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Redmond Fire & Rescue Community Paramedicine

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Presentation on theme: "Redmond Fire & Rescue Community Paramedicine"— Presentation transcript:

1 Redmond Fire & Rescue Community Paramedicine

2 RF&R Goals Meet the Triple Aim (improve outcomes, increase patient satisfaction, reduce costs) Reduce ambulance rides and ER visits (admissions/readmissions) Measurable Data Prevention

3 Community Paramedicine
Community Paramedic (CP) model: Innovative solution providing quality primary care and preventative services by employing a currently available and often underutilized healthcare resource for vulnerable populations Specialty of paramedicine Flight paramedics Tactical paramedics Community paramedics

4 New Environment Performance based payments CCO’s—global payments
Aligned incentives and risk sharing

5 Role of the Community Paramedic
Collaboration: Public Health, Home Health, Nursing, etc. Assessing and evaluating community services and systems to identify gaps between the community and health care system and services Serve as direct care in home, advocates, facilitators, liaisons, and resource coordinators

6 RF&R CP Program Transformation Grant $182,000 Dispositions: CHF
Diabetes COPD 911 frequent callers Operate outside of the 911 system

7 Entry point Referrals: May result in a unified home visit Physicians
ER and RN navigation coordinators Home health services Other health care professionals May result in a unified home visit

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10 Project Evaluation The Community Paramedicine program served patients in Central Oregon starting 7/1/2014 and ending 6/30/2015. We used de-identified claims data to determine whether the CP program resulted in two outcomes; Among intervention patients, compared to a similar group of patients not receiving the intervention, were there fewer 1) Emergency Department visits 2) Ambulance Rides

11 Population for Evaluation
Intervention Group (Cases). The Intervention = Providers in the region referred patients to the Community Paramedic for an encounter and in-home health assessment. The CP saw 55 patients ranging in age from 27 to 78 years of age. 63.6% of the patients were female. Claims data were requested for all 55 patients seen by the CP, however, a complete data set was available for 45 patients. Comparison Group (Controls). Claims data were requested on PS members – targeting at least 5 per case – who were matched to the cases on age, gender, Central Oregon residence and primary chronic health condition. 45 control observations = 432 individuals. On average, there were 9.6 controls matched to each case.

12 Intervention Patients were heavier Ambulance and ED Utilizers than Controls, but…
Differences in mean Ambulance Rides and Emergency Department Visits by Group at pre and post intervention Pre-Intervention (-210 days) Mean (SD) Post-Intervention (+210 days) Post-Pre change Mean (SD) and p-value for pre to post difference Ambulance Rides Emergency Dept. Visits Intervention (N=45) 1.04 (1.90) 4.27 (5.54) 0.44 (1.14) 3.26 (5.68) -0.65 (2.03) 0.04 -1.14 (5.64) 0.19 Control (N=45 sets) 0.18 (0.32) 0.82 (0.55) 0.12 (0.26) 0.48 (0.49) 0.06 (0.21) 0.06 -0.34 (0.49) <0.0001 Mean (SD) and p-value for intervention-control difference 0.87 (1.38) 0.004 3.45 (3.94) 0.0001 0.33 (0.82) 0.07 2.78 (3.99) 0.003 0.59 (1.43) 0.80 (3.96) 0.36 …there was a larger, though not statistically significant, decrease in both ED visits and ambulance rides from pre to post among intervention patients than controls

13 When the reduction in ED visits were categorized into 4 groups (smallest reduction<=0.09 to largest reduction >0.6)… * chi-square difference between cases and controls p< … there was a significant difference between intervention and control, with a much higher percent of intervention patients experiencing the greatest reduction in visits.

14 Was there a cost savings?
Pre-Intervention Ambulance Rides (-210 days) Pre-Intervention Emergency Dept. Visits (-210 days) Post-Intervention Ambulance Rides (+210 days) Post-Intervention Emergency Dept. Visits (+210 days) Counts 47 185 19 140 Counts per patient per 30d period 0.18 0.69 0.09 0.66 Count Reduction, Pre/Post-Intervention (%) 49.14 4.78 Costs $17,743.91 $76,781.14 $7,656.75 $54,306.35 Cost per patient per 30d period $66.21 $286.50 $35.95 $254.96 Cost Reduction, Pre/Post-Intervention (%) 45.7 11.0 For patients seen by the Community Paramedic, there was 46% savings for ambulance rides and 11% savings for ED visits per patient per 30 day period. (*No admissions/readmission data)

15 Impact Positive for Patient and Provider
Patient may not have a good understanding of post discharge instructions or the health care plan I.e. CP provides in home care and medication administration/reconciliation Case Story: 3 days post discharge, IDDM Diet Duplicate medications Post discharge instructions

16 Surveys Questions Excellent Very Good Good Fair Poor 1 The paramedic arrived on time or called to inform me if they were running late 14 3 2 The paramedic treated me with courtesy and respect 15 The paramedic explained to me the care I was receiving 4 The paramedic showed concern for my condition 5 The paramedic included me in making decisions about the care I received 6 The paramedic's volume when speaking was appropriate 7 The paramedic spent enough time that I did not feel like our home visit was rushed 8 The paramedic showed confidence in the skills they were performing 9 The paramedic listened and understood what I was saying 10 I better understand my health condition and/or medication schedule because of this home visit 13 11 I better understand how my lifestyle affects my health condition 12 Based upon the visit today, how valuable do you think this program is? Total Mean responses based upon 17 surveys 2.75

17 Summary Has, and can continue to have, significant reduction in healthcare costs and improved patient satisfaction and outcomes Has ability to reach many more populations due to access Patient Requests to Pay! Potential to help many disciplines (ortho, behavioral health)

18 Thank you St. Charles Medical Center
Pacific Source Community Solutions Mosaic Medical CORC for data analytics And many others!


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