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Clinical Care Algorithms: The Good, The Bad, and The Ugly R. Matthew Sailors, PhD UTH Medical School Department of Surgery.

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Presentation on theme: "Clinical Care Algorithms: The Good, The Bad, and The Ugly R. Matthew Sailors, PhD UTH Medical School Department of Surgery."— Presentation transcript:

1 Clinical Care Algorithms: The Good, The Bad, and The Ugly R. Matthew Sailors, PhD UTH Medical School Department of Surgery

2 Overview Modern World / Why Use AlgorithmsModern World / Why Use Algorithms Types of / Uses for AlgorithmsTypes of / Uses for Algorithms Clinical Care AlgorithmsClinical Care Algorithms –Types, Use, Automation Good, Bad, and Ugly AlgorithmsGood, Bad, and Ugly Algorithms Algorithm Classification & ExamplesAlgorithm Classification & Examples Evaluating AlgorithmsEvaluating Algorithms Writing Good AlgorithmsWriting Good Algorithms

3 Modern World Society is making ever greater demands on our healthcare delivery system and, in turn, on the healthcare providers.Society is making ever greater demands on our healthcare delivery system and, in turn, on the healthcare providers. It is imperative that the workflow of healthcare delivery be altered if quality of care and access to healthcare are to be maintained or improved.It is imperative that the workflow of healthcare delivery be altered if quality of care and access to healthcare are to be maintained or improved. One of the many ways of accomplishing this alteration is the automation of clinical algorithmsOne of the many ways of accomplishing this alteration is the automation of clinical algorithms

4 Why Do We Use Algorithms? Share or extend expertiseShare or extend expertise –Training –Disseminate processes / procedures Reduce variabilityReduce variability Standardize careStandardize care –Improve overall quality of service –Serve as baseline for new strategies Medico-Legal reasonsMedico-Legal reasons

5 Types of Algorithms ClinicalClinical AdministrativeAdministrative FinancialFinancial Time-basedTime-based Data-basedData-based State-basedState-based Evidence-basedEvidence-based HeuristicsHeuristics Model-basedModel-based WAGWAG

6 Clinical Care Algorithm Specifically clinical (patient care)Specifically clinical (patient care) NOTNOT –Financial –Administrative –Resource allocation Neutral, high-level termNeutral, high-level term –No biases or preconceptions

7 Clinical Care Algorithm Description of a process intended to guide sequential clinical (therapeutic or palliative) interventions.Description of a process intended to guide sequential clinical (therapeutic or palliative) interventions. Usually single patient-centricUsually single patient-centric Time or data-drivenTime or data-driven Evidence-based, models, heuristic, WAGEvidence-based, models, heuristic, WAG

8 Clinical Care Algorithm Protocol (I) Guideline Care Path(way) Protocol (II) Procedure Practice Care Plan Knowledge Base This is not a hierarchy diagram, just a terminology

9 Use of Clinical Algorithms Serve only as guidesServe only as guides Only good inside the design envelopeOnly good inside the design envelope Professional clinical judgment overrideProfessional clinical judgment override Handle routine situationsHandle routine situations Allows experts to concentrate on difficult casesAllows experts to concentrate on difficult cases

10 Automation of Clinical Algorithms guide (but not directly provide) therapiesguide (but not directly provide) therapies manage information flowmanage information flow assist in diagnosis and treatment planningassist in diagnosis and treatment planning provide a safety net for the patient for the times when the inevitable human / technical / system errors occur.provide a safety net for the patient for the times when the inevitable human / technical / system errors occur.

11 Automation of Clinical Algorithms Computers have no native intelligenceComputers have no native intelligence Algorithms must be as detailed as possibleAlgorithms must be as detailed as possible –streamline the implementation process –computerized algorithm must represent what we want to dowhat we want to do not just want we told the computer to do.not just want we told the computer to do.

12 Good Algorithms -- Required 1.Concise description Content and intent of the algorithm Content and intent of the algorithm Patient groups to which it can and cannot be safely applied Patient groups to which it can and cannot be safely applied 2.Structured, repeatable algorithm textual or graphical formtextual or graphical form 3.Fully specified concepts (e.g., high nasogastric tube output is defined as nasogastric tube output > 1200 cc/12 hr)(e.g., high nasogastric tube output is defined as nasogastric tube output > 1200 cc/12 hr)

13 Good Algorithms -- Required 4.Fully specified decision points E.g., PaO 2 >= 60 and PaO 2 = 60 and PaO 2 <= 80 5.Fully specified action steps, Therapeutic interventions suggested by the algorithmTherapeutic interventions suggested by the algorithm Calculations to be performedCalculations to be performed Patient-specific recommendationsPatient-specific recommendations

