\documentclass{CUP-JNL-DAP}%


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\usepackage{amsmath,amssymb,amsfonts}
\usepackage{mathrsfs}
\usepackage{amsthm}
\usepackage{apacite}
\usepackage{rotating}
\usepackage{appendix}
\usepackage[authoryear]{natbib}
\usepackage{ifpdf}
\usepackage[T1]{fontenc}%
\usepackage{times}%
\usepackage{sourcesanspro}%
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%%%%

\articletype{DATA FOR POLICY CONFERENCE PAPER}
\jname{Data \& Policy}
%\artid{20}
\jyear{2025}
%\jvol{5}
%\jissue{1}
\jdoi{10.1017/dap.2024.xx}
\raggedbottom
\begin{document}

\begin{Frontmatter}

\title[Emerging health data platforms]{Example article title: From individual control
to collective data governance}



\author*[1]{First author}\email{sample.email@institution.edu}\orcid{0000-0002-8514-4315}
\author[2]{Second author}
\author[3]{Third author}
\author[1]{Fourth author}
\author[2]{Fifth author}
\author[3]{Sixth author}
\author[1]{Seventh author}

\authormark{First author \etal}

\address*[1]{\orgdiv{Department}, \orgname{Institution}, \city{City}, \state{State}, \country{Country}}
\address[2]{\orgdiv{Department}, \orgname{Institution}, \city{City}, \state{State}, \country{Country}}
\address[3]{\orgdiv{Department}, \orgname{Institution}, \city{City}, \state{State}, \country{Country}}

\received{Blank date}
\revised{Blank date}
\accepted{Blank date}

\keywords{data governance; data stewardship; emerging data platforms; health data; person generated health data}

\keywords[Abbreviations]{EHR, Electronic Health Records; EU, European Union; GDPR, General Data Protection Regulation; HRB, Health Record Bank; ODI, Open Data Institute; PLM, Patients Like Me}

\abstract{Abstracts should be 250 words. It must be able to stand alone and so cannot contain citations to the paper's references, equations, etc. An abstract must consist of a single paragraph and be concise. Because of online formatting, abstracts must appear as plain as possible.}


\begin{policy}
Provide a 120 word statement here that summarises the significance of the work for policymakers, written at a level understandable for a broad audience.
\end{policy}

\end{Frontmatter}


\section{Introduction}

This is a template for a full paper submitted to the Data for Policy Conference 2024. It should aim for 6,000 words in length including references. The Introduction, Methods, Results, Discussion structure is not prescriptive: we have just included these as example headings. What follows is some sample text, equations and tables to help guide you in the writing of the paper. 


Note that all full paper submissions should be submitted to the Data and Policy journal at Cambridge University Press via \url{https://mc.manuscriptcentral.com/dataandpolicy} for simultaenous consideration for the conference and journal.

Example text follows. More data can now be analyzed faster enabling researchers to explore more and more complex
interactions. Data across a wide spectrum from open data\footnote{\url{https://data.gov.uk/}} that can be downloaded, through licensed data,\footnote{\url{https://www.ukdataservice.ac.uk/}}
to sensitive personal data can now contribute to our understanding of health, social, and economic outcomes.

The United Kingdom has a long tradition of safe data use by researchers. In the 50 years that the UK
Data Archive has been making data available for social and economic research, there have been no
damaging disclosures of personal information by academic researchers\footnote{That is not to say that there have been no breaches---researchers using data for a project they are not licensed for or passing data
to unlicensed colleagues---however, this, as far as we are aware of, has never caused harm to individuals or entities in the data.}. While increasing use of detailed and sometimes sensitive
data can contribute valuable insights for targeting policies, we cannot be
complacent. In order to support our policy needs and continue to use data safely and effectively, we
need a research infrastructure that protects data confidentiality while enabling researchers to undertake
innovative research.

A first step toward protecting sensitive data is to keep control of it, to disseminate access, not data. Data
providers internationally are increasing, moving toward systems in which researchers remotely access and
analyses data that are stored within a controlled environment, with any data that are removed from the
system being checked in some way to minimize chances of disclosure.

