iPatient in medical information systems and future of internet of health

The results of Study "iHealthCare Optimization", provided by Dell EMC External Research and Academic Alliances, are presented. Big Data analytics of Medical information system qMS records was implemented using cluster analysis in Python. Software for cluster analysis was created by Andrey Mazelis (Vladivostok State University of Economics and Service). There are two directions of cluster analysis: Series treatment (number of investigation procedures for each patient) and Series time (waiting time for investigation procedures for each patient). Two models of patients management (Model A and Model B) were found, that can be used for better planning of care management. Models approach provides the new capability to implement Health Care Standard in mode aaS, using feedback after Big Data analytics. Around 80-90% of patients with Essential hypertension can get treatment in Day Hospital without hospitalization

Impact of a brief faculty training to improve patient-centered communication while using electronic health records

Objective Despite rapid EHR adoption, few faculty receive training in how to implement patient-centered communication skills while using computers in exam rooms. We piloted a patient-centered EHR use training to address this issue. Methods Faculty received four hours of training at Cleveland Clinic and a condensed 90-minute version at the University of Chicago. Both included a lecture and a Group-Objective Structured Clinical Exam (GOSCE) experience. Direct observations of 10 faculty in their clinical practices were performed pre- and post-workshop. Results Thirty participants (94%) completed a post-workshop evaluation assessing knowledge, attitude, and skills. Faculty reported that training was important, relevant, and should be required for all providers; no differences were found between longer versus shorter training. Participants in the longer training reported higher GOSCE efficacy, however shorter workshop participants agreed more with the statement that they had gained new knowledge. Faculty improved their patient-centered EHR use skills in clinical practice on post- versus pre-workshop ratings using a validated direct-observation rating tool. Conclusion A brief lecture and GOSCE can be effective in training busy faculty on patient-centered EHR use skills. Practice Implications Faculty training on patient-centered EHR skills can enhance patient-doctor communication and promotes positive role modeling of these skills to learners

