ABSTRACT
The purpose of the study is to provide an empirical and systematic analysis of board sanctions and, based on the results, determine if reference points can be developed for board members. Reference points would serve as an “historical portrait” of previously adjudicated cases, providing insight into the factors found to be consistently important when determining how similarly situated cases had been sanctioned in the past. The following discusses the study’s theoretical framework and methodology, selected data analysis results, and one of the five offense-based worksheets and accompanying sanctioning grid.
INTRODUCTION
One of the most important functions of a state health regulatory board is the handling of disciplinary cases. Perhaps the most difficult aspect of handling these cases is determining an appropriate sanction for those found in violation. Our state boards spend considerable time deliberating over appropriate sanctions: “Board members devote a great deal of time and attention to overseeing the practice of physicians by reviewing complaints from consumers, malpractice data, information from hospitals and other health care institutions, and reports from government agencies.”1
The sanctions imposed and the reasons they are imposed play a significant role in the board’s ability to protect the public while ensuring that their actions are fair. Even though boards may make great efforts to sanction in a rational and proportional manner, there has been criticism suggesting further improvements are needed. Criticism has come from respondents, attorneys, consumer groups, other government bodies and scholars. Sanctioning has been viewed as too harsh, too lenient, or inconsistent across cases or over time. Some have indicated that sanctioning variation can be attributed to other undesirable influences, such as board member ID or board composition, respondent ethnicity, attorney presence or location of hearing.
Such criticism has not, however, been supported by data collection and analysis that specifically focuses on the factors related to board sanctioning. Until now, no empirical work has systematically reviewed the case circumstances that lead to mitigated or aggravated sanctions for specific types of cases.2 Many have had their views of physician discipline and sanctioning shaped by a perceived harshness or leniency arising out of individual or high profile cases. A major study released in 2000 by Virginia’s legislative watchdog agency Joint Legislative Audit and Review Commission (JLARC) came to similar conclusions, citing the difficulty in assessing whether or not board sanctioning was “… consistent over time because most cases involved a unique set of factors …”3
Aware of the criticisms of board sanctioning, approximately 20 states have adopted or are studying the use of structured sanctioning systems. These systems all have similar goals and purposes (ensure consistency, reduce disparity, forecast resource needs, maintain discretion, etc.). Of these 20, only a few states have provided actual reference guides for physician sanctioning (Arizona, Ohio, Washington); however, no state has conducted a rigorous quantitative and qualitative analysis of historical sanctioning practices.
In April 2001, the Virginia Board of Health Professions (BHP) approved a work plan to conduct an analysis of health regulatory board sanctioning and to consider the appropriateness of developing historically based sanctioning reference points for health regulatory boards. The board and project staff recognized the complexity and difficulty in sanction decision-making and indicated for any sanction reference system to be successful, it must be “developed with complete board oversight, be value-neutral and grounded in sound data analysis, and be totally voluntary—that is, be viewed strictly as a board decision tool.”4 Recognizing each health regulatory board has a distinct sanctioning “culture,” each board’s sanctioning practices should be examined in their own right. For example, initial analysis shows sanction outcomes vary dramatically depending on which health regulatory boards are examined. Chart 1 illustrates primary sanction outcomes for Virginia’s four largest health regulatory boards.
VIRGINIA BOARD OF MEDICINE SELECTED AS PILOT BOARD
To begin the study in a manageable way, the Board of Medicine (BOM) was selected as the pilot board for study.5 Starting cautiously with a single board was important because no similar study had ever been performed. Taken together, the medicine and nursing boards (including nurse aides) comprise 70 percent of the entire DHP disciplinary caseload, so these two were given initial consideration when choosing appropriate boards to examine and when assembling an agency internal working committee. Using BOM cases also helped ensure an adequate number of cases and variation in case type during analysis. Piloting with a single board allowed analysts to test which study methods worked best before conducting further analysis across 13 distinct regulatory boards. It is also hoped that analytical efficiencies can be achieved before assessing each board.
QUALITATIVE AND QUANTITATIVE STUDY APPROACH
Qualitative
Analysts employed both quantitative and qualitative research methods to gain an understanding of sanctioning practice. On the qualitative front, researchers conducted 32 in-depth personal interviews of past and current BOM members (including key board staff and representatives from the attorney general’s office). The interview results were critical for building consensus regarding the purpose and utility of a sanctioning reference system and to further frame the analysis. Additionally, interviews ensured the factors board members consider when sanctioning were included during the quantitative phase of data collection.6
Research staff recognized sanctioning is exclusively a board member function. As such, any sanctioning reference system that is workable must be developed by board members for board members. The interview process and continuous board oversight guaranteed that board input was maintained during all study phases. In essence, board member input was used to create a “blueprint” to produce functional reference points based on a valid data analysis.
