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O =q:mFFrom Health Research to Social Research: Privacy, Methods, Approaches GG G  Leslie L Roos(  5For Comparison: Panel Study of Income Dynamics (PSID)66( Compare administrative data with the only social science study noted on  the NSF s list of its fifty most significant projects in its fifty year history Highlights issues in extending population-based (health) administrative data to facilitate social research Expanding Capabilities(Link files to incorporate new data sets while preserving privacy and confidentiality Measure such outcomes as educational achievement at population level 6" >Expanding Capabilities (cont d) (>Use place of residence data (for any point in time) to calculate the number of moves, number of years in relatively poor neighborhoods, etc. Estimating family composition at any point in time (tracking marital status, family size, ages of siblings and twins). Social variables used for more powerful research designs. 4>" > Linking while Preserving Privacy!!(Multi stage de-identification process: Trustee preparation Manitoba health links Trustee s file to the encrypted PHIN Crosswalk file provided to MCHP Trustee provides data file MCHP stores data separately and unlinked&''7 Currently Available: Measures to Understand Well Being88(cAvailable for population for one or more years: Age, grade level, school attendance, marks, achievement tests for Grade 3, Grade 9, Grade 12 Well-identified health conditions such as asthma and diabetes plus a measure of general health status can be studied through childhood and adolescence Healthcare utilization and costs Receipt of social assistanceL2] / 2 Not Available(Survey-based measure of household income and education are not available for entire population Manitoba comparisons of income measure found risk estimates for health status measures derived from neighborhood income not attenuated relative to those from household income May not be true everywhere)Z)*Small Area Measures from Statistics Canada++(Publicly available Use dissemination/enumeration areas Often encompass several six digit postal code areas Indicators such as mean household income and education, unemployment rates, etc. Canadian studies of the socioeconomic gradient in utilization often use small area markersrSteps for comparing educational achievement across geographical areas parallel those developed for health researchss E Obtaining indicators of socioeconomic risk for each small area Developing individual data on educational achievement Calculate rates of achievement based on small areas Track the entire population Combine census enumeration areas as appropriate (for quartiles or quintiles based on socioeconomic status of area of residence)P<?" K" ZE Data Used9Up to nine years of Manitoba birth cohorts (1978-1987, excluding the 1983 cohort) Takes advantage of available provincial Grade 12 test scores About 13,000 in each cohort surviving and remaining in the province for the first 18 years of life Large sample for same-sex pairs (33,000) and multiple births (2,000):: 6Population-Based Data Provide a Different Perspective776 Estimating Family Circumstances (!& Number of children in the family Birth order Mother s marital status at birth of first child Age of mother at birth of first child Whether or not family was receiving income assistance Number of changes of residence Other Social Variables Number of years in different types of families Number of  family structure changes (parental separations, remarriages) Number of years living with disabled parent NOTE: Almost all variables can be measured at different points in time Importance of Social Variables(dThe first six social variables (i.e. number of children, birth order, etc.) were better predictors of educational achievement than survey model (includes household income and parental education) from PSID Predictive power varies with outcome selected (much lower for health outcomes) Used as control variables in sibling and sibling/neighbourhood research ee'Emergence of the Socioeconomic Gradient(($oAssociation between socioeconomic status and health may vary at different life stages Questions include: How do socioeconomic gradients evolve for both males and females as children grow older? What can we learn about gradient development by looking at the trajectories of individuals over time? Are socioeconomic gradients in child health changing over time?