Posts Tagged ‘clinical data’

Infographic: Unlock Your Data To Optimize Your EMR

June 6th, 2018 by Melanie Matthews

As healthcare shifts from volume to value, imaging clinicians need intelligent solutions that help them leverage the data available in the EMR at the point of care for faster, more accurate diagnoses, according to a new infographic by Change Healthcare.

The infographic examines how to mine clinical information and leverage it in a way that provides more efficient care.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results Between Medicare’s aggressive migration to value-based payment models and MACRA’s 2017 Quality Payment Program rollout, healthcare providers must accept the inevitability of participation in fee-for-quality reimbursement design—as well as cultivating a grounding in health data analytics to enhance success.

As an early adopter of the Medicare Shared Savings Program (MSSP) and the largest sponsor of MSSP accountable care organizations (ACOs), Collaborative Health Systems (CHS) is uniquely positioned to advise providers on the benefits of data analytics and technology, which CHS views as a major driver in its achievements in the MSSP arena. In performance year 2014, nine of CHS’s 24 MSSP ACOs generated savings and received payments of almost $27 million.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results examines program goals, platforms, components, development strategies, target populations and health conditions, patient engagement metrics, results and challenges reported by more than 100 healthcare organizations responding to the February 2016 Digital Health survey by the Healthcare Intelligence Network.

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Infographic: Managing Medical Data on a Blockchain

July 19th, 2017 by Melanie Matthews

Shared infrastructure for information exchange via a blockchain in healthcare can eliminate duplication of healthcare services among treating physicians and improve care coordination, according to a new infographic by Gem.

The infographic demonstrates how the blockchain is used as a common registry for medical records between providers.

Remote Patient Monitoring for Chronic Condition Management: Leveraging Technology in a Value-Based System Encouraged by early success in coaching 23 patients to wellness at home via remote monitoring, CHRISTUS Health expanded its remote patient monitoring (RPM) enrollment to 170 high-risk, high-cost patients. At that scaling-up juncture, the challenge for CHRISTUS shifted to balancing its mission of keeping patients healthy and in their homes with maintaining revenue streams sufficient to keep its doors open in a largely fee-for-service environment.

Remote Patient Monitoring for Chronic Condition Management: Leveraging Technology in a Value-Based System chronicles the evolution of the CHRISTUS RPM pilot, which is framed around a Bluetooth®-enabled monitoring kit sent home with patients at hospital discharge.

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Infographic: The Power of Medical Device Data

March 11th, 2016 by Melanie Matthews

Healthcare organizations are recognizing the value of integrating medical device data for comprehensive and timely data analysis to drive informed clinical and operational decisions, according to an infographic by Capsule, a Qualcomm Life company.

The infographic highlights the power of a vendor-neutral medical device information system to go beyond sending data to an EMR by automating the capture and sorting of the voluminous amount of data gathered from medical devices. Then, through integration capabilities, specific data can be shared with other healthcare applications and systems for alarm notification, patient surveillance, clinical decision support, and even the management of the device assets themselves, helping to improve patient care.

As quality and value increasingly drive healthcare rewards, the generation, sharing and analysis of patient data is a prerequisite for organizations desiring to enhance clinical outcomes and drive down cost. Yet the burden of creating infrastructure to support health information management deters many payors and providers from fully engaging in a robust business intelligence strategy.

2016 Healthcare Benchmarks: Data Analytics and Integration examines the goals, data types, collection processes, program elements, challenges and successes shared by healthcare organizations responding to the January 2016 Data Analytics survey by the Healthcare Intelligence Network.

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Infographic: Where Are You on the Healthcare Analytics Journey?

October 26th, 2015 by Melanie Matthews

Where Are You on the Healthcare Analytics Journey?To be successful in the value-based care and population health management paradigm, healthcare organizations must be able to leverage data to drive better outcomes, improve the patient experience and create cost efficiencies, according to a new infographic by IBM.

