Dehiscence misalgorithm

Ann M. Borzecki, M.D.Hillary Mull, Ph.D., M.Amy K. Rosen, Ph.D.b,

utcomPolicInterostod M

Boston University School of Medicine, Boston, MA; Department of Surgery, Harvard Medical School, Boston, MA

Patient safety;

isofp-nt

identification.METHODS: We selected 125 high-risk unflagged cases based on predicted probability and the pres-

exclusively in false-negative cases (representing 24% of false-negative cases).-

Patient Safety Indicators (PSIs) use administrative data todetect inpatient adverse events.1 Originally intended asscreens for quality of care problems, they are increasinglybeing used as hospital performance measures. Several

2

This study was funded by the US Department of Veterans Affairs

Health Services Research and Development Service grant number SDR

07-002. The funding agency had no involvement in: study design, data col-

lection, interpretation or analysis, manuscript writing or the decision to

submit this work for publication.

The American Journal of Surgery (2013) -, --* Corresponding author. Tel.:11-781-687-2870; fax:11-781-687-3106.CONCLUSIONS: Among high-risk cases, the PWD algorithm frequently missed events. Coder training to clarify assignment of abdominal wall repair codes, plus adding specific code combinations to thealgorithm, would improve event identification. 2013 Elsevier Inc. All rights reserved.

The Agency for Healthcare Research and QualitysQuality indicatorsence of clinically relevant codes. We determined the false-negative proportion and associated reasonsthrough chart review and calculated likelihood ratios of associated codes.

RESULTS: Thirty-two percent of cases were false negatives, 60% of which lacked any abdominalwall repair codes. All individual codes had low likelihood ratios; the combination of diagnosis code998.3x (operative wound disruption) and particular abdominal wall repair procedure codes occurredAdverse events; Diseases, Ninth Revision, Clition reclosure). We examinedKEYWORDS:Postoperative wounddehiscence;

Quality of care;

AbstractBACKGROUND: The Patient Safety Indicator (PSI) Postoperative Wound Dehiscence (PWD)

an administrative data-based algorithm that flags cases using International Classificationnical Modification (ICD-9-CM) code 54.61 (abdominal wall disruhow often PWD missed events and explored ways to improve eveaCenter forHealthQuality,OUSA; bDepartment of HealthMedicine, Section ofGeneralBoston Healthcare System, BOrganization, Leadership, anE-mail address: amb@bu.edu

Manuscript received May 4, 2012; r

0002-9610/$ - see front matter 2013http://dx.doi.org/10.1016/j.amjsurg.20dentification of Postoperative Woundsed by the Patient Safety Indicator

, M.P.H.a,b,c,*, Marisa Cevasco, M.D., M.P.H.d,e,P.P.f,g, Marlena Shin, J.D., M.P.H.f, Kamal Itani, M.D.d,g,h,f,g

es andEconomicResearch,BedfordVAMedical Center, 200SpringsRd,Bedford,MA01730,y andManagement, Boston University School of Public Health, Boston, MA; cDepartment ofnalMedicine, BostonUniversity School ofMedicine, Boston,MA; dDepartment of Surgery, VAn, MA; eDepartment of Surgery, Brigham and Womens Hospital, Boston, MA; fCenter foranagement Research, VA Boston Healthcare System, Boston, MA; gDepartment of Surgery,

hImproving the ievised manuscript July 4, 2012

Elsevier Inc. All rights reserved.

12.07.040have been endorsed by the National Quality Forum ; thusfar, 6 individual indicators and a composite indicator

have been added to the Centers for Medicare and MedicaidServices hospital reporting initiative.3,4

The PSIs were developed through a rigorous evidence-based process, including comprehensive literature review,structured clinical panel review, coding expert consultation,and empirical analyses of potential indicators.1 This pro-cess established their face and construct validity (ie, theirassociation with related measures),5 whereas additionalstudies demonstrated their predictive validity (ie, theirability to predict an outcome such as death).6,7 However,use as performance measures necessitates understandingthe PSIs measurement properties, especially their accur-acy or criterion validity (ie, their agreement with an ac-cepted standard such as medical record information). Ifhospitals are to be judged fairly based on their rates ofthese complications, we need to have measures that areas accurate as possible.

The PSIs were intentionally designed to favor specificity

of the indicators miss true events.8 This is important to elu-cidate; instead of better care, lower rates may actuallyreflect event undercoding or poor documentation in themedical record.

