Preventive service utilisation as a predictor for emergency dental examinations.

OBJECTIVE: To quantify the relationship between receipt of routine dental care and the use of non-trauma related emergency dental services. DESIGN: A multiple logistic regression was run on administrative dental claim and encounter data. The model dependent variable was the use of non-trauma related emergency dental care. Predictors included previous year oral examinations, radiographs, dental cleanings and, as a control, member age. SETTING: Administrative data were obtained from a dental health maintenance organisation located in the state of Texas. SUBJECTS: Claim and encounter data for 2,947 insured members were used, representing experience from 1995 through 1996. OUTCOME MEASURES: The outcome of interest was the use of non-trauma related emergency dental services. RESULTS: Results demonstrated empirically that those who availed themselves of preventive dental services were significantly less likely to use non-trauma related emergency services (P<0.01). The probability of needing non-trauma related dental services in 1996 was 42.7% lower among those who had an examination in 1995 when compared with those who did not. When analysed in a simple logistic regression, dental cleanings in 1995 were also significantly associated with a decreased probability of needing non-trauma related emergency services. However, this relationship did not hold in the controlled model, which was probably due to multicollinearity. CONCLUSIONS: This study provides evidence of the value of periodic preventive dental examinations and services. Those who receive such services are less likely to use non-trauma related emergency dental services.

Pharmaceutically-based severity stratification of an asthmatic population.

Algorithms designed to precisely identify disease severity for a given patient within a managed care population are helpful in organizing targeted interventions. These algorithms are also attracting considerable attention within the medical research community. Several health risk screening instruments have been developed; however, these involve survey methodologies and have several shortcomings. We present a valid and efficient method for predicting healthcare resource utilization among asthmatics in an Health Maintenance Organization (HMO) population. First, various diagnosis, procedure and pharmacy billing codes were used to identify the asthmatics within the database. The screening algorithm awards points each time one of these codes is identified for an HMO member. By varying the number of points necessary to consider a patient asthmatic, the sensitivity, specificity, positive and negative predictive values of the algorithm can be adjusted. Once identified as asthmatic, subjects were then stratified into severity levels based on pharmacy data. Severity stratification was validated directly by measuring asthma-related bed days utilized during the 12 months following the date of stratification. Our identification algorithm estimated an asthma prevalence of 3.84% within the studied population, with age-specific prevalence estimates that closely mirrored previously published survey data. There was a monotonic relationship between pharmacy severity levels and inpatient resource utilization. For example, asthmatics in severity level 1 used only 92 hospital days per 1000 asthmatics in the year following characterization, while those in levels 2-5 used 133, 156, 277 and 1168 hospital days (P < 0.001), respectively. Results from this model can be used as adjusters in other predictive models or stand alone to represent a patient's severity of illness.

Patterns of treatment for older women with newly diagnosed breast carcinoma.

The patterns of treatment for newly diagnosed breast carcinomas in older women aged 65 years or more have not been well studied, particularly in relation to screening mammography performed for the early detection of breast cancer. Therefore, the present study was performed to determine the patterns of treatment for newly diagnosed breast carcinomas in older women aged 65 years or more and to determine the impact of screening mammography on these patterns of treatment. The study population consisted of 130 women aged 65 years or more with newly diagnosed breast carcinoma from 1993 through 1994 enrolled in a large health maintenance organization. The medical records of these 130 patients were reviewed. The breast cancers detected in women who had undergone mammographic screening were more often eligible for breast-conservation treatment than the breast cancers detected in women who had not undergone mammographic screening (79% vs. 48%, respectively; p = 0.0044). For the breast cancers that were eligible for breast-conservation treatment, breast-conservation treatment was used more often for the women who had undergone mammographic screening than for the women who had not undergone mammographic screening (70% vs. 27%, respectively; p = 0.0077). Definitive radiation therapy was delivered after breast-conservation surgery in 89% (55/62) of the patients. Medical oncology consultation was obtained more commonly for more advanced staged breast cancers. Clinical management was altered in 9% (12/130) of the patients because of older patient age, comorbid medical conditions, or both. These findings have documented the patterns of treatment for older women aged 65 years or more with newly diagnosed breast cancer. Screening mammography had a significant impact on the patterns of breast cancer management, as demonstrated by the association of screening mammography with an increased eligibility for breast-conservation treatment and an increased use of breast-conservation treatment for eligible patients.

Screening mammography: experience in a health maintenance organization.

