Post PreviewThe digital technology that has swept other industries could empower frontline healthcare workers with the consolidated data and clinical decision aids (DCAs) needed. However, such a system would take time to cultivate.
In the meantime, health outcomes data can help patients make informed decisions about clinicians, facilities, and treatments.
Patient-Reported Outcomes (PROMs)
Patient-reported outcomes (PROMs) measure patients’ symptoms, functional status, mental health, and quality of life via questionnaires. This data, which can be interpreted and shared with clinicians, helps shape clinical management.
PROMs are often used in a clinical setting, so they must be designed with the patient experience in mind. Patients who do not enjoy participating in PROMs report feeling frustrated and rushed during the interview process, which can negatively affect their sense of control.
Qualitative studies also highlight how the standardized nature of many PROMs can limit the opportunities for meaningful discussions with patients. This is because they must respond to pre-defined questions, which reduces the opportunity for personalized interaction. For these reasons, clinicians must be trained in using and interpreting PROMs. They should also be given the flexibility to adapt PROM questions to their local disease trajectory and care setting.
Clinical Outcomes Assessments (COAs)
Some experts highlighted a few types of COAs that are important for clinical trials, including patient-reported outcomes (PROs), clinician-reported outcomes (ClinROs), performance outcomes (PerfOs), and observer-reported outcomes (ObsROs). They also emphasized the importance of engaging patients early on to learn what matters to them. Based on this information, researchers can judge whether existing tools might be appropriate or whether they need to develop a new device. Analyzing clinical outcomes data provides valuable insights into the effectiveness of treatments and interventions, guiding healthcare decisions and improving patient care based on evidence-based practices.
A COA can be either a PRO or a ClinRO and be used as a primary or secondary endpoint. In addition, COAs can be categorized as having intrinsic or extrinsic attributes. Inherent attributes are associated with how the instrument is developed, such as the method of data collection and the underlying assumptions. Irrelevant facts are related to the properties of the measurement instrument, such as its psychometric characteristics and thresholds for assessing within-patient meaningful change.
Patient Experience Measures (PXMs)
Patient experience measures are standardized survey tools that ask patients (or their families) to rate and report on the aspects of healthcare service delivery that matter most to them. Most are designed to be administered by organizations (such as hospitals, home health care agencies, doctors, and health and drug plans) that serve Medicare beneficiaries and often have implications for the providers’ payments.
The resulting data can identify factors that influence patient satisfaction and the extent to which those factors are associated with clinical processes or data outcomes. For example, suppose a hospital’s patient survey shows that nurses’ empathy positively impacts patients’ satisfaction with ER services. In that case, the ER staff should be encouraged to routinely measure how quickly they see their patients when they arrive in the ER.
An ongoing action research project involving practitioners and researchers has developed innovations for collecting, reporting, and using PREMs at both system and individual ward levels. These include a continuous data collection approach, three generic patient-reported measures covering relational, functional, and integration aspects of patient experience, short forms with lower reading age, and inclusion of the data in multidimensional performance evaluation systems.
Quality Measures
Quality measures allow hospitals to objectively evaluate their structures, processes, and outcomes. Many healthcare organizations use them to improve patient care, reduce costs, and demonstrate their accountability in various ways.
Quality indicators can be grouped into processes, safety, and structural measures. Process indicators indicate the degree to which a clinician adheres to evidence-based treatment guidelines. They are typically expressed as rate-based indicators (proportions or percentages with clearly defined numerators and denominators). They may be accompanied by simple count-based indicators for rare “sentinel” events, such as foreign objects left in the body after surgery.
Safety measures focus on avoiding avoidable errors (for example, the number of surgical patients who die due to complications from the procedure). Structural measures ensure that services are provided efficiently and effectively, such as the patient-to-emergency nurse ratio or the availability of a cardiac catheterization laboratory 24 hours a day.
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