In the current study, we explored this issue using PSI14, Postoperative Wound Dehiscence (PWD). We selectedPWD because we previously found that of the indicators, ithad among the highest positive predictive values (87%)and the lowest rates of present-on-admission cases(0%); furthermore, Centers for Medicare and MedicaidServices has tracked this individual indicator since2010.3,4,10,15,16 We examined the proportion of false-negative cases in a VA population at high risk for PWD.We also assessed the potential effect of adding specificInternational Classification of Diseases, Ninth Revision,Clinical Modification (ICD-9-CM) codes to the currentalgorithm and explored reasons for missed cases to try toimprove event detection.

ion osionabdod 18

ostosurgedsed serpe

linica

and m

mplet

2 The American Journal of Surgery, Vol -, No -, - 2013over sensitivity to improve identification of true events andof events that are more likely to be preventable. In fact, anearlier study using Department of Veterans Affairs (VA)data reported specificities of greater than 99% but sensi-tivities of only 19% to 56%.8 Sensitivity and specificity arethe preferable properties to define because they dependonly on the properties of the measure and not the popula-tion.9 However, given the significant time and resourcesrequired to sample the universe of patients at risk to deter-mine sensitivity and specificity, more recent studies havefocused on the PSIs predictive values, which are a propertyof both the measure and the complications prevalence inthe population. Studies have especially focused on theirpositive predictive value (ie, the proportion of flaggedevents that represent true events based on medical recordreview) and found these to vary by indicator, from as lowas 28% to as high as 91%.1014 Although positive predic-tive values of 80% or higher generally suggest good testaccuracy, little information exists on how frequently any

Table 1 PWD detailed definition and ICD-9-CM codes

Definition Cases of reclosure of postoperative disruptNumerator Discharges among cases meeting the inclu

reclosure of postoperative disruption ofDenominator All abdominopelvic surgical discharges age

Exclude cases: in which a procedure for reclosure of p

same day as the first abdominopelvic in which length of stay is less than 2 in which there is an immunocompromi MDC 14 (pregnancy, childbirth, and pu

MDC is based on the principal diagnosis.

ICD-9-CM 5 International Classification of Diseases, Ninth Revision, Cwound dehiscence.

*Reported as rates, risk-adjusted for age, sex, selected comorbiditiesSee Patient Safety Indicator (PSI) technical specifications for the co

5,20mised state.Methods

Study design and data

We performed a retrospective cross-sectional studyusing VA administrative and electronic medical recorddata from October 1, 2002 to September 30, 2007. Weobtained inpatient information (ie, demographics andICD-9-CMcoded diagnoses and procedures) from theNational Patient Care Database.17 We eliminated nonacutecare (eg, long-term care)7,18 and accessed remote electronicmedical record data using VistAWeb.10,19

Postoperative wound dehiscence definition

PWD is intended to capture cases of fascial dehiscenceoccurring after abdominopelvic surgery that require a

f abdominal wall per 1,000 cases of abdominopelvic surgery*and exclusion rules for the denominator with ICD-9-CM code forminal wall (54.61) in any procedure fieldyears and older defined by specific ICD-9-CM codes

perative disruption of abdominal wall occurs before or on thery procedure

tate

rium)

l Modification; MDC 5 major diagnostic category; PWD 5 postoperative

odified diagnosis-related groups (DRGs).4

e list of eligible surgical procedure codes and codes for immunocompro-

reparative operation, as identified by ICD-9-CM code 54.61(reclosure of a postoperative abdominal wall disruption).Table 1 shows the full PWD definition.5,20

Study sample

See Figure 1 for the study sample selection strategy. Tomaximize selection of cases at highest risk, we selectedfrom the entire pool of potential cases at 158 hospitals (un-like our previous positive predictive value study in which weselected from a subsample of hospitals).16 We first appliedthe PSI software, version 3.1.a, to our inpatient file to iden-tify the discharge pool at risk (ie, the PWD denominator).We then excluded 620 discharges that flagged positive forPWD. Next, because abstracting the universe of missedcases was impossible (the remaining sample size was99,665), we selected cases at higher risk for PWD as fol-lows: (1) we derived prediction scores representing the prob-ability of PWD developing using a regression model thatincluded age, sex, diagnosis-related groups, and comorbid-ities at admission;21 and (2) we used a list of diagnosticand procedure codes, generated by Agency for HealthcareResearch and Quality clinician-investigators, that weredeemed more likely to be present in false-negative cases(Patrick Romano, MD, personal communication) (Table 2).We selected 125 cases with the highest prediction scoresout of the 1,869 cases that had at least 1 of the listed codes.

