{"title":"Addiction:entries and exits. Edited by Jon Elster. New York: Sage, 1999","authors":"Rosalie Liccardo Pacula","doi":"10.1002/mhp.92","DOIUrl":"https://doi.org/10.1002/mhp.92","url":null,"abstract":"","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"3 3","pages":"165-166"},"PeriodicalIF":1.6,"publicationDate":"2001-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/mhp.92","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72169220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Adam Smith Award","authors":"","doi":"10.1002/mhp.99","DOIUrl":"https://doi.org/10.1002/mhp.99","url":null,"abstract":"","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"3 3","pages":"167"},"PeriodicalIF":1.6,"publicationDate":"2001-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/mhp.99","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72169219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p><b>Background:</b> The homeless population is among the poorest of the poor in the United States. Employment and government programs are potential sources of income, but many homeless people face potential barriers to work: many have serious mental and physical disabilities, and many more have alcohol and drug disorders. As a result, most homeless who work do so either for a few hours per day or only some days, which provides little income. General Assistance, a public program of last resort, also provides a low level of income support. More income might be gained through higher levels of work or participation in income support programs for people with disabilities.</p><p><b>Aims of the Study:</b> To investigate the characteristics of homeless people that impede them in the labor market and in government program participation, paying particular attention to their mental and physical health, as well as their alcohol and drug problems.</p><p><b>Data:</b> Data are from a survey of the homeless population in Alameda County, California, conducted from 1991 to 1993. Our sample is 471 homeless adults randomly selected from area shelters and meal providers, who were reinterviewed approximately 6 months later, regardless of domiciliary status. Mental health and substance use problems were assessed using the Diagnostic Interview Schedule, a structured, psychiatric interview that uses criteria based on the American Psychiatric Association's <i>Diagnostic and Statistical Manual of Mental Disorders</i> 3rd edn (revised). Employment between the first and second interview is categorized as none, low level (less than 6 hours a day or fewer than half the days between interviews) or higher level (at least 6 hours a day for at least half the days).</p><p><b>Analytical Procedures:</b> The models of employment status and program participation are recursive in that homelessness at the first wave of the survey is treated as given. Thus we explore whether, given their initial homelessness, persons can gain or maintain access to income between the two interviews, conditional on the sample member's homelessness, health and disability at the first interview. Using maximum-likelihood methods, we estimate a generalized ordered logit model of whether the person works not at all, at a low level or at a higher level. Participation in disability programs and GA are estimated as probit models over the subsamples of potentially eligible participants.</p><p><b>Results:</b> While a surprisingly large number of homeless people work, few homeless persons are able to generate significant earnings from employment alone. Physical health problems that limit work or daily activities, in particular, are barriers to employment. Drug and alcohol abuse and dependence are positively associated with lower work level but are negatively related to higher work level. Program participation is quite low relative to eligibility. Those with physical health problems are substantially more likely than
{"title":"Income and employment among homeless people: the role of mental health, health and substance abuse","authors":"Samuel H. Zuvekas, Steven C. Hill","doi":"10.1002/mhp.94","DOIUrl":"https://doi.org/10.1002/mhp.94","url":null,"abstract":"<p><b>Background:</b> The homeless population is among the poorest of the poor in the United States. Employment and government programs are potential sources of income, but many homeless people face potential barriers to work: many have serious mental and physical disabilities, and many more have alcohol and drug disorders. As a result, most homeless who work do so either for a few hours per day or only some days, which provides little income. General Assistance, a public program of last resort, also provides a low level of income support. More income might be gained through higher levels of work or participation in income support programs for people with disabilities.</p><p><b>Aims of the Study:</b> To investigate the characteristics of homeless people that impede them in the labor market and in government program participation, paying particular attention to their mental and physical health, as well as their alcohol and drug problems.