Applying diagnostic cost groups to examine the disease burden of VA facilities: comparing the six "Evaluating VA Costs" study sites with other VA sites and Medicare

Dual-System Use: Are There Implications for Risk Adjustment and Quality Assessment?

The authors examined the implications of dual-system use for risk adjustment and quality assessment. The sample (n = 34 151) included all veterans dually enrolled in the Veterans Health Administration (VA) and the private sector in 1998 with (1) an inpatient discharge from either a VA or Medicare setting for 1 of 6 conditions/procedures and (2) inpatient and/or outpatient use in both the VA and private sector. The authors used the Diagnostic Cost Groups risk-adjustment system to obtain concurrent and prospective health status (relative risk scores) using veterans' Medicare diagnoses only, VA diagnoses only, and diagnoses from both systems. Both concurrent and prospective relative risk scores increased when diagnoses from both systems were used; the population's disease profile also was affected. The authors conclude that it is important to capture the true disease burden of the population by obtaining diagnoses from all health care systems providing care to facilitate meaningful comparisons of performance.

Measures of adherence to oral hypoglycemic agents at the primary care clinic level: the role of risk adjustment

BACKGROUND

Prior research found that in the Veterans Affairs health care system (VA), the proportion of patients adherent to oral hypoglycemic agents varies from 50% to 80% across primary care clinics. This study examined whether variation in patient and facility characteristics determined those differences.

METHODS

Retrospective cohort study of 444,418 VA primary care patients with diabetes treated in 559 clinics in fiscal year (FY) 2006-2007. Patients' adherence to each oral hypoglycemic agent was computed for the first 3 months of FY2007, and averaged across agents to produce an adherence score for the patient's overall regimen. Patients with an adherence score over 0.8 were defined as adherent. Risk adjustment used hierarchical logistic regression accounting for patient factors and facility effects by clustering patients within clinics and clinics within parent VA medical centers. We then assessed the influence of risk adjustment using observed-to-expected (O/E) ratios computed for each clinic.

RESULTS

The mean unadjusted proportion of adherent patients in clinics was 0.715 (interdecile range 0.559-0.826). The percent variation in patient's likelihood of being adherent explained at the patient, clinic, and parent VA medical center levels was 2.94%, 0.27%, and 0.76%, respectively. The mean clinic-level observed-to-expected ratio was 1.001 (interdecile range 0.975-1.027).

CONCLUSIONS

The variation in the proportion of patients adherent across clinics remained large after risk adjustment. As patient and facility effects explained only 4% of the variance in adherence, comparing clinics based on unadjusted scores is a reasonable starting point unless more predictive patient, provider, and facility factors are identified.

Between-visit workload in primary care

BACKGROUND

The time spent and complexity of work done by primary internal medicine physicians between office visits has not been well studied.

OBJECTIVE

To measure the time and complexity of this care.

DESIGN

Cross-sectional study.

SETTING

General internists practicing on primary care teams with electronic medical records at a tertiary Veterans Health Administration Medical Center.

PARTICIPANTS

Ten physicians.

MAIN MEASURES

The project was designed to measure physician work between office visits. The electronic record was used to record the number and complexity of work events by physicians for 1 month. Complexity of work was measured on five levels ranging from Level I with no change in management, Level II with change in management of one disease, Level III of two diseases, Level IV of three diseases, and Level V of four or more diseases. Time sampling was done over 5 days to determine the time spent by level of complexity. Total time per physician was calculated by multiplying the number of events each physician captured by the average time for that physician for that level of complexity.

KEY RESULTS

Physicians worked a median of 7.9 h per week between office visits. Work was apportioned among Level I (18.3%), Level II (38.3%), Level III (36.5%), Level IV (4.6%), and Level V (2.3%).

LIMITATIONS

Single VA population and self-reported data. Findings may not be generalizable to other practice settings.

CONCLUSION

Primary internists spent a median of 7.9 h per week in work between office visits with 82% of the time involved in changes in management.

Depression and Other Mental Health Diagnoses After Stroke Increase Inpatient and Outpatient Medical Utilization Three Years Poststroke

OBJECTIVE

Poststroke depression (PSD) has been linked to negative outcomes, including mortality and decreased functioning. However, the effect of PSD and other mental health conditions on inpatient and outpatient healthcare utilization after stroke has not been examined. The primary objective of this study was to evaluate the relationship between PSD and healthcare utilization after stroke. The secondary objective was to evaluate the relationship between other mental health diagnoses and medical utilization after stroke.

METHOD

We examined 3 years of poststroke healthcare utilization data in a national cohort of veterans with ischemic stroke. Mental health diagnoses were identified with inpatient International Classification of Diseases, 9th Revision codes. Multivariate analysis of variance was used to compare patient characteristics and multivariate linear regression to model utilization in: 1) patients with PSD, 2) patients diagnosed with other mental health conditions poststroke, and 3) patients with no mental health diagnosis.

RESULTS

Of 51,119 veterans identified, 2405 (5%) received a PSD diagnosis and 2257 (4%) received a diagnosis of another mental health condition after their stroke. Patients with PSD had significantly more inpatient hospitalization days and outpatient visits than those without any mental health diagnosis, even after adjusting for the number of mental health clinic visits. Likewise, patients diagnosed with other mental health diagnoses had greater medical utilization than patients without any mental health diagnosis. Both PSD and other mental health diagnoses independently predicted medical utilization.

CONCLUSION

Mental health diagnosis after stroke increases inpatient and outpatient healthcare utilization in the first 3 years poststroke. Additional biologic and psychosocial factors should be investigated.

Estimating private sector values for VA health care: an overview

OBJECTIVES

To provide an overview of methods used to establish what taxpayer costs would be if all Veterans Health Administration (VA) patient care were paid for by the federal government but provided in the private sector.

METHODS

Study assumptions included (1) that there would be a hypothetical policy change to pay for VA care through a Medicare-based fee-for-service program, (2) that the VA coverage benefit would not change, (3) that practice styles would remain the same, and (4) that there would be no impact on market values. To achieve the objective, project staff adapted Medicare payment schedules and guidelines, where available, with oversight of an advisory committee with VA and non-VA expertise in costs and data. For six sites, detailed payments were estimated using VA utilization databases and software and Medicare rate schedules available in the private sector. Overhead, interest on capital, and malpractice costs were added to VA-reported operating costs. Patient severity was examined, and patient-level costs were explored.

FINDINGS

Detailed methods for pricing seven types of health services are presented. Three methods articles focus on process issues.

DISCUSSION

Because VA care is not directly comparable with private sector health care as a result in part of differences in benefits covered and the scope of services provided, estimating costs for this care based on a private sector model requires careful consideration of market valuation approaches. The articles in this supplement describe the methods used to estimate market values for VA care so that other researchers can use them in future studies.