Understanding type 2 diabetes mellitus screening practices among primary care physicians: a qualitative chart-stimulated recall study

Our team, which consisted of 3 primary care physician health services researchers, 1 fulltime primary care clinician, and 2 preclinical medical students, invited Internal Medicine physicians (n = 50), Family Medicine physicians (n = 39), nurse practitioners (n = 2), and physician assistants (n = 5) from 14 UMHS primary care practices to participate in a study about T2DM screening practices. We excluded trainees and clinicians with less than 0.5 full time equivalents devoted to outpatient clinical practice. Study invitation letters were sent by email, and informed providers that the primary aim of this study was to explore the factors that influence providers’ decisions to screen for T2DM.

Among clinicians who consented to study participation we conducted chart-stimulated recall (CSR) interviews, a methodology used to assess clinical decision-making processes [12, 13]. During CSR interviews, a clinician uses his or her own documentation to answer questions and explain the rationale for specific clinical decisions. A significant strength of this approach – which has been used to examine physician decisions about screening for colorectal cancer [14] and screening for prostate cancer [15] – is that it examines a physician’s own recent clinical decisions, which could provide more valid data on their clinical decision making than assessments of how they might respond to hypothetical clinical scenarios.

Twenty-five physicians responded to our recruitment e-mail and agreed to participate in our study. We planned to conduct a minimum of 20 interviews with additional interviews to be conducted only if data saturation was not achieved at this point. Prior to each CSR interview, one investigator (DH) reviewed in the electronic health record (EHR) each physician’s clinical encounters from the previous 2 weeks to identify visits for non-diabetic patients 45 years of age and older who were candidates for screening for T2DM at their visit and thus eligible for inclusion in the CSR interviews. We focused on patients 45 years of age and older for 2 reasons. First, the American Diabetes Association (ADA) recommends screening all individuals over the age of 45 for T2DM regardless of other risk factors; therefore an age-based focus allowed us to easily identify patients for whom the ADA recommends periodic T2DM screening. Second, this age-based criterion was more feasible to implement in the context of the EHR than other more detailed criteria for which the ADA recommends screening for T2DM, such as being less than 45 years of age and overweight with at least one additional risk factor for T2DM [16].

While both the ADA and the USPSTF recommend routine screening for T2DM among at-risk individuals, we used the ADA’s screening criteria because at the time of our interviews they were broader than the 2008 USPSTF criteria [17]. The USPSTF has since issued revised screening guidelines (disseminated in October 2015), but these were released after completion of all CSR interviews. We did not sample patients who had already been screened for T2DM within the previous year, as most non-diabetic patients do not need to be screened more than annually [16] and this study was not designed to explore reasons for over-screening.

To facilitate discussion of the range of factors that influence physicians’ decisions to screen for T2DM, we selected in approximately equal numbers encounters in which patients appeared (using the available information in the EHR) to have been screened for T2DM or not screened for T2DM. We classified the following as screening tests for T2DM, based on the ADA guidelines: hemoglobin A1c (HbA1c) tests, oral glucose tolerance tests (OGTTs), and fasting blood glucose (FBG) tests [16]. Because blood glucose tests at our institution are not routinely labeled as “fasting,” we classified blood glucose tests (drawn either in isolation or as part of a metabolic panel) as being fasting if they were obtained before 11 a.m. or drawn at the same time as a lipid panel that had been labeled in the EHR as fasting.

We also sampled in approximately equal numbers encounters in which patients were seen for either health maintenance examinations (HMEs) or return visits (RVs). We focused on both HMEs and RVs because there is debate about the utility of annual HMEs [18‐20] and physicians have been encouraged to consider providing opportunistic preventive screenings at non-HME visits [21‐23]. We excluded urgent care visits because in our institution these are typically focused, single-problem visits in which patients are commonly seen by clinicians other than their own primary care clinician.

