Operational efficiency, patient composition and regional context of U.S. health centers: Associations with access to early prenatal care and low birth weight

Beyond the First Trimester: Social Determinants of Delayed Prenatal Care at a Community Health Center Using the PRAPARE Tool

Social determinants of health have been used to explore associations with pregnancy outcomes and the birth weight of infants; however, research employing individually based social risk measures has not examined associations among underserved populations, including pregnant persons at community health centers. Data were collected from a sample (n = 345) of pregnant persons who sought care at a community health center between January 2019 and December 2020. Social risks of pregnant patients were measured using the PRAPARE tool. First, associations between patients' social risks and trimester in which they initiated care were assessed using ANOVAs, grouping social risk by PRAPARE social determinant domains (persona characteristics, family and home, money and resources, and social and emotional health). ANOVAs were stratified by ethnicity. Next, a multivariate logistic regression examined associations between social measures and seeking care after the first trimester. Patients who sought care in the first trimester reported more financial needs than those who sought care in the second (p = .02) or the third (p = .049). Hispanic patients who sought care in the first trimester reported more monetary needs than those who sought care in the second trimester (p = .048), and non-Hispanic patients who sought care in the first trimester reported greater family and home needs than those who sought care in the second trimester (p = .47). Those who experienced stress were 3.07 times as likely to seek care after the first trimester as those who reported no stress. CHC may reduce social risk among poor and underserved communities by reducing barriers to access to care.

Levels, trends, and determinants of effectiveness on the hierarchical medical system in China: Data envelopment analysis and bootstrapping truncated regression analysis

Background

The hierarchical medical system (HMS) refers to the classification of treatment according to disease priorities based on severity and difficulty to promote the fairness of medical services for residents, which is regarded as the key to the success of medical reform in China.

Methods

In the past decade of "New Medical Reform," the efficiency of HMS, including secondary and tertiary hospitals and primary healthcare centers (PHCs), was measured horizontally and vertically by employing the combination of an output-oriented superefficiency slack-based model-data envelopment analysis (SE-SBM-DEA) model with the Malmquist total factor productivity index (MTFP). In the second stage, the overall technical efficiency (OTE) scores were regressed against a set of environmental characteristics and several managerial factors through bootstrapping truncated regression.

Results

On average, the OTE score in tertiary hospitals was 0.93, which was higher than that in secondary hospitals and PHCs (0.9 and 0.92, respectively). In terms of trend, the OTE of tertiary hospitals declined at first and then increased. The opposite was true of secondary hospitals, in which the APC of the OTE was 10.82 and -3.11% in early and late 2012, respectively. The PHCs generally showed a fluctuating downward trend. In the aspects of productivity, all institutions showed a downturn by an annual average rate of 2.73, 0.51, and 2.70%, respectively. There was a significant negative relationship between the ratio of outpatients to inpatients and tertiary hospitals. Additionally, the medical technical personnel per 1,000 population negatively affected PHCs. In contrast, the GDP per capita had a significantly positive effect on tertiary hospitals, and the number of beds per 1,000 population positively influenced PHCs.

Conclusion

The efficiency of medical institutions at various levels in HMS was unbalanced and took the form of an "inverted pyramid." Multilateral factors influence the efficiency of HMS, and to address it, multi-intervention packages focusing on sinking high-quality medical resources and improving healthcare capacity, and guiding hierarchical medical practice should be adopted.

Evaluating disparities in access to obstetric services for American Indian women across Montana

PURPOSE

Pregnant women across the rural United States have increasingly limited access to obstetric care, especially specialty care for high-risk women and infants. Limited research focuses on access for rural American Indian/Alaskan Native (AIAN) women, a population warranting attention given persistent inequalities in birth outcomes.

METHODS

Using Montana birth certificate data (2014-2018), we examined variation in travel time to give birth and access to different levels of obstetric care (i.e., the proportion of individuals living within 1- and 2-h drives to facilities), by rurality (Rural-Urban Continuum Code) and race (White and AIAN people).

FINDINGS

Results point to limited obstetric care access in remote rural areas in Montana, especially higher-level specialty care, compared to urban or urban-adjacent rural areas. AIAN women traveled significantly farther than White women to access care (24.2 min farther on average), even compared to White women from similarly rural areas (5-13 min farther, after controlling for sociodemographic characteristics, risk factors, and health care utilization). AIAN women were 20 times more likely to give birth at a hospital without obstetric services and had less access to complex obstetric care. Poor access was particularly pronounced among reservation-dwelling AIAN women.

CONCLUSIONS

It is imperative to consider racial disparities and health inequities underlying poor access to obstetric services across rural America. Current federal policies aim to reduce maternity care professional shortages. Our findings suggest that racial disparities in access to complex obstetric care will persist in Montana unless facility-level infrastructure is also expanded to reach areas serving AIAN women.

