Development of process control methodology for tracking the quality and safety of pain, agitation, and sedation management in critical care units

Timothy S. Walsh (Lead / Corresponding author), Kalliopi Kydonaki, Robert J. Lee, Kirsty Everingham, Jean Antonelli, Ronald T. Harkness, Stephen Cole, Tara Quasim, James Ruddy, Marcia McDougall, Alan Davidson, John Rutherford, Jonathan Richards, Christopher J. Weir, for the Development and Evaluation of Strategies to Improve Sedation practice in inTensive care Study Investigators

    Research output: Contribution to journalArticle

    5 Citations (Scopus)

    Abstract

    OBJECTIVE: To develop sedation, pain, and agitation quality measures using process control methodology and evaluate their properties in clinical practice.

    DESIGN: A Sedation Quality Assessment Tool was developed and validated to capture data for 12-hour periods of nursing care. Domains included pain/discomfort and sedation-agitation behaviors; sedative, analgesic, and neuromuscular blocking drug administration; ventilation status; and conditions potentially justifying deep sedation. Predefined sedation-related adverse events were recorded daily. Using an iterative process, algorithms were developed to describe the proportion of care periods with poor limb relaxation, poor ventilator synchronization, unnecessary deep sedation, agitation, and an overall optimum sedation metric. Proportion charts described processes over time (2 monthly intervals) for each ICU. The numbers of patients treated between sedation-related adverse events were described with G charts. Automated algorithms generated charts for 12 months of sequential data. Mean values for each process were calculated, and variation within and between ICUs explored qualitatively.

    SETTING: Eight Scottish ICUs over a 12-month period.

    PATIENTS: Mechanically ventilated patients.

    INTERVENTIONS: None.

    MEASUREMENTS AND MAIN RESULTS: The Sedation Quality Assessment Tool agitation-sedation domains correlated with the Richmond Sedation Agitation Scale score (Spearman ρ = 0.75) and were reliable in clinician-clinician (weighted kappa; κ = 0.66) and clinician-researcher (κ = 0.82) comparisons. The limb movement domain had fair correlation with Behavioral Pain Scale (ρ = 0.24) and was reliable in clinician-clinician (κ = 0.58) and clinician-researcher (κ = 0.45) comparisons. Ventilator synchronization correlated with Behavioral Pain Scale (ρ = 0.54), and reliability in clinician-clinician (κ = 0.29) and clinician-researcher (κ = 0.42) comparisons was fair-moderate. Eight hundred twenty-five patients were enrolled (range, 59-235 across ICUs), providing 12,385 care periods for evaluation (range 655-3,481 across ICUs). The mean proportion of care periods with each quality metric varied between ICUs: excessive sedation 12-38%; agitation 4-17%; poor relaxation 13-21%; poor ventilator synchronization 8-17%; and overall optimum sedation 45-70%. Mean adverse event intervals ranged from 1.5 to 10.3 patients treated. The quality measures appeared relatively stable during the observation period.

    CONCLUSIONS: Process control methodology can be used to simultaneously monitor multiple aspects of pain-sedation-agitation management within ICUs. Variation within and between ICUs could be used as triggers to explore practice variation, improve quality, and monitor this over time.

    Original languageEnglish
    Pages (from-to)564-574
    Number of pages11
    JournalCritical Care Medicine
    Volume44
    Issue number3
    DOIs
    Publication statusPublished - 1 Mar 2016

    Fingerprint

    Critical Care
    Safety
    Pain
    Mechanical Ventilators
    Deep Sedation
    Research Personnel
    Extremities
    Process Assessment (Health Care)
    Nursing Care
    Hypnotics and Sedatives
    Ventilation
    Analgesics
    Observation
    Pharmaceutical Preparations

    Keywords

    • Aged
    • Analgesics
    • Conscious sedation
    • Critical care
    • Female
    • Humans
    • Hypnotics and sedatives
    • Intensive care units
    • Male
    • Middle aged
    • Monitoring, Physiologic
    • Pain management
    • Process assessment (Health Care)
    • Prospective studies
    • Psychomotor agitation
    • Quality improvement
    • Reproducibility of results
    • Respiration, Artificial
    • Scotland
    • Journal article
    • Research support, Non-U.S. Gov't

