Measuring change in health status of older adults at the population level: The transition probability model

There is a demographic transition occurring in the developed world. An aging population creates new demands on health services [1]. Health service utilization increases, on average, across the life course, particularly in the late life course years [2, 3]. It is expected that the baby boom generation will result in a large cohort of aging individuals with different health services utilization patterns than previous generations.

Debate exists in the health services literature concerning the role age plays relative to co-morbid illness in terms of health services utilization. Is the primary explanation for increases of utilization seen in the late life course related to age or the worsening of health status and the accumulation of chronic diseases? Many studies have identified age as a critical factor in health services utilization, These studies have failed to emphasize or acknowledge that i) health services utilization is not simply an outcome of ill health and ii) health services utilization is not an inevitable outcome of aging [4]. Factors such as availability of services, as well as social and other contextual aspects may have direct and indirect influences on the use of health services [5]. For example, it has been shown that improved nutrition and exercise have the potential to improve health and to reduce health services utilization by older adults [4].

It is critical to understand, at both the clinical and population level the determinants of the transition in health service utilization in the late life course. Transitions, in this study, refer to changes in the pattern of health service utilization over time, particularly in relation to the number of health service utilization events an individual experiences over a set period of time. It is likely that this is a dynamic process influenced by a large number of factors including changes in health status. Transitions in health services utilization can be understood as events in a dynamic system occurring with measurable probability. These probabilities may vary by the age and gender of the individual.

Most studies on health service utilization in the late life course assess utilization at one point in time and hence do not capture the dynamics of transitions in utilization of health services. The existence of large administrative databases in the province of Ontario, including the healthcare records of more than 6 million residents age 65 and older, over a period of many years, provided the opportunity to conduct linked population-based studies by age and sex to study in detail healthcare utilization at the population level over time. This unique opportunity allows us to understand better the transitions in health service utilization while testing epidemiological methods that may result in clinically relevant tools.

Our study, using population-level data, indicates significant heterogeneity in the level of health services utilization among older adults. Several important trends emerge over the 9 year period. The population of men aged 90 and over who had contacts with healthcare system grew faster than the population of women in the same age group. The population in the high utilization category increased more rapidly than those in the low utilization category. Our estimated transition probability models demonstrate that when a person moves to the high utilization category, it is almost impossible to transition back to the low utilization category. High users are more likely to stay in the high category than move to the moderate category. It is not clear what is driving this constant increase over time. Finally, those in the high utilization category have a higher probability of death the next year than moderate or low users.

The magnitudes of the transition probabilities from the low and moderate utilization categories to the high category are substantial and indicate high demands on patients and their families, on professional health care providers, and on the health care system itself. The increase in health service utilization in older adults has been shown to be largely associated with poorer health outcomes [9].

A large amount of utilization is associated with medications [10]. As Nie et al. show, the number of prescriptions increases substantially for people over the age of 65 in the province of Ontario [2]. Most medications are prescribed to seniors by family physicians, and the vast majority are prescribed for the management of the common chronic diseases of aging such as osteoporosis, hypertension, osteoarthritis, and cardiovascular disease [11]. A population-based study examining the level of total outpatient pharmaceutical expenditures in the province of British Columbia showed that high-cost users of prescription drugs were older, more likely to be female, had lower incomes, and had more diagnosed co-morbidities. With regard to the transition probabilities in pharmaceutical spending level, seniors in the high-cost category in 2001 had more than a 64% chance of either continuing to be in the highest decile of drug spending in 2004 or dying within the 3-year period, and were also highly unlikely to transition to spending deciles below the median in 2004 [12].

Our results show that women have higher rates of health services utilization than men in all years and in all age groups. This is consistent with a previous study that concluded gender is an important predictor of medical care use before and after removing sex-specific utilization [13].

Our data show that mortality is consistently higher in the high utilization groups of both genders, though with dramatic differences. Males in the moderate and low categories of health service utilization had a higher probability of death the next year than females in the moderate and low utilization category. However, males in the low utilization category surviving past 95 years of age demonstrated a significant drop in mortality probability. In a previous study looking at the risk of mortality among older adults over an 8-year period, the six most salient predictors of mortality were identified as the mean annual number of hospital episodes after baseline, age, female gender, non-kin social supports, body mass, and having a history of diabetes [14]. In another study looking at older women, mortality was predicted by heart disease, stroke, low iron, diabetes, cancer (non-skin), bronchitis/emphysema, and Alzheimer's disease [15]. Other factors, such as repetitive falling, have been shown to be related to an increased likelihood of hospitalization and death [16].

