Description
This dataset contains the statewide number and (unadjusted) rate for all-cause, unplanned, 30-day inpatient readmissions in California hospitals. Data are categorized by age, sex, race/ethnicity, expected payer and county.
Resources
| Name | Format | Description | Link |
|---|---|---|---|
| data-dictionary-30-day-all-cause-hospital-readmission-rate-V3 | This dataset contains the statewide number and (unadjusted) rate for all-cause, unplanned, 30-day inpatient readmissions in California hospitals from 2011 to 2016 (contains first three quarters for Year 2015). Data are categorized by age, sex, race/ethnicity, expected payer and county. | Open resource | |
| All resource data | ZIP | all-cause-unplanned-30-day-hospital-readmission-rate-california-luxm2h.zip | Open resource |
| All resource data | ZIP | all-cause-unplanned-30-day-hospital-readmission-rate-california-sa170e1z.zip | Open resource |
| All-Cause Unplanned 30-Day Hospital Readmission Rate, California, (CSV) | CSV | This dataset contains the statewide number and (unadjusted) rate for all-cause, unplanned, 30-day inpatient readmissions in California hospitals. Data are categorized by age, sex, race/ethnicity, expected payer and county. | Open resource |
| methodology-30-day-all-cause-hospital-readmission-rate | This dataset contains the statewide number and (unadjusted) rate for all-cause, unplanned, 30-day inpatient readmissions in California hospitals from 2011 to 2015 (contains first three quarters for Year 2015). Data are categorized by age, sex, race/ethnicity, expected payer and county. | Open resource | |
| Rate of Unplanned Hospital Readmissions Within 30 Days of Discharge | xlsx | California’s overall 30-day readmission rate has declined from 14% in 2011 to 13.5% in 2015.[1] The rate of unplanned hospital readmissions is an important measure of clinical quality. High rates may indicate concerns with low quality and are associated with high costs.[2] Fortunately, there is evidence that hospital readmission rates can be reduced using tested quality improvement methods.[3] Typically, these interventions involve system transformation. Coordinating care between in-patient, outpatient, home, and community settings is a key component of high quality health systems.[3] Patients’ demographic and economic status, social support structure, and multiple health conditions can increase or decrease the likelihood of being readmitted; though these impacts are not fully understood. Note that this indicator is not risk-adjusted and differs in some ways from the Centers for Medicaid and Medicare Services (CMS) measure. Data are categorized by age, sex, race/ethnicity, expected payer source, and county of residence. (See metadata below for further details.) Learn more at [Let's Get Healthy California](https://letsgethealthy.ca.gov/goals/redesigning-the-health-system/reducing-hospital-readmissions/) [1] 2015 LGHC Data Report – Readmission Data [2] Kocher RP, Adashi EY. Hospital readmissions and the Affordable Care Act: Paying for coordinated quality care. JAMA. 2011;306(16):1794-1795. [3] Benbassat J, Taragin MI. The effect of clinical interventions on hospital readmissions: A meta-review of published meta-analyses. Israel J. of Health Policy Res. 2013;2(1):1-15. | Open resource |
Tags
- 30-day-readmission-rate
- age
- asian
- asianpi
- black
- department-of-health-care-access-and-information
- expected-payer
- female
- gender
- healthcare
- healthcare-quality
- hispanic
- hospital-admission-and-readmission
- hospital-quality
- inpatient
- insurance
- lets-get-healthy-california
- lghc
- male
- measures
- medicaid
- medi-cal
- medicare
- native-american
- outcome
- patient
- patient-readmission
- private-insurance
- race
- readmission
- self-pay
- white