Medicine 2.0

Not available

PESCA: Developing an Open Source Platform to Bring eHealth to Latin America and the Caribbean [5 Cr2 1330 Lorca]View SlideShare presentation or Upload your own. (tags: medicine20 20)

Semantic web technology and open source, 'free range' API

development provide opportunities to build consumer-centric

services beyond current Health 2.0 strata. But the roadmap for true consumer-centric care does not end with semantic web growth -

rather it begins there.

The authors detail a new planning model, termed 'neXthealth,'

giving stakeholders concrete tools to define current positioning and create a map to future goal realization (using existing service lines and development

initiatives). We focus on four critical factors needed to realize complete consumer-centric care (aka 'nexthealth'): content + community + commerce + coherence.

The authors plot the roadmap to consumer-centric care at the intersection of two rapidly evolving developmental axes: joining patients and

professionals in the healthcare conversation, and combining brick-and-mortar real world systems with virtual online services. A case study is used to illustrate the ideal result: completely integrated care delivery where consumers may access healthcare goods and services at will, online or offline.

American Well, a Health 2.0 company included in a case study in the presentation, recently validated the nexthealth theory, partnering with Microsoft and the State of Hawaii to deliver the 'online healthcare marketplace' paid for by insurance providers.

A live, web-based Flash demo of the neXthealth model will allow Medicine 2.0 attendees to participate in a crowd-sourcing experiment, plotting points on the roadmap to 'nexthealth' and connecting the dots to determine 'what's next' for consumer-centric care, according to the Congress.

The authors present not a commercial, one-size-fits all solution to consumer-centric care evolution, but rather a 'killer planning app' - a practical, graphical, open-source tool for executive teams to determine 'what's next' for each organization. In the spirit of crowd-sourcing healthcare evolution, the model will be available free online after launch.

Nexthealth presentation at Medicine 2.0View SlideShare presentation or Upload your own. (tags:

Introduction: Despite the proven benefits of algorithmic medicine in healthcare and the plethora of implemented medical algorithms solving Medical Computational Problems (MCPs) which are available on the web [1], their usage is limited in everyday clinical practice. This is mainly due to poor organisation of MCP information, difficulties in MCP search and the missing parameters in the description of medical cases, making their management by a single algorithm rather impossible. In this paper a comprehensive approach to the usage of semantic web technologies (web-3.0) is presented, aiming to facilitate the utilisation of computerized algorithmic medicine in clinical practice. In particular, there are 3 main goals achieved, namely, the semantic descriptions of MCPs, the efficient search of MCPs, and the dynamic semantic composition of a sequence of algorithms managing a certain medical case.

Methods: For the Semantic representation of MCP knowledge the MCP OWL Ontology describes the MCPs as a triad:

(Medical Problem-Algorithmic Solution-Implementation)

Three interacting ontological schemes that refer to each part of the above triad were created.

For efficient search, the method used is an adaptation of the classical Vector Space Model (VSM) in MCP Ontology, via which the similarity between MCP semantic descriptions and the user questions is calculated. The weights of MCP vectors are created utilizing the UMLS Ontology [2].

In order to dynamically composite a pathway of algorithms for managing a certain medical case SWLR semantic rules are used. These rules automatically associate different algorithms and construct a Finite State Machine (FSM) of algorithms. The description of a certain medical case via the MCP Ontology by a user constitutes the "language" for that case. If this language is recognised by an FSM of algorithms with the final algorithm that manages the case as the initial state and the algorithm of initiation by the user as the final state, then the sequence of these algorithms can manage the medical case.

Results: A modular and expandable, Web-Based Knowledge System (KS) for the MCPs was developed. Preliminary results from its usage showed a more efficient search of MCPs, as well as, a proper management of medical cases through algorithmic pathways proposed by the system which were in agreement with international medical guidelines whenever these were available.

Discussion: The developed methods of display and management of MCP knowledge along with the further utilization of the proposed KS are expected to enhance the dissemination and use of algorithmic solutions in everyday medical practice. Simultaneously, medical research and high quality medical education are bound to be benefited at a considerable level. For the dissemination of algorithmic medicine we believe that the future is the combination of web-2.0 and web-3.0 technologies and the transformation of our system to a semantic wiki of MCPs.