This paper will look at remote data access as one method of protecting sensitive data while enabling its
effective use for research. It will look at how the Digital Economy Act can strengthen the UK data research
infrastructure and make some recommendations for other improvements

\section[This is an A Head]{Methods}

The results of data mining endeavors are majorly driven by data quality. Throughout these deployments, serious show-stopper problems are usually unresolved, such as data collection ambiguities, data imbalance, hidden biases in data, the lack of domain information, and data incompleteness. In a traditional data science lifecycle, outliers, bias, variance, boosting, over and under sampling, and data wrangling are measures that can be tuned to mitigate output quality issues and misinformation. In our work, we performed data collection from multiple sources to mitigate issues relevant to one dataset. Additionally, normalization, descriptive analytics, hyperparameter selection, and other quality-control methods are implemented.

\subsection{Data Collection}

Real-world data of this study are collected from Centers for Medicare and Medicaid Services (CMS) including data on patient complications and deaths, hospital general information, cost, and value of care for each hospital.

\subsubsection{Method 1}

RL is a subfield of AI; it involves the process of learning of an agent by using a trial and error approach that maximizes rewards by interacting with dynamic environments 

\paragraph{Method 2}

GA is a subfield of evolutionary algorithms; they are inspired by the process of biological natural selection. 

\section[This is an A Head]{Results}

Method 1 is deployed through a real-time R-Shiny web application.  The presented web application is to be used at a hospital for real-time decision-making support. The RL algorithm is connected to the application, and the model could be retrained in real time when new data are available. A hospital manager can use the “hospitalization ratio,” a parameter in clinical severity (aggregate of patients’ situation) for determining the amount of resources needed. The mentioned RL stages are represented as scales based on transmissibility and clinical severity. The outcomes (i.e., actions) are assigned as either “Idle” or “Share”—which represents the recommendation that the RL algorithm generates.

\subsection{Valdation}
\subsubsection{Limitatins}
\paragraph{Another heading}
In the 50 years that the UK
Data Archive has been making data available for social and economic research, there have been no
damaging disclosures of personal information by academic researchers. While increasing use of detailed and sometimes sensitive
data can contribute valuable insights for targeting policies, we cannot be
complacent. In order to support our policy needs and continue to use data safely and effectively, we
need a research infrastructure that protects data confidentiality while enabling researchers to undertake
innovative research.

\section{Equations}

Equations in \LaTeX{} can either be inline or on-a-line by itself. For
inline equations use the \verb+$...$+ commands. Eg: The equation
$H\psi = E \psi$ is written via the command $H \psi = E \psi$.

For on-a-line by itself equations (with auto generated equation numbers)
one can use the equation or eqnarray environments \textit{D}.
\begin{equation}
\mathcal{L} = i {\psi} \gamma^\mu D_\mu \psi
    - \frac{1}{4} F_{\mu\nu}^a F^{a\mu\nu} - m {\psi} \psi
\label{eq1}
\end{equation}
where,
\begin{align}
D_\mu &=  \partial_\mu - ig \frac{\lambda^a}{2} A^a_\mu
\nonumber \\
F^a_{\mu\nu} &= \partial_\mu A^a_\nu - \partial_\nu A^a_\mu
    + g f^{abc} A^b_\mu A^a_\nu
\label{eq2}
\end{align}
Notice the use of \verb+\nonumber+ in the align environment at the end
of each line, except the last, so as not to produce equation numbers on
lines where no equation numbers are required. The \verb+\label{}+ command
should only be used at the last line of an align environment where
\verb+\nonumber+ is not used.
\begin{equation}
Y_\infty = \left( \frac{m}{\textrm{GeV}} \right)^{-3}
    \left[ 1 + \frac{3 \ln(m/\textrm{GeV})}{15}
    + \frac{\ln(c_2/5)}{15} \right]
\end{equation}
The class file also supports the use of \verb+\mathbb{}+, \verb+\mathscr{}+ and
\verb+\mathcal{}+ commands. As such \verb+\mathbb{R}+, \verb+\mathscr{R}+
and \verb+\mathcal{R}+ produces $\mathbb{R}$, $\mathscr{R}$ and $\mathcal{R}$
respectively.


