Literature DB >> 10170577

Outcomes of surgery under Medicaid.

D Klingman, P L Pine, J Simon.   

Abstract

In this study, health outcomes during the 6-month period following surgery are examined for all Medicaid recipients in Michigan and Georgia who underwent selected surgical procedures between July 1, 1981, and June 30, 1982. Readmissions were somewhat more prevalent in both States for hysterectomy, cholecystectomy, appendectomy, and myringotomy. On almost all measures in both States, levels of post-surgical utilization, expenditure, and complications were higher among females, older patients, Supplemental Security Income enrollees, and those with higher levels of presurgical utilization and longer and more costly surgical stays. The results further demonstrate the utility of claims data in monitoring outcomes of surgery.

Entities:  

Mesh:

Year:  1990        PMID: 10170577      PMCID: PMC4193089     

Source DB:  PubMed          Journal:  Health Care Financ Rev        ISSN: 0195-8631


Introduction

The growing interest in assessing and assuring the quality of health care has spurred the search for efficient methods of measuring the numerous dimensions of that complex concept. Of particular interest is the dimension that many observers consider the ultimate criterion for judging the quality of a health care intervention: its outcome, or whether it has the intended effect on the health status of the patient. The ideal method of measuring the outcomes of health care involves repeated assessment of the health status of large numbers of individuals with a given health condition, some of whom undergo the intervention and some of whom do not. Unfortunately, this method of the controlled clinical trial is extremely expensive when employed on a sufficient number of cases to provide statistically reliable results. It also raises serious ethical questions, e.g., withholding treatment from control patients when the treatment proves effective, or risking adverse effects to experimental patients when it does not. Attention has instead focused on methods of employing secondary sources of data—medical records, hospital discharge abstracts, insurance claims, and vital records (birth and death certificates)—to capture indirect indicators of health outcomes. Most of the studies of health outcomes that have used health insurance claims (reviewed in the following section) have employed data from the Medicare program. Apparently none have used data from the Medicaid program, even though the latter is roughly comparable in magnitude to the former in terms of recipients, if not reimbursements (Ruther et al., 1987), and even though Medicaid targets the Nation's most vulnerable subpopulations: low-income elderly, disabled, and families with dependent children. This study uses Medicaid data from two States, Georgia and Michigan, to assess the outcomes of selected surgical procedures among Medicaid recipients who are not also eligible for Medicare. The purpose of the article is to demonstrate that claims data can be useful in identifying potential problems in the quality of care. It does not attempt to draw definitive inferences about differences in the quality of care among surgical procedures, patient groups, or States; factors influencing the quality of care; or Federal or State policy regarding the quality of care.

Previous studies

Mortality

Not surprisingly, the concept of health care “outcomes” is usually operationally defined as the occurrence of events that signal adverse consequences for the patient. Few would disagree that the most serious such outcome is death, which has thus been the usual focus of previous outcome-oriented studies. Most such studies (Luft, Bunker, and Enthoven, 1979; Luft, 1980; Shortell and LoGerfo, 1981; Flood, Scott, and Ewy, 1984a and 1984b; Maerki, Luft, and Hunt, 1986; Sloan, Perrin, and Valvona, 1986; Kelly and Hellinger, 1986; Blumberg, 1986; Rosenfeld et al., 1987) have confined that focus to deaths that occur during hospitalization. This limitation arises largely from reliance on hospital discharge abstract data, for few analysts would argue that only in-hospital mortality can be attributed to hospital care. Some early studies of hospital-related mortality (Brook et al., 1971; Stanford Center for Health Care Research, 1976; Flood et al., 1982) employed followup assessment and interviews to measure mortality up to 6 months after discharge. More recently, public health insurance claims and enrollment data have been used to link information on hospital care and subsequent death up to 1 year following surgery (Lubitz, Riley, and Newton, 1985; Riley and Lubitz, 1985; Wennberg et al., 1987). Most of these studies have concentrated on the inverse relationship at the hospital level between mortality (number of deaths) and surgical volume (number of surgical procedures). All have demonstrated that, for most surgical procedures, mortality is lower for hospitals that perform more surgery, either of the specific type being studied or overall. The evidence of the relationship appears strong enough to prompt most analysts to advocate regionalization of surgery for certain procedures. The direction of causality underlying this relationship remains unclear, however. It could be that hospitals performing more surgery gain experience that reduces mortality or that hospitals known to have lower death rates (for reasons unrelated to surgical volume) attract more referrals for surgery. There appears to be no corresponding relationship between volume and mortality at the individual physician level (Kelly and Hellinger, 1986), and evidence on the independent effect of other hospital and physician characteristics on patient outcomes is quite mixed. In addition, two recent studies urge caution on regionalization of surgery. Maerki, Luft, and Hunt (1986) point out the need for emergency treatment in small-volume hospitals, given their distance from designated regional specialty hospitals. They also question the capacity of some designated regional hospitals to handle a larger patient load. Sloan, Pen-in, and Valvona (1986) found variation in mortality to be more procedure-related than volume-related and concluded that “an adequate statistical basis for setting minimum volume standards does not presently exist.” These two studies appear to support Donabedian's (1984) call for further research on the nature of the association between outcome and organizational characteristics before regionalization of surgery is uncritically adopted. A related area in the literature on hospital outcomes has focused on the survival rate of patients receiving intensive care, specifically the inverse relationship of the survival rate to the cost of such care (i.e., the positive association between mortality and cost). That is, patients consuming the most resources tend to have the lowest survival rate (i.e., the highest death rate). A more refined analysis that employed measures of extent of therapy and severity of illness (Scheffler et al., 1982) found that the relationship is actually U-shaped. That is, as the extent of therapy increases, the probability of death initially declines, then levels off, and finally increases rapidly. Again the dependent variable has usually been death in the hospital (Civetta, 1973; Turnbull et al., 1979; Scheffler et al., 1982), but a few studies have used followup assessment and interviews to capture post-hospital mortality as well (Cullen et al., 1976; Thibault et al., 1980; Chassin, 1982). Another related area involves the nature of catastrophic illness and the characteristics of high-cost patients, including their mortality rates. These studies have further demonstrated the direct relationship between probability of death and amount of health care resources consumed, which stems from the fact that patients requiring more services tend to be older and more often near death. (They are also presumably “sicker,” but no consensus has yet been achieved on how best to measure initial severity of case mix.) Again, the focus has usually been confined to death in the hospital (Schroeder, Showstack, and Roberts, 1979; Zook and Moore, 1980), but one study matched patient records to death records to obtain rates of post-hospital mortality (Schroeder, Showstack, and Schwartz, 1981). These studies have been conducted with an eye toward development of catastrophic insurance, especially for Medicare recipients. They also imply that improved methods of diagnosing terminal illness need to be developed so that appropriate forms of palliative care (especially hospice) can be encouraged and scarce acute care resources redirected to patients with better prognoses. Indeed, the extent of discrepancies between premortem and postmortem diagnoses has been proposed as an indicator of the quality of care (Anderson, 1984).