[1] Iyengar MS, Svirbely JR: Computer-based medical algorithms: overview and experiences. Technol. Health Care 2005, 13(5):403-405

[2] Bratsas C, Koutkias V, Kaimakamis E, Bamidis PD, Pangalos G, Maglaveras N: KnowBaSICS-M: An ontology-based system for semantic management of medical problems and computerised algorithmic solutions. Comput. Meth. Progr. Biomed 2007, 88(1):39-51

Background: Developing Web-based electronic medical record (EMR) systems is a fundamental step in enabling resource-constrained healthcare environments to benefit from Web 2.0 applications and services. Towards this goal, we have developed and implemented a Web-based EMR in Malawi, Africa. The EMR, built using Ruby on Rails and AJAX, features touchscreen workstations that collect and validate data from the clinician in real-time at the point of care. The system is deployed in high patient burden HIV/AIDS clinics that have frequent staff turnover. This context makes two aspects of system usability - learnability and efficiency of use[1] - important design considerations.

Objective: To determine how efficiently novice users complete tasks using the touchscreen interface of the EMR.

Methods: To predict how quickly a user could be expected to perform the EMR tasks, we used an established technique for predicting skilled performance time called the Keystroke-Level-Model (KLM)[2]. This technique models the low-level perceptual motor operators required to complete a specified task using a given interface. KLM calculations require the application of a significant amount of cognitive modeling information. However, a free software application called CogTool[3] has been developed to support cognitive modeling for KLM. In the first phase of our research, we selected thirty-one routinely performed EMR tasks and conducted a KLM analysis of the tasks using CogTool. The interfaces and user actions for each task were prepared within CogTool using a storyboard approach. CogTool analyzed the storyboards to predict performance time of a skilled user (i.e., one who performs without error or hestitation). In the second phase, we recruited four volunteers who had not previously used the EMR to complete the thirty-one tasks for three mock patient encounters (resulting in 372 task observations). We collected the task performance data by modifying the EMR to collect timestamp data for all interface events. In the third phase we compared the preliminary novice performance data with the CogTool predictions.

Results: Of the 372 EMR tasks, 77% (286) were performed without errors by the novices (errors defined as any deviation from the CogTool storyboard). Of these error-free tasks, the performance time for 68% (194) was faster than the CogTool prediction. We observed two unexpected user behaviors not captured by the initial CogTool models: (1) two-handed touchscreen interface use, and (2) prolonged dialogue during patient interaction (e.g. spelling verifications).

Conclusions: Although preliminary in nature, our initial data suggests that novices can sometimes achieve the efficiency level of a skilled user of the EMR. We found CogTool to be an effective software application that permitted us to rapidly develop predictions of skilled performance time. The ability of most novices to often outperform the KLM calculations was likely related to a documented weakness in CogTool regarding the insertion of "think steps" for all touch typing. In our case, for onscreen typing tasks, CogTool inserted "think steps" before each button press. However, upon review it was not possible to identify suggested inclusion criteria for all of these "think steps" [4]. We are currently revising the CogTool models before collecting additional empirical data.

References

1. Nielsen J. Usability Engineering. 1st edition. New York: Morgan Kaufman; 1993.

2. Card SK, Moran TP, Newell A. The Keystroke-Level Model for User Performance Time with Interactive Systems. Commun ACM. 1980 Jul;23(7):396-410.

3. John BE, et al. (2006). The CogTool Project. http://www.cs.cmu.edu/~bej/cogtool/index.html. Archived at: http://www.webcitation.org/5Xayftaav

4. Kieras D. (2001). Using the Keystroke-Level Model to Estimate Execution Times. ftp://www.eecs.umich.edu/people/kieras/GOMS/KLM.pdf

Background: This work is part of an ongoing feasibility study aimed to design and deploy a PHR system for the citizens of the Province of Trento (NE Italy). The system is intended both to support storing health information important to patients and to improve relationships and communication between patients and their health care providers. With regard to the first topic, input data forms and navigation are crucial elements that would be used consistently in order not to compromise the use of the system. That's why considerable effort was dedicated to guide and support the management of health information in the system design phase. We adopted a citizen-centered approach within an iterative design-evaluation process. This work is supported by the Department of Health and the Department of Research and Innovation of the Autonomous Province of Trento (NE Italy).

Objective: Our objective was to explore the effectiveness of the traditional web forms vs. wizard step-by-step structure and to gather information about problems that users may encounter when interacting with such interfaces. We focused on testing usability and user experience of two user interfaces within an interaction design approach [1]. The two prototypes were designed and developed to support citizens to maintain drugs' information themselves.

Methods: An early evaluation by health researchers working in FBK was performed. In a second time interaction design methods were used for comparing the two user interfaces. We adopted a usability testing based on the think-aloud technique for observing users while surfing the system and filling the forms, post-task questionnaire based on a Likert-type scale for assessing user satisfaction, and debriefing semi-structure interview for exploring subjective user ex-perience behind what was previously observed [2]. According to Nielsen [3], eight participants were recruited among the administrative personnel of FBK. The inclusion criterion was the skill in using the web. The used task scenarios were stories of common drug prescription.