^j!Z!0Z" ZW&Problems with Non-Experimental Design''(Analyzing casual relationship is difficult Omitted variables and measurement error are likely to bias the coefficients attached to measured variables Standard statistical analyses suffer from this problem (a growing literature in economics on this issue) 40Z 0Z j0Z &Problems with Non-Experimental Design|Whole population, sibling and twin studies each have different strengths and weaknesses Siblings and twin designs  control differently often using  family fixed effects statistical models.X  f Literature ReviewRelationship between birth weight and infant mortality decreases when differences between twins examined Twin samples help eliminate unobserved heterogeneity across families BUT twins generally of lower birth weight than singletons Gestational length not examined in twin studies Canadian data provide uniform access to health insurance whereas coverage in U.S. may vary even among siblings Z(Approach One: Favourite Economist Tactic))(Summarizing cross-family variation (each family as a separate condition) provides estimate of effects of presumably causal individual variables (such as birth weight) by differencing out family-specific characteristics affecting all children. Comparisons of siblings within families help make up for lack of control over variables measuring household income and parental education $Comparing Twin and Sibling Estimates%%(Exploits benefits of both identification strategies Siblings provide a more representative sample but strategy risks biased estimates: A) Potential change in parental investment following the birth of first child B) Potential change in socioeconomic status between births Using twins eliminates these potential biases but sample is limited and unrepresentative Patterns of postnatal development (as a function of infant health) may differ for siblings and for twins h could affect resultsr4P0PSPP0PZP0PPResultsInfant health strongly predicted both high school completion and income assistance take-up and length, controlling for a number of possible cofounders Long-term consequences of infant health were found across families, within siblings, and within twin pairs. %Measuring Infant Health: Five Models*&&(1) Ordinary Least Squares (OLS) using entire sample OLS using sample of children with siblings Sibling sample including family fixed effects OLS using sample of twins Twin sample including family fixed effects *Looked at longer-term measures of child health and social outcomes V4" E" D*Approach Two: Sibling Neighbourhood Design++$l Compare correlations for siblings and unrelated neighbours of similar ages Use to identify an  upper bound on the influence of neighbourhoods, because neighbour correlations reflect similar family backgrounds as well as shared community backgrounds C) Extend this approach to consider schoolmates and peers|L" Z0" Z" Z0" Z:ZM:%Study Opportunity StructuresUrban-rural comparisons Socio-economic gradient (comparing means and correlations by income) Comparisons across dimensions of well beingV-Sibling Neighbourhood Design(Uses location of each family in a 6 digit postal code area Matches with neighbour in postal code area, then those  leftover , with closest  leftover in census enumeration area (neat linear program) N< " F)Figure 1. Sibling - Neighbourhood Designs**  _Sibling and Neighbour Correlations Girls Outside Winnipeg: 1978-1987 Cohorts (excluding 1983)``%A Guaranteed Annual Income Experiment&&(XA population-based guaranteed annual income experiment in Dauphin, MB from 1974 to 1978 substantially reduced poverty. To study long-term effects: Propensity matching created a 3-to-1 control for all Dauphin and rural municipality residents. A second set of controls age-and sex-matched residents living in the test site before the experimentRx  (_ exResearch QuestionsDid the elimination of income insecurity when children were particularly vulnerable affect their lives after the experiment ended? Will young children in families receiving assistance have experienced better health and social outcomes as adolescents?" 