    Cite this

    Walsh, T. S., Kydonaki, K., Lee, R. J., Everingham, K., Antonelli, J., Harkness, R. T., ... for the Development and Evaluation of Strategies to Improve Sedation practice in inTensive care Study Investigators (2016). Development of process control methodology for tracking the quality and safety of pain, agitation, and sedation management in critical care units. Critical Care Medicine, 44(3), 564-574. https://doi.org/10.1097/CCM.0000000000001463
    Walsh, Timothy S. ; Kydonaki, Kalliopi ; Lee, Robert J. ; Everingham, Kirsty ; Antonelli, Jean ; Harkness, Ronald T. ; Cole, Stephen ; Quasim, Tara ; Ruddy, James ; McDougall, Marcia ; Davidson, Alan ; Rutherford, John ; Richards, Jonathan ; Weir, Christopher J. ; for the Development and Evaluation of Strategies to Improve Sedation practice in inTensive care Study Investigators. / Development of process control methodology for tracking the quality and safety of pain, agitation, and sedation management in critical care units. In: Critical Care Medicine. 2016 ; Vol. 44, No. 3. pp. 564-574.
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    abstract = "OBJECTIVE: To develop sedation, pain, and agitation quality measures using process control methodology and evaluate their properties in clinical practice.DESIGN: A Sedation Quality Assessment Tool was developed and validated to capture data for 12-hour periods of nursing care. Domains included pain/discomfort and sedation-agitation behaviors; sedative, analgesic, and neuromuscular blocking drug administration; ventilation status; and conditions potentially justifying deep sedation. Predefined sedation-related adverse events were recorded daily. Using an iterative process, algorithms were developed to describe the proportion of care periods with poor limb relaxation, poor ventilator synchronization, unnecessary deep sedation, agitation, and an overall optimum sedation metric. Proportion charts described processes over time (2 monthly intervals) for each ICU. The numbers of patients treated between sedation-related adverse events were described with G charts. Automated algorithms generated charts for 12 months of sequential data. Mean values for each process were calculated, and variation within and between ICUs explored qualitatively.SETTING: Eight Scottish ICUs over a 12-month period.PATIENTS: Mechanically ventilated patients.INTERVENTIONS: None.MEASUREMENTS AND MAIN RESULTS: The Sedation Quality Assessment Tool agitation-sedation domains correlated with the Richmond Sedation Agitation Scale score (Spearman ρ = 0.75) and were reliable in clinician-clinician (weighted kappa; κ = 0.66) and clinician-researcher (κ = 0.82) comparisons. The limb movement domain had fair correlation with Behavioral Pain Scale (ρ = 0.24) and was reliable in clinician-clinician (κ = 0.58) and clinician-researcher (κ = 0.45) comparisons. Ventilator synchronization correlated with Behavioral Pain Scale (ρ = 0.54), and reliability in clinician-clinician (κ = 0.29) and clinician-researcher (κ = 0.42) comparisons was fair-moderate. Eight hundred twenty-five patients were enrolled (range, 59-235 across ICUs), providing 12,385 care periods for evaluation (range 655-3,481 across ICUs). The mean proportion of care periods with each quality metric varied between ICUs: excessive sedation 12-38{\%}; agitation 4-17{\%}; poor relaxation 13-21{\%}; poor ventilator synchronization 8-17{\%}; and overall optimum sedation 45-70{\%}. Mean adverse event intervals ranged from 1.5 to 10.3 patients treated. The quality measures appeared relatively stable during the observation period.CONCLUSIONS: Process control methodology can be used to simultaneously monitor multiple aspects of pain-sedation-agitation management within ICUs. Variation within and between ICUs could be used as triggers to explore practice variation, improve quality, and monitor this over time.",
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    author = "Walsh, {Timothy S.} and Kalliopi Kydonaki and Lee, {Robert J.} and Kirsty Everingham and Jean Antonelli and Harkness, {Ronald T.} and Stephen Cole and Tara Quasim and James Ruddy and Marcia McDougall and Alan Davidson and John Rutherford and Jonathan Richards and Weir, {Christopher J.} and {for the Development and Evaluation of Strategies to Improve Sedation practice in inTensive care Study Investigators}",
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    Walsh, TS, Kydonaki, K, Lee, RJ, Everingham, K, Antonelli, J, Harkness, RT, Cole, S, Quasim, T, Ruddy, J, McDougall, M, Davidson, A, Rutherford, J, Richards, J, Weir, CJ & for the Development and Evaluation of Strategies to Improve Sedation practice in inTensive care Study Investigators 2016, 'Development of process control methodology for tracking the quality and safety of pain, agitation, and sedation management in critical care units', Critical Care Medicine, vol. 44, no. 3, pp. 564-574. https://doi.org/10.1097/CCM.0000000000001463

