Improving Patients’ Choice of Clinician by Including Roll-up Measures in Public Healthcare Quality Reports: an Online Experiment

Cerully, Jennifer L.; Parker, Andrew M.; Rybowski, Lise; Schlesinger, Mark; Shaller, Dale; Grob, Rachel; Finucane, Melissa L.; Martino, Steven C.

doi:10.1007/s11606-018-4725-y

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…The participants involved in this study were selected from the Growth for Knowledge (GfK) probability-based-Internet Knowledge panel, which is representative of the US population in terms of sociodemographic characteristics, Internet usage, and health status [51]. The Knowledge Panel from which respondents are drawn is composed entirely of panelists from the United States.…”

Section: Study Participantsmentioning

confidence: 99%

How exposure to patient narratives affects stereotyped choices of primary care clinicians

Bhaumik,

Schlesinger

2023

PLoS ONE

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In this paper, we examine whether patient narratives alter the impact of stereotyping on choice of primary care clinicians: in this case, the common presumption that female doctors will be more attentive to empathic relationships with patients. 1052 individuals were selected from a nationally representative Internet panel to participate in a survey experiment. Participants were given performance data about 12 fictitious primary care physicians, including a randomized set of narrative feedback from patients. We compared the choice of clinician made by participants who value bedside manner and were exposed to narratives in the experiment, compared to those valuing bedside manner who had not had this exposure. We estimated multivariate logistic regressions to assess whether exposure to patient comments that “disrupt” stereotypes influenced choice of physicians. Participants who saw patient comments and had previously reported caring about bedside manner had a 67% higher odds of choosing a female physician than those participants that did not see a patient comments, controlling for the content of the narratives themselves. When participants were exposed to patient comments that disrupt gendered stereotypes, they had a 40% lower odds of choosing a female physician. Simple exposure to patient narratives that do not clearly disrupt gendered stereotypes increased the likelihood of choosing a female clinician by priming attention to relational aspects of care. However, when the content of a sufficient proportion of patient comments runs counter stereotypes, even a minority of narratives is sufficient to disrupt gendered-expectations and alter choices.

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Section: Study Participantsmentioning

confidence: 99%

How exposure to patient narratives affects stereotyped choices of primary care clinicians

Bhaumik,

Schlesinger

2023

PLoS ONE

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“…A popular approach to developing an overall understanding of quality has been to combine quality measures into a composite measure—as endorsed by two IOM reports8 16—to summarise information and reduce cognitive load 17 18. The value of composite measures has been mixed, some reporting substantive interpretability, internal consistency and accounting for the majority of variation,19–22 while others report significant limitations of producing widely varying results with poor face validity and lacking the ability to signal specific changes to be targeted for improvement 14 23–25…”

Section: Introductionmentioning

confidence: 99%

From measures to action: can integrating quality measures provide system-wide insights for quality improvement decision making?

Khayal

Sanz

2023

BMJ Health Care Inform

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BackgroundQuality improvement decision makers are left to develop an understanding of quality within their healthcare system from a deluge of narrowly focused measures that reflect existing fragmentation in care and lack a clear method for triggering improvement. A one-to-one metric-to-improvement strategy is intractable and leads to unintended consequences. Although composite measures have been used and their limitations noted in the literature, what remains unknown is ‘Can integrating multiple quality measures provide a systemic understanding of care quality across a healthcare system?’MethodsWe devised a four-part data-driven analytic strategy to determine if consistent insights exist about the differential utilisation of end-of-life care using up to eight publicly available end-of-life cancer care quality measures across National Cancer Institute and National Comprehensive Cancer Network-designated cancer hospitals/centres. We performed 92 experiments that included 28 correlation analyses, 4 principal component analyses, 6 parallel coordinate analyses with agglomerative hierarchical clustering across hospitals and 54 parallel coordinate analyses with agglomerative hierarchical clustering within each hospital.ResultsAcross 54 centres, integrating quality measures provided no consistent insights across different integration analyses. In other words, we could not integrate quality measures to describe how the underlying quality constructs of interest—intensive care unit (ICU) visits, emergency department (ED) visits, palliative care use, lack of hospice, recent hospice, use of life-sustaining therapy, chemotherapy and advance care planning—are used relative to each other across patients. Quality measure calculations lack interconnection information to construct a story that provides insights about where, when or what care is provided to which patients. And yet, we posit and discuss why administrative claims data—used to calculate quality measures—do contain such interconnection information.ConclusionWhile integrating quality measures does not provide systemic information, new systemic mathematical constructs designed to convey interconnection information can be developed from the same administrative claims data to support quality improvement decision making.

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“…Composites, rankings, and their star-rating derivatives can potentially serve such a purpose. When a choice of health care group is feasible, these shortcuts may promote better decision making by the public than more technical presentations of detailed performance comparisons …”

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confidence: 99%

Health Care Group Performance Ratings—Rethinking the Ruling Order

Francis

2019

JAMA Netw Open

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American people enjoy ratings and rankings-athletic teams, restaurants, music albums, television shows, movies, automobiles, books, hotels, cities, and even colleges are featured in annual top 10, top 100, or best of lists. The publications that sponsor such articles command wide appeal among consumers and have spawned a growing rating industry. The rules that underlie such ratings have many features in common: (1) important but poorly defined concepts, like the road handling of a car, are quantified using conveniently available performance metrics (eg, acceleration and braking distances) or subjective surveys of experience; (2) these proxies are then combined into an overall index using arbitrarily chosen decision rules; and (3) the composite index is translated into a ranking list or, more often, a quasi-metric such as a star rating. Not surprisingly, how one selects the individual metrics and constructs decision rules for the composite can dramatically reorder rankings. 1 For situations such as sports or cinema, ranking lists (eg, league tables) and star ratings promote friendly jousting and harmless amusement. In other settings, transparency about performance may help consumers choose a superior product and may potentially prompt a complacent business to improve the quality of and user satisfaction with its products. The rub comes when public policy directs such tactics at complex services such as education or health care, where outcome stakes are higher. When the public is paying for services, it is natural to demand added value for the investment and to request that such value be conveyed in a way that nonexperts can understand. Composites, rankings, and their star-rating derivatives can potentially serve such a purpose. When a choice of health care group is feasible, these shortcuts may promote better decision making by the public than more technical presentations of detailed performance comparisons. 2 Yet, for years experts have raised cautionary flags regarding the inherent statistical uncertainties in using league tables or similar approaches. 3,4 The policy conundrum becomes further amplified when dubious methods of ordering are used to adjust payment. Health outcomes are demonstrably dependent on underlying health risks determined by genetic, social, educational, economic, and behavioral factors that are beyond the immediate ability of health care professionals to influence. Clinicians who disproportionately serve disadvantaged populations have been shown to score lower on rankings and would therefore be likely to experience a decrease in reimbursement under zero-sum pay-for-performance plans. 5 It would be puzzling social policy to shift those dollars toward health care professionals serving the healthy, wealthy, and wise, but that may be the unintended consequence of shortcuts such as composites and star ratings. An important and timely empirical contribution to this debate is made by Nguyen and colleagues. 6 In a cross-sectional analysis, they compared the performance on standard performance measur...

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Improving Patients’ Choice of Clinician by Including Roll-up Measures in Public Healthcare Quality Reports: an Online Experiment

Cited by 5 publications

References 19 publications

How exposure to patient narratives affects stereotyped choices of primary care clinicians

How exposure to patient narratives affects stereotyped choices of primary care clinicians

From measures to action: can integrating quality measures provide system-wide insights for quality improvement decision making?

Health Care Group Performance Ratings—Rethinking the Ruling Order

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