Nonmortality outcome measures

Although mortality may be the most serious adverse outcome of hospital care, it is by no means the sole indicator of the quality of that care (Kelly and Hellinger, 1986). Most importantly, patients who survive hospitalization vary in their degree of morbidity (extent of illness). A few of the studies of post-hospital mortality (Brook et al., 1971; Stanford Center for Health Care Research, 1976; Flood et al., 1982) have also used followup interviews to assess the patient's health and functioning for up to 6 months after discharge. A similar approach has been employed in randomized trials designed to assess the efficacy of specific surgical procedures, such as tonsillectomy (Paradise et al., 1984), and was recently used to analyze outcomes among patients with chronic obstructive pulmonary disease (Strauss et al., 1986). A less direct but still useful approach to measuring morbidity has been to quantify the patient's extent of utilization of health care following hospitalization. As with morbidity, this approach has been employed to supplement analyses of post-hospital mortality (Chassin, 1982) and to assess the efficacy of various surgical procedures (Roos and Roos, 1983), including tonsillectomy (Roos, Roos, and Henteleff, 1978) and prostatectomy (Wennberg et al., 1987). More recently, it has been used to compare outcomes among patients of family physicians and internists (Franks and Dickinson, 1986). A related area of the literature has focused on the “offset effect” of treatment for mental illness (Mumford et al., 1984; Borus et al., 1985) and alcoholism (Holder and Blose, 1986) in reducing health care utilization and expenditures. One specific form of utilization following an initial hospital stay has received special attention in the literature, namely hospital readmission. Hospital recidivism has been shown to vary greatly among the States (Gornick, 1977) and to be a major factor behind high-cost use (Anderson and Knickman, 1984). In particular, readmission for the same disease accounts for nearly 60 percent of all hospital charges (Zook, Savickis, and Moore, 1980). Similarly, the probability of undergoing reoperation (specifically, prostatectomy)—not necessarily related to deficiencies in care—can be as high as 33 percent (Wennberg et al., 1987). Analysis of Medicare data reveals that “… expenditures are highly concentrated on a small percentage of beneficiaries who are repeatedly admitted to the hospital … [and] that a high percentage of Medicare hospitalizations are followed by readmissions within short periods of time” (Anderson and Steinberg, 1984). Predictors of repeat hospitalization (Zook, Savickis, and Moore, 1980; Anderson and Steinberg, 1985; Fethke, Smith, and Johnson, 1986) include: Diagnosis (severe, chronic illnesses, especially those requiring life-maintenance therapy). Absence of surgery. Dependence (especially widowhood). Low levels of life satisfaction. Harmful personal habits (e.g., substance abuse). Eligibility for Medicaid. For certain surgical procedures, rehospitalization rates among Medicare recipients are also higher for males and older patients (Riley and Lubitz, 1986). On the other hand, authors of a recent study of a sample of elderly patients in Wales assert that most rehospitalizations are the result not of social factors, but of relapse in the patient's original medical condition (Victor and Vetter, 1985). Similarly, rehospitalization following surgery is usually associated with the same body system involved in the original surgery (Riley and Lubitz, 1986). Another nonmortality measure of hospital outcomes has been the rate of occurrence of surgical complications. Like mortality, the incidence of postoperative wound infection has been shown to be inversely related to surgical volume (Farber, Kaiser, and Wenzel, 1981). Nosocomial infections have also been shown to be more extensive than reported in hospital discharge abstracts (Massanari et al., 1987). Frequency of complications has also been used to characterize high-cost users (Zook and Moore, 1980). Along with post-hospital utilization, complications have also served as indicators of the efficacy of specific surgical procedures. Paradise et al. (1984) employed direct clinical assessment to measure the occurrence of complications following tonsillectomy, and Sussman et al. (1982) used medical records and notes and pathology reports to compare resident and attending surgeons in terms of in-hospital complication rates following appendectomy. Finally, Roos et al. (1985, 1986) have demonstrated that diagnosis codes in computerized claims records can be used to measure, for a variety of surgical procedures, the incidence of complications associated with readmission to the hospital. In this study, we use a method similar to that employed by Roos et al. (1985) to measure post-surgical complications in outpatient as well as inpatient settings, plus standard measures of hospital readmission and other forms of post-hospital utilization and expenditure, to indicate outcomes of surgery among Medicaid recipients in Michigan and Georgia in 1981-82. These methods are discussed in the following section.

Methods

Population

In this article, we examine outcomes of selected inpatient surgical procedures among Medicaid recipients in Georgia and Michigan for 1981 and 1982 and identify patient characteristics associated with those outcomes. However, as pointed out in the introduction, no definitive inferences are intended concerning differences, factors, or policies regarding the quality of care. The analysis uses data from the Health Care Financing Administration's uniform State Medicaid data base known as “Tape-to-Tape,” which contains claims, enrollment, and provider information for all Medicaid recipients in five States beginning in 1980. Special considerations of data availability led to the choice of Georgia and Michigan as the two States to be used in this study, and the exclusion of “crossover” enrollees (those eligible for Medicare as well as Medicaid) from the analysis. The latter decision means that the study population includes only the younger, healthier segment of the Medicaid population in the two States. The selected surgical procedures, listed in Table 1, were chosen on the basis of high frequency and cost in the study population.
Table 1

Selected surgical procedures and corresponding ICD-9-CM codes

ProcedureICD-9-CM codes
1. Cesarean section (and ectopic pregnancy)74.0-74.99
2. Hysterectomy68.3-68.7
3. Oophorectomy and/or salpingectomy65.3-65.62, 66.2-66.69
4. Herniorraphy (inguinal, femoral)53.00-53.39
5. Appendectomy47.0
6. Cholecystectomy51.21-51.22
7. Tonsillectomy28.2-28.3
8. Myringotomy20.01-20.09

NOTES: ICD-9-CM is International Classification of Diseases, 9th Revision, Clinical Modification. A list of those complications deemed relevant to the surgical procedures in this table is presented in Table 2.

SOURCE: (Public Health Service and Health Care Financing Administration, 1980).

Adverse outcomes

The analysis focuses on certain adverse surgical outcomes, namely rehospitalizations, complications, and unusually high levels of additional health care utilization and expenditure (Medicaid amount paid) following surgery. Aside from inpatient hospital services, the types of post-surgical care most likely to occur among noncrossover Medicaid recipients are physician (ambulatory) services and prescription drugs. Long-term care (nursing home and home health services) occurred much too infrequently in this population to yield reliable figures and is thus not included in the results. Moreover, at the time of initial data processing for this study, information on death was not available for Michigan, and in Georgia, the number of decedents was too small to permit detailed analysis of their attributes. This probably reflects the fact that the study population contains only noncrossovers, who tend to be younger and thus less likely to die than crossovers (McMillan and Gornick, 1984). Of particular interest among the selected adverse outcomes is the frequency of diagnoses that can be interpreted as complications arising from the selected surgical procedures. These include diagnoses explicitly identified in the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) (Public Health Service and Health Care Financing Administration, 1980) as being either general complications of surgery or complications specific to one or more of those particular procedures. Although this method excludes many additional diagnoses that some specialists might interpret as procedure-specific complications, the lack of consensus on this topic (Roos et al., 1985) suggests a cautious approach. The frequency count of surgical complications represents the number of times any one of those complication codes appeared as a principal or secondary diagnosis on an inpatient or outpatient claim (long-term care claims were not included). Two separate counts—one for inpatient claims and one for outpatient claims—are presented in the analysis. The operational basis for this distinction, plus the specification of time periods, selection of episodes, and construction of measures for this study, are briefly explained in the following sections, and in more detail in the “Technical note.” The specific complications are listed in Table 2.
Table 2

Codes for selected surgical complications relevant to the procedures listed in Table 1

