Economic pressure on German hospitals has increased considerably in recent years. From 1994 to 2003/2004, hospitals were subject to capped budgets that could only increase in line with annual payroll revenue increases of the statutory health insurers, who insure 90% of the German population.1 In 2003/2004 a prospective payment system for >95% of all inpatient services, based on Diagnosis Related Groups, was implemented.2,3 Unsurprisingly, German hospitals engaged in numerous activities to improve their efficiency.4 Of particular importance are management innovations that focus on industry-specific, high-cost areas, such as operating rooms (ORs).5–8 In addition to being high cost, operation of the surgical suite requires a high level of coordination; a large number of interest groups (surgery, anesthesiology, nursing, technicians), with often differing objectives, have to cooperate closely to improve efficiency.9–13
The objective of reducing tardiness of first case of the day starts has traditionally been (and continues to be) a focus of the literature on OR management.14–22 Although starting the day late may seem to have a “cascading effect” on surgeries for the remainder of the day,18–21 this argument has since been proven to be incorrect.23–26 Tardiness of first case starts is important, however, because it continues to be perceived as a key indicator of inefficiencies in the surgical suite21 and can substantively increase overutilized OR time.15,17,24
In this context, we explored whether the introduction of an OR manager, OR charter, or both, reduced tardiness of first case starts. Our empirical sample is derived from 257 German anesthesiology departments that responded to a 2005 detailed survey on OR management, which was conducted by the German Society of Anesthesiology (see Supplemental Digital Content 1: Current State Anesthesiology Cost and OR Management Questionnaire, http://links.lww.com/AA/A410). Although descriptive results of this survey have been published,27,28 our study derived a hypothesis and applied inferential methods to the data.
BACKGROUND AND HYPOTHESIS DEVELOPMENT
A unique aspect of current German surgical management is that many of the successful strategies reported in the international literature that rely on parallel processing in the induction area and ORs to increase OR efficiency29–33 face legal limitations in Germany. The reason is that having 1 anesthesiologist responsible for 1 anesthetized patient is still mandatory.34 This restricts the set of feasible OR management tools mostly to changes in governance arrangements and organizational changes to the surgical suite. The surgical management tools we studied were the appointment of an OR manager and the development and adoption of a surgical suite governance document (OR charter35).
An OR charter is a written policy statement that is jointly created by the various OR stakeholders.9–13 In an attempt to improve and standardize the processes in the surgical suite, an OR charter describes OR processes and governance rules in detail.35 It generally includes statements about the objectives of surgical suite organization, a description of the scope of application, a job description of the person charged with OR coordination, rules for planning and scheduling, methods for perioperative processes, rules on intensive care use, and rules and procedures for managing emergency patients.34–36 Most charters also specify a certain time for first case starts. In our questionnaire, we first asked whether the surveyed anesthesiology department had an OR charter. If the answer was yes, we used a Likert scale to elicit the degree of detail to which the charter regulated first case starts, ranging from 1 (no regulation) to 5 (very detailed).
Whereas an OR charter is a tool that is implemented to increase efficiency, the incentive mechanisms by which an OR charter may affect OR performance are not well understood. Whereas direct financial incentives appear to have a very limited effect on OR performance,37 peer pressure effects potentially play a large role, because a department or physician found in constant violation of the charter might be subject to considerable peer pressure.10,38a
Another widely used coordination tool is the creation of the position of OR manager.35,41–44 The OR manager is usually responsible for short-term operative OR management, logistics management, and administrative management. His or her role also encompasses short-term day-to-day planning of OR use and demand management for OR capacity, which originates from both elective and emergency cases. Sometimes, he or she is also responsible for less-detailed intermediate weekly, monthly, or quarterly planning. In his or her role as logistics manager, he or she essentially ensures that the OR is in running order, with supplies of all required materials and a sterile working environment maintained at all times. Finally, the OR manager is responsible for areas such as detailed documentation of all services provided in the surgical suite for reimbursement purposes and for cost control.
Similar to the OR charter, there is little extant work on the exact mechanisms that translate the existence of an OR manager into improved OR performance. Indeed, Masursky et al. found that OR nursing directors may pursue goals other than OR productivity.11 Stepaniak et al. found that more risk-averse OR coordinators result in more unused OR time and thus reduce OR efficiency.45 In the managerial economics literature, Huddart and Liang argued that hiring an “executive partner,” who has sole responsibility for monitoring activities, increases both the quality of monitoring and productivity.46 In our setting, OR managers are designated to monitor activities inside of the OR, so we expect OR productivity (measured by first case starts) to improve. On the basis of this discussion, we propose the following hypothesis: Existence of an OR manager and/or an OR charter reduces tardiness of the starts of first cases of the day at German hospitals.
