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© 2004 American Public Health Association
RESEARCH AND PRACTICE |
Yvette Roubideaux is with the Mel and Enid Zuckerman Arizona College of Public Health, University of Arizona, Tucson. Dedra Buchwald is with the Department of Medicine, University of Washington, Seattle. Janette Beals and Spero Manson are with the Department of Psychiatry, University of Colorado Health Sciences Center, Denver. At the time of the study, Denise Middlebrook was with the Department of Psychiatry, University of Colorado Health Sciences Center, Denver. Ben Muneta is with the Indian Health Service Epidemiology Program, Albuquerque, NM. Steve Rith-Najarian is with the Indian Health Service, Bemidji Area, Cass Lake, Minn, and Ray Shields was with the Indian Health Service, Portland Area, Bellingham, Wash. Kelly Acton is the director of the Indian Health Service National Diabetes Program, Albuquerque, NM.
Correspondence: Requests for reprints should be sent to Yvette Roubideaux, University of Arizona, College of Public Health, 500 N Tucson Blvd, Suite 110, Tucson, AZ 85716 (e-mail: yvetter{at}u.arizona.edu).
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSCONCLUSIONSReferences |
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Objectives. This study evaluated the quality of diabetes care for older American Indians and Alaska Natives.
Methods. We analyzed the Indian Health Service Diabetes Care and Outcomes Audit to determine whether completion of indicators of diabetes care differed as a function of age and whether additional patient and program factors were also associated with completion of the majority of the indicators.
Results. Completion rates varied by age group, with significantly lower rates seen among the youngest and oldest. Patient diabetes education and duration of diabetes were most strongly associated with the completion of the majority of these indicators.
Conclusions. Further studies are needed to determine effective interventions, including diabetes education, to improve the quality of diabetes care in the youngest and oldest age groups.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSCONCLUSIONSReferences |
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Diabetes is a serious problem for American Indian and Alaska Native (AIAN) populations, which suffer from some of the highest rates of diabetes in the world. In some AIAN communities, more than half the adult population has diabetes and the prevalence is increasing.1,2 Previous studies in the general population have found that the frequency of diabetes and its complications increases with age3; similar trends are evident in AIAN communities.4 For instance, in the Strong Heart Study, a comprehensive epidemiological study of cardiovascular disease and its risk factors among 13 AIAN tribes, diabetes was found to be most common in the oldest age groups, with rates as high as 74% among women aged 65–74 years living in Arizona.1
Recent studies have shown that intensive control of blood glucose levels and routine preventive screening can reduce complications among patients with diabetes.5,6 For example, the implementation of practice guidelines for routine foot care in an AIAN community was associated with a substantial reduction in lower extremity amputations over time.7 Generally, the quality of diabetes care has been defined, measured, and improved in AIAN communities using a combined clinical and public health approach.8 However, despite higher rates of diabetes and its complications in older individuals, no studies exist of the overall quality of care for older American Indians/Alaska Natives to determine whether they are receiving recommended medical care to prevent diabetes complications.
In this study, we measured the quality of diabetes care for American Indians/Alaska Natives to determine if differences existed as a function of age. Thus, we addressed the following questions: (1) Do differences exist in the quality of diabetes care for older American Indians/Alaska Natives compared with younger patients and (2) if so, what patient and health care program factors explain these differences?
