Innovation in Evaluating the Impact of Integrated Service-Delivery: The Integra Indexes of HIV and Reproductive Health Integration.

BACKGROUND: The body of knowledge on evaluating complex interventions for integrated healthcare lacks both common definitions of 'integrated service delivery' and standard measures of impact. Using multiple data sources in combination with statistical modelling the aim of this study is to develop a measure of HIV-reproductive health (HIV-RH) service integration that can be used to assess the degree of service integration, and the degree to which integration may have health benefits to clients, or reduce service costs. METHODS AND FINDINGS: Data were drawn from the Integra Initiative's client flow (8,263 clients in Swaziland and 25,539 in Kenya) and costing tools implemented between 2008-2012 in 40 clinics providing RH services in Kenya and Swaziland. We used latent variable measurement models to derive dimensions of HIV-RH integration using these data, which quantified the extent and type of integration between HIV and RH services in Kenya and Swaziland. The modelling produced two clear and uncorrelated dimensions of integration at facility level leading to the development of two sub-indexes: a Structural Integration Index (integrated physical and human resource infrastructure) and a Functional Integration Index (integrated delivery of services to clients). The findings highlight the importance of multi-dimensional assessments of integration, suggesting that structural integration is not sufficient to achieve the integrated delivery of care to clients--i.e. "functional integration". CONCLUSIONS: These Indexes are an important methodological contribution for evaluating complex multi-service interventions. They help address the need to broaden traditional evaluations of integrated HIV-RH care through the incorporation of a functional integration measure, to avoid misleading conclusions on its 'impact' on health outcomes. This is particularly important for decision-makers seeking to promote integration in resource constrained environments.

Institutional delivery in rural India: the relative importance of accessibility and economic status.

BACKGROUND: Skilled attendance at delivery is an important indicator in monitoring progress towards Millennium Development Goal 5 to reduce the maternal mortality ratio by three quarters between 1990 and 2015. In addition to professional attention, it is important that mothers deliver their babies in an appropriate setting, where life saving equipment and hygienic conditions can also help reduce the risk of complications that may cause death or illness to mother and child. Over the past decade interest has grown in examining influences on care-seeking behavior and this study investigates the determinants of place of delivery in rural India, with a particular focus on assessing the relative importance of community access and economic status. METHODS: A descriptive analysis of trends in place of delivery using data from two national representative sample surveys in 1992 and 1998 is followed by a two-level (child/mother and community) random-effects logistical regression model using the second survey to investigate the determinants. RESULTS: In this investigation of institutional care seeking for child birth in rural India, economic status emerges as a more crucial determinant than access. Economic status is also the strongest influence on the choice between a private-for-profit or public facility amongst institutional births. CONCLUSION: Greater availability of obstetric services will not alone solve the problem of low institutional delivery rates. This is particularly true for the use of private-for-profit institutions, in which the distance to services does not have a significant adjusted effect. In the light of these findings a focus on increasing demand for existing services seems the most rational action. In particular, financial constraints need to be addressed, and results support current trials of demand side financing in India.

Long-term survival of intensive care and hospital patient cohorts compared with the general Australian population: a relative survival approach.

RATIONALE: Long-term post-hospital survival of intensive care cohorts has been poorly characterized. The relative survival of septic and non-septic intensive care and general hospital patient cohorts, compared with the Australian population, was determined. METHODS: A retrospective cohort study in a tertiary-level adult intensive care. Index intensive care admissions, July 1993 to June 1999, with sepsis and surviving hospital, constituted the intensive care sepsis cohort; residual patients, the intensive care non-sepsis cohort. Hospital cohorts, infected and non-infected, and Charlson Comorbidity Score (CCS) were obtained electronically, from ICD-9 codes. Follow-up was until death, or for a minimum of 4.2 years, to a maximum of 9.6 years. Time-to-death was sourced from the State registry. Relative survival was determined using the Esteve method and excess hazard modelled by covariate adjusted generalized linear models. RESULTS: The ICU sepsis (n = 224) and non-sepsis (n = 1798) cohorts were of mean (standard deviation, SD) age of 63.2 (15.6) and 59.8 (18.9) years; with co-morbidity score 1.2 (1.3) and 0.5 (0.9) respectively. Hospitalized infected (n = 8455) and non-infected (n = 51,152) cohorts were of age 56.5 (22.2) and 52.2 (20.9) years; co-morbidity score 0.4 (0.9) and 0.3 (0.9) respectively. Relative survival of all cohorts was less than the Australian population; for the two intensive care cohorts, progressive relative survival decline suggested a perpetuating excess mortality. Both age and CCS increments were associated with progressive increases in excess hazard. There was a reduced hazard for intensive care sepsis versus non-sepsis cohorts; 0.42 [95% confidence interval (CI): 0.25-0.71, P = 0.001] and surgical versus medical patients, 0.64 (95% CI: 0.50-0.84, P = 0.001); and an excess hazard for men, 1.38 (95% CI: 1.08-1.74, P = 0.009). CONCLUSIONS: Adverse long-term survival of intensive care and hospital patients was demonstrated. For hospital patients there was additional infection-related mortality risk, not evident for ICU patients after case mix control.