Electronic medical record abstraction

Two trained nurse-abstractors reviewed electronic medicalrecords using a standardized abstraction instrument devel-oped in previous work.16 It contained questions regardingevent ascertainment, including exclusions. For all cases,abstractors provided a brief clinical scenario describing anywound-related complications. For false-negative cases, nursesabstracted management and outcome information. Studyphysicians (A.B. and M.C.) reviewed cases for clarification,as necessary, throughout the abstraction process.

Because abstractors were familiar with the abstractiontool and had previously achieved high inter-rater reliabil-ity,16 especially with respect to case ascertainment (100%agreement on the inter-rater sample), we did not repeatinter-rater reliability assessment in the current study.

Analyses

We categorized cases as false negatives or true negativesper abstracted information. We initially considered all casesof wound dehiscence as false negatives, regardless ofwhether subsequent reparative surgery was performed. Wethen considered only wound dehiscence cases requiring areparative operation as false negatives. Study cliniciansreviewed all abstracted information in detail; they performedrepeated review of medical records of any wound dehiscence

A.M. Borzecki et al. Missed Postoperative Wound Dehiscence Events 3Figure 1 Study sample selection.

erativ

Possible miscoded secondary diagnoses (not present on admission)

latercipa

rocedindicounderatioeratiindewithoantenia rerniaof oothelatingl wal walr fascf skin

Clinica

4 for

iscenc553.21 Ventral hernia, incision879.25 Open wound, anterior or

without any other (prin998.13 Seroma complicating a p

Secondary diagnosis without procedure code required by current998.3 Disruption of operation w998.31 Disruption of internal op998.32 Disruption of external op

Potentially relevant corrective procedures, occurring R1 d after53.51 Incisional hernia repair (53.52 Repair of other hernia of53.61 Other open incisional her53.62 Laparoscopic incisional h53.63 Other laparoscopic repair53.69 Other and open repair of54.62 Delayed closure of granu54.63 Other suture of abdomina54.72 Other repair of abdomina83.65 Other suture of muscle o86.59 Suture or other closure o

ICD-9-CM 5 International Classification of Diseases, Ninth Revision,*See Patient Safety Indicator (PSI) technical specifications from PSIAlthough code 998.31 was intended to be used to indicate fascial deh

years used in our study.Table 2 Potential ICD-9-CM Codes Representing Missed Postop

ICD-9-CM Code Description

4cases in which reparative surgery was not performed toconfirm that they were true-negative cases. They alsorepeated review of operative reports of wound dehiscencecases in which subsequent repair was performed to betterunderstand reparative procedure coding.

We first calculated the proportion of false negatives (ie,false negatives divided by all unflagged cases) and associ-ated 95% confidence intervals. To assess whether addingcertain codes or coding combinations to the existing PSIalgorithm might improve event identification, we calculatedlikelihood ratios of associated codes (ie, how likely a codewas to occur in a false negative vs a true negative). Alikelihood ratio greater than 1.0 indicates that the code ismore likely to occur in a false-negative case; a likelihoodratio less than 1.0 indicates that the code is less likely tooccur in a false-negative case. Likelihood ratios greaterthan 10 are considered high and provide strong evidence infavor of a true event.22 Likelihood ratios of 5 to 10 are con-sidered moderate. We calculated the percentage of falsenegatives and likelihood ratios in 2 ways: (1) consideringall wound dehiscence cases as false negatives; and (2) con-sidering only cases in which a reparative operation was per-formed as false negatives.

