text:
Sens, sensitivity; DSM-IV, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; PHQ-9, Patient Health Questionnaire; C-DISC, Computerized Diagnostic Interview Schedule for Children; DIS, Diagnostic Interview Schedule; CES-D, Center for Epidemiologic Studies Depression; PPV, positive predictive value; ICD-9, International Classification of Diseases, Ninth Revision.
Original Report
A systematic review of validated methods for identifying depression using administrative data
Version of Record online: 19 JAN 2012
DOI: 10.1002/pds.2310
Copyright © 2012 John Wiley & Sons, Ltd.
Pharmacoepidemiology and Drug Safety
Supplement: The U.S. Food and Drug Administration's Mini-Sentinel Program
Volume 21, Issue Supplement S1, pages 163–173, January 2012
Additional Information
How to Cite
Townsend, L., Walkup, J. T., Crystal, S. and Olfson, M. (2012), A systematic review of validated methods for identifying depression using administrative data. Pharmacoepidem. Drug Safe., 21: 163–173. doi: 10.1002/pds.2310
Publication History
- Issue online: 19 JAN 2012
- Version of Record online: 19 JAN 2012
Funded by
- Food and Drug Administration through the Department of Health and Human Services. Grant Number: HHSF223200910006I
- Abstract
- Article
- References
- Cited By
- depression;
- antidepressants;
- epidemiology;
- surveillance
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Administrative and claims data (hereafter administrative data) represent an important resource for safety surveillance and research on the use and effectiveness of medical products. They offer opportunities to conduct safety surveillance or study drug use, other treatments, and selected outcomes for large and diverse patient populations across a broad range of usual care settings. However, because these datasets are not designed for either surveillance or research purposes, their use is subject to significant challenges and limitations.[1] One key challenge involves assessing the validity of algorithms for identifying various outcomes and coexisting conditions. This was recognized by the Food and Drug Administration as an important need for its Mini-Sentinel pilot program, which is currently focused on conducting safety surveillance to refine safety signals that emerge for its regulated medical products. An important step is to assess the validity of algorithms for identifying health outcomes of interest (HOI) in administrative data.
Depression represents an important HOI. It is a leading source of disability, accounting for approximately one third of healthy life years lost to disability for people aged 15 years and older.[2] Given the significant disease burden caused by depression, large-scale efforts to identify the disorder and monitor its outcomes are of paramount importance to public health. In the present report, we review studies that have sought to validate algorithms for identifying cases of depression using administrative data. This report summarizes the process and findings of the depression algorithm review. The full report is available on the Mini-Sentinel Web site at http://mini-sentinel.org/foundational_activities/related_projects/default.aspx.
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Data sources were limited to administrative datasets from the USA or Canada. The general search strategy was developed based on prior work by the Observational Medical Outcomes Partnership (OMOP)[3] and its contractors and modified slightly for these reports. The modified OMOP search strategy was combined with PubMed terms representing the HOI. Medical subject heading (MeSH) terms were used as HOI search terms. Details of the methods for these systematic reviews can be found in the accompanying article by Carnahan and Moores.[4] Briefly, the base PubMed search was combined with the following terms to represent depression: depression, major depressive disorder, dysthymic disorder, or seasonal affective disorder. The workgroup also searched the database of the Iowa Drug Information Service (IDIS) using a similar search strategy to identify other relevant articles that were not found in the PubMed search. To identify depression validation studies that were unpublished, in prepublication, or that were not identified by the search strategies, Mini-Sentinel investigators were requested to provide information on any published or unpublished administrative data studies that validated an algorithm for depression. Results were aggregated into two sets of files, one containing the abstracts for review and the other for documenting abstract review results. The PubMed search was conducted on 14 May 2010 and the IDIS searches on 11 June 2010.
Abstract review
Each abstract was reviewed independently by the first and second authors (L.T. and J.W.) to determine whether the full-text article should be reviewed. The following abstract exclusion criteria were applied: (i) The abstract did not mention depression or dysthymia; (ii) the study did not use an administrative database (eligible sources included insurance claims databases and other secondary databases that identify health outcomes using billing codes); and (iii) the data source was not from the USA or Canada. Exclusion criteria were documented sequentially (i.e., if one exclusion criterion was met, then the other criteria were not documented). If the reviewers disagreed on whether the full text should be reviewed, then it was selected for review. Interrater agreement on whether to include or exclude an abstract was calculated using Cohen's kappa.
Full-text review
Full-text articles were reviewed independently by the first and second authors (L.T. and J.W.), with the goal of identifying validation studies. The full-text review included examination of articles' reference sections as an additional means of capturing relevant citations. Citations from the references were selected for full-text review if they were cited as a source for a depression algorithm or were otherwise deemed likely to be relevant. Full-text studies were excluded from the final evidence table if they met one or more of the following criteria: (i) The article contained a poorly described or difficult to operationalize depression algorithm defined by the absence of Diagnostic and Statistical Manual of Mental Disorder (DSM) depression diagnosis codes (296.2, 296.3, 300.4, or 311) or the International Classification of Diseases (ICD) diagnosis codes for depression (296.2, 296.3, 300.4, 311, 298.0, or 309.1), and (ii) the article provided no validation measure of depression or did not report validity statistics. Full-text review exclusion criteria were applied sequentially. If there was disagreement on whether a study should be included, the two reviewers (L.T. and J.W.) attempted to reach consensus on inclusion by discussion. If they could not agree, an additional investigator (M.O.) was consulted to make the final decision.
