Information technologies for pain management

Millions of people around the world suffer from pain, acute or chronic and this raises the importance of its screening, assessment and treatment. The importance of pain is attested by the fact that it is considered the fifth vital sign for indicating basic bodily functions, health and quality of life, together with the four other vital signs: blood pressure, body temperature, pulse rate and respiratory rate. However, while these four signals represent an objective physical parameter, the occurrence of pain expresses an emotional status that happens inside the mind of each individual and therefore, is highly subjective that makes difficult its management and evaluation. For this reason, the self-report of pain is considered the most accurate pain assessment method wherein patients should be asked to periodically rate their pain severity and related symptoms. Thus, in the last years computerised systems based on mobile and web technologies are becoming increasingly used to enable patients to report their pain which lead to the development of electronic pain diaries (ED). This approach may provide to health care professionals (HCP) and patients the ability to interact with the system anywhere and at anytime thoroughly changes the coordinates of time and place and offers invaluable opportunities to the healthcare delivery. However, most of these systems were designed to interact directly to patients without presence of a healthcare professional or without evidence of reliability and accuracy. In fact, the observation of the existing systems revealed lack of integration with mobile devices, limited use of web-based interfaces and reduced interaction with patients in terms of obtaining and viewing information. In addition, the reliability and accuracy of computerised systems for pain management are rarely proved or their effects on HCP and patients outcomes remain understudied. This thesis is focused on technology for pain management and aims to propose a monitoring system which includes ubiquitous interfaces specifically oriented to either patients or HCP using mobile devices and Internet so as to allow decisions based on the knowledge obtained from the analysis of the collected data. With the interoperability and cloud computing technologies in mind this system uses web services (WS) to manage data which are stored in a Personal Health Record (PHR). A Randomised Controlled Trial (RCT) was implemented so as to determine the effectiveness of the proposed computerised monitoring system. The six weeks RCT evidenced the advantages provided by the ubiquitous access to HCP and patients so as to they were able to interact with the system anywhere and at anytime using WS to send and receive data. In addition, the collected data were stored in a PHR which offers integrity and security as well as permanent on line accessibility to both patients and HCP. The study evidenced not only that the majority of participants recommend the system, but also that they recognize it suitability for pain management without the requirement of advanced skills or experienced users. Furthermore, the system enabled the definition and management of patient-oriented treatments with reduced therapist time. The study also revealed that the guidance of HCP at the beginning of the monitoring is crucial to patients' satisfaction and experience stemming from the usage of the system as evidenced by the high correlation between the recommendation of the application, and it suitability to improve pain management and to provide medical information. There were no significant differences regarding to improvements in the quality of pain treatment between intervention group and control group. Based on the data collected during the RCT a clinical decision support system (CDSS) was developed so as to offer capabilities of tailored alarms, reports, and clinical guidance. This CDSS, called Patient Oriented Method of Pain Evaluation System (POMPES), is based on the combination of several statistical models (one-way ANOVA, Kruskal-Wallis and Tukey-Kramer) with an imputation model based on linear regression. This system resulted in fully accuracy related to decisions suggested by the system compared with the medical diagnosis, and therefore, revealed it suitability to manage the pain. At last, based on the aerospace systems capability to deal with different complex data sources with varied complexities and accuracies, an innovative model was proposed. This model is characterized by a qualitative analysis stemming from the data fusion method combined with a quantitative model based on the comparison of the standard deviation together with the values of mathematical expectations. This model aimed to compare the effects of technological and pen-and-paper systems when applied to different dimension of pain, such as: pain intensity, anxiety, catastrophizing, depression, disability and interference. It was observed that pen-and-paper and technology produced equivalent effects in anxiety, depression, interference and pain intensity. On the contrary, technology evidenced favourable effects in terms of catastrophizing and disability. The proposed method revealed to be suitable, intelligible, easy to implement and low time and resources consuming. Further work is needed to evaluate the proposed system to follow up participants for longer periods of time which includes a complementary RCT encompassing patients with chronic pain symptoms. Finally, additional studies should be addressed to determine the economic effects not only to patients but also to the healthcare system

Exploring the use of routine healthcare data through process mining to inform the management of musculoskeletal diseases

