This study used a sample of 209 repeat-respondent medical technologists over a 4-year period to investigate correlates of intent to leave one’s job. Correlates measured included two job search behaviors (i.e., preparatory and active) and three job search motives (i.e., gain leverage, leave employer, and family related). Results showed that active job search and the leave employer job search motives were each positively related to final intent to leave one’s job. The gain leverage job search motive was negatively related to final intent to leave one’s job. In addition, job satisfaction was negatively related, while only initial job loss insecurity was positively related, to final intent to leave one’s job. J Allied Health 2006; 35:94-100.

JOB SEARCH remains an important applied topic and research area for study across different samples, for example, graduating students entering the job market,1,2 the unemployed,3-5 and the employed.6-8 Job search is also a topic of international interest.4,9-11 Recent research on further understanding job search has focused on personality-motivation and cognitive ability variables,7 including a meta-analysis by Kanfer et al.12 The dominant research samples captured in the meta-analysis by Kanfer et al. were individuals entering the job market following a period of full-time education or those who were unemployed. Boudreau et al.7 argued for focusing more job search research on those currently employed because they compose a larger domain. There is a current general shortage of health care employees in the United States, including nursing, radiologic technology, and medical technology employees.13-15 Any type of labor shortage in a particular occupation can make it easier for those currently employed to change jobs across organizations.16 The purpose of this study was to further investigate the impact of correlates on medical technologists’ intent to leave their jobs.
Advertisement

Why Do the Employed Job Search? Different Motives

Using a sample of higher-level managers, Boswell et al.6 distinguished between specific leverage-seeking versus separation-seeking job search motives or objectives. They found that leverage-seeking but not separation-seeking search was positively associated with actual use of leverage one year later, while separation-seeking but not leverage-seeking search was positively associated with voluntary turnover one year later.

Bretz et al.17 observed that because job search activity may not always be associated with separation, there can be greater observed variance in search behavior than turnover. Using a sample of 1,388 employed managers, Bretz et al.17 found that a considerable amount of managers’ job search activity did not lead to subsequent voluntary turnover. Whether it leads to voluntary turnover or not, job search by itself can be a costly behavior because it can distract an employee from his or her current job duties18 or reduce the employee’s commitment to his or her current employer.19

Beyond its relevance to voluntary turnover, research has suggested that job search can serve several other distinct purposes for the employed.17 A second “motive” suggested for job search is to increase one’s leverage or advantage in a current job,20 such as gaining higher pay or other improved employment conditions. Clearly this motive is related to at least some degree of employee unhappiness with the current job situation. However, this motive suggests that employees do not necessarily want to leave their employer but to improve their situation (e.g., pay, promotion) while remaining with their current employer.21 Deshpande and Schoderbek22 found that getting a job offer elsewhere was used by subordinates to get a pay raise from their current boss. There can be “other” motives for job search, such as family related. For example, if one’s working spouse is transferred, the affected individual must now find a new job in the working spouse’s new location. Another family-related reason for job search is if an employee moves to be closer to an elderly parent to help care for that parent.16

Job Search Activity

For an individual who voluntarily changes jobs, most prior turnover research suggests that the closest proximal determinant to such change is the intent to leave that job.”16,23 Prior theory on job search activity suggests distinct preparatory and active search phases (Rees24 and Soelberg,25 as noted by Power and Aldag26). During the preparatory phase, individuals gather their resources (e.g., prepare/revise their resume, research getting/changing jobs) and collect potential job leads through various sources (e.g., Internet, newspaper, friends, previous employers); in the active phase, individuals apply to specific job positions/employers they have identified (e.g., sending a resume to or interviewing with an employer, filling out a job application). Generally, it is assumed that preparatory job search precedes active job search, because often individuals will want to first determine the perceived availability of “greener pastures” (preparatory job search) before determining their accessibility,27 which involves active job search.

Below are paid listings of specialty software packages for the insurance companies, risk managers and brokers. This guide is not intended to be a complete directory but is an overview of some of the packages available. Suppliers themselves have provided this data. To obtain more information on any of the programs listed, please select the appropriate URL. For more information, please contact Fred Kurst: fkurst@lrp.com; (T) 703.393.8304, (F) 703.393.9027.

Most businesses don’t like billing. It’s tedious administrative work that costs them time and money. In fact, some businesses hate billing so much they’ll pay you to do it for them. That’s a potentially profitable, low-overhead business opportunity.