ICD-9-CM codeComplicationRelevant procedure numbers
518.4Pulmonary edema (including postoperative)All
518.5Pulmonary insufficiency (including following surgery)All
551.21Incisional ventral hernia with gangrene1-6
552.21Incisional ventral hernia with obstruction1-6
553.21Incisional ventral hernia, no gangrene or obstruction1-6
576.0Postcholecystectomy syndrome6
593.3Stricture or kinking of ureter (including postoperative)1-2
598.2Postoperative urethral stricture1-2
618.5Prolapse of vaginal vault after hysterectomy2
620.6Broad ligament laceration syndrome1-3
623.2Stricture or atresia of vagina (including postoperative adhesions)2
668Complications of anesthesia in labor and delivery:1
668.00-.02Pulmonary1
668.10-.12Cardiac1
668.20-.22Central nervous system1
668.80-.82Other1
668.90-.92Unspecified1
669Other complications of labor and delivery, not otherwise specified:1
669.10-.12Obstetric shock (including following labor and delivery)1
669.30-.32Acute renal failure following labor and delivery1
669.40-.42Other complications of obstetrical procedures1
669.80-.82Other complications of labor and delivery1
669.90-.92Unspecified complications of labor and delivery1
674Other and unspecified complications of the puerperium, not otherwise specified11
674.10-.12Disruption of cesarean wound, unspecified1
674.30-.32Other complications of obstetrical surgical wounds1
995.2Unspecified adverse effect of drug, etc.All
995.4Shock due to anesthesiaAll
996.7Other complications of internal prosthetic device, etc.4
997Complications affecting specified body systems, during or resulting from a procedure, not otherwise specified:
997.0Central nervous systemAll
997.1CardiacAll
997.2Peripheral vascularAll
997.3RespiratoryAll
997.4Gastrointestinal1-6
997.5Urinary1-3
997.9OtherAll
998Other complications of procedures, not otherwise specified:
998.0Postoperative shockAll
998.1Hemorrhage or hematoma complicating a procedureAll
998.2Accidental puncture or laceration during a procedureAll
998.3Disruption of operation woundAll
998.4Foreign body accidentally left during a procedureAll
998.5Postoperative infection1-6
998.6Persistent postoperative fistula1-6
998.7Acute reaction to foreign substance accidentally left during a procedureAll
998.8Other specified complications of procedures, not otherwise specifiedAll
998.9Unspecified complication of procedure, not otherwise specifiedAll

Meaning of 5th digit for complications mainly related to pregnancy: 0 = unspecified; 1 = delivered, with or without mention of antepartum condition; 2 = delivered, with mention of postpartum condition.

NOTE: ICD-9-CM is International Classification of Diseases, 9th Revision, Clinical Modification.

SOURCE: (Public Health Service and Health Care Financing Administration, 1980).

Time periods

The focus of this study is the 180-day period following admission to the patient's “key” inpatient stay, i.e., the stay involving one of the selected surgical procedures (Table 1). However, except for the frequency count of complications (previous section), only the health care utilization occurring after discharge from the key stay is included in the post-surgical period. The characteristics of the key stay itself (number of days, amount of expenditures, etc.) are treated as predictors of post-discharge outcomes, along with the patient's demographic characteristics and levels of health care utilization during the 180-day period preceding admission to the key stay. The study uses patients whose key stays occurred in the period from July 1981 through June 1982 to allow for the 180-day presurgical period as well as the 180-day post-surgical period within only 2 calendar years of data. Finally, the study uses only those patients who were continuously enrolled in Medicaid during an entire 12-month episode.

Measures

In addition to nonhospital services, the study uses measures of the patient's utilization and expenditure during any non-key inpatient stays (i.e., those not involving one of the selected surgical procedures) that occurred during either the presurgical or post-surgical period. Post-surgical inpatient stays (i.e., readmissions) were classified as being related or unrelated to the key stay on the basis of principal diagnosis. Utilization of physician services was classified as inpatient or outpatient (ambulatory) by matching the dates of service on the physician claims to admission and discharge dates on inpatient facility claims. The counts of surgical complications were similarly classified as inpatient or outpatient.

Findings

In Table 3, we present the rate of post-surgical readmissions and complications per 1,000 patients for both Georgia and Michigan, stratified by surgical procedure. Both the overall readmission rate and the percent of readmissions judged to be related to the key surgical procedure are reported. The complication rates are further stratified by the setting in which they were diagnosed: inpatient or outpatient. Because of the small numbers of cases involved, the procedure-specific results for complications should be interpreted with caution, especially those based on less than 20 cases. Given its smaller enrollee population, Georgia will inevitably have more such instances of “low N.” Standard errors are not reported, because the estimates are based on population data rather than sample data.
Table 3

Number and percent of adverse outcomes in the 6 months after surgery among noncrossover Medicaid patients, by procedure: Georgia and Michigan, 1981-82

MeasureProcedure

All 8 proceduresCesarean sectionHysterectomyOophorectomy and/or salpingectomyHerniorraphyAppendectomyCholecystectomyTonsillectomyMyringotomy
Georgia
Number of patients3,325609354715321142397678109
Percent of total100.018.310.621.59.74.311.920.43.3
Number of readmissions1174118209144212183345114202
Percent related227.425.0357.919.616.73100.023.934.130.0
Number of complications:1
 Inpatient263115931532532835332139
 Outpatient223313423173632132531830
Michigan
Number of patients9,2552,5999751,7844686111,0851,584149
Percent of total100.028.110.519.35.16.611.717.11.6
Number of readmissions116016719415413719022881188
Percent related222.88.753.134.214.832.710.928.430.0
Number of complications:1
 Inpatient28265915311383323320
 Outpatient333750223323294423313

Mean per 1,000 patients.

Readmissions with a principal diagnosis judged to be related to the key surgical procedure (includes only diagnoses appearing on more than 1 claim).

Result based on less than 20 patients.

SOURCE: Health Care Financing Administration, Office of Research and Demonstrations: Data from the Medicaid Tape-to-Tape project.

Readmissions

The overall readmission rate for all eight procedures is slightly higher in Georgia (174 per 1,000 patients) than in Michigan (160 per 1,000). Both figures are somewhat lower than the 220 per 1,000 patients (i.e., 22 percent) reported among Medicare beneficiaries (Anderson and Steinberg, 1984). Although a higher readmission rate might be expected among Medicare patients (who would tend to be older than our sample of noncrossover Medicaid enrollees), our data include readmissions up to 6 months after admission to the key hospital stay, whereas the Medicare figure covers only readmissions within 60 days of discharge. The pattern of readmission rates among the various procedures is quite stable across the two States. In each State, the procedure with the highest readmission rate is cholecystectomy. Hysterectomy also ranks high on readmissions in both States (second in Michigan, third in Georgia), as do appendectomy (third in Michigan, fifth in Georgia) and myringotomy (fourth in both States). The two States produce identical rankings for oophorectomy and/or salpingectomy (sixth) and tonsillectomy (eighth, or lowest). The largest difference between the two States is for herniorraphy (second in Georgia, but seventh—next to lowest—in Michigan). Cesarean section is fifth in Michigan but seventh in Georgia.

Related readmissions

The percent of readmissions related to the key surgical procedure also displays a stable pattern of results across the two States, although some of the Georgia figures are based on less than 20 cases and must therefore be interpreted with caution. The overall percentage of related readmissions is more similar between the two States than was the overall readmission rate, but it is still slightly higher in Georgia (27.4 percent) than in Michigan (22.8 percent). Directly comparable figures are not available in the existing literature, but Zook and Moore (1980) report that 19 percent of low-cost users had related readmissions (“repeated hospitalization for the same disease”) within 1 year, compared with 73.6 percent of high-cost users. Their results were based on medical records, rather than claims, for a sample of 2,238 patients in 6 Massachusetts hospitals. Georgia's rankings of the various procedures on percent-related readmissions are within two ranks of Michigan's for all procedures except cesarean section (fourth in Georgia, but seventh in Michigan). The pattern of rankings is somewhat different from that for the overall readmission rate, however. This implies that many of the readmissions observed for some procedures may not really be related to the key surgical procedure. Most notably, cholecystectomy—which ranked first on the overall readmission rate in both States—ranks rather low on related readmissions (fifth in Georgia, sixth in Michigan).

