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Name
High Users of Hospital Beds
Short/Other Names

High Users of Inpatient Acute Care Services or Rate of High Users

Description

The risk-adjusted rate of patients who had 3 or more inpatient acute care hospitalizations (episodes of care) with a cumulative length of stay (LOS) longer than 30 days (high users).

For further details, please see the FAQ: Understanding the High Users of Hospital Beds Indicator and the General Methodology Notes.

Interpretation
A lower rate is more desirable.
HSP Framework Dimension

Health System Outputs: Appropriate and effective

Areas of Need

Not applicable

Geographic Coverage

All provinces/territories

Reporting Level/Disaggregation

National, Province/Territory, Region

Indicator Results

Accessing Indicator Results on Your Health System: In Depth

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<div role="button" class="expandableTitle" aria-controls="identifyingInfoRegion">Identifying Information</div>
Name
High Users of Hospital Beds
Short/Other Names

High Users of Inpatient Acute Care Services or Rate of High Users


<div role="button" class="expandableTitle" aria-controls="descAndCalRegion">Indicator Description and Calculation</div>
Description

The risk-adjusted rate of patients who had 3 or more inpatient acute care hospitalizations (episodes of care) with a cumulative length of stay (LOS) longer than 30 days (high users).

For further details, please see the FAQ: Understanding the High Users of Hospital Beds Indicator and the General Methodology Notes.

Calculation: Description

The risk-adjusted rate of high users of inpatient acute care services is calculated by dividing the number of high users (patients with multiple episodes of care in a 1-year period and a cumulative length of stay greater than 30 days) in each region by the expected number of high users in the region and multiplying by the Canadian average high users rate.

Unit of analysis: Patients

Calculation: Geographic Assignment

Place of residence

Calculation: Type of Measurement

Rate - Rate per 100

Calculation: Adjustment Applied

The following covariates are used in risk adjustment:
Age, sex, admission category (elective versus urgent) and patient clinical groups — palliative care, mental illness, obstetric, surgical and medical conditions (for a detailed description, please refer to the High Users of Hospital Beds — Appendix and the
Model Specification document.

Calculation: Method of Adjustment

Logistic regression

Denominator

Description:
Patients age 18 and older discharged from an acute care facility within the fiscal year of reporting. The most recent episode of care (hospitalization) within the fiscal year of reporting is the index episode of care.
Inclusions:
1. Patients 18 years and older (at time of index episode of care)
2. Sex recorded as male or female
3. Acute care facilities
4. The LOS of the index episode of care was shorter than 365 days
Exclusions:
1. Abstracts with an invalid/missing health card number or invalid/missing province issuing health card number
2. Abstracts with a missing age
3. Abstracts with an invalid/missing admission date
4. Abstracts with an invalid/missing discharge date

Numerator

Description:
Patients within the denominator with 3 or more previous acute care episodes of care in a 1-year period and a cumulative LOS longer than 30 days.
Inclusions:
1. Patients with 3 or more previous acute care episodes of care in a 1-year period (365 days) from the admission date of the index episode of care

AND

2. A cumulative LOS greater than 30 days: cumulative LOS is calculated by summing the total episode LOS across the multiple episodes of care in a 1-year (365-day) period. It captures the length of time patients occupied acute care beds and may include alternate level of care (ALC) days, day surgery days and acute rehabilitation days.

Exclusions:
Same as in the denominator

For further details, please see the High Users of Hospital Beds — Appendix .


<div role="button" class="expandableTitle" aria-controls="backgroundRegion">Background, Interpretation and Benchmarks</div>
Rationale

Individuals with multiple admissions to acute care facilities are among high users of health care system services and resources. It is important to identify and monitor these high users. An Ontario study has shown that the top 5% of frequent users consumed about two-thirds of total health system spending and were mainly users of acute care and home care services.

This indicator can be used to monitor the rate of high users of inpatient acute care services across jurisdictions over time. Variations in this indicator across jurisdictions may reflect differences in service delivery. Indicator results can help policy-makers and health care planners identify high-risk groups and design specific preventive strategies/programs that may prevent the need for frequent hospital admissions.

Interpretation

A lower rate is more desirable.

HSP Framework Dimension

Health System Outputs: Appropriate and effective

Areas of Need

Not applicable

Targets/Benchmarks

Not applicable

References

Doupe MB, Palatnick W, Day S, et al. Frequent users of emergency departments: developing standard definitions and defining prominent risk factors. Ann Emerg Med. July, 2012;60(1):24-32. PM:22305330.

Kirby SE, Dennis SM, Jayasinghe UW, Harris MF. Patient related factors in frequent readmissions: the influence of condition, access to services and patient choice. BMC Health Serv Res. 2010;10:216. PM:20663141.

Lain SJ, Nassar N, Bowen JR, Roberts CL. Risk Factors and Costs of Hospital Admissions in First Year of Life: A Population-Based Study. J Pediatr. June 12, 2013; PM:23769505.

Longman JM, Rolfe I, Passey MD, et al. Frequent hospital admission of older people with chronic disease: a cross-sectional survey with telephone follow-up and data linkage. BMC Health Serv Res. 2012;12:373. PM:23110342.
Rais S, Nazerian A, Ardal S, et al. High-cost users of Ontario's healthcare services. Healthc Policy. August, 2013;9(1):44-51. PM:23968673.


<div role="button" class="expandableTitle" aria-controls="availabilityRegion">Availability of Data Sources and Results</div>
Data Sources

DAD, HMDB, NACRS, OMHRS

Available Data Years

Type of Year:
Fiscal
First Available Year:
2014
Last Available Year:
2015

Geographic Coverage

All provinces/territories

Reporting Level/Disaggregation

National, Province/Territory, Region


<div role="button" class="expandableTitle" aria-controls="resultRegion">Result Updates</div>
Update Frequency

Every year

Indicator Results

Web Tool:
Your Health System: In Depth
URL:
Accessing Indicator Results on Your Health System: In Depth

Updates

Not applicable


<div role="button" class="expandableTitle" aria-controls="qualityRegion">Quality Statement</div>
Caveats and Limitations

Not applicable

Trending Issues

Not applicable

Comments

For additional information, please see the FAQ: Understanding the High Users of Hospital Beds Indicator.

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