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSCONCLUSIONSReferences |
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The quality of care for older American Indians/Alaska Natives with type 2 diabetes was evaluated in a cross-sectional study design using the Indian Health Service (IHS) Diabetes Care and Outcomes Audit data set for 1997. The IHS National Diabetes Program uses the audit to monitor the quality of diabetes care in Indian health programs (including IHS, tribal, and urban programs). The audit is a voluntary, annual systematic review of a random sample of medical records in each participating program, and quality diabetes care is defined as having met the IHS Minimum Standards of Care of Patients with Diabetes.9,10 The 1997 data set contained information on 87 demographic and quality-of-care indicators for 9626 individuals from 152 programs in all 12 IHS service areas. The IHS is organized by service units, which are often composed of several health programs/facilities. The programs that participated in the audit in 1997 represented 128 of the 150 service units in the IHS. Results reported by a few programs may represent data from both the main facility and 1 or more satellite clinics in the same community. Sample sizes for the medical record review in each program were based on a previously described random sampling strategy.8 Sample sizes for the medical record review in each program were based on a systematic random sampling technique in which a minimal sample size for each diabetes program was determined based on the total number of patients with diabetes in that program’s registry and a calculated minimal sample size to ensure with 90% confidence that a 10% difference in results would be significant. In 1997, Indian health programs reported 61 185 total patients with diabetes in their registries to the IHS National Diabetes Program. The 152 programs participating in the 1997 audit included information on a total of 9626 patients with diabetes through use of the sampling strategy described earlier. After the medical records were reviewed, the data were analyzed with Epi Info Software11 at each program, and the completed files were aggregated for analysis at the IHS service area and national levels. To protect the confidentiality of the participants in this study, patient identifiers were removed from the data set, and program and area identifiers were masked. Statistical analyses were performed using SPSS for Windows 10.0.7, 2000 (SPSS Inc, Chicago, Ill).
The results of selected quality-of-care indicators for diabetes were analyzed for the overall sample and as a function of age. For the purposes of this study, we considered the definition of "elder" patients within the context of AIAN culture. Although studies on older adults in the general US population have generally examined Medicare recipients (those aged 65 years or older), this literature may not reflect the AIAN experience because in many tribes elder status is not solely a function of chronological age. Because of increased morbidity and mortality, impairments associated with aging among American Indians/Alaska Natives may occur 20 years earlier than in the general population.12 American Indians/Alaska Natives often require, at a younger age, services typically developed solely for the "elderly." For example, Title VI of the Older Americans Act has recognized the need to provide services to American Indians/Alaska Natives living on reservations who are younger than age 60 years by allowing each tribe to set its own age eligibility requirements. Thus, for analytic purposes, individuals were grouped into 4 categories: younger than 45 years; 45 to 64 years; 65 to 74 years; and 75 years or older. The groups 45 to 54 and 55 to 64 years of age revealed similar results, so these age groups were combined in the final analysis.
The 13 quality-of-care measures evaluated were present in the IHS Minimum Standards of Care of Patients with Diabetes, which was based on the American Diabetes Association Clinical Practice Recommendations during the time period of this study, specifically: completion of recommended annual examinations (foot, eye, dental); routine laboratory tests completed at least once within the past year (cholesterol, creatinine, urinalysis, glycosylated hemoglobin); routine immunizations completed according to standards (influenza and pneumococcal vaccinations); general diabetes education at least once within the last year; and standard procedures performed at each visit at least 75% of the time (routine blood glucose level, blood pressure monitoring, and weight measurements). The variables measured the proportion of persons in each age group for whom a particular standard of care was completed according to IHS criteria. Missing values (range 0% to 16.7%, mean 2.0%) were omitted from the analysis for all the indicators. For 3 of the indicators (blood pressure, blood glucose level, and weight), missing values were greater (range 24.7% to 26.4%, mean 25.4%), so results for these indicators are only presented in the initial descriptive analysis of completion rates, and not in the subsequent regression analyses. For 6 indicators, "refused" was a response option, but refusal rates for all these indicators were small (range 0.3% to 4.5%, mean 1.9%), so they were included in the "not completed" category for each indicator in the analyses.
Pearson 
2 tests (P < .05) were used when comparing proportions. Because of the interest in the oldest age group, those aged 75 years or older were the referent group in these analyses. Additional multivariate analyses were performed to ascertain which patient and program factors were associated with completion of these indicators. Here an aggregate score of the completion of these indicators was calculated for each individual to represent adherence to recommended annual clinical and laboratory examinations and immunizations. Individuals were assigned a number from 0 to 9 to represent the number of these indicators successfully completed in 1997 according to IHS standards. As mentioned previously, 3 indicators were not included in this score because of their greater proportion of missing values (blood pressure, blood glucose level, and weight) and because they represented a distinct category of indicators that were not performed yearly, but on a per-visit basis. Completion of diabetes education was also not included because of its potential association with completion of these indicators. In addition, each indicator was considered equal in weight in the score because the IHS Minimum Standards of Care did not specify the relative importance of each indicator. Based on the distribution of the scores (mean 5.8, SD ± 1.8), a dichotomous variable was created for each individual to indicate if the person had completed the majority of indicators (
5 indicators = 1; 0–4 indicators = 0).