Complications

The overall rate of complications found in inpatient settings (which are probably more serious than those found in outpatient settings) is slightly higher in Michigan (28 per 1,000 patients) than in Georgia (26 per 1,000 patients). The rate of complications found in outpatient settings, on the other hand, is substantially higher in Michigan (33 per 1,000 patients) than in Georgia (22 per 1,000 patients). Michigan's slightly higher rate of surgical complications diagnosed in inpatient settings, despite its lower rate of inpatient readmissions, suggests that its rate of inpatient complications per readmission would be even higher. The divergence in the results for readmissions and complications may indicate that they are influenced by different sets of factors. Only one previous study (Zook and Moore, 1980) reported overall complication rates for several procedures. Keeping in mind several major methodological differences (e.g., that study used medical records rather than claims), our rates appear to be much lower than those reported for even the low-cost patients (5 percent, or 50 per 1,000 patients) in that study. As with readmissions, the two States display quite similar patterns across procedures, although most of the figures for Georgia are based on less than 20 patients and must therefore be interpreted with caution. In both States and in both inpatient and outpatient settings, the rate of complications is highest for hysterectomy. The complication rate also tends to be higher than average in both States for cholecystectomy, appendectomy, and cesarean section. Rates noticeably lower than average appear for oophorectomy and/or salpingectomy and tonsillectomy. The figures for herniorraphy and myringotomy are also generally much lower than average but are based on less than 20 cases in Michigan as well as in Georgia. Our complication rates for Michigan (giving a larger number of cases) for three of our selected procedures can be roughly compared with those reported in previous studies. For tonsillectomy, Paradise et al. (1984) reported that 137 per 1,000 patients (13 of 95 children) had surgery-related complications, based on direct followup assessment. This is almost six times greater than our claims-based rate of 23 per 1,000. On the other hand, Roos et al. (1985, 1986) used methods more similar to ours to assess the extent of inpatient complications (i.e., those that caused readmission to the hospital) for two of our selected procedures (hysterectomy and cholecystectomy) plus prostatectomy. Aside from the population used (their claims were drawn from the public health insurance system of Manitoba), the chief difference in methodology lies in the list of ICD-9-CM diagnosis codes used to indicate complications (Roos et al., 1985). Theirs was developed by a panel of physicians and included codes that were not explicitly labeled as complications of surgery. On the other hand, their list did not include all of the codes that are so labeled. For hysterectomy, their computer-coded rate was actually lower than ours—about 40 per 1,000 patients (depending on the year), compared with our rate of 59 per 1,000. For cholecystectomy, their rate was very similar to ours: about 35 per 1,000, compared with our rate of 33 per 1,000 (Roos et al., 1985). This general similarity of results—not only across States, but also across data bases, years, and countries—lends some degree of confidence to the claims-based approach to measuring complications of surgery. That is, even though they tend to be underreported, those complication rates can be used as conservative but stable measures of “sentinel health events” that indicate possible problems of quality of care. The major task would appear to be achieving consensus on an efficient method of identifying specific complication codes to monitor.

Summary

Post-surgical readmissions among Medicaid patients appear to be somewhat more prevalent in Georgia than in Michigan and for the following procedures in both States: cholecystectomy, hysterectomy, appendectomy, and myringotomy. A lower readmission rate is evident for oophorectomy and/or salpingectomy and tonsillectomy. The two States also show quite similar patterns of surgery-related readmissions, although the patterns for individual procedures differ somewhat from those for the overall readmission rate. Finally, Michigan shows higher overall rates of surgical complications than does Georgia, although the difference is smaller for inpatient than outpatient settings. Michigan's slightly higher rate of inpatient complications, despite its lower rate of inpatient readmissions, suggests that its rate of inpatient complications per readmission would be even higher. Nevertheless, the generally stable patterns of complications across States and procedures, and their similarity to those of previous studies, suggest their potential usefulness in future research.

Changes in utilization

In Tables 4 and 5, we present, for selected procedures in Georgia and Michigan, respectively, the changes in levels of health care utilization and expenditure from the 6-month presurgical period to the 6-month post-surgical period. Again, the post-surgical period excludes the utilization and expenditure involved in the surgical hospital stay itself. The four procedures selected for this analysis (hysterectomy, oophorectomy and/or salpingectomy, tonsillectomy, and myringotomy) are those in which surgery is less often done on an urgent or emergency basis. Rather, they are usually intended to reduce the patient's need for ongoing health care. The four procedures excluded from this analysis (cesarean section, herniorraphy, appendectomy, and cholecystectomy) are usually performed to resolve an acute episode, rather than to reduce the patient's ongoing level of health care utilization.
Table 4

Change in health care utilization and expenditure among noncrossover Medicaid patients in the 6-month periods before and after surgery, by procedure: Georgia, 1981-82

MeasureProcedure

HysterectomyOophorectomy and/or salpingectomyTonsillectomyMyringotomy




BeforeAfterPercent changeBeforeAfterPercent changeBeforeAfterPercent changeBeforeAfterPercent change
Patient serviceProbability
Inpatient hospital.427.153−64.2.351.108−69.2.119.096−19.3.2391.1381−42.3
Inpatient surgery.288.045−84.4.211.053−74.9.034.029−14.71.0921.0551−40.2
Physician.912.808−11.4.884.792−10.4.957.758−20.8.908.844−7.0
Outpatient surgery.280.150−46.4.143.094−34.3.081.058−28.41.0831.0830.0
Prescription drug.924.9492.7.842.786−6.7.885.832−6.0.872.807−7.5
UtilizationMean per 1,000 patients
Inpatient stays588209−64.5453144−68.2136114−16.225712021−21.4
Inpatient days2,8621,234−56.92,130822−61.4671423−37.074317341−1.2
Inpatient surgeries1,141249−78.2690283−59.014021452.913851587152.5
Physician visits7,5765,698−24.85,6923,420−39.95,4753,128−42.95,8263,908−32.9
Outpatient surgeries675325−51.9323206−36.2155127−18.111831248135.5
Prescriptions11,93511,712−1.95,8765,103−13.25,6504,481−20.76,4315,064−21.3
ExpenditureMean per patient
Total2$1,230$712−42.1$962$429−55.4$382$276−27.7$491$57717.5
 Inpatient hospital628315−49.8579237−59.1139108−22.31691287169.8
 Physician in hospital15250−67.111533−71.33023−23.354182151.9
 Ambulatory329196−40.4220113−48.6165104−37.0203166−18.2
 Prescription drug1021020.04742−10.64134−17.14737−21.3

Result based on less than 20 patients.

Includes long-term care, not shown.

SOURCE: Health Care Financing Administration, Office of Research and Demonstrations: Data from the Medicaid Tape-to-Tape project.

Table 5

Change in health care utilization and expenditure among noncrossover Medicaid patients in the 6-month periods before and after surgery, by procedure: Michigan, 1981-82

MeasureProcedure

HysterectomyOophorectomy and/or salpingectomyTonsillectomyMyringotomy




BeforeAfterPercent changeBeforeAfterPercent changeBeforeAfterPercent changeBeforeAfterPercent change
Patient serviceProbability
Inpatient hospital.381.144−62.2.285.119−58.2.104.064−38.5.148.134−9.5
Inpatient surgery.265.056−78.9.161.038−76.4.032.016−50.01.0471.054114.9
Physician.988.886−10.3.809.789−2.5.985.830−15.7.973.933−4.1
Outpatient surgery.739.435−41.1.625.454−27.4.200.178−11.0.255.235−7.8
Prescription drug.926.9330.8.892.854−4.3.916.778−15.1.906.792−12.6
UtilizationMean per 1,000 patients
Inpatient stays510194−62.0398154−61.312881−36.7302188−37.7
Inpatient days2,6431,587−40.01,628995−38.9543295−45.72,8461,000−64.9
Inpatient surgeries33182−75.222454−75.94528−37.811141811−28.9
Physician visits8,0015,405−32.44,4123,798−13.96,3213,165−49.97,8995,094−35.5
Outpatient surgeries1,805997−44.81,879907−51.7324282−13.0362289−20.2
Prescriptions12,16212,039−1.07,4476,107−18.05,5883,556−36.46,7995,154−24.2
ExpenditureMean per patient
Total2$1,541$871−43.5$934$554−40.7$420$246−41.4$1,195$521−56.4
 Inpatient hospital772438−43.3488294−39.813583−38.5835254−69.6
 Physician in hospital12756−55.96733−50.72211−50.06226−58.1
 Ambulatory530248−53.2324173−46.6218119−45.4254202−20.5
 Prescription drug9694−2.15447−13.03624−33.34337−14.0

Result based on less than 20 patients.

