Association between community health center and rural health clinic presence and county-level hospitalization rates for ambulatory care sensitive conditions: an analysis across eight US states

<p>Abstract</p> <p>Background</p> <p>Federally qualified community health centers (CHCs) and rural health clinics (RHCs) are intended to provide access to care for vulnerable populations. While some research has explored the effects of CHCs on population health, little information exists regarding RHC effects. We sought to clarify the contribution that CHCs and RHCs may make to the accessibility of primary health care, as measured by county-level rates of hospitalization for ambulatory care sensitive (ACS) conditions.</p> <p>Methods</p> <p>We conducted an ecologic analysis of the relationship between facility presence and county-level hospitalization rates, using 2002 discharge data from eight states within the US (579 counties). Counties were categorized by facility availability: CHC(s) only, RHC(s) only, both (CHC and RHC), and neither. US Agency for Healthcare Research and Quality definitions were used to identify ACS diagnoses. Discharge rates were based on the individual's county of residence and were obtained by dividing ACS hospitalizations by the relevant county population. We calculated ACS rates separately for children, working age adults, and older individuals, and for uninsured children and working age adults. To ensure stable rates, we excluded counties having fewer than 1,000 residents in the child or working age adult categories, or 500 residents among those 65 and older. Multivariate Poisson analysis was used to calculate adjusted rate ratios.</p> <p>Results</p> <p>Among working age adults, rate ratio (RR) comparing ACS hospitalization rates for CHC-only counties to those of counties with neither facility was 0.86 (95% Confidence Interval, CI, 0.78–0.95). Among older adults, the rate ratio for CHC-only counties compared to counties with neither facility was 0.84 (CI 0.81–0.87); for counties with both CHC and RHC present, the RR was 0.88 (CI 0.84–0.92). No CHC/RHC effects were found for children. No effects were found on estimated hospitalization rates among uninsured populations.</p> <p>Conclusion</p> <p>Our results suggest that CHCs and RHCs may play a useful role in providing access to primary health care. Their presence in a county may help to limit the county's rate of hospitalization for ACS diagnoses, particularly among older people.</p

Community Care Network: Health Coach Program

The Community Care Network is a unique program at The College of Wooster in which students interested in pursuing medical school are paired with patients in the local community through a partnership with Wooster Community Hospital. This initiative helps to develop practical approaches for improving the health of patients by reducing the frequency of re-hospitalization through preventative measures. The students begin with a one-semester training seminar followed by an internship in which the student, under the supervision of hospital staff, provides weekly visits to patients in their homes, checking on their physical and emotional well-being, and discussing lifestyle choices that impact their health. In the academic year 2012-2013, the Community Care Network was launched. A total of 25 students are selected every semester to complete a one-semester seminar taught by health care professionals from WCH on a weekly basis. For 14 weeks, students learn about diseases, illnesses, specialty areas such as pulmonary and cardiology, and about the health care system. During this time, they also learn how to take blood pressure and other vital signs as well as develop an understanding of frequently prescribed medications for diseases like diabetes and congestive heart failure. Upon successful completion, student health coaches are trained by home health care nurses who pair them with patients accepted in the program. Students then meet weekly with their assigned patient and develop a relationship with the focus of guiding the patient to meet their health care plan goals. From the beginning, this program has been mutually beneficial to both the college and hospital. Now in its fourth year, more than 250 students have successfully completed the seminar and have become active health coaches. Each health coach meets with a team of health care professionals on a weekly basis to discuss his or her patient, a requirement of the program. They are considered an equal member of the health care team. The outcomes for students and patients alike have been astounding. The Community Care Network key players, Robyn Laditka, pre-health advisor at The College of Wooster, and AlexSandra Davis, RN director of the Community Care Network at WCH, report several sets of outcomes since the inception of the Community Care Network. Students gain valuable direct service experiences now required to enter most health care professions, but that is only the starting point. They gain insight that doctors can't possibly know about by going into the patients' homes. They learn about the issues of poverty, hoarding, and multiple prescriptions to keep track of on a daily basis. They learn to build relationships to gain the trust of the patients. The hospital experiences fewer hospitalizations and unnecessary visits to the emergency room.AUTHOR AFFILIATION: Robyn Laditka, Pre-Health Advisor, the College of Wooster, [email protected] (Corresponding Author); Alexsandra Davis, RN Director, Community Health Network, Wooster Community Hospital.The Community Care Network is an unique program at The College of Wooster in which students interested in pursuing medical school are paired with patients in the local community through a partnership with Wooster Community Hospital. This initiative helps develop practical approaches to improve the health of patients by reducing the frequency of re-hospitalization through preventative measures. The students begin with a one-semester training seminar followed by an internship in which the student, under the supervision of hospital staff, provides weekly visits to patients in their homes, checking on their physical and emotional well-being and discussing lifestyle choices that impact their health

