Association between Frequency of Telephonic Contact And Clinical Testing for A Large, Geographically Diverse Diabetes Disease Management Population

Coberley, Carter; McGinnis, Matthew; Orr, Patty; Coberley, Sadie S.; Hobgood, Adam; Hamar, Brent; Gandy, Bill; Pope, James E.; Hudson, Laurel R.; Hara, Pam; Shurney, Dexter; Clarke, Janice L.; Crawford, Albert; Goldfarb, Neil I.

doi:10.1089/dis.2006.632

Cited by 12 publications

(11 citation statements)

References 23 publications

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“…13,14,16,17 Similar to these studies, a plateau in reduction in admissions was observed after 6-7 calls delivered over 18 months. Although there may be a point of diminishing returns with respect to the value of additional calls that varies according to severity and risk level, we did not have sufficient clinical detail to statistically adjust for changes in risk during the course of the program and thus cannot draw conclusions about optimal call frequency.…”

Section: Discussionsupporting

confidence: 61%

Impact of a Chronic Disease Management Program on Hospital Admissions and Readmissions in an Australian Population with Heart Disease or Diabetes

Hamar

Rula²,

Wells³

et al. 2013

Population Health Management

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Chronic disease management programs (CDMPs) were introduced in Australia to reduce unnecessary health care utilization by the growing population with chronic conditions; however, evidence of effectiveness is needed. This study evaluated the impact of a comprehensive CDMP, My Health Guardian (MHG), on rate of hospital admissions, readmissions, and average length of hospital stay (ALOS) for insured individuals with heart disease or diabetes. Primary outcomes were assessed through retrospective comparison of members in MHG (treatment; n = 5053) to similar nonparticipating members (comparison; n = 23,077) using a difference-in-differences approach with the year before program commencement serving as baseline and the subsequent 12 or 18 months serving as the program periods. All outcomes were evaluated for the total study population and for diseasematched subgroups (heart disease and diabetes). Statistical tests were performed using multivariate regression controlling for age, sex, number of chronic diseases, and past hospitalization status. After both 12 and 18 months, treatment members displayed decreases in admissions (both, P £ 0.001) and readmissions (both, P £ 0.01), and ALOS after 18 months (P £ 0.01) versus the comparison group; magnitude of impact increased over time for these 3 measures. All outcomes for both disease-matched subgroups directionally mirrored the total study group, but the diabetes subgroup did not achieve significance for readmissions or ALOS. Within the treatment group, admissions decreased with increasing care calls to members (12 and 18 months, P < 0.0001). These results show that MHG successfully reduced the frequency and duration of hospital admissions and presents a promising approach to reduce the burden associated with hospitalizations in populations with chronic disease. (Population Health Management 2013;16:125-131)

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Section: Discussionsupporting

confidence: 61%

Impact of a Chronic Disease Management Program on Hospital Admissions and Readmissions in an Australian Population with Heart Disease or Diabetes

Hamar

Rula²,

Wells³

et al. 2013

Population Health Management

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“…However, the central study questions differed; Heisler et al addressed diabetes control using perceived and objective measures of A1C, whereas in our study, only objective clinical measures of control were used. Despite these inconsistent findings, controlled trials that have aimed to increase diabetes knowledge, including interventions focused on diabetes self-management education, have been effective in improving clinical outcomes (8–10,23,24). Nevertheless, effective interventions have included several educational and behavioral components; ABC knowledge alone may not be sufficient to improve risk factor control.…”

Section: Discussionmentioning

confidence: 99%

“…Face-to-face individual and group diabetes education sessions in newly diagnosed type 2 diabetes (8), intensive management programs in patients with poorly controlled diabetes (9), and frequent phone contact (10) have all improved the ABCs compared with control subjects. These trials combined motivational/behavior change efforts with education; however, a trial that provided participants with only written A1C information showed improvements only in those with poor glucose control (11).…”

mentioning

confidence: 99%

Diabetes Knowledge and Its Relationship With Achieving Treatment Recommendations in a National Sample of People With Type 2 Diabetes

