Do doctors contribute to the social patterning of disease? The case of race/ethnic disparities in diabetes mellitus

The use of experimental vignette studies to identify drivers of variations in the delivery of health care: a scoping review

Background

Identifying how unwarranted variations in healthcare delivery arise is challenging. Experimental vignette studies can help, by isolating and manipulating potential drivers of differences in care. There is a lack of methodological and practical guidance on how to design and conduct these studies robustly. The aim of this study was to locate, methodologically assess, and synthesise the contribution of experimental vignette studies to the identification of drivers of unwarranted variations in healthcare delivery.

Methods

We used a scoping review approach. We searched MEDLINE, Embase, Web of Science and CINAHL databases (2007–2019) using terms relating to vignettes and variations in healthcare. We screened title/abstracts and full text to identify studies using experimental vignettes to examine drivers of variations in healthcare delivery. Included papers were assessed against a methodological framework synthesised from vignette study design recommendations within and beyond healthcare.

Results

We located 21 eligible studies. Study participants were almost exclusively clinicians (18/21). Vignettes were delivered via text (n = 6), pictures (n = 6), video (n = 6) or interactively, using face-to-face, telephone or online simulated consultations (n = 3). Few studies evaluated the credibility of vignettes, and many had flaws in their wider study design. Ten were of good methodological quality. Studies contributed to understanding variations in care, most commonly by testing hypotheses that could not be examined directly using real patients.

Conclusions

Experimental vignette studies can be an important methodological tool for identifying how unwarranted variations in care can arise. Flaws in study design or conduct can limit their credibility or produce biased results. Their full potential has yet to be realised.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01247-4.

Social disparities in patient safety in primary care: a systematic review

BACKGROUND

Patient safety is a quality indicator for primary care and it should be based on individual needs, and not differ among different social groups. Nevertheless, the attention on social disparities in patient safety has been mainly directed towards the hospital care, often overlooking the primary care setting. Therefore, this paper aims to synthesise social disparities in patient safety in the primary care setting.

METHODS

The Databases PubMed and Web of Science were searched for relevant studies published between January 1st 2006 and January 31st 2017. Papers investigating racial, gender and socioeconomic disparities in regards to administrative errors, diagnostic errors, medication errors and transition of care errors in primary care were included. No distinction in terms of participants' age was made.

RESULTS

Women and black patients are more likely to experience patient safety events in primary care, although it depends on the type of disease, treatment, and healthcare service. The available literature largely describes gender and ethnic disparities in the different patient safety domains whilst income and educational level are studied to a lesser extent.

CONCLUSIONS

The results of this systematic review suggest that vulnerable social groups are likely to experience adverse patient safety events in primary care. Enhancing family doctors' awareness of these inequities is a necessary first step to tackle them and improve patient safety for all patients. Future research should focus on social disparities in patient safety using socioeconomic indicators, such as income and education.

Does a Physician's Attitude toward a Patient with Mental Illness Affect Clinical Management of Diabetes? Results from a Mixed-Method Study

OBJECTIVE

To determine whether physician's attitudes toward patients with comorbid mental illness affect management of a chronic disease.

DATA SOURCE

A total of 256 primary care physicians interviewed in 2010.

STUDY DESIGN

This randomized factorial experiment entailed physicians observing video vignettes of patient-actors with poorly controlled diabetes. Patients were balanced across age, gender, race, and comorbidity (schizophrenia with bizarre or normal affect, depression, eczema).

DATA COLLECTION

Physicians completed structured and semistructured interviews plus chart notes about clinical management and attitudes.

PRINCIPAL FINDINGS

Physicians reported more negative attitudes for patients with schizophrenia with bizarre affect (SBA). There were few differences in clinical decisions measured quantitatively or in charting, but qualitative data revealed less trust of patients with SBA as reporters, with more reliance on sources other than engaging the patient in care. Physicians often alerted colleagues about SBA, thereby shaping expectations before interactions occurred.