</p><p><b>Data:</b> Data are from a survey of the homeless population in Alameda County, California, conducted from 1991 to 1993. Our sample is 471 homeless adults randomly selected from area shelters and meal providers, who were reinterviewed approximately 6 months later, regardless of domiciliary status. Mental health and substance use problems were assessed using the Diagnostic Interview Schedule, a structured, psychiatric interview that uses criteria based on the American Psychiatric Association's <i>Diagnostic and Statistical Manual of Mental Disorders</i> 3rd edn (revised). Employment between the first and second interview is categorized as none, low level (less than 6 hours a day or fewer than half the days between interviews) or higher level (at least 6 hours a day for at least half the days).</p><p><b>Analytical Procedures:</b> The models of employment status and program participation are recursive in that homelessness at the first wave of the survey is treated as given. Thus we explore whether, given their initial homelessness, persons can gain or maintain access to income between the two interviews, conditional on the sample member's homelessness, health and disability at the first interview. Using maximum-likelihood methods, we estimate a generalized ordered logit model of whether the person works not at all, at a low level or at a higher level. Participation in disability programs and GA are estimated as probit models over the subsamples of potentially eligible participants.</p><p><b>Results:</b> While a surprisingly large number of homeless people work, few homeless persons are able to generate significant earnings from employment alone. Physical health problems that limit work or daily activities, in particular, are barriers to employment. Drug and alcohol abuse and dependence are positively associated with lower work level but are negatively related to higher work level. Program participation is quite low relative to eligibility. Those with physical health problems are substantially more likely than","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"3 3","pages":"153-163"},"PeriodicalIF":1.6,"publicationDate":"2001-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/mhp.94","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72169223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p><b>Background:</b> Few studies have systematically compared the relationship between lost work productivity (work impairment) and mental disorders using population surveys.</p><p><b>Aims:</b> (1) To identify the importance of individual mental disorders and disorder co-occurrences (comorbidity) as predictors of two measures of work impairment over the past month—work loss (number of days unable to perform usual activities) and work cutback (number of days where usual activities were restricted); (2) to examine whether different types of disorder have a greater impact on work impairment in some occupations than others; (3) to determine whether work impairment in those with a disorder is related to treatment seeking.</p><p><b>Method:</b> Data were based on full-time workers identified by the Australian National Survey of Mental Health and Well-Being, a household survey of mental disorders modeled on the US National Comorbidity Survey. Diagnoses were of one-month DSM-IV affective, anxiety and substance-related disorders. Screening instruments generated likely cases of ICD-10 personality disorders. The association of disorder types and their co-occurrences with work impairment was examined using multivariate linear regression. Odds ratios determined the significance of mental disorder prevalence across occupations, and planned contrasts were used to test for differences in work impairment across occupations within disorder types. The relationship between work impairment and treatment seeking was determined for each broad diagnostic group with <i>t</i>-tests.</p><p><b>Results:</b> Depression, generalized anxiety disorder and personality disorders were predictive of work impairment after controlling for impairment due to physical disorders. Among pure and comorbid disorders, affective and comorbid anxiety–affective disorders respectively were associated with the greatest amount of work impairment. For all disorders, stronger associations were obtained for work cutback than for work loss. No relationship was found between type of occupation and the impact of different types of disorder on work impairment. Only 15% of people with any mental disorder had sought help in the past month. For any mental disorder, significantly greater work loss and work cutback was associated with treatment seeking, but comparisons within specific disorder types were not significant.</p><p><b>Discussion:</b> A substantial amount of lost productivity due to mental disorders comes from within the full-time working population. The greater impact of mental disorders on work cutback compared to work loss suggests that work cutback provides a more sensitive measure of work impairment in those with mental disorders. Work impairment was based on self-report only. While there is evidence for the reliability of self-assessed work loss days, no reliability or validity studies have been conducted for work cutback days. The low rates of treatment seeking are a major health issue for th