Using hospitalization for ambulatory care sensitive conditions to measure access to primary health care: an application of spatial structural equation modeling

BACKGROUND: In data commonly used for health services research, a number of relevant variables are unobservable. These include population lifestyle and socio-economic status, physician practice behaviors, population tendency to use health care resources, and disease prevalence. These variables may be considered latent constructs of many observed variables. Using health care data from South Carolina, we show an application of spatial structural equation modeling to identify how these latent constructs are associated with access to primary health care, as measured by hospitalizations for ambulatory care sensitive conditions. We applied the confirmatory factor analysis approach, using the Bayesian paradigm, to identify the spatial distribution of these latent factors. We then applied cluster detection tools to identify counties that have a higher probability of hospitalization for each of the twelve adult ambulatory care sensitive conditions, using a multivariate approach that incorporated the correlation structure among the ambulatory care sensitive conditions into the model. RESULTS: For the South Carolina population ages 18 and over, we found that counties with high rates of emergency department visits also had less access to primary health care. We also observed that in those counties there are no community health centers. CONCLUSION: Locating such clusters will be useful to health services researchers and health policy makers; doing so enables targeted policy interventions to efficiently improve access to primary care

Association of type of birth attendant and place of delivery on infant mortality in sub-Saharan Africa

Objective: To examine the association between type of birth attendant and place of delivery, and infant mortality (IM).Methods: This cross-sectional study used self-reported data from the Demographic Health Surveys for women in Ghana, Kenya, and Sierra Leone. Logistic regression estimated odds ratios (ORs) and95% confidence intervals.Results: In Ghana and Sierra Leone, odds of IM were higher for women who delivered at a health facility versus women who delivered at a household residence (OR=3.18, 95% confidence interval, CI: 1.29-7.83, p=0.01 and OR=1.62, 95% CI: 1.15-2.28, p=0.01, respectively). Compared to the use of health professionals, the use of birth attendants for assistance with delivery was not significantly associated with IM for women in Ghana or Sierra Leone (OR=2.17, 95% CI: 0.83-5.69, p=0.12 and OR=1.25, 95% CI: 0.92-1.70, p=0.15, respectively). In Kenya, odds of IM, though nonsignificant, were lower for women who used birth attendants than those who used health professionals to assist with delivery (OR=0.85, 95% CI: 0.51-1.41, p=0.46), and higher with delivery at a health facility versus a household residence (OR=1.29, 95% CI: 0.81-2.03, p=0.28).Conclusions: Women in Ghana and Sierra Leone who delivered at a health facility had statistically significant increased odds of IM. Birth attendant type-IM associations were not statistically significant.Future research should consider culturally-sensitive interventions to improve maternal health and help reduce IM.Keywords: birth attendant, infant mortality, sub-Saharan Afric

Duration Data from the National Long-Term Care Survey: Foundation for a Dynamic Multiple-Indicator Model of ADL Dependency

This report describes preparation of data from the National Long-Term Care Survey (NLTCS) fur use in a dynamic multiple-indicator model of dependency in Activities of Daily Living (ADLs). The data set described makes use of all functional status information available across four NLTCS waves for six ADLs, including information from screening interviews, detailed interviews in the community, and institutional interviews. Importantly, it also captures all available information elicited from respondents about the *duration* of any impairment in these ADLs. The data was prepared as described in this report to enable the calculation of improved estimates of the probabilities that an older individual will transition from one functional status state to another in any of six ADLs. These probabilities can then be used to improve estimates of active life expectancy