CONCLUSIONS

Results are consistent with common stereotypes about people with serious mental illness. Vignettes did not include intentional indication of unreliable reporting or danger. Reducing health care disparities requires attention to subtle aspects of managing patients--particularly those with atypical affect--as seemingly slight differences could engender disparate patient experiences over time.

Undiagnosed diabetes from cross-sectional GP practice data: an approach to identify communities with high likelihood of undiagnosed diabetes

OBJECTIVES

To estimate undiagnosed diabetes prevalence from general practitioner (GP) practice data and identify areas with high levels of undiagnosed and diagnosed diabetes.

DESIGN

Data from the North-West Adelaide Health Survey (NWAHS) were used to develop a model which predicts total diabetes at a small area. This model was then applied to cross-sectional data from general practices to predict the total level of expected diabetes. The difference between total expected and already diagnosed diabetes was defined as undiagnosed diabetes prevalence and was estimated for each small area. The patterns of diagnosed and undiagnosed diabetes were mapped to highlight the areas of high prevalence.

SETTING

North-West Adelaide, Australia.

PARTICIPANTS

This study used two population samples-one from the de-identified GP practice data (n=9327 active patients, aged 18 years and over) and another from NWAHS (n=4056, aged 18 years and over).

MAIN OUTCOME MEASURES

Total diabetes prevalence, diagnosed and undiagnosed diabetes prevalence at GP practice and Statistical Area Level 1.

RESULTS

Overall, it was estimated that there was one case of undiagnosed diabetes for every 3-4 diagnosed cases among the 9327 active patients analysed. The highest prevalence of diagnosed diabetes was seen in areas of lower socioeconomic status. However, the prevalence of undiagnosed diabetes was substantially higher in the least disadvantaged areas.

CONCLUSIONS

The method can be used to estimate population prevalence of diabetes from general practices wherever these data are available. This approach both flags the possibility that undiagnosed diabetes may be a problem of less disadvantaged social groups, and provides a tool to identify areas with high levels of unmet need for diabetes care which would enable policy makers to apply geographic targeting of effective interventions.

Variations among primary care physicians in exercise advice, imaging, and analgesics for musculoskeletal pain: results from a factorial experiment

OBJECTIVE

To examine whether medical decisions regarding evaluation and management of musculoskeletal pain conditions varied systematically by characteristics of the patient or provider.

METHODS

We conducted a balanced factorial experiment among primary care physicians in the US. Physicians (n = 192) viewed 2 videos of different patients (actors) presenting with pain: undiagnosed sciatica symptoms or diagnosed knee osteoarthritis. Systematic variations in patient gender, socioeconomic status, and race and physician gender and experience (<20 versus ≥20 years in practice) permitted estimation of unconfounded effects. Analysis of variance was used to evaluate associations between patient or provider attributes and clinical decisions. Quality of decisions was defined based on the current recommendations of the American College of Rheumatology, American Pain Society, and clinical expert consensus.

RESULTS

Despite current recommendations, less than one-third of physicians would provide exercise advice (30.2% for osteoarthritis and 32.8% for sciatica). Physicians with fewer years in practice were more likely to provide advice on lifestyle changes, particularly exercise (P ≤ 0.01), and to prescribe nonsteroidal antiinflammatory drugs for pain relief, both of which were appropriate and consistent with current recommendations for care. Newer physicians ordered fewer tests, particularly basic laboratory investigations or urinalysis. Test ordering decreased as organizational emphasis on business or profits increased. Patient factors and physician gender had no consistent effects on pain evaluation or treatment.

CONCLUSION

Physician education on disease management recommendations regarding exercise and analgesics and implementation of quality measures may be useful, particularly for physicians with more years in practice.

Physician styles of decision-making for a complex condition: Type 2 diabetes with co-morbid mental illness

RATIONALE AIMS AND OBJECTIVES

Variation in physician decisions may reflect personal styles of decision-making, as opposed to singular clinical actions and these styles may be applied differently depending on patient complexity. The objective of this study is to examine clusters of physician decision-making for type 2 diabetes, overall and in the presence of a mental health co-morbidity.

