How Population Health and Data Improve Quality-Care

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Nurse sitting at laptopCaregivers are implementing innovative technologies to improve population health. By combining data analysis technology with medical information, population health technology allows organizations to evaluate massive data repositories and discover previously unrecognized trends. Implementing the technology presents challenges, however, caregiving organizations press forward with their efforts to secure the tool.

The Focus on Population Health Emerges

Despite new legislation and recent technological breakthroughs, leading medical authorities understand that reshaping healthcare practices takes significant time. [1] The 2016 Healthcare Information and Management Systems Society (HIMSS) conference revolved around how healthcare reform is changing healthcare information technology (HIT); the mandatory shift in focus from quantity to quality is disrupting the caregiving landscape. While this transformation presents many challenges, it will eventually lead to better patient outcomes.

A New Way to Provide Care

Big data analysis capabilities have arrived at the prefect time to facilitate healthcare reform. Caregiving establishments – rather than increasing services to meet demand – are now focusing on improving population health to reduce required service levels. Population health proponents support this shift. However, industry leaders question whether healthcare organizations are truly ready for this transformation and admit that reshaping how the medical field delivers service will take considerable time.

Why Data Is Essential to Population Health

Medical practitioners are improving population health in the most challenging areas by exploiting innovative new technologies and medical practices. [2] To continue effective treatment, all caregiving organizations must participate in the information sharing networks made possible by technology and newly mandated healthcare reforms, but many caregiving organizations are still learning how to implement the tool. Care providers already exploiting the resource realize markedly better patient outcomes by combining and evaluating internal and external information sources to gain new insights into population health. For many of these organizations, this represents the first opportunity to examine such a large volume of quality patient data.

The Slow Adoption of Population Health Technology

Caregiving organizations are growing accustomed to population healthcare management, but many organizations have not updated their technological resources. [3] A 2015 poll conducted by HIMSS revealed 67 percent of member organizations practicing population management, yet only around 25 percent of the institutions have implemented technology to process population health analytics. Over 80 percent of the polled member organizations monitor and evaluate chronic conditions and wellness services in the community. Despite these practices, only a small percentage of the respondents have taken the first step toward implementing population management technology.

Data Analysis Implementation Roadblocks

Many organizations are unsure of how to evaluate and find population health technology solutions, especially among smaller caregiving organizations. With traditional electronic health record (EHR) providers now offering enhanced analytic functions, these organizations are having difficulty realizing the value of investing in a dedicated population management application and view the big data analytic capabilities offered by the new EHR platforms as sufficient.

The Public Health Debate

Data analysis technology is crucial for gathering information from scattered resources and producing positively actionable evaluations. [4] Caregivers record and share data from many sources, such as:

  • Appointment scheduling
  • Blood pressure readings
  • Body temperature readings
  • Facilities inspections
  • Income and expenses reports
  • Internal and external communications (email, fax and telephone)
  • Patient monitoring results
  • Physician-patient portals
  • Vital statistics registrars

How organizations improve community patient outcomes using these resources is the most discussed topic among healthcare leaders. However, how the technology performs generates heated debates over issues such as:

  • A lack of common medical terminology, goals and regulation
  • A lack of common HIT terminology
  • A lack of HIT data analysis expertise
  • A dispersed accountability for population health
  • Incompatibility issues among healthcare networks

These individuals warn caregiving organizations to consider these factors carefully to prevent negative outcomes.

Using Data Analytics to Improve Caregiving

A report published by the Centers for Disease Control (CDC) recognizes that community health is a growing national interest and acknowledges that new healthcare legislation places a heavy burden on organizations to improve patient outcomes while reengineering patient information management. [5] Healthcare organizations are willing to take short-term losses in exchange for long-term the benefits. However, organizations ready to implement population healthcare management technology do not have enough information. The medical community’s call for more implementation information is drawing attention among stakeholders. Although data driven healthcare is revolutionizing caregiving, transitioning to the resource presents a significant challenge. Despite this fact, healthcare leaders do not want to public to wait for improvements they can benefit from now. Population health information combined with data analysis platforms provides solutions to many challenging medical concerns. Health advocates warn about the danger of hasty implementation, but acknowledge the benefits provided by the resource. Nevertheless, the effect data analysis has on caregiving will only increase as universal healthcare and technology mature in unison.

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