Stochastic Modeling of Active Life and Its Expectancy

The concept of “active” (or “disability-free”) life, and its average value, has proven to be a useful index of public health and of quality of life for populations. A question of great interest in recent years is whether recent trends towards longer life expectancy have been accompanied by comparable increases in active life expectancy. Past research on patterns and trends of active and “inactive” life has focused almost exclusively on the expectancy—or, the average value—of years spent with and without disability. This measure is useful for actuarial calculations, for example analysis of the insurance value of programs that provide long-term care services. However, when considering broader issues of equity and efficiency in the financing and provision of services, or of targeting of programmatic resources, it is also useful to analyze the full frequency distribution of time spent in each activity status, in addition to the average values of each. Nevertheless, to our knowledge no past research has attempted to trace out the frequency distribution that underlies the calculations of Active Life Expectancy (ALE). Similarly, the uncertainty (or, the “margin of error”) in our calculations of active life expectancy traceable to sampling error has received little attention. This paper addresses two related phenomena: variability in active life, which is to say the relative likelihood that someone will spend an additional 0, 1, 2, ... or more of his or her years in various functional statuses such as “active” or “inactive;” and uncertainty about the average value of additional years spent in each such status. Our concern with both phenomena leads us to present our findings in the form of intervals, or measures of dispersion, as well in the more conventional form of point estimates. Linking the two areas of analysis is a recognition of several sources of randomness, or stochasticity, that are inevitably present when analyzing the dynamics of functional status. In general, we find that the variability in years of active life is substantial. This variability is obscured in analyses that address only the expected value of active life. In contrast, uncertainly related to sampling error appears to be quite small, at least for the combination of survey data and model specification employed here

Association of type of birth attendant and place of delivery on infant mortality in sub-Saharan Africa.

Objective: To examine the association between type of birth attendant and place of delivery, and infant mortality (IM). Methods: This cross-sectional study used self-reported data from the Demographic Health Surveys for women in Ghana, Kenya, and Sierra Leone. Logistic regression estimated odds ratios (ORs) and95% confidence intervals. Results: In Ghana and Sierra Leone, odds of IM were higher for women who delivered at a health facility versus women who delivered at a household residence (OR=3.18, 95% confidence interval, CI: 1.29-7.83, p=0.01 and OR=1.62, 95% CI: 1.15-2.28, p=0.01, respectively). Compared to the use of health professionals, the use of birth attendants for assistance with delivery was not significantly associated with IM for women in Ghana or Sierra Leone (OR=2.17, 95% CI: 0.83-5.69, p=0.12 and OR=1.25, 95% CI: 0.92-1.70, p=0.15, respectively). In Kenya, odds of IM, though nonsignificant, were lower for women who used birth attendants than those who used health professionals to assist with delivery (OR=0.85, 95% CI: 0.51-1.41, p=0.46), and higher with delivery at a health facility versus a household residence (OR=1.29, 95% CI: 0.81-2.03, p=0.28). Conclusions: Women in Ghana and Sierra Leone who delivered at a health facility had statistically significant increased odds of IM. Birth attendant type-IM associations were not statistically significant.Future research should consider culturally-sensitive interventions to improve maternal health and help reduce IM

Preventable hospitalization and access to primary health care in an area of Southern Italy

<p>Abstract</p> <p>Background</p> <p>Ambulatory care-sensitive conditions (ACSC), such as hypertension, diabetes, chronic heart failure, chronic obstructive pulmonary disease and asthma, are conditions that can be managed with timely and effective outpatient care reducing the need of hospitalization. Avoidable hospitalizations for ACSC have been used to assess access, quality and performance of the primary care delivery system. The aims of this study were to quantify the proportion of avoidable hospital admissions for ACSCs, to identify the related patient's socio-demographic profile and health conditions, to assess the relationship between the primary care access characteristics and preventable hospitalizations, and the usefulness of avoidable hospitalizations for ACSCs to monitor the effectiveness of primary health care.</p> <p>Methods</p> <p>A random sample of 520 medical records of patients admitted to medical wards (Cardiology, Internal Medicine, Pneumology, Geriatrics) of a non-teaching acute care 717-bed hospital located in Catanzaro (Italy) were reviewed.</p> <p>Results</p> <p>A total of 31.5% of the hospitalizations in the sample were judged to be preventable. Of these, 40% were for congestive heart failure, 23.2% for chronic obstructive pulmonary disease, 13.5% for angina without procedure, 8.4% for hypertension, and 7.1% for bacterial pneumonia. Preventable hospitalizations were significantly associated to age and sex since they were higher in older patients and in males. The proportion of patients who had a preventable hospitalization significantly increased with regard to the number of hospital admissions in the previous year and to the number of patients for each primary care physician (PCP), with lower number of PCP accesses and PCP medical visits in the previous year, with less satisfaction about PCP health services, and, finally, with worse self-reported health status and shorter length of hospital stay.</p> <p>Conclusion</p> <p>The findings from this study add to the evidence and the urgency of developing and implementing effective interventions to improve delivery of health care at the community level and provided support to the usefulness of avoidable hospitalizations for ACSCs to monitor this process.</p