METHOD

This randomized balanced factorial experiment presented video vignettes of a "patient" with diagnosed, but uncontrolled type 2 diabetes. "Patients" were systematically varied by age, sex, race and co-morbidity (depression, schizophrenia with normal or bizarre affect, eczema as control). Two hundred and fifty-six primary care physicians, balanced by gender and experience level, completed a structured interview about clinical management.

RESULTS

Cluster analysis identified 3 styles of diabetes management. "Minimalists" (n=84) performed fewer exams or tests compared to "middle of the road" physicians (n=84). "Interventionists" (n=88) suggested more medications and referrals. A second cluster analysis, without control for co-morbidities, identified an additional cluster of "information seekers" (n=15) who requested more additional information and referrals. Physicians ranking schizophrenia higher than diabetes on their problem list were more likely "minimalists" and none were "interventionists" or "information seekers".

CONCLUSIONS

Variations in clinical management encompass multiple clinical actions and physicians subtly shift these decision-making styles depending on patient co-morbidities. Physicians' practice styles may help explain persistent differences in patient care. Training and continuing education efforts to encourage physicians to implement evidence-based clinical practice should account for general styles of decision-making and for how physicians process complicating comorbidities.

An additional cause of health care disparities: the variable clinical decisions of primary care doctors

RATIONALE, AIMS AND OBJECTIVES

Decades of work on health disparities have culminated in identification of three contributors to variability in diagnosis and management of disease: (i) patient attributes; (ii) doctor's characteristics; and (iii) organizational factors. Understanding the relative influence of different contributors to variability in diagnosis and management of diabetes is important to improving quality and reducing disparities. This study was designed to examine the influence of patient, provider and organizational factors on the diagnosis and management of a major chronic disease - diabetes.

METHOD

A factorial experiment using video vignettes was conducted among n = 192 primary care doctors. Doctors were interviewed after viewing vignettes of (1) a 'patient' with symptoms strongly suggestive of diabetes and (2) an already diagnosed diabetes 'patient' with emerging peripheral neuropathy.

RESULTS

A total of 60.9% of doctors identified diabetes as the correct diagnosis, with significant variations depending on the patients' race/ethnicity. Many doctors offered competing diagnoses with high levels of certainty. For the 'patient' with emerging peripheral neuropathy, 42.2% of doctors would do all essential components of a foot examination, while 21.9% would do none.

CONCLUSIONS

That half of all diabetes in the United States remains undiagnosed is unsurprising given only 60.9% of doctors would diagnose it when the condition is strongly suggested, and nearly one-quarter suspecting diabetes would not order tests necessary to confirm it. The diagnosis of diabetes is significantly influenced by a patient's race/ethnicity, and clinical management (specifically for foot neuropathy) is influenced by patient socio-economic status (SES), doctor's gender and access to clinical guidelines.

Cohort profile: the Boston Area Community Health (BACH) survey

The Boston Area Community Health (BACH) Survey is a community-based, random sample, epidemiologic cohort of n = 5502 Boston (MA) residents. The baseline BACH Survey (2002-05) was designed to explore the mechanisms conferring increased health risks on minority populations with a particular focus on urologic signs/symptoms and type 2 diabetes. To this end, the cohort was designed to include adequate numbers of US racial/ethnic minorities (Black, Hispanic, White), both men and women, across a broad age of distribution. Follow-up surveys were conducted ∼5 (BACH II, 2008) and 7 (BACH III, 2010) years later, which allows for both within- and between-person comparisons over time. The BACH Survey's measures were designed to cover the following seven broad categories: socio-demographics, health care access/utilization, lifestyles, psychosocial factors, health status, physical measures and biochemical parameters. The breadth of measures has allowed BACH researchers to identify disparities and quantify contributions to social disparities in a number of health conditions including urologic conditions (e.g. nocturia, lower urinary tract symptoms, prostatitis), type 2 diabetes, obesity, bone mineral content and density, and physical function. BACH I data are available through the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repositories (www.niddkrepository.org). Further inquiries can be made through the New England Research Institutes Inc. website (www.neriscience.com/epidemiology).