Healthcare Access and Quality Index based on mortality from causes amenable to personal health care in 195 countries and territories, 1990-2015: a novel analysis from the Global Burden of Disease Study 2015

GBD 2015 Healthcare Access and Quality Collaborators. Electronic address: cjlm@uw.edu, GBD 2015 Healthcare Access and Quality Collaborators

Abstract

Background: National levels of personal health-care access and quality can be approximated by measuring mortality rates from causes that should not be fatal in the presence of effective medical care (ie, amenable mortality). Previous analyses of mortality amenable to health care only focused on high-income countries and faced several methodological challenges. In the present analysis, we use the highly standardised cause of death and risk factor estimates generated through the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015.

Methods: We mapped the most widely used list of causes amenable to personal health care developed by Nolte and McKee to 32 GBD causes. We accounted for variations in cause of death certification and misclassifications through the extensive data standardisation processes and redistribution algorithms developed for GBD. To isolate the effects of personal health-care access and quality, we risk-standardised cause-specific mortality rates for each geography-year by removing the joint effects of local environmental and behavioural risks, and adding back the global levels of risk exposure as estimated for GBD 2015. We employed principal component analysis to create a single, interpretable summary measure-the Healthcare Quality and Access (HAQ) Index-on a scale of 0 to 100. The HAQ Index showed strong convergence validity as compared with other health-system indicators, including health expenditure per capita (r=0·88), an index of 11 universal health coverage interventions (r=0·83), and human resources for health per 1000 (r=0·77). We used free disposal hull analysis with bootstrapping to produce a frontier based on the relationship between the HAQ Index and the Socio-demographic Index (SDI), a measure of overall development consisting of income per capita, average years of education, and total fertility rates. This frontier allowed us to better quantify the maximum levels of personal health-care access and quality achieved across the development spectrum, and pinpoint geographies where gaps between observed and potential levels have narrowed or widened over time.

Findings: Between 1990 and 2015, nearly all countries and territories saw their HAQ Index values improve; nonetheless, the difference between the highest and lowest observed HAQ Index was larger in 2015 than in 1990, ranging from 28·6 to 94·6. Of 195 geographies, 167 had statistically significant increases in HAQ Index levels since 1990, with South Korea, Turkey, Peru, China, and the Maldives recording among the largest gains by 2015. Performance on the HAQ Index and individual causes showed distinct patterns by region and level of development, yet substantial heterogeneities emerged for several causes, including cancers in highest-SDI countries; chronic kidney disease, diabetes, diarrhoeal diseases, and lower respiratory infections among middle-SDI countries; and measles and tetanus among lowest-SDI countries. While the global HAQ Index average rose from 40·7 (95% uncertainty interval, 39·0-42·8) in 1990 to 53·7 (52·2-55·4) in 2015, far less progress occurred in narrowing the gap between observed HAQ Index values and maximum levels achieved; at the global level, the difference between the observed and frontier HAQ Index only decreased from 21·2 in 1990 to 20·1 in 2015. If every country and territory had achieved the highest observed HAQ Index by their corresponding level of SDI, the global average would have been 73·8 in 2015. Several countries, particularly in eastern and western sub-Saharan Africa, reached HAQ Index values similar to or beyond their development levels, whereas others, namely in southern sub-Saharan Africa, the Middle East, and south Asia, lagged behind what geographies of similar development attained between 1990 and 2015.

Interpretation: This novel extension of the GBD Study shows the untapped potential for personal health-care access and quality improvement across the development spectrum. Amid substantive advances in personal health care at the national level, heterogeneous patterns for individual causes in given countries or territories suggest that few places have consistently achieved optimal health-care access and quality across health-system functions and therapeutic areas. This is especially evident in middle-SDI countries, many of which have recently undergone or are currently experiencing epidemiological transitions. The HAQ Index, if paired with other measures of health-system characteristics such as intervention coverage, could provide a robust avenue for tracking progress on universal health coverage and identifying local priorities for strengthening personal health-care quality and access throughout the world.

Funding: Bill & Melinda Gates Foundation.

