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Abstract

Aims:

There is a paucity of efficient processes for collecting information in a primary care setting to connect patients afflicted with type 2 diabetes to valuable resources. The objective of this research project was to develop a Comprehensive Diabetes Assessment (CDA) instrument which could be used to assess patients’ barriers to best outcomes.

Methods:

We reviewed published literature and online compilations for validated tools assessing threats to optimal diabetes self-management. We conducted focus groups with patients, clinicians, and service providers who provided feedback on the tools’ appropriateness and feasibility. We aggregated the favored tools and did cognitive testing with patients to assess understanding and affective response to the instrument.

Results:

Five focus groups involved varied stakeholders in Baltimore, MD and Honolulu, HI. We presented 2 tools assessing knowledge barriers, 3 tools assessing psychological barriers, 4 tools assessing literacy, and 1 numeracy. The final instrument included 6 multi-part items and takes 3 minutes to complete. Cognitive interviewing with 8 patients in Baltimore and 8 in Hawaii confirmed that the instrument is understandable, quick to complete, and is acceptable to patients.

Conclusions:

Because of the complexity of self-management of diabetes, we suggest that this CDA instrument, plus a social needs assessment, should be administered at least annually and at times of clinical deterioration. We anticipate the instrument will be proven valuable in connecting patients to services from which they will benefit.

Keywords

health equity minority populations diabetes mellitus disease self-management social determinants of health

Type 2 diabetes is, unquestionably, a challenging illness for patients given the requirement for vigilance with diet, exercise, and medications, extensive screening requirements to identify complications of the disease, and the high probability of complications. Among patients with chronic diseases, outcomes are often adversely impacted when individuals have financial insecurity, food insecurity, and other adverse social determinants of health. For individuals with diabetes, this is often mediated by difficulty with adherence to medication and diet treatment plans.¹ Additional barriers to disease self-management, such as lower health literacy, depression, and knowledge deficits can compound the impact of social determinants of health and impede a patient’s successful engagement in diabetes care. Screening to identify patients’ unique barriers is essential to connecting them to services. In most clinical settings, there are not yet efficient processes for collecting the information that will allow deep phenotyping of patients including their social and self-management needs. We aimed to develop a screening instrument for use in primary care to assess individuals’ barriers to achieving their best diabetes outcomes. We aimed to identify existing validated tools and prepare an efficient Comprehensive Diabetes Assessment (CDA) instrument to identify the needs of individuals with type 2 diabetes.

Johns Hopkins investigators partnered with investigators at Kaiser Permanente Hawaii to increase the racial and ethnic diversity of the patients and clinical stakeholders to improve the generalizability of the instrument. Our approach was motivated by a framework developed for use in the Veterans Administration (Figure 1).² Given that physical/disease states of patients can be known from the electronic health record, and that social determinants of health are being actively collected by our respective institutions, we focus on the remaining barriers to disease self-management. This led us to prioritize identification of tools that measure knowledge, skills, literacy, and psychological barriers to diabetes self-management.

Figure 1.

Key domains for phenotype

Methods

We Received Institutional Review Board Approval From Each site

Literature review

We aimed to review published literature and online compilations to identify validated tools designed to measure barriers to diabetes self-care. We began by reviewing the cited references of an existing umbrella review of systematic reviews about factors influencing diabetes self-management.⁴ Among these references, we identified tools that have been used to measure self-management and barriers to self-management. From these, we also identified a rich, online compilation of tools compilation of tools from the Social Interventions Research and Evaluation Network (SIREN).⁵

Tool selection

Our research team was assembled to have a breadth of expertise including diabetes care (JS, SP, and RD), psychology (KB), and behavioral sciences (MT). We triaged the identified tools according to their intent to measure diabetes knowledge, diabetes self-management skills, health literacy, and psychological barriers to self-care including depression. We consulted with staff members in our institution’s Center for Population Health, who were simultaneously reviewing tools for measuring social determinants of health population for use in its initiatives. Our research team sought tools that were developed specifically for use with individuals with type 2 diabetes. If there were no tools in a given domain meeting that criterion, we reviewed tools validated for use in a general patient population. The SIREN network includes a Social Needs Screening Tools Comparison table among their online products, which facilitated the review of existing tools. The team members came to consensus through discussion on the tools to prioritize for presentation to the focus groups. We restricted the tools to those published in English and that described a rigorous validation process.