The proportion of the sample that completed the majority of indicators ( 5) during the year was calculated and stratified by both patient and program factors. According to recent recommendations by the American Association of Diabetes Educators’ National Diabetes Education Outcome System, the diabetes care system can be described at 3 levels: the individual level, the program level, and the national level.13 In this analysis, individual-level data included age, gender, duration of diabetes, and diabetes education received. Program-level data included the type of program (hospital-based clinic = 1, freestanding clinic = 0) and whether the diabetes care was received in a model diabetes program, a special designation for IHS programs receiving special funding. Overall, 3705 (38.5%) of the patients in the sample received care in hospital-based clinics and 5921 (61.5%) in freestanding clinics. In addition, 1849 (19.2%) patients received care in model diabetes programs. The likelihood of completing 5 or more indicators was estimated for each individual or program factor using Mantel–Haenstzel common odds ratios.
Logistic regression analyses were then performed to determine which factors were associated with completion of 5 or more indicators. Initially, univariate logistic regression was performed to determine which factors were significantly associated with the outcome or dependent variable (score 5) at the P < .10 level to minimize the type 1 error rate associated with multiple tests. Additional tests for interactions between age and the duration of diabetes were performed and were not significant. Then multiple logistic regression was performed using 2 models: (1) all patient and program variables and (2) only the variables significant in univariate analyses. The magnitude of the association of each independent variable with the outcome variable was calculated using odds ratios and 95% confidence intervals.14
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSCONCLUSIONSReferences |
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The mean age of the sample was 54.8 years (SD ± 14.2) with a greater proportion of females than males (59% vs 41%). For all patients, the average duration of diabetes was 8.6 years, and the mean glycosylated hemoglobin level was 8.8% (SD ± 2.2). Completion rates for the 13 diabetes quality-of-care indicators are shown in Table 1
for the overall sample and for each age group. Rates for most indicators varied significantly across age groups and in differing patterns. For annual foot and dilated eye examinations, the percentage completed was lowest among patients younger than 45 years, increased in the age groups 45 to 74 years, and then declined in the oldest age group. A similar pattern was seen for diabetes education and tests of cholesterol, glycosylated hemoglobin, and creatinine levels completed during the year. For annual dental examinations and weights obtained at each visit, completion rates for the age groups declined with increasing age, with the lowest rates among those 75 years or older. For influenza and pneumococcal immunizations, the rates of completion increased with age, but this trend leveled off at the oldest age group. The mean glycosylated hemoglobin level decreased with age. There were no significant differences by age groups for the other indicators measured in these univariate analyses. Table 2 reveals that, compared with their older counterparts, patients aged 65 to 74 years were significantly more likely to receive foot, eye, and dental examinations; diabetes education; and cholesterol, glycosylated hemoglobin, and weight measurements. Compared with all other age groups, the older age group had significantly lower completion rates only for dental examinations, diabetes education, and weight measurement, and significantly higher rates only for influenza and pneumococcal vaccinations.
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In Table 3
, the proportion of individuals who completed 5 or more indicators during 1997 is shown for the overall sample and as a function of individual factors (age, gender, duration of diabetes for 5 or more years, receipt of diabetes education) and program factors (type of program, model program status). Odds of completion with 95% confidence intervals reveal significant differences for 3 factors (age younger than 45 years, duration of diabetes, diabetes education). Overall, 79.1% of the sample had completed 5 or more indicators during the year. Individuals in the youngest age group were approximately half as likely as individuals in the oldest age group to complete 5 or more indicators. Individuals who had had diabetes for 5 or more years were 1.7 times more likely to have completed 5 or more indicators, and individuals who had received diabetes education during the year were 3.1 times more likely to have completed 5 or more indicators.