At the end of January 2006, we sent questionnaires to 1305 anesthesia department heads in German hospitals.47 The official deadline for their return was May 30, 2006. To improve the response rate, we sent a reminder in mid-May 2006 and extended the deadline to November 30, 2006. No questionnaires were accepted after December 1, 2006. Two hundred fifty-six fully or partially answered questionnaires were returned, which corresponds to an overall response rate of 19.6%.27,28 This was similar to response rates obtained in earlier surveys48 and is considered typical and satisfactory by the German Society of Anesthesiology's representatives.
We first analyzed whether our survey data were representative for the German hospital industry (Table 1contains our sample descriptive statistics). We compared hospital characteristics such as ownership status and number of beds from our survey with official German hospital data from the Federal Statistical Office.49 In 2005, 35% (46%) of German (our sample) hospitals were owned by cities, counties, or states (public ownership). The percentage of nonprofit hospitals owned by churches and charitable organizations (e.g., German Red Cross) was 38% (46%). Twenty-seven percent of all German hospitals are privately owned and may be either for-profit or nonprofit. In our survey data, only 8% belong to this group, causing it to be underrepresented. Further analysis showed that this can be explained by the conspicuous absence from our survey of respondents from very small specialty hospitals, with fewer than 50 beds. While 19% of all German hospitals are in this category, only 1% of our sample consisted of small specialty hospitals. Our results therefore do not apply to this class of hospitals.b Consequently, we expect that inferences are possible from our results for all but very small (fewer than 50 beds) and privately owned German hospitals.
After eliminating questionnaires exhibiting obvious inconsistencies and missing values in the answers concerning the OR management, 244 responses contained sufficient information on OR management (presence/absence of OR management, number of ORs, etc.). Inconsistencies included a reported implementation date of an OR management tool later than the survey date and incomplete information on surgical suite management. A further 105 observations lacked sufficient information concerning our performance measure for tardiness. We lost another 32 observations because of missing entries for our control variable concerning surgical suite complexity. This variable was constructed from the numbers of disciplines using the surgical suite and their respective case loads (see below). The final sample contained 107 usable observations.
OR Performance Metric
Our performance measure was reported tardiness of first case starts, denoted Tard. This choice was motivated by the early OR management literature that argued that tardiness of first case starts is subject to considerably fewer random (stochastic) influences beyond the control of OR management than turnover time.10 Note that the previous statement only applies to the German situation with at least 1 responsible anesthesiologist per OR50 and may not apply to surgical suite management scenarios in which anesthesiologists supervise multiple ORs.51 We measured Tard as minutes delay in relation to the scheduled start. Our measure of Tard was derived from responses to the survey question: “scheduled beginning of first procedure in the OR deviates from actual beginning by _____ minutes on average.” We emphasize that this value constitutes self-reported assessments of the surveyed persons (chief or senior physician of anesthesiology department). Our questionnaire also contained a question that asked whether the entered data were systematically collected from an objective source such as an OR data management tool or were just estimated. On the basis of the findings of a recent United States study with findings that anesthesiologists' self-reported perceptions of turnover times tended to be unbiased in comparison with those of surgeons,52 we included all reported values of Tard in our analyses but addressed this issue in our robustness tests.
There are obviously huge differences in scope and complexity of OR activities between a small basic care hospital with 1 to 2 ORs and a tertiary medical center performing complex surgeries in 16 to 20 ORs. It has long been recognized in managerial accounting that the number of production facilities leads to an increase in coordination activities.53,54 To address this issue of surgical suite complexity, on the basis of findings from the OR management literature,34,55–57 we constructed a Herfindahl index of concentration on the basis of the number of cases per discipline for the various disciplines using the surgical suite. The control Herfindahl is computed as
, where a equals the number of cases in discipline i using the hospital's surgical suite. A value for Herfindahl close to 0 (1) implies low (high) concentration, i.e., many (few) disciplines use the OR. This relates to high (low) complexity because it reflects the magnitude of the coordination problem in the surgical suite. Additional controls for hospital size included the number of beds and the number of ORs in the hospital, denoted by the variables Beds and OR, respectively.
Tardiness in relation to the scheduled first case starts is a number that is always nonnegative. This truncation at zero necessitates careful consideration of the appropriate empirical methodology. For example, use of ordinary least squares models could result in a downward biased estimate of the slope coefficient and an upward biased estimate of the intercept. To address this issue, we used a Tobit model to estimate the relationship between Tard and the independent variables.58–60
To test our hypothesis, we estimated the following equation:
where Tard = tardiness in minutes in relation to scheduled start; OR management tool = 1 if hospital has an OR charter, an OR manager, or either, and 0 otherwise; Herfindahl =
, with ai = number of cases in discipline i using the hospital's surgical suite; Beds = number of beds in the hospital; OR = number of ORs in the hospital.