Includes long-term care, not shown.

SOURCE: Health Care Financing Administration, Office of Research and Demonstrations: Data from the Medicaid Tape-to-Tape project.

The most general basis for comparing the specific surgical procedures in Tables 4 and 5 is to examine the change in total expenditure from the presurgical period to the post-surgical period. By that standard, the largest reduction occurs for myringotomy (− 56 percent) in Michigan and for oophorectomy and/or salpingectomy (−55 percent) in Georgia. In Michigan, all three of the other procedures show remarkably similar reductions of slightly more than 40 percent: hysterectomy (− 44 percent), tonsillectomy (− 41 percent), and oophorectomy and/or salpingectomy (− 41 percent). The results for Georgia are far more varied. Although that State's figure for hysterectomy (−42 percent) is almost identical to Michigan's, the figure for tonsillectomy (− 28 percent) is much lower, and myringotomy actually produces an overall increase in total expenditure in Georgia (+18 percent). To ascertain the sources of these variations, let us examine the pattern of differences among procedures for each type of service. In both States, hysterectomy and oophorectomy and/or salpingectomy tend to rank first or second among the four procedures in terms of percentage reduction in most of the measures of health care utilization and expenditure, with particularly large reductions in the inpatient categories. The only exception is prescription drugs, where hysterectomy actually shows an increase, probably reflecting the use of post-surgical hormone therapy. Tonsillectomy usually ranks third or fourth in percentage reduction in most categories, with physician (outpatient) services being the major exception in both States, plus prescription drugs in Michigan. Myringotomy shows the most divergent patterns in the two States. In Georgia, it usually ranks lowest (including actual increases rather than reductions in inpatient expenditures and most of the surgery measures), except on prescription drugs, where it produces the largest reduction on all three measures (probability, utilization, and expenditure). In Michigan, although myringotomy ranks first or second on most utilization and expenditure measures, it shows the lowest reductions in probability of use for all services but prescription drugs. In summary, the results demonstrate substantial reductions in most measures of health care utilization and expenditure following all four of the selected surgical procedures in both States, with the single exception of myringotomy in Georgia. It is conceivable that myringotomy is more susceptible to geographic variations in outcomes as well as incidence. This could arise from greater uncertainty among physicians not only about appropriate use of that procedure (Wennberg, Barnes, and Zubkoff, 1982) but also about its proper execution and followup care. Nevertheless, the overall pattern of decline in utilization suggests that these four surgical procedures are generally effective in reducing health care use and cost among Medicaid recipients in these two States.

Factors in surgical outcomes

In the remaining tables, we compare various dichotomized characteristics of the entire sample of surgical cases in each State in terms of their utilization, expenditure, and complications during the post-surgical period. Unfortunately, the small size of the sample, particularly in Georgia, precluded similar breakdowns by these characteristics within each selected surgical procedure. The results for Georgia are presented in Tables 4, 6, 8, and 10 and for Michigan in Tables 5, 7, 9, and 11. In all of the tables, cases classified in lesser categories (i.e., missing data or “other”) on a given characteristic are excluded. The same measures of utilization and expenditure employed in Tables 4 and 5 are also used in these tables. Let us again emphasize that the purpose of this analysis is to explore some factors associated with surgical outcomes, not to draw definitive inferences about such factors or to explain variations in those outcomes.
Table 6

Health care utilization and expenditure among noncrossover Medicaid patients in the 6 months after surgery, by patient characteristic: Georgia, 1981-82

MeasurePatient characteristics

All patientsSexAgeRace1Eligibility2




MaleFemaleLowHighWhiteBlackAFDC3SSI4
Number of patients3,3256522,6731,6441,6811,0272,2392,559744
Percent of total100.019.680.449.450.630.967.377.022.4
Patient serviceProbability
Inpatient hospital.133.121.136.114.152.192.101.096.261
Inpatient surgery.051.040.053.044.057.076.038.040.085
Physician.785.736.796.815.755.796.782.796.749
Outpatient surgery.090.069.095.089.090.096.085.082.116
Prescription drug.829.758.847.791.867.896.795.801.925
UtilizationMean per 1,000 patients
Inpatient stays174161177144203265125114378
Inpatient days9808341,0157421,2121,5286695372,497
Inpatient surgeries294238308293296446220221544
Physician visits3,8073,3543,9183,8083,8074,9273,2563,2305,839
Outpatient surgeries192144203162221227172168274
Prescriptions6,7614,8997,2155,0838,4029,6095,2834,59614,310
ExpenditureMean per patient
Total5$528$483$540$426$627$722$413$324$1,232
 Inpatient hospital260234266221297367195157609
 Physician in hospital4244423847673026100
 Ambulatory135111141123147159122104245
 Prescription drug5843624273854437131
ComplicationsMean per 1,000 patients
Inpatient2662527213134212143
Outpatient22617232519282021924

59 patients (1.8 percent of the total sample) whose race was “other” or “unknown” were excluded.

22 patients (0.7 percent of the total sample) whose eligibility was “other” were excluded.

Aid to Families with Dependent Children.

Supplemental Security Income.

Includes long-term care, not shown.

Result based on less than 20 patients.

SOURCE: Health Care Financing Administration, Office of Research and Demonstrations: Data from the Medicaid Tape-to-Tape project.

Table 8

Health care utilization and expenditure among noncrossover Medicaid patients in the 6 months after surgery, by level of prior utilization: Georgia, 1981-82

MeasureAll patientsLevel of prior utilization

Number of inpatient daysNumber of surgeriesNumber of ambulatory visitsNumber of prescriptions




None1 or moreNone1 or moreLess than 66 or moreLess than 66 or more
Number of patients3,3252,4698562,9184072,2991,0262,1461,179
Percent of total100.074.325.787.812.269.130.964.535.5
Patient serviceProbability
Inpatient hospital.133.107.209.124.199.114.176.096.201
Inpatient surgery.051.043.074.045.091.046.060.038.074
Physician.785.768.833.776.845.723.923.746.856
Outpatient surgery.090.077.125.083.140.080.112.072.121
Prescription drug.829.810.886.824.870.800.904.755.965
UtilizationMean per 1,000 patients
Inpatient stays174126312158287138254114284
Inpatient days9806321,9828631,8217751,4405621,740
Inpatient surgeries294251418258555252389200466
Physician visits3,8073,3605,0983,6205,1502,3687,0322,6355,941
Outpatient surgeries192169256180273170241155258
Prescriptions6,7615,58810,1446,3899,4305,22710,1973,12513,378
ExpenditureMean per patient
Total1$528$401$897$480$874$414$784$316$916
 Inpatient hospital260178497227494205383164435
 Physician in hospital423077378432662672
 Ambulatory1351171891281869522596207
 Prescription drug5847895484448825117
ComplicationsMean per 1,000 patients
Inpatient2623352424421372037
Outpatient2221252122919282025

Includes long-term care, not shown.

Result based on less than 20 patients.

SOURCE: Health Care Financing Administration, Office of Research and Demonstrations: Data from the Medicaid Tape-to-Tape project.