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In the multivariate logistic regression analysis (data not shown), age, duration of diabetes, and receipt of diabetes education were again the only factors significantly associated with completion of 5 or more indicators in both models tested, with similar magnitudes of association as the stratified analysis. A final model of the association of diabetes education and duration of diabetes with completion of 5 or more indicators, adjusted for age and gender, was significant at P < .001 with adjusted odds ratios of 3.2 (95% confidence interval [CI] = 2.8, 3.6) for diabetes education, and 1.7 (95% CI = 1.5, 1.9) for duration of diabetes 5 or more years.
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CONCLUSIONS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSCONCLUSIONSReferences |
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AIAN rates of adherence to recommended diabetes care guidelines15 often equal or exceed rates reported for the general population.16 However, no previous study assessed the quality of diabetes care for American Indians/Alaska Natives across different age groups or possible factors associated with higher completion rates. Furthermore, most studies in the general population of older individuals with diabetes used the age category 65 years or older or used Medicare data.17
In this study, age groups were chosen in an attempt to reflect the cultural definition of elder in AIAN communities, because American Indians/Alaska Natives are often considered elders at ages much younger than 65 years. Although the 4 age categories represented a broader age range than is usually reported in studies on the quality of diabetes care among older adults in the United States, the significant differences in care among the oldest and youngest age groups might have been obscured by using an age threshold of 65 years or older.
Even though significant variation was observed as a function of age, the lowest rates of completion for recommended examinations, laboratory tests, and immunizations were consistently found in the oldest ( 75 years) and youngest (< 45 years) age groups. Potential reasons for less adherence to guidelines for care in the oldest individuals include difficulty accessing health care services because of decreased functional ability, the presence of other comorbid conditions, lower priority for preventive care because of decreased life expectancy, or concerns regarding the potential for hypoglycemia.18 Although this study was designed to evaluate the quality of care for older American Indians/Alaska Natives, a striking finding was that the lowest completion rates were often seen in the youngest age group. Less-frequent performance of diabetes care procedures in the youngest age group could have resulted from decreased utilization of health care services because of other priorities such as jobs and family, unfamiliarity with recommended care because of recent diagnosis, lack of ongoing patient education, or lack of awareness of the importance of routine care. These results are important because the prevention of the complications of chronic diseases in elderly persons optimally begins early in life.19
Finally, using multivariate techniques that controlled for patient and program factors, diabetes education, duration of diabetes, and less strongly, older age were associated with completion of 5 or more indicators. Other individual and program factors were not significant. In other studies, a variety of factors have been found to be associated with better preventive care for diabetes and its complications. In recent reviews, older age, insulin use, having insurance status, higher educational level, and diabetes education were associated with better diabetes care.16,20 Another study actually found that younger age, comorbid medical diagnoses, insulin use, greater number of visits, and greater access to care were associated with greater completion rates of 3 common indicators of care.21 In this study, duration of diabetes for 5 or more years was associated with completion of 5 or more indicators, and this likely reflects greater experience with the health care system and more opportunities for diabetes education and preventive care, consistent with the previous studies.
The factor most strongly associated with completion of 5 or more indicators was diabetes education, even when adjusted for age, gender, duration of diabetes, and other program factors. Diabetes education has been shown to be essential to effective diabetes care22 and has been associated with improved short-term outcomes for patients with diabetes,23 especially when included as a part of a comprehensive disease management or case management program.24 The association found in this study is likely due to the practice in Indian health programs of primary care providers initially referring individuals with diabetes to the diabetes educator, who provides information and education on preventive care services needed during the year.
There are several limitations to this retrospective, cross-sectional study. First, the independent variable in the regression analysis (diabetes education) represents a visit that could have contained multiple components of diabetes teaching delivered by various types of health professionals and was unlikely to be standardized across Indian health programs or individual patients. In addition, the data set did not contain the date the quality-of-care indicators were completed or the number of clinic visits during the year of the study. Thus, although diabetes education was strongly associated with completion of recommended examinations and procedures, the temporal relation among these variables is unknown. Likewise, we could not determine to what extent the association of diabetes education with greater completion of indicators reflected frequent visits and, therefore, increased opportunities for care.
