Hospital admission rates for a racially diverse low-income cohort of patients with diabetes: the Urban Diabetes Study

Effectiveness of a population-based integrated care model in reducing hospital activity: an interrupted time series analysis

Objectives

First impact assessment analysis of an integrated care model (ICM) to reduce hospital activity in the London Borough of Hillingdon, UK.

Methods

We evaluated a population-based ICM consisting of multiple interventions based on self-management, multidisciplinary teams, case management and discharge management. The sample included 331 330 registered Hillingdon residents (at the time of data extraction) between October 2018 and July 2020. Longitudinal data was extracted from the Whole Systems Integrated Care database. Interrupted time series Poisson and Negative binomial regressions were used to examine changes in non-elective hospital admissions (NEL admissions), accident and emergency visits (A&E) and length of stay (LoS) at the hospital. Multiple imputations were used to replace missing data. Subgroup analysis of various groups with and without long-term conditions (LTC) was also conducted using the same models.

Results

In the whole registered population of Hillingdon at the time of data collection, gradual decline over time in NEL admissions (RR 0.91, 95% CI 0.90 to 0.92), A&E visits (RR 0.94, 95% CI 0.93 to 0.95) and LoS (RR 0.93, 95% CI 0.92 to 0.94) following an immediate increase during the first months of implementation in the three outcomes was observed. Subgroup analysis across different groups, including those with and without LTCs, showed similar effects. Sensitivity analysis did not show a notable change compared with the original analysis.

Conclusion

The Hillingdon ICM showed effectiveness in reducing NEL admissions, A&E visits and LoS. However, further investigations and analyses could confirm the results of this study and rule out the potential effects of some confounding events, such as the emergence of COVID-19 pandemic.

Retrospective evaluation of healthcare utilisation and mortality of two post-discharge care programmes in Singapore

OBJECTIVE

To evaluate the impact on healthcare utilisation frequencies and charges, and mortality of a programme for frequent hospital utilisers and a programme for patients requiring high acuity post-discharge care as part of an integrated healthcare model.

DESIGN

A retrospective quasi-experimental study without randomisation where patients who received post-discharge care interventions were matched 1:1 with unenrolled patients as controls.

SETTING

The National University Health System (NUHS) Regional Health System (RHS), which was one of six RHS in Singapore, implemented the NUHS RHS Integrated Interventions and Care Extension (NICE) programme for frequent hospital utilisers and the NUHS Transitional Care Programme (NUHS TCP) for high acuity post-discharge care. The programmes were supported by the Ministry of Health in Singapore, which is a city-state nation located in Southeast Asia with a 5.6 million population.

PARTICIPANTS

Linked healthcare administrative data, for the time period of January 2013 to December 2016, were extracted for patients enrolled in NICE (n=554) or NUHS TCP (n=270) from June 2014 to December 2015, and control patients.

INTERVENTIONS

For both programmes, teams conducted follow-up home visits and phone calls to monitor and manage patients' post-discharge.

PRIMARY OUTCOME MEASURES

One-year pre- and post-enrolment healthcare utilisation frequencies and charges of all-cause inpatient admissions, emergency admissions, emergency department attendances, specialist outpatient clinic (SOC) attendances, total inpatient length of stay and mortality rates were compared.

RESULTS

Patients in NICE had lower mortality rate, but higher all-cause inpatient admission, emergency admission and emergency department attendance charges. Patients in NUHS TCP did not have lower mortality rate, but had higher emergency admission and SOC attendance charges.

CONCLUSIONS

Both NICE and NUHS TCP had no improvements in 1 year healthcare utilisation across various setting and metrics. Singular interventions might not be as impactful in effecting utilisation without an overhauling transformation and restructuring of the hospital and healthcare system.

Impact of a Pharmacy-Initiated Inpatient Diabetes Patient Education Program on 30-Day Readmission Rates

Background:

In October 2012, a pharmacy-driven Inpatient Diabetes Patient Education (IDPE) program was implemented at the University of Toledo Medical Center (UTMC).

Objective:

To determine the difference in 30-day hospital readmission rates for patients who receive IDPE compared to those who do not.

Methods:

This retrospective cohort was completed at UTMC. Patients admitted between October 1, 2012, and September 30, 2013, were included if they were ≥18 years and had one of the following: (1) diagnosis of diabetes mellitus, (2) blood glucose >200 mg/dL (>11.11 mmol/L) on admission, or (3) hemoglobin A1C of >6.5% (>48 mmol/mol). Patients who received IDPE from a pharmacist or student pharmacist (intervention group) were compared to patients who did not receive IDPE (control group).

