Integrating cost information with health management support system: an enhanced methodology to assess health care quality drivers.

Changes in health care delivery, reimbursement schemes, and organizational structure have required health organizations to manage the costs of providing patient care while maintaining high levels of clinical and patient satisfaction outcomes. Today, cost information, clinical outcomes, and patient satisfaction results must become more fully integrated if strategic competitiveness and benefits are to be realized in health management decision making, especially in multi-entity organizational settings. Unfortunately, traditional administrative and financial systems are not well equipped to cater to such information needs. This article presents a framework for the acquisition, generation, analysis, and reporting of cost information with clinical outcomes and patient satisfaction in the context of evolving health management and decision-support system technology. More specifically, the article focuses on an enhanced costing methodology for determining and producing improved, integrated cost-outcomes information. Implementation issues and areas for future research in cost-information management and decision-support domains are also discussed.

The cost and efficiency of hospital care provided by primary care physicians and medical subspecialists.

There is a perceived excess of subspecialists compared with primary care doctors, but there are few severity-adjusted data that characterize the care provided by these physician groups. In a nationwide hospital network, we studied outcomes of 17,185 patients who were hospitalized for 1 of 9 common internal medicine illnesses. For 4 of 9 conditions, the subspecialists treated more severely ill (P < .001) patients. The raw total charges for their care were higher (P < .002) for 4 of 9 conditions and longer stays were required for 2 conditions. After adjusting for severity of illness, differences between the physician groups became minimal. In nine-severity adjusted medical illnesses, subspecialists and primary care physicians provide care that produces similar results for length of stay, charge, and mortality. Health care manpower projections should be re-evaluated in light of this information.

The utility of hospital administrative data for generating a screening program to predict adverse outcomes.

A system to predict which patients will suffer medical complications or poor financial outcomes during a hospitalization would be very useful to providers of medical care. To develop such a system, we applied two previously developed indices that predict in-hospital complications to all 321,558 adult patients discharged from our hospital network. The indices identified 26,377 patients (8.2%) who experienced one or more medical complications. For these patients, high-risk admitting diagnoses were identified. We tabulated 4235 admitting diagnoses and focused on 26 (0.6%) diagnoses that were high-risk and high-volume for complications. We found that 25% of patients with these admitting diagnoses experienced complications during hospitalization. Prevention of these complications could have saved 1241 hospital days, 11 lives, and $10.5 million. Administrative data available at the time of admission can be useful in identifying the small subset of patients who are likely to experience adverse clinical outcomes during a hospitalization and those who are likely to generate adverse financial outcomes for the hospital.

The effect of gastroenterology training on the efficiency and cost of care provided to patients with diverticulitis.

BACKGROUND & AIMS: National trends emphasize the need for cost-efficient medical care with no diminution in quality. The most appropriate role for various physician groups has yet to be determined. The aim of this study was to investigate the efficiency of medical care provided by family practitioners (FPs), internists (IMs), and gastroenterologists (GIs) for acute diverticulitis. METHODS: All medicare hospitalizations from 1990 to 1993 in Illinois caused by acute diverticulitis, with FPs, IMs, or GIs as the primary attending physician, were included in the study. RESULTS: The primary attending physician was an FP in 1019 cases, an IM in 2535 cases, and a GI in 163 cases. The age and sex distributions were similar. The length of stay was significantly shorter (P < 0.0001) for GIs (7.4 +/- 6 days) than for FPs (7.9 +/- 14 days) or IMs (8.6 +/- 7 days). Readmission rate was significantly less (P < 0.03) for GIs (4.5%) than for FPs (7.7%) or IMs (10.0%). No significant differences were noted in complication rates or mortality. CONCLUSIONS: Patients with diverticulitis treated by GIs have a shorter hospital stay and a lower risk for readmission than patients treated by FPs or IMs. This improved quality of care should be considered by managed care organizations because they decide the role of various physician groups.

Use of statistical control charts to assess outcomes of medical care: pneumonia in Medicare patients.

Detection of nonrandom variation in outcomes with statistical control charts is at the heart of quality improvement techniques. The authors examined the charts' ability to detect variations in outcome of pneumonia. They surveyed Medicare claims data for DRG 89, pneumonia with complications or co-morbidities, from November 1988 through October 1991 at 20 Illinois hospitals with the most Medicare discharges for DRG 89. Control charts were constructed on five outcomes--mean length of stay, range of length of stay, mortality, readmissions, and complications. Standard techniques from industrial statistics were used to construct the historical means and control limits derived from 2 years of data, to plot the monthly samples from the 3rd year of data and to score the control charts for nonrandom variation at less than 1% probability. The observed number of control charts with nonrandom variation was 33 of 100; the expected number was 9.18 (p < 0.0001). Nineteen hospitals had 1 to 3 control charts with nonrandom variation on the five outcomes, whereas only one hospital had none. The number of control charts with nonrandom variation per hospital did not correlate with hospital size, occupancy, teaching status, location, or payer-mix. Statistical control charts provide simple tools for identification of nonrandom variation in outcomes. To the extent that these variations can be related to quality issues, the charts will be useful for quality management.