All studies that survived the exclusion screen were included in the final evidence table. A single investigator abstracted each study for the table. A second investigator confirmed the accuracy of the abstracted data. A clinician or topic expert was consulted to review the results of the evidence table and to evaluate how the findings compared with the findings of diagnostic methods used in clinical practice. This assessment helped to determine whether the algorithms excluded any depression diagnosis codes commonly used in clinical practice and the appropriateness of the validation measures in relation to clinical diagnostic criteria.
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The total number of unique citations from the combined searches was 1731. A second PubMed search incorporating additional database names identified 30 citations.
Abstract reviews
Of the 1761 abstracts reviewed, 286 were selected for full-text review; 219 were excluded because they did not study depression, 994 were excluded because they were not administrative database studies, and 262 were excluded because the data source was not from the USA or Canada. Cohen's kappa for reviewer agreement regarding abstract inclusion or exclusion was 0.77.
Full-text reviews
Of the 286 full-text articles reviewed, 10 were included in the final evidence tables; 142 were excluded because the identification algorithm was poorly defined (e.g., did not use the specified DSM or ICD diagnosis codes for depression), and 134 were excluded because they included no validation of depression or validity statistics. Reviewers identified 36 new citations from full-text article references. Of these, one was included in the final report; 9 did not study depression, 12 were not database studies, 5 were excluded because the depression algorithm was poorly defined, and 9 were excluded because they included no validation of depression or validity statistics. The final evidence tables collectively include 11 articles (see Tables 1 and 2). Cohen's kappa for reviewer agreement regarding inclusion or exclusion of full-text articles was 0.95.
|Study Population and Time Period
|Description of Outcome Studied
|Validation/Adjudication Procedure and Operational Definition
|Positive Predictive Value (PPV)
|Sensitivity (Sens)
|Kahn et al., 2008[14]
|Adult (≥18 years) Medicaid behavioral health managed care organization enrollees (n=249) with a diagnosed mental disorder and diabetes, 63.1% female, mean age 52.2 years, 2006
|PHQ-9 assessed depression by mail survey
|Depression ICD-9 code: 296.2,296.3, 298.0, 300.4, 309.0, 309.1, 309.28, or 311* in the encounter data
|Operating characteristics of depression diagnosis code in encounter data (screen) in relation to PHQ-9 score ≥ 10
|PPV=66.4% (71 of 107)
|Sens=51.1% (71 of 139)
|Katon et al., 2006[5]
|Adolescent (11–17 years) primary care outpatients (n=769), with history of asthma treatment, excluded patients treated for bipolar disorder or schizophrenia; depressed subsample 64% female, 2004–2005
|C-DISC assessed DSM-IV major depression or dysthymia; C-DISC assessed DSM-IV panic, generalized anxiety, social phobia, agoraphobia, or separation anxiety disorder
|≥1 ICD-9: 296.2,296.3, 298.0, 300.4, 309.0, 309.1, 309.28, or 311* depressive disorder diagnosis in utilization record during 12 months before C-DISC
|Proportion of patients with utilization claim for depression who met C-DISC criteria for a depressive disorder (PPV1); Proportion of patients with utilization claim for depression who met C-DISC depressive or anxiety disorder criteria (PPV2)
|PPV1=31.5% (29 of 92) PPV2= 39.4% (41 of 104)
|Sens1=48.3% (29 of 60) Sens2=36.6% (41 of 112)
|Katon et al., 2004[6]
|Adult HMO patients (n=4385) with treatment of diabetes mellitus and major depression as assessed by PHQ-9, 60% female, mean age 59 years, excluded patients without diabetes, with cognitive impairment, too ill to participate, or language/hearing problem.
|PHQ-9 positive screen for current major depression.
|In 12 months before assessment: 1. ICD-9 code for ≥1 depression: 296.2,296.3, 298.0, 300.4, 309.0, 309.1, 309.28, or 311* AND 2. Antidepressant (AD) prescription
|Proportion of patients with PHQ-9 major depression disorder who were detected by ICD-9 code (S1) or AD prescription (S2).
|Sens (S1) = 36.3% (190 of 524) Sens (S2) = 42.9% (225 of 524)
|McCusker et al., 2008[12]
|Emergently admitted medical inpatients ages ≥65 years (n=185) from 2 university-affiliated acute care hospitals in Montreal, over sampled for depression, excluding patients with cognitive impairment.
|DIS assessed major depressive disorder of > 6 months or < 6 months duration.
|During 12 months after index inpatient admission, 3 Algorithms: 1. Outpatient claim for physicians services for ICD-9: 311, 300.4. 2. Antidepressant prescription. 3. Psychiatrist visit.
|Proportion with DIS assessed major depression > 6 months (Sens1) and < 6months (Sens2) duration with outpatient claims for depression during 12 months before or after index inpatient admission.
|PPV1=56.3% (9 of 16) PPV2=54.5% PPV3=62.5% (10 of 16)
|Sens1= 15.8% (9 of 57) Sens2= 52.6% (30 of 57) Sens3=17.5% (10 of 57)
|Solberg et al., 2003[13]
|Adult (≥18 years) outpatients (n=274) from 9 staff model primary care clinics in a metropolitan area with depression code, no antidepressant prescription 6 months, no diagnosis bipolar, schizophrenia, or alcoholism past year, 1998–1999
|1. Depressive symptoms (CES-D ≥6) ( PPV1)
|ICD-9 311 (only code available for depression) code, no other 311 codes in previous 6 months, no AP fills in previous 6 months.