Results:

The 30-day readmission rate was 13.2% for the intervention group (n = 364) and 21.5% for the control group (n = 149) ( P = .023). Average time to 30-day readmission was 13.1 (±8.3) days for the IDPE group and 11.9 (±7.9) days for the control group. There was no significant difference in diabetes-related readmission between the intervention and control groups (25.5% vs 21.9%).

Conclusions:

An IDPE program delivered primarily by pharmacists and student pharmacists significantly reduced 30-day readmission rates among patients with diabetes.

Are Ethnic Disparities in HbA1c Levels Explained by Mental Wellbeing? Analysis of Population-Based Data from the Health Survey for England

Aims

It is unclear how ethnic differences in HbA_1c levels are affected by individual variations in mental wellbeing. Thus, the aim of this study was to assess the extent to which HbA_1c disparities between Caucasian and South Asian adults are mediated by various aspects of positive psychological functioning.

Methods

Data from the 2014 Health Survey for England was analysed using bootstrapping methods. A total of 3894 UK residents with HbA_1c data were eligible to participate. Mental wellbeing was assessed using the Warwick-Edinburgh Mental Well-being Scale. To reduce bias BMI, blood pressure, diabetes status, and other factors were treated as covariates.

Results

Ethnicity directly predicted blood sugar control (unadjusted coefficient −2.15; 95% CI −3.64, −0.67), with Caucasians generating lower average HbA_1c levels (37.68 mmol/mol (5.6%)) compared to South Asians (39.87 mmol/mol (5.8%)). This association was mediated by positive mental wellbeing, specifically concerning perceived vigour (unadjusted effect 0.30; 95% CI 0.13, 0.58): South Asians felt more energetic than Caucasians (unadjusted coefficient −0.32; 95% CI −0.49, −0.16), and greater perceived energy predicted lower HbA_1c levels (unadjusted coefficient −0.92; 95% CI −1.29, −0.55). This mediator effect accounted for just over 14% of the HbA_1c variance and was negated after adjusting for BMI.

Conclusions

Caucasian experience better HbA_1c levels compared with their South Asian counterparts. However, this association is partly confounded by individual differences in perceived energy levels, which is implicated in better glycaemic control, and appears to serve a protective function in South Asians.

High-Cost Patients: Hot-Spotters Don't Explain the Half of It

BACKGROUND

Understanding resource utilization patterns among high-cost patients may inform cost reduction strategies.

OBJECTIVE

To identify patterns of high-cost healthcare utilization and associated clinical diagnoses and to quantify the significance of hot-spotters among high-cost users.

DESIGN

Retrospective analysis of high-cost patients in 2012 using data from electronic medical records, internal cost accounting, and the Centers for Medicare and Medicaid Services. K-medoids cluster analysis was performed on utilization measures of the highest-cost decile of patients. Clusters were compared using clinical diagnoses. We defined "hot-spotters" as those in the highest-cost decile with ≥4 hospitalizations or ED visits during the study period.

PARTICIPANTS AND EXPOSURE

A total of 14,855 Medicare Fee-for-service beneficiaries identified by the Medicare Quality Resource and Use Report as having received 100 % of inpatient care and ≥90 % of primary care services at Cleveland Clinic Health System (CCHS) in Northeast Ohio. The highest-cost decile was selected from this population.

MAIN MEASURES

Healthcare utilization and diagnoses.

KEY RESULTS

The highest-cost decile of patients (n = 1486) accounted for 60 % of total costs. We identified five patient clusters: "Ambulatory," with 0 admissions; "Surgical," with a median of 2 surgeries; "Critically Ill," with a median of 4 ICU days; "Frequent Care," with a median of 2 admissions, 3 ED visits, and 29 outpatient visits; and "Mixed Utilization," with 1 median admission and 1 ED visit. Cancer diagnoses were prevalent in the Ambulatory group, care complications in the Surgical group, cardiac diseases in the Critically Ill group, and psychiatric disorders in the Frequent Care group. Most hot-spotters (55 %) were in the "frequent care" cluster. Overall, hot-spotters represented 9 % of the high-cost population and accounted for 19 % of their overall costs.

