Computational Technology for Effective Health Care Immediate Steps and Strategic Directions (2009) / Chapter Skim
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5 Research Challenges
5 Research Challenges
Pages 36-58
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From page 36... ...
Indeed, interdisciplinary work will be necessary to go beyond incremental improvement of existing health care IT or the automation of traditional paper-based workflows. Systematic development of the health care ITrelated research agenda is beyond the scope of this brief study, but the committee offers a framework for organizing such an agenda.
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From page 37... ...
. As an illustration of how a solution to a major problem in health care might be decomposed into a technology-related research agenda, consider that most clinicians spend a significant amount of time in documenting the care provided to a patient. One challenge for health care IT would be The committee noted this point in its site visits.
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From page 38... ...
, which would increase the continuity and richness of information available for the clinician, as well as being helpful in dealing with expected future burdens on patients to manage their own care outside traditional health care organizations; this research agenda would fit into Quadrant 2. On the other hand, a system to provide a patient or caregivers with interactive explanations of a disease, particularized by the of time they spend filling out paperwork and documenting patient care has increased more than fourfold over the past 25 years.
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From page 39... ...
. Specific advanced work on advanced ontologies and reasoning in the medical domain, modeling of the human body and the virtual patient, interpretation of medical information to different communities, approaches to learning and improving data quality, aggregation of patient health care information into a trustworthy database with explicit representation of uncertainty [C4O17, C5O23]
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From page 40... ...
Rather, they squeeze all cognitive support for the clinician through the lens of health care transactions and the related raw data, without an underlying representation of a conceptual model for the patient showing how data fit together and which data are important or unimportant. There is little or no cognitive support for clinicians to reason about their "virtual patient." So the health care IT systems force clinicians to a transactional view of the raw data.
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From page 41... ...
The availability of these models would free clinicians from having to scan raw data, and thus they would have a much easier time defining, testing, and exploring their own working theories. What links the raw data to the abstract models might be called medical logic -- that is, computer-based tools examine raw data relevant to a specific patient and suggest their clinical implications given the context of the models and abstractions.
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From page 42... ...
Again, raw research data about biological and medical phenomena are at the base. Clinical research transactional systems add to and use raw data during the process of executing or running clinical research protocols.
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From page 43... ...
The committee's vision for patient-centered cognitive support is not wholly new. Indeed, development of IT-based tools that examine raw data relevant to a specific patient and suggest their clinical implications was the focus of a great deal of medical expert system work a number Box 5.2 Research Problems Categorized by Quadrant for Patient-Centered Cognitive Support • Quadrant 1 (General -- applied efforts)
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From page 44... ...
Obviously, different interfaces would be required (e.g., interfaces that translate medical jargon into lay language) -- but the underlying tools for medical data integration, modeling, and abstraction designed for patient-centered cognitive support are likely to be the same in any system for lay end users (i.e., patients)
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From page 45... ...
Thus, a sensible approach to modeling subsystems in a specific patient is to appropriately parameterize a generic model of those subsystems. But finding appropriate parameterizations for any given model and coupling the different models and the data to drive them pose significant intellectual challenges.
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From page 46... ...
The actual determination of patient treatment will remain in the hands and minds of the clinician. But the feedback that can be provided by bringing data collections, metabolic models, and their processing to an interactive care setting is essential to extract value out of the many technology investments that are in process or being planned.
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From page 47... ...
. Coding and deployment of existing health care models • Quadrant 3 (General -- advanced efforts)
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From page 48... ...
Sheridan, Humans and Automation: System Design and Research Issues, Human Factors and Ergonomics Society, Santa Monica, Calif. (Wiley Series in Systems Engineering and Management)
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From page 49... ...
5.2.3 Data Sharing and Collaboration The data relevant to health care are highly heterogeneous, and the types and quantity of data evolve rapidly. In addition to patient-record information that exists in multiple forms, health care requires data about drugs and diagnoses, including data from signals captured by biomedical devices, voice recordings, and data captured as codes.
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From page 50... ...
Today, the challenge for data integration, by which is meant systems that enable data owners to share data and collaborate in flexible ways without having to store all the data in a single repository or have them all conform to a common schema, is understood from the systems and logical perspectives. One approach is to aggregate patient health care information into a common data repository [C4O14]
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From page 51... ...
Currently, the common architecture for such systems envisages a single mediated schema and mappings to that schema.16 While this architecture has the advantage that the data can still remain in the sources and be managed there, the creation of the mediated schema is still a centralized effort. Systems are needed that enable data owners to share data in a more ad hoc fashion and extend the coverage of data sharing as they see fit.
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From page 52... ...
, a personal health record contains an individual's entire medical history, that is, from all interactions with all health care providers (and self-provided care as well) and is under the control of the patient.19 For information to be easily accessible to the patient, data supplied by different providers -- likely each with their own local health care IT systems generating data in idiosyncratic formats and with different meanings -- must be integrated in a way that they appear to have common semantics.
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From page 53... ...
. Extracting useful medical information from textual notes is therefore an important problem that calls for computer science expertise in text processing, natural language processing, and statistical text-mining techniques as well as medical expertise to understand the concepts and ideas to which the information refers.
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From page 54... ...
Epidemiological research and phase IV drug testing (postapproval) both depend on the aggregation of select medical data from large numbers of individual records, even if individual identities need not be associated with these data.
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From page 55... ...
While technically not data management per se, the data models, data federation technologies, and security and privacy approaches must all support the wide variety of usage that is expected. What an emergency room physician needs is very different from what is required by a physician reviewing the data with an eye toward wellness, a point understood by at least some in the biomedical informatics community since the 1980s.22 Visualization tools that help users integrate and manage data pulled from multiple sources might also be considered part of a sophisticated user interface, and coupled with analytic techniques may help to solve problems that are not possible to solve using analytic techniques alone.
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From page 56... ...
. Applications for handling inaccu rate data to improve input to health care data models, better coding techniques for information 5.2.5 Automated Full Capture of Physician-Patient Interactions As noted above, care providers spend a great deal of time in documenting their interactions with patients.
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From page 57... ...
Box 5.7 describes some of the technical research challenges for automated full capture of physician-patient interactions organized by quadrant. Box 5.7 Research Problems Categorized by Quadrant for Automated Full Capture of Physician-Patient Interactions • Quadrant 1 (General -- applied efforts)
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From page 58... ...
In the absence of believable assurances in full-capture clinical interactions that such sensitive information will not be recorded, patients may well be less forthcoming or complete in their accounting of their medical histories and circumstances. Such problems will have to be addressed before any such system will be widely acceptable.
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