and Triage Accuracy of Ada Health and WebMD Symptom Checkers, ChatGPT, and Physicians for Patients in an Emergency Department: Clinical Data Analysis Study.

BACKGROUND: Diagnosis is a core component of effective health care, but misdiagnosis is common and can put patients at risk. Diagnostic decision support systems can play a role in improving diagnosis by physicians and other health care workers. Symptom checkers (SCs) have been designed to improve diagnosis and triage (ie, which level of care to seek) by patients. OBJECTIVE: The aim of this study was to evaluate the performance of the new large language model ChatGPT (versions 3.5 and 4.0), the widely used WebMD SC, and an SC developed by Ada Health in the diagnosis and triage of patients with urgent or emergent clinical problems compared with the final emergency department (ED) diagnoses and physician reviews. METHODS: We used previously collected, deidentified, self-report data from 40 patients presenting to an ED for care who used the Ada SC to record their symptoms prior to seeing the ED physician. Deidentified data were entered into ChatGPT versions 3.5 and 4.0 and WebMD by a research assistant blinded to diagnoses and triage. Diagnoses from all 4 systems were compared with the previously abstracted final diagnoses in the ED as well as with diagnoses and triage recommendations from three independent board-certified ED physicians who had blindly reviewed the self-report clinical data from Ada. Diagnostic accuracy was calculated as the proportion of the diagnoses from ChatGPT, Ada SC, WebMD SC, and the independent physicians that matched at least one ED diagnosis (stratified as top 1 or top 3). Triage accuracy was calculated as the number of recommendations from ChatGPT, WebMD, or Ada that agreed with at least 2 of the independent physicians or were rated "unsafe" or "too cautious." RESULTS: Overall, 30 and 37 cases had sufficient data for diagnostic and triage analysis, respectively. The rate of top-1 diagnosis matches for Ada, ChatGPT 3.5, ChatGPT 4.0, and WebMD was 9 (30%), 12 (40%), 10 (33%), and 12 (40%), respectively, with a mean rate of 47% for the physicians. The rate of top-3 diagnostic matches for Ada, ChatGPT 3.5, ChatGPT 4.0, and WebMD was 19 (63%), 19 (63%), 15 (50%), and 17 (57%), respectively, with a mean rate of 69% for physicians. The distribution of triage results for Ada was 62% (n=23) agree, 14% unsafe (n=5), and 24% (n=9) too cautious; that for ChatGPT 3.5 was 59% (n=22) agree, 41% (n=15) unsafe, and 0% (n=0) too cautious; that for ChatGPT 4.0 was 76% (n=28) agree, 22% (n=8) unsafe, and 3% (n=1) too cautious; and that for WebMD was 70% (n=26) agree, 19% (n=7) unsafe, and 11% (n=4) too cautious. The unsafe triage rate for ChatGPT 3.5 (41%) was significantly higher (P=.009) than that of Ada (14%). CONCLUSIONS: ChatGPT 3.5 had high diagnostic accuracy but a high unsafe triage rate. ChatGPT 4.0 had the poorest diagnostic accuracy, but a lower unsafe triage rate and the highest triage agreement with the physicians. The Ada and WebMD SCs performed better overall than ChatGPT. Unsupervised patient use of ChatGPT for diagnosis and triage is not recommended without improvements to triage accuracy and extensive clinical evaluation.

Underlying factors determining grain morphologies in high-strength titanium alloys processed by additive manufacturing.

In recent research, additions of solute to Ti and some Ti-based alloys have been employed to produce equiaxed microstructures when processing these materials using additive manufacturing. The present study develops a computational scheme for guiding the selection of such alloying additions, and the minimum amounts required, to effect the columnar to equiaxed microstructural transition. We put forward two physical mechanisms that may produce this transition; the first and more commonly discussed is based on growth restriction factors, and the second on the increased freezing range effected by the alloying addition coupled with the imposed rapid cooling rates associated with AM techniques. We show in the research described here, involving a number of model binary as well as complex multi-component Ti alloys, and the use of two different AM approaches, that the latter mechanism is more reliable regarding prediction of the grain morphology resulting from given solute additions.

Impacts of e-health on the outcomes of care in low- and middle-income countries: where do we go from here?

E-health encompasses a diverse set of informatics tools that have been designed to improve public health and health care. Little information is available on the impacts of e-health programmes, particularly in low- and middle-income countries. We therefore conducted a scoping review of the published and non-published literature to identify data on the effects of e-health on health outcomes and costs. The emphasis was on the identification of unanswered questions for future research, particularly on topics relevant to low- and middle-income countries. Although e-health tools supporting clinical practice have growing penetration globally, there is more evidence of benefits for tools that support clinical decisions and laboratory information systems than for those that support picture archiving and communication systems. Community information systems for disease surveillance have been implemented successfully in several low- and middle-income countries. Although information on outcomes is generally lacking, a large project in Brazil has documented notable impacts on health-system efficiency. Meta-analyses and rigorous trials have documented the benefits of text messaging for improving outcomes such as patients' self-care. Automated telephone monitoring and self-care support calls have been shown to improve some outcomes of chronic disease management, such as glycaemia and blood pressure control, in low- and middle-income countries. Although large programmes for e-health implementation and research are being conducted in many low- and middle-income countries, more information on the impacts of e-health on outcomes and costs in these settings is still needed.

Adaptation of a web-based, open source electronic medical record system platform to support a large study of tuberculosis epidemiology.

BACKGROUND: In 2006, we were funded by the US National Institutes of Health to implement a study of tuberculosis epidemiology in Peru. The study required a secure information system to manage data from a target goal of 16,000 subjects who needed to be followed for at least one year. With previous experience in the development and deployment of web-based medical record systems for TB treatment in Peru, we chose to use the OpenMRS open source electronic medical record system platform to develop the study information system. Supported by a core technical and management team and a large and growing worldwide community, OpenMRS is now being used in more than 40 developing countries. We adapted the OpenMRS platform to better support foreign languages. We added a new module to support double data entry, linkage to an existing laboratory information system, automatic upload of GPS data from handheld devices, and better security and auditing of data changes. We added new reports for study managers, and developed data extraction tools for research staff and statisticians. Further adaptation to handle direct entry of laboratory data occurred after the study was launched. RESULTS: Data collection in the OpenMRS system began in September 2009. By August 2011 a total of 9,256 participants had been enrolled, 102,274 forms and 13,829 laboratory results had been entered, and there were 208 users. The system is now entirely supported by the Peruvian study staff and programmers. CONCLUSIONS: The information system served the study objectives well despite requiring some significant adaptations mid-stream. OpenMRS has more tools and capabilities than it did in 2008, and requires less adaptations for future projects. OpenMRS can be an effective research data system in resource poor environments, especially for organizations using or considering it for clinical care as well as research.