Classic and Digital Anamnesis

Background & Aims With the ever-increasing adoption of Electronic Health Records (EHR) and its varying influence in clinical practice, physician’s adaptability has been strained. Multiple workflow challenges and necessary changes regarding EHR use are identifiable. Anamnesis remains cornerstone for good medical practice, yet how to conduct such practice in this new context is problematic and may need to be analyzed. The conceptualization of a model for the hybridization of classic and digital means of medical history taking or anamnesis may be a relevant part of the solution. This study aims to explore how physicians gather data, how is it integrated, and what factors play a role in the decision-making process from both classic and digital sources – the first relying on the patient and the latter on EHRs. It further attempts to conceptualize digital anamnesis and discuss its hybridization with conventional medical practices. It additionally touches aspects of medical education models regarding EHRs and expectations around them. Methods The study development benefited from the input gathered from systematic review and four interviews conducted to junior interns. Then the survey, aimed at both physicians and medical students with specific questions to each sample, was distributed across hospitals and medical schools via email. Data was collected and integrated, with both quantitative and qualitative data originating from the survey. Results There was a total of 656 observations, from both medical students (n=374) and physicians (n=282). Regarding clinical practice, physicians were divided in two groups, young physicians (n=159) and experienced physicians (n=123), with a cutoff or 35 years old. A huge variability of current medical practices on medical history taking in the context of EHRs was observed. Time usage, data review and entry, and data compatibility with patient-provided information reported said variability. With age being a prevalent factor. EHR education showed major gaps in medical students and junior interns’ curriculum. However, it is seen as highly valued in both cases Current medical practices regarding medical history taking in the context of medical work with EHRs were highly variable. Physicians employed different tactics and workflows while using EHRs without any visible evidence-based adaptation. The conceptualization of a model for Digital Anamnesis, to somehow organize medical history taking through digital tools, such as EHR, maybe helpful for practice and medical education purposes. Based on the systematic review conducted, survey answers and current classic anamnesis frameworks, a model for Digital Anamnesis was conceptualized, with regards to data review and entry. Three interconnected aspects of digital medical history can be identified. The first being the content to be discovered in the EHR, which equates to the virtual construct of the patient in EHR data (iPatient) and background information regarding past medical history, family, personal and social history, drug and allergy history. The second, are the process skills for exploration of data, such as computer literacy and skills, multitasking management, data selection for note review and entry and documentation managing. Lastly, EHR-specific characteristics that influent user interface, data management and system interoperability. Nonetheless, digital anamnesis benefits from its integration with classic anamnesis. For that, development, and testing of different teaching models, based in virtual and simulation components can be conducted within medical schools and with junior interns. Clinical and simulation-based medical education can further develop EHR skills both in communication and proficiency. EHR proficiency skills are also related with data management and can impact physicians work habits. Aiming for a better understanding of the issues that affect EHR data and uniformization of EHR data entry can decrease physicians’ workload and fatigue. Medical education should focus on the integration between digital and classic anamnesis. Future physicians will rely increasingly on EHRs and major gaps regarding education on EHR use were identified. Further work should be done in creating models for classic and digital anamnesis integration that could be implemented in medical education and practice. It is recommended further educational opportunities to be created towards EHR simulation its integration in medical curriculum.Contexto e objetivos Com permanente expansão da adoção de Processos Clínicos Eletrónicos (PCE) e a sua influência na prática clínica, a adaptabilidade dos médicos foi posta à prova. Foram identificados desafios no fluxo de trabalho e mudanças necessárias no uso de PCE. A anamnese continua a ser fundamental para uma correta prática clínica, no entanto como a fazer neste novo contexto é alvo de discussão e necessita ser analisado. A conceptualização de um modelo híbrido de anamnese clássica e digital pode ser uma parte relevante para a solução. Este estudo propõe-se a explorar como é que os médicos recolhem informação, como esta é integrada, e que fatores influenciam o processo de decisão de fontes clássicas e digitais – a primeira fundamentada no doente e a segunda em PCE. Além disso, pretende conceptualizar Anamnese Digital, e discutir a sua hibridização com métodos convencionais de prática clínica. Aborda, também, aspetos de modelos de educação médica relacionados com PCE e expectativas nos mesmos. Materiais e métodos O desenvolvimento do estudo beneficiou dos contributos de médicos e da revisão sistemática desenvolvida e publicada. O questionário, direcionado a médicos e a estudantes de medicina, com questões especificas para cada, foi divulgado em hospitais e escolas médicas por email. Os dados recolhidos foram analisados com uso de estatística descritiva e analítica. Resultados Foram colhidas um total de 656 respostas, de estudantes (n=374) e de médicos (n=282). Relativamente à prática clínica, os médicos foram divididos em novos (n=159), com 35 anos ou menos, e em experientes (n=123). Foi observada uma enorme variabilidade de práticas clínicas relativamente à colheita de história médica com uso de PCE. O tempo de uso, o processo de consulta e inclusão de informação, e a compatibilidade entre informação proveniente do doente e do PCE refletiram essa variabilidade. Sendo a idade um fator significativo. O currículo de estudantes de medicina e de médicos internos revelou lacunas a nível de educação em PCE. Sendo, no entanto, considerado útil por ambos os grupos. Foi observada grande variabilidade entre práticas clínicas relativamente à colheita de história médica com uso de PCE. Diferentes fluxos de trabalho são usados pelos médicos na sua relação com PCE, aparentemente sem serem fundamentados em adaptações baseadas na evidência. A conceptualização de Anamnese Digital, a fim de poder sugerir um método para organizar o processo de colheita de informação em ferramentas digitais como PCE, pode ser útil para a prática e educação médicas. Foi conceptualizado um modelo de Anamnese Digital respeitante à colheita e inclusão de informação, com base na revisão sistemática desenvolvida e publicada, nos resultados do questionário e em abordagens atuais de história clínica clássica. Três componentes de Anamnese Digital foram identificados e interrelacionados. O primeiro diz respeito ao conteúdo a ser descoberto em PCE, que se traduz na construção de uma imagem virtual do doente representada neste contexto (iPatient) e a informação adicional sobre historial médico, história pessoal, familiar e social do doente, bem como medicação e alergias. O segundo são as competências do profissional relativas à procura de informação em PCE, como literacia em computadores, gestão de tarefas, seleção de informação consultada e incluída e gestão de documentação. Por último, as características do PCE que influenciam a interface do usuário, a gestão de dados e de documentação. Não obstante, a Anamnese Digital beneficia da sua integração com Anamnese Clássica. Para tal, a criação e estudo de diferentes modelos de ensino, baseados em componentes virtuais e de simulação, podem ser desenvolvidos em escolas médicas e com participação de internos. Educação médica, em contextos clínicos e de simulação, pode desenvolver competências tanto em comunicação como proficiência dos estudantes com PCE. Estas podem estar relacionadas com gestão de dados podendo, assim, ter impacto nos hábitos de trabalho dos profissionais. Ambicionando um melhor conhecimento dos desafios que afligem a informação em PCE, bem como uma maior uniformização da sua introdução em PCE, podem traduzir uma diminuição da sobrecarga de trabalho e fadiga dos médicos. Educação médica deve-se, assim, focar na integração entre anamnese digital e clássica. No futuro, os médicos irão cada vez mais recorrer a PCE na sua prática clínica sendo que, atualmente foram encontradas falhas no seu currículo. Sendo necessário criar modelos para integração entre anamnese clássica e digital que possam ser implementados na prática e ensino médico. É recomendada a criação de oportunidades de ensino em PCE munindo-se de ambientes simulados

