Physician Cost Consciousness and Use of Low-Value Clinical Services

Grover, Michael; Abraham, Neena S.; Chang, Yu Hui; Tilburt, Jon C.

doi:10.3122/jabfm.2016.06.160176

Cited by 19 publications

(19 citation statements)

References 16 publications

(18 reference statements)

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“…[46,51]). Two studies identified determinants that were linked to lower use of LVC: professionals' cost-consciousness [42] and perceived usefulness of guidelines as well as self-efficacy with regard to discussing LVC and costs [52].…”

Section: Professional Determinantsmentioning

confidence: 99%

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Determinants for the use and de-implementation of low-value care in health care: a scoping review

Augustsson

Ingvarsson

Nilsén

et al. 2021

Implement Sci Commun

118

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Background A considerable proportion of interventions provided to patients lack evidence of their effectiveness. This implies that patients may receive ineffective, unnecessary or even harmful care. However, despite some empirical studies in the field, there has been no synthesis of determinants impacting the use of low-value care (LVC) and the process of de-implementing LVC. Aim The aim was to identify determinants influencing the use of LVC, as well as determinants for de-implementation of LVC practices in health care. Methods A scoping review was performed based on the framework by Arksey and O’Malley. We searched four scientific databases, conducted snowball searches of relevant articles and hand searched the journal Implementation Science for peer-reviewed journal articles in English. Articles were included if they were empirical studies reporting on determinants for the use of LVC or de-implementation of LVC. The abstract review and the full-text review were conducted in duplicate and conflicting decisions were discussed until consensus was reached. Data were charted using a piloted data charting form and the determinants were inductively coded and categorised in an iterative process conducted by the project group. Results In total, 101 citations were included in the review. Of these, 92 reported on determinants for the use of LVC and nine on determinants for de-implementation. The studies were conducted in a range of health care settings and investigated a variety of LVC practices with LVC medication prescriptions, imaging and screening procedures being the most common. The identified determinants for the use of LVC as well as for de-implementation of LVC practices broadly concerned: patients, professionals, outer context, inner context, process and evidence and LVC practice. The results were discussed in relation to the Consolidated Framework for Implementation Research. Conclusion The identified determinants largely overlap with existing implementation frameworks, although patient expectations and professionals’ fear of malpractice appear to be more prominent determinants for the use and de-implementation of LVC. Thus, existing implementation determinant frameworks may require adaptation to be transferable to de-implementation. Strategies to reduce the use of LVC should specifically consider determinants for the use and de-implementation of LVC. Registration The review has not been registered.

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Section: Professional Determinantsmentioning

confidence: 99%

“…Evidence included conflicting guidelines [50,59] and inappropriate or inapplicable guidelines for the patient group [52,77], which led to more LVC. Furthermore, professionals' belief that the LVC was, in fact, effective, despite guidelines recommending against its use was reported as a reason for using LVC (e.g.…”

Section: Evidence and Lvc Practice Determinantsmentioning

confidence: 99%

Determinants for the use and de-implementation of low-value care in health care: a scoping review

Augustsson

Ingvarsson

Nilsén

et al. 2021

Implement Sci Commun

118

View full text Add to dashboard Cite

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“…7 Repeated BMD testing is commonly performed, with a substantial proportion of women receiving repeated tests within 2 years, a practice questioned by the Choosing Wisely campaign, 8 speaking to the need for guidance to help clinicians make higher-value decisions regarding repeated BMD measurement. [8][9][10] Studies examining BMD loss and transition to osteoporosis have provided insights into BMD testing intervals according to the level of baseline BMD. 11 Subsequent analyses have evaluated time to reach clinically relevant fracture risk for those who fall below the treatment threshold at baseline 12 and the doubling time in fracture risk, 13 although these have not adequately considered baseline fracture risk relative to the treatment threshold, which would be expected to affect treatment eligibility.…”

Section: Introductionmentioning

confidence: 99%

Reassessment Intervals for Transition From Low to High Fracture Risk Among Adults Older Than 50 Years

