Excellent Patient Care Processes in Poor Hospitals? Why Hospital-Level and Patient-Level Care Quality-Outcome Relationships Can Differ

Finney, John W.; Humphreys, Keith; Kivlahan, Daniel R.; Harris, Alex H. S.

doi:10.1007/s11606-015-3564-3

Cited by 12 publications

(14 citation statements)

References 20 publications

(16 reference statements)

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“…[32][33][34] Secondarily, it is important to note the variability in items that are the strongest drivers of OHR in different populations because it indicates that these same analyses must be done for any neurosurgical department that wishes to draw conclusions about the utility of the OHR. 35,36 In this regard, our findings agree with the results in more limited neurosurgical populations such as adult spine patients and adult cranial patients. 37,38 Each microenvironment is unique, and our findings demonstrate that while trends exist, there are no hard rules about the OHR even within a single health system.…”

Section: Discussionsupporting

confidence: 89%

The limited influence of neurosurgeons’ behavior on inpatient satisfaction: a retrospective multihospital analysis

Park

Zakare-Fagbamila

Dickson

et al. 2021

Journal of Neurosurgery

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OBJECTIVEThe Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) is a survey that assesses patient satisfaction, which is an important measure of the quality of hospital care and ultimately the overall hospital rating (OHR). However, the survey covers several elements of patient satisfaction beyond the patient-surgeon interaction. In this study, authors investigated which admission and experience factors had the highest impact on the OHR.METHODSThis was a retrospective cohort analysis of HCAHPS surveys from patients who, in the period between August 1, 2016, and January 31, 2018, had been discharged from the neurosurgical or orthopedic service at three hospitals serving a single metropolitan area. The top-box score was defined as the highest rating obtainable for each survey question. Baseline admission attributes were obtained, and multivariate logistic regression was used to determine predictors of the top-box OHR.RESULTSAfter application of the inclusion and exclusion criteria, 1470 patients remained in the analysis. Categories on the HCAHPS included OHR, communication, education, environment, pain management, and responsiveness. After excluding identifying questions from the survey and adjusting for subspecialty and hospital, 7 of 17 HCAHPS survey items were significant predictors of OHR. Only 2 of these were related to the surgeon: 1) discharge, “Did you get information in writing about what symptoms or health problems to look out for after you left the hospital?” (OR 5.93, 95% CI 2.52–13.94); and 2) doctor, “Did doctors explain things in a way you could understand?” (OR 2.78, 95% CI 1.73–4.46). The top three strongest correlating items were 1) discharge; 2) nursing, “Did nurses treat you with courtesy and respect?” (OR 3.86, 95% CI 2.28–6.52); and 3) hospital environment, “Were your room and bathroom kept clean?” (OR 2.86, 95% CI 1.96–4.17).CONCLUSIONSThe study findings demonstrated that there are several nonmodifiable factors (i.e., specialty, experience) and items that are not under the direct purview of the neurosurgeon (e.g., nursing communication, hospital environment) that are significant influences on overall inpatient satisfaction on the HCAHPS survey. Furthermore, components of the survey that ultimately influence the OHR vary across different hospitals. Hence, HCAHPS survey results should be broadly interpreted as a way to make health systems more aware of the overall hospital factors that can improve quality of care and patient experience.

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Section: Discussionsupporting

confidence: 89%

The limited influence of neurosurgeons’ behavior on inpatient satisfaction: a retrospective multihospital analysis

Park

Zakare-Fagbamila

Dickson

et al. 2021

Journal of Neurosurgery

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“…9 Finney and colleagues explore the relationship between a hospital's performance on measures of providing recommended care and patient outcomes. 10 Because the process-outcome relationship is complex, they recommend multi-level analyses to evaluate process measure-outcome relationships at both the patient and hospital levels.…”