Protecting healing relationships in the age of electronic health records: report from an international conference

We present findings of an international conference of diverse participants exploring the influence of electronic health records (EHRs) on the patient-practitioner relationship. Attendees united around a belief in the primacy of this relationship and the importance of undistracted attention. They explored administrative, regulatory, and financial requirements that have guided United States (US) EHR design and challenged patient-care documentation, usability, user satisfaction, interconnectivity, and data sharing. The United States experience was contrasted with those of other nations, many of which have prioritized patient-care documentation rather than billing requirements and experienced high user satisfaction. Conference participants examined educational methods to teach diverse learners effective patient-centered EHR use, including alternative models of care delivery and documentation, and explored novel ways to involve patients as healthcare partners like health-data uploading, chart co-creation, shared practitioner notes, applications, and telehealth. Future best practices must preserve human relationships, while building an effective patient-practitioner (or team)-EHR triad

Outlier detection of vital sign trajectories from COVID-19 patients

There is growing interest in continuous wearable vital sign sensors for monitoring patients remotely at home. These monitors are usually coupled to an alerting system, which is triggered when vital sign measurements fall outside a predefined normal range. Trends in vital signs, such as an increasing heart rate, are often indicative of deteriorating health, but are rarely incorporated into alerting systems. In this work, we present a novel outlier detection algorithm to identify such abnormal vital sign trends. We introduce a distance-based measure to compare vital sign trajectories. For each patient in our dataset, we split vital sign time series into 180 minute, non-overlapping epochs. We then calculated a distance between all pairs of epochs using the dynamic time warp distance. Each epoch was characterized by its mean pairwise distance (average link distance) to all other epochs, with large distances considered as outliers. We applied this method to a pilot dataset collected over 1561 patient-hours from 8 patients who had recently been discharged from hospital after contracting COVID-19. We show that outlier epochs correspond well with patients who were subsequently readmitted to hospital. We also show, descriptively, how epochs transition from normal to abnormal for one such patient.Comment: 4 pages, 4 figures, 1 table. Submitted to IEEE BHI 2022, decision pendin

Master of Science

thesisThe Nursing Minimum Data Set (NMDS) and the Nursing Interventions Classification (NIC) are standardized nomenclatures to describe nursing care core data. The aim of this study was to evaluate the effect of the NMDS and the NIC in flight nursing practice. The study investigated the usefulness of the NMDS for flight nursing documentation and nursing activities performed by flight nurses. The study also examined whether the activities and interventions of flight nurses were consistent with the NIC as proposed in the Iowa Intervention project. The documentation for 20 cardiac patients transported by rotor wing aircraft was examined and analyzed. Findings demonstrated that nursing interventions were the most frequently found elements from the NMDS. Hemodynamic Regulation was the most frequently occurring nursing intervention from the NIC. Although the NMDS and NIC can be used, the fit was not always sufficient or strong. Recommendations are given for strengthening the NMDS and NIC for use in flight nursing practice

Building ALLAS: Creation of an Asthma and Allergies App

The purpose of this project was to determine the potential need for an app to allow patients to self-manage their asthma and allergies. Through a substantial literature review, the need for an app as well as a desire for this population to manage their disease was demonstrated. Determination was made to have three separate components to create an all-inclusive app, an education component, an asthma tracker, and a personalized allergy profile. The app was storyboarded before being sent to providers and small focus group for proof of concept and functionality of components. The app, ALLAS, was constructed and housed on goodbarber.com allowing the creator to update information and push that information out immediately as features or along with the establishment of an LLC (Limited Liability Corporation) and trademarking of ALLAS. Content will continue to be added and beta-testing will occur in early 2017 in preparation of a general release to all mobile device download stores. For sustainability, ALLAS is currently funded by the creator, with the ability to have advertising on screens in the app