Table 1 reports descriptive statistics for our variables of interest. Both use of an OR manager (75%) and use of an OR charter (81%) were popular. Because many hospitals used both (69%), it is important to examine the tools both individually and together. The mean tardiness of first case starts is 15 minutes. OR complexity (Herfindahl) ranges from simple (1) to complex (0.1156).
Table 2 provides results of the tobit estimation of model 1. Consistent with our hypothesis, the presence of an OR manager or an OR charter reduced tardiness of first case starts by at least 7 minutes (mean reduction 15 minutes, 95% confidence interval [CI], 7–22 minutes, P < 0.001).c
The coefficient of Herfindahl was both negative (a reduction in mean tardiness of about 15 minutes for less complex surgical suite scenarios) and significant in our estimation model (95% CI, 0–29 minutes, P = 0.032). As one would expect, morning tardiness thus tended to be less of a problem in simpler OR settings (with few disciplines sharing the OR). Other variables in the model were not significantly different from zero at conventional levels.
We performed a series of robustness tests to increase confidence in our results (untabled; details available from the authors). Our results remained qualitatively consistent across all of our tests. Our tests included examination of the sensitivity of our results to (1) inclusion of self-reported tardiness rather than an objective measure of tardiness;61,d (2) ownership status; (3) the length of time that an OR management tool had been in existence at the time of our survey (these results are consistent with those of Lapierre et al.)10; and (4) potential self-selection by hospitals that chose to answer our survey. e
Our results provide evidence that the introduction of an OR manager, the adoption of an OR charter, or both can have an effect on tardiness of first case starts. This provides a starting point for further investigation of the impact of OR management tools. For example, though we find significant results for broadly defined OR management tools (OR charters and managers), our sample size limits the depth of our investigation. For example, OR managers differ with respect to professional background (physician, nursing, other).
Although our results are statistically significant, the question remains whether the tardiness reductions for first case starts are economically significant. Several methods of determining economic impact have been suggested in the literature. Dexter and Epstein and McIntosh et al. provided a framework of the set of ordered priorities for surgical suite management.15,24 Within this framework, economic impact of OR management tools can be viewed as stemming from (1) efficiency increases from long-term investments (such as investments in the OR management tools we examine); (2) improvements in short-term decision making on the day of surgery, resulting in an increase in the number of additional surgical cases that can be performed (access of surgeons to OR time)24,62,63; and (3) reduction in overutilized OR time (which either creates direct costs because of overtime pay or intangible costs, e.g., OR staff dissatisfaction).f,g
Clearly, the introduction of an OR manager and the adoption of an OR charter constitute long-term investments. Unfortunately, we lack the necessary cost data to assess whether these tools have “earned their keep” by improving OR efficiency sufficiently to justify the related expenditures.h It is also hard to argue that the mean decrease in tardiness by 15 minutes is sufficient to allow additional surgical cases to be performed, a statement that is corroborated by findings in the extant literature.25 Perhaps the most compelling case for economic impact that can be made is for a possible reduction in the hours of overutilized OR time. This issue is clearly relevant to the German setting because most surgical suites routinely operate at capacity during the work week. i In this context, overutilized OR time either creates direct costs because of overtime pay or intangible costs in the form of OR staff dissatisfaction, possibly leading to high staff turnover. For such a situation, Dexter and Epstein found in their screening analysis for the application of the McIntosh et al. method that each minute reduction in tardiness of first case starts typically resulted in a mean reduction of 1.1 minute (with an SE of ±0.1 minute) in regularly scheduled labor costs.15,24 Thus, in the short term, tardiness can be linked to personnel costs in a meaningful way. It is important to note, however, that even though tardiness of first case starts is frequently used as a key OR performance indicator in Germany and elsewhere, targeting this indicator may be quite costly because many ORs (the entire surgical suite) have to be coordinated simultaneously at considerable transaction cost.25 A full evaluation of the economic benefit would necessitate consideration of these costs in balance with the benefits.
Our study suffers from a number of limitations. A general problem is the relatively low explanatory power of our model. Data heterogeneity is considerable for our performance measure of tardiness of first case starts. A possible explanation is that tardiness in the morning is affected by many factors that we cannot control for in our data. Obvious examples are distance(s) from the wards to the surgical suite, age of buildings and elevators, etc. Other possible factors include the degree of sophistication of a hospital's internal transport system (radio frequency identification technology versus paper slips or phone calls). As stated earlier, our sample size was too small to extend the analyses to ordered subsamples ranked by hospital size or surgical suite complexity. Thus, we cannot provide meaningful comparisons with the results obtained for the single institution settings studied in previous work.10, 11,15,17 This constitutes a promising avenue for future research.