You can run a billing service from home full-time or part-time, with little specialized knowledge beyond the ability to use a computer. Adding a billing service is a great way for an accounting or secretarial service to expand its offerings. Of course, as with any business, the ability to market your service is the key to success.

There are two main types of billing services: those that serve health-care providers and those that serve small businesses (see “Billing-Software Companies”). Start-up costs for a general business billing service are significantly lower than those for medical billing services. If you already own a computer and printer, you can get started for less than $500 ($300 for software, $150 to $200 for stationery supplies). Start-up costs for medical billing services range from $4,000 to $10,000. In either case, a high-speed, wide-carriage dot-matrix printer is recommended for producing duplicate copies, along with a fast computer (preferably a 386).

GENERAL BUSINESS BILLING
Advertisement

“Our research shows that small businesses in the service sector, such as landscapers and janitorial companies, lack the staff needed to generate invoices promptly and to adequately track payments and receivables,” says Scott McIntire, president of the American Association of Billing Professionals and owner of BlueJay Systems, which sells small-business billing software.

Lori Ende, who lives in Minnesota, chose to add a billing service to her home-based secretarial business when several of her existing clients asked for such assistance. She looked at several types of software before settling on the Basic Billing program ($289) developed by BlueJay Systems. (If you’re comfortable with database or accounting software, you can design your own billing system.) “Then I contacted the businesses that had previously expressed an interest, as well as others I thought were good prospects,” says Ende. “Eleven of the 50 businesses I spoke to agreed to try the service free for one month, and all signed on as clients.”

Ende received so many referrals from her original accounts that she was forced to turn away several prospective clients. The 45 to 50 hours she devotes to her billing service each month produces a gross income of about $2,400.

MEDICAL BILLING SERVICES

Medical billing primarily involves transmitting claims from doctors and dentists to insurance companies. Demand for medical-billing services, already strong, is expected to grow as pressure mounts to streamline the American health-care system. “Medicare in particular wants to see more efficiency,” says Art Streim, supervisor of support and training at AR Professionals. “Transmitting claims electronically can reduce processing time to as little as 7 to 14 days, whereas by mail it can take two months or more.”

Currently less than 10 percent of the more than six billion insurance claims filed annually are electronically processed. “Despite the pressure on health practitioners to file claims electronically, fewer than half of practitioners have computers,” says William J. Sarracini, president of National Healthcare Support Corporation in Mission, Kansas, “This gives the billing-service operator a considerable advantage in marketing his or her services.” Another key selling point is that a billing service can reduce a doctor’s overhead and improve cash flow by speeding claims.

The potential income from a medical billing service is determined by the number of claims filed. Some operators charge per claim, and other charge a percentage of the amount billed or flat monthly fees. “Most people charge $1.50 to $2 per claim,” says Merry Schiff, owner of Health Software Systems, although some services charge as much as $3 per claim. “Once you get going, it’s possible to make $10,000 a month.” That’s the case for Linda Jones, who runs Our Billing Service in Sebastopol, California, and has processed as many as 11,000 claims in one month (at $1.80 per claim).

Medical billing is more complex than general small-business billing. The method for filing insurance claims can vary from state to state. Thus, the training and ongoing support that a billing-software company offers is just as important as the software itself. When choosing a software package, ask for references of doctors who have worked with a given system; doctors are more likely than operators to give you an honest appraisal.

“Both types of billing services offer outstanding opportunity and income potential,” says McIntire. “But remember that you are the one who has to market the service. Your success depends on how much effort you put into it.”

A report released in September by The Commonwealth Fund finds that, as employers cope with rising healthcare costs by dropping health benefits or increasing employee cost- sharing through higher deductibles, workers and their families are being squeezed. When people lose coverage, many who turn to the individual insurance market find that coverage is unobtainable or unaffordable. The report also finds that those with high-deductible health plans are more likely than those with lower deductibles to have burdensome medical debt and to forgo needed health care; those with low incomes are especially at risk.

Of working-age adults who sought coverage in the individual market during the past three years, 89 percent ended up never buying a plan; 58 percent found it very difficult or impossible to find affordable coverage; and 21 percent were turned down, were charged a higher price because of a pre-existing condition, or had a health problem excluded from coverage.