Copyright © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Figures

Figure 1
Figure 1
Map of HAQ Index values, by decile, in 1990 (A) and 2015 (B) Deciles were based on the distribution of HAQ Index values in 2015 and then were applied for 1990. HAQ Index = Healthcare Access and Quality Index. ATG=Antigua and Barbuda. VCT=Saint Vincent and the Grenadines. LCA=Saint Lucia. TTO=Trinidad and Tobago. TLS=Timor-Leste. FSM=Federated States of Micronesia.
Figure 2
Figure 2
Performance of the HAQ Index and 25 individual causes by the fourth SDI quartile (A), third SDI quartile (B), second SDI quartile (C), and first SDI quartile (D) in 2015 In addition to the HAQ Index, all causes presented in this figure are scaled 0 to 100, with 100 being the “best” value (ie, lowest observed age-standardised risk-standardised mortality rate by cause) and 0 being the “worst value” (ie, highest observed age-standardised risk-standardised mortality rate by cause) between 1990 and 2015. Within each SDI quartile, countries and geographies are ordered by their HAQ Index in 2015. HAQ Index=Healthcare Access and Quality Index. SDI=Socio-demographic Index.
Figure 2
Figure 2
Performance of the HAQ Index and 25 individual causes by the fourth SDI quartile (A), third SDI quartile (B), second SDI quartile (C), and first SDI quartile (D) in 2015 In addition to the HAQ Index, all causes presented in this figure are scaled 0 to 100, with 100 being the “best” value (ie, lowest observed age-standardised risk-standardised mortality rate by cause) and 0 being the “worst value” (ie, highest observed age-standardised risk-standardised mortality rate by cause) between 1990 and 2015. Within each SDI quartile, countries and geographies are ordered by their HAQ Index in 2015. HAQ Index=Healthcare Access and Quality Index. SDI=Socio-demographic Index.
Figure 2
Figure 2
Performance of the HAQ Index and 25 individual causes by the fourth SDI quartile (A), third SDI quartile (B), second SDI quartile (C), and first SDI quartile (D) in 2015 In addition to the HAQ Index, all causes presented in this figure are scaled 0 to 100, with 100 being the “best” value (ie, lowest observed age-standardised risk-standardised mortality rate by cause) and 0 being the “worst value” (ie, highest observed age-standardised risk-standardised mortality rate by cause) between 1990 and 2015. Within each SDI quartile, countries and geographies are ordered by their HAQ Index in 2015. HAQ Index=Healthcare Access and Quality Index. SDI=Socio-demographic Index.
Figure 2
Figure 2
Performance of the HAQ Index and 25 individual causes by the fourth SDI quartile (A), third SDI quartile (B), second SDI quartile (C), and first SDI quartile (D) in 2015 In addition to the HAQ Index, all causes presented in this figure are scaled 0 to 100, with 100 being the “best” value (ie, lowest observed age-standardised risk-standardised mortality rate by cause) and 0 being the “worst value” (ie, highest observed age-standardised risk-standardised mortality rate by cause) between 1990 and 2015. Within each SDI quartile, countries and geographies are ordered by their HAQ Index in 2015. HAQ Index=Healthcare Access and Quality Index. SDI=Socio-demographic Index.
Figure 3
Figure 3
Comparison of 1990 and 2015 HAQ Index estimates, with uncertainty, by country or territory Geographies with the largest improvement in the HAQ Index from 1990 to 2015 are labelled. All countries and territories are colour-coded by SDI quintile in 2015. HAQ Index=Healthcare Access and Quality Index. SDI=Socio-demographic Index.
Figure 4
Figure 4
Defining the HAQ Index frontier on the basis of SDI Each circle represents the HAQ Index and level of SDI for a given geography-year, and circles are colour-coded by year from 1990 to 2015. The black line represents the HAQ Index frontier, or the highest observed HAQ Index value, at a given level of SDI across years. HAQ Index=Healthcare Access and Quality Index. SDI=Socio-demographic Index.
Figure 5
Figure 5
Map of the gap between observed HAQ Index and frontier values in 1990 (A) and 2015 (B) Difference in observed HAQ Index and frontier values were the highest levels achieved by geographies of similar SDI in a given year. HAQ Index=Healthcare Access and Quality Index. SDI=Socio-demographic Index. ATG=Antigua and Barbuda. VCT=Saint Vincent and the Grenadines. LCA=Saint Lucia. TTO=Trinidad and Tobago. TLS=Timor-Leste. FSM=Federated States of Micronesia.