PURPOSE: To evaluate (a) the relationship between mammogram interpretation and diagnosis of new breast cancer and (b) interprovider variation in mammogram interpretation. MATERIALS AND METHODS: Interpretations of screening mammograms (133,668 mammograms in 114,899 women) acquired during 21 months in a large health maintenance organization were categorized (categories 1-5) with use of a standard format. During 1 year after mammography, new breast cancer was identified with use of claims data. Interprovider variation in the categories read was evaluated, and percentages of these categories were correlated with breast cancer detection. RESULTS: Over the 21 months, 1,018 mammograms were followed by a diagnosis of new breast cancer. The category of mammogram interpretation was strongly associated with the diagnosis of new breast cancer; in 47.5% cases of category 5 mammograms, breast cancer was diagnosed. There was substantial interprovider variation in the percentages of category 3, 4, or 5 mammograms read. The percentage of category 4 and 5 mammograms read correlated inversely with the likelihood of cancer detection (Pearson correlation coefficient [r] = -.4778 after log-log transformation, P < .001). CONCLUSION: A strong correlation existed between a mammographic abnormality suggestive of cancer and its detection; however, substantial interprovider variation in the reading of category 3, 4, and 5 mammograms and their positive predictive values existed. Reduction of interprovider variation should improve quality of care because the number of false-negative and false-positive mammograms should decrease.

The use of administrative data to risk-stratify asthmatic patients.

In this article, a simple methodology to risk-stratify asthmatics is presented and validated. Such a model can be used to identify those high risk and more severely ill asthmatics who could benefit the most from case management and increased educational efforts. Using logistic regression, the model was created to predict the probability of an asthma-related admission among all asthmatics who were members of a large HMO during calendar year 1994 (N = 54,573). The model used data from pharmacy, laboratory, and specialist claims, as well as encounter and demographic data available in U.S. Healthcare's administrative database. A member's prior asthma-specific utilization patterns, pharmaceutically determined severity of illness, and length of enrollment in the managed care organization had the most influence on the equation. A cross-validation of the model confirms how administrative data can be used to accurately risk-stratify those with a chronic disease. Finally, some additional research possibilities associated with the identification of high risk subscribers using only administrative data are outlined.

Evaluation of an algorithm to identify women with carcinoma of the breast.

Although claims data are increasingly being used to measure and manage the cost and quality of health care, few studies have evaluated algorithms developed for such analyses. Therefore, the present study was performed to evaluate prospectively a previously published algorithm used to identify women with the new diagnosis of carcinoma of the breast. This algorithm had been developed from the patterns of claims that suggested common clinical presentations of carcinoma of the breast. In the present study, this algorithm was used to identify 177 potential cases of women with newly diagnosed carcinoma of the breast from the claims database of a large health maintenance organization (HMO). The algorithm's positive predictive value for cases identified in the present study was 83% (147/177). To attempt to improve upon the positive predictive value, multiple modifications of the algorithm were performed. The previously defined best modification of the initial algorithm yielded a positive predictive value of 84% (147/174) in the present study with the loss of none of the true positive cases. These results demonstrate that logic-based algorithms can be used as a valid and efficient method of identifying large numbers of new breast cancer cases from claims data. This algorithm provides a powerful tool to perform health care analysis and research for women with newly diagnosed carcinoma of the breast.

Results of a radiology performance report for a health maintenance organization.

PURPOSE: To present results with a radiology performance report to help evaluate utilization of radiologic examinations by primary-care practices (family practice, internal medicine, or pediatrics) in an independent practice association health maintenance organization (HMO). MATERIALS AND METHODS: Utilization reports for primary-care-physician practices (n = 5,000) over a 12-month period (July 1, 1993 through June 30, 1994) were derived from administrative data collected from claim and encounter forms submitted by radiologic practices. Data were divided into 22 measures to help define practice utilization. five overall measures helped evaluate procedures performed by HMO member or nonmember practices per 1,000 members. Twelve specific measures helped evaluate patterns of use of frequently ordered imaging procedures (eg, computed tomography, magnetic resonance imaging, bone scanning, cardiovascular nuclear imaging, nonobstetric ultrasound, and plain radiography). Five quality measures helped evaluate utilization of screening mammography in women aged 50-64 years (as a percentage of all women in the HMO aged 50-64 years) and of low-yield examinations (ie, sinus, rib, and skull radiography per 1,000 adult members). RESULTS: Individual practice utilisation mean results were compared with overall HMO mean results adjusted for practice type and age and sex of members. CONCLUSION: Utilization data are an integral part of evaluation of HMOs and their providers, and these results helped establish a baseline level of performance.

