Data-Driven Personalization of a Physiotherapy Care Pathway: Case Study of Posture Scanning (Preprint)

2020 ◽  
Author(s):  
Olli Korhonen ◽  
Karin Väyrynen ◽  
Tino Krautwald ◽  
Glenn Bilby ◽  
Hedwig Anna Theresia Broers ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Information System ◽  
Health Care Professionals ◽  
Digital Data ◽  
Digital Tools ◽  
Data Driven ◽  
Care Process ◽  
The Impact

BACKGROUND Advanced sensor, measurement, and analytics technologies are enabling entirely new ways to deliver health care. The increased availability of digital data can be used for data-driven personalization of care. Data-driven personalization can complement expert-driven personalization by providing support for decision making or even by automating some parts of decision making in relation to the care process. OBJECTIVE The aim of this study was to analyze how digital data acquired from posture scanning can enhance physiotherapy services and enable more personalized delivery of physiotherapy. METHODS A case study was conducted with a company that designed a posture scan recording system (PSRS), which is an information system that can digitally record, measure, and report human movement for use in physiotherapy. Data were collected through interviews with different stakeholders, such as health care professionals, health care users, and the information system provider, and were analyzed thematically. RESULTS Based on the results of our thematic analysis, we propose three different types of support that posture scanning data can provide to enhance and enable more personalized delivery of physiotherapy: 1) modeling the condition, in which the posture scanning data are used to detect and understand the health care user’s condition and the root cause of the possible pain; 2) visualization for shared understanding, in which the posture scanning data are used to provide information to the health care user and involve them in more collaborative decision-making regarding their care; and 3) evaluating the impact of the intervention, in which the posture scanning data are used to evaluate the care progress and impact of the intervention. CONCLUSIONS The adoption of digital tools in physiotherapy has remained low. Physiotherapy has also lacked digital tools and means to inform and involve the health care user in their care in a person-centered manner. In this study, we gathered insights from different stakeholders to provide understanding of how the availability of digital posture scanning data can enhance and enable personalized physiotherapy services.

scholarly journals Data-Driven Personalization of a Physiotherapy Care Pathway: Case Study of Posture Scanning

10.2196/18508 ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. e18508
Author(s):  
Olli Korhonen ◽  
Karin Väyrynen ◽  
Tino Krautwald ◽  
Glenn Bilby ◽  
Hedwig Anna Theresia Broers ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Information System ◽  
Health Care Professionals ◽  
Digital Data ◽  
Digital Tools ◽  
Data Driven ◽  
Care Process ◽  
The Impact

Background Advanced sensor, measurement, and analytics technologies are enabling entirely new ways to deliver health care. The increased availability of digital data can be used for data-driven personalization of care. Data-driven personalization can complement expert-driven personalization by providing support for decision making or even by automating some parts of decision making in relation to the care process. Objective The aim of this study was to analyze how digital data acquired from posture scanning can enhance physiotherapy services and enable more personalized delivery of physiotherapy. Methods A case study was conducted with a company that designed a posture scan recording system (PSRS), which is an information system that can digitally record, measure, and report human movement for use in physiotherapy. Data were collected through interviews with different stakeholders, such as health care professionals, health care users, and the information system provider, and were analyzed thematically. Results Based on the results of our thematic analysis, we propose three different types of support that posture scanning data can provide to enhance and enable more personalized delivery of physiotherapy: 1) modeling the condition, in which the posture scanning data are used to detect and understand the health care user’s condition and the root cause of the possible pain; 2) visualization for shared understanding, in which the posture scanning data are used to provide information to the health care user and involve them in more collaborative decision-making regarding their care; and 3) evaluating the impact of the intervention, in which the posture scanning data are used to evaluate the care progress and impact of the intervention. Conclusions The adoption of digital tools in physiotherapy has remained low. Physiotherapy has also lacked digital tools and means to inform and involve the health care user in their care in a person-centered manner. In this study, we gathered insights from different stakeholders to provide understanding of how the availability of digital posture scanning data can enhance and enable personalized physiotherapy services.

