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1.
Am J Prev Med ; 21(3): 170-6, 2001 Oct.
Article in English | MEDLINE | ID: mdl-11567836

ABSTRACT

BACKGROUND: Implementation of screening guidelines for domestic violence has been challenging. The multifaceted "systems model" may provide an effective means to improve domestic violence screening, identification, and intervention in the healthcare setting. METHODS: We developed: (1) a systems model approach using tools for effective referral, evaluation, and reporting of domestic violence; (2) materials for distribution to female patients; (3) training for social service and mental health clinicians to provide domestic violence evaluation; and (4) strong links to the community. SETTING: A nonprofit, managed care facility in Richmond, California. PARTICIPANTS: Staff and members of the managed care plan. MAIN OUTCOME MEASURES: (1) Increased screening for domestic violence by clinicians; (2) increased awareness of the healthcare facility as a resource for domestic violence assistance; and (3) increased member satisfaction with the health plan's efforts to address domestic violence. RESULTS: The number of clinician referrals and patient self-referrals to an on-site domestic violence evaluator increased more than twofold. A pre-intervention and post-intervention phone survey of members seen for routine checkup showed an increase in member recall of being asked about domestic violence. After intervention, statistically significant increases were seen in members' perception that the health plan was concerned about the health effects of domestic violence (p<0.0001) and about members' satisfaction with the health plan's efforts to address this issue (p<0.0001). CONCLUSIONS: A systems model approach improved domestic violence services in a managed care health setting within 1 year and affected clinicians' behavior as well as health plan members' experience. This successful implementation makes it possible to address critical research questions about the impact of a healthcare intervention for victims of domestic violence in a managed healthcare setting.


Subject(s)
Domestic Violence/prevention & control , Managed Care Programs , Adolescent , Adult , Community-Institutional Relations , Data Collection/methods , Female , Humans , Middle Aged , Models, Organizational , Patient Satisfaction , Referral and Consultation/organization & administration , Spouse Abuse/prevention & control , Surveys and Questionnaires , Women's Health Services/organization & administration
2.
MD Comput ; 14(1): 24-30, 32-5, 1997.
Article in English | MEDLINE | ID: mdl-9000846

ABSTRACT

Inefficiency in the work of health care providers is evident and contributes to health care costs. In the early 20th century, industrial engineers developed scientific methods for studying work to improve performance (efficiency) by measuring results--i.e., quality, cost, and productivity. In the mid-20th century, business managers developed ways to apply these methods to improve the work process. These scientific methods and management approaches can be applied to improving medical work. Fee-for-service practice has had incentives to maximize productivity, and prepaid practice has had incentives to minimize costs, but no sector of the health care system has systematically pursued the optimization of all performance variables: quality, cost, and productivity. We have reviewed evolving methods for the automation of continual assessment of performance in health care using touch screen and computer telephone, logging and scheduling software, appropriate combinations of generic or disease-specific health status questionnaires, physiologic measurements or laboratory assays from computerized records, and cost and productivity data from computerized registration logs. We propose that the results of outcome assessment be rapidly and continually transmitted to providers, patients, and managers so that health care processes can be progressively improved. The evolving systems we have described are the practical tools that can help us achieve our performance goals.


Subject(s)
Quality Assurance, Health Care , Automation , Biomedical Engineering , Cost Control , Efficiency , Health Status , Humans , Quality Assurance, Health Care/economics , Quality Assurance, Health Care/statistics & numerical data , Surveys and Questionnaires , Therapeutics/standards
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