CONCLUSIONS

High-cost patients are heterogeneous; most are not so-called "hot-spotters" with frequent admissions. Effective interventions to reduce costs will require a more multi-faceted approach to the high-cost population.

Length of Stay and Deaths in Diabetes-Related Preventable Hospitalizations Among Asian American, Pacific Islander, and White Older Adults on Medicare, Hawai'i, December 2006-December 2010

INTRODUCTION

The objective of this study was to compare in-hospital deaths and length of stays for diabetes-related preventable hospitalizations (D-RPHs) in Hawai'i for Asian American, Pacific Islander, and white Medicare recipients aged 65 years or older.

METHODS

We considered all hospitalizations of older (>65 years) Japanese, Chinese, Native Hawaiians, Filipinos, and whites living in Hawai'i with Medicare as the primary insurer from December 2006 through December 2010 (n = 127,079). We used International Classification of Diseases - 9th Revision (ICD-9) codes to identify D-RPHs as defined by the Agency for Healthcare Research and Quality. Length of stays and deaths during hospitalization were compared for Asian American and Pacific Islander versus whites in multivariable regression models, adjusting for age, sex, location of residence (Oahu, y/n), and comorbidity.

RESULTS

Among the group studied, 1,700 hospitalizations of 1,424 patients were D-RPHs. Native Hawaiians were significantly more likely to die during a D-RPH (odds ratio [OR], 3.92; 95% confidence interval [CI], 1.42-10.87) than whites. Filipinos had a significantly shorter length of stay (relative risk [RR], 0.77; 95% CI, 0.62-0.95) for D-RPH than whites. Among Native Hawaiians with a D-RPH, 59% were in the youngest age group (65-75 y) whereas only 6.3% were in the oldest (≥85 y). By contrast, 23.2% of Japanese were in the youngest age group, and 32.2% were in the oldest.

CONCLUSION

This statewide study found significant differences in the clinical characteristics and outcomes of D-RPHs for Asian American and Pacific Islanders in Hawai'i. Native Hawaiians were more likely to die during a D-RPH and were hospitalized at a younger age for a D-RPH than other studied racial/ethnic groups. Focused interventions targeting Native Hawaiians are needed to avoid these outcomes.

Relationship between primary care visits and hospital admissions in remote Indigenous patients with diabetes: a multivariate spline regression model

AIMS

To determine if access to primary health care (PHC) is associated with reduced hospitalisations for remote Indigenous patients with diabetes.

METHODS

Using individual level linked health clinic and hospital data, a retrospective cohort study was conducted to estimate annual hospital admission rate by number of clinic visits in the Northern Territory of Australia, stratified by age group, sex and the presence of comorbidities. A spline regression model was used to describe the clinic-hospital relationship with covariates. An impact index of PHC visits was derived using the first derivative of the quadratic equations evaluated at the parameter estimates.

RESULTS

The relationship between PHC visits and hospitalisations in diabetes care appeared to be a U-curve. Low levels of PHC visits were associated with increased hospital admissions amongst people with diabetes. The overall level of all-cause hospitalisations for patients with diabetes was minimised when the PHC visits were 7.9 per person-year (95% confidence interval 5.8-10).

CONCLUSIONS

Using existing empirical data, this study suggests that other things being equal, diabetes patients who had an adequate level of PHC visits are likely to have a lower level of hospitalisations than those with fewer or more PHC visits. This study highlights the importance for remote Indigenous patients with diabetes to have adequate access to PHC.

Identifying predictors of hospital readmission following congenital heart surgery through analysis of a multiinstitutional administrative Database

BACKGROUND

Despite resource burdens associated with hospital readmission, there remains little multiinstitutional data available to identify children at risk for readmission following congenital heart surgery.

METHODS AND RESULTS

Children undergoing congenital heart surgery and discharged home between January of 2011 and December 2012 were identified within the Pediatric Health Information System database, a multiinstitutional collection of clinical and administrative data. Patient discharges were assigned to derivation and validation cohorts for the purposes of predictive model design, with 17 871 discharges meeting inclusion criteria. Readmission within 30 days was noted following 956 (11%) of discharges within the derivation cohort (n = 9104), with a median time to readmission of 9 days (interquartile range [IQR] 5-18 days). Readmissions resulted in a rehospitalization length of stay of 4 days (IQR 2-8 days) and were associated with an intensive care unit (ICU) admission in 36% of cases. Independent perioperative predictors of readmission included Risk Adjustment in Congenital Heart Surgery score of 6 (odds ratio [OR] 2.6, 95% confidence interval [CI] 1.8-3.7, P < .001) and ICU length of stay of at least 7 days (OR 1.9 95% CI 1.6-2.2, P < .001). Demographic predictors included Hispanic ethnicity (OR 1.2, 95% CI 1.1-1.4, P = .014) and government payor status (OR 1.2, 95% CI 1.1-1.4, P = .007). Predictive model performance was modest among validation cohort (c statistic 0.68, 95% CI 0.66-0.69, P < .001).

