Pub Date : 1999-12-24DOI: 10.1002/(SICI)1099-176X(199909)2:3<141::AID-MHP56>3.0.CO;2-1
Roland Sturm
The most valuable research integrates from thre levels of investigation: clinical efficacy, ‘real life’ effectiveness (including cost-effectiveness) and policy research. Successful applications of systematic reviews have largely been limited to clinical efficacy questions. The contribution of systematic reviews/meta-analyses to effectiveness and economic questions in mental health has been very minor and their contribution to inform policy is negligible. The latter is unlikely to change due to the different type of information that policy makers need.
{"title":"What type of information is needed to inform mental health policy?","authors":"Roland Sturm","doi":"10.1002/(SICI)1099-176X(199909)2:3<141::AID-MHP56>3.0.CO;2-1","DOIUrl":"https://doi.org/10.1002/(SICI)1099-176X(199909)2:3<141::AID-MHP56>3.0.CO;2-1","url":null,"abstract":"<p>The most valuable research integrates from thre levels of investigation: clinical efficacy, ‘real life’ effectiveness (including cost-effectiveness) and policy research. Successful applications of systematic reviews have largely been limited to clinical efficacy questions. The contribution of systematic reviews/meta-analyses to effectiveness and economic questions in mental health has been very minor and their contribution to inform policy is negligible. The latter is unlikely to change due to the different type of information that policy makers need.</p>","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"2 3","pages":"141-144"},"PeriodicalIF":1.6,"publicationDate":"1999-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/(SICI)1099-176X(199909)2:3<141::AID-MHP56>3.0.CO;2-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72191527","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 : 1999-12-24DOI: 10.1002/(SICI)1099-176X(199909)2:3<137::AID-MHP57>3.0.CO;2-W
Dirk Sauerland
From an economic viewpoint, the amount of primary research conducted on a topic at any given point in time depends on grantmaker and researcher incentives. The potential addresses of research findings often set these incentives. Following this logic, there is an economic explanation provided for the availability of primary data in effcacy studies. This also explains the lack of data in other important fields of health care. This article evaluates why there are few studies on effectiveness and cost-effectiveness then discusses how research incentives might be changed to overcome this problem. As a result of cost containment efforts in some countries, this process has already been initialized.
{"title":"How to get the information needed to inform decision-makers—an economic perspective","authors":"Dirk Sauerland","doi":"10.1002/(SICI)1099-176X(199909)2:3<137::AID-MHP57>3.0.CO;2-W","DOIUrl":"https://doi.org/10.1002/(SICI)1099-176X(199909)2:3<137::AID-MHP57>3.0.CO;2-W","url":null,"abstract":"<p>From an economic viewpoint, the amount of primary research conducted on a topic at any given point in time depends on grantmaker and researcher incentives. The potential addresses of research findings often set these incentives. Following this logic, there is an economic explanation provided for the availability of primary data in effcacy studies. This also explains the lack of data in other important fields of health care. This article evaluates why there are few studies on effectiveness and cost-effectiveness then discusses how research incentives might be changed to overcome this problem. As a result of cost containment efforts in some countries, this process has already been initialized.</p>","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"2 3","pages":"137-139"},"PeriodicalIF":1.6,"publicationDate":"1999-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/(SICI)1099-176X(199909)2:3<137::AID-MHP57>3.0.CO;2-W","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72191526","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 : 1999-09-10DOI: 10.1002/(SICI)1099-176X(199906)2:2<73::AID-MHP40>3.0.CO;2-3
Jeanne Miranda, Bonnie L. Green
<div> <section> <p>Despite the fact that the relationship between poverty and increased risk for a broad spectrum of mental disorders has been documented for several decades, very little is known about providing mental health treatments to poor individuals. In this paper, we emphasize the importance of developing, and empirically evaluating, sensitive and appropriate interventions for poor young women who suffer from common mental disorders.</p> </section> <section> <h3> Who are the US poor?</h3> <p>In the US, nearly 14% of individuals live in poverty, and another 20% in near poverty. The poor are disproportionally women and children such that 63% of female-headed households are poor. Young women and ethnic minorities are over-represented among the poor also, with 55% of those living below the poverty level being minorities.</p> </section> <section> <h3> Needs and Barriers to Care among Poor, Young Women</h3> <p>The poor have more mental disorders than those with more resources. Further, women are twice as likely as men to have a mood or anxiety disorder, including major depression and post-traumatic stress disorder (PTSD), with younger women at higher risk than older women. Research alos indicates that poor women have high exposure to traumatic events and cumulative adversity that is directly related to their mental health. This history may serve, in part, as a barrier to seeking mental health care. Other barriers in this population include lack of insurance, lack of access to primary care where mental disorders might be detected, practical problems like lack of childcare or transportation, and the inflexibility of low-income service jobs. Religious beliefs and attitudes about mental health treatment may play a role as well. Recent policy changes in the US have contributed to the vulnerability of this group as eligibility for welfare programs has reduced, and time limits have decreasd. Services for immigrants are also severely limited, and managed care strategies for those in the public sector may be confusing.