Results

The 125 reviewed cases came from 59 hospitals (me-dian, 2 cases per hospital; range, 1 to 5). Fifty-four cases ore Wound Dehiscence Cases

al abdominal wall, without or without mention of complication,l or secondary) diagnosis of trauma*ureator logic (54.61)

n wound

on woundx abdominopelvic surgical procedureut graft or prosthesis)rior abdominal wall (without graft or prosthesis)epair with graft or prosthesisrepair with graft or prosthesis

ther hernia of anterior abdominal wall with graft or prosthesisr hernia of anterior abdominal wall with graft or prosthesisabdominal wound

llliaand subcutaneous tissue, other sites

l Modification.

trauma diagnosis codes.5,20

e, this was not made explicit in the coding guidelines until after the data

The American Journal of Surgery, Vol -, No -, - 201343% (34% to 52%) involved a wound dehiscence. In 14 ofthese cases, reparative surgery was not performed for thewound dehiscence; considering these as true negatives, thepercentage of false negatives decreased to 32% (24% to41%). Five of these 14 patients were too ill or died the sameday as the dehiscence diagnosis; the remainder were treatedconservatively (eg, using dressing changes).

Considering all wound dehiscence cases, 50 false neg-atives (93%) had the term fascial dehiscence (n 5 31)or wound dehiscence (n 5 19) noted in the electronic med-ical record. (It was clear from reviewing notes of theselatter cases that the fascia had dehisced). In the remaining4 cases, there was mention of the fascia being open or ofbowel eviscerating through the wound, or both. Excludingthe 14 nonsurgically treated patients, findings were similar:38 (95%) had fascial or wound dehiscence explicitlydocumented.

Because candidate code likelihood ratios were similarfor both false-negative identification methods, we summa-rize results for cases considered false negatives in which areparative operation was performed (Table 3). Table 3shows only candidate codes found in our sample. (Resultsof analyses considering all cases of wound dehiscence asfalse negatives are not shown, but are available from theauthors).

The most frequent diagnosis code was 998.3x (operativewound disruption), which includes codes 998.3 (wounddisruption), 998.31 (internal wound disruption), and 998.32(external wound disruption), which was seen in 95% of

ce ETable 3 Likelihood Ratio of Various ICD-9-CM Codes (WoundDehiscence with Reparative Operation Considered as FalseNegative)*

Variable FNs (n 5 40) TNs (n 5 85) LR

Diagnosis codes

553.21 0 3 (3.5%) 0998.13 0 4 (4.7%) 0998.3x 40 (95.0%) 58 (70.6%) 1.35

A.M. Borzecki et al. Missed Postoperative Wound Dehiscenfalse negatives and 71% of true negatives (78% of the entiresample). The associated likelihood ratio was 1.4. The mostcommon single code among both false negatives and truenegatives was 998.32, followed by 998.31 (65% of falsenegatives vs 51% of true negatives, and 30% of falsenegatives vs 22% of true negatives, respectively). Associ-ated respective likelihood ratios were both 1.3. Codes553.21 (incisional ventral hernia) and 998.13 (seromacomplicating a procedure) occurred only in true-negativecases.

nosis codes, occurred with adequate specificity in false-

998.3 1 (2.5%) 1 (1.2%) 2.13998.31 12 (30.0%) 19 (22.4%) 1.34998.32 26 (65.0%) 43 (50.6%) 1.28

Procedure codes53.51 1 (2.5%) 2 (2.4%) 1.0653.61 1 (2.5%) 1 (1.2%) 2.1354.62 1 (2.5%) 12 (14.1%) 0.1854.63 4 (10.0%) 6 (7.1%) 1.4254.72 6 (15.0%) 4 (4.7%) 3.1983.65 1 (2.5%) 1 (1.2%) 2.1386.59 5 (12.5%) 5 (5.9%) 2.13Any proc code 16 (40.0%) 27 (31.8) 1.26

Diagnosis and procedurecodes

998.3x 1 proc code 14 (35.0%) 5 (5.9%) 5.95998.31 1 proc code 5 (12.5%) 2 (2.4%) 5.31998.32 1 proc code 10 (25.0%) 3 (3.5%) 7.08998.3x 1 53.51 1 (2.5%) 1 (1.2%) 2.13998.3x 1 53.61 1 (2.5%) 1 (1.2%) 2.13998.3x 1 54.62 1 (2.5%) 2 (2.4%) 1.06998.3x 1 54.63 3 (7.5%) 0 N998.3x 1 54.72 6 (15.0%) 0 N998.3x 1 83.65 1 (2.5%) 0 N998.3x 1 86.59 4 (10.0%) 2 (2.4%) 4.25

We have bolded LRs ,1.0 and .5.0. (An LR ,1.0 indicates thatthe code is more likely to occur in TNs than in FNs. An LR .1.0indicates that the code is more likely to occur in FNs than in TNs. See

Methods section for further information on interpreting LRs.).