14 Good Algorithms -- Desired 1.Formal expression language Describe the decision and action stepsDescribe the decision and action steps Delineated scope and purposeDelineated scope and purpose Define entry and exclusion criteriaDefine entry and exclusion criteria 2.Formalism to describe the flow of the algorithm from one state to the next 3.Encoded links DidacticsDidactics Reference materialsReference materials On-line resourcesOn-line resources

15 Bad Algorithms Full of vagaries (weasel words)Full of vagaries (weasel words) –optimize patients respiratory status Fail to adequately describe the decisions and actions that are required to care for the patientFail to adequately describe the decisions and actions that are required to care for the patient Important entry or exclusion criteria and conditional values missingImportant entry or exclusion criteria and conditional values missing Concepts poorly definedConcepts poorly defined –high NG output

16 Ugly Algorithms Unstructured / poorly structured algorithmUnstructured / poorly structured algorithm Algorithm follows no sequential orderAlgorithm follows no sequential order Important entry or exclusion criteria appear at the end of the algorithm or in footnotesImportant entry or exclusion criteria appear at the end of the algorithm or in footnotes No standard formalism used to describe algorithmNo standard formalism used to describe algorithm

17 Algorithm Classifications Proposal to HL7 Clinical Decision Support Technical CommitteeProposal to HL7 Clinical Decision Support Technical Committee 5 levels5 levels –0 – 4 –Increasing detail with higher classification #

18 Class 0 Often encoded only in textual form.Often encoded only in textual form. Full of vagariesFull of vagaries Fail to adequately describe the decisions and actions that are required to care for the patientFail to adequately describe the decisions and actions that are required to care for the patient Actual algorithmActual algorithm –often unstructured or poorly structured –may follow no sequential order Important entry or exclusion criteria and conditional values often appear at the end of the algorithm or in footnotes, if at all.Important entry or exclusion criteria and conditional values often appear at the end of the algorithm or in footnotes, if at all.

19 Class 1 Improve upon Class 0 algorithmsImprove upon Class 0 algorithms All of the entry and exclusion criteria specified at the beginning of the description.All of the entry and exclusion criteria specified at the beginning of the description. Algorithms steps are coarsely structured and are arranged in a temporal or logical progression.Algorithms steps are coarsely structured and are arranged in a temporal or logical progression. Algorithms are usually still represented in textual form, but may also be represented in other forms.Algorithms are usually still represented in textual form, but may also be represented in other forms.

20 Class 2 Improve upon Class 1 algorithmsImprove upon Class 1 algorithms Explicitly defining all thresholds and decisions within the algorithms.Explicitly defining all thresholds and decisions within the algorithms. Some action steps are also defined.Some action steps are also defined.

21 Class 3 Distinguished from Class 2 algorithms byDistinguished from Class 2 algorithms by –Representation format –Presence of definitions for all steps Represented using structured formalismRepresented using structured formalism –flow diagrams –formal, structured text (pseudo-code)

22 Class 4 Include all of the details necessary for a non- expert or computer to negotiate the algorithm in a reliable and repeatable manner.Include all of the details necessary for a non- expert or computer to negotiate the algorithm in a reliable and repeatable manner. All logical and clinical concepts are explicitly spelled out and are described in terms of patient-specific values.All logical and clinical concepts are explicitly spelled out and are described in terms of patient-specific values. Most often disseminated as either flow diagrams or encoded using a knowledge base formalism.Most often disseminated as either flow diagrams or encoded using a knowledge base formalism.

23 Intermediate Classifications A given clinical algorithm may fulfill all of the requirements for a given classification and part of the requirements for a higher classificationA given clinical algorithm may fulfill all of the requirements for a given classification and part of the requirements for a higher classification May be necessary to classify the algorithm as a intermediate value.May be necessary to classify the algorithm as a intermediate value. Separate the two levels with a forward slash (/), such as, Class 3 / 4.Separate the two levels with a forward slash (/), such as, Class 3 / 4. This notation, while less precise than a decimal or true fractional notation, has the advantage of being simple and efficient.This notation, while less precise than a decimal or true fractional notation, has the advantage of being simple and efficient.