Using this approach, for each clinician we aimed to select 12 encounters (i.e., roughly 3 each for HMEs with screening, HMEs without screening, RVs with screening, and RVs without screening) from the previous 2 weeks to potentially be discussed during the CSR interview. A goal of 12 encounters for each physician provided the opportunity to skip a particular encounter during the interview in the event that the clinician did not recall the encounter, while still permitting discussion of at least 6 separate patient encounters which has previously been shown sufficient to yield a valid and reliable assessment of practice patterns [24].

Interviews were conducted by trained preclinical medical students (DN, EM) and lasted approximately 30 min in duration. During the CSR interviews, physicians were first asked whether they screened each patient for T2DM and what factors influenced this decision. Our questions about reasons for the physician’s decision were guided by whether the physician stated they had or had not screened the patient for T2DM, rather than how the patient had been classified in our purposive sampling. For example, if it appeared from the EHR that the physician had screened the patient for T2DM, but the physician stated that they had not screened the patient for T2DM, then the physician was asked why they had not screened the patient for T2DM. Conversely, if a patient had been sampled as having not been screened (e.g., because they had a random glucose), but the physician said they had screened the patient for T2DM, we asked the physician why they screened the patient (even though the test chosen was not an ADA-recommended test). This approach allowed us to focus on physicians’ decision making processes irrespective of the outcome of that process.

When a screening test result was available for review (i.e., there was a lab result for a screening test that had been ordered at that visit), physicians were asked how they interpreted the result, whether and how they communicated the result to the patient, and what they communicated to the patient about the result. Following the CSR interview, physicians were also asked general questions regarding barriers to T2DM screening. Physicians had access to their EHR documentation during the interview. The interview guide was derived from previous CSR studies [14, 15] and is provided in the Additional file 1.

For each interview, physicians received a $50 gift card. The study was approved by the Institutional Review Board at the University of Michigan Medical School.

All interviews were audio-recorded and transcribed verbatim. Three members of the research team (DH, DN, JK) independently reviewed a subset of transcripts. The transcripts were de-identified prior to data analysis to minimize the potential for biased interpretation of the data. Codes and definitions were generated during consensus conferences using directed content analysis [25]. Specifically, initial codes were created to reflect the main topics in the interview guide (e.g. decision to screen or not screen patients for T2DM), and additional codes were subsequently generated to reflect the patterns and themes that emerged from the data [26]. Once the coding scheme was established, two investigators (DH, DN) independently coded each transcript. These investigators then met to review their coding and resolve all differences. Few new themes emerged after coding 12 transcripts and no new themes emerged after coding 16 transcripts. Given that we reached data saturation [27, 28], we did not conduct additional interviews following the 20 interviews. All transcripts were coded in Dedoose, a software program for qualitative analysis.

The following data were abstracted from the EHR for each patient after the interviews were completed: age; sex; race; ethnicity; BMI; risk factors for T2DM documented in the patient’s problem list such as hypertension, hyperlipidemia, cardiovascular disease, prediabetes, history of gestational diabetes or polycystic ovarian disease.

For the 63 patients who were not screened for T2DM, the most common reasons for not screening that physicians cited were knowledge of a previous normal screening test (49%) and the visit being for a reason other than a health maintenance examination (48%). Clinicians frequently cited more than one reason for not screening, and additional reasons are shown in Table 2.

For the 71 patients who were screened for T2DM, the most common reasons for screening that physicians cited were knowledge of a previously abnormal screening test for T2DM (49%), the patient being overweight or obese (42%), and patient age (38%). Two physicians specifically mentioned age ≥ 45 years as a screening criterion; others referenced the patient’s actual age (e.g. “she is 60 years old”) or noted that “the risk of diabetes goes up as we get older.” Clinicians often cited multiple reasons for screening, and these additional reasons are shown in Table 3.