Results: The first evaluation identified mainly navigation problems from screen to screen. A brainstorming with the health researchers allows us to reorganize internal navigation according to the critiques. The usability testing was carried out on the refined user interfaces. Think-aloud reports were transcribed in a world processing file and a content analysis was performed using coding categories described in literature about human-computer-interaction [2]. The most frequent problems were related to the selection of malaises and diagnoses from the related lists. These lists were difficult to use since they were based on large medical terms organized in apparatus. The other issues were about navigation: the button for adding a new prescription in the main page need to be more highlighted and the tab label for editing personal evaluation should be reworded for clarity.

Conclusions: Repeated cycles of design-testing-measure-redesign allow pointing out wrong design assumption that could cause usability problems later. No one system prevailed against the other and the incidental preference coming from the debriefing interview was founded on subjective impressions. It could be interested to repeat this test after people have used the wizard interface for a period of time.

References:

1. Preece, J. Roger, Y. and Sharp, H. Interaction design: beyond human-computer interaction. New York, John Wiley & Sons, Inc.

2. Kushniruk, Andre W. and Patel Vimla L. Cognitive and usability engineering methods for the evaluation of clinical information systems. Journal of Biomedical Informatics, 37, 56-76, 2004

3. Nielsen, J. Usability engineering. Academic Press, San Diego, CA, 1993

Objectives

There is still much to understand about the benefits of Patient Portals and patient access to their electronic health record. Specifically usability best practices for their design and development and insight into what patients really want to see in a Patient Portal.

The InfoWell Patient Portal is a tool designed to assist patients in the management of a chronic condition by providing education, and improving access, support, and navigation through the continuum of care. The objective of the usability component of the InfoWell Patient Portal project is to engage patients throughout the design and development phase to ensure the final end product meets user needs in terms of content and tools, and is easy to use in order to encourage user adoption.

Context/Situation

The InfoWell Patient Portal represents the largest comprehensive personalized health information website in the province that spans the continuum of care. The SIMS Partnership, the information management and technology (IM/IT) group shared between thirteen health care organizations in the Greater Toronto Area, has led its development.

The InfoWell Patient Portal was developed in response to the demand for greater access to health information for patients. Breast cancer, diabetes, and chronic kidney disease patients were chosen in particular due to the perceived benefits of being more educated, informed, and proactive, enabling self-management and ultimately resulting in improved health outcomes, for these particular groups.

Method

The InfoWell Patient Portal utilized a user-centred design (UCD) methodology to gather requirements, insight, and feedback from patients. This provided health care and IT professionals, and researchers an enlightened perspective as to what patients really want. The requirements gathering process involved an ethnographic approach of using patient interviews and surveys. Patients helped to improve content organization, navigation, menus, and taxonomy of the website through a "Card Sorting Method". Several stages of iterative user testing were conducted to determine the ease of use of the website and to collect suggestions on future tools and functionality for the portal.

Benefits

Involving end-users in the design and development of the InfoWell Patient Portal help to ensure that 1) The content and tools are useful and meet the needs of patients, 2) The website is intuitive and easy-to-use in terms of design and navigation, thereby increasing the likelihood of widespread adoption by end-users.

Results

Results of usability testing were incorporated into the iterative design cycle for the Patient Portal and resulted in continual improvement in terms of ease of use with regards to navigation, content groupings and labels, with potential for scalability of disease groups and additional partner organizations. In particular, the card sorting exercise significantly improved the content organization of the website to better correspond to patient expectations.

While it is important to engage patients in the requirements gathering phase, it has proven essential to directly observe patients' interaction with the website and tools through iterative usability testing in order identify any disconnects between the goals of health care organizations for the portal, and those of the patient.

InfoWell Patient Portal: A Case of Patient-Centred Design [05 Cr2 1100 Chan]

The interoperability of Electronic Medical Records is a worldwide problem difficult to solve and with lots of resources involved and working on it. There are some standards to interchange information that are being implemented and good advances have been made.

But the reality is that the clinical information is poorly shared in regions and countries and even less between countries. That means that a citizen that moves between countries has no guarantee that, if something happens and medical service in requiered, the clinicians have the right information to treat the patient.

At a european level the problem is adding the fact that the european citizens have the right to have health services at any european contry. The multilingual problem, poor interoperability implementation technology makes the solution difficult to achieve. For that reason the EU is funding projects through the FP7 that pretend to achieve the "Health without barriers".

In the context os the Innovative European Program (FEDER 2000-2006) a Balearic Islands (Spain) consortium has defined and implemented a project that pretends to provide a solution for Electronic Patient Record Interoperability between european countries. Such a project has been evaluated in the Medical Tourism environment, dinamic sector happy to provide high level service to tourists.