{"title":"Lost productivity among full-time workers with mental disorders","authors":"Debbie Lim, Kristy Sanderson, Gavin Andrews","doi":"10.1002/mhp.93","DOIUrl":"https://doi.org/10.1002/mhp.93","url":null,"abstract":"<p><b>Background:</b> Few studies have systematically compared the relationship between lost work productivity (work impairment) and mental disorders using population surveys.</p><p><b>Aims:</b> (1) To identify the importance of individual mental disorders and disorder co-occurrences (comorbidity) as predictors of two measures of work impairment over the past month—work loss (number of days unable to perform usual activities) and work cutback (number of days where usual activities were restricted); (2) to examine whether different types of disorder have a greater impact on work impairment in some occupations than others; (3) to determine whether work impairment in those with a disorder is related to treatment seeking.</p><p><b>Method:</b> Data were based on full-time workers identified by the Australian National Survey of Mental Health and Well-Being, a household survey of mental disorders modeled on the US National Comorbidity Survey. Diagnoses were of one-month DSM-IV affective, anxiety and substance-related disorders. Screening instruments generated likely cases of ICD-10 personality disorders. The association of disorder types and their co-occurrences with work impairment was examined using multivariate linear regression. Odds ratios determined the significance of mental disorder prevalence across occupations, and planned contrasts were used to test for differences in work impairment across occupations within disorder types. The relationship between work impairment and treatment seeking was determined for each broad diagnostic group with <i>t</i>-tests.</p><p><b>Results:</b> Depression, generalized anxiety disorder and personality disorders were predictive of work impairment after controlling for impairment due to physical disorders. Among pure and comorbid disorders, affective and comorbid anxiety–affective disorders respectively were associated with the greatest amount of work impairment. For all disorders, stronger associations were obtained for work cutback than for work loss. No relationship was found between type of occupation and the impact of different types of disorder on work impairment. Only 15% of people with any mental disorder had sought help in the past month. For any mental disorder, significantly greater work loss and work cutback was associated with treatment seeking, but comparisons within specific disorder types were not significant.</p><p><b>Discussion:</b> A substantial amount of lost productivity due to mental disorders comes from within the full-time working population. The greater impact of mental disorders on work cutback compared to work loss suggests that work cutback provides a more sensitive measure of work impairment in those with mental disorders. Work impairment was based on self-report only. While there is evidence for the reliability of self-assessed work loss days, no reliability or validity studies have been conducted for work cutback days. The low rates of treatment seeking are a major health issue for th","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"3 3","pages":"139-146"},"PeriodicalIF":1.6,"publicationDate":"2001-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/mhp.93","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72169216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BACKGROUND: The 1990's witnessed a new wave of state and federal legislation affecting mental health insurance in the United States. Although patient advocacy groups have hailed the passage of numerous "parity" laws that require insurance coverage for mental illnesses to equal that for physical ailments, it is unclear whether this activity represents a major improvement in insurance benefits among mentally ill or significantly increases their access to care. AIMS: This paper contrasts how insurance coverage has changed among individuals with mental health problems in states with and without parity legislation. METHODS: National survey data from 1996 to 1998, subset to a panel of 1220 individuals exceeding clinical screeners for a mental health disorder. Dependent variables are change in insurance status, insurance generosity and perception of access to care. The analysis contrasts changes in dependent variables between states with and without parity legislation (a difference-in-differences analysis). RESULTS: There are no statistical significant effects of state parity; point estimates suggest that parity mandates are associated with a slightly higher number of mentally ill reporting improved insurance generosity and access to care, but also with a higher number of mentally ill losing all insurance coverage in parity states. The estimated effects are too small to be statistically significant, although the sample size is limited and the study