Relations between clinical decision support and knowledge management

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Relations between clinical decision support and
knowledge management

• Andrew Grant MD PhD

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What is clinical decision support ?
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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

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Knowledge management
System
Output
Input
Learning and decision making for system continuity
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Knowledge Management

System
Team
Person
Input
Output
Learning and decision making for system continuity
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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

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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 Xs plan. The first antibiotic
is off-formulary, so Dr. Smith selects the
second antibiotic. The computer checks the
patients 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 patients age or
kidney function, which was responsible for
patient Xs vomiting in the first scenario in
that scenario, the physician never did make this
connection).
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Automating Complex Guidelines for
Chronic Disease Lessons Learned J Am Med
Inform Assoc. 200310154165.

• 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

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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)
200714146 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
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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.

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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).

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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. 2007142528.

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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. 200714156 163.

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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.
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Knowledge Management

System
Team
Person
Input
Output
Learning and decision making for system continuity
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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.

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Discussion