Need For Diabetes Care Research Articles

Profiles of diabetes care, control and complications in Benghazi, Libya 2020: A cross sectional study

Background: Diabetes mellitus is one of the growing health problems worldwide. Comprehensive medical evaluation, screening for complications, and proper diabetes care are crucial to improve outcome. Objectives: We aimed to study the profile of diabetes in Benghazi city and assess the changes since the last study of 2002. Patients and Methods: This study is a descriptive cross-sectional study of 504 persons with diabetes who were following at Benghazi diabetes center during June and July in 2020. Results: The age was, mean ± standard deviation; 57.8 ±12.3 years. with equal sex split. A quarter (24.8%) of participants graduated from a university/college. About half of the patients were obese (48.4%) Hypertension and dyslipidemia were found in 35.1% and 42.1%. respectively. The mean glycated hemoglobin A1c (HbA1c) was 8.3% ±1.7%. Self-monitoring of blood glucose (SMBG) was practiced by 20.2% of all patients, Less than two thirds (63.5%) of all patients had diabetes eye screening within the previous year. However, none of the participants had ever had a comprehensive feet examination. Ramadan fasting was observed by most of participants (95.4%). Conclusions: There is an improvement regarding annual eye examination, taking the medications regularly, SMBG, assessment of lipid profile, and regular follow-up with HbA1c in comparison with the practice in 2002. On the other hand, there is a decline in having comprehensive feet examination, practicing regular exercise, and diet control. The uncovered gaps in diabetes care need urgent attention.

Factors affecting the likelihood of a hospitalization following a diabetes-related emergency department visit: A regional and urban-rural analysis.

The objective of this study is to examine place-based and individual-level predictors of diabetes-related hospitalizations that stem from emergency department (ED) visits. We conducted a pooled cross-sectional analysis of the National Inpatient Sample (NIS) for 2009 to 2014 to identify ED-initiated hospitalizations that were driven by the need for diabetes care. The odds of an ED-initiated diabetes-related hospitalization were assessed for the United States as a whole and separately for each census region. Nationally, residents of noncore areas (odds ratio [OR] 1.10; CI 1.08, 1.12), the South (OR 8.03; CI 6.84, 9.42), Blacks (OR 2.49; CI 2.47, 2.52), Hispanics (OR 2.32; CI 2.29, 2.35), Asians or Pacific Islanders (OR 1.20; CI 1.16, 1.23), Native Americans (OR 2.18; CI 2.10, 2.27), and the uninsured (OR 2.14; CI 2.11, 2.27) were significantly more likely to experience an ED-initiated hospitalization for diabetes care. Census region-stratified models showed that noncore residents of the South (OR 1.17; CI 1.14, 1.20) and Midwest (OR 1.06; CI 1.02, 1.11) had higher odds of a diabetes-related ED-initiated hospitalization. As continued efforts are made to reduce place-based disparities in diabetes care and management, targeted focus should be placed on residents of noncore areas in the South and Midwest, racial and ethnic minorities, as well as the uninsured population.

Health system performance for people with diabetes in 28 low- and middle-income countries: A cross-sectional study of nationally representative surveys.