Healthcare informatics can help address some of the challenges faced by both healthcare providers and patients. The medical domain is characterised by inherently complex and intricate issues, data can often be of poor quality and novel techniques are required. Process mining is a discipline that uses techniques to extract insights from event data, generated during the execution of processes. It has had good results in various branches of medical science but applications to musculoskeletal diseases remain largely unexplored. This research commenced with a review of the healthcare and technical literature and applied a variety of process mining techniques in order to investigate approaches to the healthcare plans of patients with musculoskeletal conditions. The analysis involved three datasets from: 1) a private hospital in Boston, US, where data was used to create disease trajectory models. Results suggest the method may be of interest to healthcare researchers, as it enables a more rapid modelling and visualisation; 2) a mobile healthcare application for patients receiving physiotherapy in Sheffield, UK, where data was used to identify possible indicators for health outcomes. After evaluation of the results, it was found that the indicators identified may be down to chance; and 3) the population of Wales to explore knee pain surgery pathways. Results suggest that process mining is an effective technique. This work demonstrates how routine healthcare data can be analysed using process mining techniques to provide insights that may benefit patients suffering with musculoskeletal conditions. This thesis explores how strict criteria for analysis can be performed. The work is intended to expand the breadth of process mining methods available to the data science community and has contributed by making recommendations for service utilisation within physiotherapy at Sheffield Hospital and helped to define a roadmap for a leading healthcare software company

Decision Support for Tailored Biopsychosocial Rehabilitation : In Non-specific Low Back Pain