We present results for any codes that occurred at least once in the

sample.

All observed 998.3x and procedure code combinations are shown.

Findings were similar when we examined diagnosis codes 998.31 and

998.32 separately with the procedure codes; however, there were no

combinations of 998.31 and 53.51 or 53.61.

FN 5 false negative; LR 5 likelihood ratio; proc 5 procedure;TN 5 true negative.

*We found similar results when we considered all cases with wound

dehiscence as false negatives regardless of whether they had a repar-

ative procedure or not.Sum of 998.3, 998.31, and 998.32.Includes at least 1 of listed procedure codes.negative cases.

Comments

This is the first study we know of that reports theproportion of false-negative cases associated with the PSIPWD and examines in detail reasons for missed cases andpossible ways to improve the indicators algorithm. Amonghigh-risk cases, the existing algorithm frequently missedtrue PWD events (32% vs 43% of events, depending on thedefinition used).

By defining a PWD event based on the presence of asingle procedure code, ie, 54.61, which is postoperativeabdominal wall disruption reclosure, the PWD algorithmfavors specificity over sensitivity. The intent is to capturedehiscences that are deep and severe enough to requirereparative surgery and to avoid capturing clinically insig-nificant events or nondehiscence wound-related problems.The sensitivity of PWD was only 29% in the largest studythat reported it, which is consistent with our current findingof frequently missed cases;8 (respective specificity and pro-portion of false-negative cases calculated from publishednumbers were 99.8% and 1.2% in this lower risk sample).However, this study did not include in-depth analysis ofmissed cases.

Our findings suggest that a few algorithm modificationsshould enhance PWD identification. Theoretically, onecould identify wound dehiscence cases by diagnosis codes;Of false-negative cases in which reparative surgery wasperformed, only 40% had a candidate procedure code.Individual codes were relatively rare; no single codeoccurred in more than 15% of false-negative cases or 14%of true-negative cases: all had relatively low likelihoodratios. The most common procedure among false-negativecases was 54.72 (other abdominal wall repair); it had thehighest single codeassociated likelihood ratio at 3.2. Themost common code among true-negative cases was 54.62(delayed granulating abdominal wound closure); it had thelowest likelihood ratio at 0.18.

Combining a 998.3x diagnosis code and any procedurecode resulted in higher likelihood ratios (.5.3) butoccurred in at most 35% of false-negative cases. However,several combinations of 998.31 or 998.32 plus specificprocedure codes appeared exclusively in false-negativecasesd998.31 or 998.32, considered either separately ortogether, plus procedure codes 54.63 (other abdominal wallsuture), 54.72 (other abdominal wall repair), and 83.65(other muscle or fascia suture). This represented 24% offalse-negative cases (n 5 10).

Further examination of false-negative cases revealed thatmost lacked codes specific to the abdominal wall (fascial)repair part of the procedure (n5 20); the remainder (n5 4)lacked any codes for the relevant abdominal procedure. Noadditional procedure code, alone or combined with diag-

vents 5after the data years studied, the postoperative wound

Conclusionsdisruption diagnosis codes (998.3x) were made morespecific. In 2008, code 998.31 (internal wound disruption)had fascial dehiscence explicitly added to its definition. Inthis study and in our previous study of PWDs positivepredictive value,16 coders used either 998.31 or 998.32(external wound disruption) to indicate a wound dehisce-nce, with 998.32 occurring more commonly than 998.31(66% vs 25% of true-positive cases), suggesting coder con-fusion regarding when to use code 998.31 over 998.32.Whether increased specification has improved assignmentof these codes requires study using more recent data.

Although adding a specific wound dehiscence diagnosiscode to the algorithm should improve identification ofevents, without the requirement of an associated reparativeprocedure code, detection of clinically insignificant eventswould increase. Conversely, requiring a reparative proce-dure code will miss some clinically significant patients whoare too ill to undergo repair or who require repair at a latertime. Nevertheless, adhering to the current reparative oper-ation definition, we found opportunities to improve codingof fascial dehiscence and abdominal wall repair, includingwhen to use code 54.61, through coder education. All butpossibly 2 false-negative cases in which reparative surgerieswere performed should have received a 54.61 code. Addi-tionally, in several cases, the procedure indicating abdom-inal wall closure was not coded at all. This lack of codingwas not related to whether the abdominal wall repair wasexplicitly listed as a secondary procedure in surgical notes orto the number of other secondary procedures coded.

