Example of Health Services and Outcomes Research Methodology format
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Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format
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Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format Example of Health Services and Outcomes Research Methodology format
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open access Open Access

Health Services and Outcomes Research Methodology — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Health Policy #95 of 242 up up by 18 ranks
Public Health, Environmental and Occupational Health #229 of 526 up up by 27 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 59 Published Papers | 162 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 13/06/2020
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open access Open Access
recommended Recommended

Springer

Quality:  
High
CiteRatio: 4.5
SJR: 0.909
SNIP: 1.357
open access Open Access

Springer

Quality:  
High
CiteRatio: 4.0
SNIP: 1.464
open access Open Access

Springer

Quality:  
High
CiteRatio: 5.1
SJR: 1.472
SNIP: 2.009
open access Open Access

Springer

Quality:  
High
CiteRatio: 4.6
SJR: 1.367
SNIP: 1.702

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

2.7

7% from 2019

CiteRatio for Health Services and Outcomes Research Methodology from 2016 - 2020
Year Value
2020 2.7
2019 2.9
2018 2.0
2017 1.9
2016 1.5
graph view Graph view
table view Table view

0.716

13% from 2019

SJR for Health Services and Outcomes Research Methodology from 2016 - 2020
Year Value
2020 0.716
2019 0.824
2018 0.758
2017 0.683
2016 0.338
graph view Graph view
table view Table view

1.231

23% from 2019

SNIP for Health Services and Outcomes Research Methodology from 2016 - 2020
Year Value
2020 1.231
2019 1.001
2018 0.686
2017 0.781
2016 0.688
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has decreased by 7% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has decreased by 13% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 23% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Health Services and Outcomes Research Methodology

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Springer

Health Services and Outcomes Research Methodology

The journal reflects the multidisciplinary nature of the field of health services and outcomes research. It addresses the needs of multiple, interlocking communities, including methodologists in statistics, econometrics, social and behavioral sciences; designers and analysts o...... Read More

Health Policy

Public Health, Environmental and Occupational Health

Medicine

i
Last updated on
13 Jun 2020
i
ISSN
1387-3741
i
Impact Factor
Low - 0.295
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
SPBASIC
i
Citation Type
Author Year
(Blonder et al, 1982)
i
Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

Journal Article DOI: 10.1023/A:1020363010465
Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation
Donald B. Rubin1

Abstract:

Propensity score methodology can be used to help design observational studies in a way analogous to the way randomized experiments are designed: without seeing any answers involving outcome variables. The typical models used to analyze observational data (e.g., least squares regressions, difference of difference methods) invo... Propensity score methodology can be used to help design observational studies in a way analogous to the way randomized experiments are designed: without seeing any answers involving outcome variables. The typical models used to analyze observational data (e.g., least squares regressions, difference of difference methods) involve outcomes, and so cannot be used for design in this sense. Because the propensity score is a function only of covariates, not outcomes, repeated analyses attempting to balance covariate distributions across treatment groups do not bias estimates of the treatment effect on outcome variables. This theme will the primary focus of this article: how to use the techniques of matching, subclassification and/or weighting to help design observational studies. The article also proposes a new diagnostic table to aid in this endeavor, which is especially useful when there are many covariates under consideration. The conclusion of the initial design phase may be that the treatment and control groups are too far apart to produce reliable effect estimates without heroic modeling assumptions. In such cases, it may be wisest to abandon the intended observational study, and search for a more acceptable data set where such heroic modeling assumptions are not necessary. The ideas and techniques will be illustrated using the initial design of an observational study for use in the tobacco litigation based on the NMES data set. read more read less

Topics:

Average treatment effect (60%)60% related to the paper, Observational study (59%)59% related to the paper, Propensity score matching (57%)57% related to the paper, Matching (statistics) (56%)56% related to the paper, Rubin causal model (54%)54% related to the paper
1,830 Citations
Journal Article DOI: 10.1023/A:1020371312283
Estimation of Causal Effects using Propensity Score Weighting: An Application to Data on Right Heart Catheterization
Keisuke Hirano1, Guido W. Imbens2