Alaselkäkipu on maailman yleisin toimintakyvyn haittaa aiheuttava oire. Suurin osa alaselkäkivusta on niin sanottua epäspesifiä, eikä sille ole osoitettavissa aukottomasti patoanatomista taustaa. Kivun ja toimintakyvyn haitan kokemukseen ja kroonistumiseen liittyy laajasti erilaisia biopsykososiaalisia tekijöitä, joista osaan voidaan vaikuttaa kohdentamalla interventioita oikea-aikaisesti oikealle potilaalle, ja täten vähentää kivun pitkittymisen riskiä. Kipuun liittyviä biopsykososiaalisia tekijöitä ja niiden välisiä yhteyksiä voidaan ymmärtää paremmin maailman terveysjärjestö WHO:n kansainvälisen toimintakyvyn, toimintarajoitteiden ja terveyden luokituksen (ICF-viitekehys) avulla, joka kuvaa toimintakykyä laaja- alaisena biopsykososiaalisena kokonaisuutena. Tämän artikkeliväitöskirjan päätavoitteena oli kehittää menetelmiä tukemaan yksilöllisen biopsykososiaalisen kuntoutuksen suunnittelua ja toteutusta selkäkipupotilailla. Alatavoitteina oli tuottaa ajankohtaista tietoa tunnistetuista alaselkäkivun kroonistumisen riskitekijöistä, sekä löytää uusia menetelmiä biopsykososiaalisten tekijöiden tunnistamiseen ja näiden tekijöiden avulla sopivan intervention valintaan yksilöllisesti. Alaselkäkivun kroonistumisen riskitekijöistä tehtiin systemaattinen kirjallisuuskatsaus, jossa tutkittiin 25 tutkimuksen tuloksia. Tutkimusten tuli arvioida mahdollista riskitekijää ennen kivun kroonistumisen alkamista (3kk), jotta riskitekijää voitiin pitää ennakoivana tekijänä kroonistumiselle. Biopsykososiaalisten tekijöiden tunnistamiseen kehitettiin sovellus tekoälyalgoritmista, jonka tarkoituksena on tunnistaa toimintakykyyn liittyvää tietoa potilaskertomusteksteistä ICF-viitekehyksen mukaisesti. Sovelluksen tuloksia verrattiin alan asiantuntijan tekemään tunnistamiseen. Selkäpotilaan prosesseja perusterveydenhuollossa ja työterveydessä kehitettiin paremmin tunnistamaan kroonistumisen riskitekijöitä sekä valitsemaan sopivat interventiot yksilöllisesti. Prosessin kehittämisessä oli mukana moniammatillinen työryhmä perusterveydenhuollosta, työterveydestä sekä erikoissairaanhoidosta. Uusien menetelmien kehityksen tueksi kerättiin 93 kroonisen alaselkäkipuisen potilaan aineisto. Aineisto sisälsi vapaata tekstiä potilaskertomusteksteistä sekä numeerista dataa esitietolomakkeiden muodossa. Systemaattisen kirjallisuuskatsauksen mukaan yhteensä 45 erilaista riskitekijää on tunnistettavissa selkäkivun kroonistumisen riskitekijäksi. Riskitekijät jaoteltiin demografisiin ja sairaushistoriaan liittyviin tekijöihin, biomekaanisiin tekijöihin, oireiden ominaisuuksiin liittyviin tekijöihin, psykologisiin ja psykososiaalisiin tekijöihin, sekä elintapatekijöihin. Tunnistetut riskitekijät olivat yhdistettävissä ICF- viitekehyksen toimintakyvyn kuvauksiin, lukuun ottamatta demografisia ja sairaushistoriaan liittyviä tekijöitä. Kehitetty tekoälyalgoritmin sovellus tunnisti toimintakykytietoa potilaskertomusteksteistä 83.1 % herkkyydellä ja 99.84 % tarkkuudella verrattuna alan asiantuntijan tekemään tunnistukseen. Selkäpotilaan prosessin kehityksen tuotoksena syntyi vuokaavio, jonka avulla oikeat ammattilaiset ohjautuvat mukaan prosessiin potilaan tarpeiden mukaisesti, tietävät omat tehtävänsä, sekä pystyvät hyödyntämään paremmin moniammatillista ja monisektorista yhteisöä yksilöllisesti potilaan hyväksi. Tämä artikkeliväitöskirja luo uusia tutkimusmahdollisuuksia sekä selkäpotilaiden että toimintakykytiedon hyödyntämisen alueilla. Kirjallisuuskatsauksen tulokset auttavat kliinikoita paremmin ymmärtämään selkäkivun biospykososiaalista kokonaisuutta ja tutkijoita laajentamaan interventiotutkimusasetelmiaan. Tulevaisuudessa kuntoutusprosessista voidaan tehdä soveltuvuustutkimusta ennen laajempaa interventiota, ja tekoälyalgoritmin sovelluksen hyödyntämistä muille potilasryhmille ja kielille suunnitellaan.Low back pain is globally the most burdensome symptom causing disability. It is most commonly defined as non-specific, which means no pathoanatomical cause can be demonstrated as the cause. Different biopsychosocial factors are widely related to the experience and prolongation of pain and disability. Some of these factors can be affected by targeting timely interventions and decreasing the risk for pain chronicity. Pain related biopsychosocial factors and their connections can be understood more profoundly with the help of the International Classification of Functioning, Disability, and Health (ICF) framework developed by the World Health Organization (WHO), which describes disability from a wide biopsychosocial perspective. The main aim of this dissertation was to develop methods to support the decision-making in the tailored biopsychosocial rehabilitation of patients with non- specific LBP. The secondary aims were to produce a topical summary of the known biopsychosocial risk factors for low back pain chronicity, and to find methods to recognize those factors as well as support the assessment and execution of tailored interventions targeted to the individually recognized factors. A systematic literature review was compiled from the results of 25 different studies on the risk factors associated with low back pain chronicity. The studies had to evaluate the possible risk factor before the chronic phase of pain (3 months) in order to be regarded as a preceding factor for pain. To help the recognition of biopsychosocial factors at the individual level, an artificial intelligence algorithm application was developed that identifies disability information from electronic health records in accordance with the ICF framework. The results of the application were compared to the findings of a domain expert. The processes of patients with low back pain in primary and occupational health care were developed to more comprehensively assess possible risk factors and better tailor interventions to the individuals. A multidisciplinary team was formed from primary, occupational, and special health care professionals for the process design. For the purposes of developing new methods, a patient population of 93 patients with chronic low back pain were gathered. The data comprised free text from electronic health records and quantitative information from medical history forms. According to the systematic review, 45 different factors were identified as being associated with low back pain chronification. The factors were divided into demographical and medical history related factors, biomechanical factors, symptom related factors, psychological and psychosocial factors, and lifestyle factors. The factors were interrelated with the description of disability in the ICF framework, with the exception of the demographic and medical history related factors. The applied artificial intelligence algorithm was able to recognize disability information from the electronic health records with a sensitivity of 83.1% and specificity of 99.84% compared to the results of the domain expert. The rehabilitation process design was presented in a logic model that guides the needed professionals into the process according to the patients’ needs, clearly states the activities of the professionals, and comprehensively exploits a multidisciplinary community over sector boundaries. The findings of this dissertation open new research possibilities in the areas of low back pain and the exploitation of disability information. The results of the systematic review will help clinicians to better understand the biopsychosocial entity of low back pain more competently and researchers to extend their intervention study designs. In future, a feasibility study on the rehabilitation process should be executed before a larger intervention. The benefits of the artificial intelligence algorithm application are planned to be expanded to other patient groups and languages

Low Back Pain (LBP)

