The health status of veterans using mobile clinics in rural areas.

Between 1992 and 1994, the Department of Veterans Affairs (VA) experimented with mobile clinics to provide health care for rural veterans. The objective was to assess the health status of rural mobile clinics' patients and compare this with patients receiving care in VA hospital-based clinics. This study hypothesized that hospital-based clinic patients would be more ill (i.e., have a greater reduction in health status). The Medical Outcomes Study (MOS) Short Form was used to evaluate patients' health status. Most patients sought care for the management of chronic disease. Patients in both groups had similar types of diseases. Mobile clinic patients were as ill as hospital-based patients (i.e., similar health status scores). This study shows that rural veterans have a case mix and a reduction in health status similar to that of VA hospital-based patients. Planners should account for this health reduction when planning the kinds of facilities and services needed in rural areas.

The hospital multistay rate as an indicator of quality of care.

OBJECTIVES: To evaluate the hospital multistay rate to determine if it has the attributes necessary for a performance indicator that can be applied to administrative databases. DATA SOURCES/STUDY SETTING: The fiscal year 1994 Veterans Affairs Patient Treatment File (PTF), which contains discharge data on all VA inpatients. STUDY DESIGN: Using a retrospective study design, we assessed cross-hospital variation in (a) the multistay rate and (b) the standardized multistay ratio. A hospital's multistay rate is the observed average number of hospitalizations for patients with one or more hospital stays. A hospital's standardized multistay ratio is the ratio of the geometric mean of the observed number of hospitalizations per patient to the geometric mean of the expected number of hospitalizations per patient, conditional on the types of patients admitted to that hospital. DATA COLLECTION/EXTRACTION METHODS: Discharge data were extracted for the 135,434 VA patients who had one or more admissions in one of seven disease groups. PRINCIPAL FINDINGS: We found that 17.3 percent (28,300) of the admissions in the seven disease categories were readmissions. The average number of stays per person (multistay rate) for an average of seven months of follow-up ranged from 1.15 to 1.45 across the disease categories. The maximum standardized multistay ratio ranged from 1.12 to 1.39. CONCLUSIONS: This study has shown that the hospital multistay rate offers sufficient ease of measurement, frequency, and variation to potentially serve as a performance indicator.

Evaluation of the VA mobile clinics demonstration project.

In 1988 the Veterans' Benefits and Services Act attempted to solve the problem of the lack of adequate VA healthcare facilities in rural areas by establishing a demonstration program using mobile clinics. Six clinics operated in areas that were at least 100 miles from a VA healthcare facility during the time period between October 1, 1992 and May 28, 1994. This article evaluated the effect of the mobile clinics' structural limitations on clinical care, the increased number of sites on VA usage, and cost. Limited space for storage of medical records and the unavailability of laboratory, electrocardiographic, or radiographic facilities significantly affected clinical practice. However, even with these space limitations, veterans' use of healthcare in the areas served by the mobile clinics increased significantly in comparison to reference areas. The direct costs per visit averaged more than three times what the VA would have reimbursed the private sector.

How do physicians and nurses spend their time in the emergency department?

STUDY OBJECTIVES: To determine how emergency physicians and nurses spend their time on emergency department activities. METHODS: An observational time-and-motion study was performed at a 36-bed ED with annual census of 84,000 in a central city teaching hospital sponsoring an emergency medicine residency program. Participants were emergency medicine faculty physicians, second- and third-year emergency medicine resident physicians, and emergency nurses. A single investigator followed individual health care providers for 180-minute periods and recorded time spent on various activities, type and number of activities, and distance walked. Activities were categorized as direct patient care (eg. history and physical examination), indirect patient care (eg. charting), or non-patient care (eg. break time). RESULTS: On average, subjects spent 32% of their time on direct patient care, 47% on indirect patient care, and 21% on non-patient care Faculty physicians, residents, and emergency nurses differed in the time spent on these three categories of activities. Although the overall time spent on direct patient care activities was not significantly different, emergency nurses spent more of their time (2.2%) providing comfort measures (a subcategory of direct patient care) than did faculty physicians (.05%) or resident physicians (.03%). Emergency nurses spent 38.9% of their time performing indirect care, whereas faculty physicians spent 51.3% and resident physicians 53.7%. Resident physicians spent more time charting than did faculty physicians or emergency nurses (21.4%, 11.9%, and 6.9%, respectively). Emergency nurses spent more time on personal activities than did physicians, and faculty physicians walked less than either emergency nurses or resident physicians. CONCLUSION: Emergency physicians and nurses spent almost half of their time on indirect patient care. Physicians spent significantly more time on indirect patient care activities and significantly less time on personal activities than did nurses.

Application of an analytic model to early readmission rates within the Department of Veterans Affairs.