had only good statistical power to detect large effects. DISCUSSION: At the population level, state parity legislation appears to have not had large effects on the insurance coverage of the group that was intended as the primary beneficiary of legislation. Likely reasons include the limited scope of the actual legal requirements and large numbers of mentally ill that are not covered by health insurance subject to such legislation. The results do not exclude the possibility that some subgroups experienced substantial improvements in their insurance coverage. At the population level, large effects experienced by small subgroup are diluted by groups that experienced no similar changes. However, parity legislation was not considered a minor issue by advocates and opponents and this analysis has the statistical power to detect the sizeable differences that were argued in the policy debate. IMPLICATIONS FOR HEALTH POLICIES: While state parity legislation may have improved insurance benefits for some, it appears not to have resulted in substantial improvements for the mentally ill as a whole. The results could be very different, however, if strong federal legislation were passed that has a broader scope than state legislation. IMPLICATIONS FOR RESEARCH: The parity debate provides an important reminder of how little research is available to inform policy. This study provides a crude picture, but it is far from being a conclusive evaluation. The most urgent need is for data that continue to track changes in markets an
{"title":"State parity legislation and changes in health insurance and perceived access to care among individuals with mental illness: 1996–1998","authors":"R. Sturm","doi":"10.1002/MHP.97","DOIUrl":"https://doi.org/10.1002/MHP.97","url":null,"abstract":"BACKGROUND: The 1990's witnessed a new wave of state and federal legislation affecting mental health insurance in the United States. Although patient advocacy groups have hailed the passage of numerous \"parity\" laws that require insurance coverage for mental illnesses to equal that for physical ailments, it is unclear whether this activity represents a major improvement in insurance benefits among mentally ill or significantly increases their access to care. AIMS: This paper contrasts how insurance coverage has changed among individuals with mental health problems in states with and without parity legislation. METHODS: National survey data from 1996 to 1998, subset to a panel of 1220 individuals exceeding clinical screeners for a mental health disorder. Dependent variables are change in insurance status, insurance generosity and perception of access to care. The analysis contrasts changes in dependent variables between states with and without parity legislation (a difference-in-differences analysis). RESULTS: There are no statistical significant effects of state parity; point estimates suggest that parity mandates are associated with a slightly higher number of mentally ill reporting improved insurance generosity and access to care, but also with a higher number of mentally ill losing all insurance coverage in parity states. The estimated effects are too small to be statistically significant, although the sample size is limited and the study had only good statistical power to detect large effects. DISCUSSION: At the population level, state parity legislation appears to have not had large effects on the insurance coverage of the group that was intended as the primary beneficiary of legislation. Likely reasons include the limited scope of the actual legal requirements and large numbers of mentally ill that are not covered by health insurance subject to such legislation. The results do not exclude the possibility that some subgroups experienced substantial improvements in their insurance coverage. At the population level, large effects experienced by small subgroup are diluted by groups that experienced no similar changes. However, parity legislation was not considered a minor issue by advocates and opponents and this analysis has the statistical power to detect the sizeable differences that were argued in the policy debate. IMPLICATIONS FOR HEALTH POLICIES: While state parity legislation may have improved insurance benefits for some, it appears not to have resulted in substantial improvements for the mentally ill as a whole. The results could be very different, however, if strong federal legislation were passed that has a broader scope than state legislation. IMPLICATIONS FOR RESEARCH: The parity debate provides an important reminder of how little research is available to inform policy. This study provides a crude picture, but it is far from being a conclusive evaluation. The most urgent need is for data that continue to track changes in markets an","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"1 1","pages":"209-213"},"PeriodicalIF":1.6,"publicationDate":"2000-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80401395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<div> <section> <h3> <b>Organization of care</b>:</h3> <p> Health care is provided to patients with mental disorders by the state health care facilities as well as by social help agencies. Mental health care services are provided mostly by mental health facilities and partly by primary care units. Outpatient clinics, separate for psychiatric patients and substance abusers, are the most numerous mental health care units, amounting to a total of 1120. Intermediate care facilities include 110 day hospitals, 23 community mobile teams and ten hostels. The number of hospital beds amounts to 31913, i.e. 8.3 beds per 10000 population. 