24 Classification Overview

25 Class 0 AED Algorithm 1.ABCs, start CPR, apply AED 2.Push analyze, if indicated defibrillate at 200 J 3.If no conversion, defibrillate at 300 J 4.If no conversion, defibrillate at 360 J 5.Check pulse, if present, support airway 6.If no pulse, CPR for one minute 7.Check pulse, if absent press analyze 8.If advised, defibrillate up to three times at 360 J 9.Repeat steps 2 thru 8 until arrival at medical facility

26 Class 0 AED Algorithm (cont.) Notes: A.Single rescuer with AED should verify unresponsiveness, open airway give two breaths, and check pulse. If full arrest, AED should be attached and proceed with algorithm. B.Pulse checks are not required after shocks 1, 2, 4, and 5 unless no shock indicated is displayed C.Only to be used on pulse-less, non-pediatric patients D.If advanced personnel are present, they can use the manual mode E.Advanced personnel can enter the above algorithm at any point and continue with appropriate advanced protocol

27 Class 1 AED Algorithm Notes: A.If advanced personnel can use the manual mode B.Advanced personnel can enter the algorithm at any point and continue with appropriate advanced protocol

28 Class 1 AED Algorithm (cont.) 1.If patient has pulse or is a pediatric patient then do not continue with algorithm. Instead use alternate algorithms for VF 2.Single rescuer with AED should verify unresponsiveness, open airway give two breaths, and check pulse. If full arrest, AED should be attached and proceed with algorithm. If multiple rescuers then ABCs, start CPR, apply AED 3.Push analyze, if indicated defibrillate at 200 J 4.If no shock indicated then check pulse 5.If no conversion, defibrillate at 300 J 6.If no shock indicated then check pulse 7.If no conversion, defibrillate at 360 J 8.Check pulse, if present, support airway 9.If no pulse, CPR for one minute 10.Check pulse, if absent press analyze 11.If advised, defibrillate up to three times at 360 J 12.Repeat steps 3 thru 11 until arrival at medical facility

29 Class 2 AED Algorithm Notes: A.If advanced personnel can use the manual mode B.Advanced personnel can enter the algorithm at any point and continue with appropriate advanced protocol

30 Class 2 AED Algorithm (cont.) 1.If patient has pulse or patient age <= 8 years then do not continue with algorithm. Instead use alternate algorithms for VF 2.Single rescuer with AED should verify unresponsiveness, open airway give two breaths, and check pulse. If full arrest, AED should be attached and proceed with algorithm. If multiple rescuers then ABCs, start CPR, apply AED 3.Push analyze, if AED displays shock indicated, defibrillate at 200 J 4.If no shock indicated then check pulse 5.If AED displays shock indicated (no conversion), defibrillate at 300 J 6.If no shock indicated then check pulse 7.If AED displays shock indicated (no conversion), defibrillate at 360 J 8.Check pulse, if present, support airway 9.If no pulse, CPR for one minute 10.Check pulse, if absent press analyze 11.If AED displays shock indicated, defibrillate up to three times at 360 J 12.Repeat steps 3 thru 11 until arrival at medical facility

31 Class 3 AED Algorithm

32 Class 4 AED Algorithm (Part 1)

33 Class 4 AED Algorithm (Part 2)

34 Critically Evaluating Algorithms Identify target audienceIdentify target audience –Experts –Novices –Related fields Identify intended useIdentify intended use –Authors –Yours Look for well-defined decision and action targets (no weasel words)Look for well-defined decision and action targets (no weasel words) Look for individual-based outputsLook for individual-based outputs

35 Critically Evaluating Algorithms Look for well-defined decision and action targets (no weasel words)Look for well-defined decision and action targets (no weasel words) Look for individual-based outputsLook for individual-based outputs Use the table to help classify algorithmsUse the table to help classify algorithms

36 Writing Good Algorithms Start with general and work to specificStart with general and work to specific –Iterative process Avoid Gotchas -- later slideAvoid Gotchas -- later slide Think like a child (or engineer)Think like a child (or engineer) –Simple, discrete, decisions Keep it simple at firstKeep it simple at first Add complexity as neededAdd complexity as needed

37 Tips Simple binary (yes / no) decisions involving 1 or 2 data pointsSimple binary (yes / no) decisions involving 1 or 2 data points –X < 25 –X > 36 or Y 36 or Y <= 18 String together lots of small steps rather than having one or two big onesString together lots of small steps rather than having one or two big ones Nest complexities awayNest complexities away

38 Gotchas Over generalizationsOver generalizations Weasel WordsWeasel Words Being Too AmbitiousBeing Too Ambitious Not Understanding Problem DomainNot Understanding Problem Domain Trying to Solve Wrong ProblemTrying to Solve Wrong Problem Trying to Use Wrong TechniquesTrying to Use Wrong Techniques

39 Summary Algorithms – many uses: for good, for badAlgorithms – many uses: for good, for bad Good, bad, and ugly algorithmsGood, bad, and ugly algorithms Good algorithms share expertiseGood algorithms share expertise Algorithm classifications: 0 (low) – 4 (high)Algorithm classifications: 0 (low) – 4 (high) Critically evaluate algorithmsCritically evaluate algorithms Writing good algorithms is about attention to detailsWriting good algorithms is about attention to details


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