OBJECTIVES: Adverse outcome rates are increasingly used as yardsticks for the quality of hospital care. However, the validity of many outcome studies has been undermined by the application of one outcome to all patients in large, diagnostically diverse populations, many of which lack evidence of a link between antecedent process of care and the rate of the outcome, the underlying assumption of the analysis. METHODS: To address this analytic problem, the authors developed a model that improves the ability to identify quality problems because it selects diseases for which there are processes of care known to affect the outcome of interest. Thus, for these diseases, the outcome is most likely to be causally related to the antecedent care. In this study of hospital readmissions, risk-adjusted models were created for 17 disease categories with strong links between process and outcome. Using these models, we identified outlier hospitals. RESULTS: The authors hypothesized that if the model improved on identifying hospitals with quality of care problems, then outlier status would not be random. That is, hospitals found to have extreme rates in one year would be more likely to have extreme rates in subsequent years, and hospitals with extreme rates in one condition would be more likely to have extreme rates in related disease categories. It was hypothesized further that the correlation of outlier status across time and across diseases would be stronger in the 17 disease categories selected by the model than in 10 comparison disease categories with weak links between process and outcome. CONCLUSIONS: The findings support all these hypotheses. Although the present study shows that the model selects disease-outcome pairs where hospital outlier status is not random, the causal factors leading to outlier status could include (1) systematic unmeasured patient variation, (2) practice pattern variation that, although stable with time, is not indicative of substandard care, or (3) true quality-of-care problems. Primary data collection must be done to determine which of these three factors is most causally related to hospital outlier status.

Pain and tissue-interface pressures during spine-board immobilization.

STUDY OBJECTIVES: Although spine boards are one of the main EMS means of immobilization and transportation, few studies have addressed the discomfort and potential harmful consequences of using this common EMS tool. We compared the levels of pain and tissue-interface (contact) pressures in volunteers immobilized on spine boards with and without interposed air mattresses. DESIGN: Prospective crossover study. SETTING: Emergency department of Methodist Hospital of Indiana, Indianapolis, Indiana. PARTICIPANTS: Twenty healthy volunteers who had not taken any analgesic drugs in the preceding 24 hours, were not experiencing any pain at the time of the study, and did not have history of chronic back pain. INTERVENTIONS: To simulate prehospital transport conditions, we immobilized volunteers with hard cervical collars and single-buckle chest straps on wooden spine boards with or without commercially available medical air mattresses. The crossover order was randomized. After 80 minutes, immobilization measures were discontinued and the subjects were allowed to get off the boards for a recovery period of 60 minutes. Subjects were then studied for a second 80-minute period with the opposite intervention. At baseline and at 20-minute intervals, the level of pain was rated with a 100-mm visual analog scale. Tissue-interface pressures were measured at the occiput, sacrum, and left heel. RESULTS: Mean pain on the visual analog scale was 9.7 mm at the end of the mattress period and 37.5 mm at the end of the no-mattress period (P = .0001). Although there were no significant differences in pain between the two groups at time 0, volunteers reported significantly more pain during the no-mattress period at 20 (P = .003), 40 (P = .0001), and 60 minutes (P = .0001). All 20 subjects reported that immobilization on the spine board with the mattress was "much better" (five-point scale) than that without the mattress. Interface pressure levels were significantly less in the mattress period than in the no-mattress period measured at occiput (P = .0001), sacrum (P = .0001), and heel (P = .0001). CONCLUSION: In a simulated immobilization experiment, healthy volunteers reported significantly less pain during immobilization on a spine board with an interposed air mattress than during that on a spine board without a mattress. Tissue-interface pressures were significantly higher on spine boards without air mattresses. This and previous studies suggest that immobilization on rigid spine boards is painful and may produce tissue-interface pressure high enough to result in the development of pressure necrosis ("bedsores"). Emergency care providers should consider the use of interposed air mattresses to reduce the pain and potential tissue injury associated with immobilization on rigid spine boards.

Using administrative databases to evaluate the quality of medical care: a conceptual framework.

Health care is consuming an ever larger share of national resources in the United States. Measures to contain costs and evidence of unexplained variation in patient outcomes have led to concern about inadequacy in the quality of health care. As a measure of quality, the evaluation of hospitals through analysis of their discharge databases has been suggested because of the scope and economy offered by this methodology. However, the value of the information obtained through these analyses has been questioned because of the inadequacy of the clinical data contained in administrative databases and the resultant inability to control accurately for patient variation. We suggest, however, that the major shortcoming of prior attempts to use large databases to perform across-facility evaluation has resulted from the lack of a conceptual framework to guide the analysis. We propose a framework which identifies component areas and clarifies the underlying assumptions of the analytic process. For each area, criteria are identified which will maximize the validity of the results. Hospitals identified as having unexpectedly high unfavorable outcomes when our framework is applied will be those where poor quality will most likely be found by primary review of the process of care.(ABSTRACT TRUNCATED AT 250 WORDS)

Selecting disease-outcome pairs for monitoring the quality of hospital care.

Health care payors and providers are increasingly monitoring hospital discharge data bases for adverse events as markers for quality of care. The principal criticisms of these analyses have focused on the impediments to risk adjustment posed by the incompleteness and inaccuracy of the data bases. However, efforts to address the inadequacies of the data bases will not correct deficiencies of the analytic process. These deficiencies arise from the application of one adverse outcome to all disease states. Instead, analysis should be restricted to comparisons of subgroups of patients in which a close fit exists between the quality of care for the disease state and the expected outcome. Furthermore, these disease-outcome pairs should be minimally subject to measurement error. The authors present a conceptual framework for developing such meaningful disease-outcome pairs, and using the hospital discharge data base of the Department of Veterans Affairs, show how the framework can be used to devise a monitoring strategy for re-admission.