QI History & Physical: A Natural Extension of the Clinician Skillset

Current approaches to quality improvement (QI) resident education have made limited progress in bridging the healthcare quality chasm, despite over two decades since medical practitioners first recognized the extent of this divide. Prior research has identified the inadequate integration of QI concepts into everyday clinical practice as a significant barrier to their uptake and application by trainees. In response, we developed a novel schema for conceptualizing QI methods as analogs of familiar steps in medical diagnosis. Additionally, we have repurposed the components of the well-known history and physical to serve as an organizing framework for QI activities. By adapting and extending core bedside skills to encompass QI, rather than explaining concepts through an unfamiliar manufacturing lens, we aim to accelerate both the dissemination and acquisition of QI knowledge within practice communities and clinical learning environments.

Background

As we mark a quarter century since the Institute of Medicine published its landmark report “To Err is Human,”¹ clinicians have cause for both celebration and measured introspection. QI is now recognized as an important physician skillset, but its integration into graduate medical education has been limited. In its 2025 Clinical Learning Environment Review, the Accreditation Council for Graduate Medical Education found widespread familiarity with QI concepts at fewer than 4% of surveyed training programs.² We cannot expect physicians to engage in meaningful QI if they graduate with only superficial knowledge and cursory practice. Across training environments, frequently cited challenges have included a lack of expert faculty, competition for scarce time between QI and clinical curricula, and perceived irrelevance of QI to core physician duties.^3-8

Countering these challenges, some programs have achieved pedagogical success by integrating improvement discussions within clinical dialogues, emphasizing experiential rather than didactic learning, and eschewing abstract datasets in favor of bedside problems.^6,7,9-13 Indeed, the Royal College of Physicians and Surgeons of Canada sounded an urgent call for better integration of QI education and patient care as the best path forward.¹⁴

In response, we propose appropriating a familiar clinical framework, the history and physical (H&P), to teach QI. Following the H&P structure, we present a QI problem in the context of a clinical case and highlight similarities in the approach used to address both. We demonstrate that the core pursuit of QI—the correct determination of root causes followed by rapid cycles of intervention, assessment, and re-adjustment—mirrors the experience of clinicians managing patients from hospital admission through discharge. We reinforce this message by highlighting other shared strategies, including physical examination and adaptation to practical circumstances. By reframing QI through a clinical lens, we aim to make previously obtuse concepts more familiar and to transform QI engagement from something that may seem daunting and peripheral to patient care into an approachable extension of the core activity central to patient care.

Clinical Case Featuring Embedded QI Problem

A 75-year-old man with ischemic cardiomyopathy presents with dyspnea, weight gain, and lower extremity swelling. He denies chest pain. He lives alone, has limited mobility, and admits to eating mostly processed foods. He reports adherence to his oral diuretic regimen. On exam, he has lung crackles bilaterally, distended neck veins, and dependent lower extremity edema. His electrocardiogram is non-ischemic, and biomarkers for myocardial injury are negative. The B-type natriuretic peptide level is markedly elevated. Chest imaging demonstrates pulmonary vascular congestion.

Importantly, the patient was recently discharged from this hospital after completing treatment for acute decompensated heart failure (ADHF). Weights from his hospitalization cannot be found.

Clinicians are taught to organize the above case using a structured H&P, which helps them to remember, communicate, and systematize important points. The central elements of this familiar framework include succinct orientation (chief complaint), pertinent subjective details from the patient and other informants (history of present illness, or HPI), influential medical and psychosocial details (allergies and historical factors), and objective findings from direct scrutiny (physical examination) and other testing (vital signs and laboratory results). To conclude, a diagnostic impression and initial treatment strategy are constructed (assessment and treatment plan). Acute care of the patient is continued—and continually adjusted—until recovery goals are met (discharge criteria).

After reading the vignette, most clinicians will have little difficulty diagnosing ADHF and intervening to address the patient’s volume overload, nutritional insecurity, and excessive sodium intake, which are the root causes of his recurrent exacerbations. They will know how to monitor vital signs, weight, and serum creatinine for evidence of physiological improvement or deterioration and will adjust the treatment plan accordingly based on these indicators.

The vignette also suggests that inconsistent weight tracking during the previous hospitalization may have contributed to his readmission and, if not addressed, could impede his care once more. While most clinicians can confidently manage ADHF, far fewer feel comfortable addressing the systems-level issues underlying structured daily weight collection, especially when using approaches and terminology rooted in manufacturing rather than medicine. However, with their robust background in clinical problem-solving, clinicians already possess the essential skills needed for implementing QI measures. After all, what is the root cause if not a diagnosis? And what is a plan-do-study-act (PDSA) cycle if not a daily treatment plan?