CONCLUSIONS

Readmissions following congenital heart surgery are common and associated with significant resource consumption. While we describe independent predictors that may identify patients at risk for readmission prior to hospital discharge, there likely remains other unreported factors that may contribute to readmission following congenital heart surgery.

Health insurance and chronic conditions in low-income urban whites

Little is known about how health insurance contributes to the prevalence of chronic disease in the overlooked population of low-income urban whites. This study uses cross-sectional data on 491 low-income urban non-elderly non-Hispanic whites from the Exploring Health Disparities in Integrated Communities-Southwest Baltimore (EHDIC-SWB) study to examine the relationship between insurance status and chronic conditions (defined as participant report of ever being told by a doctor they had hypertension, diabetes, stroke, heart attack, anxiety or depression, asthma or emphysema, or cancer). In this sample, 45.8 % were uninsured, 28.3 % were publicly insured, and 25.9 % had private insurance. Insured participants had similar odds of having any chronic condition (odds ratios (OR) 1.06; 95 % confidence intervals (CI) 0.70-1.62) compared to uninsured participants. However, those who had public insurance had a higher odds of reporting any chronic condition compared to the privately insured (OR 2.29; 95 % CI 1.21-4.35). In low-income urban areas, the health of whites is not often considered. However, this is a significant population whose reported prevalence of chronic conditions has implications for the Medicaid expansion and the implementation of health insurance exchanges.

Patient-centered group diabetes care: a practice innovation

The purpose of this project was to evaluate the efficacy of group diabetes care for an underserved population using a patient-centered approach with the inclusion of interactive diabetes self-management education. In place of the traditional office visit, patients attended three group visits. Improvements in diabetes knowledge and patient-perceived self-efficacy resulted.

Intensification of diabetes medication and risk for 30-day readmission

AIM

To examine the association of in-hospital diabetes regimen intensification with subsequent 30-day risk for unplanned readmission/emergency department admission.

METHODS

We retrospectively studied 1949 adults with Type 2 diabetes receiving primary care within an academic health network admitted to the hospital between January 2007 and December 2009. Glucose therapy intensification was defined as new start of insulin or oral hypoglycaemic agents, or addition of prandial insulin or insulin mixtures. The association of glucose therapy intensification with subsequent 30-day risk for unplanned readmission/emergency department admission was examined, with focus on medicine service patients with poorly controlled glycaemia (baseline HbA(1c) ≥ 64 mmol/mol).

RESULTS

One in six patients (324/1949, 17%) had early readmission/emergency department admission. Compared with patients without early readmission, readmitted patients were more often male (58 vs. 52%, P = 0.03), had higher Charlson co-morbidity score [mean (sd) 3.0 (2.0) vs. 2.8 (1.8), P = 0.02], longer length of stay [5 (4.4) vs. 3.9 (3.3) days, P < 0.01] and were more often discharged home with nursing services (38 vs. 32%, P = 0.03). Overall, glucose therapy intensification was not associated with early hospital readmission/emergency department admission (odds ratio 0.94, 95% CI 0.64-1.37, P = 0.74). However, among medicine service patients with baseline HbA(1c) ≥ 64 mmol/mol (8%), glucose therapy intensification was associated with a significantly decreased early readmission risk (adjusted odds ratio 0.33, 95% CI 0.12-0.88, P = 0.03) and lower post-discharge HbA(1c) {mean decrease (sd): 20 (26) mmol/mol [1.8 (2.4)%] vs. 7 (15) mmol/mol [0.6 (1.4)%], P < 0.01}.

CONCLUSIONS

Diabetes medical regimen intensification during hospitalization was not associated with early readmission. Among patients with elevated HbA(1c) , glucose therapy intensification was associated with a decreased 30-day readmission/emergency department admission risk and lower outpatient HbA(1c) levels. Our findings support the safety and durable impact of diabetes regimen optimization during hospital admission.