Focus groups

We assembled focus groups to offer feedback about the candidate tools. Focus groups were formed to include patients with type 2 diabetes and, separately, clinicians. The Maryland participants and the Hawaii participants were engaged, separately, via Zoom. The principal investigators of each site conducted the focus groups in their respective cities. The participants were shown the candidate tools, in the MURAL application (a digital whiteboard), and asked to provide verbal feedback on each tools’ appropriateness, feasibility for use in a primary care setting, and the expected value of the gathered information for directing patients to services. The meetings were recorded and automatically transcribed for our reference.

Cognitive interviewing

Based on the feedback from the stakeholder focus groups, we selected the most preferred tools, which we assembled as the CDA instrument. We included only full tools—not isolated questions from the identified tools. We used Qualtrics software (v11.0.3) to create on online survey instrument, which was also accessible via smartphones. We recruited patients with type 2 diabetes from both clinical sites and conducted cognitive interviewing in person or via Zoom. As they completed the instrument, team members delivered cognitive probes to assess whether each question was understandable or whether any question generates an aversive response in the participant (Supplemental Appendix 1) We also asked each participant to comment on their experience with the instrument (eg, length and acceptability), and to suggest how often it should be offered. We probed to understand whether participants expected the instrument to be useful to their care, who should access the results, and how the results should be used.

Results

We identified relevant published literature and online compilations of tools and instruments, including those of SIREN, the social interventions research and evaluation network.^1,4
-24 We also identified many tools for assessing adverse social determinants of health; however, these were set aside and not included in the CDA instrument. We recognized that many health systems, including both of the research sites, are establishing system-wide processes for screening for social needs and we sought not to duplicate efforts of our respective health systems.

We recognized early in the process that the tools and scales that we were reviewing were largely developed to predict an outcome of interest or to indicate the impact of an intervention. We were more interested in identifying those that function as needs assessment tools. Thus, the tools that were selected to share with the focus groups included: 1 tool, with 2 parts, about self-management challenges driven by knowledge gaps and self-efficacy barriers,²⁴ 3 tools about psychological barriers,^18
-20 4 tools about literacy,^8
-11,19 and 1 numeracy tool²³ (Supplemental Appendix 2).

We conducted 5 online focus groups with our stakeholders. There were 14 non-patient participants and 16 diverse patient participants recruited from Baltimore, MD and Waimanalo, HI. All of the patient participants in Hawaii were indigenous to Hawaii; the Baltimore patients reflected the demography of Baltimore City and were predominantly non-Hispanic black. The majority of the Hawaiian staff participants were native Hawaiian. The non-patient participants across sites included primary care doctors, an endocrinologist, diabetes educators, dieticians, a patient experience officer, a pharmacist, and staff members responsible for making referrals to community services.

The feedback from the participants allowed us to select the most user-centered tools. Illustrative comments from the focus groups are in Supplemental Appendices 3a and 3b. The patient stakeholders saw overwhelming value in the questions proposed; they proposed that primary care clinicians should confirm their needs and interest in interventions before making referrals to services. They were comfortable with these responses being included in their health records for access by their care team. One of the most common areas of feedback focused on the need for the CDA instrument to be available electronically and accessible via phone or iPad, however, assessment at the physician’s office was still felt to be the most appropriate. All stakeholders felt that a social needs assessment would be valuable (although tools were not presented for discussion); however, only if interventions were readily available. The clinician stakeholders believed the tools to valuable, although expected that most patients would be referred for diabetes education regardless of the responses. They suggested that numeracy assessment, while important, is probably not necessary as a functional assessment of ability to adjust insulin is more valuable. The clinicians felt that having the collected information available in the chart will help the diabetes educators to target their interventions.

Based on the input from these focus groups, the final instrument includes validated tools that include 6 multi-part questions (Table 1). After agreement on the topics included in the CDA instrument, cognitive interviewing was completed with 8 patients in Baltimore and 8 patients in Waimanalo to assess the feasibility and acceptability of the CDA instrument. Cognitive interviewing confirmed that the instrument is understandable, quick to complete (approximately 3 minutes), and acceptable to patients.