Advancing this concept, we use the well-known H&P framework to present a QI project focused on daily weight collection. Information is presented stepwise to emphasize key similarities as the case progresses. A glossary (see Table 1) maps italicized QI terms to their bolded clinical counterparts.

Formulate a High-Level Summary of the Problem

Scenario: At this hospital, inconsistent daily weight collection impedes ADHF management and increases readmission risk.

Much like the recording of the chief complaint at the beginning of a clinical H&P, the initial step in any QI endeavor is to explicitly and succinctly state the problem being addressed. This problem statement informs interested parties and other team members about the high-level objective of the QI initiative.

Gather Subjective Information About the Problem and Associated Processes Through an Interview

Scenario: Information gathered from patients admitted with ADHF and their providers reveals several issues. Resident trainees frequently forget to activate the computerized provider order entry (CPOE) “daily weight” command because it is absent from the templated ADHF admission order set. Some trainees input free-text instructions for nurses, but the CPOE command and free-text prompts appear in different sections within the electronic health record (EHR). Nurses note that daily weights are recorded in a specific vital sign application, separate from the primary EHR. Most trainees are unfamiliar with this application and instead transcribe values from a paper flowsheet at the patient’s bedside. Nurses also report that the bedside flowsheets are incomplete and used only for rough calculations. Attending physicians depend on trainee reports to make decisions regarding diuretic management. Additionally, there is no standard protocol for weighing patients; the common practice is to attempt weighing at the end of the night shift. Patients often express dissatisfaction with being disturbed so early, and many refuse to be weighed at that time.

Just as the clinical HPI recounts how an illness began, its symptoms, and the factors that modify those symptoms, a similar narrative can be constructed for any QI problem through stakeholder interviews. Asking open-ended questions to gather insights from individuals most familiar with the problem is just as effective in QI as it is in clinical investigations. Furthermore, just as curating pertinent details in the HPI can guide clinicians toward certain diagnoses and treatment strategies, stakeholder interviews can highlight specific process deficiencies and inspire the development of countermeasures.

Catalog Additional Factors Likely to Influence the Final Plan

Scenario: Reduction in readmissions is a hospital-wide priority. Staffing levels are adequate across the organization, and collegiality among staff is strong. Financially, the hospital can afford minor process changes but not large purchases like a new EHR. While replacing the EHR outright is not possible, limited modifications can be made.

In the same way that the H&P records allergies and historical factors that might sway treatment decisions, improvement projects must acknowledge the technical, financial, and organizational fabric in which they are embedded. By accounting for these modifying elements, surprise challenges and opportunities are often revealed. In this example, we learn that the EHR can be partially customized and professional relationships are strong enough to withstand workflow alterations. We also learn that reducing readmissions is a hospital priority, which means additional resources beyond those originally envisioned may become available. Consequently, the improvement plan that takes shape under these conditions will differ significantly from what it would be without such support.

Physically Examine the System and Identify Parameters that Should Be Tracked

Scenario: On average, the hospital cares for five ADHF patients each day. These patients are randomly distributed across three hospital wards, each equipped with two well-maintained portable scales. Weight collection efficiency is constrained more by nighttime staffing than by scale availability. Additionally, there is no standardized process for collecting or documenting weights. The following parameters are proposed to monitor the effects of implementing a standardized process for weight collection and documentation:

1. Percent of patients admitted with ADHF who have CPOE daily weight orders (process measure)
2. Percent of patients admitted with ADHF who have daily weights recorded in the dedicated vital signs application (process measure)
3. Staff satisfaction with revised workflows (balance measure)
4. Patient satisfaction with revised workflows (balance and outcome measure)
5. ADHF length of stay (balance and outcome measure)
6. ADHF readmission rate (balance and outcome measure)

The QI equivalent of a physical examination is the Gemba walk, a term borrowed from Japanese manufacturing, which means to “go and see in the real place.” Clinically, we inspect, palpate, percuss, and auscultate anatomic sites to supplement the history and refine the differential diagnosis. Similarly, the Gemba walk provides valuable insights into existing processes, the physical environment, and staff dynamics, which are crucial for identifying root causes of a problem and selecting the most effective improvement strategy.

In managing ADHF, clinicians respond to changes in vital signs, exam findings, and laboratory results, such as serum creatinine levels, by either escalating or curtailing diuresis. Similarly, improvement teams must monitor key parameters, broadly categorized as outcome, process, and balance measures, to track progress and detect deviations. Outcome measures are analogous to clinical endpoints, reflecting the most downstream consequences of an intervention; for our case, this would be the ADHF readmission rate. Process measures evaluate how effectively individuals complete tasks. Balance measures, meanwhile, assess for the emergence of unwanted trends, such as staff dissatisfaction after workflow revisions or longer inpatient stays, even as readmissions decline. As with clinical care, QI projects should adapt intelligently to signals emanating from these vital measures.

