Profiling outcomes of ambulatory care: casemix affects perceived performance

Chronic illness with complexity: implications for performance measurement of optimal glycemic control

OBJECTIVE

To evaluate the association between chronic illness with complexity (CIC) and optimal glycemic control.

PARTICIPANTS

Cross-sectional and longitudinal analyses of Diabetes Epidemiologic Cohort database of Veterans Health Administration (VHA) users with diabetes, less than 75 years old, with HbA1c tests in fiscal year (FY) 1999 and 2000, alive at FY2000 end (N = 95,423).

DESIGN/MEASUREMENTS

Outcomes were HbA1c < 7% in each FY. CIC included three domains: nondiabetes physical illness, diabetes-related, and mental illness/substance abuse conditions. Other independent variables included age, gender, race, marital status, VHA priority status, and diabetes severity. Longitudinal analyses were restricted to patients with HbA1c >or= 7% in FY1999 and included hospitalizations between final HbA1c's in FY1999 and FY2000. Multiple logistic regressions examined associations between CIC categories and HbA1c.

RESULTS

In FY1999, 33% had HbA1c <7%. In multivariate analyses, patients with nondiabetes physical illness and mental illness/substance abuse were more likely to have HbA1c <7% in FY1999 [adjusted odds ratios for cancer (AOR), 1.31; 95% CI (1.25-1.37); mental illness only, 1.18; 95% CI (1.14-1.22)]. Those with diabetes-related complications were less likely to have HbA1c <7% in FY1999. Associations generally held in FY2000. However, conditions in the mental illness/substance abuse complexity domain were less strongly associated with HbA1c <7%. Macrovascular-related hospitalizations were positively associated with HbA1c <7% [AOR, 1.41; 95% CI (1.34-1.49)].

CONCLUSIONS

The association between CIC and HbA1c <7% is heterogeneous and depends on the domain of complexity. The varying associations of CIC categories with optimal glycemic control suggest the need for appropriate risk adjustment when using HbA1c <7% as a valid performance measure for diabetes quality of care.

Use of risk-adjusted change in health status to assess the performance of integrated service networks in the Veterans Health Administration

OBJECTIVE

Health outcome assessments have become an expectation of regulatory and accreditation agencies. We examined whether a clinically credible risk adjustment methodology for the outcome of change in health status can be developed for performance assessment of integrated service networks.

STUDY DESIGN

Longitudinal study.

SETTING

Outpatient.

STUDY PARTICIPANTS

Thirty-one thousand eight hundred and twenty-three patients from 22 Veterans Health Administration (VHA) integrated service networks were followed for 18 months.

MAIN MEASURE

The physical (PCS) and mental (MCS) component scales from the Veterans Rand 36-items Health Survey (VR-36) and mortality. The outcomes were decline in PCS (decline in PCS scores greater than -6.5 points or death) and MCS (decline in MCS scores greater than -7.9 points).

RESULTS

Four thousand three hundred and twenty-eight (13.6%) patients showed a decline in PCS scores greater than -6.5 points, 4322 (13.5%) had a decline in MCS scores by more than -7.9 points, and 1737 died (5.5%). Multivariate logistic regression models were used to adjust for case-mix. The models performed reasonably well in cross-validated tests of discrimination (c-statistics = 0.72 and 0.68 for decline in PCS and MCS, respectively) and calibration. The resulting risk-adjusted rates of decline in PCS and MCS and ranks of the networks differed considerably from unadjusted ratings.

CONCLUSION

It is feasible to develop clinically credible risk adjustment models for the outcomes of decline in PCS and MCS. Without adequate controls for case-mix, we could not determine whether poor patient outcomes reflect poor performance, sicker patients, or other factors. This methodology can help to measure and report the performance of health care systems.

Profiling quality of diabetes care in a Veterans Affairs Healthcare System

Profiling care on the basis of standard sets of measures has been extensively studied in the inpatient setting. However, less attention has been given to profiling outpatient care. The purpose of this study was to determine the influence of case-mix adjustment when profiling care for persons with diabetes. This is a cross-sectional study using medical and pharmacy data. Four process and 3 outcomes measures were used to assess the quality of care provided between 4 outpatient clinics. Diabetics were predominantly elderly (mean = 66 years), married (61%), white (73%), males (96%), with high body mass index (31 +/- 6.3 kg/m2), and mean comorbidity score of 4.2 +/- 1.8 conditions. Screening for hemoglobin A1c (HbA1c) and microalbuminuria was frequently performed in all clinics. However, 61% (n = 1697) and 36% (n = 254) of study patients had not undergone foot or eye examinations during the study period, respectively. Approximately 27% (n = 408), 41% (n = 643), and 26% (n = 515) of the study patients had poor glycemic, renal function, and lipid control, respectively. Significant differences (P < .05) in poor HbA1c and creatinine clearance rates between the clinics were observed after adjusting for patient case-mix. No differences between the clinics in cholesterol levels were observed after adjusting for patient case-mix. Overall, these clinics performed well in process of care measures, except for foot screening. After adjusting for patient case-mix, significant disparities between the clinics were observed with respect to glycemic control and renal function measures, whereas differences were nullified with respect to cardiovascular outcome measure.