References

    1. United Nations . Transforming our World: the 2030 Agenda for Sustainable Development. UN; New York, NY, USA: 2015.
    1. Tobias M, Yeh L-C. How much does health care contribute to health gain and to health inequality? Trends in amenable mortality in New Zealand 1981–2004. Aust N Z J Public Health. 2009;33:70–78.
    1. Gay JG, Paris V, Devaux M, de Looper M. Mortality Amenable to Health Care in 31 OECD Countries. Organisation for Economic Co-operation and Development; Paris: 2011. (accessed Dec 23, 2016).
    1. Nolte E, McKee M. Does healthcare save lives? Avoidable mortality revisited. Nuffield Trust; London, UK: 2004.
    1. Murray CJ, Lopez AD. On the comparable quantification of health risks: lessons from the Global Burden of Disease Study. Epidemiol Camb Mass. 1999;10:594–605.
    1. Rutstein DD, Berenberg W, Chalmers TC. Measuring the Quality of Medical Care. N Engl J Med. 1976;294:582–588.
    1. Charlton JR, Velez R. Some international comparisons of mortality amenable to medical intervention. Br Med J Clin Res Ed. 1986;292:295–301.
    1. Holland W. Avoidable death as a measure of quality. Int J Qual Health Care. 1990;2:227–233.
    1. Nolte E, McKee M. Measuring the health of nations: analysis of mortality amenable to health care. BMJ. 2003;327:1129.
    1. Treurniet HF, Boshuizen HC, Harteloh PPM. Avoidable mortality in Europe (1980–1997): a comparison of trends. J Epidemiol Community Health. 2004;58:290–295.
    1. Nolte E, McKee M. Variations in amenable mortality—trends in 16 high-income nations. Health Policy Amst Neth. 2011;103:47–52.
    1. Petrie D, Tang KK. Relative health performance in BRICS over the past 20 years: the winners and losers. Bull World Health Organ. 2014;92:396–404.
    1. McKeown T. The role of medicine: dream, mirage or nemesis? Blackwell; Oxford, UK: 1979.
    1. Illich I. Medical Nemesis: the Appropriation of Health. Calder and Boyars; London, UK: 1975.
    1. McKinlay JB, McKinlay SM. The questionable contribution of medical measures to the decline of mortality in the United States in the twentieth century. Milbank Mem Fund Q Health Soc. 1977;55:405–428.
    1. Mackenbach JP. The contribution of medical care to mortality decline: McKeown revisited. J Clin Epidemiol. 1996;49:1207–1213.
    1. Dye C, Fengzeng Z, Scheele S, Williams B. Evaluating the impact of tuberculosis control: number of deaths prevented by short-course chemotherapy in China. Int J Epidemiol. 2000;29:558–564.
    1. Borgdorff MW, Floyd K, Broekmans JF. Interventions to reduce tuberculosis mortality and transmission in low- and middle-income countries. Bull World Health Organ. 2002;80:217–227.
    1. Koenig MA, Khan MA, Wojtyniak B. Impact of measles vaccination on childhood mortality in rural Bangladesh. Bull World Health Organ. 1990;68:441–447.
    1. Campbell OM, Graham WJ. Strategies for reducing maternal mortality: getting on with what works. Lancet. 2006;368:1284–1299.
    1. Adam T, Lim SS, Mehta S. Cost effectiveness analysis of strategies for maternal and neonatal health in developing countries. BMJ. 2005;331:1107.
    1. Richards MA, Stockton D, Babb P, Coleman MP. How many deaths have been avoided through improvements in cancer survival? BMJ. 2000;320:895–898.
    1. Stockton D, Davies T, Day N, McCann J. Retrospective study of reasons for improved survival in patients with breast cancer in east Anglia: earlier diagnosis or better treatment. BMJ. 1997;314:472–475.
    1. Ebrahim S, Harwood R. Stroke: Epidemiology, Evidence and Clinical Practice. 2nd edn. Oxford University Press; Oxford; New York: 1999.
    1. Nolte E, Bain C, McKee M. Diabetes as a tracer condition in international benchmarking of health systems. Diabetes Care. 2006;29:1007–1011.
    1. Tonelli M, Wiebe N, Culleton B. Chronic kidney disease and mortality risk: a systematic review. J Am Soc Nephrol. 2006;17:2034–2047.
    1. Rutstein DD, Berenberg W, Chalmers TC, Fishman AP, Perrin EB, Zuidema GD. Measuring the quality of medical care: second revision of tables of indexes. N Engl J Med. 1980;302:1146.