Table 1.

Comprehensive Diabetes Assessment.

	I don’t understand at all	I understand a little bit	I understand pretty well	I understand completely
How can we help? We know that diabetes is a hard diagnosis to have. Your doctor wants to make this easier for you. [Your institution] has many services that may be useful, but we need to know what you need. Please answer these 6 questions (takes 3 minutes or less) so that your doctor can make these connections for you. How often do you need someone to help you when you are given information to read by your doctor, nurse, or pharmacist? (From: Chinn and McCarthy¹¹) ❍ Rarely ❍ Sometimes ❍ Often When you need help, can you easily get hold of someone to assist you? (From: Chinn and McCarthy¹¹) ❍ Rarely ❍ Sometimes ❍ Often ❍ Not Applicable Do you need help filling out official documents? (From: Chinn and McCarthy¹¹) ❍ Rarely ❍ Sometimes ❍ Often
Please rate how well you understand each of the following areas of diabetes care: (Described in Zulman et al²⁴).
How to take your insulin or other medications	❍	❍	❍	❍
What each of your prescribed medications do	❍	❍	❍	❍
How to choose the food you should eat	❍	❍	❍	❍
How to read nutrition labels	❍	❍	❍	❍
How to exercise	❍	❍	❍	❍
How and when to test your blood sugar	❍	❍	❍	❍
How to care for your feet	❍	❍	❍	❍
What the complications of diabetes are	❍	❍	❍	❍
What to do for symptoms of low blood sugar	❍	❍	❍	❍
What your target blood sugar values should be	❍	❍	❍	❍
Over the past 6 months, how difficult has it been to do each of the following exactly as the doctor who takes care of your diabetes suggested? (Describe in Zulman et al²⁴).
	So difficult: that I couldn’t do it at all	Very difficult: I hardly ever do this	Difficult: but I managed some of the time	Not difficult: I managed most of the time	Not difficult: I got it exactly right
Taking diabetes medications (pills and/or insulin)	❍	❍	❍	❍	❍
Exercising regularly	❍	❍	❍	❍	❍
Following your recommended eating plan	❍	❍	❍	❍	❍
Checking your blood sugar	❍	❍	❍	❍	❍
Checking your feet for wounds or sores	❍	❍	❍	❍	❍
Which of the following diabetes issues are currently a problem for you? (From McGuire et al¹⁸).
	Serious problem	Somewhat serious problem	Moderate problem	Minor problem	No problem at all
Feeling scared when you think about living with diabetes	❍	❍	❍	❍	❍
Feeling depressed when you think about living with diabetes	❍	❍	❍	❍	❍
Feeling that diabetes is taking up too much of your mental and physical energy every day	❍	❍	❍	❍	❍
Coping with complications of diabetes	❍	❍	❍	❍	❍
Worrying about the future and the possibility of serious complications	❍	❍	❍	❍	❍

Discussion

We rigorously selected tools, with meaningful input from patients and professionals, to yield an efficient instrument by which to screen patients with type 2 diabetes. Our instrument assesses literacy, diabetes knowledge, confidence with diabetes skills, and mood-associated issues impacting diabetes management. We did not identify any existing single instrument for use in a clinical setting that can expediently assess these needs and foster connection to services.

The literacy screener is a subset of the items from the All Aspects of Health Literacy Scale (AAHLS) that is specifically designed to assess functional health literacy. This tool was developed in 2013 with participation of a multiethnic, low-income population in the United Kingdom.¹¹ The designers of the AAHLS believe that health literacy is a “distributed competency” where patients may function competently if they have ready access to support, despite literacy challenges. This tool does have a specific point cutoff for the subscale containing the 3 questions assessing functional health literacy, expecting that the users of the tool may establish the cutoffs according to the usage. The knowledge and self-efficacy questions that we included were used in the Health and Retirement Survey (HRS) when administered to a subgroup of individuals with type 2 diabetes in 2003.⁶ The self-management questions were developed by Heisler et al,¹⁴ and the self-efficacy questions were adapted from work by Fitzgerald et al.¹² The HRS survey responses were evaluated by Zulman et al in 2012,²⁴ who confirmed that poor self-management ratings correlate with worse glycemic control cross-sectionally and are strongly associated with worsening perceived diabetes status over 1 year. The psychosocial screener that we incorporated was the Problem Areas in Diabetes Scale (PAID-5).¹⁸ McGuire et al¹⁸ created this 5-item version of the PAID tool, which has 20 items, and validated it against the longer tool. The authors suggest that a score of 8 or above is the appropriate threshold for identifying individuals with possible diabetes-related emotional distress that warrants further assessment.

