The National Program for Quality Indicators In Community Healthcare:  Methodological Issues
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The National Program for Quality Indicators In Community Healthcare: Methodological Issues Orly Manor 7th meeting of the Eastern Mediterranean Region of the International Biometric Society (EMR-IBS) Tel-Aviv April 22-25, 2013.

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The national program for quality indicators in community healthcare methodological issues

The National Program for Quality Indicators In Community Healthcare: Methodological Issues

Orly Manor

7th meeting of the Eastern Mediterranean Region of the International Biometric Society (EMR-IBS)

Tel-Aviv April 22-25, 2013


The national program for quality indicators in community healthcare methodological issues

“Efforts to improve quality require efforts to measure it”(Casalino, 2000:NEJM)


Healthcare in israel

Healthcare in Israel

National Health Insurance law (1995)

  • Universal healthcare

  • Standard basket of medical services

  • Four health plans (kupot cholim)

  • “Justice, equity and solidarity…medical services will be offered based on medical considerations, with reasonable quality.”


Healthcare in israel1

Healthcare in Israel

  • Health Tax - progressive , paid to the National Insurance Institute (funds are distributed to the health plans according to a capitation formulae) + modest copayment directly to health plan for specific services

  • Open enrollment, no option to reject applicant, annual option to switch plans

  • Managed competition between plans (uniform benefits)

  • Competition is based on quality and nature of services


The national program for quality indicators in community healthcare methodological issues

Israel National Program for Quality Indicatorsin Community Healthcare (QICH)

  • Supervisory bodies were established “to follow and assess the influence of the NHI law on health services in Israel, their quality, effectiveness and cost"

  • QICH started as a research project (Porath & Rabinovitz, 2002) and later adopted as a national program.

  • Full cooperation and support by all four health plans


Mission

Mission

To provide the public and policy-makers information on the quality of community healthcare provided in Israel. This information covers various health categories and is intended to promote and improve the standard of healthcare in Israel.


Main product

Main Product

Annual report presenting national results

of quality indicators in community healthcare

Enables

  • the evaluation of developments and changes in healthcare over time

  • the early identification of risk factors in the Israeli population and in sub-populations

  • the comparison of healthcare quality in Israel with other countries


The national program for quality indicators in community healthcare methodological issues

8

"Not everything that counts can be counted,

and not everything that can be counted counts."

Einstein


Quality indicators methods

Quality Indicators- Methods

9

  • Measures of clinical performance (structure, process, outcome)

  • Based on electronic health records from the four health plans

  • All indicators are rates

  • Some indicators are conditional on others

  • Covariates: age, sex, SEP (proxy)


Quality indicators 2013

Quality indicators (2013)

10


Example diabetes

Example: Diabetes

11

  • Blood glucose levels of individuals with diabetes are directly related to the development of complications: cardiovascular disease, blindness, kidney failure

  • Monitoring blood glucose by periodic hemoglobin A1c testing and achieving adequate glycemic control


Example diabetes1

Example: Diabetes

12

Prevalence measure:

  • Rate of individuals with diabetes mellitus from the entire population (overall and by age and gender)

    Process measure:

  • Rate of individuals with diabetes with documented levels of hemoglobin A1c (HbA1c)

    Outcome (intermediate) measure:

  • Rate of individuals with controlled levels of HbA1c from patients with diabetes with documented levels of hemoglobin A1c (HbA1c)


Methodological issues

Methodological Issues

  • Criteria

  • Population coverage

  • Data quality-measurement error

  • Data sources

  • Consistency of measures

  • Reporting


Criteria

Criteria

Implementation


Population coverage

Population Coverage

  • Population-based, near-complete coverage (not sample)

  • Transfers between health plans

  • Births/deaths

  • Other populations: e.g., soldiers


Data quality misclassification error

Data Quality- misclassification error

16

  • Estimating the prevalence of a medical condition in the absence of neither a gold standard nor an additional classification.

  • We wish to estimate - prevalence, sensitivity and specificity , yet df=1.