Data-driven Personalization of Physiotherapy Care Pathway: Case Posture Scanning (Preprint)

2020 ◽  
Author(s):  
Olli Korhonen ◽  
Karin Väyrynen ◽  
Tino Krautwald ◽  
Glenn Bilby ◽  
Anna Broers ◽  
...  
Keyword(s):  
Decision Making ◽  
Care Pathway ◽  
Human Movement ◽  
Digital Data ◽  
Data Driven ◽  
Care Process ◽  
Root Cause ◽  
Care Models ◽  
The Impact

BACKGROUND Advanced sensor, measurement and analytics technologies enable entirely new ways to deliver care. Increased availability of digital data can be used for data-driven personalization of care. Data-driven personalization can complement expert-driven personalization by providing support for decision making, or even automating some parts of decision making in relation to the care process. OBJECTIVE The aim of this study is to analyze how digital data acquired from posture scanning can enhance physiotherapy and enable more personalized delivery of physiotherapy. METHODS A Case study is conducted with a company that has designed a Posture Scan Recording System (PSRS), which is an Information System (IS) that can record, measure and report human movement digitally to be used in physiotherapy. Interviews are used to explore the viewpoints of different stakeholders involved in physiotherapy. The data is analyzed thematically. RESULTS As the result of our thematic analysis, we identified three different support types the posture scanning can provide to enable more personalized delivery of physiotherapy. The types are: (1) Modeling the condition, which is about the use of posture scanning data for detecting and understanding the healthcare user’s condition and the root cause of the possible pain. (2) Visualization for a shared understanding, which is about the use of posture scanning data to inform and involve the healthcare user in more collaborative decision-making regarding care. (3) Evaluating the impact of the intervention, which is about the use of posture scanning data to evaluate the care progress and impact of the intervention. CONCLUSIONS Current care models in healthcare emphasize the importance to put the healthcare user at the center of the care. However, physiotherapy has lacked data driven solutions to inform and involve the healthcare user in care in a person-centered manner. The present study analyzes how posture scanning can enhance physiotherapy and presents three different types of support that posture scanning can provide for data-driven personalization of physiotherapy.

scholarly journals Interventions visant l’application des connaissances en pratique pharmaceutique

2018 ◽  
Vol 71 (3) ◽  
Author(s):  
Apolline Adé ◽  
Denis Lebel ◽  
Jean-François Bussières
Keyword(s):  
Health Care ◽  
Knowledge Translation ◽  
Pharmaceutical Care ◽  
Health Care Professionals ◽  
Data Extraction ◽  
Pharmacy Practice ◽  
Geographic Location ◽  
Care Process ◽  
Post Intervention ◽  
The Impact