\section{Tables}

Tables can be inserted via the normal table and tabular environment. To put
footnotes inside tables one has to use the additional ``fntable" environment
enclosing the tabular environment. The footnote appears just below the table
itself.

%\begin{table}[h]
%\TBL{\caption{Caption text.\label{tab1}}}
%{%
%\begin{tabular}{@{}llll@{}}\toprule
%\TCH{column 1} & \TCH{column 2}  & \TCH{column 3} &
%\TCH{column 4}\\\midrule
%row 1    & data 1   & data 2  & data 3  \\
%row 2    & data 4   & data 5  & data 6  \\
%row 3    & data 7   & data 8  & data 9  \\\botrule
%\end{tabular}}
%\end{table}
%%

\begin{table}[b]
\tabcolsep=0pt%
\TBL{\caption{Tables which are too long to fit,
should be written using the ``table*'' environment as shown here\label{tab2}}}
{\begin{fntable}
\begin{tabular*}{\textwidth}{@{\extracolsep{\fill}}lcccccc@{}}\toprule%
 & \multicolumn{3}{@{}c@{}}{\TCH{Element 1}}& \multicolumn{3}{@{}c@{}}{\TCH{Element 2\smash{\footnotemark[1]}}}
 \\\cmidrule{2-4}\cmidrule{5-7}%
\TCH{Projectile} & \TCH{Energy} & \TCH{$\sigma_{\mathit{calc}}$} & \TCH{$\sigma_{\mathit{expt}}$} &
\TCH{Energy} & \TCH{$\sigma_{\mathit{calc}}$} & \TCH{$\sigma_{\mathit{expt}}$} \\\midrule
\TCH{Element 3}&990 A &1168 &$1547\pm12$ &780 A &1166 &$1239\pm100$\\
{\TCH{Element 4}}&500 A &961 &$922\pm10$ &900 A &1268 &$1092\pm40$\\
\botrule
\end{tabular*}%
\footnotetext[]{{Note:} This is an example of table footnote this is an example of table footnote this is an example of table footnote this is an example of~table footnote this is an example of table footnote}
\footnotetext[1]{This is an example of table footnote}%
\end{fntable}}
\end{table}


\section{Figures}

As per the \LaTeX\ standards eps images in \verb!latex! and pdf/jpg/png images in
\verb!pdflatex! should be used. This is one of the major differences between \verb!latex!
and \verb!pdflatex!. The images should be single page documents. The command for inserting images
for latex and pdflatex can be generalized. The package that should be used
is the graphicx package.

\begin{figure}[t]%
\FIG{\includegraphics[width=0.9\textwidth]{Fig}}
{\caption{This is a widefig. This is an example of long caption this is an example of long caption  this~is~an example of long caption this is an example of long caption}
\label{fig1}}
\end{figure}



\section{Cross referencing}

Environments such as figure, table, equation, align can have a label
declared via the \verb+\label{#label}+ command. For figures and table
environments one should use the \verb+\label{}+ command inside or just
below the \verb+\caption{}+ command.  One can then use the
\verb+\ref{#label}+ command to cross-reference them. As an example, consider
the label declared for Figure \ref{fig1} which is
\verb+\label{fig1}+. To cross-reference it, use the command
\verb+ Figure \ref{fig1}+, for which it comes up as
``Figure \ref{fig1}".
The reference citations should used as per the "natbib" packages. Some sample citations:  \cite{bib1,bib2,bib3,bib4,bib5,bib6,bib7}.

