In Touch EMR Analytics Overview & Improvements

Administration > Analytics > Patient Analysis

When you upgrade to In Touch EMR analytics, you can take advantage of insight into the following categories:

1. Patient Analysis
2. Staff Productivity
3. Clinic Comparator
4. Revenue Predictor

Most of these components can be filtered by:

– Providers
– Clinics
– Time Frame

For patient analysis, the following are represented in visual charts:

1. Email Reach
2. Cellphone Reach
3. Insurance Spread
4. Demographic Distribution
5. Gender Distribution

 

With In Touch EMR analytics, you will be able to get insight (and recommendations) on the following:
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1. The percentage of patients with valid email addresses.
2. The percentage of patients with an insurance company on file.
3. The age distribution of your patients.
4. The gender distribution of your patients.
5. The total number of scheduled patients visits in a particular period.
6. The total number of documented patients visits in a particular period.
7. The completion factor – a ratio calculated when the total documented visits are divided by the total scheduled visits in a given time period.
8. The number of new patients in a given time period
9. The number of visits with a ‘cancelled’ status in a given time period, for selected clinicians and selected clinics.
10. The cancellation factor – a ratio calculated when the total number of cancelled visits are divided by the total number of scheduled visits in a given time period.
11. The number of visits with a ‘no show’ status in a given time period, for selected clinicians and selected clinics.
12. The no show factor, also a ratio – calculated when the total number of no show visits are divided by the total number of scheduled visits in a given time period.
13. Appointment analysis – a detailed breakdown of the various statuses (new, cancel, no show, in progress and finalized) for the ‘total scheduled visits’.
14. Documents in progress analysis – a detailed breakdown of the various statuses for the ‘total documented visits’. This includes documents in progress and finalized documents.
15. Finalized documents analysis – a detailed breakdown of the various statuses for the ‘finalized visits’.
16. Payer visit breakdown – a breakdown of dependence (and dominance) of certain payers in your patient population.
17. Payer variance – the number of scheduled visits, and the associated payors, over a period of time.
18. Dominant ICD codes (physician diagnosis) – the number of instances that particular ICD code has been assigned to a patient visit in In Touch EMR.
19. Dominant ICD codes (treatment diagnosis) – the number of instances that particular ICD code has been assigned to a patient visit in In Touch EMR by the clinician / therapist 
treating the patient.
20. Dominant CPT codes (procedure codes) – the number of instances that particular procedure code has been assigned to a patient visit in In Touch EMR by the clinician / therapist 
treating the patient.
21. Referral predictor – the number of initial evaluations created over a period of time. It provides an indicator of how many new patients / referrals were seen by a certain number of 
clinicians / clinics over a period of time.
22. Productivity predictor – the number of visits scheduled over a period of time.
23. Referral source summary – the number of referred patients from all the available referral sources over a period of time.
24. Payer macroview – a high level overview of the payer mix of the entire patient population over a period of time.
25. Improvements for Analytics
26. Improved BMI Calculation

Administration > Analytics > Patient Analysis

For patient analysis, the following are represented in visual charts:

1. Email Reach
2. Cellphone Reach
3. Insurance Spread
4. Demographic Distribution
5. Gender Distribution

 

PLEASE CLICK ON THE IMAGE BELOW TO EXPAND

Administration > Analytics > Email Reach

Administration > Analytics > Cellphone Reach

Administration > Analytics > Insurance Spread

Administration > Analytics > Demographic Distribution

Administration > Analytics > Gender Distribution

Administration > Analytics > Staff Productivity

1 – All charts can be filtered over a 7 day, 30 day, 90 day or a custom period.

2 – Components in red indicate an upward trend, and components in green indicate a downward trend as compared to the previous reporting period.

For example, in the chart below, note that the total scheduled visits in the current 7-day period (12/ 20/14 to 12/26/14) are down by 27% compared to the 7-day period immediately preceding 12/20/14.

This gives the clinic an unprecented level of insight into growth and productivity.

Administration > Analytics > Staff Productivity (continued)

Administration > Analytics > Total Scheduled Visits

1 – These metrics can be broken down for one or all of your providers

2 – These metrics can be broken down for one or all clinics

3 – These metrics can also be further broken down over 7 days, 30 days, 90 days or a custom date range.

4 – This comparator tool shows you whether there is an upward or a downward trend over the corresponding period in the past.

Administration > Analytics > Total Documented Visits

Administration > Analytics > Documentation Factor

Administration > Analytics > New Patients

Administration > Analytics > Cancellations

Administration > Analytics > Cancellation Factor

Administration > Analytics > Cancellation Factor

Administration > Analytics > No Shows

Administration > Analytics > No Show Factor

Administration > Analytics > Appointment Analysis

Administration > Analytics > Documents in Progress Analysis

Administration > Analytics > Finalized Documents Analysis

Administration > Analytics > Clinic Comparator

Administration > Analytics > Revenue Predictor > Payer VisitBreakdown

Administration > Analytics > Revenue Predictor > PayerVariance

Administration > Analytics > Revenue Predictor > Dominant ICD Codes (Physician Diagnosis)

Administration > Analytics > Revenue Predictor > DominantICD Codes (Treatment Diagnosis)

Administration > Analytics > Revenue Predictor > DominantCPT Codes

Administration > Analytics > Revenue Predictor > ReferralPredictor

Administration > Analytics > Revenue Predictor > ProductivityPredictor

Administration > Analytics > Revenue Predictor > ReferralSource Summary

Administration > Analytics > Revenue Predictor > PayorMacroview

Improvements to Analytics

Significant speed improvements to analytics including custom date selection

– Ability to export results in PDF and excel file format.

Improved BMI calculation