understanding and identifying target populations for system improvement virtual ward. july 2, 2010
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Understanding and Identifying Target Populations for System Improvement Virtual Ward. July 2, 2010 W.Wodchis, X.Camacho, I. Dhalla, A. Guttman, E.Lin, G.Anderson. - PowerPoint PPT PresentationTRANSCRIPT
1Leveraging the Culture of Performance Excellence in Ontario’s Health
SystemHSPRN is an inter-organization Network funded by the Ontario Ministry of Health and Long Term Care
Understanding and Identifying Target Populations for System Improvement
Virtual Ward. July 2, 2010
W.Wodchis, X.Camacho, I. Dhalla, A. Guttman, E.Lin, G.Anderson
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Target Populations for System Improvement
Populations with high health utilization rates who move from one sector of the health care system (e.g. acute) to another (e.g. community) may represent opportunities to improve quality and reduce costs – primarily by reducing adverse events and preventing acute hospital readmission.
While quality of care within providers is being enhanced by performance measurement and reporting, payment incentives and quality improvement programs…
Care transitions between providers are fraught with lack of coordination, poor communication, safety issues related to medication management...etc,etc.
Example System Improvement Interventions
Care for Complex Patients
e.g.Rich et al., (NEJM 1995) RCT of nurse-directed intervention for CHF
90 day Risk of Readmission = 0.56
Naylor et al., (NEJM 1995) RCT of Advanced Practice Nurse-lead intervention including coordination with primary care physician for CHF
1-year Readmissions in intervention group = 1.18/patient vs 1.79 in control
Coleman et al., (AIM, 2006) RCT of APN-lead intervention for select conditions
90-day Readmissions in intervention group = 16.7% vs. 22.5% (Odds=0.64)
Common components of these interventions: 1. Case management (including discharge planning)2. Follow-up care in home (24-72 hours)3. Medication management / reconciliation4. Patient education/empowerment (Rich, Coleman) e.g. Patient
personal health record
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Target Populations for System Improvement
Purpose for our study: 1. Identify the Ontario prevalence of
populations that have been included in prior transition interventions.
2. Examine the treatment and follow-up patterns of care for these patients.
3. Examine the relationship between follow-up care (as suggested by interventions) and patient outcomes (hospital readmission) in the Ontario population cohort.
4. Examine health system costs associated with total 1- year care for this population.
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Target Populations for System Improvement
What we’ve done: 1. Identify community-based cohort of clients aged 66+
based on Acute care discharge (April 2006-March 2007) with :
1. 2 or more ACSC conditions (Angina, Asthma, COPD, Diabetes, Grand
Mal Seizure, Heart Failure, Hypertension) or any one of the following ‘tracer’ conditions: Stroke, Cardiac Arrhythmia, Spinal Stenosis, Hip Fracture, Peripheral Vascular Disease, Deep Vein Thrombosis or Pulmonary Embolism
Follow for 365 days (until March 2008)1. Describe characteristics of the patients2. Examine readmission rates to Acute Inpatient Care3. Examine relationship between follow-up and readmission4. Understand system utilization and costs
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Target Populations for System Improvement
Data Sources for Ontario, Canada:
1. Canadian Institute for Health Information (CIHI) Discharge Abstract Database.
2. Ontario Health Insurance Program Physician Billing
3. Ontario Home Care Database (service claims)
4. Ontario Drug Benefit Pharmacy Claims
5. Other hospital service databases (Emergency, Rehabilitation, Complex Continuing Care Long Term Care)
Data available at the Institute for Clinical Evaluative Sciences.
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Target Populations for System Improvement
Acute Diagnosis Prevalence
Cardiac Arrhythmia 14,976 38.4%
Stroke 8,707 22.3%
ACSC (>1 diagnosis) 7,351 18.9%
Hip Fracture 5,749 14.7%
DVT/PE 1,887 4.8%
PVD 1,634 4.2%
Spinal Stenosis 1,418 3.6%
Total 38,978
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Target Populations for System Improvement
Summary Characteristics:
Average Age: 79
Slightly more women (56%) except Hip Fracture (75% women)
Average number of medications in prior year = 11 ACSC Average=14.4 and 25% with 19 or more
28% with new medication within 30 days prior to index hospitalization (35% for ACSC conditions)
88% have a Regular family physician
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Target Populations for System Improvement
Post-acute follow-up care:
• 39% receive home care within 30 days 21% within one day and 25% within 3 days
• 18% receive home nursing visit within 30 days 9% within one day and 12% within 3 days
• 52% receive primary care within 30 days 25% within 7 days
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Target Populations for System Improvement
Outcomes : 16,605 (43%) discharged to community 17,727 (45%) discharged to other health care institution 4,646 (12%) died during initial hospitalization
Among 16,605 discharged to community@ 30 days
23.4% have ED visit 12.8% readmitted to acute care 3.2% dead
@ 90 days 38.0% have ED visit 22.2% readmitted to acute care 7.3% dead
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Target Populations for System Improvement
(Among 16,605 discharged to community)
Examine likelihood of readmission to acute care within 7-30 days and 7-90 days
associated with: 1. Home care nursing visit (show 1 day vs 3 days)
2. Primary care visit (show <7 days vs >7 days)
(controlling for host of risk factors using logistic regression - 51 covariates).
