Presentation is loading. Please wait.

Presentation is loading. Please wait.

Preventable Hospitalizations: Assessing Access and the Performance of Local Safety Net Presented by Yu Fang (Frances) Lee Feb. 9 th, 2007.

Similar presentations


Presentation on theme: "Preventable Hospitalizations: Assessing Access and the Performance of Local Safety Net Presented by Yu Fang (Frances) Lee Feb. 9 th, 2007."— Presentation transcript:

1 Preventable Hospitalizations: Assessing Access and the Performance of Local Safety Net Presented by Yu Fang (Frances) Lee Feb. 9 th, 2007

2 2 Outline Preventable hospitalizations Connection between local safety net capacity and preventable hospitalizations Research proposals

3 3 Preventable Hospitalizations Avoidable Hospitalizations Avoidable Hospital Conditions (AHCs) Ambulatory-Care Sensitive Conditions (ACSCs or ACS Conditions)

4 4 Preventable Hospitalizations Inpatient treatments of conditions for which timely and effective use of primary care should have reduced the risk of hospitalizations (Texas Health Care Information Collection, 2003)

5 5 Preventable Hospitalizations A list of ICD-9-CM codes based on hospital discharge data Usually measured as rates of admission to the hospitals Different technical definitions of PH: Billings et al. (1993) Weissman et al. (1992) Agency for Healthcare Research and Quality (AHRQ) – Prevention Quality Indicators

6 6 Preventable Hospitalizations PQIPrevention Quality Indicators 1Diabetes short-term complication admission rate 2Perforated appendix admission rate 3Diabetes long-term complication admission rate 5Chronic obstructive pulmonary disease admission rate 7Hypertension admission rate 8Congestive heart failure admission rate 9Low birth weight 10Dehydration admission rate 11Bacterial pneumonia admission rate 12Urinary tract infection admission rate 13Angina admission without procedure 14Uncontrolled diabetes admission rate 15 Adult asthma admission rate 16 Rate of lower-extremity amputation among patients with diabetes Resource:

7 7 PQI 1: Diabetes Short-term Complication Admission Rate Admissions for diabetic short-term complications per 100,000 population Relationship to quality: Proper outpatient treatment and adherence to care may reduce the incidence of diabetic short-term complications Population at Risk : Population in Metro Area or county, age 18 years and older Benchmark : State, regional, or peer group average lower rates represent better quality care

8 8 PQI 1: Diabetes Short-term Complication Admission Rate Numerator: All non-maternal/non-neonatal discharges of age 18 years and older, with ICD-9-CM principal diagnosis code for short-term complications Excluded cases: transfer from other institution MDC 14 (pregnancy, childbirth, and puerperium) Denominator: Population in Metro Area or county, age 18 years and older

9 9 Use of Preventable Hospitalizations To assess quality of health services in the community To identify unmet community health care needs To monitor how well complications from a number of common conditions are being avoided in the outpatient setting To compare the performance of local health care systems across communities Resource: Department of Health and Human Services, & Agency for Health Research and Quality. (2006a). Guide to Prevention Quality Indicators: Hospital Admission for Ambulatory Care Sensitive Conditions.

10 10 Preventable Hospitalizations Strengths minimal requirement for resources comparison across different levels Weaknesses strong relationship between PHs and SES limited evidence for each PH limited evidence on the effectiveness of treatments in reducing incidence of PH Resource: Department of Health and Human Services, & Agency for Health Research and Quality. (2006a). Guide to Prevention Quality Indicators: Hospital Admission for Ambulatory Care Sensitive Conditions.