|Proportion of patients meeting administrative code definition of depression who met each of the four outcomes (CES-D score, self-reported current depression, told by health care professional at visit had depression, and chart audit with depression diagnosis or treatment at index visit.
|PPV1=71.5% (196 of 274)
|Study Population and Time Period
|Description of Outcome Studied
|Validation/Adjudication Procedure and Operational Definition
|Positive Predictive Value (PPV)
|Frayne et al., 2010[7]
|National sample (n=133,068) of Veterans who were treated for diabetes mellitus and responded to a health survey, 98.1% male, 76.6% white, mean age-66.3 years, 1998-1999.
|Patient self-report of depression: "Has a doctor ever told you that you have depression?"
|Diagnosis of ICD-9: 296.2x, 296.3x, 311.
|Proportion of patients meeting algorithm criteria told that they have depression (PPV) and proportion not meeting algorithm criteria not told that they have depression (NPV).
|Kramer et al., 2003[10]
|Veterans (n=109) from 3 VA medical centers with ≥1 outpatient claim for a depressive disorder (296.2-296.26, 296.3-296.36, or 311) after 180 days without such a claim or an AD fill, 95.2% male, mean age 55.5 years,1999-2001.
|Presence of depression diagnosis in medical record during 180 day period after the new depressive disorder claim
|≥1 outpatient claims for depression (ICD-9: 296.2, 296.3, or 311) in any service setting after 189 days without such a claim or an antidepressant fill.
|Estimate of PPV for new onset depression by determining proportion of cases with depression diagnosis in medical record during 180 days prior to new index claim for depression.
|PPV= 48.6% (53 of 109) (New onset depression)
|Rawson et al., 1997[15]
|Randomly selected inpatients with a first listed discharge diagnosis of depression (311) in administrative files, Saskatchewan, 1986
|A diagnosis of depression (311) or a depression-related disorder (ICD-9: 296.1, 296.4, 296.6, 300.4, 309, 311) in the medical record discharge note.
|First listed inpatient discharge diagnosis of depression (311) in administrative files.
|Proportion with first listed discharge diagnosis of depression with ICD-9 311 (PPV1) or depression-related diagnosis (ICD-9: 296.1, 296.4, 296.6, 300.4, 309, 311) in medical record discharge note.
|PPV1= 58.3% (91 of 156) PPV2= 93.6% (146 of 156)
|Smith et al., 2009[11]
|Adult (19–64 years) work disabled Medicaid beneficiaries with depression claims who responded to an employment and disability survey, 2003 or 2005
|Self-rated depressed mood item.
|≥1 Medicaid claims for ICD-9: 296.2, 296.3, or 311 during 12 months prior to survey
|Proportion of beneficiaries with depression claims who report depressed mood (PPV1). Also the corresponding proportion among subgroup with adequately treated depression (ATHF score of 3 or 4) (PPV2).
|PPV1= 87.9% (175 of 199) PPV2= 91.1% (153 of 168)
|Solberg et al., 2006[9]
|Adults (>19 years) from a large private health plan (N=135,842). 5 random samples (N=20) meeting different algorithms for depression, 2000.
|Medical record diagnosis of depression.
|D1. Prevalent depression: ≥2 outpatient or ≥1 inpatient ICD-9 296.2, 296.3, 300.4, 311 in 12 months D2. Antidepressant (AD) treatment (A and B and C): A. 6-months no AD prior to new AD fill B. ≥1 depression code 3 months before or after AD. C. ≥1 more depression code or AD fill in 1.5 years before or after new AD
|Proportion of selected plan members with D1 claims-based algorithm found to have depression diagnosis in medical record (PPV1) and proportion with D2 algorithm found in medical record to have started a new antidepressant treatment episode for depression (PPV2)
|PPV1= 98.8% (79 of 80) PPV2= 65.0% (13 of 20) and 90.0% (18 of 20)
|Solberg et al., 2003[13]
|Adult (≥18 years) outpatients (n=274) from 9 staff model primary care clinics in a metropolitan area with depression code, no antidepressant prescription 6 months, no diagnosis bipolar, schizophrenia, or alcoholism past year, 1998-1999
|2. Self-reported current depression (PPV2) 3. Reported told at index visit has depression (PPV3) 4. Chart audit depression diagnosis or treatment (PPV4)
|ICD-9 311 (only code available for depression) code, no other 311 codes in previous 6 months, no AP fills in previous 6 months.
|Proportion of patients meeting administrative code definition of depression who met each of the four outcomes (CES-D score, self-reported current depression, told by health care professional at visit had depression, and chart audit with depression diagnosis or treatment at index visit.
|PPV2=71.5% (196 of 274) PPV3=54.6% (149 of 274) PPV4=94.9% (260 of 274)
|Spettell, et al, 2003[8]
|Primary care physician panel members (≥12 years) from a large MCO (n=892,786) selected for meeting algorithm 1 or 2 and members matched by age, gender, and number of comorbid conditions not meeting algorithms, 1997.
|Physician diagnosis of depression in medical record during the 12 month study period.
|Algorithm 1. In 12 months, ≥2: A. First listed ICD-9 296.2, 296.3, 300.4, 311 B. AD fill Algorithm 2. In 12 months, A. above and ≥1 of A or B. Bipolar disorder, depressive psychosis or lithium fills excluded. A or B above during 12 months before study period also excluded.