<p><strong>RÉSUMÉ</strong></p><p><strong>Contexte : </strong>La littérature scientifique portant sur l’application des connaissances (AC) est vaste et complexe et les publications sur les interventions dans le domaine de la santé concernent surtout les médecins et les infirmières. Pour autant que les auteurs sachent, il n’existe pas de revue documentaire s’intéressant à l’AC et à ses retombées en pharmacie.</p><p><strong>Objectif : </strong>Décrire le profil des interventions visant l’AC en pratique pharmaceutique.</p><p><strong>Source des données : </strong>La plateforme Knowledge Translation+ (KT+) a été utilisée pour en extraire des articles publiés entre janvier 2010 et décembre 2016 à l’aide du terme « pharmacist ».</p><p><strong>Sélection des études et extraction des données : </strong>Les principales variables retenues pour établir le profil des interventions visant l’AC en pratique pharmaceutique étaient le protocole de recherche de l’étude, le lieu de l’intervention, les rôles du pharmacien, les types de connaissances transférées et les retombées. Le codage de la nature des interventions pharmaceutiques reposait sur la classification du site Impact Pharmacie.</p><p><strong>Synthèse des données : </strong>Au total, 114 articles ont été sélectionnés : revues systématiques (<em>n </em>= 25, 22 %), études contrôlées à répartition aléatoire (<em>n </em>= 45, 40 %) études rétrospectives (<em>n </em>= 21, 18 %), études prospectives (<em>n </em>= 13, 11 %), études pré-post intervention (<em>n </em>= 10, 9 %). Les études se déroulaient surtout en établissement de santé (74 %). La majorité des interventions ciblaient des étapes de soins pharmaceutiques et la realization de séances d’éducation thérapeutique et de conseils prodigués aux patients. Il existait un manque de rigueur méthodologique lors de la conception des interventions et quant à leur description.</p><p><strong>Conclusion : </strong>Le pharmacien est le principal producteur de connaissances et oriente les interventions visant leur application vers les patients ou les professionnels de santé. Celles-ci concernaient principalement la démarche de soins pharmaceutiques et le travail en interdisciplinarité. La mise en place d’une formation initiale et continue, la gestion de l’information et la désignation d’un pharmacien responsable de l’AC au sein de chaque département de pharmacie pourraient encourager le développement de cette mise en application des connaissances. Ce concept peut être utile pour soutenir la création d’un modèle de pratique pharmaceutique cohérent.</p><p><strong>ABSTRACT</strong></p><p><strong>Background: </strong>The scientific literature on knowledge translation (KT) is vast and complex, and most publications concerning health care interventions involve physicians and nurses. To the authors’ knowledge, there have been no literature reviews on KT and its impact on pharmacy practice.</p><p><strong>Objective: </strong>To determine the profile of interventions relating to KT in pharmacy practice.</p><p><strong>Data Sources: </strong>The term “pharmacist” was used to search the web platform Knowledge Translation+ (KT+) to identify pertinent articles published between January 2010 and December 2016.</p><p><strong>Study Selection and Data Extraction: </strong>The main variables analyzed to determine the profile of KT interventions in pharmacy practice were the study’s research protocol, the geographic location of the intervention, pharmacist roles, the types of knowledge transferred, and impacts of the interventions. The nature of pharmacy interventions was coded according to the classification on the Impact Pharmacie website.</p><p><strong>Data Synthesis: </strong>A total of 114 articles were selected: systematic reviews (<em>n </em>= 25, 22%), randomized controlled trials (<em>n </em>= 45, 40%), retrospective studies (<em>n </em>= 21, 18%), prospective studies (<em>n </em>= 13, 11%), and pre-post intervention studies (<em>n </em>= 10, 9%). Most of the studies (74%) were conducted in a health care institution. The majority of interventions targeted pharmaceutical care steps, therapeutic educational sessions, and patient education. There was a lack of methodological rigour during the development of interventions and in their description.</p><p><strong>Conclusion: </strong>Pharmacists are key generators of knowledge, and their interventions related to KT are directed toward patients or other health care professionals. These interventions have mainly addressed the pharmaceutical care process and interdisciplinary work. The implementation of initial and continuing education, the management of information, and the designation of a pharmacist responsible for KT in each pharmacy department might promote the development of such KT. This concept might in turn support the design of a coherent pharmacy practice model.</p>

scholarly journals Kaizen–Kata, a Problem-Solving Approach to Public Service Health Care in Mexico. A Multiple-Case Study

2020 ◽  
Vol 17 (9) ◽  
pp. 3297 ◽  
Author(s):  
Manuel F. Suárez-Barraza ◽  
José A. Miguel-Davila
Keyword(s):  
Health Care ◽  
Public Hospitals ◽  
Care Process ◽  
Customer Complaints ◽  
Study Approach ◽  
Operational Problem ◽  
Multiple Case ◽  
The Impact ◽  
Practical Implications

