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An analysis of access to end-of-life care for adults dying of cancer in Nova Scotia

An analysis of access to end-of-life care for adults dying of cancer in Nova Scotia. Meaghan O’Brien June 6, 2006. Outline. Purpose Databases Study subjects Concentration #1 – Culture in research Concentration #2 – EOL data quality

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An analysis of access to end-of-life care for adults dying of cancer in Nova Scotia

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  1. An analysis of access to end-of-life care for adults dying of cancer in Nova Scotia Meaghan O’Brien June 6, 2006

  2. Outline • Purpose • Databases • Study subjects • Concentration #1 – Culture in research • Concentration #2 – EOL data quality • Concentration #3 – Trends in the place of death of cancer patients • Strengths and limitations • The future

  3. Purpose • Identify variables associated with place of cancer deaths in NS to help assess level of equality in access to EOL/PC services

  4. Databases Cape Breton PC Program Database Capital Health PC Program Database NS Vital Statistics NS Cancer Centre OPIS Study Subjects NS Cancer Registry 1996 and 2001 Census Data Statistics Canada Postal Code Conversion File

  5. All NS residents who died of cancer according to death certificates, 1994-2003 (n = 25,127) Study Subjects Excluding: Those 19 years of age or younger (n = 63) Those whose cancer diagnosis was not known prior to death, i.e. death certificate only cases (n = 930) Those who died out of province (n = 150) Those with missing place of death information (n= 1097) 22,886 final study subjects 6,151 died out of hospital 16,735 died in hospital

  6. Concentration #1 – A sociological critique of ecological measures of culture • No universally accepted definition of culture • Leads to difficulties in research • Cultural safety issues also arise • Potential method for developing ecological cultural variables presented

  7. Ecological cultural variable creation Subjects’ postal code of usual residence at time of death or most recent residential postal code from OPIS Cut-points for EA/DA’s developed for each cultural variable (ex. 10%, 50%) Census EA/DA Subjects assigned cultural labels based on the cultural description developed for their EA/DA

  8. Likelihood of out-of-hospital death * From multivariate logistic regression analysis with year of death, sex, age and tumour group also in the model to control for potential confounding

  9. Strengths • Information in existence • Available nation-wide • Weaknesses • Conceptually narrow definition • Undercount in census • Describes communities of residence not individuals • Cultural safety and acceptance of method could be a problem

  10. Concentration #2 - Assessment and improvement of end-of-life and palliative care datasets • Increasing interest in EOL/PC, meaning increasing # of EOL/PC datasets • Quality data is essential • Little published to guide data quality improvement in EOL/PC dataset development

  11. Data acceptance Subject completeness Service completeness Data field completeness Coding constancy Data field accuracy Validity Reporting constancy Timeliness Concentration #2 From literature and NS EOL dataset development, 9 data quality concepts described with examples:

  12. Concentration #3 – Trends in the place of death of cancer patients in Nova Scotia, 1994-2003 • Based on: Burge F, Lawson B, Johnston G. (2003) Trends in the Place of Death of Cancer Patients. CMAJ • Dependent variable - place of death • In hospital (includes deaths in acute care hospital beds, transitional care beds and nursing home beds in a nursing home that occupies the same location as a hospital) • Out of hospital

  13. Variables ENVIRONMENT POPULATION HEALTH OUTCOMES CHARACTERISTICS BEHAVIOUR • Health care • system • Distance to • cancer care • External • environment • Year of death • Predisposing • characteristics • - Demographics • Age • Sex • -Social structure • -Health beliefs • Ecological • cultural • variables • Enabling • resources • Personal • Nursing home • resident • Community • Income • Region of • province • Need • Tumour • group • Time from • diagnosis • to death • Time from • initial • registration • in a PCP • to death • Personal health • practices • Use of health • services • Medical • oncology • Palliative • radiation • Palliative care • program • Location of • death • Consumer • satisfaction

  14. Definitions • Nursing home residence – place of death or place of usual residence at time of death matches the name of a nursing home on an extended list of nursing homes in NS • Systemic therapy – receipt of chemotherapy in last 12 months of life • Palliative radiation - definition based Johnston et al. (2001): given a palliative intent code by treating radiation oncologist or if <=10 fractions were administered in last 9 months of life

  15. Method of analysis • Statistical software (SAS) • Univariate and multivariate logistic regression analysis used to identify odds of dying out of hospital over time • Most parsimonious model of out-of-hospital death developed using multivariate logistic regression analyses

  16. Population characteristics Predisposing characteristics - Demographics Female (OR=1.3, CI 1.2-1.3, vs male) 75-84 yrs(OR=1.5, CI 1.3-1.9, vs 20-44 yrs) 85+ years (OR=2.4, CI 2.0-2.9, vs 20-44 yrs) - Social structure and health beliefs Immigrant cmty (OR=1.2, CI 1.1-1.3) Enabling Resources - Personal Nursing home residence (OR=12.3, CI 9.3-16.2) - Community Upper quintile MHI (OR=1.2, CI 1.1-1.3, vs lowest quintile) Predictors of out-of-hospital death

  17. Population characteristics Need Survival 61-120 days (OR=2.2, CI 1.9-2.4, vs <=60 days) 121+ days (OR=2.6, CI 2.4-2.8, vs <= 60 days) Tumour group Breast (OR=1.2, CI 1.03-1.3 vs lung) Colorectal(OR=1.2, CI 1.1-1.4, vs lung) Prostate (OR=1.1, CI 1.00-1.3, vs lung) CB PCP 17-45 days in program(OR=1.4, CI 1.01-1.9 vs <=16 days) 46-124 days in program(OR=1.4, CI 1.03-2.0 vs <=16 days 125+ days in program(OR=1.7, CI 1.2-2.3 vs <=16 days) CH PCP 17-45 days in program(OR=2.0, CI 1.6-2.5 vs <=16 days) 46-124 days in program(OR=2.3, CI 1.8-2.9 vs <=16 days) 125+ days in program(OR=2.1, CI 1.7-2.7 vs <=16 days) Predictors of out-of-hospital death

  18. Health Behaviour Use of health services Referral to: CB PCP (OR=1.5, CI 1.2-1.8) CH PCP (OR=1.1, CI 1.0-1.2) Predictors of out-of-hospital death Systemic therapy, Aboriginal and French were not significant in univariate analysis.

  19. Population characteristics Predisposing characteristics - Social structure and health beliefs Non-official language cmty (OR=0.8, CI 0.7-1.00) Enabling Resources - Community Cape Breton County(OR=0.7, CI 0.6-0.7, vs Halifax County) All other NS counties(OR=0.7, CI 0.7-0.8, vs Halifax County) Health behaviour Use of health services Palliative radiation (OR=0.9, CI 0.8-0.9) Predictors of out-of-hospital death

  20. Variables significant in univariate but not multivariate analysis

  21. Strengths • Creation of several new variables • Nursing home residence • Systemic therapy • Palliative radiation • Addition of CB PCP database • Co-operation with researchers in other provinces • Increased attention to cultural safety • Creation of detailed data quality and study methods • Data and results reviewed by stakeholders • Results presented to peers at 4 conferences

  22. Limitations • Data limited to what was available from existing databases • Absence of preferred place of death data • Lack of data on intensity of hospital use at EOL and type of hospital unit (PC, ICU, ..) • Only deals with inequality, not inequity

  23. The future • Co-operation amongst researchers, database administrators and stakeholders • Linkage to: • Hospital separations database • Physician claims • Home care data • Drug data • Other PCP databases • Addition of other variables • Begin to assess whether inequities exist

  24. Questions, concerns, ideas?

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