Measuring the quality of inpatient health care.

A validated case mix and severity adjusted performance measurement system and methodology are presented. Using this methodology in a user-friendly interactive interface, those who are interested in the performance of a hospital or providers within a hospital can easily identify areas for quality improvement.

Bridging the gap between managed care and academic medicine: an innovative fellowship.

Numerous challenges face academic medicine in the era of managed care. This environment is stimulating the development of innovative educational programs that can adapt to changes in the healthcare system. The U.S. Quality Algorithms Managed Care Fellowship at Jefferson Medical College is one response to these challenges. Two postresidency physicians are chosen as fellows each year. The 1-year curriculum is organized into four 3-month modules covering such subjects as biostatistics and epidemiology, medical informatics, the theory and practice of managed care, managed care finance, integrated healthcare systems, quality assessment and improvement, clinical parameters and guidelines, utilization management, and risk management. The fellowship may serve as a possible prototype for future post-graduate education.

Medicare managed care and the need for quality measurement.

With the increasing penetration of managed care as health insurance coverage for Medicare beneficiaries, accountability for quality of care is being demanded. While HEDIS 2.5 has become the standard for assessing the performance of health plans in caring for their commercial members, no such standard exists for Medicare enrollees. U.S. Quality Algorithms, the performance measurement subsidiary of U.S. Healthcare, has developed the Medicare Quality Report Card as a tool for performance assessment and quality improvement. This article describes how the measures of quality important to the Medicare population were chosen, how the measures were calculated, and how they have been used in programs designed to improve the quality of care for U.S. Healthcare Medicare members.

Patient misunderstanding of dosing instructions.

OBJECTIVE: To compare outpatients' understanding of medication dosing instructions written in terms of daily frequency with patients' understanding of instructions specifying hourly intervals. DESIGN: Prospective cohort study involving patient interviews. SETTING: A university hospital outpatient pharmacy. PATIENTS: Five hundred patients presenting new and refill prescriptions to the hospital outpatient pharmacy. INTERVENTION: Patients were interviewed using a standardised questionnaire. MEASUREMENTS AND MAIN RESULTS: Of the 71 patients with prescriptions specifying dosing instructions in hourly intervals (e.g., q6h), 55 (77%) misinterpreted the recommended frequency of dosage compared with only 4 (0.99%) of the 429 patients with dosing instructions specifying daily frequency (e.g., qid) (relative risk 83; 95% confidence interval 31-200). This difference remained when patient subgroups were evaluated by education level, new versus refill prescriptions, and analgesic versus nonanalgesic medications. CONCLUSIONS: This study indicates that the intended dosing regimen is frequently misunderstood when the physician writes outpatient prescriptions in hourly intervals. To promote optimal patient compliance, the outpatient prescription label should state the number of times a day a medication is to be taken.

Managed care, accountability, and the physician.

The 1990s is truly the era of increased accountability in the practice of medicine. Through the methods of cost and quality measurement and the introduction of a manager (i.e., the MCO), society as a whole will benefit from a medical delivery system that focuses on linking the outcomes of care delivered to the processes of the care provided. Report cards serve an important tool by which information about quality and costs can be quantified and shared with the purchasers and users of the medical delivery system. Purchasers and patients are asking for greater accountability from payers and providers. The increased accountability of physicians to health plans, IDSs, hospitals, and patients with whom they interact has major implications on the definition of success in the managed medical delivery system of today. The theme of accountability has been described by the examples of the HEDIS Quality Report Card for health plans and Quality Report Cards for hospitals, PCPs, and specialists. Physicians must provide high-quality care to each patient they see but must also develop the mindset and structures to manage an entire population of patients. The expectations of each of the entities with whom they interact must be understood, and physicians need to develop the skills and infrastructure to put total quality management and information technology to work to help them facilitate the delivery of high-quality care in a cost-effective manner. Everyone involved in the health care system--from purchasers to payers to consumers--shares the same goals as physicians: provide the highest-quality care and achieve the best possible outcomes in the most cost-effective manner.

U.S. Healthcare's quality-based compensation model.

U.S. Healthcare has developed a quality-based compensation model through which its primary care physicians, hospitals, and specialists can earn additional compensation based on the quality and cost-effectiveness of the care they provide to their patients. The model clearly delineates the expectations of U.S. Healthcare, and in contrast with traditional payment models, encourages improvement in performance. In addition, the model aligns the incentives of U.S. Healthcare purchasers, participating providers, and members in order to provide high-quality, cost-effective care that maximizes patient outcomes.