A number of options became available when selecting a methodology for examining board sanctioning and proposing reference points. Perhaps the most fundamental question was whether the sanctioning system should be grounded in historical data (descriptive) or whether it should be developed normatively (prescriptive) – that is, should the analysis reflect what policymakers feel sanction recommendations have been or what they should be? Reference points can also be developed using historical data analysis with normative adjustments to follow; this approach combines information from past practice with policy adjustments in order to change sanctioning practice to achieve a desired goal (to increase or decrease sanction severity, to direct persons into treatment programs, etc.).
In this study, the decision to proceed with a descriptive over a prescriptive model is based on a theoretical framework that is directly tied to the BHP and BOM’s purposes and goals of initiating sanction reference points. In Virginia, the goals and purposes most often cited by board members included:
Making sanctioning decisions more predictable
Providing an education tool for new board members
Adding an empirical element to a process or system that is inherently subjective
Providing a resource for BOM staff and attorneys (both sides)
“Neutralizing” sanctioning inconsistencies
Validating board member or staff recall of past cases
Constraining the influence of such undesirable factors as board member ID, overall board makeup, race or ethnic origin
Helping predict future caseloads and need for probation services and terms
The above list defined the study’s theoretical framework, clarified research questions and served as an anchor throughout the study period. Equally important, incorporating the stated goals impacted the form and structure of the sanctioning reference points. If disparity in sanctioning is found to exist, a goal could be to initiate reference points that ensure similarly situated respondents are sanctioned in similar ways, thus neutralizing sanctioning inconsistencies. If past sanctioning was deemed too lenient or harsh for a particular case type, a goal could be to create sanctioning references that treat selected case types in a manner different from the past (normative adjustments to past practice). Given the goals and purposes articulated by the BOM, analysts began with a purely descriptive approach. This approach is also considered the most incremental and cautious approach to providing additional structure to the sanctioning process.7
Quantitative
On the quantitative side, researchers collected detailed information on a sample of disciplinary cases ending in violation and receiving a sanction (as opposed to cases dismissed, undetermined, or where the person was found not in violation). The sample consisted of all cases closed by consent order or informal or formal conference during the period 1996–2001.8 Analysts used data available through the agency case management system combined with hard copy files containing investigative reports, board notices and orders, and all other documentation available to board members when deciding a case disposition. Although current automated data provides general information on sanction types, it does not adequately describe the offense and respondent factors which board members say influence sanction outcomes. These include, but are not limited to, precise degree of injury (physical, emotional, or threatened), prior record, retention of attorneys, time in practice, employment record, history of substance abuse, patient or source presence at hearing, etc. There is also disagreement on how these factors affect sanction outcomes. For example, the presence of an attorney in a case is thought by some to help a respondent, while others indicate retaining an attorney could result in a more unfavorable outcome. The analysis was designed to identify the factors that consistently played a role in sanctioning.
DESCRIPTIVE RESULTS
Chart 2 shows five general offense groups (identified under “case types”) that were derived from more than 30 specific case types. The greatest number of cases are Fraud/Deception/Misrepresentation and Patient Care cases, together comprising two-thirds of the sample. Patient Care includes physician performance cases such as delay in treatment and improper or unnecessary surgery issues. Fraud/Deception/Misrepresentation cases include such matters as deceptive advertising, claims of superiority, improper use of trade names, and certain business practices cases.
Sample Profile for the Virginia Board of Medicine
Chart 2 shows physical or mental injury occurred in roughly 26 percent of the cases. Eighteen cases over the six-year period involved patient death. The Virginia Department of Health Professions also evaluates complaints on a priority scale to help identify case seriousness. The table shows the six priority levels grouped into three categories ranging from the least serious Priority 5 and 6 (harm to the public without obvious risk) to the most serious Priority 1 and 2 cases (posing an imminent and substantial danger). All six of the priority levels are represented in the sample, with approximately 80 percent of the cases indicated as priority 2, 3 or 4. Priority 1 cases are represented in the study at a rate of 12 percent.9
About 40 percent showed evidence of some past substance abuse, mental health, boundary, or sexual deviance problems. Almost one-third of respondents were involved in counseling or some other type of self-corrective action at the time of their hearing. The vast majority of respondents were male, respondents had an attorney in 45 percent of the cases, 19 percent were international medical school graduates, and most had considerable experience practicing (on average, 18 years).10 Once reaching the board stage, the cases required an average of 11 months to process.