80% of beds are located in mental hospitals.</p> </section> <section> <h3> <b>Trends of development</b>:</h3> <p> The trends in mental health care development are outlined in the Mental Health Programme and accompanying documents accepted by the Minister of Health and Social Welfare. The programme defines specific goals to be achieved by the year 2005 in the primary, secondary and tertiary prevention of mental disorders. In the domain of mental health care accessibility the most important goals are the following: a significant reduction in the number of beds in large mental hospitals, a marked (nearly threefold) rise in the number of beds in psychiatric wards at general hospitals and a significant increase in the number of community-based forms of care (e.g. a fourfold rise in the number of day hospitals).</p> </section> <section> <h3> <b>Financing of care</b>:</h3> <p> Before 1999, the health care system was financed from the state budget and the health care spendings were subject to a political auction each year. Allocation of funds among hospitals and health care centres was based on the total previous year budgetary spendings of particular facilities and did not take into account a detailed cost analysis. Such a financing approach, although giving a feeling of a relative financial safety, did not encourage health care facilities to introduce an organizational flexibility and to expand the scope of their services. In psychiatry, it manifested itself in a very slow development of some community psychiatry forms (mostly day hospitals, mobile community teams and hostels). The Health Care Institutions Act has created a legal framework for the financial management of health care units in their new, independent form. Conditions for health care financing through regional sickness funds were thus created. The financing is currently based on contracts made by sickness funds with health care facilities for specific health services. Both the quantity and price of services should be mutually negotiated.</p> <p>Some simplified measures of services offered were us
{"title":"Organization and financing of mental health care in Poland","authors":"Wanda Langiewicz, Elzbieta Slupczynska-Kossobudzka","doi":"10.1002/1099-176X(200006)3:2<77::AID-MHP79>3.0.CO;2-S","DOIUrl":"https://doi.org/10.1002/1099-176X(200006)3:2<77::AID-MHP79>3.0.CO;2-S","url":null,"abstract":"<div>\u0000 \u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Organization of care</b>:</h3>\u0000 \u0000 <p> Health care is provided to patients with mental disorders by the state health care facilities as well as by social help agencies. Mental health care services are provided mostly by mental health facilities and partly by primary care units. Outpatient clinics, separate for psychiatric patients and substance abusers, are the most numerous mental health care units, amounting to a total of 1120. Intermediate care facilities include 110 day hospitals, 23 community mobile teams and ten hostels. The number of hospital beds amounts to 31913, i.e. 8.3 beds per 10000 population. 80% of beds are located in mental hospitals.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Trends of development</b>:</h3>\u0000 \u0000 <p> The trends in mental health care development are outlined in the Mental Health Programme and accompanying documents accepted by the Minister of Health and Social Welfare. The programme defines specific goals to be achieved by the year 2005 in the primary, secondary and tertiary prevention of mental disorders. In the domain of mental health care accessibility the most important goals are the following: a significant reduction in the number of beds in large mental hospitals, a marked (nearly threefold) rise in the number of beds in psychiatric wards at general hospitals and a significant increase in the number of community-based forms of care (e.g. a fourfold rise in the number of day hospitals).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Financing of care</b>:</h3>\u0000 \u0000 <p> Before 1999, the health care system was financed from the state budget and the health care spendings were subject to a political auction each year. Allocation of funds among hospitals and health care centres was based on the total previous year budgetary spendings of particular facilities and did not take into account a detailed cost analysis. Such a financing approach, although giving a feeling of a relative financial safety, did not encourage health care facilities to introduce an organizational flexibility and to expand the scope of their services. In psychiatry, it manifested itself in a very slow development of some community psychiatry forms (mostly day hospitals, mobile community teams and hostels). The Health Care Institutions Act has created a legal framework for the financial management of health care units in their new, independent form. Conditions for health care financing through regional sickness funds were thus created. The financing is currently based on contracts made by sickness funds with health care facilities for specific health services. Both the quantity and price of services should be mutually negotiated.