\section{Lists}

List in \LaTeX{} can be of three types: enumerate, itemize and description.
In each environments, new entry is added via the \verb+\item+ command.
Enumerate creates numbered lists, itemize creates bulleted lists and
description creates description lists.
List in \LaTeX{} can be of three types: enumerate, itemize and description.
In each environments, new entry is added via the \verb+\item+ command.
Enumerate creates numbered lists, itemize creates bulleted lists and
description creates description lists.
\begin{enumerate}[1.]
\item This is the 1st item
\item Enumerate creates numbered lists, itemize creates bulleted lists and
description creates description lists.
\item Numbered lists continue.
\end{enumerate}
List in \LaTeX{} can be of three types: enumerate, itemize and description.
In each environments, new entry is added via the \verb+\item+ command.
\begin{itemize}
\item This is the 1st item
\item Itemize creates bulleted lists and
description creates description lists.
\item Bullet lists continue.
\end{itemize}



\section{Conclusion}

Some Conclusions here.


\begin{Backmatter}

\paragraph{Provenance}

This article was submitted for consideration for the 2024 Data for Policy Conference to be published in Data and Policy on the strength of the Conference review process.

\paragraph{Acknowledgments}
We are grateful for the technical assistance of A. Author.

\paragraph{Funding Statement}
This research was supported by grants from the <funder-name><doi>(<award ID>); <funder-name><doi>(<award ID>).

\paragraph{Competing Interests}
A statement about any financial, professional, contractual or personal relationships or situations that could be perceived to impact the presentation of the work --- or `None' if none exist

\paragraph{Data Availability Statement}
A statement about how to access data, code and other materials allowing users to understand, verify and replicate findings --- e.g. Replication data and code can be found in Harvard Dataverse: \url{https://doi.org/link}.

\paragraph{Author Contributions}
A.A. and A.B.C. designed the study, abstracted the data wrote the first draft, and approved the final
version of the manuscript. A.R.E.J., M.R.L., K.L.S., and A.D.P. revised the manuscript and approved the final version.

\paragraph{Additional Material}
Description and links to any other relevant online materials, such as videos, presentations, papers hosted in the Data for Policy Zenodo site.

%\bibliographystyle{apalike}
%\bibliography{Sample-refs}

\begin{thebibliography}{}

\bibitem[Freud, 1953]{bib7}
\textbf{Freud S} (1953) \textit{The Method of Interpreting Dreams}, volume~4, pages 96--121.
 American Psychological Association.

\bibitem[Gilbert et~al., 2004]{bib2}
\textbf{Gilbert DG}, \textbf{McClernon JF}, \textbf{Rabinovich NE}, \textbf{Sugai C}, \textbf{Plath LC},
  \textbf{Asgaard G}, \textbf{Dickinson D and Botros N} (2004)
 Effects of quitting smoking and {EEG} activation and attention last
  for more than 31 days and are more severe with stress, dependence, {DRD2 A1}
  allele, and depressive traits. \textit{Nicotine and Tobacco Research} \textit{6}, 249--267.

\bibitem[Herbst-Damm and Kulik, 2005]{bib1}
\textbf{Herbst-Damm KL and Kulik JA} (2005)
Volunteer support, marital status, and the survival times of terminally ill patients.
\textit{Health Psychology} \textit{24}, 225--229.

\bibitem[Light and Light, 2008]{bib3}
\textbf{Light MA and Light IH} (2008)
 The geographic expansion of {M}exican immigration in the {U}nited {S}tates and its implications for local law enforcement. \textit{Law Enforcement Executive Forum Journal} \textit{8}(1), 73--82.

\bibitem[Schiraldi, 2001]{bib5}
\textbf{Schiraldi GR} (2001) \textit{The Post-traumatic Stress Disorder Sourcebook}. Springer.

\bibitem[Shotton, 1989]{bib4}
\textbf{Shotton MA} (1989) \textit{Computer Addiction? {A} Study of Computer Dependency}.  Taylor \& Francis.

\bibitem[VandenBos, 2007]{bib6}
\textbf{VandenBos GR}, editor (2007) \textit{APA Dictionary of Psychology}. American Psychological Association.
\end{thebibliography}

\end{Backmatter}



\end{document}