“Most of the increase in the number of uninsured Americans–now upwards of 46.6 million–was due to a decline in workplace coverage,” said Commonwealth Fund assistant vice president Sara Collins, lead author of the report, Squeezed: Why Rising Exposure to Health Care Costs Threatens the Health and Financial Well-Being of American Families. “Although the individual market is a last resort for those shut out of employer-sponsored coverage, it is by no means a safe or secure haven for everyone.”
Advertisement

The report, based on findings from the Commonwealth Fund 2005 Biennial Health Insurance Survey, also highlights the increasing cost burdens families are facing due to the decline in the quality of coverage and more cost-shifting to employees. Adults with high-deductible health plans–those with individual market or employer-based coverage–have higher out-of-pocket costs than do those with lower-deductible plans. In addition, many adults with such plans are left with burdensome medical bills because of limits to their insurance coverage. Of those with deductibles over $1,000, 40 percent had expensive medical bills for services not covered by their insurance, compared with about 19 percent of those with deductibles under $500.

Those with high-deductible health plans were also more likely to report that they did not get needed health care or prescription drugs because of costs. In addition, many adults with such plans said they had problems with medical bills or were paying off medical debt over time and were more likely to give low ratings to their coverage. Two of five (41 percent) of those with deductibles over $1,000 had medical bill problems compared with about a3 percent of those with deductibles under $500. Of those with higher deductibles, 41 percent rated their health plan fair or poor, compared with 15 percent of those with lower deductibles.

“We need a national solution to the problem of affordable and comprehensive coverage for all,” said Commonwealth Fund President Karen Davis, “following the lead of states like Maine, Massachusetts, and Vermont that have expanded coverage through shared financial contributions from individuals, employers, and government.”

Other key findings from the report include:

* Two of five (43 percent) adults with individual coverage spent 5 percent or more of income on premiums, compared with 14 percent with employer-sponsored coverage.

* Of adults with individual coverage, 37 percent have annual deductibles of $1,000 or more.

* Adults with high deductibles are less satisfied with the quality of the health care they have received: 29 percent of those with deductibles over $1,000 are very satisfied with quality, compared with 54 percent of those with deductibles under $500.

* Of those with deductibles over $1,000, 44 percent experienced problems with access to care (didn’t fill a prescription; didn’t see a specialist when needed; skipped a recommended test, treatment, or follow-up; or had a medical problem and didn’t go to a doctor or clinic) compared with a5 percent of those with deductibles under $500.

* One-fifth (22 percent) of those with higher deductibles took on credit card debt to pay medical bills, compared with 8 percent of those with lower deductibles.

The aim of this paper is to examine possible determinants of the prevalence of private medical insurance (PMI) in England. The entire British public has access to free care in the National Health Service (NHS) financed by general taxation and national insurance paid by all employed United Kingdom (U.K.) residents. There is no option for U.K. residents to opt out of contributing to the NHS, and NHS coverage is comprehensive. Thus, PMI is supplementary, typically purchased to guarantee faster access to health care (particularly specialists) and in some cases, better amenities in health care facilities. In the United Kingdom, PMI covers treatment for curable, short-term illness or injury. PMI does not cover general practitioner (GP) services, chronic conditions, or conditions an individual had prior to taking out insurance. At the end of year 2000, 6.88 million people in the U.K. (approximately 11.5 percent of the population) were covered by PMI and the value of the PMI market was estimated at 2.45 billion [pounds sterling] (Laing and Buisson 2001), 5.1 percent of the estimated year 2000/2001 NHS expenditure of 48 billion [pounds sterling].

Since 1988, Laing and Buisson, an independent specialist consultancy in health and community care, have reviewed the U.K. PMI market. The number of subscribers covered through an employer-paid plan has increased by approximately 23 percent since 1990, while during the same period, the number of subscribers who were either paying individually or as employees (as partial payment of a company plan) declined by about 6 percent (Laing and Buisson 2001). At the end of 2000, 66.5 percent of PMI subscribers were in plans fully paid for by their employer (Laing and Buisson 2001).
Advertisement

Tax policies introduced between 1979 and 1997 encouraged both employer-paid and individual PMI subscription. Employers did not pay employers’ National Insurance contributions on PMI provided to employees as a benefit-in-kind. (1) And in 1990, tax relief on the total premium cost, at the marginal tax rate, was provided to holders of individual PMI over age 60 years.

