Enabling a learning healthcare system with automated computer protocols that produce replicable and personalized clinician actions

Abstract

Clinical decision-making is based on knowledge, expertise, and authority, with clinicians approving almost every intervention-the starting point for delivery of "All the right care, but only the right care," an unachieved healthcare quality improvement goal. Unaided clinicians suffer from human cognitive limitations and biases when decisions are based only on their training, expertise, and experience. Electronic health records (EHRs) could improve healthcare with robust decision-support tools that reduce unwarranted variation of clinician decisions and actions. Current EHRs, focused on results review, documentation, and accounting, are awkward, time-consuming, and contribute to clinician stress and burnout. Decision-support tools could reduce clinician burden and enable replicable clinician decisions and actions that personalize patient care. Most current clinical decision-support tools or aids lack detail and neither reduce burden nor enable replicable actions. Clinicians must provide subjective interpretation and missing logic, thus introducing personal biases and mindless, unwarranted, variation from evidence-based practice. Replicability occurs when different clinicians, with the same patient information and context, come to the same decision and action. We propose a feasible subset of therapeutic decision-support tools based on credible clinical outcome evidence: computer protocols leading to replicable clinician actions (eActions). eActions enable different clinicians to make consistent decisions and actions when faced with the same patient input data. eActions embrace good everyday decision-making informed by evidence, experience, EHR data, and individual patient status. eActions can reduce unwarranted variation, increase quality of clinical care and research, reduce EHR noise, and could enable a learning healthcare system.

Figure 1.

(a) Replicable rules from a small section of an early mechanical ventilation eActions. CORE = Continuous Respiratory Evaluation protocol. (b) Computer displays of an early (1988) mechanical ventilation eActions.^,(c) More complicated section of rules for Continuous Positive Pressure Ventilation (1992).

Figure 1.

(a) Replicable rules from a small section of an early mechanical ventilation eActions. CORE = Continuous Respiratory Evaluation protocol. (b) Computer displays of an early (1988) mechanical ventilation eActions.^,(c) More complicated section of rules for Continuous Positive Pressure Ventilation (1992).

Figure 1.

(a) Replicable rules from a small section of an early mechanical ventilation eActions. CORE = Continuous Respiratory Evaluation protocol. (b) Computer displays of an early (1988) mechanical ventilation eActions.^,(c) More complicated section of rules for Continuous Positive Pressure Ventilation (1992).

Figure 2.

(a) Unpublished data (tidal volume, first 15, and PaO2, first 19 subjects) of an acute respiratory distress syndrome (ARDS) clinical trial of mechanical ventilation eActions, 72 hours after randomization in 6 and 12 ml/kg predicted body weight tidal volume target groups. VT = Tidal Volume, SEM = Standard Error of the Mean and N = measurement number. Replicable tidal volumes reflect rigorous control of the study intervention (VT targets not reached 100% of the time because of individual patient needs, although the eActions rules are identical except for the VT targets). Replicable PaO2 reflects rigorous control of this potential cointervention (a care element that can influence the study outcome and could obscure the impact of the study intervention). eActions PaO2 rules were identical for both tidal volume target group subjects. (b) Baseline distribution of ICU blood glucose values in multiple ICUs using different management strategies with an 80–110 mg/dl blood glucose target (left panel) and after exporting a bedside computer-protocol (eActions) to all US ICUs and to the National University Hospital of Singapore (right panel) with 95%–98% clinician compliance with eActions instructions—modified from. This demonstrates replicability of clinician action (blood glucose value outcome), not correctness of blood glucose target.

Figure 2.

(a) Unpublished data (tidal volume, first 15, and PaO2, first 19 subjects) of an acute respiratory distress syndrome (ARDS) clinical trial of mechanical ventilation eActions, 72 hours after randomization in 6 and 12 ml/kg predicted body weight tidal volume target groups. VT = Tidal Volume, SEM = Standard Error of the Mean and N = measurement number. Replicable tidal volumes reflect rigorous control of the study intervention (VT targets not reached 100% of the time because of individual patient needs, although the eActions rules are identical except for the VT targets). Replicable PaO2 reflects rigorous control of this potential cointervention (a care element that can influence the study outcome and could obscure the impact of the study intervention). eActions PaO2 rules were identical for both tidal volume target group subjects. (b) Baseline distribution of ICU blood glucose values in multiple ICUs using different management strategies with an 80–110 mg/dl blood glucose target (left panel) and after exporting a bedside computer-protocol (eActions) to all US ICUs and to the National University Hospital of Singapore (right panel) with 95%–98% clinician compliance with eActions instructions—modified from. This demonstrates replicability of clinician action (blood glucose value outcome), not correctness of blood glucose target.