Restate the Problem and Synthesize Conclusions

Scenario: Inconsistent daily weight collection hampers effective ADHF management and increases the risk of readmissions. Attending physicians depend on morning weights to guide diuretic dosing, but the unreliability of these data leads to suboptimal care. The root causes include 1) lack of standardized workflows for order entry, weight collection, and weight documentation; 2) bottlenecks resulting from reduced nighttime staffing; and 3) patient dissatisfaction, which often results in refusal to be weighed.

The identification of root causes mirrors the formulation of the assessment in a clinical H&P. Once the relevant subjective, contextual, and objective details are cataloged, the central problem can be re-stated, and conclusions about its causes can be formally presented.

Propose an Improvement Plan that Will Be Iteratively Tested, Studied, and Readjusted

Scenario: Preparatory work:

Leverage the hospital-wide readmissions reduction campaign to recruit manpower for data collection.

First PDSA cycle:

1. Coordinate morning blood draws with weight collection to reduce patient dissatisfaction.
2. Remove bedside paper flowsheets and replace them with notices directing providers to check the dedicated vital signs application.
3. Assign weight collection responsibilities to the night shift charge nurse, pending approval from that stakeholder group.
4. Future PDSA cycles:
5. Add a discrete “daily weights” order to the ADHF admission order set
6. Automatically import weight data from a dedicated vital signs application into the primary EHR
7. Co-locate ADHF patients on the same ward to streamline care processes

A good improvement plan, much like a curative treatment plan, addresses root causes rather than merely alleviating symptoms. It involves thoughtfully selecting interventions that respect practical constraints. Most importantly, these interventions should be trialed, their effectiveness assessed at regular intervals, and the plan adjusted accordingly. This embodies the essence of the PDSA cycle, which is central to QI and mirrors the iterative nature of patient care in a hospital setting.

Declare Clear Thresholds for Success

Scenario: The endpoint for this project is achieving greater than 90% adherence to daily weight collection among patients admitted with ADHF.

In caring for hospitalized patients, clinicians need to establish clear discharge criteria. For ADHF, this typically involves weaning the patient to baseline oxygenation, diuresing to dry weight, and transitioning to oral medications. Similarly, in QI, setting clear project goals is crucial. These goals are usually detailed in an aim statement, which specifies the degree of improvement sought before success is declared. New interventions should be tested in successive PDSA cycles until this goal is achieved.

Conclusion

As we have shown, QI and clinical care share a single problem-solving paradigm: to succeed, one must hear the complete story, inspect the problem first-hand, determine root causes, and continuously enact, review, and revise a corrective plan. Moreover, our vignette underscores the extent to which QI and clinical problems are entangled, with system deficiencies exerting considerable influence on patient outcomes. To deliver optimal care, providers must address both dimensions, but training in and adoption of QI has been stymied by numerous practical and cultural barriers. After appreciating the parallels between QI and clinical care, which we have drawn, we hope that physicians will feel emboldened to carry out—and to spread—QI according to fundamentals with which they are already familiar and in which they are already expert.

We recognize that this approach fails to instruct clinicians on more advanced QI concepts, nor does it prepare them to steer enterprise-wide quality measures. However, it is intuitive and easily employed in the clinical learning environment. It emphasizes the relevance of QI to bedside care and provides a schema that any clinician can follow to start teaching improvement methodology. Importantly, while not meant as the final outpost on a path toward QI mastery, our approach nevertheless serves as a catalytic first step in that rewarding journey. 

Dr. Wu

Dr. Meo

Dr. Paul

Dr. Wahl

Dr. Redinger

Dr. Khalighi

Dr. Wu is an assistant professor of medicine in the department of medicine at the University of Washington and a hospitalist physician and director of quality and safety for hospital and specialty medicine at the VA Puget Sound Health Care System, both in Seattle. Dr. Meo is a hospitalist and associate chief medical officer for quality and safety at Harborview Medical Center, and an associate professor of medicine in the department of medicine at the University of Washington, both in Seattle. Dr. Paul is a hospitalist at the VA Puget Sound Health Care System and a clinical assistant professor of medicine in the department of medicine at the University of Washington, both in Seattle.  Dr. Wahl is a hospitalist at the VA Puget Sound Health Care System and an assistant professor in the division of rheumatology in the department of medicine at the University of Washington School of Medicine, both in Seattle. Dr. Redinger is a hospitalist at the VA Puget Sound Health Care System and an assistant professor of medicine in the department of medicine at the University of Washington, both in Seattle. Dr. Khalighi is a clinical associate professor of medicine at the University of Washington and director of the preoperative medicine consult clinic at the VA Puget Sound Health Care System, both in Seattle.

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