et al. 2012

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OBJECTIVEWe examined the prevalence of knowledge of A1C, blood pressure, and LDL cholesterol (ABC) levels and goals among people with diabetes, its variation by patient characteristics, and whether knowledge was associated with achieving levels of ABC control recommended for the general diabetic population.RESEARCH DESIGN AND METHODSData came from 1,233 adults who self-reported diabetes in the 2005–2008 National Health and Nutrition Examination Survey. Participants reported their last ABC level and goals specified by their physician (not validated by medical record data). Analysis included descriptive statistics and logistic regression.RESULTSAmong participants tested in the past year, 48% stated their last A1C level. Overall, 63% stated their last blood pressure level and 22% stated their last LDL cholesterol level. Knowledge of ABC levels was greatest in non-Hispanic whites, lowest in Mexican Americans, and higher with more education and income (all P ≤ 0.02). Demographic associations were similar for those reporting physician-specified ABC goals at the American Diabetes Association–recommended levels (A1C <7%, blood pressure <130/80 mmHg, and LDL cholesterol <100 mg/dL). Nineteen percent of participants stated that their provider did not specify an A1C goal compared with 47% and 41% for blood pressure and LDL cholesterol goals, respectively. For people who self-reported A1C <7.0%, 83% had an actual A1C <7.0%. Otherwise, participant knowledge was not significantly associated with risk factor control, except for in those who knew their last LDL cholesterol level (P = 0.046 for A1C <7.0%). Results from logistic regression corroborated these findings.CONCLUSIONSAmple opportunity exists to improve ABC knowledge. Diabetes education should include behavior change components in addition to information on ABC clinical measures.

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“…This result is consistent with previous research demonstrating that an increased frequency of care calls is associated with greater adherence to standards of care among DM participants. 20,21 The primary limitation of this study was the use of a Comparison group that had a significantly lower rate of admissions during the Base year compared with the Intervention group, which introduces the potential for regression to the mean. This statistical phenomenon describes the propensity of extreme observations to naturally return to a predictable mean value.…”

Section: Impact Of Chronic Care Management On Admissionsmentioning

confidence: 99%

The Impact of a Proactive Chronic Care Management Program on Hospital Admission Rates in a German Health Insurance Society

Hamar

Wells

Gandy

et al. 2010

Population Health Management

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Hospital admissions are the source of significant health care expenses, although a large proportion of these admissions can be avoided through proper management of chronic disease. In the present study, we evaluate the impact of a proactive chronic care management program for members of a German insurance society who suffer from chronic disease. Specifically, we tested the impact of nurse-delivered care calls on hospital admission rates. Study participants were insured individuals with coronary artery disease, heart failure, diabetes, or chronic obstructive pulmonary disease who consented to participate in the chronic care management program. Intervention (n ¼ 17,319) and Comparison (n ¼ 5668) groups were defined based on records of participating (or not participating) in telephonic interactions. Changes in admission rates were calculated from the year prior to (Base) and year after program commencement. Comparative analyses were adjusted for age, sex, region of residence, and disease severity (stratification of 3 [least severe] to 1 [most severe]). Overall, the admission rate in the Intervention group decreased by 6.2% compared with a 14.9% increase in the Comparison group (P < 0.001). The overall decrease in admissions for the Intervention group was driven by risk stratification levels 2 and 1, for which admissions decreased by 8.2% and 14.2% compared to Comparison group increases of 12.1% and 7.9%, respectively. Additionally, Intervention group admissions decreased as the number of calls increased (P ¼ 0.004), indicating a dose-response relationship. These findings indicate that proactive chronic care management care calls can help reduce hospital admissions among German health insurance members with chronic disease.

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Association between Frequency of Telephonic Contact And Clinical Testing for A Large, Geographically Diverse Diabetes Disease Management Population

Cited by 12 publications

References 23 publications

Impact of a Chronic Disease Management Program on Hospital Admissions and Readmissions in an Australian Population with Heart Disease or Diabetes

Impact of a Chronic Disease Management Program on Hospital Admissions and Readmissions in an Australian Population with Heart Disease or Diabetes

Diabetes Knowledge and Its Relationship With Achieving Treatment Recommendations in a National Sample of People With Type 2 Diabetes

The Impact of a Proactive Chronic Care Management Program on Hospital Admission Rates in a German Health Insurance Society

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