  • We can use a Bayesian approach- simultaneous inferences of the prevalence, sensitivity and specificity and positive and negative predictive value (Joseph et al 1995)

  • Selecting priors- experts’ opinion, understanding sources of data and errors (Greenland 2009)


Data quality consistency of measures

Data Quality- Consistency of Measures

17

Uniform definitions across health plans

  • Membership

  • Data collection period

  • Numerator and denominator


Data sources

Data Sources

  • Medical records (e.g., documentation of BMI)

  • Nurse’s records (e.g., documentation of vaccination)

  • Pharmacy claim records (e.g., medication purchase)

  • Laboratory results (e.g., HbA1c levels)

  • Hospital procedure codes (e.g., CABG)

  • Other (e.g., mammography)


Data quality sources of data and sources of error

Data Quality – Sources of Data and Sources of Error

  • Medical records (e.g., documentation of BMI)

  • Nurse’s records (e.g., documentation of vaccination)

  • Pharmacy claim records (e.g., medication purchase)

  • Laboratory results (e.g., HbA1c levels)

  • Hospital procedure codes (e.g., CABG)

  • Other (e.g., mammography)

Automated vs manual data input

(variation between and within health plans)

Pop-up options vs typing in vaccine name, historical data

(variation between health plans)

ATC vs YARPA/LARGO

(variation between health plans)

Standardized values for calibration

(variation between laboratories)

MOH codes used for billing

(too broad)

Self reported, billing-based


Data quality checks and audit

Data Quality – Checks and Audit

  • Internal (health plans)

    • Data checks (BI)

    • Feedback loops/criterion validity

  • Quasi-external (directorate)

    • Between and within health plan data checks (outliers)

    • Comparison with existing national data

  • External (independent auditor)

    • Process audit of infrastructure changes

    • Process audit of indicator implementation


Reporting

Reporting

  • Transparency + courtruling of the public reporting of indicators by health plan

  • Case mix: substantial differences between health plans by SEP

  • Limited available data on SEP

Friedberg et al. (2011). Rand Corporation: Methodological Issues in Public Reporting


Reporting adjusting for case mix

Reporting - Adjusting for Case Mix

22

  • Israel is divided into statistical areas.

  • The Israel Central Bureau of Statistics calculates SEP scores for each statistical area using recent census information

  • Currently-using GIS each person’s address (unidentified data) is linked to his statistical area and the respective SEP score


Reporting benchmarking

Reporting -Benchmarking

23

  • Setting benchmarks: setting, testing, comparing??


Diabetes care

Diabetes care


Diabetes care1

Diabetes care

Diabetes care includes routine monitoring and proper control of:

  • Blood glucose levels (93%)

  • Cholesterol levels (90%)

  • Blood pressure measurement (92%)

  • BMI assessment (86%)

  • Eye examination (65%)

  • Influenza (55%) and pneumococcal vaccination (77%)


Diabetes care2

Diabetes care

26


International comparisons diabetes care 2010

International comparisons – Diabetes care (2010)

*US data from the National Committee for Quality Assurance, HEDIS data set for 2010


Diabetes care israel and england qof 2009

Diabetes care – Israel and England (QOF) (2009)


Thank you

Thank you

Directorate: Orly Manor, Arie Ben-Yehuda, Amir Shmueli, Ora Paltiel, Ronit Calderon and Dena Jaffe

Directorate staff: Wiessam Abu Ahmad, Galit Shefer.

Clalit

Chaim Bitterman

Orit Ya’akobson

Arnon Cohen

Margalit Goldsprecht

Tamara Koren

Maccabi

YairBirenboim

EinatElran

Nesya Gordon

Rachel Marom

Guy Levy

Meuhedet

Liora Valinsky

Yossi Zini

Alon Yaffe

Leumit

Daniel Vardi

Eran Matz

Doron Dushnitzky

Nirit Peretz

External auditor: AlizaLukach

Israel National Institute for Health Policy Research

Advisory boards


Importance and relevance

Importance and Relevance


Evidence moving target

Evidence – Moving Target

HbA1c control

“Intensive therapy was stopped after a mean of 3.5 years due to increased mortality”The Action to Control Cardiovascular Risk in Diabetes Study Group N Engl J Med 2008; 358:2545-2559

.


Ability to quantify defining diabetes

Ability to Quantify – Defining Diabetes

32


Reporting1

Reporting

33


Quasi external audit

Quasi-external Audit


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