11 11 Davidson et al’s Framework Community Characteristics Safety-Net population Uninsured population Medicaid beneficiaries Vulnerable populations Low-income population support Medicaid eligibility level Health care market Physician supply Managed care penetration Managed care competition Safety-net Support Direct government & private support of safety net  Medicaid payment level Safety-net services Public hospitals Teaching hospitals Community clinics Individual Characteristics Predisposing Need Enabling__ Demographics Perceived Income Social factor Evaluated Health insurance Beliefs Usual source of care Health care Access and Outcomes Potential access Usual source of care Realized access Doctor visits Other health care Access outcomes Preventable hospitalizations Other outcome indicators Safety-Net population Uninsured population Medicaid beneficiaries Vulnerable populations Low-income population support Medicaid eligibility level Health care market Physician supply Managed care penetration Managed care competition Safety-net Support Direct government & private support of safety net Medicaid payment level Safety-net services Public hospitals Teaching hospitals Community clinics Predisposing Need Enabling__ Demographics Perceived Income Social factor Evaluated Health insurance Beliefs Usual source of care Health care Access and Outcomes Potential access Usual source of care Realized access Doctor visits Other health care Access outcomes Preventable hospitalizations Other outcome indicators Resource: Davidson, P. L., Andersen, R. M., Wyn, R., & Brown, E. R. (2004). A framework for evaluating safety-net and other community-level factors on access for low-income populations. Inquiry, 41(1), Individual Characteristics Community Characteristics

12 12 Proposal 1: Small-Area Analysis Study population: residents aged in Harris County, Texas (2004 ) Unit of Analysis: ZIP code Datasets: Project Safety Net (2004) Texas Health Care Information Collection (2004) Census 2000 Data analysis: linear regression

13 13 Proposal 1: Small-Area Analysis Objectives: To investigate the rate of preventable hospitalizations by insurance type in Harris County, Texas To investigate the association between the capacity of primary care services and preventable hospitalizations for the low-income population To Investigate the association between the proximity to the nearest primary care services and preventable hospitalizations for the low-income population

14 14 Proposal 1: Local Safety Net and Preventable Hospitalization at ZIP-code level Safety-net population at ZIP-code level  Uninsurance rate  Poverty level  Age  Gender  Ethnicity Safety-net primary care services at ZIP- code level  Availability of primary care providers  Capacity of primary care providers Access outcome Preventable hospitalization rate

15 15 Proposal 2: Multi-Level Analysis Study population: hospitalized, non-elderly (aged 18-64) low-income adults in Harris County, Texas (2004 ) Unit of Analysis: individual as level-one ZIP code as level-two Datasets: Project Safety Net (2004) Texas Health Care Information Collection (2004) Census 2000 Data analysis: Multi-level logistic regression

16 16 Proposal 2: Multi-Level Analysis Objectives: To learn about the fraction of total variability in preventable hospitalization at the individual level and at the community level for hospitalized, non-elderly low-income adults To analyze the association between the proximity to the nearest safety net clinic and preventable hospitalizations among the low-income population, after controlling for individual characteristics and community characteristics To analyze the association between the capacity of local primary care services and the preventable hospitalization among the hospitalized low-income population, after controlling for individual characteristics and area characteristics

17 17 Proposal 2: Multi-Level Analysis To compare the relative importance of health insurance and the proximity to the local safety net clinics in reducing the likelihood of preventable hospitalization for the hospitalized low-income, non-elderly adults To estimate the direct costs of preventable hospitalizations in Harris County for all low-income, non-elderly hospitalized population in 2004, and compare the average costs of preventable hospitalization in Harris County with those measured in the existing literature

18 18 Proposal 2: Local Safety Net and Preventable Hospitalization at Two Different Levels Population characteristics at zip-code level Uninsurance rate Education Area income at zip-code level Safety-net Services at zip-code level Primary-care capacity of safety net clinics Hospitalized Safety- Net Population Individual characteristics Predisposing Enabling Gender Health insurance Age Proximity to the nearest safety-net clinic Race Access Outcome Preventable hospitalization Community Characteristics Reference: Davidson, P. L., Andersen, R. M., Wyn, R., & Brown, E. R. (2004). A framework for evaluating safety-net and other community-level factors on access for low-income populations. Inquiry, 41(1), 21-38

19 19 Summary Preventable hospitalization rate is based on hospital discharge data Preventable hospitalization is an access outcome, and is one of the main tools to monitor the local safety net Individual and community characteristics both contribute to preventable hospitalization


Download ppt "Preventable Hospitalizations: Assessing Access and the Performance of Local Safety Net Presented by Yu Fang (Frances) Lee Feb. 9 th, 2007."

Similar presentations


Ads by Google