Table 10

Health care utilization and expenditure among noncrossover Medicaid patients in the 6 months after surgery, by characteristics of the key hospital stay: Georgia, 1981-82

MeasureAll patientsCharacteristics of the key hospital stay

Length of stayHospital payment1Physician payment2



Less than averageAverage or moreLess than averageAverage or moreLess than averageAverage or more
Number of patients3,3251,7911,5341,9441,3551,3481,677
Percent of total100.053.946.158.540.840.550.4
Patient serviceProbability
Inpatient hospital.133.095.177.098.185.119.144
Inpatient surgery.051.038.065.035.073.052.055
Physician.785.765.807.761.819.769.835
Outpatient surgery.090.070.113.081.102.068.115
Prescription drug.829.779.889.799.873.813.857
UtilizationMean per 1,000 patients
Inpatient stays174117241123249151194
Inpatient days9804871,5555491,6087721,122
Inpatient surgeries294246350228386320318
Physician visits3,8073,2664,4393,4714,2993,7024,248
Outpatient surgeries192158231178213121261
Prescriptions6,7614,6589,2165,3688,7455,2557,821
ExpenditureMean per patient
Total3$528$337$751$360$777$426$611
 Inpatient hospital260139400141435209306
 Physician in hospital42276027643751
 Ambulatory135112163117163126154
 Prescription drug58388144784369
ComplicationsMean per 1,000 patients
Inpatient26124314441836
Outpatient22172715321627

26 patients (0.8 percent of the total sample) whose hospital payment was unknown were excluded.

300 patients (9.0 percent of the total sample) whose physician payment was unknown were excluded.

Includes long-term care, not shown.

SOURCE: Health Care Financing Administration, Office of Research and Demonstrations: Data from the Medicaid Tape-to-Tape project.

Table 7

Health care utilization and expenditure among noncrossover Medicaid patients in the 6 months after surgery, by patient characteristic: Michigan, 1981-82

MeasurePatient characteristics

All patientsSexAgeRace1Eligibility2




MaleFemaleLowHighWhiteBlackAFDC3SSI4
Number of patients9,2551,4507,8054,5514,7045,8882,9938,501589
Percent of total100.015.784.349.250.863.632.391.96.4
Patient serviceProbability
Inpatient hospital.121.090.127.112.130.114.138.111.268
Inpatient surgery.043.032.045.041.045.041.048.039.100
Physician.835.815.839.831.839.827.853.833.900
Outpatient surgery.422.183.467.412.432.403.463.430.334
Prescription drug.860.738.883.849.871.862.861.857.920
UtilizationMean per 1,000 patients
Inpatient stays160132165147173154178139467
Inpatient days1,1047831,1649781,2269521,3708624,492
Inpatient surgeries6547685970587856189
Physician visits4,0963,3894,2273,9504,2383,8524,6133,8987,080
Outpatient surgeries809295904776840741954821685
Prescriptions6,7993,7837,3596,0597,5156,3027,8746,11316,888
ExpenditureMean per patient
Total5$601$439$621$545$654$519$739$497$2,078
 Inpatient hospital3102243262833362553932381,344
 Physician in hospital3625383338343929129
 Ambulatory188128199177198167230179322
 Prescription drug5329574659496146144
ComplicationsMean per 1,000 patients
Inpatient282728253030232563
Outpatient332634303636283142

374 patients (4.0 percent of the total sample) whose race was “other” or “unknown” were excluded.

165 patients (1.8 percent of the total sample) whose eligibility was “other” were excluded.

Aid to Families with Dependent Children.

Supplemental Security Income.

Includes long-term care, not shown.

SOURCE: Health Care Financing Administration, Office of Research and Demonstrations: Data from the Medicaid Tape-to-Tape project.

Table 9

Health care utilization and expenditure among noncrossover Medicaid patients in the 6 months after surgery, by level of prior utilization: Michigan, 1981-82

MeasureAll patientsLevel of prior utilization

Number of inpatient daysNumber of surgeriesNumber of ambulatory visitsNumber of prescriptions




None1 or moreNone1 or moreLess than 66 or moreLess than 66 or more
Number of patients9,2556,9912,2648,2081,0476,8052,4505,8633,392
Percent of total100.075.524.588.711.373.526.563.336.7
Patient serviceProbability
Inpatient hospital.121.101.185.112.190.106.163.094.169
Inpatient surgery.043.034.069.038.082.037.060.032.062
Physician.835.821.881.830.877.795.949.789.915
Outpatient surgery.422.398.498.410.518.416.439.380.495
Prescription drug.860.841.918.853.919.836.926.803.959
UtilizationMean per 1,000 patients
Inpatient stays160118289145279135228115238
Inpatient days1,1047412,2269552,2729301,5867191,769
Inpatient surgeries654811855142569144101
Physician visits4,0963,6465,4863,8965,6633,0726,9382,9806,024
Outpatient surgeries8097321,0487571,2187201,0566461,091
Prescriptions6,7995,8049,8696,33310,4515,09411,5333,73612,093
ExpenditureMean per patient
Total1$601$454$1,050$485$818$454$945$404$937
 Inpatient hospital310206630261696269423205491
 Physician in hospital362569308029562357
 Ambulatory188164259176275144309138273
 Prescription drug534577498239892895
ComplicationsMean per 1,000 patients
Inpatient282535263727282435
Outpatient332945315029442841

Includes long-term care, not shown.

SOURCE: Health Care Financing Administration, Office of Research and Demonstrations: Data from the Medicaid Tape-to-Tape project.

Table 11

Health care utilization and expenditure among noncrossover Medicaid patients in the 6 months after surgery, by characteristics of the key hospital stay: Michigan, 1981-82

MeasureAll patientsCharacteristics of the key hospital stay

Length of stay1Hospital payment2Physician payment3

Less than averageAverage or moreLess than averageAverage or moreLess than averageAverage or more
Number of patients9,2554,9854,2514,5904,6204,6214,343
Percent of total100.053.945.949.650.049.946.9
Patient serviceProbability
Inpatient hospital.121.090.158.084.159.099.145
Inpatient surgery.043.030.058.028.058.033.054
Physician.835.811.864.815.858.815.862
Outpatient surgery.422.354.501.317.529.339.508
Prescription drug.860.812.916.817.905.817.906
UtilizationMean per 1,000 patients
Inpatient stays160116211106214125194
Inpatient days1,1045911,7015711,6317691,429
Inpatient surgeries65429236944982
Physician visits4,0963,4274,8783,4814,7283,6164,644
Outpatient surgeries8096181,0325611,0616171,009
Prescriptions6,7994,7269,2204,8968,7105,1608,468
ExpenditureMean per patient
Total4$601$377$859$364$838$464$870
 Inpatient hospital310170473161460220396
 Physician in hospital36215321512547
 Ambulatory188146236141235159219
 Prescription drug533507336693967
ComplicationsMean per 1,000 patients
Inpatient28183919361936
Outpatient33254129372641

19 patients (0.2 percent of the total sample) whose length of stay was unknown were excluded.

45 patients (0.5 percent of the total sample) whose hospital payment was unknown were excluded.

291 patients (3.1 percent of the total sample) whose physician payment was unknown were excluded.

Includes long-term care, not shown.

SOURCE: Health Care Financing Administration, Office of Research and Demonstrations: Data from the Medicaid Tape-to-Tape project.

Patient characteristics

Tables 6 and 7 (Georgia and Michigan, respectively) stratify the measures of post-surgical utilization, expenditure, and complications by various categories of patient characteristics: sex, age, race, and Medicaid eligibility. (Recall that age is dichotomized on a procedure-specific basis.) As might be expected, on virtually all measures in both States, utilization and expenditures are higher among females, older patients, and enrollees eligible through Supplemental Security Income (SSI) rather than Aid to Families with Dependent Children (AFDC). There are some notable exceptions to this pattern, however. In Georgia, younger patients have a higher probability of using physician services (as do AFDC recipients) and suffer more outpatient-based complications, and they score about the same as older patients on several outpatient measures. In Michigan, AFDC recipients score higher on both measures of outpatient surgery. Perhaps the most noteworthy finding emerging from Tables 6 and 7 is the opposite racial pattern in the two States. In Georgia, white patients consistently show higher levels of utilization and expenditure than do black patients, whereas in Michigan, the pattern is exactly opposite. Similar contrasting patterns of racial differences in overall utilization and expenditure between the South and North Central Regions have been observed in Medicare data (Ruther and Dobson, 1981) and National Health Interview Survey data (Link, Long, and Settle, 1982). These patterns have usually been attributed to greater problems of access to health care for black patients and to less generous Medicaid programs in the South. On the other hand, the rate of surgical complications is higher among white patients in both States, and it is higher overall in Michigan than in Georgia.