</p>\u0000 \u0000 <p>Some simplified measures of services offered were us","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"3 2","pages":"77-81"},"PeriodicalIF":1.6,"publicationDate":"2000-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/1099-176X(200006)3:2<77::AID-MHP79>3.0.CO;2-S","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72162502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-11-23DOI: 10.1002/1099-176X(200006)3:2<83::AID-MHP81>3.0.CO;2-F
David S. Salkever, Judith A. Shinogle
<div> <section> <h3> <b>Background and Aims of Study</b>:</h3> <p> The use of specialized behavioral health companies to manage mental/health benefits has become widespread in recent years. Recent studies have reported on the cost and utilization impacts of behavioral health carve-outs. Yet little previous research has examined the factors which lead employer-based health plans to adopt a carve-out strategy for mental health benefits. The examination of these factors is the main focus of our study. Our empirical analysis is also intended to explore several hypotheses (moral hazard, adverse selection, economies of scale and alternate utilization management strategies) that have recently been advanced to explain the popularity of carve-outs.</p> </section> <section> <h3> <b>Methods</b>:</h3> <p> The data for this study are from a survey of employers who have long-term disability contracts with one large insurer. The analysis uses data from 248 employers who offer mental health benefits combined with local market information (e.g. health care price proxies, state tax rates etc), state regulations (mental health and substance abuse mandate and parity laws) and employee characteristics. Two different measures of carve-out use were used as dependent variables in the analysis: (1) the fraction of health plans offered by the employer that contained carve-out provisions and (2) a dichotomous indicator for those employers who included a carve-out arrangement in all the health plans they offered.</p> </section> <section> <h3> <b>Results</b>:</h3> <p> Our results tended to support the general cost-control hypothesis that factors associated with higher use and/or costs of mental health services increase the demand for carve-outs. Our results gave less consistent support to the argument that carve-outs are demanded to control adverse selection, though only a few variables provided a direct test of this hypothesis. The role of economies of scale (i.e., group size) and the effectiveness of alternative strategies for managing moral hazard costs (i.e., HMOs) were confirmed by our results.</p> </section> <section> <h3> <b>Discussion</b>:</h3> <p> We considered a number of different hypotheses concerning employers' demands for mental health carve-outs and found varying degrees of support for these hypotheses in our data. Our results tended to support the general cost-control hypothesis that factors associated with higher use and/or costs of mental health services increase the demand for carve-outs.</p> </section> <section> <h3> <b>Limitations</b>:</h3> <p> Our
{"title":"Empirical evidence on the demand for carve-outs in employment group mental health coverage","authors":"David S. Salkever, Judith A. Shinogle","doi":"10.1002/1099-176X(200006)3:2<83::AID-MHP81>3.0.CO;2-F","DOIUrl":"https://doi.org/10.1002/1099-176X(200006)3:2<83::AID-MHP81>3.0.CO;2-F","url":null,"abstract":"<div>\u0000 \u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Background and Aims of Study</b>:</h3>\u0000 \u0000 <p> The use of specialized behavioral health companies to manage mental/health benefits has become widespread in recent years. Recent studies have reported on the cost and utilization impacts of behavioral health carve-outs. Yet little previous research has examined the factors which lead employer-based health plans to adopt a carve-out strategy for mental health benefits. The examination of these factors is the main focus of our study. Our empirical analysis is also intended to explore several hypotheses (moral hazard, adverse selection, economies of scale and alternate utilization management strategies) that have recently been advanced to explain the popularity of carve-outs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Methods</b>:</h3>\u0000 \u0000 <p> The data for this study are from a survey of employers who have long-term disability contracts with one large insurer. The analysis uses data from 248 employers who offer mental health benefits combined with local market information (e.g. health care price proxies, state tax rates etc), state regulations (mental health and substance abuse mandate and parity laws) and employee characteristics. Two different measures of carve-out use were used as dependent variables in the analysis: (1) the fraction of health plans offered by the employer that contained carve-out provisions and (2) a dichotomous indicator for those employers who included a carve-out arrangement in all the health plans they offered.