</p> </section> <section> <h3> Important, Unanswered Questions</h3> <p>More needs to be learned about the mental health status and needs of poor women, along with the impact of loss of public support on their physical and mental health. Access to mental health care within a managed care setting also needs to be addressed, and care taken to understand the particular needs of poor populations that will actually make these services accessible to them. Insufficient attention has thus far been paid to the cost implications of providing these services to the poor. While providing treatment is associated with significant costs, the costs of not
{"title":"The need for mental health services research focusing on poor young women","authors":"Jeanne Miranda, Bonnie L. Green","doi":"10.1002/(SICI)1099-176X(199906)2:2<73::AID-MHP40>3.0.CO;2-3","DOIUrl":"https://doi.org/10.1002/(SICI)1099-176X(199906)2:2<73::AID-MHP40>3.0.CO;2-3","url":null,"abstract":"<div>\u0000 \u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>Despite the fact that the relationship between poverty and increased risk for a broad spectrum of mental disorders has been documented for several decades, very little is known about providing mental health treatments to poor individuals. In this paper, we emphasize the importance of developing, and empirically evaluating, sensitive and appropriate interventions for poor young women who suffer from common mental disorders.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Who are the US poor?</h3>\u0000 \u0000 <p>In the US, nearly 14% of individuals live in poverty, and another 20% in near poverty. The poor are disproportionally women and children such that 63% of female-headed households are poor. Young women and ethnic minorities are over-represented among the poor also, with 55% of those living below the poverty level being minorities.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Needs and Barriers to Care among Poor, Young Women</h3>\u0000 \u0000 <p>The poor have more mental disorders than those with more resources. Further, women are twice as likely as men to have a mood or anxiety disorder, including major depression and post-traumatic stress disorder (PTSD), with younger women at higher risk than older women. Research alos indicates that poor women have high exposure to traumatic events and cumulative adversity that is directly related to their mental health. This history may serve, in part, as a barrier to seeking mental health care. Other barriers in this population include lack of insurance, lack of access to primary care where mental disorders might be detected, practical problems like lack of childcare or transportation, and the inflexibility of low-income service jobs. Religious beliefs and attitudes about mental health treatment may play a role as well. Recent policy changes in the US have contributed to the vulnerability of this group as eligibility for welfare programs has reduced, and time limits have decreasd. Services for immigrants are also severely limited, and managed care strategies for those in the public sector may be confusing.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Important, Unanswered Questions</h3>\u0000 \u0000 <p>More needs to be learned about the mental health status and needs of poor women, along with the impact of loss of public support on their physical and mental health. Access to mental health care within a managed care setting also needs to be addressed, and care taken to understand the particular needs of poor populations that will actually make these services accessible to them. Insufficient attention has thus far been paid to the cost implications of providing these services to the poor. While providing treatment is associated with significant costs, the costs of not","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"2 2","pages":"73-80"},"PeriodicalIF":1.6,"publicationDate":"1999-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/(SICI)1099-176X(199906)2:2<73::AID-MHP40>3.0.CO;2-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71952746","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 : 1999-09-10DOI: 10.1002/(SICI)1099-176X(199906)2:2<93::AID-MHP48>3.0.CO;2-A
Dr Ella Rytik
{"title":"Abstracts translations","authors":"Dr Ella Rytik","doi":"10.1002/(SICI)1099-176X(199906)2:2<93::AID-MHP48>3.0.CO;2-A","DOIUrl":"https://doi.org/10.1002/(SICI)1099-176X(199906)2:2<93::AID-MHP48>3.0.CO;2-A","url":null,"abstract":"","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"2 2","pages":"93-95"},"PeriodicalIF":1.6,"publicationDate":"1999-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/(SICI)1099-176X(199906)2:2<93::AID-MHP48>3.0.CO;2-A","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71952748","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 : 1999-09-10DOI: 10.1002/(SICI)1099-176X(199906)2:2<59::AID-MHP47>3.0.CO;2-J
Mingshan Lu