|Sensitivity (Sens), Specificity (Spec), positive predictive value (PPV), and negative predictive value (NPV) determined for a sample of 465 patients for algorithm 1 and 2 with physician diagnosis of depression in medical record as the criterion standard.
|PPV1= 49.1% (115 of 234) PPV2 = 60.6% (63 of 103)
|Sens1= 95.0% (115 of 121) Sens2= 52.1% (63 of 121)
Depression algorithms and validation statistics
All 11 publications listed in the evidence tables included algorithms with various combinations of four different ICD-9 diagnostic codes to define depression: depression NOS (311), dysthymic disorder (300.4), and major depressive disorder, single episode (296.2) or recurrent (296.3) (Tables 1 and 2). Two studies further permitted adjustment disorder with brief depressive reaction (309.0), adjustment reaction with prolonged depressive reaction (309.1), adjustment reaction with mixed emotional features (309.28), and depressive type psychosis (298.0).[5, 6] For some algorithms in one study,[7] the following codes were also included: alcohol-induced mental disorder (291.89); other specified drug-induced mental disorders (292.89); bipolar affective disorder, depressed (296.5); and bipolar affective disorder, mixed (296.6). Algorithms in three studies also required a claim for a filled antidepressant prescription.[8-10]
Two categories of studies are presented. Table 1 summarizes studies that used standardized scales or structured diagnostic interviews as validation standards. Table 2 presents studies that employed medical record or self-report information as validation standards. Each table includes studies that were population based, allowing for calculation of both positive predictive values (PPVs) and sensitivities and cohort-based studies that permitted calculation of PPV only. Algorithms for individual studies varied with respect to selected codes, treatment setting (outpatient or inpatient), position of code listing (principal vs. secondary), billing health care professional, number of required codes, and timing of the codes. The heterogeneity of the algorithms across the studies constrains strict comparisons. For example, the study that defined depression on the basis of at least two outpatient or one inpatient codes for depression (296.2, 296.3, 300.4, and 311) in a 12-month period likely included a narrower patient population[9] than did the study that required only a single depression claim (296.2, 296.3, and 311).[11]
Validation criteria and method
The studies used three main comparators for validating depression algorithms: structured diagnostic interviews for depressive disorders,[5, 12] self-report items or questionnaires,[6, 7, 11, 13, 14] and depression diagnoses contained in the medical record.[8-10, 13, 15] Some of the self-report validations were based on a single item for depression or depressed mood[11, 13] or whether patients had ever been told by a doctor that they had depression.[7, 13] One study[13] used a 20-item self-report depression scale (Center for Epidemiologic Studies Depression Scale [CES-D]),[16] and two studies[6, 14] used the PHQ-9, which is a brief, 9-item validated screen for major depressive disorder.[17] One of the studies permitted direct comparison of four different validation criteria: a CES-D score of ≥6, self-report depression item, being told by a physician of depression diagnosis, and a medical record diagnosis of depression.[13] This study appears in both Tables 1 and 2 for ease of comparison.
Validation statistics
Four of the 11 studies provided sufficient information to derive a chance-corrected measure of agreement (kappa) between the algorithm and a criterion standard. Landis and Koch suggested the following kappa agreement standards: 0.0–0.20 (slight), 0.21–0.40 (fair), 0.41–0.60 (moderate), and 0.61–0.80 (substantial).[18] In the three studies that used an independent assessment of depression as the criterion standard, agreement was either in the slight[12, 14] or fair[5, 12] range. The only study that permitted calculation of kappa and used a physician diagnosis of depression in the medical record as the criterion standard achieved a moderate level of chance-corrected agreement.[8] However, use of medical record or chart information is not an optimal method for validating depression diagnoses in administrative data given the variability with which diagnostic information is represented in chart notation.[19-21]
The other seven studies did not provide sufficient information to calculate kappa values. In six of these studies,[7, 9-11, 13, 15] the analysis was limited to patients who met criteria for the depression algorithm. These studies only permit assessment of the extent to which patients who meet algorithm criteria also meet the criterion standard (PPV) but do not permit determination of the proportion of patients with the criterion standard who meet algorithm criteria (sensitivity). In four of these six studies,[9, 10, 13, 15] the criterion standard was a medical record diagnosis of depression. PPVs ranged from 48.6%[9] to 98.8%.[9] Because PPVs vary as function of prevalence, the relevance of these PPVs is undermined by the absence of prevalence data. Furthermore, findings based on medical record diagnoses of depression must be interpreted with caution given that chart information may not reference diagnoses used for billing purposes.[19-21]
None of the algorithms achieved a high level of agreement with depression as measured by independent assessment. The highest agreement with clinically diagnosed depression was achieved by an algorithm that required over a 12-month period at least two first-listed ICD-9 codes for 296.2 (major depressive episode, single episode), 296.3 (major depressive episode, recurrent episode), 300.4 (dysthymic disorder), or 311 (depression not elsewhere classified) as well as a filled prescription for an antidepressant medication.[8] In a large population of primary care patients, the chance-corrected agreement of this algorithm was moderate (kappa = 0.464).[18]
Factors influencing algorithm performance
Algorithm construction
Operating characteristics varied as a function of the validation algorithm. These relationships were most readily apparent in studies that tested different algorithms against the same criterion standard within the same patient population. In a study of veterans treated for diabetes mellitus, for example, broadening the algorithm from unipolar depression codes to include bipolar disorder and substance-related mood disorder codes markedly increased the percentage of patients captured by the algorithm from 4.5% to 16.5% but reduced the PPV (0.90 to 0.82). In this study, the criterion standard was patient report of being told by a doctor that the patient had depression.[7]
In one primary care study in which physician medical record diagnosis of depression was the criterion standard, narrowing an algorithm markedly altered the operating characteristics.[8] In the first algorithm, patients were required to have at least two events either of which could be outpatient encounter with a primary diagnosis of depression or pharmacy claims for an antidepressant medication. Thus, patients with antidepressant claims without an outpatient depression diagnosis met algorithm requirements. The second algorithm required one outpatient claim with a primary depression diagnosis and another event which could be either a second outpatient depression diagnosis or an antidepressant claim. Perhaps not surprisingly, the less stringent first algorithm had a lower specificity (65.4% vs. 88.4%) but a much higher sensitivity (95.0% vs. 52.1%) than that of the more stringent second algorithm. The kappa was slightly higher for the first (0.464) than for the second (0.425) algorithm.[8]
The position of the listed depression code may affect algorithm performance. Only one study included algorithms that required the depression code to appear in the principal position.[8] The other studies did not specify position of depression codes. Whether the validity of depression codes varies with code position has not been subjected to systematic study.