Our results also depict a disconcerting trend in the increase of utilization on an annual basis. The first and third quartiles showed 30% and 28% increases over the study period, indicating a progressive escalation of baseline utilization rates in these categories. This means that, on average in each year, the cut point for the low, moderate and high use categories crept upwards. However, it is unclear what benefit is conferred by steadily increased utilization. While the data do not permit commentary on the appropriateness of the increasing levels of utilization over time, they certainly point to scenarios of problematic sustainability, particularly in an era of cost containment and fiscal restraint. It is imperative that research into determining the appropriate level of utilization be conducted as well as more precise delineation of outcomes of care in advanced age.

The reason for the increases in health service utilization over time is unclear. It is not likely a function of increased physicians supply, as Ontario has a chronic shortage of family physicians. The supply of family physicians has not kept pace with population increases. The most significant increases in utilization are associated with medication claims. Thus, it seems reasonable to hypothesize that changes in clinical practice guidelines may be implicated in the increase in utilization, as many medications require ongoing laboratory monitoring and follow up. This will be a topic for future research.

While our data shows that health service utilization increases with age, there is also evidence of resiliency in the older population, in that it identifies a growing cohort surviving into the oldest age group who were more likely to have been low users of health care services initially. On the other hand, the data suggest significant challenges in sustainability. The combination of the increasing number of people age 65 and over, with increasing probabilities of moving into the high utilization category with age, and the unlikely chance of reducing healthcare services utilization indicates that healthcare utilizations may increase exponentially with attendant cost escalation. This emphasizes the overarching importance of prevention and health promotion in the years preceding age 65 and beyond. The healthier one is entering the later years, the less likely one will require health services.

There are very few published peer-reviewed studies examining the association between age and healthcare service utilization using the transition probability matrix at a population level. The present study uses a very large sample with reliable administrative database linkages for a comprehensive array of indicators of health service utilization over a long duration. The use of administrative data provides significantly better predictions of death than variables obtained from interview data [17].

There are several potential limitations with our study. The OHIP database includes only fee-for-service claims, therefore, doctors and patients enrolled in alternative payment plans, who are still in the minority, were not captured, nor were utilization events within other sectors of the Ontario health care system (e.g., home care, physiotherapy, etc.). Exclusion of these services leads to an underestimation of overall utilization of services. The Ontario Drug Benefit database includes only the prescriptions dispensed for residents of Ontario age 65 and over and thus will not capture over the counter medication usage. Thus the models no doubt underestimate total health service utilization. However, the model captures the majority of services provided under the universal health care insurance program in Ontario. As well, the models may underestimate the numbers of people in the higher utilization categories in the later years of the study. Rather than employing fixed cut points, we left the categorization of utilization levels vary by year. Had we used an absolute cut point, we would likely have had greater numbers in the higher utilization categories.

Utilization variables which were used for categorizing the residents of Ontario into one of the low, moderate, or high utilization categories were not weighted to account for the fact that a visit to the emergency department or hospital admission may reflect a more serious illness than a visit to a family physician. Also, although this study assumes independence of date, patients often schedule multiple appointments on the same day so as to minimize the total number of trips. The number of utilizations for those residents who left the province for a period of less than two years is under-counted, which could inflate the probability of moving from the high utilization category to the moderate or low category and deflate the probability of moving from the low or moderate category to the high utilization category.

Finally, the present study did not look at health service utilization of younger persons and that they too can be high users of health services.

This pattern of findings highlights the need for a long-term strategy in aging with a focus on chronic disease management[18] This is especially pertinent as we have demonstrated that people entering the age of 65 as high users of health services are very likely to remain high users. The increasing number of nonagenarians indicates a pressing need to understand the health needs and preferences of individuals well past their actuarial life expectancy. We believe this study will be informative to clinicians as it will enable them to communicate to patients and caregivers about the ongoing need to plan for high rates of health services utilization. We believe this study will be of value to policy makers and health planners as it will assist in modeling need for service delivery. Future studies should focus on developing clinically relevant risk scores to aid clinicians in estimating risk of transitioning to higher levels of utilization. Analysis of mortality and its association with number of medications used would further contribute to our understanding of life course health service utilization patterns and mortality.