    Development of process control methodology for tracking the quality and safety of pain, agitation, and sedation management in critical care units. / Walsh, Timothy S. (Lead / Corresponding author); Kydonaki, Kalliopi; Lee, Robert J.; Everingham, Kirsty; Antonelli, Jean; Harkness, Ronald T.; Cole, Stephen; Quasim, Tara; Ruddy, James; McDougall, Marcia; Davidson, Alan; Rutherford, John; Richards, Jonathan; Weir, Christopher J.; for the Development and Evaluation of Strategies to Improve Sedation practice in inTensive care Study Investigators.

    In: Critical Care Medicine, Vol. 44, No. 3, 01.03.2016, p. 564-574.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Development of process control methodology for tracking the quality and safety of pain, agitation, and sedation management in critical care units

    AU - Walsh, Timothy S.

    AU - Kydonaki, Kalliopi

    AU - Lee, Robert J.

    AU - Everingham, Kirsty

    AU - Antonelli, Jean

    AU - Harkness, Ronald T.

    AU - Cole, Stephen

    AU - Quasim, Tara

    AU - Ruddy, James

    AU - McDougall, Marcia

    AU - Davidson, Alan

    AU - Rutherford, John

    AU - Richards, Jonathan

    AU - Weir, Christopher J.

    AU - for the Development and Evaluation of Strategies to Improve Sedation practice in inTensive care Study Investigators

    PY - 2016/3/1

    Y1 - 2016/3/1

    N2 - OBJECTIVE: To develop sedation, pain, and agitation quality measures using process control methodology and evaluate their properties in clinical practice.DESIGN: A Sedation Quality Assessment Tool was developed and validated to capture data for 12-hour periods of nursing care. Domains included pain/discomfort and sedation-agitation behaviors; sedative, analgesic, and neuromuscular blocking drug administration; ventilation status; and conditions potentially justifying deep sedation. Predefined sedation-related adverse events were recorded daily. Using an iterative process, algorithms were developed to describe the proportion of care periods with poor limb relaxation, poor ventilator synchronization, unnecessary deep sedation, agitation, and an overall optimum sedation metric. Proportion charts described processes over time (2 monthly intervals) for each ICU. The numbers of patients treated between sedation-related adverse events were described with G charts. Automated algorithms generated charts for 12 months of sequential data. Mean values for each process were calculated, and variation within and between ICUs explored qualitatively.SETTING: Eight Scottish ICUs over a 12-month period.PATIENTS: Mechanically ventilated patients.INTERVENTIONS: None.MEASUREMENTS AND MAIN RESULTS: The Sedation Quality Assessment Tool agitation-sedation domains correlated with the Richmond Sedation Agitation Scale score (Spearman ρ = 0.75) and were reliable in clinician-clinician (weighted kappa; κ = 0.66) and clinician-researcher (κ = 0.82) comparisons. The limb movement domain had fair correlation with Behavioral Pain Scale (ρ = 0.24) and was reliable in clinician-clinician (κ = 0.58) and clinician-researcher (κ = 0.45) comparisons. Ventilator synchronization correlated with Behavioral Pain Scale (ρ = 0.54), and reliability in clinician-clinician (κ = 0.29) and clinician-researcher (κ = 0.42) comparisons was fair-moderate. Eight hundred twenty-five patients were enrolled (range, 59-235 across ICUs), providing 12,385 care periods for evaluation (range 655-3,481 across ICUs). The mean proportion of care periods with each quality metric varied between ICUs: excessive sedation 12-38%; agitation 4-17%; poor relaxation 13-21%; poor ventilator synchronization 8-17%; and overall optimum sedation 45-70%. Mean adverse event intervals ranged from 1.5 to 10.3 patients treated. The quality measures appeared relatively stable during the observation period.CONCLUSIONS: Process control methodology can be used to simultaneously monitor multiple aspects of pain-sedation-agitation management within ICUs. Variation within and between ICUs could be used as triggers to explore practice variation, improve quality, and monitor this over time.