Roughly four of 10 respondents had at least one prior complaint filed against them (regardless of outcome), and 15 percent of the respondents had at least one prior board order or notice (reaching probable cause). About one-quarter of the respondents were involved in some concurrent action outside of the medical board’s purview (malpractice, etc.).
Patients were identified as especially vulnerable (e.g., juveniles, seniors, or mentally incapacitated) in about 10 percent of the cases, 17 percent of respondents were impaired at the time of the offense, and nine percent realized some type of material gain from their actions. More than one-half of the respondents had multiple patients or incidents associated with their offense(s).
Sanctions
The primary sanction types handed down by the board are shown in Chart 3. Because the sanction reference system was designed to provide general guidance — not detailed and specific recommendations — the board members agreed to classify the more than 30 types of sanctions and terms available to them into four general categories. The four groups were created based on the underlying goals and purposes of sanctioning (e.g., protecting the public, reprimanding, treatment and monitoring, etc.). For example, approximately one-quarter of the cases ended in a sanction primarily geared toward “protecting the public” by requiring the respondent to stop working for some period of time (e.g., suspension, revocation, or surrender of license).
Sanctions Handed Down
In an additional 35 percent of the cases, the respondent received some set of terms (e.g., counseling, chaperone, practice restrictions) requiring specific treatment or monitoring. The conceptual design of the sanction reference system is to identify a broad category of sanctions as a recommendation from which the board selects one or more specific sanctions. Approximately one-fourth of the cases ended in some type of loss of license. Almost 16 percent of cases ended in a violation where no sanction was given.
The 258 sanction events studied were resolved by a prehearing (consent order), an informal hearing or a formal hearing. Respondents opted to sign a consent order in one out of five cases, including agreeing to the findings of fact, a disposition, and if ordered, a sanction. Informal hearings were most common, where respondents chose to have their case heard by a panel of three board members. A formal hearing (requiring a minimum of five board members) occurred in roughly 12 percent of the cases.
MULTIVARIATE RESULTS AND SANCTION REFERENCE POINT DEVELOPMENT
After examining the BOM sample on a basic descriptive level, the empirical study proceeded in two stages. In the first stage, logistic regression was used to analyze the influence of all factors shown in Chart 2 on the board’s sanctioning decisions. Although it is impossible to predict with certainty the sanction a particular respondent will receive, logit analysis allows us to reasonably estimate the probability of a particular sanction by examining the statistical relationship between the characteristics of the respondent and the observed pattern of board decisions. That is, this analysis provided a clearer understanding of how, in practice, different sorts of factors influence board decisions. It identifies the factors board members emphasized most consistently. In the second stage, results from the logit analyses were used to craft a sanction reference system based solely on what the advisory group deemed to be legally relevant criteria.
To illustrate this approach, the left side of Chart 4 shows the results of a logit model used to determine which factors are significantly associated with the board’s decision that the respondent will “lose their license” (i.e., suspension, revocation or surrender of license) versus receiving some other sanction.11 The 30 individual factors are grouped into eight blocks with common properties. For example, the Injury block includes all factors related to the severity of injury and the level of risk of harm (priority level) to the patient. The coefficients indicate the relative influence of each independent variable on the probability a respondent will lose their license. A positive coefficient indicates larger values of the independent variable are associated with an increased probability of losing their license, while a negative coefficient indicates a diminished probability. Individual factors that were found to be significantly related to an increase in the probability of the respondent losing their license include12: the case types of Fraud/Deception/ Misrepresentation, Patient Care, Impairment;13 death of a patient; years in practice; days in board stage; prior board orders or decisions; and concurrent action (civil, malpractice, criminal, other). Some of the factors that are significantly associated with a decrease in the probability of the respondent losing their license include past alcohol treatment, attorney presence, treatment at time of the order and prior cases (not orders or violations).
Logit and Multinomial Logit Models
Chart 5 above shows how well the logit model predicts the board decision to revoke/suspend a respondent’s license. The model accurately predicted 88 percent of the cases (88 percent is computed from the shaded cells, 188 + 39 = 227 ÷ 258 total cases). This percentage is compared to the “null hypothesis,” defined as the most frequent outcome, which in this case is “no loss” (77 percent or 199 out of 258). Overall, we conclude that the model has significant explanatory capability. More importantly, we see that an empirical analysis of past sanctioning practices provides a way (1) to identify which factors have been historically important and can be used in a reference system and, (2) for the BOM to assess the legitimacy and fairness of past sanctioning practice.
