Alumni Profile
Lahn Straney
Former Post-Graduate Fellow
PhD, Epidemiology and Biostatistics
University of Queensland
Graduate Certificate in Science, Statistics
University of Queensland
BSc, Biotechnology
Queensland University of Technology
Alumni Profile
Lahn Straney is obsessed with the performance of health systems and how it can be quantified.
“Particularly in global health, measurements of quality are often confounded by differences across health systems,” Lahn said. “I want to figure out how to directly measure quality so decision-makers have the opportunity – and information they need – to improve those systems.”
As a graduate student, Lahn researched methods for evaluating the performance of pediatric intensive care units in Australia and New Zealand. He discovered that the length of stay in intensive care was affected by factors other than inherent differences among patients, and that administrative differences may affect unit efficiency.
Some hospitals implement administrative scorecard systems to ensure they are providing the best possible care, but Lahn knows these can lack an evidence basis. “Scorecards and benchmark systems are great for hospitals, but sometimes they can be overly simplified,” Lahn said. “We need hard data to support whatever recommendations we make.”
At IHME, he found like-minded, quantitatively focused researchers. He’s a member of the Effective Intervention Coverage research team, helping measure how well health systems are performing and the quality of the interventions they deliver.
Currently, Lahn is working on two projects at IHME. The first uses a unique statistical approach to measure the effectiveness of contraception methods in about 25 different countries. “Effectiveness is different than efficacy,” Lahn explained. Effectiveness relates to how well a treatment works in the real world, while efficacy measures how well a treatment works in an ideal setting, such as a clinical trial or laboratory study.
The project uses survey data on contraceptive use collected from households over a five-year period. “The data allow us to make inferences about the practical effectiveness of different contraceptive methods under real-world conditions,” Lahn said.
Lahn and his IHME teammates can use these measurements in fascinating ways. “Once we know the hypothetical levels of contraceptive prevalence and effectiveness in a real-world setting, we can estimate the number of births averted through contraceptive use – and, most importantly, the maternal and infant mortality reductions attributable to modern contraception.”
Lahn is also working on a project that examines variations in neonatal deaths by county in the United States. Identifying why some counties have a higher rate of infant deaths than others, after adjusting for risk factors such as birth weight and gestational age, can help inform policies to reduce neonatal mortality.
“Traditional assessment methods provide an indication of quality for health systems – you can tell that one hospital is performing better than another,” Lahn said. “But they don’t provide any direction for improvement. Our research can quantify the variation in performance that may be attributable to specific practices of care.”
Lahn said his goal during his fellowship is to help develop ways of representing data that are significant in terms of improving health. “And that’s why IHME is such a great place to be – everyone shares that goal and brings a unique skill set to the table to help solve these important problems.”
Published Works
Lim SS‡, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H*, Amann M*, Anderson HR*, Andrews KG*, Aryee M*, Atkinson C*, Bacchus LJ*, Bahalim AN*, Balakrishnan K*, Balmes J*, Barker-Collo S*, Baxter A*, Bell ML*, Blore JD*, Blyth F*, Bonner C*, Borges G*, Bourne R*, Boussinesq M*, Brauer M*, Brooks P*, Bruce NG*, Brunekreef B*, Bryan-Hancock C*, Bucello C*, Buchbinder R*, Bull F*, Burnett RT*, Byers TE*, Calabria B*, Carapetis J*, Carnahan E*, Chafe Z*, Charlson F*, Chen H*, Chen JS*, Cheng ATA*, Child JC*, Cohen A*, Colson KE*, Cowie BC*, Darby S*, Darling S*, Davis A*, Degenhardt L*, Dentener* F, Des Jarlais DC*, Devries K*, Dherani M*, Ding EL*, Dorsey ER*, Driscoll T*, Edmond K*, Eltahir Ali S*, Engell RE*, Erwin PJ*, Fahimi S*, Falder G*, Farzadfar F*, Ferrari A*, Finucane MM*, Flaxman S*, Fowkes FGR*, Freedman G*, Freeman MK*, Gakidou E*, Ghosh S*, Giovannucci E*, Gmel G*, Graham K*, Grainger R*, Grant B*, Gunnell D*, Gutierrez HR*, Hall W*, Hoek HW*, Hogan A*, Hosgood III, HD*, Hoy D*, Hu H*, Hubbell BJ*, Hutchings SJ*, Ibeanusi SE*, Jacklyn GL*, Jasrasaria R*, Jonas JB*, Kan H*, Kanis JA*, Kassebaum N*, Kawakami N*, Khang YH*, Khatibzadeh S*, Khoo JP*, Kok C*, Laden F*, Lalloo R*, Lan Q*, Lathlean T*, Leasher JL*, Leigh J*, Li Y*, Lin JK*, Lipshultz SE*, London S*, Lozano R*, Lu Y*, Mak J*, Malekzadeh R*, Mallinger L*, Marcenes W*, March L*, Marks R*, Martin R*, McGale P*, McGrath J*, Mehta S*, Mensah GA*, Merriman TR*, Micha R*, Michaud C*, Mishra V*, Mohd Hanafiah K*, Mokdad AA*, Morawska L*, Mozaffarian D*, Murphy T*, Naghavi M*, Neal B*, Nelson PK*, Nolla JM*, Norman R*, Olives C*, Omer SB*, Orchard J*, Osborne R*, Ostro B*, Page A*, Pandey KD*, Parry CDH*, Passmore E*, Patra J*, Pearce N*, Pelizzari PM*, Petzold M*, Phillips MR*, Pope D*, Pope III, CA*, Powles J*, Rao M*, Razavi H*, Rehfuess EA*, Rehm JT*, Ritz B*, Rivara FP*, Roberts T*, Robinson C*, Rodriguez-Portales JA*, Romieu I*, Room R*, Rosenfeld LC*, Roy A*, Rushton L*, Salomon JA*, Sampson U*, Sanchez-Riera L*, Sanman E*, Sapkota A*, Seedat S*, Shi P*, Shield K*, Shivakoti R*, Singh GM*, Sleet DA*, Smith E*, Smith KR*, Stapelberg NJC*, Steenland K*, Stöckl H*, Stovner LJ*, Straif K*, Straney L*, Thurston GD*, Tran JH*, Van Dingenen R*, van Donkelaar A*, Veerman JL*, Vijayakumar L*, Weintraub R*, Weissman MM*, White RA*, Whiteford H*, Wiersma ST*, Wilkinson JD*, Williams HC*, Williams W*, Wilson N*, Woolf AD*, Yip P*, Zielinski JM*, Lopez AD†, Murray CJL†, Ezzati M.† A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. The Lancet. 2012 Dec 13; 380: 2224–2260.
