Download - big data and healthcare management
BIG DATA & HEALTHCARE
Tahereh SahebphD in Science Technology Studies, NY, USAssistant Professor at Tarbiat Modares UniversitySpJain School of Global Management, [email protected]
بیگ دیتا: کشف الگوها، پیش بینی آینده و ارایه تحلیل های تجویزی
US Companies spend millions of dollars on health competitions to innovate modern analytical solutions for the healthcare
industry
WHY THE ROLE OF BIG DATA IS INCREASING ON HEALTHCARE INDUSTRY
• Additional Data Sources Development of new technologies such as capturing devices, sensors, and mobile applications. Collection of genomic information became cheaper. Patient social communications in digital forms are increasing. More medical knowledge/discoveries are being accumulated
INTERNET OF MEDICAL THINGS ( IOMT)Examples of IoMT include• remote patient monitoring of people
with chronic or long-term conditions; • tracking patient's prescriptions• and the location of patients
admitted to hospitals; patients' wearable mHealth devices, which can send information to caregivers.
The Spyder ECG System incorporates the worlds' smallest wearable continuos ECG sensor and is
designed to replace traditional remote ECG devices such as the Holter ECG, Trans-telephonic
ECG and Implantable loop recorders, utilizing ubiquitous ‘Digital Health’ Info-Comm Technology
platforms .
SOURCES OF BIG DATA IN HEALTH CARE:1-CLINICAL INFORMATION SYSTEMS
) a Electronic ( )health records EHRs collect, store, and display data and information related to a patient.Major types of information in the EHR include:
• Demographics (e.g. age, date of birth, gender)• Contact information (e.g. phone number, address)• Past medical history• Active medical problems• Immunizations• Allergies • Medications• Vital signs• Results from laboratory and radiology tests• Progress notes (narrative description of the patient's
status, diagnoses, tests, and treatments)• Administrative and financial documents
b) Health information exchanges serve as hubs between disparate clinical information systems.Health information exchange (HIE) is the secure electronic exchange of health information among otherwise disconnected health care organizations.
Hospitals, clinics, pharmacies, and lab facilities can be connected by HIE at the regional, state, or national level.
When is HIE useful?• Patient is transferred from one hospital to
another• Patient is sent to the emergency department
after having tests done in a clinic• Patient is discharged from a hospital and
then follows up in a clinic• Patient moves across town and finds a new
primary care provider
) c Patient registries :A disease registry is a special database that contains information about people diagnosed with a specific type of disease
Patient Registries
TYPES OF REGISTRIES
• Disease registries include patients with the same disease (e.g. diabetes). Registries exist now for common medical conditions as well as rare ones.
• Health services registries are defined by patients who have had the same procedure (e.g. hernia surgery), hospitalization, or other clinical encounter
• Product registries track patients who have been exposed to a certain drug, vaccine, or medical device
Common reasons for using a patient registry are:
•Monitor health status of defined populations•Facilitate disease management, such as by identifying patients with warning signs•Understand variations in treatment and outcomes •Observe the natural history of a disease•Evaluate clinical effectiveness or cost effectiveness of health care products and services•Measure quality of health care•Monitor safety or harm•Public health surveillance
PATIENT PORTALS• Patient portals A patient portal is an online application which gives patients access to personal health information stored in a health care organization’s electronic health record (EHR).
• Some patient portals also allow users to request prescription refills and exchange secure electronic messages with the health care team.
CLINICAL DATA WAREHOUSE
• In 2005, Boston Medical Center started this project.
•A Clinical Data Warehouse (CDW) is a real time database that consolidates data from a variety of clinical sources to present a unified view of a single patient
DEVICES
• Smartphones: Thousands of mHealth apps capture information on the user’s physical activity, nutritional intake, sleep patterns, emotions, and other parameters. Native cell phone apps (e.g. GPS, email, texting) can also give clues about an individual’s health status.
• Wearable monitors and devices: Pedometers, accelerometers, glasses, watches, and chips embedded under the skin also gather health-related information.
• Telemedicine devices allow health care providers to monitor patients’ parameters such as blood pressure, heart rate, respiratory rate, oxygenation, temperature, ECG tracings, and weight.
5 WAYS HEALTHCARE DATA IS DIFFERENT
1 .MUCH OF THE DATA IS IN MULTIPLE PLACES
• Healthcare data tends to reside in multiple places.
From different source systems, like EMRs or HR software, to different departments, like radiology or pharmacy. The data comes from all over the organization. Aggregating this data into a single, central system, such as an enterprise data warehouse (EDW), makes this data accessible and actionable.
2-THE DATA IS STRUCTURED AND UNSTRUCTURED
3-INCONSISTENT/VARIABLE DEFINITIONS; EVIDENCE-BASED PRACTICE AND NEW RESEARCH IS COMING OUT EVERY DAY.
• Oftentimes, healthcare data can have inconsistent or variable definitions.
For example, one group of clinicians may define a cohort of asthmatic patients differently than another group of clinicians. Ask two clinicians what criteria are necessary to identify someone as a diabetic and you may get three different answers. There may just not be a level of consensus about a particular treatment or cohort definition.
4-THE DATA IS COMPLEX
• We are looking at an amalgam of individual systems that are so complex we don’t even begin to profess we understand how they work together (that is to say, the human body).
• Managing the data related to each of those systems (which is often being captured in disparate applications), and turning it into something usable across a population, requires a far more sophisticated set of tools than is needed for other industries like manufacturing.
5 .CHANGING REGULATORY REQUIREMENTS
• Regulatory and reporting requirements also continue to increase and evolve.
They developed an open-source modeling
application dubbed the Spatio Temporal
Epidemiological Modeler (STEM) that
allows any kind of data to be quickly combined
and correlated with disease data.
• Experts from Facebook and genetics labs team up to help doctors make personalized predictions about their patients.
• The goal is to replace the general guidelines doctors often use in deciding how to treat diabetics.
• Instead, new risk models—powered by genomics, lab tests, billing records, and demographics—could make up-to-date predictions about the individual patient a doctor is seeing
Personalized predictions
• Validic is a cloud-based technology platform that connects patient-recorded data from digital health applications, devices and wearables to key healthcare companies like hospital systems, providers, pharmaceutical companies, payers, health information technology platforms, health clubs and wellness companies.
• With access to this information, Validic’s clients can accelerate their strategic healthcare initiatives — from patient engagement and population management to care coordination, wellness programs and more
PRACTICE FUSION: THE LARGEST CLOUD-BASED ELECTRONIC HEALTH RECORDS
(EHR) PLATFORM IN THE U.S.
• is a real-time healthcare database based upon records of over 250K patients per day.
• You’ll be able to see information like disease trends over time and by patient, what diseases are being diagnosed.
Conclusion:
Provide right intervention to the right patient at the right time.
Personalized care to the patientPotentially benefit all the components of a healthcare systemi.e., provider, payer, patient, and management.
Benefits of big data