Accuracy of Predictions of Logistic Regression Model
Looking back to the right hand side of Chart 4, the final step in developing a more sophisticated perspective on the sanctions respondents receive is displayed. This model moves beyond a simple loss/no loss outcome and instead focuses on four discrete sanctioning outcomes meted out by the board:
No sanction
Reprimand
Treatment/monitoring
Loss of license
As mentioned earlier, multinomial logit is a statistical technique used when there are more than two nominal categories. The results under the column headed “chi-square” show the significance of each factor in distinguishing which of the four broad sanction types is imposed by the board.14 Comparing the logit with the multinomial logit results shows that more factors become significant as we move from two general sanction categories to four. We view this result as confirmation that the four general sanction categories developed by the board have both intuitive and substantive meaning.
Not all individual factors are significant and not all significant factors met with board approval for inclusion in the sanction reference system. The size of the chi-square statistic allows one to assess the relative importance of each factor. Scanning the magnitude of the chi-square statistics shows relatively high values for such factors as past mental health problems, prior board orders and attorney presence at the board hearing. These results provided the board with the first multivariate look at past sanctioning practice and set the stage for determining which factors should be included in the sanction reference system. For example, the board determined the four factors in the group labeled Respondent Characteristics should not be explicitly considered as part of a structured sanctioning system. That is, factors like respondent gender or whether a respondent has an attorney present should not have a consistent impact on sanctioning decision. Such factors are often termed “extra-legal” because they are “extra” to the issues of respondent culpability and the need for treatment and monitoring. However, board members did acknowledge the legitimate role of some factors that were labeled extra-legal. For example, most agreed that a skilled attorney helped frame the case and often helped to clarify the facts and case circumstances. This was especially true for physicians with poor communication or presentation skills. But the board felt that the presence of an attorney should not, in itself, greatly influence the final sanction. Instead, the board wanted to ensure that recommended sanctions were based more consistently on “legal” factors.
To further assist the board in this assessment process, analysts examined the significance of the eight groups (or blocks) of independent variables: case types, injury, treatment, past problems, respondent characteristics, processing, prior record, and offense factors. As shown in Chart 6, the groups of factors labeled “past problems” and “respondent characteristics” had the most significant impact on the sanction type decision, although seven of the eight blocks were found to be consistently related to sanctioning decisions.
Block Tests for Multinomial Logistic Regression Model
Offenses Covered by the Reference Points
Offenses Covered by the Reference Points
All components of the multivariate analysis had several important implications for the development of sanction reference points. First, many types of factors are shown to be significant in the sanction decision process. Second, sanction choice has historically been determined by a mix of legal and extra-legal factors. Third, case type was important, so that the development of a separate offense specific (e.g., patient care, impairment, unlicensed activity) set of reference points was worth pursuing.
FROM DATA ANALYSIS TO SANCTION WORKSHEETS
Factors found to be statistically important were translated into offense and respondent attributes that could be scored on a worksheet in order to derive a sanction. To adhere as closely as possible to a descriptive model, the worksheet scores were proportionate to their relative importance in the models. However, in several instances the board made normative adjustments to the scores. The first type of adjustment involved removing all extra-legal factors, those the board felt should not be consistently scored on a worksheet. For example, the presence of an attorney, years in practice, respondent gender, and case processing time were not considered for scoring, even though they did help explain sanctioning variation in certain instances for certain offense groups. The second type of adjustment occurred when statistical weights did not intuitively match current board practice. For example, while patient injury was important, the statistical models did not discriminate between different levels of injury. This could have been due to the small number of cases with injury, or because this factor was not used consistently in past board decisions. In this case, the board worked with analysts to derive injury scores that made the most logical sense, with death being the most serious.
The remaining process of applying scores to each factor was an iterative and often complex exercise involving fine-tuning the factors and their relative scores. The accuracy of this process was measured by how well predicted sanctions on the worksheets matched actual sanctions handed down over the past six years. This was accomplished by retrospectively scoring all respondents (all 258 sanction events) using the worksheet scores. Grid recommendations were then derived by arraying all respondents in the sample on a two-dimensional grid using their offense and respondent scores (see sample Impairment worksheet below). The cell recommendations (No Sanction, Reprimand, Treatment/Monitoring, and Remove from Practice) were placed in each cell so the reference point recommendations will encompass, on average, about 70 percent of past historical sanctioning decisions; an estimated 30 percent of future sanctions will fall above or below the sanction point recommendations. This allows considerable flexibility when sanctioning cases that are particularly egregious or less serious in nature. Additionally, one of the most important features of this system is its voluntary nature. The board is encouraged to depart from the grid recommendation when aggravating or mitigating circumstances exist.