Purpose: Mexico’s public hospitals are experiencing major operational problems which seriously affect the care of Mexican citizens. Some hospitals have initiated efforts to apply the Kaizen philosophy to improve this situation. Therefore, the purpose of this article is to analyze the methodological impact of Kaizen–Kata implementation in Mexican public hospitals that have tried to solve operational problems using this improvement approach. Design/Methodology/Approach: The service organization implemented Kaizen–Kata methodology in order to improve one operational problem-process in health care. A case-study approach was used in this research in order to understand the effects of the Kaizen–Kata methodology in solving problems in their operational procedures. Findings: Six specific drivers were identified when applying the Kaizen–Kata methodology. Furthermore, the impact on the levels of implementation of the Kaizen–Kata methodology in each of the improvement teams studied was also identified. Research Limitations: The main limitation of the research is that only three case-studies are presented thus it is not possible to generalize its results. Practical Implications (Where Possible): Other public hospitals can use this specific example as a working guide to solve the operational problems of health systems. Originality/Value: A methodology of continuous improvement in manufacturing was imported from the industry sector for application in an operational health care process. The Kaizen–Kata methodology contributed significantly to improving issues involving delays, customer complaints, process reworks and extra-cost, among other effects of operational problems.

scholarly journals Data Storytelling with Dashboard: Accelerating Understanding Through Data Visualization in Financial Technology Company Case Study

Jurnal METRIS ◽  
2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Ferdian Suprata
Keyword(s):  
Decision Making ◽  
Data Visualization ◽  
Rapid Development ◽  
Data Driven ◽  
Decision Making Process ◽  
Business Practices ◽  
Context Data ◽  
The Impact ◽  
Financial Technology

In the rapid development many organisation rely on context data to support as well as to assist its decision making process. Consequently, Business Intelligence (BI), Dashboard, and Data Visualization emerged as primary tools in early 1990s as a way to help practitioners, data analyst, and data scientist to present context data into an actionable information for decision making process. However, despite its robust and powerful tools, recent study done by Kaggle’s survey in 2017 resulted that in the last five years, many companies were not able to create effective data-driven dashboard due to complex dataset, poor dashboard design, and insufficient storytelling. Hence, understanding of who is going to use dashboard, choosing which data and metrics to visualize in the right context, knowing how to convey information, driving engagement, and persuading audiences are essential in current business practices. This study is aimed to help practitioners to understand the impact of effective dashboard can have on decision making process, to design leveraging dashboard, and to present the dashboard in storytelling. A literature study is performed to gather all relevant information resulted in guidelines for dashboard creator. Case study in financial technology company is applied to experiment and to test the guidelines for assisting dashboard creator to present data-driven insight to the stakeholder.

scholarly journals Evaluating the Impact of the Grading and Assessment of Predictive Tools Framework on Clinicians and Health Care Professionals’ Decisions in Selecting Clinical Predictive Tools: Randomized Controlled Trial

10.2196/15770 ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. e15770
Author(s):  
Mohamed Khalifa ◽  
Farah Magrabi ◽  
Blanca Gallego Luxan
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Health Care Professionals ◽  
Completion Time ◽  
Decisional Conflict ◽  
Task Completion ◽  
Evidence Based ◽  
Task Completion Time ◽  
Predictive Tools ◽  
The Impact