Efficient and Secure Data Sharing Using Attribute-based Cryptography

La crescita incontrollata di dati prodotti da molte sorgenti, eterogenee e di- namiche, spinge molti possessori di tali dati a immagazzinarli su server nel cloud, anche al fine di condividerli con terze parti. La condivisione di dati su server (possibilmente) non fidati fonte di importanti e non banali questioni riguardanti sicurezza, privacy, confidenzialit e controllo degli accessi. Al fine di prevenire accessi incontrollati ai dati, una tipica soluzione consiste nel cifrare i dati stessi. Seguendo tale strada, la progettazione e la realizzazione di politiche di accesso ai dati cifrati da parte di terze parti (che possono avere differenti diritti sui dati stessi) un compito complesso, che impone la presenza di un controllore fidato delle politiche. Una possibile soluzione l\u2019impiego di un meccanismo per il controllo degli accessi basato su schemi di cifratura attribute-base (ABE ), che permette al possessore dei dati di cifrare i dati in funzione delle politiche di accesso dei dati stessi. Di contro, l\u2019adozione di tali meccanismi di controllo degli accessi presentano due problemi (i) privacy debole: le politiche di accesso sono pubbliche e (ii) inefficienza: le politiche di accesso sono statiche e una loro modifica richiede la ricifratura (o la cifratura multipla) di tutti i dati. Al fine di porre rimedio a tali problemi, il lavoro proposto in questa tesi prende in con- siderazione un particolare schema di cifratura attribute-based, chiamato inner product encryption (IPE, che gode della propriet attribute-hiding e pertanto riesce a proteggere la privatezza delle politiche di accesso) e lo combina con le tecniche di proxy re-encryption, che introducono una maggiore flessibilit ed efficienza. La prima parte di questa tesi discute l\u2019adeguatezza dell\u2019introduzione di un meccanismo di controllo degli accessi fondato su schema basato su inner product e proxy re-encryption (IPPRE ) al fine di garantire la condivisione sicura di dati immagazzinati su cloud server non fidati. Pi specificamente, proponiamo due proponiamo due versioni di IPE : in prima istanza, presentiamo una versione es- tesa con proxy re-encryption di un noto schema basato su inner product [1]. In seguito, usiamo tale schema in uno scenario in cui vengono raccolti e gestiti dati medici. In tale scenario, una volta che i dati sono stati raccolti, le politiche di ac- cesso possono variare al variare delle necessit dei diversi staff medici. Lo schema proposto delega il compito della ricifratura dei dati a un server proxy parzial- mente fidato, che pu trasformare la cifratura dei dati (che dipende da una polit- ica di accesso) in un\u2019altra cifratura (che dipende da un\u2019altra politica di accesso) senza per questo avere accesso ai dati in chiaro o alla chiave segreta utilizzata dal possessore dei dati. In tal modo, il possessore di una chiave di decifratura corrispondente alla seconda politica di accesso pu accedere ai dati senza intera- gire con il possessore dei dati (richiedendo cio una chiave di decifratura associata alla propria politica di accesso). Presentiamo un\u2019analisi relativa alle prestazioni di tale schema implementato su curve ellittiche appartenenti alle classi SS, MNT e BN e otteniamo incoraggianti risultati sperimentali. Dimostriamo inoltre che lo schema proposto sicuro contro attacchi chosen plaintext sotto la nota ipotesi DLIN. In seconda istanza, presentiamo una versione ottimizzata dello schema proposto in precedenza (E-IPPRE ), basata su un ben noto schema basato suinner product, proposto da Kim [2]. Lo schema E-IPPRE proposto richiede un numero costante di operazioni di calcolo di pairing e ci garantisce che gli oggetti prodotti dall esecuzione dello schema (chiavi di decifratura, chiavi pubbliche e le cifrature stesse) sono di piccole rispetto ai parametri di sicurezza e sono efficientemente calcolabili. Testiamo sperimentalmente l\u2019efficienza dello schema proposto e lo proviamo (selettivamente nei confronti degli attributi) sicuro nei confronti di attacchi chosen plaintext sotto la nota ipotesi BDH. In altri termini, lo schema proposto non rivela alcuna informazione riguardante le politiche di accesso. La seconda parte di questa tesi presenta uno schema crittografico per la condivisione sicura dei dati basato su crittografia attribute-based e adatto per scenari basati su IoT. Come noto, il problema principale in tale ambito riguarda le limitate risorse computazionali dei device IoT coinvolti. A tal proposito, proponiamo uno schema che combina la flessibilit di E-IPPRE con l\u2019efficienza di uno schema di cifratura simmetrico quale AES, ottenendo uno schema di cifratura basato su inner product, proxy-based leggero (L-IPPRE ). I risultati sperimentali confermano l\u2019adeguatezza di tale schema in scenari IoT.Riferimenti [1] Jong Hwan Park. Inner-product encryption under standard assumptions. Des. Codes Cryptography, 58(3):235\u2013257, March 2011. [2] Intae Kim, Seong Oun Hwang, Jong Hwan Park, and Chanil Park. An effi- cient predicate encryption with constant pairing computations and minimum costs. IEEE Trans. Comput., 65(10):2947\u20132958, October 2016.With the ever-growing production of data coming from multiple, scattered, and highly dynamical