Another option would be to add a 998.3x code, togetherwith a 54.72 or 83.65 procedure code, to the algorithmbecause these occurred exclusively in false-negative cases,or the diagnosis code could be restricted to 998.31, givenits subsequent increased specificity. (Although 998.3xplus 54.63 also occurred only in false-negative cases, the54.63 code is intended to capture repair of traumaticabdominal wall injuries, not postoperative complications).

As noted, this is the first study in any setting (that we areaware of) to examine in detail ways to improve thisindicator. In addition, repeated review by the study clini-cian of electronic medical records of false-negative caseslacking follow-up operations plus operative reports of false-negative cases in which reparative surgery was performedstrengthens our findings. Further, because we were lookingfor relatively rare events, we designed our case selectionmethod to maximize the likelihood of finding false-negativecases. At least 32% of cases were false negatives, signify-ing that we successfully identified a high-risk group;similar methods may be used to study false-negative casesfor other PSIs.

Since this indicator is based only on a procedure code,recent modifications to diagnostic codes representingwound dehiscence would not have affected our conclusionsregarding coding problems related to procedures. Addition-ally, we used PSI software version 3.1a, whereas the currentversion is 4.3. Again, this should not have impacted our

6findings or conclusions because the specifications for PWDIn summary, among a sample at high risk for PWD, theexisting PSI algorithm frequently missed true events. Caseidentification could be improved through coder training toclarify appropriate assignment of code 54.61, as well asadding a requirement for a 998.31 diagnosis code plusspecific procedure codes representing abdominal wallrepair. These methods will enable fairer facility-levelcomparisons of PWD rates, in addition to assisting localquality improvement efforts. Until then, despite PWDshigh positive predictive value, publicly reported hospitalrates should be interpreted cautiously, because variation inrates may reflect missed events caused by coding differ-ences as opposed to true quality of care differences.

References

1. McDonald KM, Romano PS, Geppert J, et al. Measures of Patient

Safety Based on Hospital Administrative DatadThe Patient Safety In-

dicators. Technical Review 5 (Prepared by the University of California

San FranciscoStanford Evidence-Based Practice Center under Con-

tract No. 290-97-0013). AHRQ Publication No. 02-0038. Rockville,

MD: Agency for Health Care Research and Quality; August 2002.

2. National Quality Forum. NQF Endorsed Standards. Available at:

http://www.qualityforum.org/Measures_List.aspx. Accessed January

10, 2012.

3. Centers forMedicare&Medicaid Services. Fiscal Year 2009QualityMea-

sure Reporting for 2010 Payment Update. Available at: http://www.cms.

hhs.gov/HospitalQualityInits/downloads/HospitalRHQDAPU200808.pdf.

Accessed March 1, 2012.

4. Hospital Inpatient Quality Reporting Program Overview: Resources

for Fiscal Year 2012 Payment Determination: Program Changes/Updates.

Available at: http://www.qualitynet.org/dcs/ContentServer?cid51138115987129&pagename5QnetPublic%2FPage%2FQnetTier2&c5Page. Acc-essed September 1, 2011.

5. Agency for Healthcare Research and Quality (AHRQ). AHRQ Quality

Indicators: Guide to Patient Safety Indicators. Version 3.0a. Rockville,

MD: Agency for Healthcare Research and Quality; March 2003have not appreciably changed between these versions.Although we previously studied PWDs positive predictivevalue (the proportion of true-positive cases among flaggedcases)16 and now report the proportion of false-negativecases among unflagged cases, we cannot meaningfullycombine samples to calculate sensitivity or specificitybecause we abstracted only a small pool of high-riskunflagged cases herein. We also did not have sufficientnumbers to examine whether coding issues varied by hospi-tal. Nonetheless, our analysis yields important informationwith respect to improving PWD identification. Addition-ally, we do not know how generalizable these findings areto non-VA settings; several of our false-negative caseswere missing codes for the wound repair. We would expectthis might occur less frequently in more reimbursement-dependent health care settings. (We await results from asimilar study conducted in the non-VA setting for compar-ison [Patrick Romano, MD, personal communication]).