Patient–Illness characteristics
The studies varied with respect to patient population, ranging from unselected primary care HMO beneficiaries to populations selected for chronic illness. Clinical differences were evident among the study populations: three studies were limited to patients treated for diabetes mellitus,[6, 7, 14] one focused exclusively on patients with a history of asthma treatment,[5] and one involved only disabled persons.[11] Some evidence suggests that co-occurrence of general medical disorders may compromise the management and perhaps the recognition of depression either because comorbid medical disorders compete for clinical attention[22] or because physicians may attribute signs and symptoms of depression to other medical disorders.[23] For these reasons, the validity of claims-based measures of depression may vary by the general medical status of the patient population.
Level of care
The studies included in this report examined depression outcomes based on billing codes for inpatient treatment,[7, 9, 15] outpatient visits,[7-10, 12, 13] or emergency encounters.[7, 10, 13] None of the studies separately assessed or compared the validation of depression outcomes from different treatment settings, although one study compared validity measures from primary care visit codes with mental health service codes.[7]
Patient age
One study was limited to adolescents,[5] one included children and adults,[15] and one included only patients at least 65 years of age.[12] The remaining eight studies involved non-elderly and elderly adults. The average patient age in these studies was between 50 and 60 years. None of the studies included validation information stratified by patient age. Because PPV depends upon the prevalence of the underlying condition, it is likely that PPV will be lower in children and adolescents than in adults because of the lower treated prevalence of depression in children and adolescents.[24]
Patient gender
Except for two studies of veterans,[7, 10] all of the studies involved a predominance of female patients. None of the studies, however, provided validation data stratified by patient sex. After controlling for measures of severity and impairment, patient sex has not been found to be related to the rate of treatment of major depression.[25]
Payment source
The patient populations included a range of payment sources for medical services. Although some of the studies were limited to patients with Medicaid coverage,[11, 14] others included only patients with private insurance.[5, 6, 9] Two studies were based on patients receiving care that was financed and provided by the Veterans Health Administration.[7, 10] The effects of differences in payment source and associated billing systems on validity of depression codes remain unknown. One study of veterans care indicated that supplementing Veterans Health Administration data with Medicare data enhanced the rate of depression detection[7] (Table 2).
Period of data collection
The 11 reviewed studies were published between 1997 and 2010. The earliest data were based on care delivered in 1986,[15] and the most recent data were derived from 2006,[14] although 2 studies did not specify the dates of service delivery.[6, 12] It is likely that increases in rates of antidepressant prescribing[26] over time may influence the performance of algorithms including antidepressant prescriptions as a criterion, rendering it difficult to compare studies conducted at different periods. Although time effects were not examined specifically in this study, the influence of improvements in depression detection on algorithm performance over time remains an important question for further research.
Excluded populations and diagnoses
Five studies focused exclusively on populations with specific conditions including diabetes,[6, 7, 14] asthma,[5] and disability.[11] Of the other six studies, two were limited to patients who had received inpatient treatment,[12, 15] and one was limited to veterans and focused on new onsets of depression.[10] Only one of the studies was based on a national population.[7] The other studies were derived from a Canadian province,[15] two acute care hospitals,[12] three Veterans Health Administration medical centers,[10] large managed care organizations,[8, 14] a private health plan or health maintenance organization,[5, 6, 9] or a group of nine primary care clinics.[13] The composition of the study samples included herein is an important variable in evaluating the utility of algorithms to detect depression in administrative data. Population-based studies that are likely to include both individuals with and without depression allow for assessment of algorithm sensitivity in identifying depression and in providing a measure of precision (PPV). Cohort-based studies, especially those that oversample for individuals who are likely to have depression, only allow for estimation of precision and do not provide information regarding algorithm sensitivity. It is possible that cohort-based studies designed to measure PPV may utilize stricter algorithms, leading to a loss of sensitivity. The magnitude of reduction in sensitivity is unable to be determined from cohort-based data. In addition, the interpretive value of PPV statistics is dependent on the degree to which the prevalence of depression in the sample matches the epidemiological prevalence of depression.