The infographic drills down on five layers of data analytics, the type of data that is collected at each layer and the how that data can be used.

While widespread adoption of electronic health records has generated new streams of actionable patient data, John C. Lincoln has taken data mining to new levels to enhance performance of its accountable care organization (ACO).

Beyond the EMR: Mining Population Health Analytics to Elevate Accountable Care reviews the concentrated data dig undertaken by John C. Lincoln to prepare for participation in the CMS Medicare Shared Savings Program (MSSP).

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Infographic: Analytics in Healthcare

April 3rd, 2015 by Melanie Matthews

Analytics is clearly a top priority for healthcare decision-makers. In fact, according to CDW Healthcare’s recent Analytics in Healthcare Report, two-thirds of these decision makers say analytics is a top three priority — and for good reason. With the influx of data from electronic health records and health information exchanges, the healthcare industry is poised to see big benefits from clinical analytics.

A new infographic by CDW Healthcare looks at the demographic make-up of organizations using analytics, successful treatments based on analytical data, possible complications from using data analytics and where healthcare organizations expect to spend their analytics budget.

Beyond the EMR: Mining Population Health Analytics to Elevate Accountable CareWhile widespread adoption of electronic health records has generated new streams of actionable patient data, John C. Lincoln has taken data mining to new levels to enhance performance of its accountable care organization (ACO).

Beyond the EMR: Mining Population Health Analytics to Elevate Accountable Care reviews the concentrated data dig undertaken by John C. Lincoln to prepare for participation in the CMS Medicare Shared Savings Program (MSSP).

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11 Statistics about Stratifying High-Risk Patients

November 20th, 2014 by Cheryl Miller

Healthcare organizations use a range of tools and practices to identify and stratify high-risk, high-cost patients and determine appropriate interventions. Most critical to the stratification process is clinical patient data, say an overwhelming 87 percent of respondents to the Healthcare Intelligence Network’s (HIN) inaugural survey on Stratifying High-Risk Patients. However, obtaining and verifying patient data remain major challenges for many respondents. Following are 10 more statistics from our survey.

  • „„Hospital readmissions is the metric most favorably impacted by risk stratification tools, according to a majority of respondents.
  • „„In addition to high utilization, clinical diagnosis is considered a key factor in stratifying high-risk patients, according to 16 percent of respondents.
  • „„Case management as a post-stratification intervention is offered by 83 percent of respondents; health coaching by 56 percent.
  • Reducing heart failure (HF), pneumonia (PN), and atrial myocardial infarction (AMI) are among the greatest successes of risk stratification programs.
  • Diabetes is considered the prominent health condition among high-risk populations, according to 37 percent of respondents; other prominent conditions include hypertension (20 percent) and mental health/psychological issues (15 percent).
  • Physician referrals are cited by 76 percent of respondents as an important input for stratification, followed by case/care manager referrals (71 percent).
  • „„Home health and/or home visits are available to risk-stratified populations of 56 percent of respondents.
  • „„LACE (Length of stay, Acute admission, Charleston Comorbidity score, ED visits) is considered the primary indice and screen to assess health risk, according to 33 percent of respondents.
  • Nearly half of respondents (45 percent) cite high utilization of the emergency department (ED) or hospital as the most critical attribute of high-risk patients.
  • „„While more than half of respondents have a program in place to identify and risk-stratify complex cases, the majority admit it is too early to tell the ROI achieved.

Source: 2014 Healthcare Benchmarks: Stratifying High-Risk Patients

http://hin.3dcartstores.com/2014-Healthcare-Benchmarks-Stratifying-High-Risk-Patients_p_4963.html

2014 Healthcare Benchmarks: Stratifying High-Risk Patients captures the tools and practices employed by dozens of organizations in this prerequisite for care management and jumping-off point for population health improvement — data analytics that will ultimately enhance quality ratings and improve reimbursement in the industry’s value-focused climate.