Some of these incentives were weakened in 1997. Tax relief for individual PMI premiums paid by those over the age of 60 years was discontinued (Laing and Buisson 2000b) and the Insurance Premium Tax on all PMI policies (in effect, a sales tax on PMI purchase) was increased to 5 percent from 4 percent (introduced in October 1994 at an initial rate of 2.5 percent [HM Customs and Excise 2001]). Also, in April 2000 the government extended employer-paid national insurance contributions (2) to cover PMI benefits in kind (Laing and Buisson 2000b). Evidence exists to suggest that incentives intended to increase PMI prevalence were expensive, and largely unsuccessful in stimulating demand (Emmerson, Frayne, and Goodman 2001). Furthermore, the elimination of tax relief for those over age 60 years increased premiums for individual subscribers in this age group by 29.9 percent (Emmerson, Frayne, and Goodman 2001).

The future trend of PMI prevalence may be influenced by two factors: substantial increases in premiums on individual PMI policies (over the calendar year 1999 they were estimated to have increased by over 15 percent or five times the rate of inflation in 1999 [Laing and Buisson 2001; U.K. National Statistics 2001] and the current government’s significant increase in funding to the NHS, pledging to increase real NHS spending by 7.3 percent in each year until 2007 [HM Treasury 2002]).

Data from the British Household Panel Survey (BHPS) 1997-2000, the U.K. Department of Health and Laing’s Healthcare Market Review 1999-2000, are used in this analysis. The panel nature of the survey allows a national, representative sample of households to be followed over the years for which data on PMI subscription are available. The BHPS has not previously been used to examine determinants of PMI prevalence. Previous analysis utilized cross-sectional data that do not well reflect the dynamic nature of the PMI market. Insurance status, PMI policy changes, individual circumstances and waiting lists are all subject to change over time. Our analysis also incorporates data from other sources. We include data on inpatient and outpatient waiting times estimated at the health authority (HA) and regional level (provided by the NHS Waiting Times Team), as well as data on the number of private acute care beds, at the regional level (Laing and Buisson 2000a), and estimates of the regional distribution of physicians working in the private health care sector (DH 2001). The results provide new evidence as to what factors determine the size of the PMI market in England.

MODELLING THE DECISION TO PURCHASE PMI

Several factors impact on the decision to purchase PMI. These include the perceived magnitude of a potential loss because of illness, relative to income and an individual’s degree of risk aversion (Cutler and Zeckhauser 2000; Santerre and Neun 2000). Choice and convenience, as offered by a private health care alternative, are also benefits sought by PMI subscribers (Bosanquet and Pollard 1997; Barr 1998). In some cases quality of care available through private insurance, relative to that available through an NHS system, may also be an incentive (Besley, Hall, and Preston 1999).

R857

2004-115811

0-7695-2289-0

IDEAS workshop on medical information systems; the digital hospital; proceedings.

IDEAS Workshop on Medical Information Systems (2004: Beijing, China) Ed. by Bipin C. Desai et al.

Computer Society Press, [c]2005
Advertisement

175 p.

$69.00 (pa)

Papers from a September 2004 workshop present new findings on technological and theoretical aspects of information technology applied in the area of health care. Presented in sections on applications in diagnostic and clinical decision support, health care information, e-disease management, electronic health information exchange, and ICU, papers report on innovations such as development of a clinical data warehouse, knowledge representation of traditional Chinese acupuncture points using the UMLS and a terminology model, and a rule-based intelligent ICU information system. There is no index.

Medical information visualisation; biomedical visualisation; proceedings.

Int’l conference on Medical Information Visualisation (3d) BioMedical Visual…(2005: London, England) Ed. by Gordon Clapworthy et al.

Computer Society Press

2005

83 pages

$157.00
Advertisement

Paperback

R859

In these proceedings from the July 2005 conference, contributors describe their work in bio-mechanical modeling and simulation, treatment planning, analytical visualization and multi-dimensional data visualization. Specific topics include patient-specific muscle models, the influence of bio-mechanical parameters on simulation of lung behavior, simplification of mesh models, complex pre-operative planning environments for total hip replacements and targeted radiation therapy, a simple method to show variations, 3D reconstruction of lymph nodes, statistical analysis for brain EIT images using SPM, a 3D visualization system of a cranium using x-ray images and visualization of biochemical results using SimWiz3D.

The radiology handbook; a pocket guide to medical imaging.

Benseler, J. S.

Ohio University Press

2006

283 pages

$20.00

Paperback
Advertisement

White coat pocket guide series

RM847

This pocket (7×5″) reference on medical image interpretation is written for medical students, but can also serve as a basic introduction for any practitioner who needs readily accessible information on ordering or interpreting images. Material is presented in sections on ordering schemes, general information, and practice images. All chapters are arranged in question-and-answer format. A quiz provides 60 images of normal anatomy and common imaging pathology, plus an answer key. Editor information is not given.