Abstract:

We consider methods for estimating causal effects of treatments when treatment assignment is unconfounded with outcomes conditional on a possibly large set of covariates. Robins and Rotnitzky (1995) suggested combining regression adjustment with weighting based on the propensity score (Rosenbaum and Rubin, 1983). We adopt thi... We consider methods for estimating causal effects of treatments when treatment assignment is unconfounded with outcomes conditional on a possibly large set of covariates. Robins and Rotnitzky (1995) suggested combining regression adjustment with weighting based on the propensity score (Rosenbaum and Rubin, 1983). We adopt this approach, allowing for a flexible specification of both the propensity score and the regression function. We apply these methods to data on the effects of right heart catheterization (RHC) studied in Connors et al (1996), and we find that our estimator gives stable estimates over a wide range of values for the two parameters governing the selection of variables. read more read less

Topics:

Propensity score matching (57%)57% related to the paper, Causal inference (52%)52% related to the paper
View PDF
1,070 Citations
open accessOpen access Journal Article DOI: 10.1007/S10742-014-0123-Z
Using propensity scores in difference-in-differences models to estimate the effects of a policy change

Abstract:

Difference-in-difference (DD) methods are a common strategy for evaluating the effects of policies or programs that are instituted at a particular point in time, such as the implementation of a new law. The DD method compares changes over time in a group unaffected by the policy intervention to the changes over time in a grou... Difference-in-difference (DD) methods are a common strategy for evaluating the effects of policies or programs that are instituted at a particular point in time, such as the implementation of a new law. The DD method compares changes over time in a group unaffected by the policy intervention to the changes over time in a group affected by the policy intervention, and attributes the “difference-in-differences” to the effect of the policy. DD methods provide unbiased effect estimates if the trend over time would have been the same between the intervention and comparison groups in the absence of the intervention. However, a concern with DD models is that the program and intervention groups may differ in ways that would affect their trends over time, or their compositions may change over time. Propensity score methods are commonly used to handle this type of confounding in other non-experimental studies, but the particular considerations when using them in the context of a DD model have not been well investigated. In this paper, we describe the use of propensity scores in conjunction with DD models, in particular investigating a propensity score weighting strategy that weights the four groups (defined by time and intervention status) to be balanced on a set of characteristics. We discuss the conceptual issues associated with this approach, including the need for caution when selecting variables to include in the propensity score model, particularly given the multiple time point nature of the analysis. We illustrate the ideas and method with an application estimating the effects of a new payment and delivery system innovation (an accountable care organization model called the “Alternative Quality Contract” (AQC) implemented by Blue Cross Blue Shield of Massachusetts) on health plan enrollee out-of-pocket mental health service expenditures. We find no evidence that the AQC affected out-of-pocket mental health service expenditures of enrollees. read more read less

Topics:

Propensity score matching (54%)54% related to the paper, Context (language use) (50%)50% related to the paper, Difference in differences (50%)50% related to the paper
View PDF
344 Citations
open accessOpen access Journal Article DOI: 10.1007/S10742-008-0041-Z
The Analysis of Social Networks
A. James O'Malley1, Peter V. Marsden1

Abstract:

Many questions about the social organization of medicine and health services involve interdependencies among social actors that may be depicted by networks of relationships. Social network studies have been pursued for some time in social science disciplines, where numerous descriptive methods for analyzing them have been pro... Many questions about the social organization of medicine and health services involve interdependencies among social actors that may be depicted by networks of relationships. Social network studies have been pursued for some time in social science disciplines, where numerous descriptive methods for analyzing them have been proposed. More recently, interest in the analysis of social network data has grown among statisticians, who have developed more elaborate models and methods for fitting them to network data. This article reviews fundamentals of, and recent innovations in, social network analysis using a physician influence network as an example. After introducing forms of network data, basic network statistics, and common descriptive measures, it describes two distinct types of statistical models for network data: individual-outcome models in which networks enter the construction of explanatory variables, and relational models in which the network itself is a multivariate dependent variable. Complexities in estimating both types of models arise due to the complex correlation structures among outcome measures. read more read less