Background While selecting predictive tools for implementation in clinical practice or for recommendation in clinical guidelines, clinicians and health care professionals are challenged with an overwhelming number of tools. Many of these tools have never been implemented or evaluated for comparative effectiveness. To overcome this challenge, the authors developed and validated an evidence-based framework for grading and assessment of predictive tools (the GRASP framework). This framework was based on the critical appraisal of the published evidence on such tools. Objective The aim of the study was to examine the impact of using the GRASP framework on clinicians’ and health care professionals’ decisions in selecting clinical predictive tools. Methods A controlled experiment was conducted through a web-based survey. Participants were randomized to either review the derivation publications, such as studies describing the development of the predictive tools, on common traumatic brain injury predictive tools (control group) or to review an evidence-based summary, where each tool had been graded and assessed using the GRASP framework (intervention group). Participants in both groups were asked to select the best tool based on the greatest validation or implementation. A wide group of international clinicians and health care professionals were invited to participate in the survey. Task completion time, rate of correct decisions, rate of objective versus subjective decisions, and level of decisional conflict were measured. Results We received a total of 194 valid responses. In comparison with not using GRASP, using the framework significantly increased correct decisions by 64%, from 53.7% to 88.1% (88.1/53.7=1.64; t193=8.53; P<.001); increased objective decision making by 32%, from 62% (3.11/5) to 82% (4.10/5; t189=9.24; P<.001); decreased subjective decision making based on guessing by 20%, from 49% (2.48/5) to 39% (1.98/5; t188=−5.47; P<.001); and decreased prior knowledge or experience by 8%, from 71% (3.55/5) to 65% (3.27/5; t187=−2.99; P=.003). Using GRASP significantly decreased decisional conflict and increased the confidence and satisfaction of participants with their decisions by 11%, from 71% (3.55/5) to 79% (3.96/5; t188=4.27; P<.001), and by 13%, from 70% (3.54/5) to 79% (3.99/5; t188=4.89; P<.001), respectively. Using GRASP decreased the task completion time, on the 90th percentile, by 52%, from 12.4 to 6.4 min (t193=−0.87; P=.38). The average System Usability Scale of the GRASP framework was very good: 72.5% and 88% (108/122) of the participants found the GRASP useful. Conclusions Using GRASP has positively supported and significantly improved evidence-based decision making. It has increased the accuracy and efficiency of selecting predictive tools. GRASP is not meant to be prescriptive; it represents a high-level approach and an effective, evidence-based, and comprehensive yet simple and feasible method to evaluate, compare, and select clinical predictive tools.

A Review into E-Health Services and Therapies

2013 ◽  
pp. 267-279
Author(s):  
Alice Good ◽  
Arunasalam Sambhanthan
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Mental Illness ◽  
Health Care Providers ◽  
Health Care Professionals ◽  
Patient Records ◽  
Care Providers ◽  
Health It ◽  
The Impact

E-health has expanded hugely over the last fifteen years and continues to evolve, providing greater benefits for patients, health care professionals, and providers alike. The technologies that support these systems have become increasingly more sophisticated and have progressed significantly from standard databases, used for patient records, to highly advanced Virtual Reality (VR) systems for the treatment of complex mental health illnesses. The scope of this chapter is to initially explore e-health, particularly in relation to technologies supporting the treatment and management of wellbeing in mental health. It then provides a case study of how technology in e-health can lend itself to an application that could support and maintain the wellbeing of people with a severe mental illness. The case study uses Borderline Personality Disorder as an example, but could be applicable in many other areas, including depression, anxiety, addiction, and PTSD. This type of application demonstrates how e-health can empower the individuals using it but also potentially reduce the impact upon health care providers and services.

scholarly journals Impact of Corporate Governance on the Effectiveness of Accounting Information System in Jordanian Industrial Companies

2017 ◽  
Vol 10 (10) ◽  
pp. 1
Author(s):  
Feras Izzat Oqlah Kasasbeh
Keyword(s):  
Decision Making ◽  
Information System ◽  
Corporate Governance ◽  
Performance Evaluation ◽  
Accounting Information ◽  
Ease Of Use ◽  
Data Driven ◽  
Accounting Information System ◽  
Industrial Companies ◽  
The Impact

In this study, the impact of corporate governance factors on the effectiveness of accounting information system has been investigated considering Jordanian Industrial Companies. Authors considered the influence of corporate governance factors such as organisational vision, and goal translation, data-driven decision making, expertise and experience of governing committee, KPI based performance evaluation and effective collaboration between leaders and departments on the effectiveness of accounting information system. The effectiveness of accounting information system has been measured by the ease of use, security, storage, it's usability for delivery and decision making. The secondary data was collected using a questionnaire from 30 accounting firms in Jordan. Specialised software called Statistical Package for the Social Sciences (SPSS) has been used to analyse the data gathered and draw conclusions. Authors found that AIS is an effective tool for decision making and performance evaluation when management adopts the data-driven approach. However, for an effective AIS, it must be governed by subject matter experts who have expertise and experience is financial and accounting methodologies. Authors emphasised on the role of the leadership team in creating a clear vision and ASMART goals so that the AIS system can be aligned and help the departments to deliver on targets. It was observed that effective communication, collaboration among the leaders and departments significantly influence the effectiveness of AIS structure and it's ability to deliver results.