BackgroundThe prevalence of diabetes is increasing rapidly in low- and middle-income countries (LMICs), urgently requiring detailed evidence to guide the response of health systems to this epidemic. In an effort to understand at what step in the diabetes care continuum individuals are lost to care, and how this varies between countries and population groups, this study examined health system performance for diabetes among adults in 28 LMICs using a cascade of care approach.Methods and findingsWe pooled individual participant data from nationally representative surveys done between 2008 and 2016 in 28 LMICs. Diabetes was defined as fasting plasma glucose ≥ 7.0 mmol/l (126 mg/dl), random plasma glucose ≥ 11.1 mmol/l (200 mg/dl), HbA1c ≥ 6.5%, or reporting to be taking medication for diabetes. Stages of the care cascade were as follows: tested, diagnosed, lifestyle advice and/or medication given (“treated”), and controlled (HbA1c < 8.0% or equivalent). We stratified cascades of care by country, geographic region, World Bank income group, and individual-level characteristics (age, sex, educational attainment, household wealth quintile, and body mass index [BMI]). We then used logistic regression models with country-level fixed effects to evaluate predictors of (1) testing, (2) treatment, and (3) control. The final sample included 847,413 adults in 28 LMICs (8 low income, 9 lower-middle income, 11 upper-middle income). Survey sample size ranged from 824 in Guyana to 750,451 in India. The prevalence of diabetes was 8.8% (95% CI: 8.2%–9.5%), and the prevalence of undiagnosed diabetes was 4.8% (95% CI: 4.5%–5.2%). Health system performance for management of diabetes showed large losses to care at the stage of being tested, and low rates of diabetes control. Total unmet need for diabetes care (defined as the sum of those not tested, tested but undiagnosed, diagnosed but untreated, and treated but with diabetes not controlled) was 77.0% (95% CI: 74.9%–78.9%). Performance along the care cascade was significantly better in upper-middle income countries, but across all World Bank income groups, only half of participants with diabetes who were tested achieved diabetes control. Greater age, educational attainment, and BMI were associated with higher odds of being tested, being treated, and achieving control. The limitations of this study included the use of a single glucose measurement to assess diabetes, differences in the approach to wealth measurement across surveys, and variation in the date of the surveys.ConclusionsThe study uncovered poor management of diabetes along the care cascade, indicating large unmet need for diabetes care across 28 LMICs. Performance across the care cascade varied by World Bank income group and individual-level characteristics, particularly age, educational attainment, and BMI. This policy-relevant analysis can inform country-specific interventions and offers a baseline by which future progress can be measured.

Prevalence and unmet need for diabetes care across the care continuum in a national sample of South African adults: Evidence from the SANHANES-1, 2011-2012.

South Africa faces an epidemic of chronic non-communicable diseases (NCDs), yet national surveillance is limited due to the lack of recent data. We used data from the first comprehensive national survey on NCDs—the South African National Health and Nutrition Examination Survey (SANHANES-1 (2011–2012))—to evaluate the prevalence of and health system response to diabetes through a diabetes care cascade. We defined diabetes as a Hemoglobin A1c equal to or above 6.5% or currently on treatment for diabetes. We constructed a diabetes care cascade by categorizing the population with diabetes into those who were unscreened, screened but undiagnosed, diagnosed but untreated, treated but uncontrolled, and treated and controlled. We then used multivariable logistic regression models to explore factors associated with diagnosed and undiagnosed diabetes. The age-standardized prevalence of diabetes in South Africans aged 15+ was 10.1%. Prevalence rates were higher among the non-white population and among women. Among individuals with diabetes, a total of 45.4% were unscreened, 14.7% were screened but undiagnosed, 2.3% were diagnosed but untreated, 18.1% were treated but uncontrolled, and 19.4% were treated and controlled, suggesting that 80.6% of the diabetic population had unmet need for care. The diabetes care cascade revealed significant losses from lack of screening, between screening and diagnosis, and between treatment and control. These results point to significant unmet need for diabetes care in South Africa. Additionally, this analysis provides a benchmark for evaluating efforts to manage the rising burden of diabetes in South Africa.

Diabetes diagnosis and care in sub-Saharan Africa: pooled analysis of individual data from 12 countries