<div> <section> <h3> Background</h3> <p>Like many other medical technologies and treatments, there is a lack of reliable evidence on treatment effectiveness of mental health care. Increasingly, data from non-experimental settings are being used to study the effect of treatment. However, as in a number of studies using non-experimental data, a simple regression of outcome on treatment shows a puzzling negative and significant impact of mental health care on the improvement of mental health status, even after including a large number of potential control variables. The central problem in interpreting evidence from real-world or non-experimental settings is, therefore, the potential ‘selection bias’ problem in observational data set. In other words, the choice/quantity of mental health care may be correlated with other variables, particularly unobserved variables, that influence outcome and this may lead to a bias in the estimate of the effect of care in conventional models.</p> </section> <section> <h3> Aims of the Study</h3> <p>This paper addresses the issue of estimating treatment effects using an observational data set. The information in a mental health data set obtained from two waves of data in Puerto Rico is explored. The results using conventional models—in which the potential selection bias is not controlled—and that from instrumental variable (IV) models—which is what was proposed in this study to correct for the contaminated estimation from conventional models—are compared.</p> </section> <section> <h3> Methods</h3> <p>Treatment effectiveness is estimated in a production function framework. Effectiveness is measured as the improvement in mental health status. To control for the potential selection bias problem, IV approaches are employed. The essence of the IV method is to use one or more instruments, which are observable factors that influence treatment but do not directly affect patient outcomes, to isolate the effect of treatment variation that is independent of unobserved patient characteristics. The data used in this study are the first (1992–1993) and second (1993–1994) wave of the ongoing longitudinal study <i>Mental Health Care Utilization Among Puerto Ricans</i>, which includes information for an island-wide probability sample of over 3000 adults living in poor areas of Puerto Rico. The instrumental variables employed in this study are travel distance and health insurance sources.</p> </section> <section> <h3> Results</h3> <p>It is very noticeable that in this study, treatment effects were found to be negative in all conventional models (in some cases, highly significant). However, after the IV method w
{"title":"The productivity of mental health care: an instrumental variable approach","authors":"Mingshan Lu","doi":"10.1002/(SICI)1099-176X(199906)2:2<59::AID-MHP47>3.0.CO;2-J","DOIUrl":"https://doi.org/10.1002/(SICI)1099-176X(199906)2:2<59::AID-MHP47>3.0.CO;2-J","url":null,"abstract":"<div>\u0000 \u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Like many other medical technologies and treatments, there is a lack of reliable evidence on treatment effectiveness of mental health care. Increasingly, data from non-experimental settings are being used to study the effect of treatment. However, as in a number of studies using non-experimental data, a simple regression of outcome on treatment shows a puzzling negative and significant impact of mental health care on the improvement of mental health status, even after including a large number of potential control variables. The central problem in interpreting evidence from real-world or non-experimental settings is, therefore, the potential ‘selection bias’ problem in observational data set. In other words, the choice/quantity of mental health care may be correlated with other variables, particularly unobserved variables, that influence outcome and this may lead to a bias in the estimate of the effect of care in conventional models.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Aims of the Study</h3>\u0000 \u0000 <p>This paper addresses the issue of estimating treatment effects using an observational data set. The information in a mental health data set obtained from two waves of data in Puerto Rico is explored. The results using conventional models—in which the potential selection bias is not controlled—and that from instrumental variable (IV) models—which is what was proposed in this study to correct for the contaminated estimation from conventional models—are compared.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Treatment effectiveness is estimated in a production function framework. Effectiveness is measured as the improvement in mental health status. To control for the potential selection bias problem, IV approaches are employed. The essence of the IV method is to use one or more instruments, which are observable factors that influence treatment but do not directly affect patient outcomes, to isolate the effect of treatment variation that is independent of unobserved patient characteristics. The data used in this study are the first (1992–1993) and second (1993–1994) wave of the ongoing longitudinal study <i>Mental Health Care Utilization Among Puerto Ricans</i>, which includes information for an island-wide probability sample of over 3000 adults living in poor areas of Puerto Rico. The instrumental variables employed in this study are travel distance and health insurance sources.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>It is very noticeable that in this study, treatment effects were found to be negative in all conventional models (in some cases, highly significant). However, after the IV method w","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"2 2","pages":"59-71"},"PeriodicalIF":1.6,"publicationDate":"1999-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/(SICI)1099-176X(199906)2:2<59::AID-MHP47>3.0.CO;2-J","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71920826","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 : 1999-09-10DOI: 10.1002/(SICI)1099-176X(199906)2:2<81::AID-MHP41>3.0.CO;2-%23
Kathryn Rost
Background and Aims of the Manuscript
The purpose of this manuscript is to define under-recognized perspectives that the primary care research field needs to integrate into research initiatives, and to discuss practical strategies to ensure the successful implementation of these initiatives.
