John Paul Backhouse

John Paul Backhouse

New York, New York, United States
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I am an innovative and results-oriented Chief Information Officer (CIO) with a…

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Articles by John Paul

  • Backhouse, The Distinguished Surname.
    Sep 26, 2017

    Backhouse, The Distinguished Surname.

    As I originate from England, I am often asked about the origins of my surname, as it is quite unusual to hear this name…

    4 Comments
  • 240 years ago...
    Jun 30, 2017

    240 years ago...

    To All my America friends, happy Independence day hope you all have an memorable day.

  • Blueprint for Consolidated Enterprise Information Governance
    Dec 7, 2016

    Blueprint for Consolidated Enterprise Information Governance

    Here is our blueprint for enterprise information consolidated governance. We break our governance into two groups -…

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Experience

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    Sutherland

    United States

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    United States

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    United States

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    New York, New York, United States

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    Covington, Louisiana, United States

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    Pittsburgh, Pennsylvania, United States

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    Greater New York City Area

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    Indiana USA

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    Valparaiso, Indiana

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    Greater Denver Area

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    New York

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    United Kingdom

Education

Publications

  • Return on Value

    John Backhouse - Information Builders

    While most technology solutions refer to Return on Investment studies to ensure the net financial,
    operational and cultural fit of a solution, the recent 2014 National Survey of CIOs titled “The Landscape of Data & Analytics in Healthcare” suggests Return on Value to be used as a broader approach, given the difficult issues around funding and culture. Below is an excerpt from the study:
    Analytics used to be based on simpler approaches to grouping patients. Now, to do things right…

    While most technology solutions refer to Return on Investment studies to ensure the net financial,
    operational and cultural fit of a solution, the recent 2014 National Survey of CIOs titled “The Landscape of Data & Analytics in Healthcare” suggests Return on Value to be used as a broader approach, given the difficult issues around funding and culture. Below is an excerpt from the study:
    Analytics used to be based on simpler approaches to grouping patients. Now, to do things right, you
    have to have expertise in epidemiology, biostatistics, economics... As the sophistication has increased, so has the amount of knowledge needed to use technologies.”
    ‐ Dave Foster, PhD, MPH
    “To navigate issues of funding and culture, leaders have sought to reframe costs in terms of value. Tom Gordon focuses on ways in which analytics provide a “return on value, bend the cost curve, improve patient safety and quality, and help manage the patient population,” rather than recouping
    implementation and operational expenses. Mony Weschler stressed the overall importance of
    technology to modern healthcare, noting that some clinical specialties can’t function today without
    advanced health IT systems. “The organization has to understand that you need to manage the patient from all aspects. Once you start collecting the data, it’s essential to survival.” Chuck Christian
    compared analytics to essential infrastructure: “I don’t know too many businesses that do an ROI on
    their parking lot, but they’d better have one if they want customers. If we don’t have these things,
    we can’t compete.”

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  • Improving Patient Matching Using Healthcare IT and Data Strategy to Create a Single Patient View

    John Backhouse - Information Builders

    Patient matching is one of the biggest issues facing healthcare today. It is critical to effective
    health information exchange (HIE) and population health. The challenge starts with getting it
    right within a healthcare organization first.
    The risks of pattern-matching inaccuracies are both clinical and financial. The clinical impact is
    manifested as inadequate, ineffective, or inappropriate care, and results in readmissions, privacy
    violations, and low-quality short- and…

    Patient matching is one of the biggest issues facing healthcare today. It is critical to effective
    health information exchange (HIE) and population health. The challenge starts with getting it
    right within a healthcare organization first.
    The risks of pattern-matching inaccuracies are both clinical and financial. The clinical impact is
    manifested as inadequate, ineffective, or inappropriate care, and results in readmissions, privacy
    violations, and low-quality short- and long-term wellness. Financially, patient-matching failures result
    in billing errors that delay payments and increase customer frustration and dissatisfaction, as well as
    regulatory and compliance violations that can result in fines or reduced reimbursement funds.
    A November 2013 report by Kaiser Health News, in collaboration with NPR, reported, “Medicare
    penalizes nearly 1,500 hospitals for poor quality scores.”1 The article also stated, “Medicare has
    raised payment rates to 1,231 hospitals based on two-dozen quality measurements, including
    surveys of patient satisfaction and – for the first time – death rates. Another 1,451 hospitals are
    being paid less for each Medicare patient they treat.”
    Patient matching is a complex process, and that complexity grows the more patients use healthcare.
    As patients move through their pathways of care, their journey will ultimately take them
    beyond their first provider. That is where the patient-matching challenge begins. Moving from that
    first provider to the second, the third, and so on increases the complexity of matching patients
    and their records across healthcare organizations. It also potentially increases the associated
    clinical and financial costs (Figure 1). Understanding where it all started, and the current state of
    patient data within a single healthcare organization, will shed light on effective solutions.