Prior utilization

Tables 8 and 9 compare post-surgical outcomes by dichotomized levels of presurgical utilization: inpatient days of care (none versus 1 or more), inpatient surgeries (none versus 1 or more), ambulatory visits (less than 6 versus 6 or more), and drug prescriptions (less than 6 versus 6 or more). Even more consistently than the results by patient characteristics, recipients with high levels of pre-period utilization show higher levels of post-period utilization, expenditure, and complications. Indeed, neither State produces a single exception to this pattern on any measure. Moreover, the differences between high users and low users are often quite large. This finding fits the pattern of overall stability in individual health care utilization reported in most previous research (Anderson and Steinberg, 1984), demonstrating that patients who were sicker prior to surgery are likely to remain sicker after surgery.

Key-stay characteristics

Tables 10 and 11 stratify the measures of surgical outcomes by dichotomized characteristics of the key (surgical) hospital stay: length of stay, hospital payment, and physician payment. Again, quite consistently in both States, patients whose key stay was above average on these three measures tend to show much higher levels of post-surgical utilization, expenditure, and complications. Indeed, only one exception to this pattern emerges: In Georgia, the rate of post-period inpatient surgery is about the same in both categories of physician payment. As with prior utilization, patients requiring more extensive and/or intensive care during the key hospital stay generally require more post-surgical care as well. It should be pointed out, however, that the characteristics of the key stay may, to some extent, reflect the influence of complications arising from the surgery. Nevertheless, throughout Tables 6 through 11, the rate of surgical complications shows quite stable and consistent patterns in both States, with higher figures appearing in patient categories that also show higher levels of post-surgical utilization and expenditure. As noted, the major exception is for race in Michigan. Some rather strong and consistent patterns characterize the factors underlying surgical outcomes. On almost all measures in both States, post-surgical levels of utilization, expenditure, and complications are higher among females, older patients, and enrollees eligible though SSI rather than AFDC. Without exception, moreover, those levels are higher among patients with higher levels of presurgical utilization and among patients whose key (surgical) hospital stay was above average in length of stay, hospital payment, and physician payment. On the other hand, the two States do show opposite racial patterns of post-surgical levels of utilization and expenditure, with white patients consistently higher than black patients in Georgia, but the reverse in Michigan. The rate of surgical complications, however, is higher among white patients in both States.

Conclusion

In this study, we examined outcomes of surgery among all Medicaid recipients in Michigan and Georgia who underwent selected surgical procedures between July 1, 1981, and June 30, 1982. Outcomes were measured during the 6-month period following surgery using the following indicators: rate of inpatient hospital readmission, percentage of such readmissions related to the key surgical procedure, rate of surgical complications, and extent of post-surgical utilization of and expenditure for various kinds of health services. Readmissions appeared to be somewhat more prevalent in Georgia than in Michigan and for hysterectomy, cholecystectomy, appendectomy, and myringotomy in both States. On the other hand, Michigan showed higher overall rates of surgical complications than did Georgia, although the difference was smaller for inpatient than outpatient settings. Michigan's slightly higher rate of inpatient complications, despite its lower rate of inpatient readmissions, suggests that its rate of inpatient complications per readmission would be even higher. The divergence in the results for readmissions and complications may indicate that they are influenced by different sets of factors. Changes in health care utilization and expenditure from the 6-month period preceding surgery to the 6-month period following surgery were analyzed using four procedures (hysterectomy, oophorectomy and/or salpingectomy, tonsillectomy, and myringotomy). These procedures are not usually performed on an urgent or emergency basis, but rather are intended to reduce the patient's need for ongoing health care. The results showed substantial reductions in most utilization and expenditure measures following all four of the selected procedures in both States, with the single exception of myringotomy in Georgia. This pattern suggests that these four surgical procedures were generally effective in reducing health care use and cost among Medicaid recipients in these two States. On almost all measures in both States, levels of post-surgical utilization, expenditure, and complications were higher among females, older patients, enrollees eligible through SSI rather than AFDC, patients with higher levels of presurgical utilization and expenditure, and patients whose key (surgical) hospital stay was above average in length of stay, hospital payment, or physician payment. The two States produced opposite racial patterns, however, with white patients showing consistently higher levels than black patients in Georgia, but the reverse in Michigan. The rate of surgical complications, on the other hand, was higher among white patients in both States. In terms of methodology, the results further demonstrate the utility of claims data in monitoring outcomes of surgery and inpatient hospital care more generally. In particular, analyzing changes in utilization following surgical procedures designed to reduce utilization (e.g., tonsillectomy) appears to be a promising approach. Also, the stability and consistency of our measure of surgical complications across States and procedures, and its adherence to expected patterns across patient categories, make it worthy of further exploration. Even though it captures only those diagnoses explicitly identified as complications of surgery in the ICD-9-CM coding system, it may ultimately prove useful in quality-monitoring activities as a preliminary screen in selecting cases for more intensive investigation.

Technical note

Post-surgical period

The time periods employed in this study center around the “key” (or “index”) inpatient stay for each patient, i.e., the stay that involved one of the selected surgical procedures (Table 1). Patients who had more than one of the selected surgical procedures were excluded from the analysis in order to avoid analytical complications that would arise from duplicating their characteristics in the analysis file. More is said about the selection of episodes in a later section. The post-surgical period used in this study extends from the date of discharge from the key stay through the 180th day following admission to that stay. Each patient is thus monitored over a uniform period of 6 months following the date of surgical admission—not the date of actual surgery (principal procedure date), for reasons given in this section. Except for the frequency count of surgical complications, all health care utilization and expenditures occurring during the key stay itself are excluded from the measures representing the post-surgical period. These key-stay characteristics (number of days, amount of expenditure, etc.) are instead treated as predictors of post-discharge outcomes, because they more truly reflect what went into the surgery than what came out of it. To be sure, that utilization is part of the total package of health care consumed by the patient as part of the entire episode of illness involving the surgical procedure and its subsequent effects. The focus of this study, however, is on those later outcomes, which are influenced in part by the nature of the health care rendered during the key stay. Of course, the characteristics of the key stay may, to some extent, reflect the influence of complications arising from the surgery. Moreover, the admission date, rather than the date of surgery, is used to anchor the 6-month ending date of the post-surgical period so that all of the key-stay utilization and expenditure can be kept intact, rather than having to allocate it somewhat arbitrarily into the presurgical and post-surgical periods. This means that some presurgical services rendered during the key stay, but which may not have been directly related to the surgery itself, are included in the attributes of that stay. Such services are usually not very extensive, however. Surgery tends to occur soon after admission, and most diagnostic and ancillary services rendered between admission and surgery are actually preparatory to surgery. Moreover, because it is not required for Medicaid reimbursement, the date of surgery tends to be less reliable than the admission date in the Tape-to-Tape data. Finally, using date of admission to commence measuring outcomes tends to correct for variations in discharge practices.

Presurgical period

The patient's levels of health care utilization during the 6-month period preceding the admission date of the key hospital stay are also included in the analysis. For surgical procedures that are more elective in nature, the percentage change in levels of utilization from the presurgical period to the post-surgical period is a potentially useful outcome measure. For example, tonsillectomy is intended to reduce the frequency and severity of throat infections. One method of assessing the extent to which it does so is to compare levels of health care utilization before and after surgery. On the other hand, such procedures as appendectomy are usually performed to alleviate an acute episode, so that the patient's post-surgical levels of utilization would be expected to return to presurgical levels. Most previous research suggests that the general stability of individual patterns of health care consumption makes prior levels of utilization reliable predictors of subsequent levels. Thus, when comparing levels of post-surgical utilization among different types of patients, presurgical utilization levels should be controlled in the analysis.