In addition, because our results reflect the care received by users of programs that voluntarily participated in the IHS Diabetes Care and Outcomes Audit, we cannot comment on the care of patients with diabetes who were infrequent users of the Indian health system or who may have been receiving care from other non-Indian health sources. Because programs voluntarily participated in the audit, selection bias was possible, because programs with better outcomes might have been more likely to participate. To minimize this possibility, the IHS National Diabetes Program and area diabetes consultants encouraged all programs to participate in the audit as a routine part of their quality-improvement efforts, regardless of their potential results. Programs are encouraged to use these results to identify areas for improvements in care and to monitor their performance over time. IHS area and national reports do not identify programs by name, so confidentially of results is maintained. Other factors not assessed here may also influence the completion of recommended diabetes care indicators, such as socioeconomic status,25 educational level, transportation, and other patient, provider, and health system characteristics. Lastly, our analysis used 1997 data that was collected just before the implementation of the Special Diabetes Program for Indians initiative in 1998, which resulted in many new diabetes programs and services in Indian communities to prevent and treat diabetes. Because the authors plan a follow-up study in 2003 to review whether diabetes care for older American Indians/Alaska Natives has improved over time in comparison with this baseline study, the results of this study are especially germane.
This study assessed diabetes care by measuring completion rates for various examinations and laboratory tests as recommended by the IHS Minimum Standards of Diabetes Care in place at the time of the study. Additional measurements and comparisons of intermediate outcomes of diabetes treatment have been recommended more recently, such as in the Diabetes Quality Improvement Project measures set16 or in the RAND Corp–recommended indicators of quality for diabetes mellitus.26 These measures include intermediate outcomes of care, such as achievement of specific levels of blood pressure or glucose control, and are not included in our study because those criteria were not widely used at the time of this study and the audit was not initially designed to measure those specific indicators. The original purpose of the audit was to measure performance on selected diabetes care indicators among programs within the Indian health system for internal quality-improvement purposes, not for comparison to other non-Indian health programs. A recent article by the IHS National Diabetes Program does demonstrate how the Diabetes Quality Improvement Project measures can be applied to one of the more recent audit reviews, and the audit is currently being modified to enable comparison using national standardized measures in the future.15 However, the measures used in this study focus on completion of recommended examinations and laboratory tests and are comparable to those of other studies.
Recommendations for the care of older adults with diabetes are similar to those for all ages, with the goals of individualizing preventive care to help reduce morbidity and mortality, as well as maximizing quality of life and overall functioning.19,27,28 This study suggests the need for further attention to the quality of care in both older and younger adults with diabetes for many of the indicators measured. Recent evidence that the prevalence of type 2 diabetes is increasing in AIAN youth29 underscores the need for greater efforts to improve the quality of diabetes care in all age groups. Although a striking finding was the strong association of diabetes education with adherence to recommended procedures, future studies are needed to identify the specific diabetes education program components associated with better outcomes, clarify the temporal association of diabetes education with completion of quality-of-care indicators, and determine the effect of visit frequency on completion rates. Finally, with the substantial and continuing increase in both the number of older Americans3 and older American Indians/Alaska Natives,30 it will be crucial to modify or adapt standards of care relevant to specific age and cultural groups.
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Footnotes |
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Contributors
Y. Roubideaux conceived the study and supervised and participated in all aspects of its design, conduct, and implementation and in the analysis, interpretation of results, and writing. D. Buchwald assisted with design, interpretation, and writing. J. Beals assisted with study design and analysis, and the writing. D. Middlebrook assisted with study design, analysis, and reviewing the article. S. Manson assisted with study design, interpretation of analysis, and reviewing the article. B. Muneta assisted with study design, interpretation of results, and reviewing the article. S. Rith-Najarian assisted with collection of data, interpretation of results, and reviewing the article. R. Shields assisted with collection of data, analysis, and reviewing the article. K. Acton assisted with study design, approval of use of data, interpretation of analysis, and reviewing the article.
Human Participant Protection
The institutional review board of the Indian Health Service approved this article for publication.
Accepted for publication April 24, 2003.
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References |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSCONCLUSIONSReferences |
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