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Results</b>:</h3>\u0000 \u0000 <p> Our results tended to support the general cost-control hypothesis that factors associated with higher use and/or costs of mental health services increase the demand for carve-outs. Our results gave less consistent support to the argument that carve-outs are demanded to control adverse selection, though only a few variables provided a direct test of this hypothesis. The role of economies of scale (i.e., group size) and the effectiveness of alternative strategies for managing moral hazard costs (i.e., HMOs) were confirmed by our results.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Discussion</b>:</h3>\u0000 \u0000 <p> We considered a number of different hypotheses concerning employers' demands for mental health carve-outs and found varying degrees of support for these hypotheses in our data. Our results tended to support the general cost-control hypothesis that factors associated with higher use and/or costs of mental health services increase the demand for carve-outs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Limitations</b>:</h3>\u0000 \u0000 <p> Our ","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"3 2","pages":"83-95"},"PeriodicalIF":1.6,"publicationDate":"2000-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/1099-176X(200006)3:2<83::AID-MHP81>3.0.CO;2-F","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72127422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-11-23DOI: 10.1002/1099-176X(200006)3:2<111::AID-MHP80>3.0.CO;2-X
Susan M. Essock
Goldman describes how service systems research examines the impact of economic and organizational strategies designed to promote particular service combinations (such as continuity of care) and inhibit others (such as preferentially serving only those individuals who are the easiest to treat). The recurring theme from the large services research initiatives is that the content of care, as well as the organization and financing of care, matters. This theme is distinct from what these large services research projects were designed to assess, which speaks both to the unexpected benefits from these massive studies and the need for more efficient tools to examine the interrelationships among the organization, financing and content of care.
{"title":"Big studies, simple lessons","authors":"Susan M. Essock","doi":"10.1002/1099-176X(200006)3:2<111::AID-MHP80>3.0.CO;2-X","DOIUrl":"https://doi.org/10.1002/1099-176X(200006)3:2<111::AID-MHP80>3.0.CO;2-X","url":null,"abstract":"<p>Goldman describes how service systems research examines the impact of economic and organizational strategies designed to promote particular service combinations (such as continuity of care) and inhibit others (such as preferentially serving only those individuals who are the easiest to treat). The recurring theme from the large services research initiatives is that the content of care, as well as the organization and financing of care, matters. This theme is distinct from what these large services research projects were designed to assess, which speaks both to the unexpected benefits from these massive studies and the need for more efficient tools to examine the interrelationships among the organization, financing and content of care.</p>","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"3 2","pages":"111-112"},"PeriodicalIF":1.6,"publicationDate":"2000-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/1099-176X(200006)3:2<111::AID-MHP80>3.0.CO;2-X","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72162498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-11-23DOI: 10.1002/1099-176X(200006)3:2<61::AID-MHP74>3.0.CO;2-F
Rani A. Desai, Robert A. Rosenheck
<div> <section> <h3> <b>Background:</b></h3> <p> There are relatively few published data on how the financial structures of different health systems affect each other. With increasing financial restrictions in both public and private healthcare systems, it is important to understand how changes in one system (e.g. VA mental healthcare) affect utilization of other systems (e.g. state hospitals).</p> </section> <section> <h3> <b>Aims of Study:</b></h3> <p> This study utilizes data from state hospitals in eight states to examine the relationship of VA <i>per capita</i> mental health funding and state <i>per capita</i> mental health expenditures to veterans' use of state hospitals, adjusting for other determinants of utilization.