Abdominal Pain, Asthma, Back Pain, Cellulitis, Chest Pain, Confusion, COPD, Cough, Deep Vein Thrombosis, Delirium, Diarrhea, Dyspnea, Electrolyte Metabolism Abnormal, Failure to Thrive, Fever, Headache, Hip Pain Chronic, Hypoxia, Leg Pain, Mental Status Change, Neck Pain, Pneumonia, Protein-Calorie Malnutrition, Pulmonary Embolism, Sepsis, Soft Tissue Infections, Syncope, Venous Thromboembolism, Vomiting, Weakness
Conditions
Keywords
Diagnostic errors
Brief summary
To improve the safety of diagnosis and therapy for a set of conditions and undifferentiated symptoms for hospitalized patients, the investigators will employ a set of methods and tools from the disciplines of systems engineering, human factors, quality improvement,and data analytics to thoroughly analyze the problem, design and develop potential solutions that leverage existing current technological infrastructure, and implement and evaluate the final interventions. The investigators will engage the interdisciplinary care team and patient (or their caregivers) to ensure treatment trajectories match the anticipated course for working diagnoses (or symptoms), and whether they are in line with patient and clinician expectations. The investigators will use an Interrupted time series (ITS) design to assess impact on diagnostic errors that lead to patient harm. The investigators will perform quantitative and qualitative evaluations using implementation science principles to understand if the interventions worked, and why or why not.
Detailed description
The goal of this study is to improve the safety of diagnosis and therapy for a set of conditions and undifferentiated symptoms for hospitalized patients. The investigators will employ a set of methods and tools from the disciplines of systems engineering, human factors, quality improvement, and implementation science to thoroughly analyze the problem, design and develop potential solutions that leverage the current technological infrastructure, and implement and evaluate the final interventions. The aims of this study are to: 1. Analyze the problem of diagnostic error over the acute episode of care, identifying system and cognitive factors for a set of morbid, costly common conditions and undifferentiated symptoms by using system engineering and human factors methods, as well as electronic health record and administrative data review. 2. Design, develop, and iteratively refine intervention components using lessons learned from problem analysis and a participatory process that involves patients, clinicians, and institutional stakeholders. 3. Implement an intervention for patient and clinician subjects on general medicine units. Using a pre-post, interrupted time series study design, the investigators will evaluate the effect of the intervention primarily on diagnostic and therapeutic errors. The investigators will use mixed methods to understand barriers and facilitators of implementation.
Interventions
A Diagnostic Uncertainty Educational Curriculum will consist of an interactive, one-hour teach-the-teacher workshop delivered to resident-attending pairs early on during their inpatient medicine rotation. During the workshop, we will discuss the motivation behind teaching diagnostic uncertainty, review factors that may predict risk of diagnostic error during hospitalization, introduce the framework. Each resident-attending pair will work through a case-based exercise focused on managing learners' diagnostic uncertainty during rounds. Our research team will also conduct Training for clinical staff working on intervention units and will provide at-the-elbow support during the intervention period of the main trial.
A Diagnostic Timeout is a structured pocket guide that clinicians may use to address uncertainty in a step-wise approach for patients who have risk factors for diagnostic error. This tool can be used during or after clinical rounds, inside or outside of a patient's room if the patient is agreeable. The Diagnostic Timeout will be introduced as part of the Diagnostic Uncertainty Educational Curriculum as well as Training.
We will administer a survey, the Dx Questionnaire, to patients which asks a series of questions on communication regarding diagnosis with the care team. Patients admitted to inpatient units within the prior 24 hours will be approached after asking the patient's nurse to determine whether it is the appropriate time to approach for enrollment. Upon explaining the objectives of the survey and obtaining verbal informed consent, patients will be asked to complete the Dx Questionnaire via REDCap on an iPad. Alternatively, the research assistant administering the survey will go through the Dx Questionnaire with the patient and record their answers in REDCap on their behalf. If patients' answers indicate a gap in communication (i.e., an answer of No on a question), the Research Assistant will ask for permission to follow-up within the next few days and will relay the gap in communication to the patients' care team (i.e., nurse).
Epic-integrated Quality and Safety Dashboard, currently in operational use at BWH, will be enhanced to include a new diagnostic safety column. Clinical staff will receive Training and at-the-elbow support by the research team upon implementation.
Sponsors
Study design
Intervention model description
We will conduct a pre-post interrupted time series design study in which we compare the relative effectiveness of the intervention over pre-post intervention for enrolled patients for our main outcomes.
Eligibility
Inclusion criteria
* Age 18 or older * Adult patients admitted to General Medicine Services at Brigham and Women's Hospital during the 21-months study data collection period * English speakers * Patients who were diagnosed with any of the following conditions and symptoms upon admission: * Abdominal pain * Altered mental status/ delirium / confusion * Asthma / chronic obstructive pulmonary disease (COPD) * Cellulitis / soft tissue infection * Chest pain * Cough * Deep vein thrombosis / pulmonary embolism / venous thromboembolism * Dyspnea / short of breath * Failure to thrive * Pneumonia * Protein-calorie malnutrition * Sepsis * Other conditions typical of general medicine patients
Exclusion criteria
* Not pregnant women, prisoners and institutionalized individuals
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic error | 30 days (at most) from admission to the hospital | Data Source: Chart audit Analytic Variables: * % patients with diagnostic error * % patients with diagnostic error with actual or potential AE (i.e., harmful DE) * % patients with diagnostic error with actual or potential AE that was severe (i.e., harmful and severe DE) * % patients with diagnostic error with actual or potential AE that was preventable (i.e., harmful, severe, and preventable DE) |
| Safe diagnosis | 30 days (at most) from admission to the hospital | Data Source: Chart audit Analytic variables: • % patients with correct diagnosis or therapy established within 24 hours of admission |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Healthcare resource utilization | 30 days after discharge from the hospital | Data Source: EDW (enterprise data warehouse) Analytic variables: • % patients with ≥ 1 unscheduled ED visit or readmission |
| Patient satisfaction | 30 days after discharge from the hospital | HCAPHS (the Hospital Consumer Assessment of Healthcare Providers and Systems)patient satisfaction survey: The survey is composed of 27 items: 18 substantive items that encompass critical aspects of the hospital experience (communication with doctors, communication with nurses, responsiveness of hospital staff, cleanliness of the hospital environment, quietness of the hospital environment, pain management, communication about medicines, discharge information, overall rating of hospital, and recommendation of hospital). |
Countries
United States