discussed along with the formula for their computation and definitions The collection of meaningful statistics is an important function of a hospital or clinic. Hospital Statistical Formulas for the RHIT Exam. Average Daily Census. Total service days for the unit for the period. Total number of days in the period. Average. Formula: Daily Inpatient Bed Occupancy the statistical formulae. to health care settings, other than the hospital, as more and more health.
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1BGENERAL FORMULA FOR PERCENTAGE RATES: UTotal number Number of deaths of hospital patients whose bodies are available for hospital autopsy. A brief description on Hospital Statistics. Formula for calculating average length of stay: (TOTAL INPATIENT DAYS OF CARE / TOTAL. It is often said that hospitals and other types of health care facilities are data rich . In this formula, x and y are the two quantities being compared, and x is.
University clinics, i. Type of supporting organizations and of the legal form According to the type of supporting organizations and the legal form the facilities can be differentiated as follows: Public hospitals and prevention or rehabilitation facilities can be conducted under public or private-law.
Hospitals or prevention or rehabilitation facilities, which are operated under public law are either legally independent e. Hospitals and prevention or rehabilitation facilities operated under private law e.
In case of hospitals or prevention or rehabilitation facilities with different supporting organizations, the supporting organization is specified, which is mainly involved or which mainly bears the costs. Medical staff According to the classification criterion of the medical staff institutional hospitals and private bed allocation hospitals can be distinguished.
In the hospital statistics only the pure private bed allocation hospitals Belegkrankenhaus are reported within this category. These are hospitals, which have exclusively privately allocated beds, i. Number of specialist departments A further classification of hospitals and prevention or rehabilitation facilities is based on the number of specialist departments.
With this criterion statements about specialisation and differentiation within the range of services of hospitals and prevention or rehabilitation facilities are possible. If a hospital or a prevention or rehabilitation facility indicates to have "other specialist departments" - i. So, perhaps the situation is not shown correctly, in particular, when the category of "other specialist departments" for the relevant hospital or the prevention and rehabilitation facility includes more than one specialist department.
For the number of specialist departments the main areas and subordinate fields are counted. That means, in a hospital, which has a thorax surgery department and this is a subordinate field of the surgery department, two specialist departments are counted. Because of this mode of counting there are deviations from the "number of specialist departments total", because only the main areas are included in this position. Number of beds The classification by the number of installed beds gives information about the size of a facility.
Therefore in the hospital statistics groups in terms of number of beds are formed, which show depending on survey variables and reporting target a different width of classes. The number of beds is calculated as an annual average of the beds at the end of each month.
Not included are beds for partly inpatient or outpatient patients. Subsidization This classification is based on the percentage of subsidized beds of all installed beds in the facility.
Not subsidized hospitals have no subsidized beds. Medico-technical large-scale equipment Reported are special equipments and medico-technical large-scale equipment, which are in possession of the facility and which are used for the care of patients in the facility.
Not counted is equipment, which is only used for demonstration and teaching purposes or which is only used by practitioners with own practices. If equipment is used by several facilities, it is only reported by the facility, where it is installed.
Since the expression "kidney stone fragmentation and gallstone fragmentation equipment" is replaced by "shock wave lithotripter". Newly collected are also: digital subtraction angiography equipments, gamma cameras, heart-lung-machines and dialysis equipments.
Dialysis places Collected is the number of dialysis places in facilities. Places which are maintained by third parties, for example curatorships "Kuratorien" or medical practices are not counted. Day and night clinic places Day and night clinic places serve for partly inpatient medical care of patients during the day or the night.
The classification of the specialist department is based on the field or subordinate field qualifications of the medical practitioners. Exceptions from this are the specialist departments geriatrics and addiction.
In a hospital structured by specialist departments the corresponding organizational units are assigned to one of the listed specialist departments. For reasons of a uniform way of counting there is no separate statement of a specialist department "intensive care medicine" in the statistics. If there is an organisationally independent specialist department "intensive care medicine" in the hospitals, its beds are listed according to use with the listed specialist departments.
The same applies to the patients who are treated there and the occupancy and billing days. Transfers to and from the specialist department "intensive care medicine" are not counted in the statistics. Cases and days are then further recorded with the delivering specialist department. As far as an admission of a patient takes place directly from outside into the intensive care medicine, the patient data are assigned to one of the listed specialist departments.
Because of this adaptation the specialist departments "psychosomatics" and "addictions" are no longer reported. Such data are, therefore, of value in determining the relative importance of each with respect to overall hospital activities. Labor input For our purposes, labor input refers to BLS estimates for the total number of hours worked in community hospitals during the year. The Current Employment Statistics program publishes employment data for all employees and nonsupervisory workers, along with average weekly hours for nonsupervisory workers.
To estimate hours for supervisory workers, ratios of average weekly hours for supervisory workers relative to those of nonsupervisory workers are estimated using data from the Current Population Survey. These ratios are applied to average weekly hours for nonsupervisory workers.