    See publication

  • Data in Motion – Big Data Analytics in Healthcare

    John Backhouse - Information Builders

    There are a number of questions – and lots of marketing hype – surrounding big data. Some
    healthcare providers argue that the use of big data is the key to achieving sustainable competitive
    advantage and optimizing clinical outcomes. Others wonder if it is a buzzword with more risk than
    reward. All will agree that new approaches to analytics are needed to fully harness the available
    data points across the patient journey and transform it into actionable insight that will…

    There are a number of questions – and lots of marketing hype – surrounding big data. Some
    healthcare providers argue that the use of big data is the key to achieving sustainable competitive
    advantage and optimizing clinical outcomes. Others wonder if it is a buzzword with more risk than
    reward. All will agree that new approaches to analytics are needed to fully harness the available
    data points across the patient journey and transform it into actionable insight that will truly
    enhance care quality.
    Some providers believe they already have solutions in place, but those solutions often consist of
    just an Excel spreadsheet and a database. For healthcare providers and payers alike, more powerful
    and robust tools are needed to successfully leverage big data and analytics to improve patient
    care delivery, accelerate accountable care business models, reduce costs, and drive organizational
    change throughout the value chain.
    Data – especially when generated in the healthcare setting – is never at rest. As patients see
    physicians and receive diagnostic tests, information about those visits and procedures flows
    between systems, providers, insurance companies, and healthcare networks. Other data may also
    be required, including details about enrollments, provider credentialing, or fee schedules, as well
    as information collected from medical collaborators and other external sources, such as electronic
    health records, medical images, and care management documentation. This data in motion drives
    the need for the continual use of analytics to improve services, reduce costs, and enable informed
    patient care and decision-making.
    This paper explores the real-world challenges healthcare providers face when considering big
    data and analytics. We will present a successful case study, as well as a comprehensive strategy for
    implementing big data analytics within an organization.

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  • Integration, Data Quality, and the Patient Journey

    John Backhouse - Information Builders

    How do today’s frontline clinicians and managers overcome the demanding challenges they face
    each day? Interoperability is not the answer; it is simply a buzzword that has been used too often,
    and for too long.
    What healthcare facilities truly need is realistic integration and sustainable data quality throughout
    their entire health information system.
    Healthcare organizations are under constant pressure to improve quality of care without adding
    staff or increasing…

    How do today’s frontline clinicians and managers overcome the demanding challenges they face
    each day? Interoperability is not the answer; it is simply a buzzword that has been used too often,
    and for too long.
    What healthcare facilities truly need is realistic integration and sustainable data quality throughout
    their entire health information system.
    Healthcare organizations are under constant pressure to improve quality of care without adding
    staff or increasing expenditures. The current challenge is to slash departmental budgets by at least
    10 percent – without causing staff attrition or negatively impacting patient services.
    How can this be achieved? More efficient and intelligent use of the various information systems
    that exist across the environment can enable healthcare organizations to improve services without
    increasing staff or expenditures. Matching, merging, and creating a single “golden record” for each
    patient allows healthcare organizations to enrich the patient’s journey to recovery by proactively
    leveraging timely, accurate, and complete data for real-time decision-making at the point of service.

    See publication

Courses

  • ATLS - Providers Course

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  • EMS - Association Bronze Commander Course

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  • EMS - Emergency Ambulance Driving

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  • EMS - Emergency Medical Technician

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  • EMS - Paramedic

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  • EMS - Special Response Training USRP

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  • Health Protection Agency Chemical Incident Response Training

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  • Reserve Army Trauma Training

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  • Royal College of Edinburgh Surgeons Entrapment Training

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Projects

  • Cyber Security & Governance

    • Cyber Security & Governance – Currently designing a system to analyze network traffic patterns and user behavioral patterns to ensure data breaches are detected and patient & employee data is secure.

  • Data Quality

    • Data Quality – Successfully recouped $20m of lost capitation revenue after deployment of successful 3-month data quality initiative, allowing patient re-engagement at the point of care. Data enrichment process included multiple sets of algorithms to enrich and standardize the patient population data.

  • Financial savings

    • Financial savings – Developing the automation of data management in my current role has saved in one department alone $1.8m pa in the removal of manual and duplicate data acquisition and report preparation, resulting in the increased efficiency of operational staff. Through the development of an Enterprise Information Management solution, the data acquisition process has been automated and managed through Mastered Data Management. This has populated a single version of truth repository and…

    • Financial savings – Developing the automation of data management in my current role has saved in one department alone $1.8m pa in the removal of manual and duplicate data acquisition and report preparation, resulting in the increased efficiency of operational staff. Through the development of an Enterprise Information Management solution, the data acquisition process has been automated and managed through Mastered Data Management. This has populated a single version of truth repository and automated managed reports.

  • Procurement & Compliance

    • Procurement & Compliance – Led recent project to purchase Enterprise Data Management & Analytics platform requiring the identification and evaluation of leading vendors in Enterprise Information Management, with an expected spend of $10m. Prepared vendor functionality and elimination process. Contract negotiations allowed project to fall within budget, saving $4m in consolidation of technology and infrastructure within first 6 months.

  • Innovation

    • Innovation – Recognized success in initial trials and accountable for on-going design & development of Department of Health project to introduce Electronic Patient Report Forms within the UK NHS. Highly complex project with multiple moving parts which required the smooth coordination of work streams, vendors and project deliverables. Project led to improved post and pre acute care within UK NHS and navigated patients more effectively through pathways of care.

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