</p> </section> <section> <h3> <b>Methods:</b></h3> <p> This study utilized a large database that included records from all male inpatient admissions to state hospitals between 1984 and 1989 in eight states (<i>n</i> = 152541). Funding levels for state hospitals and VA mental health systems were examined as alternative enabling factors for veterans' use of state hospital care. Logistic regression models were adjusted for other determinants of utilization such as socio-economic status, diagnosis, travel distances to VA and non-VA facilities and the proportion of veterans in the population.</p> </section> <section> <h3> <b>Results:</b></h3> <p> The single strongest predictor of whether a state hospital patient would be a veteran was the level of VA mental healthcare funding (OR = 0.81 per $10 of funding per veteran in the population, <i>p</i> = 0.0001), with higher VA funding associated with less use of state hospitals by veterans. Higher <i>per capita</i> state funding, reciprocally, increased veterans' use of state hospitals. We also calculated elasticities for state hospital use with respect to VA mental healthcare funding and with respect to state hospital <i>per capita</i> funding. A 50% increase in VA <i>per capita</i> mental health spending was associated with a 30% decrease in veterans' use of state hospitals (elasticity of −0.6). Conversely, a 50% increase in state hospital <i>per capita</i> funding was associated with only an 11% increase in veterans' use of state hospitals (elasticity of 0.06).</p> </section> <section> <h3> <b>Implications for Health Care Provision and Use:</b></h3> <p>These data indicate that <i>per capita</i> funding for state hospitals and VA mental health systems exerts a significant influence on service use, apparently mediated by the effect on supply of mental health services. Veterans are
{"title":"The interdependence of mental health service systems: the effects of VA mental health funding on veterans' use of state mental health inpatient facilities","authors":"Rani A. Desai, Robert A. Rosenheck","doi":"10.1002/1099-176X(200006)3:2<61::AID-MHP74>3.0.CO;2-F","DOIUrl":"https://doi.org/10.1002/1099-176X(200006)3:2<61::AID-MHP74>3.0.CO;2-F","url":null,"abstract":"<div>\u0000 \u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Background:</b></h3>\u0000 \u0000 <p> There are relatively few published data on how the financial structures of different health systems affect each other. With increasing financial restrictions in both public and private healthcare systems, it is important to understand how changes in one system (e.g. VA mental healthcare) affect utilization of other systems (e.g. state hospitals).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Aims of Study:</b></h3>\u0000 \u0000 <p> This study utilizes data from state hospitals in eight states to examine the relationship of VA <i>per capita</i> mental health funding and state <i>per capita</i> mental health expenditures to veterans' use of state hospitals, adjusting for other determinants of utilization.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Methods:</b></h3>\u0000 \u0000 <p> This study utilized a large database that included records from all male inpatient admissions to state hospitals between 1984 and 1989 in eight states (<i>n</i> = 152541). Funding levels for state hospitals and VA mental health systems were examined as alternative enabling factors for veterans' use of state hospital care. Logistic regression models were adjusted for other determinants of utilization such as socio-economic status, diagnosis, travel distances to VA and non-VA facilities and the proportion of veterans in the population.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Results:</b></h3>\u0000 \u0000 <p> The single strongest predictor of whether a state hospital patient would be a veteran was the level of VA mental healthcare funding (OR = 0.81 per $10 of funding per veteran in the population, <i>p</i> = 0.0001), with higher VA funding associated with less use of state hospitals by veterans. Higher <i>per capita</i> state funding, reciprocally, increased veterans' use of state hospitals. We also calculated elasticities for state hospital use with respect to VA mental healthcare funding and with respect to state hospital <i>per capita</i> funding. A 50% increase in VA <i>per capita</i> mental health spending was associated with a 30% decrease in veterans' use of state hospitals (elasticity of −0.6). Conversely, a 50% increase in state hospital <i>per capita</i> funding was associated with only an 11% increase in veterans' use of state hospitals (elasticity of 0.06).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> <b>Implications for Health Care Provision and Use:</b></h3>\u0000 \u0000 <p>These data indicate that <i>per capita</i> funding for state hospitals and VA mental health systems exerts a significant influence on service use, apparently mediated by the effect on supply of mental health services. Veterans are","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"3 2","pages":"61-67"},"PeriodicalIF":1.6,"publicationDate":"2000-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/1099-176X(200006)3:2<61::AID-MHP74>3.0.CO;2-F","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72127423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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