et al. 2020

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IMPORTANCE Fracture risk scores are used to identify individuals at high risk of major osteoporotic fracture or hip fracture for antiosteoporosis treatment. For those not meeting treatment thresholds at baseline, the optimal interval for reassessing fracture risk is uncertain.OBJECTIVE To examine reassessment intervals for transition from low to high fracture risk under guidelines-defined treatment thresholds. DESIGN, SETTING, AND PARTICIPANTSThis retrospective cohort study included persons aged 50 years or older with fracture risk below treatment thresholds at baseline who had fracture risk reassessed at least 1 year later. Data were obtained from a population-based bone mineral density registry (baseline assessment during 1996-2015; reassessment to 2016) in the Province of Manitoba, Canada. Primary analysis was performed from May to June 2019. Analysis for the revision was performed in October 2019. MAIN OUTCOMES AND MEASURES The primary outcome was time to transition from low (below the treatment threshold) to high fracture risk (treatment-qualifying risk score using osteoporosis clinical practice guidelines strategies for Canada, the United States, and the United Kingdom). RESULTS The study population consisted of 10 564 individuals (94.1% women; mean [SD] age at baseline, 63.2 [8.2] years). At the time of reassessment (a mean [SD] interval of 5.2 [2.9] yearsbetween initial and subsequent fracture risk assessment), 690 (6.6%) had reached the fixed major osteoporotic fracture treatment threshold of 20%, 1546 (16.2%) had reached the fixed hip treatment threshold of 3%, and 932 (9.4%) had reached the age-dependent major osteoporotic fracture treatment threshold. Among those below 25% of the treatment threshold at baseline for each guideline, few (0%-3.0%) reached guidelines-defined high fracture risk at follow-up. In contrast, among those at the upper end of the scale for each guideline (75%-99% of the treatment threshold at baseline), 30.6% to 74.4% reached guidelines-defined high fracture risk. An increased number of clinical risk factors was associated with increased likelihood of reaching guidelines-defined high fracture risk (range for 3 guidelines, 17.1%-28.2%) compared with unchanged or decreased clinical risk factors (range for 3 guidelines, 3.3%-12.8%) (P < .001). Estimated time for 10% of the population to reach treatment-qualifying high fracture risk ranged from fewer than 3 years to more than 15 years. CONCLUSIONS AND RELEVANCEThe findings suggest that baseline fracture risk (as a fraction of the treatment threshold) and change in clinical risk factors can identify individuals with low and high probability of guidelines-defined high fracture risk during follow-up, thereby potentially helping to inform the reassessment interval. Question What is the optimal reassessment interval to detect high fracture risk for those who do not meet the treatment threshold at baseline? Findings In this cohort study of 10 564 individuals, after a mean interval of 5.2 years between initial and subsequent fracture risk a...

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“…Besides dealing with private gain, personal advantages and other potential conflicts of interests, their responsibilities include the wisely use of health care resources, as well as the duty to guarantee the patients’ best interests [2, 3]. In a situation of pressure from patients to order more tests, it is also difficult for the physician to maintain the right cost-conscious behavior [4–6]. To maintain the base of medicine’s social contract, in times of conflict of interests, physicians need continuous education, exercising the principles of professionalism, enhancing their personal commitment to patients’ welfare and collectivity.…”

Section: Introductionmentioning

confidence: 99%

Translation, transcultural adaptation, and validation of the role-modeling cost-conscious behaviors scale

et al. 2019

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Background Training in the use of cost-conscious strategies for medical students may prepare new physicians to deliver health care in a more sustainable way. Recently, a role-modeling cost-conscious behaviors scale (RMCCBS) was developed for assessing students’ perceptions of their teachers’ attitudes to cost consciousness. We aimed to translate the RMCCBS into Brazilian Portuguese, adapt the scale, transculturally, and validate it. Methods We adopted rigorous methodological approaches for translating, transculturally adapting and validating the original scale English version into Brazilian Portuguese. We invited all 400 undergraduate medical students enrolled in the 5th and 6th years of a medical course in Northeast Brazil between January and March 2017 to participate. Of the 400 students, 281 accepted to take part in the study. We analyzed the collected data using the SPSS software version 21 and structural equation modeling (SEM) was performed using AMOS SPSS version 18. We conducted exploratory factor analysis (EFA), varimax rotation, with Kaiser Normalization and Principal Axis Factoring extraction method. We conducted confirmatory factor analysis (CFA), using the SEM. We used the following indexes of adherence of the model: Comparative fit index (CFI), Goodness-of-fit index (GFI) and Tucker-Lewis Index (TLI). We considered the Bayesian Information Criterion (BIC) for Sample-size adjusted. The root mean square error of approximation was calculated. Values below 0.08 were considered acceptable. Composite reliability analyzes were performed to evaluate the accuracy of the instrument. Values above 0.70 were considered satisfactory. Results Of the 281 undergraduate medical students, 195 (69.3%) were female. Mean age of participants was 25.0 ± 2.6 years. In the EFA, the KMO was 0.720 and the Bartlett sphericity test was significant ( p < 0.001). We conducted the EFA into two factors: role-modeling cost-conscious behaviors in health (seven items) and health waste behaviors (six items). The 13 item-scale was submitted to composite reliability analyzes, obtaining values of 0.813 and 0.761 for the role-modeling cost-conscious behaviors and the health waste behaviors factors, respectively. Conclusions We concluded that the cost-conscious behaviors scale has good psychometric properties and is a valid and reliable instrument for evaluating medical students’ perception of their teachers’ cost-conscious behaviors.

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Physician Cost Consciousness and Use of Low-Value Clinical Services

Cited by 19 publications

References 16 publications

Determinants for the use and de-implementation of low-value care in health care: a scoping review

Determinants for the use and de-implementation of low-value care in health care: a scoping review

Reassessment Intervals for Transition From Low to High Fracture Risk Among Adults Older Than 50 Years

Translation, transcultural adaptation, and validation of the role-modeling cost-conscious behaviors scale

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