Characteristics of general practices associated with numbers of elective admissions

BACKGROUND

In England both emergency (unplanned) and non-emergency (elective) hospital admissions have been increasing. Some elective admissions are potentially avoidable.

AIM

to identify the characteristics of general practices and patients associated with elective admissions.

METHODS

A cross-sectional study, in Leicestershire, England, was conducted using admission data (2006-07 and 2007-08). Practice characteristics (list size, distance from principal hospital, quality and outcomes framework score and general practitioner (GP) patient access survey data) and patient characteristics (age, ethnicity and deprivation and gender) were used as predictors of elective hospital admissions in a negative binomial regression model.

RESULTS

Practices with a higher proportion of patients aged 65 years or greater and of white ethnicity had higher rates of elective hospital admissions. Practices with more male patients and with more patients reporting being able to consult a particular GP had fewer elective hospital admissions. For 2007-08 practices with a larger list size were associated with higher elective hospital admissions. Quality and outcomes framework performance did not predict admission numbers.

CONCLUSIONS

As for unplanned admissions, elective admissions increase as being able to consult a particular GP declines. Interventions to improve continuity should be investigated. Practices face major problems in managing the increased need for planned care as the population ages.

Lower rehospitalization rates among rural Medicare beneficiaries with diabetes

PURPOSE

We estimated the 30-day readmission rate of Medicare beneficiaries with diabetes, across levels of rurality.

METHODS

We merged the 2005 Medicare Chronic Conditions 5% sample data with the 2007 Area Resource File. The study population was delimited to those with diabetes and at least 1 hospitalization in the year. Unadjusted readmission rates were estimated across levels of rurality. Multivariate logistic regression estimated the factors associated with readmissions.

FINDINGS

Overall, 14.4% had a readmission; this was higher among urban (14.9%) than rural (12.9%) residents. The adjusted odds indicated that remote rural residents were less likely to have a readmission (OR 0.74, 0.57-0.95) than urban residents. Also, those with a 30-day physician follow-up visit were more likely to have a readmission (OR 2.25, 1.96-2.58) than those without a visit.

CONCLUSION

The factors that contribute to hospital readmissions are complex; our findings indicate that access to follow-up care is highly associated with having a readmission. It is possible that residents of remote rural counties may not receive necessary readmissions due to lower availability of such follow-up care. Policy makers should continue to monitor this apparent disparity to determine the impact of these lower rates on both patients and hospitals alike.

Scheduled and unscheduled hospital readmissions among patients with diabetes

OBJECTIVES

To describe rates of scheduled and unscheduled readmissions among midlife and older patients with diabetes and to examine associated socioeconomic and clinical factors.

STUDY DESIGN

Population-based data set study.

METHODS

Using the 2006 California State Inpatient Dataset, we identified 124,967 patients 50 years or older with diabetes who were discharged from acute care hospitals between April and September 2006 and examined readmissions in the 3 months following their index hospitalizations.

RESULTS

About 26.3% of patients were readmitted within the 3-month period following their index hospitalizations, 87.2% of which were unscheduled readmissions. Patients with unscheduled readmissions were more likely to have a higher comorbidity burden, be members of racial/ethnic minority groups with public insurance, and live in lower-income neighborhoods. Having a history of hospitalization in the 3 months preceding the index hospitalization was also a strong predictor of unscheduled readmissions. Almost one-fifth of unscheduled readmissions (constituting approximately 27,500 inpatient days and costing almost $72.7 million) were potentially preventable based on definitions of Prevention Quality Indicators by the Agency for Healthcare Research and Quality. Scheduled readmissions were less likely to occur among patients 80 years or older, the uninsured, and those with an unscheduled index hospitalization.

CONCLUSIONS

The predictors of scheduled and unscheduled readmissions are different. Transition care to prevent unscheduled readmissions in acutely ill patients with diabetes may help reduce rates, improving care. Further studies are needed on potential disparities in scheduled readmissions.