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When their performance was measured in terms of agreement with independent assessment of depression, most algorithms produced only slight or fair levels of agreement with the criterion standard. Performance improved when a physician diagnosis of depression in the medical record was used as the criterion standard. However, physician diagnoses and measures based on administrative data do not capture individuals whose depression has not come to medical attention. Furthermore, using medical records can be problematic for ascertaining whether administrative data can accurately identify individuals with depression given potential variability in the types of information recorded in patient charts.[19-21] For depression cases identified algorithmically, PPV was somewhat higher, ranging from 48.6% to 98.8%. However, the overall performance of algorithms to detect depression in administrative data has shortcomings, suggesting that in view of current limitations in the clinical recognition of depression in primary care, it is unlikely that an algorithm derived from administrative data will be developed that has generally acceptable validity for identifying depression as an outcome. For this reason, it is suggested that when possible, research should focus on clinical practices that systematically screen for depression while recognizing that routine screening for depression in adults and youth, although consistent with recommendations from the US Preventive Services Task Force,[27, 28] may not be conducted in all service settings.
The goal of identifying depression from administrative data is constrained by incomplete clinical detection. In the community, just over one half of adults with major depression receive treatment for their symptoms during the course of 1 year.[25, 29] In addition, primary care physicians recognize as depressed only about half of patients with depression who present for medical treatment.[30] The detection rate may be even lower among patients with medical morbidity (30%)[23] and veterans (40%).[31] Deficiencies in the clinical diagnosis of depression, especially varying identification rates in different clinical subgroups, impose a ceiling on the performance of efforts to detect depression using administrative data. One countervailing consideration is that clinically detected or treated depression may be more severe than undetected or untreated depression.[25, 32] Screening initiatives[33] and other efforts to improve the detection and management of depression in primary care practice[34] may have an incidental salutary effect on the validity of electronic-health-record-based detection of depression.
Beyond problems with clinical detection, psychosocial considerations may further limit the accuracy of administrative data for identifying depression. Although attributions regarding the causes of depression are changing,[35] concern about protecting patient confidentiality may lead some physicians to substitute non-mental disorder diagnoses on claims and patient encounter forms.[36] Underreporting of depression may occur in a conscious effort by the clinician to reduce social stigma that might otherwise have adverse occupational or legal consequences for the patient.[37, 38]
Constraints on clinical diagnosis may help to explain the range of sensitivities in the reported studies. When self-report patient assessments that capture clinically undetected depression serve as the criterion standard, sensitivities are low, ranging from 12.5%[15] to 51.1%.[14] When medical record diagnoses are treated as the criterion standard, the sensitivity of algorithms based on administrative data reaches as high as 95.0%.[8] These differences are also reflected in the kappa values that measure agreement between the algorithm and a criterion standard.
Studies with independent assessments of depression[5-7, 12, 13] rather than medical record diagnoses[8-10, 15] provide more credible evidence of algorithm validity. In this regard, the most rigorous studies involve structured diagnostic assessments[5, 12] followed by those that use a depression screening instrument[14] as the criterion standard. Unfortunately, low chance-corrected agreement of these studies precludes the algorithms in these studies from being recommended for case identification.
One strategy for broadening algorithms and capturing more patients with depression is to include pharmacy records indicating an antidepressant prescription fill.[6, 8-10] Although this strategy tends to increase sensitivity by capturing more patients with depression, it comes at the expense of false positive cases that diminish PPV.[6, 8, 9] These trade-offs arise from the large proportion of antidepressant prescriptions that are for psychiatric and general medical conditions other than depression. In one national study, only 27% of individuals treated with antidepressants reported receiving them for depression.[26]
Positive predictive value depends upon the prevalence of the underlying condition. Many of the studies were performed in highly enriched samples with base prevalence rates of depression that greatly exceed primary care populations. Without careful attention to the prevalence of depression in the base population, the PPVs may appear deceptively high. Although this may be obvious in samples that are limited only to patients with depression,[8, 13] it also distorts estimates in samples that are enriched by oversampling of patients with depression. In one study, for example, the base prevalence of depression in a sample selected for treatment of a mental disorder (28.5%)[14] yielded a PPV of 66.4%. In another study that involved matching patients without depression to patients with depression, the base prevalence of depression from the resulting study sample was 26.0% and the PPV was 49.1% to 60.6% depending upon the algorithm.[8] Substantially lower PPVs would be expected in general populations of primary care patients. The prevalence of major depression occurs in only 5%–10% of primary care patients and approximately 10%–14% of medical inpatients.[39]
No algorithm achieved a high level of concordance with independent assessments of depression. Most routine electronic billing data do not currently include sufficient information to identify depression in a reasonably reliable manner. Electronic health records do provide sufficient information to identify adult primary care patients who have been diagnosed with depression with a moderate level of agreement. The algorithm with the strongest psychometric properties required at least two first-listed depression codes (296.2, 296.3, 300.4, and 311) over the course of 12 months as well as an antidepressant prescription claim (kappa: 0.464).[8] However, this algorithm utilized medical record diagnosis of depression as a validation standard and therefore cannot be recommended for identifying clinically diagnosed depression on the basis of administrative data.
Given that depression is an established side-effect of several medications,[40, 41] a well-validated algorithm to identify depression in electronic health data would be valuable for postmarketing evaluation of drug safety. To improve detection of depression in electronic health records, recommendations for future research efforts include the following:
- Replicating the evaluation of the most promising depression algorithm[8] for identifying clinically diagnosed depression in a fee-for-service or other primary care setting using standardized scales or structured diagnostic interviews as the validation standard is encouraged.