    AB - OBJECTIVE: To develop sedation, pain, and agitation quality measures using process control methodology and evaluate their properties in clinical practice.DESIGN: A Sedation Quality Assessment Tool was developed and validated to capture data for 12-hour periods of nursing care. Domains included pain/discomfort and sedation-agitation behaviors; sedative, analgesic, and neuromuscular blocking drug administration; ventilation status; and conditions potentially justifying deep sedation. Predefined sedation-related adverse events were recorded daily. Using an iterative process, algorithms were developed to describe the proportion of care periods with poor limb relaxation, poor ventilator synchronization, unnecessary deep sedation, agitation, and an overall optimum sedation metric. Proportion charts described processes over time (2 monthly intervals) for each ICU. The numbers of patients treated between sedation-related adverse events were described with G charts. Automated algorithms generated charts for 12 months of sequential data. Mean values for each process were calculated, and variation within and between ICUs explored qualitatively.SETTING: Eight Scottish ICUs over a 12-month period.PATIENTS: Mechanically ventilated patients.INTERVENTIONS: None.MEASUREMENTS AND MAIN RESULTS: The Sedation Quality Assessment Tool agitation-sedation domains correlated with the Richmond Sedation Agitation Scale score (Spearman ρ = 0.75) and were reliable in clinician-clinician (weighted kappa; κ = 0.66) and clinician-researcher (κ = 0.82) comparisons. The limb movement domain had fair correlation with Behavioral Pain Scale (ρ = 0.24) and was reliable in clinician-clinician (κ = 0.58) and clinician-researcher (κ = 0.45) comparisons. Ventilator synchronization correlated with Behavioral Pain Scale (ρ = 0.54), and reliability in clinician-clinician (κ = 0.29) and clinician-researcher (κ = 0.42) comparisons was fair-moderate. Eight hundred twenty-five patients were enrolled (range, 59-235 across ICUs), providing 12,385 care periods for evaluation (range 655-3,481 across ICUs). The mean proportion of care periods with each quality metric varied between ICUs: excessive sedation 12-38%; agitation 4-17%; poor relaxation 13-21%; poor ventilator synchronization 8-17%; and overall optimum sedation 45-70%. Mean adverse event intervals ranged from 1.5 to 10.3 patients treated. The quality measures appeared relatively stable during the observation period.CONCLUSIONS: Process control methodology can be used to simultaneously monitor multiple aspects of pain-sedation-agitation management within ICUs. Variation within and between ICUs could be used as triggers to explore practice variation, improve quality, and monitor this over time.

    KW - Aged

    KW - Analgesics

    KW - Conscious sedation

    KW - Critical care

    KW - Female

    KW - Humans

    KW - Hypnotics and sedatives

    KW - Intensive care units

    KW - Male

    KW - Middle aged

    KW - Monitoring, Physiologic

    KW - Pain management

    KW - Process assessment (Health Care)

    KW - Prospective studies

    KW - Psychomotor agitation

    KW - Quality improvement

    KW - Reproducibility of results

    KW - Respiration, Artificial

    KW - Scotland

    KW - Journal article

    KW - Research support, Non-U.S. Gov't

    U2 - 10.1097/CCM.0000000000001463

    DO - 10.1097/CCM.0000000000001463

    M3 - Article

    VL - 44

    SP - 564

    EP - 574

    JO - Critical Care Medicine

    JF - Critical Care Medicine

    SN - 0090-3493

    IS - 3

    ER -