scholarly journals Evaluating the Impact of the Grading and Assessment of Predictive Tools Framework on Clinicians and Health Care Professionals’ Decisions in Selecting Clinical Predictive Tools: Randomized Controlled Trial (Preprint)

2019 ◽  
Author(s):  
Mohamed Khalifa ◽  
Farah Magrabi ◽  
Blanca Gallego Luxan
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Health Care Professionals ◽  
Completion Time ◽  
Decisional Conflict ◽  
Task Completion ◽  
Evidence Based ◽  
Task Completion Time ◽  
Predictive Tools ◽  
The Impact

BACKGROUND While selecting predictive tools for implementation in clinical practice or for recommendation in clinical guidelines, clinicians and health care professionals are challenged with an overwhelming number of tools. Many of these tools have never been implemented or evaluated for comparative effectiveness. To overcome this challenge, the authors developed and validated an evidence-based framework for grading and assessment of predictive tools (the GRASP framework). This framework was based on the critical appraisal of the published evidence on such tools. OBJECTIVE The aim of the study was to examine the impact of using the GRASP framework on clinicians’ and health care professionals’ decisions in selecting clinical predictive tools. METHODS A controlled experiment was conducted through a web-based survey. Participants were randomized to either review the derivation publications, such as studies describing the development of the predictive tools, on common traumatic brain injury predictive tools (control group) or to review an evidence-based summary, where each tool had been graded and assessed using the GRASP framework (intervention group). Participants in both groups were asked to select the best tool based on the greatest validation or implementation. A wide group of international clinicians and health care professionals were invited to participate in the survey. Task completion time, rate of correct decisions, rate of objective versus subjective decisions, and level of decisional conflict were measured. RESULTS We received a total of 194 valid responses. In comparison with not using GRASP, using the framework significantly increased correct decisions by 64%, from 53.7% to 88.1% (88.1/53.7=1.64; <i>t<sub>193</sub></i>=8.53; <i>P</i>&lt;.001); increased objective decision making by 32%, from 62% (3.11/5) to 82% (4.10/5; <i>t<sub>189</sub></i>=9.24; <i>P</i>&lt;.001); decreased subjective decision making based on guessing by 20%, from 49% (2.48/5) to 39% (1.98/5; <i>t<sub>188</sub></i>=−5.47; <i>P</i>&lt;.001); and decreased prior knowledge or experience by 8%, from 71% (3.55/5) to 65% (3.27/5; <i>t<sub>187</sub></i>=−2.99; <i>P</i>=.003). Using GRASP significantly decreased decisional conflict and increased the confidence and satisfaction of participants with their decisions by 11%, from 71% (3.55/5) to 79% (3.96/5; <i>t<sub>188</sub></i>=4.27; <i>P</i>&lt;.001), and by 13%, from 70% (3.54/5) to 79% (3.99/5; <i>t<sub>188</sub></i>=4.89; <i>P</i>&lt;.001), respectively. Using GRASP decreased the task completion time, on the 90th percentile, by 52%, from 12.4 to 6.4 min (<i>t<sub>193</sub></i>=−0.87; <i>P</i>=.38). The average System Usability Scale of the GRASP framework was very good: 72.5% and 88% (108/122) of the participants found the GRASP useful. CONCLUSIONS Using GRASP has positively supported and significantly improved evidence-based decision making. It has increased the accuracy and efficiency of selecting predictive tools. GRASP is not meant to be prescriptive; it represents a high-level approach and an effective, evidence-based, and comprehensive yet simple and feasible method to evaluate, compare, and select clinical predictive tools.

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