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(G&0: ^N0 5-P (     0P  B 2   0$V  o7Information-Rich Environment: Using Administrative Data8(28w F 1K  5   A2 6   `\ gֳgֳo?=?E  Research Registry002 7   `a gֳgֳo?"` 0 oMedical02 8   `i gֳgֳo?"`a E    Vital Statistics 40002 9   `b gֳgֳo?"`4b A Home Care  2 :   `hQ gֳgֳo?"` UK t Nursing Home  0 2 ;   ` gֳgֳo?"`  pHospital  0~2 <   `P gֳgֳo?"` K   Provider R  0 0 2 =   `” gֳgֳo?"`1p  vPharmaceutical0A2 >   `8ϔ gֳgֳo?"` M j   Immunization Monitoring 40" ? < >?"6@`NNN?N@" @ B >?"6@`NNN?N@ " A B >?"6@`NNN?N` 0@" B B >?"6@`NNN?Np " C B >?"6@`NNN?Np" D B >?"6@`NNN?N 0 `" E B >?"6@`NNN?N` @  F BPՔ  >?"6@`NNN?Npp ]#Inflammatory Bowel Disease Database$(2$  G B@ڔ  >?"6@`NNN?Np0 P  QSleep Lab Clinical Data(2  H BTݔ  >?"6@`NNN?N@ RAlcoholism Panel Surveys(2  I B@  >?"6@`NNN?N @m  ICancer Registry(2  J BLp  >?"6@`NNN?N0Pm  UEducational and Social Data(2  K Bs  >?"6@`NNN?N @` MHeart Health Survey(2  L BLx  >?"6@`NNN?N ` = QAging in Manitoba Study(2   M B|  >?"6@`NNN?N  [!National Population Health Survey"(2"  N B@  >?"6@`NNN?N`  H(2  r" P < ?"`0 B  s *޽h ? ffD3fy___PPT10Y+D=' = @B +n 0  ^N0  V(      <A _? ?"`q2/  _H  0޽h ? fD3f80___PPT10.`Ȅ 0  ^N0 80o (    e  <A H? ?"``-  HjB o BD|?rH  0޽h ? fD3f80___PPT10.V 0  ^N0 80  (      <A K? ?"`  KjB  BDo?rrH  0޽h ? fD3f80___PPT10.rHR 0  ^N0 L p(  L  L 0(   `p    L 0@  `   "p`Pp  L 0 ?0` tMoving from health research to social research involves preparatory work with databases, which must be organized to:u(2u H L 0޽h ? fD3f80___PPT10.v 0  ^N0 P ^(  P  P 0B `}    P 0I  `  "p`PpH P 0޽h ? fD3f80___PPT10.K0  ^N0  (     0D] B 2 i  0L~p C Canada Foundation for Innovation and provincially funded Data Laboratory Highest standards of security, privacy & confidentiality of data No names, no addresses Probabilistic linkages across files as needed Data for research, not for administrative use Provincial privacy offices kept fully informed(''0 2   ( 'o  0< ? l2Respect for Privacy In Building Manitoba Database3(23 H  0޽h ? 33___PPT10i.ܺpV+D=' = @B +`  0  ^N0 T H(  T  T 0x `}    T 0  `  H T 0޽h ? fD3f80___PPT10.0` 0  ^N0 X H(  X  X 0@ p`}    X 0< V  H X 0޽h ? fD3f80___PPT10. ` 0  ^N0 P H(     0  `}     0  `  H  0޽h ? fD3f80___PPT10.=` 0  ^N0 @ H(     0@}  ``     0  `  H  0޽h ? fD3f80___PPT10.ev 0  ^N0 ` ^(  `  ` 0 `0    ` 0 @ `s  "p`PpH ` 0޽h ? fD3f80___PPT10. 0  ^N0 P p(      6& "` `}      6|' "`0 `  H  0޽h ? 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ZXdbmo80___PPT10. 0  ^N0 Tp(  T T 6PG  "` `}  G   T 6G  "`  ` G  H T 0޽h ? ZXdbmo80___PPT10.=@_ 0  ^N0  `p(  ` ` 6G  "` `}  G   ` 6G  "` ` G  H ` 0޽h ? 3380___PPT10.oL 0  ^N0  X(  X X 6G  "` `}  G   X 6 G  "`P ` G  "p`PpH X 0޽h ? ZXdbmo80___PPT10.9Ry 0  ^N0 0 d(  d d 6L6G  "` `}  G   d 60A  "`0c G  "p`PpH d 0޽h ? 3380___PPT10.L` 0  ^N0 !H(    0@A   `}  A    0A   ` A  H  0޽h ? fD3f80___PPT10.d$* 0  ^N0 P l(  l l 6lA  "`@`}  A   l 6,A  "``P A  "p`PpH l 0޽h ? ZXdbmo80___PPT10.a\P 0  ^N0   @ h (  h h 6A  ` A  o   h3 s"j* 4@Z4@Zq4@ZuqC"h4@Z ?b h c $X99?"` x" hB HG)HbISo_s944133> > `x" h HG)H]I'o_s944134> > `" h ZLA ww_s9441353"`  ^   MNeighbourhood A"0 " h Z A ww_s9441363"`  `  hFamily 1 Sibling 1a Sibling 1b.0  "  h ZA ww_s9441373"`   `  hFamily 2 Sibling 2a Sibling 2b.0  o -$   h3 s"j*\ JJ J+I\JȌ00 l b  h c $X99?"`-$ x"  hB HG)H0I7o_s944140? 