Meeting the Challenge of Perinatal Care in Rural Communities

The complexities of providing quality perinatal care within rural communities provide significant challenges to providers and policy makers. Provision of healthcare in rural communities is challenging on individual as well as community-based levels. A quality improvement lens is applied to consider key challenges that pertain to patients, providers, place, and policy. Potential solutions from a provider perspective include nurse-midwifery care and inclusion of advanced practice providers in a variety of specialties in addition to creating care models for registered nurses to practice at the top of their scope. To enhance access in the rural place, telehealth and coordination activities are recommended. Finally, policy approaches such as Perinatal Care Collaboratives, Area Health Education Centers, and enhanced financial resources to eliminate socioeconomic disparities will enhance perinatal care in rural communities.

Spatial variation in access to the health care safety net for Hispanic immigrants, 1970-2017

Hispanic immigrants have long faced barriers to accessing health care in the U.S., as they are largely excluded from federal programs like Medicaid. Since the 1960s, the federal government has operated a nationwide network of Community Health Centers (CHCs) that serve anyone, regardless of ability to pay or citizenship status. To what extent has this widespread, immigrant-inclusive institution been accessible to Hispanic immigrants? Using novel administrative data joined with Census and American Community Survey data from 1970 to 2017, this study documents spatial variation in population-level proximity to CHCs in relation to changing Hispanic migration patterns. Findings show that health centers, both historically and contemporarily, have been far more spatially proximate to poor and foreign-born Hispanics than to poor whites. In 2017, 56% of poor and foreign-born Hispanics in the U.S. lived within two miles of a CHC compared to 30% of poor whites. While access to CHCs has been consistently greater in established gateways, regardless of urbanicity, growth in new destination safety net infrastructure has increased at a faster rate. The CHC program has been substantially more accessible to the foreign-born than U.S.-born Hispanic and uninsured populations, showing the geographic potential for CHCs to provide care to underserved immigrant communities. This study provides the first descriptive evidence of the programmatic reach of this safety net institution across time and space, highlighting a crucial yet underexplored factor in understanding the health of Hispanic immigrants.

Diabetes management at community health centers: Examining associations with patient and regional characteristics, efficiency, and staffing patterns

A major source of primary health care for millions of Americans, community health centers (CHCs) act as a key point of access for diabetes care. The ability of a CHC to deliver high quality care, that supports patients' management of their diabetes, may be impacted by the unique set of resources and constraints it faces, both in terms of characteristics of its patient population and aspects of operations. This study examines how patient and regional characteristics, staffing patterns, and efficiency were associated with diabetes management at CHCs (percentage of patients with uncontrolled diabetes, HbA1C > 9%). Data on a sample of 1229 CHCs came from multiple sources. CHC-level information was obtained from the Uniform Data System and regional-level information from the Behavioral Risk Factor Surveillance System and the US Census American Community Survey. A clustering methodology, latent class analysis, identified seven underlying staffing patterns at CHCs. Data envelopment analysis was performed to evaluate the efficiency of CHCs, relative to centers with similar staffing patterns. Finally, generalized linear models were used to examine the association between staffing patterns, efficiency, and patient and regional-level characteristics. Findings from this study have sociological, practical, and methodological implications. Findings highlight that the intersection of patient racial composition with regional racial composition is significant; diabetes control appears to be worse at CHCs serving racial minorities living in predominantly White areas. Findings suggest that CHCs that incorporate more behavioral health care into their staffing mix have lower rates of uncontrolled diabetes among their patients. Finally, greater efficiency in CHC operations is associated with better diabetes control among patients. By identifying sociodemographic and operational characteristics associated with better hemoglobin control among diabetes patients, the current study contributes to our understanding of both health care operations and health inequalities.

Sustainable efficiency assessment of private diagnostic laboratories under uncertainty

Purpose

Assessing the performance of medical laboratories plays an important role in the quality of health services. However, because of imprecise data, reliable results from laboratory performance cannot be obtained easily. The purpose of this paper is to illustrate the use of interval network data envelopment analysis (INDEA) based on sustainable development indicators under uncertainty.

Design/methodology/approach

In this study, each medical diagnostic laboratory is considered as a decision-making unit (DMU) and an INDEA model is used for calculating the efficiency of each medical diagnostic laboratory under imprecise inputs and outputs. The proposed model helps provide managers with effective performance scores for deficiencies and business improvements. The proposed model with realistic efficiency scores can help administrators manage their deficiencies and ultimately improve their business.

Findings

The results indicate that uncertainty can lead to changes in performance scores, rankings and performance classifications. Therefore, the use of DEA models under certainty can be potentially misleading.

Originality/value

The contribution of this study provides useful insights into the use of INDEA as a modeling tool to aid managerial decision-making in assessing efficiency of medical diagnostic laboratories based on sustainable development indicators under uncertainty.