IMPLEMENTATION
The Virginia Board of Medicine will pilot test the sanction reference points for a period long enough to allow for an evaluation of the project’s utility. The reference points have an accompanying manual with detailed scoring instructions for each worksheet and grid. Although compliance with recommendations is strictly voluntary, the Board has agreed to complete worksheets in cases that are heard by an informal conference committee.15 As mentioned above, the Sanctioning Reference Points are organized into five offense groups. The scoring factors found within a particular offense group are those that proved important in determining historical sanctions for that offense category. When multiple cases have been combined into one “event” (one order) for disposition by the board, only one offense group worksheet will be completed that covers the entire sanctioning event. If a case has more than one offense type, one worksheet is selected according to the offense group that appears highest on the following table. For example, a physician found in violation of both fraud and a treatment-related offense would have their case scored on a Patient Care worksheet, since Patient Care is above Fraud/Deception/Misrepresentation on the table.16 The table also assigns the various case categories brought before the board to one of the five offense groups.
The following is the current worksheet used for Impairment cases. After calculating an offense and respondent score, the person completing the worksheet finds the intersection of the two scores on the grid at the bottom of the page.
Worksheet and Grid Example
Management and Use of Worksheets
Instructions are provided for each line item of each worksheet to ensure accurate scoring for a specific factor.17 The scoring weights assigned to a factor on the worksheet cannot be adjusted. The scoring weights can only be applied as ‘yes’ or ‘no’ with all or none of the points applied. In instances where a scoring factor is difficult to interpret, the board has final say in how a case is scored.
If the board feels the sanctioning grid does not recommend an appropriate sanction, the board is encouraged to depart either high or low when handing down a sanction. If the board disagrees with the sanction grid recommendation and imposes a sanction greater or less than the recommended sanction, a written departure explanation will be recorded on a separate cover sheet. The explanation will identify the factors and the reasons for departure. It is hoped that this process will ensure that worksheets are revised appropriately to reflect current board practice. If a particular reason is continually cited, the board can examine the issue more closely to determine if the worksheets should be modified to better reflect board practice.
Aggravating and mitigating circumstances that may influence board decisions can include, but should not be limited to, such things as:
Prior record
Dishonesty/Obstruction
Motivation
Remorse
Victim vulnerability
Restitution/Self-corrective action
Multiple offenses/Isolated incident
As shown earlier, the sanction grids have four separate sanctioning outcomes: remove from practice, reprimand, treatment/monitoring and no sanction. Chart 8 on the next page lists the most frequently cited sanctions under the four sanctioning outcomes that are part of the sanction grid. After considering the sanction grid recommendation, the board will fashion a more detailed sanction based on the individual case circumstances.
Specific Sanction Options Available Under Each Grid Recommendation
SUMMARY
Under the proposed research approach, the development of useful and credible sanction reference points depends largely on the ability to closely integrate both quantitative and qualitative methods. The consensus building within and across the different health regulatory boards helps to direct and narrow the scope of the study, and feedback from in-depth interviews and exercises is used to formulate research goals and to guide the data analysis. Preliminary research shows the development of empirically based sanctioning reference points is possible in an effort to ensure consistency and reduce disparity in sanctions.
Perhaps as important to recommending a sanction, the system allows each respondent to be evaluated against a common set of factors, making sanctioning more predictable, providing an educational tool for new board members, and neutralizing the possible influence of “inappropriate” factors (e.g., race, sex, attorney presence and identity of board members). Future plans call for evaluating the proposed system to determine if board members, health professionals, and the general public have benefited from the new policy.
The authors are grateful to the Virginia Board of Medicine and the Virginia Board of Health Professions for having the courage and vision to allow this important research initiative to advance. For providing the leadership necessary to sustain this project, special thanks goes to Dr. Harold Beaver, Past-president, and Dr. Diane Reynolds-Cane, President, Virginia Board of Medicine. Also to Dr. William Harp, executive director, and Karen Perrine, Esq., deputy executive director, along with other members of the staff of the Board of Medicine for graciously assisting in all aspects of the study. Very importantly, we wish to recognize Robert Nebiker, agency director, Virginia Department of Health Professions, for his unwavering support throughout the entire process. Kimberly Langston, M.S., Patrick Davis, M.B.A., and Brian Ostrom, Ph.D., skillfully assisted in the data analysis and planning phases of the study.