56 x"  h HG)HIPo_s944141G 5? " h ZA 00_s9441423"`    5 MNeighbourhood B"0 " h ZA 00_s9441433"`   9  hFamily 3 Sibling 3a Sibling 3b.0  " h ZA 00_s9441443"`   9  hFamily 4 Sibling 4a Sibling 4b.0  H h 0޽h ?Ohhh hhhhh hhh h 3380___PPT10.?`5  0  ^N0 / ' x (  x x 6!A  "`q `A  A   r  `` x# #"0P x <A ? ` f .675* .369* .111*" @` x <A ?   }Held back by Grade 12 Sibling (Unadjusted) Neighbour (Unadjusted) Neighbour (Adjusted),   @` x <A ? `  ] .612* .174* .000* @` x <`A ?    6 Income Assistance After Age 18 ( 1978-1982) Sibling (Unadjusted) Neighbour (Unadjusted) Neighbour (Adjusted):7+  @` x <A ?``  f .576* .368* .120*" @`  x <PA ? `  w!Pregnancy Before Age 19 Sibling (Unadjusted) Neighbour (Unadjusted) Neighbour (Adjusted)$"  @``B  x 0o ? ```ZB  x s *1 ?  ` ZB  x s *1 ?  ` `B  x 0o ? ``B x 0o ? ` ZB x s *1 ?``B x 0o ?```H x 0޽h ? 3380___PPT10.r6` 0  ^N0 0h H(  h  h 0A   `}  A   h 0A  P `s A  H h 0޽h ? fD3f80___PPT10.^v 0  ^N0 `t ^(  t  t 09A   `}  A   t 0T@A   ` A  "p`PpH t 0޽h ? fD3f80___PPT10.`,v 0  ^N0 !^(    0GA   `}  A    0PA   ` A  "p`PpH  0޽h ? fD3f80___PPT10.0&@v 0  ^N0 !^(    0 |A   `}  A    0pA   ` A  "p`PpH  0޽h ? fD3f80___PPT10.0&00   (   d  c $$XK     3 r kk$ M(   " H  0.k ? ̙33. 0   Pp > (  p d p c $$YK   A   p s *ܬ< $ (  A  (  Graph on the left reflects what schools see when they review the performance of students taking the tests: 92% of students who live in the High SES areas passed, along with 75% of those from Low SES areas. Sounds pretty good. The problem is, this just reports results for those who are in school, in grade 12, and writing the standards tests. But who should be writing the standards test and isn t? Very different story told by the graph on the right side. Here we identified all children born in Manitoba in 1984 who remained in Manitoba since then (84%). For those residing in Winnipeg in 2001/02, we figured out where they were in the school system (in what should have been their last year in school). The graph on the right captures a different reality: only 27% of the youths in the Low SES areas who should have been writing the standards test that year passed. A very large group (almost 36%) were behind at least one year (in grade 11 (S3) or lower), and almost 20% had withdrawn (not enrolled in school for at least 2 years). For all 4 SES groups, if students were in grade 12 and writing  the great majority passed, but many of the kids from Low SES areas had not yet made it to grade 12 (and many were not in school at all). P  H p 0.k ? 3380___PPT10.JhU/0 " (   d  c $$XK   A   s *< $ (  A  These variables are used in many survey-based studies of well being (see Concept Dictionary) Used as covariates in statistical studies H  0.k ? 3380___PPT10.P g 0  Z(   d  c $$XK   <   3 r< e߲e߲$ M(  <   The central feature of Manitoba Centre for Health Policy s (MCHP) data is the Registry: includes an encrypted personal health identification number ( PHIN), residential post code, and family composition for each registrant The encrypted PHIN (Personal Health Identification Number) is used to link the datasets to the registry. The linkage facilitates research, decreasing the need for new data collection. The outer ring of data sets have allowed the study of particular issues and has increased the number of variables available. This presentation emphasizes research using health, educational, and income assistance data. Collectively, they form the Population Health Research Data Repository (or simply the Repository).   H  0.k ? ̙330 $(  d  c $$XK   <   s *\< $ M(  <  Additional information on record linkage in MCHP s Concept DictionaryH  0.k ? ̙3380___PPT10.  