Because of the complexity of self-management of diabetes, and the impact of psychosocial impairment on self-management, we suggest that this CDA, plus a social needs assessment, should be administered at least annually and at times of clinical deterioration, such as hospitalization or worsening of glycemic control. Individuals cannot be appropriately directed to services that will help them overcome their barriers unless they are identified as having these barriers. We anticipate that this stream-lined instrument will prove valuable in connecting patients to services from which they will benefit. The entire process, then, of screening, referral, and delivery of services needs rigorous evaluation.

Each health system or practice is likely to know best where their patients can have their needs met. We anticipate that patients with self-management challenges might be directed to intensive diabetes education programs led by certified diabetes and education specialists. This might require supplementation by peer support or visits by community health workers. We expect that individuals with limited self-efficacy might respond well to behavioral health specialists for coaching. Those reporting depression or with significant impairment in mood might require a psychologist’s or clinical social worker’s care. The screen for health literacy will inform all who are involved in the patients care about special needs—the diabetes educators and behavioral health specialists will know upon receiving the referral that the patient may need additional support.

We note, too, that these resources are not uniformly available. Indeed, many primary care clinics do not even have ready access to diabetes educators and these services may need to be subsumed by the primary care practice. We expect that implementation of the screening instrument and systematized awareness of the challenges of their patients with diabetes should allow practices to prioritize their accrual of appropriate resources or make high impact referrals to community-based services.

There were several limitations to this study. The assessment instrument focuses primarily on factors important to the care of patients with diabetes mellitus while avoiding topics being addressed through system wide efforts to identify social determinants of health. Further, although the project was conducted in 2 locations that serve very different populations, the focus groups were small and may not fully capture the experiences of individuals for whom this assessment might be appropriate. We do not intend for this to be used as a scale for research; we expect this to be valuable to the treating clinicians. Appropriate next steps should include using this instrument in primary care with careful evaluation of the implementation to assure that this is a high-value activity. There is a need to design the clinical processes that incorporate use of the instrument and then evaluate its use in practice. This evaluation may be done as a clinical trial or as an evaluation of the implementation of a new clinical protocol. Outcomes of interest may include rates of appropriate referrals, patient-experience with the instrument in practice, and clinical outcomes attributable to the instrument’s use.

In conclusion, the CDA was developed through an iterative process, first involving a thorough literature review and then the creation of an assessment tool, with input from focus groups involving diverse patients and clinicians. The purpose of this tool was to focus on barriers to optimal diabetes management that are not included in system wide tools that elicit social determinants of health. The CDA was found to be straight forward, timely, and acceptable to all participants. Future studies involving the CDA instrument should focus on the degree to which it improves the management of patients with type 2 diabetes.

Supplemental Material

sj-docx-1-jpc-10.1177_21501319231204590 – Supplemental material for Comprehensive Diabetes Assessment Instrument for Patients With Type 2 Diabetes

Supplemental material, sj-docx-1-jpc-10.1177_21501319231204590 for Comprehensive Diabetes Assessment Instrument for Patients With Type 2 Diabetes by Jodi Segal, Robert DeGrazia, Samantha Pitts, Kristal Brown and Maile Taualii in Journal of Primary Care & Community Health

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: From the Johns Hopkins Institute for Clinical and Translational Research, which is funded by the National Center for Advancing Translational Sciences (NCATS) through the Clinical and Translational Science Awards Program (5 UL1 TR003098-04).

ORCID iD

Jodi Segal

Supplemental Material

Supplemental material for this article is available online.

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Supplementary Material

Please find the following supplemental material available below.

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