From research to practice: factors affecting implementation of prospective targeted injury-detection systems.

AIM This paper describes key factors that shaped implementation of prospective targeted injury-detection systems (TIDS) for adverse drug events (ADEs) and nosocomial pressure ulcers (PrU). METHODS Using case-study methodology, the authors conducted semistructured interviews with implementation champions and TIDS users at five hospitals. Interviews focused on implementation experiences, assessment of TIDS' effectiveness and utility, and plans for sustainability. The authors used content analysis techniques to compare implementation experiences within and across organisations and triangulated data for explanation and confirmation of common themes. FINDINGS Participating hospitals were more successful in implementing the low-complexity PrU-TIDS, as compared with high-complexity ADE-TIDS. This pattern reflected the greater complexity of ADE-TIDS, its higher costs and poorer alignment with existing workflows. Complexity affected the innovations' perceived usability, the time needed to learn and install the trigger systems, and their costs. Local factors affecting implementation and sustainability of both innovations included turnover affecting champions and other staff, shifting organisational priorities, changing information infrastructures, and institutional constraints on adapting existing IT to the electronic TIDS. CONCLUSIONS To facilitate implementation of complex healthcare innovations such as ADE-TIDS, staff in adopting organisations should give high priority to innovation implementation; allocate sufficient resources; effectively communicate with and involve local champions and users; and align innovations with workflows and information systems. In addition, they should monitor local factors, such as changes in organisational priorities and IT, availability of implementation staff and champions, and external regulations and constraints that may pose barriers to innovation implementation and sustainability.

Physicians practicing in methadone treatment programs: who are they and what do they do?

OBJECTIVE: This study examines the characteristics and roles of physicians practicing in methadone maintenance treatment programs (MTPs). METHODS: Physicians and clinic directors at 172 MTPs in the United States completed surveys. MTPs were selected for study participation based on their locations (large urban, urban, or nonurban area) ownership status (for profit and non-profit), and size (patient capacity of 1-100, 101-300, and 300+). Weighted data were analyzed with descriptive and multivariate methods. RESULTS. Physicians were primarily white males aged 45 or older; 44% had 10 or more years of experience working in methadone treatment. Physicians reported spending 26% of their time completing administrative tasks. Most reported that they determine dosing levels on an individual patient basis. Average maintenance dose was 69 mg/day. CONCLUSIONS: Physicians' treatment practices play a major role in overall treatment, treatment retention, and outcomes. Physicians at for-profit and large urban MTPs reported spending the most time in direct patient contact.

Measuring the "managedness" and covered benefits of health plans.

STUDY AIMS: (1) To develop indexes measuring the degree of managedness and the covered benefits of health insurance plans, (2) to describe the variation in these indexes among plans in one health insurance market, (3) to assess the validity of the health plan indexes, and (4) to examine the association between patient characteristics and the health plan indexes. Measures of the "managedness" and covered benefits of health plans are requisite for studying the effects of managed care on clinical practice and health system performance, and they may improve people's understanding of our complex health care system. DATA SOURCES/STUDY SETTING: As part of our larger Physician Referral Study, we collected health insurance information for 189 insurance product lines and 755 products in the Seattle, Washington metropolitan area, which we linked with the study's data for 2,277 patients recruited in local primary care offices. STUDY DESIGN: Managed care and benefit variables were constructed through content analysis of health plan information. Principal component analysis of the variables produced a managedness index, an in-network benefits index, and an out-of-network benefits index. Bivariable analyses examined associations between patient characteristics and the three indexes. PRINCIPAL FINDINGS: From the managed care variables, we constructed three provider-oriented indexes for the financial, utilization management, and network domains of health plans. From these, we constructed a single managedness index, which correlated as expected with the individual measures, with the domain indexes, with plan type (FFS, PPO, POS, HMO), with independent assessments of local experts, and with patients' attitudes about their health insurance. For benefits, we constructed an in-network benefits index and an out-of-network benefits index, which were correlated with the managedness index. The personal characteristics of study patients were associated with the managed care and benefit indexes. Study patients in more managed plans reported somewhat better health than patients in less managed plans. CONCLUSIONS: Indexes of the managedness and benefits of health plans can be constructed from publicly available information. The managedness and benefit indexes are associated with the personal characteristics and health status of study patients. Potential uses of the managed care and benefits indexes are discussed.

Primary care physicians' participation in managed care networks.

The study described in this article explored the relationships between primary care physician characteristics and patterns of managed care affiliation in a single region. Secondary data sources were used to investigate the affiliations of all primary care physicians in King County, Washington (Seattle and environs) with 29 managed care products in 1996. Descriptive findings indicate that specialty, board certification, and experience all are associated with the managed care affiliations held by physicians. Differences between managed care product provider lists suggest that there are different strategies for the design and management of provider networks.