So 0  |(  |^ | S $XK   < ~ | c $b< $ M(p  < XP___PPT92* 2PSID represents annual or biennial survey data collected on about 5000 representative American households. From 1968 to the present Includes: Capacity to study a second generation in families Corrections for immigration Research on neighborhood effects A wide variety of questions asked But very costly to collect the data Most highly-cited study from University of Michigan s Institute for Social Research d--U--UH | 0.k ? ̙3380___PPT10.T9x0 ZR (  ^  S $XK   < L  c $< $ M(n  < VN___PPT90( This screen and the next two compares the Panel Study in Income Dynamics and MCHP s data: Start dates are close: 1968 for PSID and 1970 for the Registry High levels of follow-up exist in both sets of data Manitoba health s data are updated more frequently  every six months: new enrollees are added and reasons for terminations are given Important differences or similarities: Number of cases for population based data is much larger Cost is considerably lower for administrative data PSID samples; MCHP includes an entire population Cost for studies with population data do not necessarily go up greatly when the research becomes more complex MCHP data does require validation when linking new sources of data Z?--4--G-A-'-O-W'qH  0.k ? ̙3380___PPT10.U@0 <4 (  ^  S $XK   < .  c $-< $ M(  <   MCHP does not need to be concerned with non-responses Updates require significant work with both types of data: population based data can updated regularly and routinelyH  0.k ? ̙3380___PPT10.V0 .& (  ^  S $XK   <    c $6< $ M(  <   Data on life events (collected by PSID) need to come from elsewhere for the administrative data Variables for collected data, like PSID s, are defined by the researchers  often in advance of the study Data collection for MCHP resources is defined by others and requires effort to create variables that match the researcher s intentH  0.k ? ̙3380___PPT10.V.0   (  ^  S $XK   <   c $X< $ M(r  < ZR___PPT94, 6This process protects privacy and allows for high-quality linkage. Steps: Trustee prepares files containing a scrambled record number and identifying information such as name, date of birth, and address. 2. Manitoba Health uses the Trustee s file to link the person to his/her personal health identification number. An encrypted PHIN is attached to the Trustee s scrambled number. 3. After removal of all identifying information, a crosswalk file with the encrypted PHIN and the Trustee s scrambled number is provided to MCHP. 4. The Trustee sends the data file to MCHP with the scrambled number. Each file is stored separately and unlinked at MCHP. Only authorized persons have access to the data and crosswalk files. VL" " |" L|H  0.k ? ̙3380___PPT10.W`60  ,(  ^  S $XK   <   c $< $ M(  <  " H  0.k ? ̙3380___PPT10.0 xp (  ^  S $XK   < j  c $;< $ M(  <  Through the information obtained from the  supporting data sets, we can attempt to measure well-being. Not all measures are available for all years. Measures are described in MCHP s Glossary and Concept Dictionary. Plan to add Justice data.H  0.k ? ̙3380___PPT10.`s#n0 !~(  ^  S $XK   <   c $@< $ M(  <  t`Statistics Canada data provide additional information and assist in  breaking down population data into smaller areas which can be characterized along a number of dimensions. H  0.k ? ̙3380___PPT10.07R0 !b(  ^  S $XK   <   c $< $ M(  <  XDThis study on educational achievement is described more fully later.H  0.k ? ̙3380___PPT10.0 ' !(  ^  S $XK   <   c $[$ M(  <  The association could remain constant throughout life. Or, socioeconomic status (SES) could have the strongest association with health in childhood and lessen throughout life. Or, it could be the opposite, the relationship could be weak in childhood and grow stronger as a person ages. Any change in SES will likely influence the relationship. Some studies have been completed on SES and newborn health H  0.k ? ̙3380___PPT10. gq0 0!(  ^  S $XK     c $g$ M(   wcDeal with issues of generalizability and validity by making comparisons within individual studies. H  0.k ? ̙3380___PPT10.6e0 91@!(  ^  S $XK   +  c $ q$ M(   Other income researchers have focused on labor market outcomes. This study took into consideration: teen pregnancy birth outcomes and both chronic and acute conditionsH  0.k ? ̙3380___PPT10.0 F>P!(  X  C $XK   >  S x$ M(   Each year an additional birth cohort is added. 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