Topics:

Dynamic network analysis (67%)67% related to the paper, Social network (67%)67% related to the paper, Organizational network analysis (67%)67% related to the paper, Network science (66%)66% related to the paper, Social network analysis (criminology) (65%)65% related to the paper
View PDF
308 Citations
Journal Article DOI: 10.1007/S10742-005-4304-7
A Literature Review of the Use of GIS-Based Measures of Access to Health Care Services
Gary Higgs1

Abstract:

The increasing availability of Geographical Information Systems (GIS) in health organisations, together with the proliferation of spatially disaggregate data, has led to a number of studies that have been concerned with developing measures of access to health care services. The main aim of this paper is to review the use of G... The increasing availability of Geographical Information Systems (GIS) in health organisations, together with the proliferation of spatially disaggregate data, has led to a number of studies that have been concerned with developing measures of access to health care services. The main aim of this paper is to review the use of GIS-based measures in exploring the relationship between geographic access, utilisation, quality and health outcomes. The varieties of approaches taken by researchers concerned with teasing out the relative importance of geographical factors that may influence access are examined. To date, in the absence of detailed data on health utilisation patterns, much of this research has focused on developing measures of potential accessibility. This paper then critically evaluates the situation with regard to the use of such measures in a broad range of accessibility studies. In particular, there has been less research to date that examines the relationship between such measures and health outcomes. In the final sections of the paper, I draw on the review to outline areas where a broader research agenda is needed, particularly in relation to more recent innovations in health care delivery. read more read less

Topics:

Health care (61%)61% related to the paper, Health policy (58%)58% related to the paper, HRHIS (57%)57% related to the paper, Public health (53%)53% related to the paper, Health administration (53%)53% related to the paper
View PDF
265 Citations
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Health Services and Outcomes Research Methodology format uses SPBASIC citation style.

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Frequently asked questions

1. Can I write Health Services and Outcomes Research Methodology in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Health Services and Outcomes Research Methodology guidelines and auto format it.

2. Do you follow the Health Services and Outcomes Research Methodology guidelines?

Yes, the template is compliant with the Health Services and Outcomes Research Methodology guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Health Services and Outcomes Research Methodology?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Health Services and Outcomes Research Methodology citation style.

4. Can I use the Health Services and Outcomes Research Methodology templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Health Services and Outcomes Research Methodology.

5. Can I use a manuscript in Health Services and Outcomes Research Methodology that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Health Services and Outcomes Research Methodology that you can download at the end.

6. How long does it usually take you to format my papers in Health Services and Outcomes Research Methodology?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Health Services and Outcomes Research Methodology.

7. Where can I find the template for the Health Services and Outcomes Research Methodology?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Health Services and Outcomes Research Methodology's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Health Services and Outcomes Research Methodology's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Health Services and Outcomes Research Methodology an online tool or is there a desktop version?

SciSpace's Health Services and Outcomes Research Methodology is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Health Services and Outcomes Research Methodology?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Health Services and Outcomes Research Methodology?”

11. What is the output that I would get after using Health Services and Outcomes Research Methodology?

After writing your paper autoformatting in Health Services and Outcomes Research Methodology, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Health Services and Outcomes Research Methodology's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Health Services and Outcomes Research Methodology?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Health Services and Outcomes Research Methodology. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Health Services and Outcomes Research Methodology?

The 5 most common citation types in order of usage for Health Services and Outcomes Research Methodology are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Health Services and Outcomes Research Methodology?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Health Services and Outcomes Research Methodology's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Health Services and Outcomes Research Methodology in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Health Services and Outcomes Research Methodology Endnote style according to Elsevier guidelines.

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