Low back pain (LBP) is a major public health problem, being the most commonly reported musculoskeletal disorder (MSD) and the leading cause of compromised quality of life and work absenteeism. Indeed, LBP is the leading worldwide cause of years lost to disability, and its burden is growing alongside the increasing and aging population. The etiology, pathogenesis, and occupational risk factors of LBP are still not fully understood. It is crucial to give a stronger focus to reducing the consequences of LBP, as well as preventing its onset. Primary prevention at the occupational level remains important for highly exposed groups. Therefore, it is essential to identify which treatment options and workplace-based intervention strategies are effective in increasing participation at work and encouraging early return-to-work to reduce the consequences of LBP. The present Special Issue offers a unique opportunity to update many of the recent advances and perspectives of this health problem. A number of topics will be covered in order to attract high-quality research papers, including the following major areas: prevalence and epidemiological data, etiology, prevention, assessment and treatment approaches, and health promotion strategies for LBP. We have received a wide range of submissions, including research on the physical, psychosocial, environmental, and occupational perspectives, also focused on workplace interventions

Cultural influences on low back pain - Extending the biopsychosocial model

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The present investigation examined the influence of cultural factors on Low Back Pain (LBP). Multiple regression techniques were used to determine the relative importance of clinical, social and psychological factors to LBP disability and cultural influences on these factors were then explored. The findings indicated that compared to clinical and social factors, LBP disability was most strongly associated with psychological factors (adjusted R2 change = 0.38, p<0.00), the most important of which was psychological distress. Clinical (adjusted R2 change = 0.11, p<0.00) or social (adjusted R2 change = 0.02, p=0.09) factors were only moderately or weakly associated with LBP disability. A series of hierarchical regression models examined the mediating role of cognitive Coping Strategies (Catastrophising & Praying and Hoping (Rosenstiel and Keefe (1983)) and Pain Control Beliefs (Control of Pain & Responsibility for management of Pain (Main and Waddell (1991)) on the relationship between LBP disability and distress. In support of the Cognitive Behavioural Mediational Model of chronic pain (Rudy and Turk, 1987), evidence was found to suggest that the relationship between LBP disability and distress was largely dependent upon Coping Strategies and Pain Control Beliefs. The findings also suggested that Pain Control Beliefs were largely dependent upon Coping strategies, although these relationships varied between specific Pain Control Beliefs and Coping Strategies. The study found evidence to suggest that certain self report questionnaires which are commonly used to assess cognitive factors associated with LBP may not have robust cross cultural reliabilities as measured by Cronbach's Alpha (Cronbach 1951) (Praying and Hoping (P&H) subscale of the Coping Strategies Questionnaire (CSQ) Rosensteil and Keefe 1983; Pain Responsibility (PR) subscale of the Pain Locus of Control (PLC) Main and Waddell 1991). The findings indicated that when used in their present form, these self reported questionnaires may provide inconsistent results with South Asian, African-born or Muslim LBP patients. The study provided evidence for the role of Cultural factors (self defined Ethnicity, Country of Birth and reported Religious Affiliation) on the experience of LBP. Although the relationship between cultural factors and LBP was generally weak (R2 change < 0.15), it appeared that South Asian, African-born and Muslim patients experienced LBP significantly worse than other LBP patients. The cultural group differences were strongest for the "passive" coping strategy "Praying and Hoping" (Rosensteil and Keefe 1983) (R2 change = 0.15, p < 0.001). The most apparent cultural differences were for Muslim patients who compared with all other Religious groups consistently reported the worst experience of LBP. Muslim LBP patients were clinically more disabled than either Christian (mean Roland and Morris Disability Questionnaire (RMDQ) difference (Roland and Morris, 1983) = 4.13) or other (mean RMDQ difference = 4.29) LBP patients. The statistical control of clinical variables in the regression models led to the conclusion that these groups of patients had a more "chronic" experience of LBP. Religious affiliation may help to identify LBP patients who present to secondary care with more chronic symptoms of LBP. Standardisation of self report questionnaire in these cultural groups may improve the precision of these findings. The present investigation was primarily descriptive in that reasons for cultural differences were not empirically examined. However the study findings suggest potentially fruitful areas for further investigation particularly that work on the meaning of "Praying" as a coping strategy and on its relationship with LBP disability for non-Christian groups would appear warranted

Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject

Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject

Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe

NOTIFICATION !!!

All the content of this special edition is retrieved from the conference proceedings published by the European Scientific Institute, ESI. http://eujournal.org/index.php/esj/pages/view/books The European Scientific Journal, ESJ, after approval from the publisher re publishes the papers in a Special edition

NOTIFICATION !!!

All the content of this special edition is retrieved from the conference proceedings published by the European Scientific Institute, ESI. http://eujournal.org/index.php/esj/pages/view/books The European Scientific Journal, ESJ, after approval from the publisher re publishes the papers in a Special edition