Regional health care planning: a methodology to cluster facilities using community utilization patterns (original) (raw)
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Scientific Reports
The sustained COVID-19 case numbers and the associated hospitalizations have placed a substantial burden on health care ecosystem comprising of hospitals, clinics, doctors and nurses. However, as of today, only a small number of studies have examined detailed hospitalization data from a planning perspective. The current study develops a comprehensive framework for understanding the critical factors associated with county level hospitalization and ICU usage rates across the US employing a host of independent variables. Drawing from the recently released Department of Health and Human Services weekly hospitalization data, we study the overall hospitalization and ICU usage—not only COVID-19 hospitalizations. Developing a framework that examines overall hospitalizations and ICU usage can better reflect the plausible hospital system recovery path to pre-COVID level hospitalization trends. The models are subsequently employed to generate predictions for county level hospitalization and IC...
A methodology for projecting hospital bed need: a Michigan case study
Source code for biology and medicine, 2010
Michigan's Department of Community Health (MDCH) is responsible for managing hospitals through the utilization of a Certificate of Need (CON) Commission. Regulation is achieved by limiting the number of beds a hospital can use for inpatient services. MDCH assigns hospitals to service areas and sub areas by use patterns. Hospital beds are then assigned within these Hospital Service Areas and Facility Sub Areas. The determination of the number of hospital beds a facility subarea is authorized to hold, called bed need, is defined in the Michigan Hospital Standards and published by the CON Commission and MDCH. These standards vaguely define a methodology for calculating hospital bed need for a projection year, five years ahead of the base year (defined as the most recent year for which patient data have been published by the Michigan Hospital Association). MDCH approached the authors and requested a reformulation of the process. Here we present a comprehensive guide and associated ...
Evaluating Michigan's community hospital access: spatial methods for decision support
International journal of health geographics, 2006
Community hospital placement is dictated by a diverse set of geographical factors and historical contingency. In the summer of 2004, a multi-organizational committee headed by the State of Michigan's Department of Community Health approached the authors of this paper with questions about how spatial analyses might be employed to develop a revised community hospital approval procedure. Three objectives were set. First, the committee needed visualizations of both the spatial pattern of Michigan's population and its 139 community hospitals. Second, the committee required a clear, defensible assessment methodology to quantify access to existing hospitals statewide, taking into account factors such as distance to nearest hospital and road network density to estimate travel time. Third, the committee wanted to contrast the spatial distribution of existing community hospitals with a theoretical configuration that best met statewide demand. This paper presents our efforts to first...
Hospital Site Selection Analysis
Michigan Community hospitals are tasked with serving diverse populations and providing a full range of medical procedures. Many healthcare facilities were built to serve large local populations (e.g. Detroit); others were intended to provide regional coverage across less populated areas (e.g. Alpena). The precise settings of these hospitals were dictated by a diverse set of geographical and historical factors, including the distribution of population at the time each facility was constructed, the physical characteristics of available sites, and the human and political context of the moment. In Michigan, it seems quite likely that the factors leading to the development of today's spatial constellation of 139 community hospitals were largely local and unique to each individual hospital. A multi-organization committee headed by the State of Michigan's Department of Community Health approached the authors with questions about how spatial analyses might employed to develop a revised community hospital approval procedure. In particular, the State was concerned with identifying populations with lengthy drive times to existing community hospitals. The methods used in this research quantify access to existing hospitals statewide, taking into account factors such as distance to nearest hospital and road network density to estimate travel time. Areas falling outside of a particular time threshold are identified as limited access areas (LAA). This criterion is now state policy in the evaluation of new community hospital proposals. Results help policymakers understand some of the spatial complexities associated with the demand and the accessibility dimensions of health care access and equity.
2021
SUMMARYBackgroundAs of February 19, 2021, our review yielded a small number of studies that investigated high resolution hospitalization demand data from a public health planning perspective. The earlier studies compiled were conducted early in the pandemic and do not include any analysis of the hospitalization trends in the last 3 months when the US experienced a substantial surge in hospitalization and ICU demand. The earlier studies also focused on COVID 19 transmission influence on COVID 19 hospitalization rates. While this emphasis is understandable, there is evidence to suggest that non COVID hospitalization demand is being displaced due to the hospitalization and ICU surge. Further, with the discovery of multiple mutated variants of COVID 19, it is important to remain vigilant in an effort to control the pandemic. Given these circumstances, the development of a high resolution framework that examines overall hospitalizations and ICU usage rate for COVID and non COVID patients...