- Future research assessing promising algorithms should be conducted in general medical or specialty mental health settings that routinely screen for depression. It should be noted that even within specialty mental health settings, correlations are modest between clinical diagnoses and structured diagnostic interviews.[42]
- Improvement in the clinical recognition of depression through implementation of routine depression screening is an important variable that can affect algorithm performance. Future research should specifically examine algorithm performance over time as depression screening becomes more thoroughly implemented in youth and primary care populations.
- Because of increasing concern over depression-related adverse events in youth[43, 44] and the paucity of information that is currently available for this age group,[5] priority should be given to developing algorithms to identify depression in children and adolescents.
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Incomplete recognition of depression in routine clinical practice constrains the performance of electronic health information to identify depression. Unless substantial progress is made in the clinical detection of depression, algorithms based on administrative depression codes are unlikely to achieve acceptable sensitivity in identifying depression as measured by independent assessment. Depression estimates are partly a reflection of the base rates of depression in any given sample; therefore, depression rates may be elevated in samples with a high prevalence of mental disorders (e.g., Medicaid samples) and underestimated in samples with a comparatively low prevalence of mental disorders (e.g., general primary care samples). At the same time, administrative depression codes have been demonstrated to have reasonable concordance with medical record diagnoses of depression. In several contexts, most adults who receive administrative codes for depression have notations of depression in their medical records. Much less is known, however, about the sensitivity of administrative depression codes for identifying depression in the medical record. However, given the variability of information contained in medical records,[19-21] these sources are not considered an optimal means of validating diagnoses in administrative data. Given that antidepressants are prescribed for a wide variety of psychiatric disorders and some general medical conditions, inclusion of prescription claims for antidepressant medications may or may not improve the PPV of algorithms to identify depression. The current value of administrative depression codes appears to be limited to identification of selected cases with a reasonable probability of having clinically recognized depression.
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The authors declare no conflict of interest.
- None of the algorithms evaluated achieved a high level of agreement with depression as measured by independent assessment.
- Detection of depression in administrative records is influenced by the base prevalence of depression in the population of interest and is constrained by incomplete clinical detection of the disorder.
- The algorithms with the strongest psychometric properties employed the following: encounter depression codes (296.2, 296.3, 298.0, 300.4, 309.0, 309.1, 309.28, or 311) validated against the PHQ-9 (sensitivity = 51.1%, PPV = 66.4%) or an antidepressant claim within 12 months after an emergent medical hospital admission validated against a structured diagnostic interview (sensitivity = 52.6%, PPV = 54.5%).
- Use of antidepressant claims to identify individuals with depression is problematic given the widespread use of antidepressants for purpose unrelated to depressive disorders.
- The strongest algorithm performance was found when medical record notation of depression in patient charts was used as the criterion standard. However, use of medical record notation information is problematic due to the variability with which depression is referenced in these documents.
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This work was supported by the Food and Drug Administration through the Department of Health and Human Services Contract Number HHSF223200910006I. The views expressed in this document do not necessarily reflect the official policies of the Department of Health and Human Services, nor does mention of trade names, commercial practices, or organizations imply endorsement by the US government.
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- 1Epidemiological context of signalling. Drug Saf 2007; 30(7): 611–613..
- 2World Health Organization. The Global Burden of Disease: 2004 Update. 2004. Available at: http://www.who.int/healthinfo/global_burden_disease/2004_report_update/en/index.html. [1/16/2011].
- 3The Observational Medical Outcomes Partnership (OMOP). Health Outcomes of Interest. Available at: http://omop.fnih.org/HOI. [6/4/2010].
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- 5Quality of mental health care for youth with asthma and comorbid anxiety and depression. Med Care 2006; 44: 1064–1072. DOI: 10.1097/01.mlr.0000237421.17555.8f, , , et al.
- 6Quality of depression care in a population-based sample of patients with diabetes and major depression. Med Care 2004; 42: 1222–1229. DOI: 10.1097/00005650-200412000-00009, , , et al.
- 7Using administrative data to identify mental illness: What approach is best? Am J Med Quality 2010; 25(1): 42–50. DOI: 10.1177/10628606093446347, , , et al.
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- 9Are claims data accurate enough to identify patients for performance measures or quality improvement? The case of diabetes, heart disease, and depression. Am J Med Qual 2006; 21: 238–245. DOI: 10.1177/1062860606288243, , , et al.
- 10How well do automated performance measures assess guideline adherence for new-onset depression in the Veterans Health Administration? Joint Comm J Quality & Safety 2003; 9: 479–489..
- 11Antidepressant adequacy and work status among Medicaid enrollees with disabilities: A restriction-based, propensity score-adjusted analysis. Community Ment Health J 2009; 45: 333–340., , , et al.
- 12Recognition of depression in older medical inpatients discharged to ambulatory care settings: A longitudinal study. Gen Hosp Psychiatry 2008; 30: 245–251. DOI: 10.1016/j.genhosppsych.2008.01.006, , , et al.
- 13When depression is the diagnosis, what happens to patients and are they satisfied? Am J Manag Care 2003; 9: 131–140., , , et al.
- 14Assessing the prevalence of depression among individuals with diabetes in a Medicaid managed-care program. Int J Psychiatry Med 2008; 38: 13–29., , , et al.
- 15Reliability of the recording of schizophrenia and depressive disorder in the Saskatchewan health care datafiles. Soc Psychiatry Psychiatr Epidemiol 1997; 32: 191–199. Reference ID: 10219., , .