The American Journal of Surgery, Vol -, No -, - 2013(Version 3.1, March 12, 2007).

6. Zhan C, Miller MR. Excess length of stay, charges, and mortality at-

tributable to medical injuries during hospitalization. JAMA 2003;

290:186874.

7. Rosen AK, Rivard P, Zhao S, et al. Evaluating the PSI: how well do

they perform on Veterans Health Administration data? Med Care

2005;43:87384.

8. Romano PS, Mull HJ, Rivard PE, et al. Validity of selected AHRQ PSI

based on VA National Surgical Quality Improvement Program data.

Health Serv Res 2009;44:182204.

9. Sackett DL, Haynes RB, Guyatt GH, et al. Clinical Epidemiology: A

Basic Science for Clinical Medicine. 2nd ed. Boston, MA: Little,

Brown and Company; 1991.

10. Rosen AK, Itani KM, Cevasco M, et al. Validating the PSI in the Vet-

erans Health Administration: do they accurately identify true safety

events? Med Care 2012;50:7485.

11. Utter GH, Cuny J, Sama P, et al. Detection of postoperative respiratory

failure: how predictive is the Agency for Healthcare Research and Qual-

itys Patient Safety Indicator? JAmColl Surg 2010;211:347354.e129.

12. Sadeghi B, Baron R, Zrelak P, et al. Cases of iatrogenic pneumothorax

can be identified from ICD-9-CM coded data. Am J Med Qual 2010;

25:21824.

13. White RH, Sadeghi B, Tancredi DJ, et al. How valid is the ICD-9-CM

based AHRQ patient safety indicator for postoperative venous throm-

boembolism? Med Care 2009;47:123743.

14. Zrelak PA, Sadeghi B, Utter GH, et al. Positive predictive value of the

Agency for Healthcare Research and Quality Patient Safety Indicator

for central line-related bloodstream infection (selected infections

due to medical care). J Healthc Qual 2011;33:2936.

15. USDepartment of Health andHuman Services.Medicare.gov - Hospital

Compare. Available at: http://www.medicare.gov/hospitalcompare/

Accessed January 31, 2013.

16. Cevasco M, Borzecki AM, McClusky 3rd DA, et al. Positive predictive

value of the AHRQ Patient Safety Indicator postoperative wound de-

hiscence. J Am Coll Surg 2011;212:9627.

17. VA InformationResourceCenter. VIReCResearchUserGuide: FY2002

VHA Medical SAS Inpatient Datasets. Available at: http://www.virec.

research.va.gov/RUGs/MedSAS-Archive/IP/RUG-MedSAS-IP-FY02-

ER.pdf. Accessed January 22, 2013.

18. Rivard P, ElwyAR, Loveland S, et al. Applying PSI (PSIs) across health-

care systems: achieving data comparability. In: Henriksen K, Battles JB,

Marks ES, et al., editors. Advances in Patient Safety: From Research to

Implementation. vol 2. Rockville, MD: Agency for Healthcare Research

and Quality; 2005. p. 725.

19. VistAWeb Technical Manual, Version 8.0. Health Provider Systems Of-

fice of Information and Technology, Department of Veterans Affairs.

November 2008. Available at: http://www.va.gov/vdl/documents/

Clinical/VistaWeb/webv_1_13_tm.pdf. Accessed: October 27, 2012.

20. Agency for Healthcare Research and Quality. Patient Safety Indicators:

Technical Specifications. March 2003; Version 3.1 (March 12, 2007).

Available at: http://www.qualityindicators.ahrq.gov/Downloads/Modules/

PQI/V31/pqi_guide_v31.pdf.

21. Healthcare Cost and Utilization Project (HCUP). Comorbidity Software.

Available at: http://www.hcup-us.ahrq.gov/toolssoftware/comorbidity/

comorbidity.jsp#overview. Accessed September 5, 2011.

22. Deeks JJ, Altman DG. Diagnostic tests 4: likelihood ratios. BMJ 2004;

329:1689.

A.M. Borzecki et al. Missed Postoperative Wound Dehiscence Events 7

Improving the identification of Postoperative Wound Dehiscence missed by the Patient Safety Indicator algorithmMethodsStudy design and dataPostoperative wound dehiscence definitionStudy sampleElectronic medical record abstractionAnalyses

ResultsCommentsConclusionsReferences