The Use of Health Service Areas for Measuring Provider Availability
The Journal of Rural Health, 1991
Measurement of the availability of health care providers in a geographic area is a useful component in assessing access to health care. One of the problems associated with the county provider-to-population ratio as a measure of availability is that patients frequently travel outside their counties of residence for health care, especially those residing in nonmetropolitan counties. Thus, in measuring the number of providers per capita, it is important that the geographic unit of analysis be a health service area. We have defined health care service areas for the coterminous United States, based on 1988 Medicaredata on travel patterns between counties for routine hospital care. We used hierarchical cluster analysis to group counties into 802 service areas. More than one half of the service areas include only nonmetropolitan counties. The service areas vary substantially in theavailability of health care resources as measured by physicians and hospital beds per 100,000 population. For almost all of the service areas, the majority of hospital stays by area residents occur within the service area. In contrast, for 39 percent of counties, the majority of hospital stays by county residents occur outside the county. Thus, the service areas are a more appropriate georgraphic unit than the coun ty for measuring the availability of health care.
Do Market-Level Hospital and Physician Resources Affect Small Area Variation in Hospital Use?
Medical Care Research and Review, 1999
This study evaluates the effect of market-level physician and hospital resources on hospital use. It is anticipated that higher hospital discharges are associated with (1) greater hospital and physician resources, (2) more differentiated hospital and physician resources, and (3) higher levels of teaching intensity in the community. Data on 14 modified diagnostically related groups (DRGs) and 58 hospital market communities in Michigan are analyzed during a 7-year period. Findings indicate that physician resources, hospital resources, differentiation of hospital and physician resources, and teaching intensity contribute only modestly to discharges, holding constant the socioeconomic attributes of the community and adjusting for the variation in hospital use over time. With the inclusion of hospital and physician resource variables, socioeconomic factors remain important determinants of the variation across market communities. Findings are discussed in terms of their implications for health care organizations, managed care programs, and cost control efforts in general.
Preliminary Investigations of Hospital Geography and Patient Choice in Iowa
This report provides a spatial representation of hospital geography in Iowa and of the decisions of patients to patronize hospitals. It begins with a brief analysis of hospital proximity and hospital proximity’s relationship to population distributions and existing hospital capacity. This is followed with a discussion of hospital capacity as a proxy for the supply of hospital services and the construction of hospital service area gravity models based upon capacity. Patient patronage of hospitals is then presented as a proxy of demand for hospital services, and gravity models are estimated on the basis of patronage.
International Journal of Environmental Research and Public Health, 2023
Based upon 30-years of research by the author, a new approach to hospital bed planning and international benchmarking is proposed. The number of hospital beds per 1000 people is commonly used to compare international bed numbers. This method is flawed because it does not consider population age structure or the effect of nearness-to-death on hospital utilization. Deaths are also serving as a proxy for wider bed demand arising from undetected outbreaks of 3000 species of human pathogens. To remedy this problem, a new approach to bed modeling has been developed that plots beds per 1000 deaths against deaths per 1000 population. Lines of equivalence can be drawn on the plot to delineate countries with a higher or lower bed supply. This method is extended to attempt to define the optimum region for bed supply in an effective health care system. England is used as an example of a health system descending into operational chaos due to too few beds and manpower. The former Soviet bloc countries represent a health system overly dependent on hospital beds. Several countries also show evidence of overutilization of hospital beds. The new method is used to define a potential range for bed supply and manpower where the most effective health systems currently reside. The method is applied to total curative beds, medical beds, psychiatric beds, critical care, geriatric care, etc., and can also be used to compare different types of healthcare staff, i.e., nurses, physicians, and surgeons. Issues surrounding the optimum hospital size and the optimum average occupancy will also be discussed. The role of poor policy in the English NHS is used to show how the NHS has been led into a bed crisis. The method is also extended beyond international benchmarking to illustrate how it can be applied at a local or regional level in the process of long-term bed planning. Issues regarding the volatility in hospital admissions are also addressed to explain the need for surge capacity and why an adequate average bed occupancy margin is required for an optimally functioning hospital.
Regional variations in hospital occupancy rates
Journal of Urban Economics, 1976
This paper analyzes theoretically and empirically SMSA differences in occupancy rates in short-term general hospitals. Because of the randomness of shortrun demands for admission to hospitals, occupancy rates are greater, the greater the admission rate, the larger the population, and the fewer the hospitals in the SMSA. Occupancy rates are higher where a greater proportion of the population is black and where the winters are colder, both due to longer hospital stays. More beds per capita lowers the occupancy rate. The efficiency of bed use could be increased by greater coordination among hospitals.