Improving population health begins with focusing on the health of each on of your patients. To do so, we in the healthcare community – nurses and physicians alike, need to identify and engage patients (particularly high-risk patients) throughout the continuum of care. These are the individuals most likely to be readmitted, miss an appointment, skip medications or who may not be able to pay their bill. 
How can we pinpoint these individuals quickly and easily when on the nursing floor, we’re often looking at multiple and databases and EMRs, examining enormous quantities of (unstructured) data – multiple note fields, physician notes, nurses’ notes, pathology reports, radiology notes, admission notes – all entered at different times, in different ways by different people? All of these fields include invaluable, information about a patient’s history including diagnosis, family history, complaints, observations and statistics. 
Standard EMR systems do not presently provide an easy way to synthesize and summarize patient information on the changing risk factors recorded in different EMR’s to support clinical decision-making. In addition, EMRs do not capture all the data points to understand the risks patients face, nor does it prioritize the care for those that are high risk for readmissions or infections.
Imagine then how far ahead and how much we could do to identify, treat and engage patients if we had a way to analyze unstructured data!
The primary benefit is a much fuller, cohesive picture of the patient’s history, diagnosis, treatment, and outcome. If details around the pathology of a patient’s tumor are only recorded within the pathology note for example, then analysis cannot include such things as genomics, margin reports, laterality, size, shape or even perhaps the stage of the tumor. Including that information along with trends for an individual patient or an entire population could be extremely value. Additionally, combining that information with data about the treatment and outcome of a patient, possibly available within textual notes fields, can provide a rich field for research and then results driven treatment.
As such, we thrive to compile, and where applicable translate better data from hospitals, preferably electronically. Through our system (CRM, technology and software), we are able to identify patients at high risk of readmission and
hospitalization using solutions that look at combination of clinical and 3rd party data to identify at-risk patients. We can put in place standard care plans so everyone on the team knows the steps that they should be taking to manage the patients. The CRM also allows our partners to reach out to patients, using our Iris platform after they have left the nursing facility and document the follow up care to provide them resources as needed.
All in all the benefits extend beyond medical issues to address, to the extent possible, how patients’ psychosocial circumstances affect their ability to follow treatment recommendations and achieve a healthy lifestyle. The goals are to maintain or improve patients’ functional status, increase their capacity to self-manage their condition, eliminate unnecessary clinical testing, and reduce the need for acute care services.
The result? Fewer nursing visits, shorter hospital stays, better intra-office communication, faster and more efficient communication between primary physician and nursing facilities; and also cost savings that could pay for the expansion of EMR use in those facilities. 
Benefits of integrated care management, leveraged by data/analytics helps nursing home administrators to:
 
  1. Identify and engage patients who are at high risk for poor outcomes and unnecessary intervention
  2. Perform comprehensive health assessments to identify problems that, if addressed through effective interventions, will improve care and reduce the need for expensive services
  3. Working closely with patients and their caregivers as well primary care, specialty, behavioral health, and social service providers.
  4. Rapidly and effectively respond to changes in patients’ conditions to avoid use of unnecessary services, particularly emergency department visits or hospitalizations
  5. Show their hospital partner they can do good follow-up care
  6. Have an integrated system that combines use of risk prediction software, chronic disease criteria, or utilization thresholds with patient/provider referrals or assessments.
  7. Provides Well-validated system for identifying a subset of high-risk patients
  8. Provides the most complete picture of expenditures
  9. Identifies a high-risk population at a time of significant need and opportunity for impact
  10. Combines the strengths of all the quantitative approaches and brings data together from multiple sources (including qualitative assessments)
  11. Takes advantage of the strengths of different approaches
 Jas Grewal is the CEO of CareSkore.