    1. Holland WW. The ‘avoidable death’ guide to Europe. Health Policy. 1986;6:115–117.
    1. Mackenbach JP, Looman CW, Kunst AE, Habbema JD, van der Maas PJ. Post-1950 mortality trends and medical care: gains in life expectancy due to declines in mortality from conditions amenable to medical intervention in The Netherlands. Soc Sci Med. 1988;27:889–894.
    1. Nolte E, McKee CM. Measuring the health of nations: updating an earlier analysis. Health Aff (Millwood) 2008;27:58–71.
    1. Nolte E, McKee CM. In amenable mortality—deaths avoidable through health care—progress in the US lags that of three European countries. Health Aff (Millwood) 2012;31:2114–2122.
    1. Manuel DG, Mao Y. Avoidable Mortality in the United States and Canada, 1980–1996. Am J Public Health. 2002;92:1481–1484.
    1. Niti M, Ng TP. Temporal trends and ethnic variations in amenable mortality in Singapore 1965-1994: the impact of health care in transition. Int J Epidemiol. 2001;30:966–973.
    1. OECD . Health at a Glance: Europe 2016. State of the Health in the EU Cycle. Organisation for Economic Cooperation and Development; Paris, France: 2016.
    1. Nolte E, Scholz R, Shkolnikov V, McKee M. The contribution of medical care to changing life expectancy in Germany and Poland. Soc Sci Med. 2002;55:1905–1921.
    1. Kelson M, Farebrother M. The effect of inaccuracies in death certification and coding practices in the European Economic Community (EEC) on international cancer mortality statistics. Int J Epidemiol. 1987;16:411–414.
    1. Mackenbach JP. Health care expenditure and mortality from amenable conditions in the European Community. Health Policy Amst Neth. 1991;19:245–255.
    1. Poikolainen K, Eskola J. Health services resources and their relation to mortality from causes amenable to health care intervention: a cross-national study. Int J Epidemiol. 1988;17:86–89.
    1. Pampalon R. Avoidable mortality in Québec and its regions. Soc Sci Med 1982. 1993;37:823–831.
    1. Mackenbach JP, Kunst AE, Looman CW, Habbema JD, van der Maas PJ. Regional differences in mortality from conditions amenable to medical intervention in The Netherlands: a comparison of four time periods. J Epidemiol Community Health. 1988;42:325–332.
    1. Harris AR, Thomas SH, Fisher GA, Hirsch DJ. Murder and medicine: the lethality of criminal assault 1960-1999. Homicide Stud. 2002;6:128–166.
    1. Lecky F, Woodford M, Yates D. Trends in trauma care in England and Wales 1989–97. Lancet. 2000;355:1771–1775.
    1. Modig K, Andersson T, Drefahl S, Ahlbom A. Age-specific trends in morbidity, mortality and case-fatality from cardiovascular disease, myocardial infarction and stroke in advanced age: evaluation in the Swedish population. PLoS One. 2013;8:e64928.
    1. Endreseth BH, Romundstad P, Myrvold HE, Bjerkeset T, Wibe A, The Norwegian Rectal Cancer Group Rectal cancer treatment of the elderly. Colorectal Dis. 2006;8:471–479.
    1. The Primary Health Care Performance Initiative (PHCPI) Coverage Index. Sept 17, 2015. (accessed Dec 23, 2016).
    1. International Labour Organization . World Social Security Report 2010/2011: Providing coverage times of crisis and beyond. International Labour Organization; Geneva, Switzerland: 2010.
    1. Wang H, Naghavi M, Allen C. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1459–1544.
    1. Forouzanfar MH, Afshin A, Alexander LT. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1659–1724.
    1. Vos T, Allen C, Arora M. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1545–1602.
    1. Kassebaum NJ, Arora M, Barber RM. Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1603–1658.
    1. Naghavi M, Makela S, Foreman K, O'Brien J, Pourmalek F, Lozano R. Algorithms for enhancing public health utility of national causes-of-death data. Popul Health Metr. 2010;8:9.
    1. Stevens GA, Alkema L, Black RE. Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement. Lancet. 2016;388:e19–e23.