An estimate of the veteran population in England: based on data from the 2007 Adult Psychiatric Morbidity Survey.

BACKGROUND: The health and well-being of military veterans has recently generated much media and political interest. Estimating the current and future size of the veteran population is important to the planning and allocation of veteran support services. METHODS: Data from a 2007 nationally representative residential survey of England (the Adult Psychiatric Morbidity Survey) were extrapolated to the whole population to estimate the number of veterans currently residing in private households in England. This population was projected forward in two ten-year blocks up to 2027 using a current life table. RESULTS: It was estimated that in 2007, 3,771,534 (95% CI: 2,986,315-4,910,205) veterans were living in residential households in England. By 2027, this figure was predicted to decline by 50.4 per cent, mainly due to large reductions in the number of veterans in the older age groups (65-74 and 75+ years). CONCLUSION: Approximately three to five million veterans are currently estimated to be living in the community in England. As the proportion of National Service veterans reduces with time, the veteran population is expected to halve over the next 20 years.

Fertility in Kenya and Uganda: a comparative study of trends and determinants.

Between 1980 and 2000 total fertility in Kenya fell by about 40 per cent, from some eight births per woman to around five. During the same period, fertility in Uganda declined by less than 10 per cent. An analysis of the proximate determinants shows that the difference was due primarily to greater contraceptive use in Kenya, though in Uganda there was also a reduction in pathological sterility. The Demographic and Health Surveys show that women in Kenya wanted fewer children than those in Uganda, but that in Uganda there was also a greater unmet need for contraception. We suggest that these differences may be attributed, in part at least, first, to the divergent paths of economic development followed by the two countries after Independence; and, second, to the Kenya Government's active promotion of family planning through the health services, which the Uganda Government did not promote until 1995.

Regression models for relative survival.

Four approaches to estimating a regression model for relative survival using the method of maximum likelihood are described and compared. The underlying model is an additive hazards model where the total hazard is written as the sum of the known baseline hazard and the excess hazard associated with a diagnosis of cancer. The excess hazards are assumed to be constant within pre-specified bands of follow-up. The likelihood can be maximized directly or in the framework of generalized linear models. Minor differences exist due to, for example, the way the data are presented (individual, aggregated or grouped), and in some assumptions (e.g. distributional assumptions). The four approaches are applied to two real data sets and produce very similar estimates even when the assumption of proportional excess hazards is violated. The choice of approach to use in practice can, therefore, be guided by ease of use and availability of software. We recommend using a generalized linear model with a Poisson error structure based on collapsed data using exact survival times. The model can be estimated in any software package that estimates GLMs with user-defined link functions (including SAS, Stata, S-plus, and R) and utilizes the theory of generalized linear models for assessing goodness-of-fit and studying regression diagnostics.

Health inequalities in the older population: the role of personal capital, social resources and socio-economic circumstances.

Older people now constitute the majority of those with health problems in developed countries so an understanding of health variations in later life is increasingly important. In this paper, we use data from three rounds of the Health Survey for England, a large nationally representative sample, to analyse variations in the health of adults aged 65-84 by indicators of attributes acquired in childhood and young adulthood, termed personal capital; and by current social resources and current socio-economic circumstances, while controlling for smoking behaviour and age. We used six indicators of health status in the analysis, four based on self-reports and two based on nurse collected data, which we hypothesised would identify different dimensions of health. Results showed that socio-economic indicators, particularly receipt of income support (a marker of poverty) were most consistently associated with raised odds of poor health outcomes. Associations between marital status and health were in some cases not in the expected direction. This may reflect bias arising from exclusion of the institutional population (although among those under 85 the proportion in institutions is very low) but merits further investigation, especially as the marital status composition of the older population is changing. Analysis of deviance showed that social resources (marital status and social support) had the greatest effect on the indicator of psychological health (GHQ) and also contributed significantly to variation in self-rated health, but among women not to variation in taking three or more medicines and among men not to self-reported long-standing illnesses. Smoking, in contrast, was much more strongly associated with these indicators than with self-rated health. These results are consistent with the view that self-rated health may provide a holistic indicator of health in the sense of well-being, whereas measures such as taking prescribed medications may be more indicative of specific morbidities. The results emphasise again the need to consider both socio-economic and socio-psychological influences on later life health.