Section: Performance Measures That Enhance Value-related Researchmentioning

confidence: 99%

The Next Generation of Clinical Performance Measures

Atkins

2016

J GEN INTERN MED

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M any are familiar with the adage that Byou can't improve what you can't measure.^Adopting clinical performance measures was an important part of the VA transformation of the 1990s, and measuring clinical performance has become an integral part of current efforts to drive improvement under Medicare, the Affordable Care Act (ACA), and in programs run by private payers. Measuring clinical performance, however, is a health system intervention, and as such, needs to be carefully examined. This includes how measures are created, how they are implemented, and the evidence for their potential benefits and harms. The landscape of healthcare has also changed substantially since the advent of the performance measurement movement, and it is time to update our approach to measuring quality. Rather than setting a single standard, identifying a random number of patients to whom the measure should apply, and conducting manual chart reviews at a single point in time, we need to be assessing quality for the entire population, including the more complex patients. A world with electronic health records and a much richer array of administrative and clinical data allows us to update our approach to include measures that consider population health, episodes of care, changes over time, and individual circumstances. The Department of Veterans Affairs (VA), which operates the largest integrated healthcare system in the United States, is a key contributor to the emerging knowledge base regarding how best to create and implement performance measures.Funded by the VA's Health Services Research and Development (HSR&D) Service, this Journal of General Internal Medicine (JGIM) Supplement is the product of an HSR&D-sponsored state-of-the-art (SOTA) conference titled BNext-Generation Clinical Performance Measures: Patient-Centered, Clinically Meaningful, and High Value,^held in 2014. After the conference, a Call for Papers was issued, and 14 manuscripts were submitted to JGIM. After rigorous JGIM peer review, ten articles were accepted for publication in this special JGIM Supplement. Published papers discuss empirical research on the effects of performance measurement on improvements in clinical care, as well as on unintended outcomes (e.g., inappropriate treatment or over-treatment). Papers also describe new methods and methodological challenges in the selection and creation of performance measures that incorporate measures of benefit and harm, value, or patient preferences, as well as research on the implementation of performance measures that address human factors, incentives and facilitators, barriers, and expected and unintended consequences. USING VA'S ELECTRONIC HEALTH RECORD SYSTEM TO MEASURE QUALITYThree papers examined the ability to use VA electronic data to measure clinical quality in specific clinical areas. Phipps and colleagues developed and validated inpatient stroke electronic clinical quality measures that are part of the Meaningful Use (MU) program and VA efforts to improve inpatient stroke care. 1 The authors found that stro...

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“…We used this operations metric for initial site selection of low-adopting VHA facilities, which we operationalized as facilities in the bottom quartile based on the facilities MOUD/OUD ratio. The risk in using operations-calculated quality measures versus researcher-calculated metrics to determine site eligibility is that operational leadership may institute changes to the definition of the measure or discontinue calculating the measure mid-project [ 16 ]. This can lead to inaccurate conclusions about the level of change achieved by facilities during the study or difficulties in continued tracking of performance over time.…”

Section: Impact Of Healthcare Quality Measure Use On Site Selectionmentioning

confidence: 99%

Healthcare quality measures in implementation research: advantages, risks and lessons learned

Gustavson

Hagedorn

Jesser

et al. 2022

Health Res Policy Sys

Self Cite

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Implementation studies evaluate strategies to move evidence-based practices into routine clinical practice. Often, implementation scientists use healthcare quality measures to evaluate the integration of an evidence-based clinical practice into real-world healthcare settings. Healthcare quality measures have standardized definitions and are a method to operationalize and monitor guideline-congruent care. Implementation scientists can access existing data on healthcare quality measures through various sources (e.g. operations-calculated), or they can calculate the measures directly from healthcare claims and administrative data (i.e. researcher-calculated). Implementation scientists need a better understanding of the advantages and disadvantages of these methods of obtaining healthcare quality data for designing, planning and executing an implementation study. The purpose of this paper is to describe the advantages, risks and lessons learned when using operations- versus researcher-calculated healthcare quality measures in site selection, implementation monitoring and implementation outcome evaluation. A key lesson learned was that relying solely on operations-calculated healthcare quality measures during an implementation study poses risks to site selection, accurate feedback on implementation progress to stakeholders, and the integrity of study results. A possible solution is using operations-calculated quality measures for monitoring of evidence-based practice uptake and researcher-calculated measures for site section and outcomes evaluation. This approach provides researchers greater control over the data and consistency of the measurement from site selection to outcomes evaluation while still retaining measures that are familiar and understood by key stakeholders whom implementation scientists need to engage in practice change efforts.

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Excellent Patient Care Processes in Poor Hospitals? Why Hospital-Level and Patient-Level Care Quality-Outcome Relationships Can Differ

Cited by 12 publications

References 20 publications

The limited influence of neurosurgeons’ behavior on inpatient satisfaction: a retrospective multihospital analysis

The limited influence of neurosurgeons’ behavior on inpatient satisfaction: a retrospective multihospital analysis

The Next Generation of Clinical Performance Measures

Healthcare quality measures in implementation research: advantages, risks and lessons learned

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