Medicaid patients at high risk for frequent hospital admission: real-time identification and remediable risks

Patients with frequent hospitalizations generate a disproportionate share of hospital visits and costs. Accurate determination of patients who might benefit from interventions is challenging: most patients with frequent admissions in 1 year would not continue to have them in the next. Our objective was to employ a validated regression algorithm to case-find Medicaid patients at high-risk for hospitalization in the next 12 months and identify intervention-amenable characteristics to reduce hospitalization risk. We obtained encounter data for 36,457 Medicaid patients with any visit to an urban public hospital from 2001 to 2006 and generated an algorithm-based score for hospitalization risk in the subsequent 12 months for each patient (0 = lowest, 100 = highest). To determine medical and social contributors to the current admission, we conducted in-depth interviews with high-risk hospitalized patients (scores >50) and analyzed associated Medicaid claims data. An algorithm-based risk score >50 was attained in 2,618 (7.2%) patients. The algorithm's positive predictive value was equal to 0.67. During the study period, 139 high-risk patients were admitted: 60 met inclusion criteria and 50 were interviewed. Fifty-six percent cited the Emergency Department as their usual source of care or had none. Sixty-eight percent had >1 chronic medical conditions, and 42% were admitted for conditions related to substance use. Sixty percent were homeless or precariously housed. Mean Medicaid expenditures for the interviewed patients were $39,188 and $84,040 per patient for the years immediately prior to and following study participation, respectively. Findings including high rates of substance use, homelessness, social isolation, and lack of a medical home will inform the design of interventions to improve community-based care and reduce hospitalizations and associated costs.

Quality of primary care and hospital admissions for diabetes mellitus in England

The National Health Service in England has invested substantially in recent years to improve the quality of primary care services for patients with chronic diseases such as diabetes. A key aim of this investment is to reduce associated complication rates and decrease consequent hospital admission rates. The goal of the study was to examine associations between the quality of primary care services and hospital admission rates for diabetes mellitus in England. An ecological cross-sectional study design was used. Three hundred three primary care trusts in England participated in the public reporting and performance-linked reimbursement of quality measures, including measures relevant to diabetes care. A total of 1,760,898 persons with diabetes registered with 8441 family practices in England. Hospital admission rates (total admissions for diabetes, admissions for ketoacidosis) were compared with quality of care scores, diabetes prevalence and neighborhood socio-economic status. We found a 10-fold variation across the country in total admissions for diabetes despite uniformly high scores on quality measures over the first year of the new family practitioner contract. Significant but weak inverse associations were found between primary care quality scores and hospital admission rates in patients aged 60 years and older, with a correlation coefficient of -0.21 (P < .001) between glycemic control and total admissions. Neighborhood socioeconomic status was more strongly correlated with total hospital admission rates than quality scores in patients aged 25-59 years (r = 0.58; P < .001) and 60 years and older (r = 0.45; P < .001). Quality of care scores and prevalence data were available only at the practice level rather than at the patient level. Improving the quality of primary care services may lead to modest reductions in demand for hospital services among older patients with diabetes. However, low neighborhood socioeconomic status is more strongly associated with hospital admission rates for diabetes.

Nutritionist visits, diabetes classes, and hospitalization rates and charges: the Urban Diabetes Study

OBJECTIVE

We evaluated the association of different types of educational visits for diabetic patients of the eight Philadelphia Health Care Centers (PHCCs) (public safety-net primary care clinics), with hospital admission rates and charges reported to the Pennsylvania Health Care Cost Containment Council.

RESEARCH DESIGN AND METHODS

The study population included 18,404 patients who had a PHCC visit with a diabetes diagnosis recorded between 1 March 1993 and 31 December 2001 and had at least 1 month follow-up time.

RESULTS

A total of 31,657 hospitalizations were recorded for 7,839 (42.6%) patients in the cohort. After adjustment for demographic variables, baseline comorbid conditions, hospitalizations before the diabetes diagnosis, and number of other primary care visits, having had any type of educational visit was associated with 9.18 (95% CI 5.02-13.33) fewer hospitalizations per 100 person-years and $11,571 ($6,377 to $16,765) less in hospital charges per person. Each nutritionist visit was associated with 4.70 (2.23-7.16) fewer hospitalizations per 100 person-years and a $6,503 ($3,421 to $9,586) reduction in total hospital charges.

CONCLUSIONS

Any type of educational visit was associated with lower hospitalization rates and charges. Nutritionist visits were more strongly associated with reduced hospitalizations than diabetes classes. Each nutritionist visit was associated with a substantial reduction in hospital charges, suggesting that providing these services in the primary care setting may be highly cost-effective for the health care system.