Straney LD, Lim SS, Murray CJL. Disentangling the effects of risk factors and clinical care on subnational variation in early neonatal mortality in the United States. PLoS ONE. 2012;7(11):e49399. doi:10.1371/journal.pone.0049399
Related Publications & Presentations
Lim SS‡, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H*, Amann M*, Anderson HR*, Andrews KG*, Aryee M*, Atkinson C*, Bacchus LJ*, Bahalim AN*, Balakrishnan K*, Balmes J*, Barker-Collo S*, Baxter A*, Bell ML*, Blore JD*, Blyth F*, Bonner C*, Borges G*, Bourne R*, Boussinesq M*, Brauer M*, Brooks P*, Bruce NG*, Brunekreef B*, Bryan-Hancock C*, Bucello C*, Buchbinder R*, Bull F*, Burnett RT*, Byers TE*, Calabria B*, Carapetis J*, Carnahan E*, Chafe Z*, Charlson F*, Chen H*, Chen JS*, Cheng ATA*, Child JC*, Cohen A*, Colson KE*, Cowie BC*, Darby S*, Darling S*, Davis A*, Degenhardt L*, Dentener* F, Des Jarlais DC*, Devries K*, Dherani M*, Ding EL*, Dorsey ER*, Driscoll T*, Edmond K*, Eltahir Ali S*, Engell RE*, Erwin PJ*, Fahimi S*, Falder G*, Farzadfar F*, Ferrari A*, Finucane MM*, Flaxman S*, Fowkes FGR*, Freedman G*, Freeman MK*, Gakidou E*, Ghosh S*, Giovannucci E*, Gmel G*, Graham K*, Grainger R*, Grant B*, Gunnell D*, Gutierrez HR*, Hall W*, Hoek HW*, Hogan A*, Hosgood III, HD*, Hoy D*, Hu H*, Hubbell BJ*, Hutchings SJ*, Ibeanusi SE*, Jacklyn GL*, Jasrasaria R*, Jonas JB*, Kan H*, Kanis JA*, Kassebaum N*, Kawakami N*, Khang YH*, Khatibzadeh S*, Khoo JP*, Kok C*, Laden F*, Lalloo R*, Lan Q*, Lathlean T*, Leasher JL*, Leigh J*, Li Y*, Lin JK*, Lipshultz SE*, London S*, Lozano R*, Lu Y*, Mak J*, Malekzadeh R*, Mallinger L*, Marcenes W*, March L*, Marks R*, Martin R*, McGale P*, McGrath J*, Mehta S*, Mensah GA*, Merriman TR*, Micha R*, Michaud C*, Mishra V*, Mohd Hanafiah K*, Mokdad AA*, Morawska L*, Mozaffarian D*, Murphy T*, Naghavi M*, Neal B*, Nelson PK*, Nolla JM*, Norman R*, Olives C*, Omer SB*, Orchard J*, Osborne R*, Ostro B*, Page A*, Pandey KD*, Parry CDH*, Passmore E*, Patra J*, Pearce N*, Pelizzari PM*, Petzold M*, Phillips MR*, Pope D*, Pope III, CA*, Powles J*, Rao M*, Razavi H*, Rehfuess EA*, Rehm JT*, Ritz B*, Rivara FP*, Roberts T*, Robinson C*, Rodriguez-Portales JA*, Romieu I*, Room R*, Rosenfeld LC*, Roy A*, Rushton L*, Salomon JA*, Sampson U*, Sanchez-Riera L*, Sanman E*, Sapkota A*, Seedat S*, Shi P*, Shield K*, Shivakoti R*, Singh GM*, Sleet DA*, Smith E*, Smith KR*, Stapelberg NJC*, Steenland K*, Stöckl H*, Stovner LJ*, Straif K*, Straney L*, Thurston GD*, Tran JH*, Van Dingenen R*, van Donkelaar A*, Veerman JL*, Vijayakumar L*, Weintraub R*, Weissman MM*, White RA*, Whiteford H*, Wiersma ST*, Wilkinson JD*, Williams HC*, Williams W*, Wilson N*, Woolf AD*, Yip P*, Zielinski JM*, Lopez AD†, Murray CJL†, Ezzati M.† A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. The Lancet. 2012 Dec 13; 380: 2224–2260.
Straney LD, Lim SS, Murray CJL. Disentangling the effects of risk factors and clinical care on subnational variation in early neonatal mortality in the United States. PLoS ONE. 2012;7(11):e49399. doi:10.1371/journal.pone.0049399
Related News & Events
Related Research Teams & Projects
Research Team