REFERENCES
- 1.↵What is a State Medical Board? Federation of State Medical Boards, www.fsmb.org.
- 2.↵Although little empirical work has been published on the issue of health regulatory sanctioning practice, there is considerable literature available on court related sanctioning practices. See Michael Tonry, Sentencing Matters, 1996; Sentencing Commission Profiles, National Center For State Courts, 1997; National Assessment of Structured Sentencing, Bureau of Justice Assistance, 1996: Andrew Von Hirsch The Sentencing Commission and Its Guidelines, June 1987.
- 3.↵Joint Legislative Audit and Review Commission, Final Report: Review of the Health Regulatory Boards, House Document No. 5, 2000.
- 4.↵Department of Health Professions Internal Committee and Staff, Fall 2001 organizational meeting.
- 5.↵The Virginia Department of Health Professions houses 13 distinct boards for the following professions: Audiology and Speech, Counseling, Dentistry, Funeral Directors and Embalmers, Medicine, Nursing, Nursing Home Administrators, Optometry, Pharmacy, Physical Therapy, Psychology, Social Work and Veterinary Medicine.
- 6.↵Interviews were conducted from January to April 2002. All candidates were given the opportunity to have the interview conducted at their location. The interview format consisted of 17 open-ended questions covering a wide range of sanctioning issues. Individual board member anonymity was maintained when reporting out results.
- 7.↵As will be discussed later, some normative adjustments were considered to ensure sanctioning consistency and to neutralize certain factors identified in the statistical analysis that were deemed inappropriate by board members.
- 8.↵Quantitative analysis includes data collection and statistical analysis of all automated and non-automated files on a representative sample of cases. The analysis is intended to differentiate similarly situated cases (same case type, level of seriousness, history of recidivism, etc.) in terms of case outcomes and sanction. In total, 447 cases were identified with the final sample consisting of 258 sanctioning “events.” A comprehensive data collection instrument with 120 variables captured the factors identified as potentially impacting sanction decisions. Narrowing the sample involved removing reinstatement and compliance cases, mandatory suspensions, and actions by other states. Most of the narrowing was due to merging multiple cases handled in a single order into a single sanctioning “event.” The sanction event is more reflective of actual board work, as board members fashion sanctions based on the “totality” of behavior, not for each “case” docketed.
- 9.↵Physical and mental injury first were measured on separate scales. A case(s) could have both mental and physical injury associated with one or more patients.
- 10.↵Although the board expressed interest in examining race and ethnicity, the information was not found in the case files nor was it collected on any agency or board related documents. Board members expressed an interest in modifying agency systems to collect race and ethnicity in the future.
- 11.↵Logit regression analysis controls simultaneously for the influence of independent variables on the likelihood of “loss of license”— the dependent variable. This enables researchers to determine the unique contribution of each case factor in explaining the type of sanction received. In addition to logit, analysis also involved using multinomial logistic regression. Where logit is appropriate with dichotomous dependent variables, multinomial logit was used when there were more than two categories of the dependent variable. The left side of Chart 4 shows the results when “sanction type” is coded as a dichotomous variable (“1” for loss of license, “0” if not) and right side shows the results when the case outcome was broken into four sanction categories.
- 12.↵The standard level of statistical significance is <.10 (one-tailed test). The Wald statistic is calculated for every independent variable by dividing the coefficient estimate by its standard error. The Wald statistic is used to test the significance of each coefficient with an “x” indicating significance for the Wald statistic.
- 13.↵The reference category for case types is Inappropriate Relationship/Sexual Abuse, and Level 5 and 6 for Priority (under Injury).
- 14.↵The standard level of significance is <.10 (one-tailed test).
- 15.↵There are five exceptions: formal hearings, consent orders, mandatory suspensions, compliance and rein statement cases, and cases that are the result of an action by an out-of-state board or other entity.
- 16.↵The hierarchy of offenses was established by comparing the loss of license rate for the five offense groups.Impairment cases had a loss rate approaching 43 percent while unlicensed activity cases were about 4 percent.
- 17.↵See Sanction Reference Points Instruction Manual, July 2003, Virginia Department of Health Professions.