    1. Lozano R, Naghavi M, Foreman K. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2095–2128.
    1. Forouzanfar MH, Alexander L, Anderson HR. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;386:2287–2323.
    1. Lim SS, Vos T, Flaxman AD. 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. Lancet. 2012;380:2224–2260.
    1. Lim SS, Allen K, Bhutta ZA. Measuring the health-related Sustainable Development Goals in 188 countries: a baseline analysis from the Global Burden of Disease Study 2015. Lancet. 2016;388:1813–1850.
    1. WHO Global Health Observatory. World Health Organization. (accessed Sept 10, 2015).
    1. Bogetoft P, Otto L. Benchmarking with data envelopment analysis, stochastic frontier analysis, and R. 2011 edition. Springer; New York, NY, USA: 2013.
    1. Hwang S-N, Lee H-S, Zhu J. Handbook of operations analytics using data envelopment analysis. Springer; Berlin: 2016.
    1. Smith OK, Cortez RA, Tandon A, Nagpal S, Cotlear D. Going universal: how 24 developing countries are implementing universal health coverage reforms from the bottom up. The World Bank; 2015. (accessed Dec 3, 2016).
    1. IAEG-SDGs . Report of the Inter-Agency and Expert Group on the Sustainable Development Goal Indicators. Economic and Social Council; 2016. (accessed Nov 18, 2016).
    1. McKee M, Nolte E. Health systems in low- and middle-income countries. Oxford University Press; Oxford, UK: 2011. Measuring and evaluating performance.
    1. Risso-Gill I, Balabanova D, Majid F. Understanding the modifiable health systems barriers to hypertension management in Malaysia: a multi-method health systems appraisal approach. BMC Health Serv Res. 2015;15:254.
    1. Burki TK. Radiotherapy challenges in Uganda. Lancet Oncol. 2016;17:e185.
    1. Schoen C, Osborn R, Huynh PT. Primary Care And Health-system performance: Adults' Experiences In Five Countries. Health Aff (Millwood) 2004 published online Oct 28.
    1. Bartlett JA, DeMasi R, Quinn J, Moxham C, Rousseau F. Overview of the effectiveness of triple combination therapy in antiretroviral-naive HIV-1 infected adults. AIDS. 2001;15:1369–1377.
    1. Baird JK. Effectiveness of antimalarial drugs. N Engl J Med. 2005;352:1565–1577.
    1. Group IAS. Artesunate combinations for treatment of malaria: meta-analysis. Lancet. 2004;363:9–17.
    1. Strader DB, Wright T, Thomas DL, Seeff LB. Diagnosis, management, and treatment of hepatitis C. Hepatology. 2004;39:1147–1171.
    1. WHO . The World Health Report 2000. Health systems: improving performance. World Health Organization; Geneva, Switzerland: 2000.
    1. McKee M. The World Health Report 2000: 10 years on. Health Policy Plan. 2010;25:346–348.
    1. Morris S, Hunter RM, Ramsay AIG. Impact of centralising acute stroke services in English metropolitan areas on mortality and length of hospital stay: difference-in-differences analysis. BMJ. 2014;349:g4757.
    1. Merali HS, Lipsitz S, Hevelone N. Audit-identified avoidable factors in maternal and perinatal deaths in low resource settings: a systematic review. BMC Pregnancy Childbirth. 2014;14:280.
    1. Jamison DT, Summers LH, Alleyne G. Global health 2035: a world converging within a generation. Lancet. 2013;382:1898–1955.
    1. Mackenbach JP, McKee M. A comparative analysis of health policy performance in 43 European countries. Eur J Public Health. 2013;23:195–201.
    1. Halstead S, Walsh J, Warren K. Good health at low cost. Rockefeller Foundation; Bellagio: 1985.
    1. Campbell DT, Fiske DW. Convergent and discriminant validation by the multitrait-multimethod matrix. Psychol Bull. 1959;56:81–105.
    1. Carmines EG, Zeller RA. Reliability and Validity Assessment. SAGE Publications; Beverly Hills, CA, USA and London, UK: 1979.
    1. McCarthy D, Radley D, Hayes S. Aiming higher: results from a scorecard on state health-system performance. 2015 Edition. The Commonwealth Fund; Washington DC: 2015.

Source: PubMed

Sponsors en medewerkers

Medische omstandigheden

Geneesmiddelinterventies

3
Abonneren