The implemented solution (Virtual Health Platform) consists on a basic interoperable platform with this characteristics:

- A personal health record with the basic and resumen relevant clinical information from the patient (diagnosis, medication, allergies) but codified with SNOMED a worldwide multilanguage medical standard terminology.

- A virtual asyncronous teleconsultation solution that allows referral physician to ask for a second opinion or to referer a patient. It allows to add interconsultation information plus images and videos in Dicom Format (also for interoperability reasons)

- The interoperable platform allows to send and receive HL7 messages

- The platform is integrated with a USB Devices and allows to store the medical data into a secure USB bracelete.

The platform allows to cover the workflow:

1. the patient that is going to travel can store some critical data on the Virtual Health Platform. If travelling because of a medical tourism process can also perform a teleconsultation and send some presurgery information or images.

2. The source health center received the information and can manage the teleconsultation and schedule the patient.

3. To treat the patient the physicians can access to the personal health record and get the information into a local language (SNOMED performs the translation).

4. If there is an emergency or connection problem the information can be reviewed trought the usb bracelete.

5. when the patient has already been treated and has to go back home (other country) the information is stored in the personal health record platform.

The Virtual Health Platform acts as Medical Record Gateway allowing access to information between countries, translating the clinical content and integration with other information systems.

As a result of the project there are two outpus:

- the virtual health platform

- a paralel study of medical tourism business cases and requirements

The project is one more step in the interoperability problem that europe is trying to reach. To focus in a very dinamic sector like tourism has been good to achieve concrete results fast. The standard terminology SNOMED has helped to get translation and to better organise the medical record. Standards are necessary.

MyOpenCare enables users to manage the creation and sharing of treatment plans and/or approaches in combination with the system's multimedia content. Once the "thread" has been created, the user will then be able to edit the content, i.e. with the inclusion or deletion of text or image.

The user will manage his or her content according to a graph-based structure. This information will then branch out according to the user's choices.

The creation of personal H-Books is a feature available to every user. It is designed for medical professionals interested in contributing content in exchange for increased visibility.Using MyOpenCare health professionals will be able to manage the creation and distribution of treatment and/or formative paths, which will be paths created combining the multimedia content in the system, aimed towards the production of different threads. On the nodes and edges of the path users will be able to include descriptive texts or short in-depth examinations. The user will travel along graph-based structures: on certain nodes the path will fork into two or more edges depending on the users' choices (i.e.. slightly different symptoms lead to different pathologies, or there can be multiple suggested cures) MyOpenCare: Multicontent treatment paths to share medical knowledge and experience [5 Cr2 900 Narduzzi]View SlideShare presentation or Upload your own. (tags: medicine20 20)

Healthcare workflows are complex and highly variable. Healthcare workflow execution can be affected by any participant in a process, including clinicians, the patient, and the patient's family, as well as environmental factors such as clinician, staff, facility and equipment availability, and patient clinical status. Attempts to document healthcare workflows result in highly detailed descriptions (often incomplete) with many possible pathways to achieve the goals. A variety of graphical methods and languages have emerged to support the documentation of workflow and computer-based execution. However, only a few solutions exist that enable workflow to address the full complexity and variability of healthcare processes. We have re-conceptualized workflow and developed a new workflow representation and execution framework based on software engineering, inference engine, and database concepts, which has freed workflow representation from the constraints of past methods. We have reported our work on context-aware workflow in a separate paper.

Although much has been done on the representation of workflow in business settings, the representation of workflow in highly dynamic settings is still a focus of research.

Complex dynamic environments are characteristic of healthcare. They typically involve considerable human interaction resulting in a high degree of variability in scenario outcome. Healthcare settings have many decision makers, kinds of decisions, events and a multitude of reactive, subsidiary workflows that often require a quick revision of the course of action (See Table 1). Operational and treatment protocols attempt to regularize workflow, but the needs of care, the great variety of situations and individuals, the exigencies of the moment (such as equipment failure), and the nature of human beings frustrate attempts at regularization, often resulting in protocols being labeled as "rigid" and hence being abandoned. While event sequences in healthcare processes may abide by loose constraints, they are largely non-deterministic. Therefore, it is difficult, if not impossible, to prescribe fully healthcare workflow. Instead, workflow must be dynamic, self-adapting and evolving at execution-time to match the dynamicity of the environment.

Traditional workflow technology by its very static nature supports a finite set of scenarios. In fact, traditional workflow is understood to support, at best, the union of atomic workflow patterns described by van der Aalst1. Available workflow platforms that support these patterns are often incomplete, unsatisfactory, or even non-existent. In fact, no single commercial product supports all listed patterns.1

We have developed a new way of representing healthcare processes that is able to address human-machine interaction and complexity. It converges service oriented architectures concepts with decision support techniques.