Although we made an attempt to control for selection bias in the robustness section, we cannot exclude the possibility that adoption of an OR management tool was nonrandom and depended on unavailable background variables. This is clearly a concern for all studies that perform cross-sectional analyses across large numbers of hospitals. Because these studies are decidedly in the minority in comparison with studies based on one site or a small number of sites, it is clear that this issue must be addressed in future research. Apart from industry-wide trends such as a change in reimbursement systems (e.g., German diagnosis-related groups), little is known about the factors that cause hospitals to introduce surgical suite management systems and how they are organized.
Another concern is the quality of the self-reported tardiness data. Although we addressed this in the robustness section econometrically, exclusive use of hard data on tardiness extracted from information technology–based OR management tools would be clearly preferable.
Name: Christian Ernst, PhD.
Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.
Attestation: Ernst has seen the original study data, reviewed the analysis of the data, approved the final manuscript, and is the author responsible for archiving the study files.
Name: Andrea Szczesny, PhD.
Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.
Attestation: Andrea Szczesny has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Naomi Soderstrom, PhD.
Contribution: This author helped analyze the data and write the manuscript.
Attestation: Naomi Soderstrom has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Frank Siegmund, PhD.
Contribution: This author helped design the study and conduct the study.
Attestation: Frank Siegmund has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Alexander Schleppers, MD.
Contribution: This author helped design the study and conduct the study.
Attestation: Alexander Schleppers has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
This manuscript was handled by: Franklin Dexter, MD, PhD.
a The charter may also be interpreted as the introduction of an implicit social norm (tardiness is substandard, so work should start on time to reduce tardiness) that may (positively) affect team performance.39,40
b Small specialty clinics often have only 1–2 ORs, which are used by only 1 specialty. Consequently, questions of OR management may not be very pressing in such an environment.
c Because many of the hospitals that use an OR manager also use an OR charter (69%), we also investigated the relation between the 2 OR management tools in reducing tardiness using an interaction term. Results (untabled) indicate a reduction of 7 minutes (95% CI: 1–13 minutes, P = 0.012). This estimate is significantly lower than for either OR manager alone or OR charter alone (untabled), indicating that there is no advantage to using both tools at the same time.
d Because of missing values, this reduced the number of usable observations to N = 79. Re-estimating the models for these 79 observations did not alter our main results for reduced tardiness. In the models, the coefficient of estimate was positive and weakly significant (P = 0.062), which indicates that subjective assessments tended to overestimate tardiness. This was consistent with a recent finding for the assessment of turnover times by surgeons.52
e Unfortunately, we were unable to address this issue using propensity scores (which is a typical methodology used for this purpose) because we lacked information on the necessary background variables (financial situation, economic responsibility of department head, etc.). To attempt to correct for a possible selection bias, we re-estimated all models using the Heckman procedure,60 which uses an inverse Mills ratio as a further independent variable. Intuitively, the Mills ratio may be interpreted as the inverse of a hospital's probability to adopt an OR management mechanism. We obtained the inverse Mills ratio from a probit model that models the probability of the existence of OR management on the basis of ownership status, surgical suite complexity (Herfindahl), number of beds, number of ORs, and position in the German hospital hierarchy (basic care, regular care, specialized care, maximal care hospitals). In this estimation we found that an increase in complexity (Herfindahl decrease) significantly (P = 0.053) increased the probability of OR management mechanism adoption. In addition, this probability was significantly lower (P = 0.054) for smaller basic care hospitals in comparison with regular care hospitals. Results from incorporating the inverse Mills ratio into the original estimations continued to provide evidence of a tardiness-reducing effect of a surgical suite management, although the inverse Mills ratio was insignificant. This suggests that (within the limitations posed by our data) selection bias appears to have played a limited role in our results.
f Whereas the German situation until about 2005 was characterized by high intangible costs because of OR staff being asked to routinely provide uncompensated overtime, recent changes to labor laws and a marked shortage of qualified OR staff have led to an increase in direct costs. Whether or not this changed the relative cost ratio between regular OR time and overutilized OR time remains an open question.
g For this scenario, Dexter and Epstein (2009) found that each minute reduction in tardiness of first case starts resulted in a 1.1 minute (with a standard error of ±0.1 minute) reduction (mean) in regularly scheduled labor costs.15
h These constitute mainly opportunity costs, because an anaesthesiologist/ senior nurse appointed OR manager cannot work in her former capacity.
i The problem of underutilized OR time as described by Dexter et al. (2006) for U.S. community hospitals is therefore not an issue.64
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