Selection of episodes

This study uses only those patients whose key hospital stay occurred in the period from July 1981 through June 1982. This permits a full 6-month post-surgical period ending as late as December 1982 (for patients admitted to the hospital in June 1982) and a full 6-month presurgical period beginning as early as January 1981 (for patients admitted to the hospital in July 1981). It therefore requires the use of only the 1981 and 1982 Tape-to-Tape files and keeps the study period short enough to minimize the effects of the rapid changes in State Medicaid programs taking place in the early 1980s. Furthermore, the analysis uses only those patients continuously enrolled in Medicaid during an entire 12-month episode. Recipients who were not continuously enrolled may well have consumed health care services not captured in the Tape-to-Tape data base during their periods of nonenrollment. This could seriously bias the results of the analysis by underrepresenting the overall levels of health care utilization and expenditure. Unfortunately, excluding such patients means that medically needy recipients who enrolled in Medicaid shortly before, or even during, a surgical hospital stay are not represented in the study population. In addition to nonhospital services, the utilization and expenditure measures used in this study include summary characteristics of any non-key hospital stays that occurred in either the presurgical period or the post-surgical period. Non-key stays are those not involving one of the selected surgical procedures, even though they could well be clinically related to that patient's key procedure. The characteristics of those non-key stays include the number of stays, the number of days of care, the number of inpatient surgeries, the amount of expenditure (Medicaid amount paid), and (for post-surgical stays only) the frequency of surgical complications (Table 1) involved in those stays. To ascertain which of a patient's post-surgical inpatient stays were related to the key surgical procedure, a senior medical records specialist classified as “related” or “unrelated” (to the key procedure) all principal diagnoses recorded during at least two post-surgical inpatient stays (thereby eliminating diagnoses appearing in only one isolated instance). Again, the key (surgical) stay itself was excluded from these tabulations. The percentage of such stays with a principal diagnosis judged to be related to the key surgical procedure thus serves as an additional measure of surgical outcome. Put differently, it represents the percentage of inpatient hospital readmissions that can be considered related to the key surgical procedure. In addition to utilization and expenditure measures, each Tape-to-Tape claim record also contains certain basic information about the patient involved in that claim. These indicators, including the patient's sex, age, race, and eligibility group (Supplemental Security Income versus Aid to Families with Dependent Children), are used here as potential predictors of surgical outcomes. Month-by-month enrollment status (to check for continuity of enrollment throughout a 12-month episode) and any patient background data not available in the claim records were drawn from the Tape-to-Tape enrollment file. For purposes of crosstabulation analysis, the quantitative independent variables (length of stay, etc.) were dichotomized at the median. Patient age groups were tailored to each surgical procedure by dichotomizing at the age suggested by a senior medical records specialist as being about average for patients undergoing that procedure. The dependent variables are standard measures of health care utilization and expenditure in the post-surgical period: the probability of use of (i.e., the proportion of patients using) various types of health services (e.g., inpatient hospital); the level of utilization of those services (e.g., mean number of inpatient days per 1,000 patients); and the level of expenditure for those services (e.g., mean amount paid per patient for inpatient hospital care). When measured for the presurgical period, these same variables serve as predictors of their counterparts in the post-surgical period. Of particular interest among these standard dependent variables is the mean number of post-surgical hospital stays (i.e., readmissions). Also serving as a dependent variable (i.e., for the post-surgical period only) is the rate of surgical complications (mean number per 1,000 patients), as listed in Table 2. A final dependent variable is the percentage of post-surgical inpatient hospital stays (i.e., readmissions) with a principal diagnosis judged to be related to the key surgical procedure. (Only diagnoses appearing on more than one such claim are included.) The nature of the measures of outpatient (ambulatory) care requires further elaboration. The Tape-to-Tape “outpatient” claims file contains not only claims for outpatient hospital, clinic, laboratory, X-ray, and other ambulatory services. It also contains claims for physician and other nondental practitioner services (hereafter referred to simply as physician services) rendered in any setting, including an inpatient hospital. Such services can involve surgery or other procedures, no matter how minor. In this study, outpatient (ambulatory) utilization is measured by the number of physician visits in settings other than an inpatient hospital: physician's office, hospital outpatient department or emergency room, freestanding clinic, nursing home, or patient's home. Physician claims for inpatient services (including surgery) were identified by matching the outpatient claims file to the inpatient claims file by dates of service and were placed in a separate file. Simultaneously, expenditures (Medicaid payments) for physician services rendered in a hospital were also separated from all other expenditures for ambulatory care. Similarly, surgical procedures (excluding claims from anesthesiologists and physician assistants) were separated into inpatient and outpatient surgeries. However, even more so than in the inpatient category, outpatient “surgery” includes many kinds of intrusive diagnostic and palliative procedures, as well as actual therapeutic operations, no matter how minor. The frequency count of surgical complications is also broken down into inpatient and outpatient settings. Finally, the measures of “prescription drug” utilization and expenditure used in this study cover only medicines obtained by prescription or over the counter. They do not include drugs “bundled in” with hospital or nursing home bills. Fortunately, bundling was not extensively practiced in either State during 1981-82.
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1.  Predicting hospital readmissions in the Medicare population.

Authors:  G F Anderson; E P Steinberg
Journal:  Inquiry       Date:  1985       Impact factor: 1.730

2.  Comparisons of family physicians and internists. Process and outcome in adult patients at a community hospital.

Authors:  P Franks; J C Dickinson
Journal:  Med Care       Date:  1986-10       Impact factor: 2.983

3.  Medicare patients: geographic differences in hospital discharge rates and multiple stays.

Authors:  M Gornick
Journal:  Soc Secur Bull       Date:  1977-06

4.  Effectiveness of inpatient follow-up care.

Authors:  R H Brook; F A Appel; C Avery; M Orman; R L Stevenson
Journal:  N Engl J Med       Date:  1971-12-30       Impact factor: 91.245

5.  Frequency and clinical description of high-cost patients in 17 acute-care hospitals.

Authors:  S A Schroeder; J A Showstack; H E Roberts
Journal:  N Engl J Med       Date:  1979-06-07       Impact factor: 91.245

6.  Survival of adult high-cost patients. Report of a follow-up study from nine acute-care hospitals.

Authors:  S A Schroeder; J A Showstack; J Schwartz
Journal:  JAMA       Date:  1981-04-10       Impact factor: 56.272

7.  Physician and hospital factors associated with mortality of surgical patients.

Authors:  J V Kelly; F J Hellinger
Journal:  Med Care       Date:  1986-09       Impact factor: 2.983

8.  Survival, hospitalization charges and follow-up results in critically ill patients.

Authors:  D J Cullen; L C Ferrara; B A Briggs; P F Walker; J Gilbert
Journal:  N Engl J Med       Date:  1976-04-29       Impact factor: 91.245

9.  The 'offset effect' of mental health treatment on ambulatory medical care utilization and charges. Month-by-month and grouped-month analyses of a five-year study.

Authors:  J F Borus; M C Olendzki; L Kessler; B J Burns; U C Brandt; C A Broverman; P R Henderson
Journal:  Arch Gen Psychiatry       Date:  1985-06

10.  Surgical outcome for resident and attending surgeons.

Authors:  E J Sussman; J N Kastanis; W Feigin; H M Rosen
Journal:  Am J Surg       Date:  1982-08       Impact factor: 2.565

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  1 in total

1.  Psychosocial Risks are Independently Associated with Cancer Surgery Outcomes in Medically Comorbid Patients.

Authors:  Ira L Leeds; Patrick M Meyers; Zachary O Enumah; Jin He; Richard A Burkhart; Elliott R Haut; Jonathan E Efron; Fabian M Johnston
Journal:  Ann Surg Oncol       Date:  2019-01-07       Impact factor: 5.344

  1 in total

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