Case-mix adjusting performance measures in a veteran population: pharmacy- and diagnosis-based approaches

OBJECTIVE

To compare the rankings for health care utilization performance measures at the facility level in a Veterans Health Administration (VHA) health care delivery network using pharmacy- and diagnosis-based case-mix adjustment measures.

DATA SOURCES/STUDY SETTING

The study included veterans who used inpatient or outpatient services in Veterans Integrated Service Network (VISN) 20 during fiscal year 1998 (October 1997 to September 1998; N = 126,076). Utilization and pharmacy data were extracted from VHA national databases and the VISN 20 data warehouse.

STUDY DESIGN

We estimated concurrent regression models using pharmacy or diagnosis information in the base year (FY1998) to predict health service utilization in the same year. Utilization measures included bed days of care for inpatient care and provider visits for outpatient care.

PRINCIPAL FINDINGS

Rankings of predicted utilization measures across facilities vary by case-mix adjustment measure. There is greater consistency within the diagnosis-based models than between the diagnosis- and pharmacy-based models. The eight facilities were ranked differently by the diagnosis- and pharmacy-based models.

CONCLUSIONS

Choice of case-mix adjustment measure affects rankings of facilities on performance measures, raising concerns about the validity of profiling practices. Differences in rankings may reflect differences in comparability of data capture across facilities between pharmacy and diagnosis data sources, and unstable estimates due to small numbers of patients in a facility.

The best of both worlds? Potential of hybrid prospective/concurrent risk adjustment

BACKGROUND

There remains considerable uncertainty about whether prospective or concurrent risk adjustment (RA) is preferable. Although concurrent models have better predictive power than prospective models, the large payments associated with concurrent RA create incentives for fraudulent coding. A hybrid strategy--in which prospective payments were used for patients with low expected costs and concurrent payments were available upon the diagnosis of a small number of common, expensive conditions--might improve predictive performance while requiring less auditing than fully concurrent RA. In addition, within-condition RA (using clinical data) for the selected conditions could further improve predictive power.

OBJECTIVES

To assess how such a hybrid strategy might perform, focusing on a small number of chronic, expensive conditions that are verifiable (hence auditable).

SUBJECTS AND MEASURES

All patients from seven health plans who had two complete years of utilization data were considered. RA models were estimated among patients younger than 65 (n = 319,209) using the Hierarchical Coexisting Conditions (HCC) model with and without stratification of the sample based on the presence of one or more of 100 verifiable, expensive, predictive conditions (VEP100). R2 and predictive ratios were calculated for each model studied.

RESULTS

Patients with a VEP100 condition (9.3% of the population) accounted for 84.3% of the variation in cost. R2 was 0.08 using a prospective HCC model on the entire population, but increased to 0.26 for a hybrid using prospective HCCs on the 90.7% of the sample without a VEP100 condition and a simple concurrent model consisting of dummy variables for each of the VEP100 conditions.

CONCLUSION

Combined with targeted auditing, a hybrid approach to RA could improve our ability to match payments to costs. However, because this would require additional, costly data collection, more research is needed to determine whether this benefit justifies the data collection and auditing burden.

Clinicians, educators, and investigators in general internal medicine: bridging the gaps

Financial and time pressures, disparate promotional pathways, geographic separation, and difficulty acknowledging personal fallibility can contribute to polarization of clinician-educators and investigators in general internal medicine (GIM). As a consequence, clinician-educators and investigators may fail to use their joint expertise, may encounter friction in their relationships, and may present a troubled image to trainees considering careers in GIM. We suggest specific strategies that clinician-educators, investigators, administrative leaders, and medical schools might use to foster collaboration.

Risk-adjusted mortality rates as a potential outcome indicator for outpatient quality assessments

OBJECTIVE

The quality of outpatient medical care is increasingly recognized as having an important impact on mortality. We examined whether a clinically credible risk adjustment methodology can be developed for outpatient quality assessments.

RESEARCH DESIGN

This study used data from the 1998 National Survey of Ambulatory Care Patients, a prospective monitoring system of outcomes of patients receiving ambulatory care in the Veterans Affairs (VA) integrated service networks.