Methods
Perspectives and strategies were identified through personal experience, informal discussion with ten senior investigators in the field and a selected literature review.
Results
Research on improving treatment for the mental health problems of primary care patients will progress more rapidly if investigators explore the usefulness of a competing demands framework, integrate a readiness to change perspective in developing more individualized interventions for providers and patients, evaluate interventions for their effect on productivity and test alternative interventions particularly in patients who fail to benefit from currently accepted treatment. The implementation of these initiatives will be more successful if research teams define unique scientific agendas, invest energy in pursuing questions whose value is undisputed by multiple parties, increase the rate of inter-institutional exchange between senior and junior investigators, pilot test assumptions that affect project budget and timeline, build in a limited amount of slack time in early phases of project implementation and network effectively.
Pub Date : 1999-09-10DOI: 10.1002/(SICI)1099-176X(199906)2:2<55::AID-MHP42>3.0.CO;2-1
Andrew Healey, Daniel Chisholm
Background
Decision-makers would benefit from being able to plan and evaluate mental health care interventions or programmes on the basis of costs and consequences that are measured in the same unit of measurement (money being the most convenient). Monetized quantification of the consequences of alternative interventions could be subsequently incorporated into cost–benefit allocation decisions.
Aim
This paper provides an overview of the policy and research context within which willingness-to-pay survey techniques are located, together with a review of the main approaches used to date. We also highlight key issues in the application of these techniques and indicate areas of mental health research and policy that could benefit from their introduction.
Method
Willingness-to-pay survey techniques are reviewed, and issues concerning their validity and application in the context of cost–benefit analyses of mental health policies are discussed.
Discussion
Different survey methods are available for generating willingness-to-pay data, the most common being the contingent valuation approach. An assessment of the validity of data generated by these alternative techniques is vital in order to ensure that they are consistent with the notion of economic preferences and values.
Pub Date : 1999-09-10DOI: 10.1002/(SICI)1099-176X(199906)2:2<91::AID-MHP46>3.0.CO;2-I
Donald S. Shepard
{"title":"Cost-effectiveness in Health and Medicine. By M.R. Gold, J.E Siegel, L.B. Russell, and M.C. Weinstein (eds). New York: Oxford University Press, 1996","authors":"Donald S. Shepard","doi":"10.1002/(SICI)1099-176X(199906)2:2<91::AID-MHP46>3.0.CO;2-I","DOIUrl":"https://doi.org/10.1002/(SICI)1099-176X(199906)2:2<91::AID-MHP46>3.0.CO;2-I","url":null,"abstract":"","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"2 2","pages":"91-92"},"PeriodicalIF":1.6,"publicationDate":"1999-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/(SICI)1099-176X(199906)2:2<91::AID-MHP46>3.0.CO;2-I","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71952749","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 : 1999-09-10DOI: 10.1002/(SICI)1099-176X(199906)2:2<85::AID-MHP43>3.0.CO;2-Q
Sir David Goldberg
{"title":"Comments upon ‘improving research on primary care patients with mental health problems’","authors":"Sir David Goldberg","doi":"10.1002/(SICI)1099-176X(199906)2:2<85::AID-MHP43>3.0.CO;2-Q","DOIUrl":"https://doi.org/10.1002/(SICI)1099-176X(199906)2:2<85::AID-MHP43>3.0.CO;2-Q","url":null,"abstract":"","PeriodicalId":46381,"journal":{"name":"Journal of Mental Health Policy and Economics","volume":"2 2","pages":"85-86"},"PeriodicalIF":1.6,"publicationDate":"1999-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/(SICI)1099-176X(199906)2:2<85::AID-MHP43>3.0.CO;2-Q","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71945007","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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