Both total employment and total hours worked in community hospitals have seen continuous growth between and Over this period, community hospitals have added over a million new employees, and hours have increased by an average of 1. Trends in labor productivity growth View Chart Data From to , the output of community hospitals grew at an average annual rate of 2.
The index of outpatient services rose by an average of 3. Starting in , outpatient services experienced 20 years of almost continuous yearly growth. However, this trend is not replicated for inpatient services. From through , inpatient services grew by an average annual rate of 1. But in the years since, inpatient services growth has slowed significantly. From to , the growth rate was a mere 0. See figure 2. View Chart Data Labor hours increased at an average annual rate of 1.
These indexes moved in tandem from to From to , the number of hours worked increased by an average of 2. This indicates that employees began to work more hours per year over that time period. From to , average annual growth has been modest for both hours worked 0. See figure 3. Labor productivity is determined by dividing the index of output by the index of labor hours.
From through , hospital output has grown at a faster rate than hours, resulting in average annual growth of 0. A closer look at the index reveals that labor productivity increased through , and declined thereafter. From to , labor productivity decreased by an average of 0.
See figure 4. View Chart Data A number of factors have contributed to the decline in hospital labor productivity since As technology, pharmacology, and medical science have improved, many conditions that once required hospitalization can now be treated on an outpatient basis.
As seen in figures 1 and 2, the volume of outpatient treatments has grown significantly over the period studied. This trend generally serves to increase labor productivity in hospitals, as fewer labor hours are required to treat patients on an outpatient basis.
However, the rise in outpatient procedures has not been confined to the hospital industry.
In general, outpatients require fewer resources for treatment than do inpatients, and therefore receive less weight in the overall output index. Shifts between outpatient and inpatient treatments therefore impact the labor productivity index through the influence of their relative weights. As a certain percentage of patients shift from inpatient to outpatient care, the remaining inpatients are given a greater relative weight in the output measure.
This weighting effect is further magnified by the fact that the cases still being treated as inpatients are increasingly those with the most serious health conditions. One way of quantifying the level of sickness of patients is the presence of multiple chronic conditions MCC. Certain DRGs classify patients with comorbidities or complications. These DRGs indicate cases with serious problems that require more resources to treat.
In , the NIS sample showed that By , this percentage had risen to There are two countervailing trends on productivity. On the one hand, patients who are less sick can be treated on an outpatient basis, requiring fewer labor hours and raising labor productivity.
On the other hand, the remaining inpatients tend to be the most serious cases, requiring more resources and lowering labor productivity.
These resource-intensive patients also receive a higher weight in the overall output index. This impact is further heightened by the fact that, as discussed earlier, the outcome of treatment is currently not accounted for in this measure. Future changes in patient treatment, as well as potential incorporation of new data on treatment outcomes, may result in very different labor productivity trends.
Conclusion Over the last several years, U. Such efforts include the Bureau of Economic Analysis health care satellite accounts and the BLS disease-based producer price indexes.
Complementary to these statistics are the new measures of hospital output and labor productivity introduced in this article.
While the majority of IPS industry labor productivity measures are calculated using a deflated-value methodology, the most logical and practical means to measure productivity for community hospitals is to use a physical quantity measure, specifically by counting the number of courses of treatment. Each inpatient stay is counted when the patient is discharged from the hospital, while each outpatient visit is a single discrete unit.
This labor productivity measure is available on the BLS website and will be updated annually. Sponsored by the Agency for Healthcare Research and Quality AHRQ , the NIS is the largest all-payer inpatient care database publicly available in the United States, providing information on health care utilization and charge data, with annual data starting in The database contains information on more than 8 million hospital stays, from about 1, hospitals in 45 states, sampled to approximate a percent stratified sample of U.
The NIS is a stratified probability sample of hospitals in the frame, with sampling probabilities proportional to the number of U. The universe of U.
In , the NIS sample was redesigned to improve national estimates. The unit of observation is an inpatient stay record.
NIS inpatient stay records are composed of clinical and resource use information, typically available from discharge abstracts. We do this to ensure consistency between the output measure and the BLS labor input series that is used in the final labor productivity calculations. The sample of discharge records is made into a nationwide measure by applying weights to each inpatient discharge and its associated charge.
Patient-level data are weighted with respect to the type of hospital where the service takes place. Suggested citation: Brian Chansky, Corby A.
Garner, and Ronjoy Raichoudhary, "New measure of labor productivity for private community hospitals: —," Monthly Labor Review, U. Other special hospitals include obstetrics and gynecology; eye, ear, nose, and throat; rehabilitation; orthopedic; and other individually described specialty services.
Community hospitals include academic medical centers or other teaching hospitals if they are nonfederal short-term hospitals.
Excluded are hospitals not accessible by the general public, such as prison hospitals or college infirmaries. Prior to , only a small number of states were sampled. Thus, based primarily on the addition of states to the NIS dataset over time, the U. Department of Health and Human Services recommends that time-series analyses of these data begin with PHS 06— The NIS provides yearly discharge data for these versions. NIS data are used to calculate the percentage of hospitals that are privately owned in the United States.
This percentage is applied to the AHA data to remove government-owned hospitals.