Despite widespread recognition that the burden of diabetes is rapidly growing in many countries in sub-Saharan Africa, nationally representative estimates of unmet need for diabetes diagnosis and care are in short supply for the region. We use national population-based survey data to quantify diabetes prevalence and met and unmet need for diabetes diagnosis and care in 12 countries in sub-Saharan Africa. We further estimate demographic and economic gradients of met need for diabetes diagnosis and care. We did a pooled analysis of individual-level data from nationally representative population-based surveys that met the following inclusion criteria: the data were collected during 2005-15; the data were made available at the individual level; a biomarker for diabetes was available in the dataset; and the dataset included information on use of core health services for diabetes diagnosis and care. We first quantified the population in need of diabetes diagnosis and care by estimating the prevalence of diabetes across the surveys; we also quantified the prevalence of overweight and obesity, as a major risk factor for diabetes and an indicator of need for diabetes screening. Second, we determined the level of met need for diabetes diagnosis, preventive counselling, and treatment in both the diabetic and the overweight and obese population. Finally, we did survey fixed-effects regressions to establish the demographic and economic gradients of met need for diabetes diagnosis, counselling, and treatment. We pooled data from 12 nationally representative population-based surveys in sub-Saharan Africa, representing 38 311 individuals with a biomarker measurement for diabetes. Across the surveys, the median prevalence of diabetes was 5% (range 2-14) and the median prevalence of overweight or obesity was 27% (range 16-68). We estimated seven measures of met need for diabetes-related care across the 12 surveys: (1) percentage of the overweight or obese population who received a blood glucose measurement (median 22% [IQR 11-37]); and percentage of the diabetic population who reported that they (2) had ever received a blood glucose measurement (median 36% [IQR 27-63]); (3) had ever been told that they had diabetes (median 27% [IQR 22-51]); (4) had ever been counselled to lose weight (median 15% [IQR 13-23]); (5) had ever been counselled to exercise (median 15% [IQR 11-30]); (6) were using oral diabetes drugs (median 25% [IQR 18-42]); and (7) were using insulin (median 11% [IQR 6-13]). Compared with those aged 15-39 years, the adjusted odds of met need for diabetes diagnosis (measures 1-3) were 2·22 to 3·53 (40-54 years) and 3·82 to 5·01 (≥55 years) times higher. The adjusted odds of met need for diabetes diagnosis also increased consistently with educational attainment and were between 3·07 and 4·56 higher for the group with 8 years or more of education than for the group with less than 1 year of education. Finally, need for diabetes care was significantly more likely to be met (measures 4-7) in the oldest age and highest educational groups. Diabetes has already reached high levels of prevalence in several countries in sub-Saharan Africa. Large proportions of need for diabetes diagnosis and care in the region remain unmet, but the patterns of unmet need vary widely across the countries in our sample. Novel health policies and programmes are urgently needed to increase awareness of diabetes and to expand coverage of preventive counselling, diagnosis, and linkage to diabetes care. Because the probability of met need for diabetes diagnosis and care consistently increases with age and educational attainment, policy makers should pay particular attention to improved access to diabetes services for young adults and people with low educational attainment. None.

Automatic classification of glycaemia measurements to enhance data interpretation in an expert system for gestational diabetes

Expert systems for diabetes care need to automatically evaluate glycaemia measurements in relationship to meals to correctly determine patients’ metabolic condition and generate recommendations about therapy adjustments. Most glucose meters allow patients to manually label each measurement with a meal tag, but as this utility is not always used, a completion procedure is needed. Classification methods are usually based on predefined mealtimes and present insufficient accuracy that might affect the automatic data analysis. Expert systems in diabetes require a reliable method to manage incomplete glycaemia data so that they can determine if patients’ metabolic condition is altered due to a specific meal or due to an extended fasting period.This paper presents the design and application of a classification module to automatically assign the appropriate meal and ‘moment of measurement’ to incomplete glycaemia data. Different machine learning techniques were studied in order to design the best classification algorithm in terms of accuracy. The selected classifier was implemented with a C4.5 decision tree with 7 input features selected with a wrapper evaluator and the genetic search algorithm, which achieved 95.45% of accuracy with the training set on cross-validation. The classification module was integrated in the Sinedie expert system for gestational diabetes care and was evaluated in a clinical environment for 8 months with 42 patients. A total of 7,113 glycaemia measurements were uploaded by patients into the Sinedie system and were completed by the “classification module”. The 98.79% of the measurements were correctly classified, while patients modified the automatic classification of 1.21% of them. Classification results were improved by 21.04% compared to a classification based on predefined mealtimes. The automatic classification of glycaemia measurements minimizes the patient's intervention, allows structuring measurements in relationship to meals and makes automatic data interpretation by expert systems more reliable.

