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.     

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.     

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.     

USQA Health Profile Database as a tool for health plan quality improvement

Managed care organizations are in a unique position to evaluate and improve the quality of care delivered to their defined memberships. Traditionally, health services delivery has been claims-focused. We describe a potentially richer, patient-centered approach, whereby patients with certain chronic diseases are first identified and then used as the unit of analysis. U.S. Quality Algorithms (USQA), a subsidiary of U.S. Healthcare (USHC) based in Blue Bell, Pennsylvania, has developed selection criteria for 36 different chronic diseases and a new database, the USQA Health Profile Database (HPD), to identify and archive patients with those diseases. Examples of how this approach and database can be used as a quality tool are demonstrated.     

The measurement of physician performance

There is growing interest in measuring the performance of physicians. At U.S. Healthcare (USHC), performance assessment is the responsibility of U.S. Quality Algorithms, one of its subsidiaries. This article discusses the development and application of certain measures employed to assess the performance of physicians and how compensation is linked to performance in USHC's quality-based compensation model.     

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.     

Physician intention to recommend complete diagnostic evaluation in colorectal cancer screening.

Primary care physicians (PCPs) often do not recommend complete diagnostic evaluation (CDE; i.e., diagnostic colonoscopy or the combination of flexible sigmoidoscopy and barium enema X-ray procedures) for patients with an abnormal screening fecal occult blood test (FOBT+) result. Information is needed to understand why PCPs do not recommend CDE. In the spring of 1994, a telephone survey was carried out using a random sample of 520 PCPs in Pennsylvania or New Jersey who had patients that were targeted for an FOBT screening program. Survey data were obtained from 363 (70%) PCPs on physician practice characteristics; personal background; perceptions concerning FOBT screening, CDE performance, and patient behavior; social influence related to CDE; and intention to recommend CDE for FOBT+ patients. Physician CDE intention scores were distributed as follows: low (22%), moderate (51%), and high (27%). Multivariate analyses demonstrate that physician board certification status, time in practice, belief in CDE efficacy, and belief that CDE is standard practice were positively associated with CDE intention, whereas concern about CDE-related costs was negatively associated with CDE intention. Among physicians in larger practices, perceived FOBT screening efficacy was negatively associated with CDE intention, and belief in the benefit of CDE was positively associated with outcome. There is substantial variability in CDE intention among PCPs. Physician perceptions about FOBT screening and follow-up are associated with CDE intention, are likely to influence CDE performance, and may be amenable to educational intervention. Additional research is needed to evaluate the impact of educational interventions on CDE intention and performance.