SUBJECTS

Thirty-one thousand eight hundred twenty-three patients were followed for 18 months.

MEASURES

The main study outcome measures were observed and risk-adjusted mortality rates.

RESULTS

Of the 31,823 patients, 1559 (5%) died during the 18-months of follow-up. Observed mortality rates across the 22 VA integrated service networks varied significantly from 3.3% to 6.7% (P <0.001). Age, gender, comorbidities (Charlson Index), physical health, and mental health were significant predictors of dying. The resulting risk-adjusted mortality model performed well in cross-validated tests of discrimination (c-statistic = 0.768; 95% CI, 0.749-0.788) and calibration. Analysis of variance confirmed that the 22 integrated service networks differed in their average level of expected risk (P <0.001). Risk-adjusted rates and ranks of the networks differed considerably from unadjusted ratings.

CONCLUSIONS

Risk-adjusted mortality rates may be a useful outcome measure for assessing quality of outpatient care. We have developed a clinically credible risk adjustment model with good performance properties using sociodemographics, diagnoses, and functional status data. The resulting risk adjustment model altered assessments of the performance of the integrated service networks when compared with the unadjusted mortality rates.

Impact of sociodemographic case mix on the HEDIS measures of health plan quality

BACKGROUND

The widely used Health Plan Employer Data and Information Set (HEDIS) measures may be affected by differences among plans in sociodemographic characteristics of members.

OBJECTIVE

The objective of this study was to estimate effects of geographically linked patient sociodemographic characteristics on differential performance within and among plans on HEDIS measures.

RESEARCH DESIGN

Using logistic regression, we modeled associations between age, sex, and residential area characteristics of health plan members and results on HEDIS measures. We then calculated the impact of adjusting for these associations on plan-level measures.

SUBJECTS

This study included 92,232 commercially insured members with individual-level HEDIS data and an additional 20,615 members whose geographic distribution was provided.

MEASURES

This study used 7 measures of screening and preventive services.

RESULTS

Performance was negatively associated with percent receiving public assistance in the local area (6 of 7 measures), percent black (5 measures), and percent Hispanic (2 measures) and positively associated with percent college educated (6 measures), percent urban (2 measures), and percent Asian (1 measure) after controlling for plan and product type. These effects were generally consistent across plans. When measures were adjusted for these characteristics, rates for most plans changed by less than 5 percentage points. The largest change in the difference between plans ranged from 1.5% for retinal exams for people with diabetes to 20.2% for immunization of adolescents.

CONCLUSIONS

Performance on quality indicators for individual members is associated with sociodemographic context. Adjustment has little impact on the measured performance of most plans but a substantial impact on a few. Further study with more plans is required to determine the appropriateness and feasibility of adjustment.

Defining and measuring quality of diabetes care

The literature on diabetes mellitus has increasingly focused on the quality of diabetes care and its measurement. Serious and widespread quality problems exist throughout American medicine. Current efforts to improve will not succeed unless we undertake a major, systematic effort to overhaul how we deliver health care services, educate and train clinicians, and assess and improve quality. This article defines the components of quality of diabetes care provision and discusses approaches to their measurement individually and globally.

Inadequate management of blood pressure in a hypertensive population

BACKGROUND

Many patients with hypertension have inadequate control of their blood pressure. Improving the treatment of hypertension requires an understanding of the ways in which physicians manage this condition and a means of assessing the efficacy of this care.

METHODS

We examined the care of 800 hypertensive men at five Department of Veterans Affairs sites in New England over a two-year period. Their mean (+/-SD) age was 65.5+/-9.1 years, and the average duration of hypertension was 12.6+/-5.3 years. We used recursive partitioning to assess the probability that antihypertensive therapy would be increased at a given clinic visit using several variables. We then used these predictions to define the intensity of treatment for each patient during the study period, and we examined the associations between the intensity of treatment and the degree of control of blood pressure.

RESULTS

Approximately 40 percent of the patients had a blood pressure of > or =160/90 mm Hg despite an average of more than six hypertension-related visits per year. Increases in therapy occurred during 6.7 percent of visits. Characteristics associated with an increase in antihypertensive therapy included increased levels of both systolic and diastolic blood pressure at that visit (but not previous visits), a previous change in therapy, the presence of coronary artery disease, and a scheduled visit. Patients who had more intensive therapy had significantly (P<0.01) better control of blood pressure. During the two-year period, systolic blood pressure declined by 6.3 mm Hg among patients with the most intensive treatment, but increased by 4.8 mm Hg among the patients with the least intensive treatment.

CONCLUSIONS

In a selected population of older men, blood pressure was poorly controlled in many. Those who received more intensive medical therapy had better control. Many physicians are not aggressive enough in their approach to hypertension.