South Carolina 20 Years of Diabetes—A Public Health Concern

ObjectiveTo assess and enumerate the trends in diabetes prevalence, morbidity and mortality rates in South Carolina (SC) within the past 2 decades. Materials and MethodsWe analyzed state-level data from vital records, Behavioral Risk Factor Surveillance System, Children׳s Health Assessment Survey and Administrative Claim Files. ResultsOver the past 20 years, there has been an average 2.5% annual increase in diabetes prevalence among adults in SC (P < 0.01). Although a typical reduction in mortality rate of 2.2% has been observed during the same period, the increased number of people living with diabetes (from 5.0% in 1995 to 12.0% in 2014) has brought more need for diabetes care, particularly for severe in-hospital cases and cases with crisis at the emergency department, totaling $404 million in annual costs. ConclusionsSC has experienced an epidemic of diabetes. Coupled with declining trends in mortality and increased hospitalization and emergency department visits, the state is experiencing historical morbidity and complications due to diabetes. The shift in complexity of the disease onset and management has resulted in more individuals living with cardiovascular disease and other comorbidities. The cost of care for all South Carolinians with diabetes is estimated to exceed 2.8 billion dollars in 2014 and projected to be more than 4 billion dollars by 2020. If the diabetes prevalence trend of increasing rates continues over the next 20 years, the number of individuals living with diabetes and its complications would rise to 1.3 million in SC.

Barriers to effective management of type 2 diabetes in primary care: qualitative systematic review.

Despite the availability of evidence-based guidance, many patients with type 2 diabetes do not achieve treatment goals. To guide quality improvement strategies for type 2 diabetes by synthesising qualitative evidence on primary care physicians' and nurses' perceived influences on care. Systematic review of qualitative studies with findings organised using the Theoretical Domains Framework. Databases searched were MEDLINE, Embase, CINAHL, PsycInfo, and ASSIA from 1980 until March 2014. Studies included were English-language qualitative studies in primary care of physicians' or nurses' perceived influences on treatment goals for type 2 diabetes. A total of 32 studies were included: 17 address general diabetes care, 11 glycaemic control, three blood pressure, and one cholesterol control. Clinicians struggle to meet evolving treatment targets within limited time and resources, and are frustrated with resulting compromises. They lack confidence in knowledge of guidelines and skills, notably initiating insulin and facilitating patient behaviour change. Changing professional boundaries have resulted in uncertainty about where clinical responsibility resides. Accounts are often couched in emotional terms, especially frustrations over patient compliance and anxieties about treatment intensification. Although resources are important, many barriers to improving care are amenable to behaviour change strategies. Improvement strategies need to account for differences between clinical targets and consider tailored rather than 'one size fits all' approaches. Training targeting knowledge is necessary but insufficient to bring about major change; approaches to improve diabetes care need to delineate roles and responsibilities, and address clinicians' skills and emotions around treatment intensification and facilitation of patient behaviour change.

The impact of a patient’s concordant and discordant chronic conditions on diabetes care quality measures

AimsMost patients with diabetes have comorbid chronic conditions that could support (concordant) or compete with (discordant) diabetes care. We sought to determine the impact of the number of concordant and discordant chronic conditions on diabetes care quality. MethodsLogistic regression analysis of electronic health record data from 7 health systems on 24,430 patients with diabetes aged 18–75 years. Diabetes testing and control quality care goals were the outcome variables. The number of diabetes-concordant and the number of diabetes-discordant conditions were the main explanatory variables. Analysis was adjusted for health care utilization, health system and patient demographics. ResultsA higher number of concordant conditions were associated with higher odds of achieving testing and control goals for all outcomes except blood pressure control. There was no to minimal positive association between the number of discordant conditions and outcomes, except for cholesterol testing which was less likely with 4+ discordant conditions. ConclusionsHaving more concordant conditions makes diabetes care goal achievement more likely. The number of discordant conditions has a smaller, inconsistently significant impact on diabetes goal achievement. Interventions to improve diabetes care need to align with a patient’s comorbidities, including the absence of comorbidities, especially concordant comorbidities.

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

ObjectivesTo estimate undiagnosed diabetes prevalence from general practitioner (GP) practice data and identify areas with high levels of undiagnosed and diagnosed diabetes.DesignData from the North-West Adelaide Health Survey (NWAHS) were...

