Relations between clinical decision support and knowledge management by rt3463df

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									   Relations between clinical
decision support and knowledge
          management


      Andrew Grant MD PhD
What is clinical decision
       support ?
            Aim of this talk
• To provoke a discussion that contrasts
  notions of knowledge management with
  current research and perspectives on
  clinical decision making
• The hypothesis is that clinical decision
  making has aquired in health informatics
  research a bias that is slowing down and
  possibly inhibiting effective support to
  clinical knowledge management
Knowledge management


          System
Input                           Output


        Learning and decision
        making for system
        continuity
    Knowledge Management

        System
             Team
                     Person

Input
                                         Output


                 Learning and decision
                 making for system
                 continuity
Clinical decision support definitions
•   computer software employing a knowledge base designed for use by a
    clinician involved in patient care, as a direct aid to clinical decision making

•   a set of knowledge-based tools that are fully integrated with both the
    clinician workflow components of a computerized patient record, and a
    repository of complete and accurate data

•   providing clinicians or patients with clinical knowledge and patient-related
    information, intelligently filtered and presented at appropriate times, to
    enhance patient care




Clinical Decision Support in Electronic Prescribing: Recommendations and an Action Plan

Report of the Joint Clinical Decision Support Workgroup
JONATHAN M. TEICH, MD, PHD, JEROME A. OSHEROFF, MD, ERIC A. PIFER, MD, DEAN
   F.SITTIG, PHD, ROBERT A. JENDERS, MD, MS, THE CDS EXPERT REVIEW PANEL

J Am Med Inform Assoc. 2005;12:365–376.
Scenario of point of care DS
Patient X arrives for her office visit. The nurse brings her back
to the examination room and puts a preliminary diagnosis of
„„sinus infection‟‟ into the computer. Dr. Smith arrives to see
her a few minutes later. After examining her and confirming
the preliminary diagnosis, Dr. Smith clicks a button to reveal
an evidence-based recommendation on the best antibiotic
options for this condition. The computer returns a list of three
antibiotic choices; next to each choice is an icon indicating
whether that medication is covered on patient X‟s plan. The
first antibiotic is off-formulary, so Dr. Smith selects the second
antibiotic. The computer checks the patient‟s other active
medications, and an alert window pops up indicating that the drug
may interact with one of her diabetes drugs, resulting in vomiting
(in fact, it was this interaction, not the patient‟s age or kidney
function, which was responsible for patient X‟s vomiting
in the first scenario; in that scenario, the physician never did
make this connection).
 Automating Complex
 Guidelines for Chronic
 Disease: Lessons Learned

 J Am Med Inform Assoc. 2003;10:154–165.


• Reports on creating, maintaining, and navigating
  computer-based clinical algorithms integrated with
  our electronic medical record.
• As computers become standard tools of clinical
  practice, computer-based guidelines increasingly
  can be integrated into routine workflow, delivering
  “just-in-time” information pertinent to the current
  clinical situation.
• National cholesterol educational guideline
• In general difficult, most difficulty with workflow
       Clinical decision making
• The right information to the right people at
  the right point in the clinical workflow


 J Am Med Inform Assoc.
 (Kawamoto and Lobach)
 2007;14:146 –155.
 Proposal for Fulfilling Strategic
 Objectives of the U.S. Roadmap
 for National Action on Decision
 Support through a Service
 oriented Architecture
 Leveraging HL7 Services
           Goal of Road Map
• Optimal, usable and effective clinical decision
  support that is widely available to providers,
  patients, and individuals where and when they
  need it to make health care decisions.”
• It encompasses a variety of tools and
  interventions such as computerized alerts and
  reminders, clinical guidelines, order sets, patient
  data reports and dashboards, documentation
  templates, diagnostic support, and clinical
  workflow tools.
 HL7 based module (Kawamoto paper)

From a functional perspective, a DSS can be conceptually
understood as the guardian of one or more modules of
medical knowledge, wherein each DSS knowledge module
(KM) is capable of utilizing patient data to arrive at machine-
interpretable conclusions regarding the patient under
evaluation. The scope of a typical DSS KM is the assessment
of a single patient in a specified topic area. The topic area
may be narrow (e.g., the need for a glycated hemoglobin test
for a patient with diabetes) or broad (e.g., the existence of
contraindications to any medications prescribed or about to
be prescribed for a patient).
                     Pragmatic DS?
• Issues of how to plan and manage care optimally across the
  inpatient– outpatient continuum represent another unsolved
  challenge to current CDS applications within CPOE systems.

• An important topic discussed at the meeting was the optimal method
  for providing patients with computer-storededucational information
  about their prescriptions.




  A Pragmatic Approach to Implementing Best Practices for Clinical Decision Support
  Systems in Computerized Provider Order Entry Systems
  Bates and Gross
  J Am Med Inform Assoc. 2007;14:25–28.
         KM and chronic disease
• Components closely correlated with positive experimental results
  (quality outcomes and health care costs) were connection to an
  electronic medical record, computerized prompts, population
  management (including reports and feedback), specialized decision
  support, electronic scheduling, and personal health records. Barriers
  identified included costs, data privacy and security concerns, and
  failure to consider workflow.

Informatics Systems to Promote Improved Care for Chronic Illness: A
   Literature Review

Dorr et al

J Am Med Inform Assoc. 2007;14:156 –163.
From Dorr et al
Results of technological, process, and clinical outcomes measures
in 50 experimental studies of information
technology used for care of chronic disease.
    Knowledge Management

        System
             Team
                     Person

Input
                                         Output


                 Learning and decision
                 making for system
                 continuity
    Knowledge management question
•   D + D + D … = best outcome
•   DS + DS +DS = best outcome
•   DS has many forms
•   We make recommendations but we do not have
    a corpus of study – yet - that looks at overall
    knowledge management = best outcome rather
    than huge resources on part of the problem –
    often the hardest part of the problem –
    adversion to the low hanging fruit.
Discussion

								
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