Barrington Medical Imaging can optimize the clinical and financial possibilities of its customers’ practices by offering preowned imaging technology. Barrington completely refurbishes and stages its equipment in one of six staging bays at its large Chicago facility. All customers are encouraged to personally inspect any system in which they are interested.

Barrington Medical Imaging offers turnkey solutions to meet customers’ needs, with services ranging from complete site planning to financing options. The company’s team has a combined 50 years of imaging experience to help customers meet their practice goals.

Several recent studies have examined the consequences of uninsurance in a near-elderly population using data from the longitudinal Health and Retirement Survey (Heeringa and Conner 1995). Baker et al. (2001, 2002) found that those who were continuously or intermittently uninsured, or lost their insurance coverage over a 2-4 year period, experienced greater health declines than those who were continuously insured. McWilliams et al. (2004, 2003) found that lack of insurance was associated with significantly increased mortality, and that previously uninsured near-elderly adults who survived to age 65 increased their use of basic clinical services after they obtained Medicare coverage more than those who had been fully insured.

These research findings raise two important questions. Does lack of insurance prior to age 65 result in people qualifying for Medicare in worse health than if they had been insured? If so, is public insurance spending through Medicare and Medicaid on newly enrolled beneficiaries greater than it would be if people had continuous insurance coverage prior to age 65?

Our analysis extends these previous studies in several ways. As the prior studies were not specifically interested in the question of health status at entry to Medicare, they included changes in health for people as young as 57, as well as people who were older than 65 and had already aged into Medicare coverage. If attaining Medicare coverage improves health (Lichtenberg 2002), then the previous results may understate the impact of lack of insurance on health status at age 65. We also analyze data from the Health and Retirement Survey (HRS), but define our endpoint as health status at the last survey before turning 65.
Advertisement

Second, Baker et al. (2001, 2002) did not adjust for possible bias in the estimation of the health insurance effect because of the selection of people into insurance states based on their unobserved health. This bias could occur through a combination of mechanisms. People who are uninsured at this age and in good health may forego insurance coverage, especially nongroup coverage, because of its very high cost for older people. At the other extreme, people in poor health who are unable to work may qualify for Medicaid and/ or Medicare coverage because of a work-limiting disability. Similarly, people in less than perfect health with employer-sponsored insurance may be more likely to continue working to keep their insurance coverage, as opposed to taking early retirement without coverage. These behaviors raise the possibility that unobserved health, which affects future health, may be better among the uninsured and worse among the insured than if people were randomly assigned to alternative insurance states in an experiment.

McWilliams et al. (2004) used a propensity score method based on health insurance status in 1992 to adjust for the effects of observable differences associated with insurance coverage. However, this adjustment may not fully account for the effects of unobserved factors. We use instrumental variable (IV) analysis (McClellan and Newhouse 2000) to adjust for possible biases because of unobserved factors, focusing on the percentage of time a person was insured over the entire observation period prior to turning 65. (McWilliams et al. [2004] adjust only for insurance status at baseline, 1992.)

Third, Baker et al. (2001, 2002) measured the change in health by two categorical variables: a “major decline in health,” defined as a change in self-reported health status between baseline and endpoint either (1) from excellent, very good, or good health to fair or poor, or (2) from fair to poor, and a “new difficulty with mobility,” defined from specific questions asking whether the person had “no difficulty” with an activity at baseline, but was unable to perform the activity at the endpoint. Consequently, people already in poor health or unable to perform the mobility activities at baseline, as well as people who died, were excluded from the analysis. McWilliams et al. (2004) analyzed only mortality, ignoring changes in health status among survivors. We analyze a broader and more detailed measure of health prior to age 65, taking into account mortality, self-reported health status, and the presence of instrumental activities of daily living (IADL) or activities of daily living (ADL) limitations.

Finally, we use the results from our analysis of the relationship between insurance coverage and health prior to age 65 to simulate whether medical spending by newly enrolled, aged Medicare beneficiaries might be affected by extending continuous insurance coverage to all people between the ages of 55 and 64. We use data on health and medical care spending from the Medicare Current Beneficiary Survey (MCBS) to simulate the effects of a change in the distribution of initial health states on both total and public (Medicare plus Medicaid) medical care spending by 66-70-year olds. (1)