Diabetes management in Swedish schools: a national survey of attitudes of parents, children, and diabetes teams

Parents of children with type 1 diabetes often raise complaints about self-care support during school time. The aim of this study was to investigate attitudes to diabetes care in school reported by children with type 1 diabetes, their parents, and their diabetes teams. Children who had completed preschool class or at least one grade in the 9-yr compulsory school system were invited to participate. Data were collected using separate questionnaires for the children and their parents. In addition, the members of the diabetes team answered a separate questionnaire. All pediatric diabetes centers in Sweden were invited to participate in the study. All Swedish children and adolescents with diabetes are treated at pediatric diabetes centers. Out of 44 eligible centers, 41 were able to participate. The questionnaires were completed by 317 children and adolescents and 323 parents. The mean age was 11.4 ± 2.7 yr and hemoglobin A1c (HbA1c) was 61.8 ± 12.4 mmol/mol (7.8 ± 1.1%). For 57% of the children, there was no member of staff at the school with principal responsibility to support diabetes self-care. A written action plan for hypoglycemia existed for 60% of the children. Twenty-one percent of the parents regularly gave less insulin than they calculated would be needed at breakfast because of fear of hypoglycemia during school time. Although Sweden has legislation underlining the specific need for diabetes care in school, this nationwide study demonstrates deficiencies in the support of self-care management.

The Evolution of Diabetes Care in the Rural, Resource-Constrained Setting of Western Kenya

The initial focused effort on addressing the HIV pandemic in sub-Saharan Africa has helped set the groundwork for addressing many of the other areas of the health-care system requiring support in resource-constrained settings. With the growing prevalence of diabetes in this setting, the US Agency for International Development-Academic Model Providing Access to Healthcare Partnership (USAID-AMPATH) has begun developing infrastructure to meet the growing need for diabetes care. To describe the evolution of diabetes care in the rural, resource-constrained setting of western Kenya and to analyze preliminary data on the current status of glucose control of patients. Through partnerships, USAID-AMPATH has facilitated the provision of basic modalities of diabetes care, including reliable stocks of insulin, hemoglobin A(1c) (A1C) testing, and point-of-care glucose-testing supplies. Through the introduction of A1C testing, the poor quality of diabetes care was revealed, as the average A1C for the clinic population was 10.4%, with insulin-dependent patients constituting the majority of individuals with markedly elevated A1C levels. To address this, a contextualized electronic medical record and a cell phone-based home glucose monitoring program were created to improve glycemic control, which has led to significant reductions in A1C levels. Through the inclusion of clinical data within the electronic medical record, there is an ongoing effort to research various aspects of diabetes care in this understudied population, with the goal of addressing many of the unanswered questions surrounding diabetes care in sub-Saharan Africa. The lessons learned from this pilot program will be used to create sustainable infrastructure for diabetes care in partnership with the Kenyan government and will serve as a model for similar programs.

Patient computer use to prompt doctor adherence to diabetes management guidelines

Doctor compliance with diabetic care guidelines is low and may be improved with system-wide changes that include patient involvement. The objective of this study was to determine if patients in an internal medicine teaching clinic would use a touch-screen computer to receive personalized information regarding their need for diabetes care. Outcomes included determining if this intervention would improve resident doctor compliance with diabetic guidelines. In this prospective study a computer was available for patients to use independently in one clinic, while another computer was placed in a second clinic with nursing support. Patients responding they were diabetic to the first screen received screens covering HbA1c, blood pressure, cholesterol, foot, eye examinations and compliance with having labs drawn. Non-diabetic patients received three general health screens. A response-based report was printed for patients to share with their doctor. Chart reviews were conducted to assess diabetic health care delivery. The computer was used voluntarily by 20.6% of patients in the primary clinic and by 100% of patients in the nurse-assisted clinic. A total of 104 patients from both clinics responded they were diabetic; over 50% did not know what HbA1c meant and a minority responded their HbA1c, blood pressure and cholesterol were at good levels. Significantly more HbA1c tests conducted within 6 months were documented in patients' charts. Patients used the computer effectively without direction in the primary clinic. In this initial study, implementation of the computer program increased the number of HbA1c tests ordered. Future studies incorporating refinements may increase both usage and efficacy of this intervention.