sources, many providers are motivated to upload their data to the cloud servers and share them with other persons for different purposes. However, storing data on untrusted cloud servers imposes serious concerns in terms of security, privacy, data confidentiality, and access control. In order to prevent privacy and security breaches, it is vital that data is encrypted first before it is outsourced to the cloud. However, designing access control mod- els that enable different users to have various access rights to the shared data is the main challenge. To tackle this issue, a possible solution is to employ a cryptographic-based data access control mechanism such as attribute-based encryption (ABE ) scheme, which enables a data owner to take full control over data access. However, access control mechanisms based on ABE raise two chal- lenges: (i) weak privacy: they do not conceal the attributes associated with the ciphertexts, and therefore they do not satisfy attribute-hiding security, and (ii) inefficiency: they do not support efficient access policy change when data is required to be shared among multiple users with different access policies. To address these issues, this thesis studies and enhances inner-product encryption (IPE ), a type of public-key cryptosystem, which supports the attribute-hiding property as well as the flexible fine-grained access control based payload-hiding property, and combines it with an advanced cryptographic technique known as proxy re-encryption (PRE ). The first part of this thesis discusses the necessity of applying the inner- product proxy re-encryption (IPPRE ) scheme to guarantee secure data sharing on untrusted cloud servers. More specifically, we propose two extended schemes of IPE : in the first extended scheme, we propose an inner-product proxy re- encryption (IPPRE ) protocol derived from a well-known inner-product encryp- tion scheme [1]. We deploy this technique in the healthcare scenario where data, collected by medical devices according to some access policy, has to be changed afterwards for sharing with other medical staffs. The proposed scheme delegates the re-encryption capability to a semi-trusted proxy who can transform a dele- gator\u2019s ciphertext associated with an attribute vector to a new ciphertext associ- ated with delegatee\u2019s attribute vector set, without knowing the underlying data and private key. Our proposed policy updating scheme enables the delegatee to decrypt the shared data with its own key without requesting a new decryption key. We analyze the proposed protocol in terms of its performance on three dif- ferent types of elliptic curves such as the SS curve, the MNT curve, and the BN curve, respectively. Hereby, we achieve some encouraging experimental results. We show that our scheme is adaptive attribute-secure against chosen-plaintext under standard Decisional Linear (D-Linear ) assumption. To improve the per- formance of this scheme in terms of storage, communication, and computation costs, we propose an efficient inner-product proxy re-encryption (E-IPPRE ) scheme using the transformation of Kim\u2019s inner-product encryption method [2]. The proposed E-IPPRE scheme requires constant pairing operations for its al- gorithms and ensures a short size of the public key, private key, and ciphertext,making it the most efficient and practical compared to state of the art schemes in terms of computation and communication overhead. We experimentally as- sess the efficiency of our protocol and show that it is selective attribute-secure against chosen-plaintext attacks in the standard model under Asymmetric De- cisional Bilinear Diffie-Hellman assumption. Specifically, our proposed schemes do not reveal any information about the data owner\u2019s access policy to not only the untrusted servers (e.g, cloud and proxy) but also to the other users. The second part of this thesis presents a new lightweight secure data sharing scheme based on attribute-based cryptography for a specific IoT -based health- care application. To achieve secure data sharing on IoT devices while preserving data confidentiality, the IoT devices encrypt data before it is outsourced to the cloud and authorized users, who have corresponding decryption keys, can ac- cess the data. The main challenge, in this case, is on the one hand that IoT devices are resource-constrained in terms of energy, CPU, and memory. On the other hand, the existing public-key encryption mechanisms (e.g., ABE ) require expensive computation. We address this issue by combining the flexibility and expressiveness of the proposed E-IPPRE scheme with the efficiency of symmet- ric key encryption technique (AES ) and propose a light inner-product proxy re-encryption (L-IPPRE ) scheme to guarantee secure data sharing between dif- ferent entities in the IoT environment. The experimental results confirm that the proposed L-IPPRE scheme is suitable for resource-constrained IoT scenar- ios.References [1] Jong Hwan Park. Inner-product encryption under standard assumptions. Des. Codes Cryptography, 58(3):235\u2013257, March 2011. [2] Intae Kim, Seong Oun Hwang, Jong Hwan Park, and Chanil Park. An effi- cient predicate encryption with constant pairing computations and minimum costs. IEEE Trans. Comput., 65(10):2947\u20132958, October 2016