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Target Populations for System Improvement
Risk of Readmission to Inpatient Acute Care
Independent Variable
7-30 daysAdj. Odds Ratio* (95% Confidence Interval)
7-90 daysAdj. Odds Ratio* (95% Confidence Interval)
Home Nursing Visit within 1 day
(vs 2-3 days)
0.72ł
(0.53, 0.98)0.70ł
(0.55, 0.90)
Primary Care Visit within 7 days
0.91 (0.81, 1.03)
0.85ł (0.78, 0.93)
New Filled Prescription
1.07ł (1.04, 1.10)
1.04ł (1.01, 1.06)
* Adjusted for 51 measures of patient characteristics, prior medical treatment, diagnoses and geography
Ł significant at the 5% level
Population Discharged to Community n = 16,605
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Target Populations for System Improvement
Summarize Utilization and Costs in 365 days following acute discharge:
• Index Hospitalization (Hospital and Physician Cost)• Subsequent:
Acute Hospital Care (Hospital and Physician Cost) Rehabilitation Hospital CCC: Complex Continuing Care Hospital LTC: Long Term Care Facility HC: Home Care Primary and Specialist Physician care Pharmaceutical (Ontario Drug Benefit - ODB) ED: Emergency Department (Hospital and Physician
Cost)
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Target Populations for System Improvement
Summarize Utilization and Costs in 365 days following acute discharge:
• Total Population 38,978 (0.3% population)
• Average Annual Cost $35,935
• System Cost $1,400,689,862 (3% system cost)
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Target Populations for System Improvement
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Target Populations for System Improvement
Summary1. This example population presents significant
opportunities for improvement by increasing access to nurse visit at home within one day and physician visit within one week. (and medication reconciliation)
2. Value-proposition: Data represent baseline system cost for evaluating interventions.(e.g. preventing 785 (5%) of readmissions would ‘free-up’ $14,106,792 in acute care costs; provincial target of 30% =$210 Million)
Research in Progress: 1. Further examination of subsequent transitions in health
system.2. Other target populations: A. Adult Mental Health and B.
Complex Paediatric Populations.
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What Can We Work On ? e.g. Integration and Transitions of Care
Acute
LTC
Rehab / CCC / Sub-acute Care
Community
Urgent / ED Care
Patient Flow
Patient Rebound
Primary - Specialist
Home Care
Pharma
e.g. Elderly: Home Care, Primary Care
and Medication Management
e.g. Elderly: Home Care, Primary Care
and Medication Management
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Desired GoalBetter Transitions of Care
Acute
LTC
Rehab / CCC / Sub-acute Care
Community
Urgent / ED Care
Patient Flow
Patient Rebound
Primary - Specialist
Home Care
Pharma
e.g. Elderly: Home Care, Primary Care
and Medication Management
e.g. Elderly: Home Care, Primary Care
and Medication Management
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TransitionsOntario >66 discharged with 2+ ACSC;
2006-08
Acute
Died Rehab / CCC / Sub-acute Care
CommunityLTC
Initial transition after acute care
discharge.
Initial transition after acute care
discharge.n=5,648
N=576n=805
n=213
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TransitionsOntario >66 discharged with 2+ ACSC;
2006-08
Acute
Died Rehab / CCC / Sub-acute Care
CommunityLTC
Initial transition after acute care
discharge.
Initial transition after acute care
discharge.n=5,648
N=576n=805
n=213
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TransitionsOntario >66 discharged with 2+ ACSC;
2006-08
Acute
Died Rehab / CCC / Sub-acute Care
CommunityN=1,538
LTC
N=5,648
n=19
n=620
n=82
First 2 transitions after
acute care discharge 1-year
follow-up.
First 2 transitions after
acute care discharge 1-year
follow-up.n = 3,381
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TransitionsOntario >66 discharged with 2+ ACSC;
2006-08
Acute
Died Rehab / CCC / Sub-acute Care
CommunityN=1,538
LTC
N=5,648
n=19
n=620
n=82
First 2 transitions after
acute care discharge 1-year
follow-up.
First 2 transitions after
acute care discharge 1-year
follow-up.n = 3,381
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Selected 1-year post-discharge visits
Measure Community ReadmitNumber of Primary Care Visits Median [Q25 – Q75]
15 [9-24] 29 [17-47]
Number of Specialist Visits 17 [8-30] 45 [22-77]
6 or more Different Physicians20 or more Different Physicians
70%4%
96%44%
4 or more Different Pharmacies 10% 15%
2 or more ED visits 20% 73%
2+ Acute Readmissions 0 54%
2+ Post-acute institutions 0 4%
Total Number of Provider Visits
46 [30-78] 126 [75-204]
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Target Populations for System Improvement
1. Populations that have high health utilization rates and that move from one sector to another have important implications for both the costs and quality of care.
2. These populations are of interest because they may represent opportunities both to improve the quality and reduce the burden and costs on the health care system.
3. There are opportunities for improvement and we should be able to track performance improvements.
What we know about Performance
Carl van Walraven (2008):
• 3250 patients with 39,469 previous-current visit combinations (12 per patient) in 6 months after discharge.
• Information about the previous visit was available 22% of the time.
…We could improve
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