Among the 71 patients who were screened for T2DM, the most commonly ordered screening tests were a laboratory HbA1c (n = 29, 40.8%) and a fasting blood glucose (n = 23, 32.4%). Four patients (5%) were screened with a point-of-care HbA1c, and 8 patients were screened with a random blood glucose (i.e., a blood glucose drawn after 11 a.m.). Seven patients (9.9%) had more than one screening test ordered (i.e., both a fasting blood glucose and an HbA1c). No physician ordered an OGTT to screen for T2DM. Physicians reported ordering an HbA1c test for reasons such as: “it is more familiar and comfortable,” “it is a little more reliable,” “patients don’t need to be fasting” and “it gives a better [overall] picture.” Physicians ordered a fasting blood glucose – either in isolation or as part of a metabolic panel – if the patient had already been fasting for another test (e.g., a fasting lipid panel) or if the physician wanted to concurrently evaluate other components of the metabolic panel (e.g., electrolytes or renal function).

Of the 71 patients for whom screening tests for T2DM were ordered, 50 had screening test results available in the EHR for review at the time of the interview. Based on the ADA guidelines,[29] 24 patients had screening test results that showed prediabetes, and 26 patients had screening test results that were normal. None of the sampled patients were found to have a new diagnosis of T2DM. Physicians discussed 47 of the 50 available test results, and of these correctly classified the majority (42, 89%) of the screening test results.

Physicians communicated 95% of screening test results to patients. Most communications occurred by mailed letter or secure electronic messaging through the health system’s patient portal (69%). Communication occurred by phone when either the screening test or another laboratory study was abnormal (16%); such telephone communications were always performed by a nurse. Communication occurred during an office visit only if the patient had laboratory tests performed prior to the encounter (15%).

Among patients found to have prediabetes, the content of communications focused mostly on diet and exercise, often with offers of referral to a nutritionist. For example, one physician stated, “I told her…diet and exercise would be the key. [We] can also offer referral to our nutritionist for pre-diabetes counseling, if she would like.” In many cases, physicians’ recommendations to patients were general and lacked specific goals or targets. An example of this was a physician who recommended, “just to continue with, what we call…lifestyle modifications. You know, a little bit of exercise, healthy diet, stuff like that.” Some physicians minimized the significance of screening test results if they were at the lower end of the prediabetic range. For example, one physician said, “[The blood glucose] is slightly high at 101. What I told [him] is that he is just out normal range, but not in a concerning…urgent way, and that we’ll talk about it in his next visit.” Another said, “[The HbA1c] is stable from a year ago at 6.2%, which I feel is consistent with pre-diabetes and puts her at a high risk of developing diabetes…[I told her] that the lab looks stable…I kept it very short and sweet. I probably could have said something more about lifestyle.”

Communications to patients with prediabetes never included specific, evidence-based treatment recommendations such as DPP participation or pharmacotherapy with metformin [30]. One physician said that “we talked about the diabetes prevention trial, and we set 150 min of exercise for her goal [per] week,” but she did not specifically recommend or refer the patient to a DPP. None of the physicians started metformin for patients whose test results were in the prediabetic range, although one mentioned that a patient with prediabetes was already using metformin and a few acknowledged that metformin might be an option for such patients. One physician said, “I know there is some data talking about using metformin early on people like this. I don’t like to add more medications than I have [to]. So I don’t typically do that until the A1C starts to get up to closer to 6.5.”

First, we conducted our study in a single academic center and our findings may not generalize to all clinical environments. Second, it is possible that physicians with a particular interest in screening for T2DM may have been more likely to participate in the study, and there were no nurse practitioners or physician assistants who chose to participate. Third, none of the patients discussed in the CSR interviews were found to have T2DM through screening, thus limiting our insight into how physicians interpret and respond to such results. Fourth, physicians’ responses could have been influenced by recall or social desirability biases, though physician use of the EHR during interviews and our inquiries about recent visits by preclinical medical students aimed to mitigate the potential for such biases. Further, although physician access to the EHR at the time of the interview was intended to prompt recall of the encounter, it is possible that some physicians may have used EHR data to justify their decisions to screen or not screen a patient for T2DM. Finally, the USPSTF issued an updated recommendation for screening for T2DM following our study period, which could lead to changes in physician screening practices that we could not capture during this study.