- 16The CES-D scale: A self report depression scale for research in the general population. Applied Psychological Measurement 1977; 1: 385–401. DOI: 10.1007/BF00788238.
- 17The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 2001; 16: 606–613. DOI: 10.1046/j.1525-1497.2001.016009606.x, , .
- 18The measurement of observer agreement for categorical data. Biometrics 1977; 33: 159–174. DOI: 10.2307/2529310, .
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- 20Case finding for depression among medical outpatients in the Veterans Health Administration. Med Care 2006; 44: 175–181. DOI: 10.1097/01.mlr.0000196962.97345.21, , .
- 21Recognition of mental distress and diagnosis of mental disorder in primary care. JAMA 1985; 253: 1903–1907. DOI: 10.1001/jama.253.13.1903.
- 22The role of competing demands in the treatment provided primary care patients with major depression. Arch Fam Med 2000; 9: 150–154. DOI: 10.1001/archifami.9.2.150, , , et al.
- 23Why do general practitioners recognize major depression in one woman patient yet miss it in another? Br J Gen Practice 1993; 43(373): 327–30., , .
- 24National trends in the outpatient treatment of depression. JAMA 2002; 287: 203–209. DOI: 10.1001/jama.287.2.203, , , et al.
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- 26National patterns in antidepressant medication treatment. Arch Gen Psychiatry 2009; 66: 848–856. DOI: 10.1001/archgenpsychiatry.2009.81, .
- 27Screening for Depression in Adults. December 2009. U.S. Preventive Services Task Force. http://www.uspreventiveservicestaskforce.org/uspstf/uspsaddepr.htm
- 28Screening for child and adolescent depression in primary care settings: A systematic evidence review for the US Preventive Services Task Force. Pediatrics 2009; 123(4): e716–e735. DOI: 10.1542/peds.2008-2415, , , et al.
- 29Epidemiology of major depressive disorder: Results from the National Epidemiologic Survey on Alcoholism and Related Conditions. Arch Gen Psychiatry 2005; 62: 1097–1106. DOI: 10.1001/archpsyc.62.10.1097, , , et al.
- 30Detection of depressive disorder for patients receiving prepaid or fee-for-service care: results from the Medical Outcomes Study. JAMA 1989; 262(23): 3298–302. DOI: 10.1001/jama.262.23.3298., , , et al.
- 31Depression diagnosis and antidepressant treatment among depressed VA primary care patients. Adm Policy Ment Health & Ment Health Serv Res 2006; 33: 331–341. DOI: 10.1007/s10488-006-0043-5., , , et al.
- 32Targeting quality improvement activities for depression: implications of using administrative data. J Fam Practice 2000; 49(8): 721–8., , , et al.
- 33The cost-utility of screening for depression in primary care. Ann Intern Med 2001; 134: 345–360., , , et al.
- 34Impact of disseminating quality improvement programs for depression in managed primary care: a randomized controlled trial. JAMA 2000; 12(283): 212–220. DOI: 10.1001/jama.283.2.212., , , et al.
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- 37Psychological distress and help seeking in rural America. Am J Commun Psychology 1997; 25(4): 449–70. DOI: 10.1023/A:1024655521619., , , et al.
- 38The National Depressive and Manic-Depressive Association consensus statement on the undertreatment of depression. JAMA 1997; 277(4): 333–40. DOI: 10.1001/jama.277.4.333., , , et al.
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- 44Risk of suicidality in clinical trials of antidepressants in adults: analysis of proprietary data submitted to US Food and Drug Administration BMJ 2009; 339: b2880. DOI: 10.1136/bmj.b2880., , , et al.


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Join Park Interpreter Beckie to discover some of the many animal tracks you can see here at White Oak Lake State Park. Then join in the fun of making your very own track to take home with you.
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Meditation has not only spiritual benefit but worldly benefit, and can be a means for healing and finding creative solutions to difficult problems.Meditation is one of the most important aspects of a successful Islamic lifestyle. When we consciously adopt Islam for ourselves, we do so through recognition and cognizance of the Oneness of God. We contemplate and recognize that Allah is worthy of worship and that nothing else is. We recognize Truth in His words and in the guides He sent to us for our benefit. None of this is possible without contemplation, reflection, concentration, observation, and presence of mind.
The Prophet (peace be upon him and his progeny) was well-known for his meditation practice. People often related that he would go to the cave in Mount Hira for meditation, contemplation, and prayer. It was during this practice that he first received Qur'anic revelation. Thus, meditation opened the door of revelation.
We are very busy people, and our lives are filled with distractions and stressors. Without meditation, we can be carried along by various influences without ever contemplating anything. That is a very dangerous way to live, because then we can easily lose our way in life, going wherever the wind blows us rather than directing our life course toward Allah.
It seems that children and adults alike suffer increasingly from a constant crisis of inattention, lack of focus, inability to concentrate, and inability to maintain progress toward goals. Students claim teachers aren't explaining things well enough, when in reality the students are not engaging their minds enough during the lessons. Worshippers claim their prayers aren't benefitting them enough, when in reality the worshippers lack presence of heart and mind in their worship – they are merely going through the motions without truly being engaged in worship.
Meditation in Islam can be described as the development of the presence of body, heart, and mind in worship and religious contemplation. It is essential to spiritual development and acceptance of and benefit from prayers. Without meditation, Jihad Akbar (struggle against the self's temptations to make wrong choices) cannot truly take place except in a most haphazard manner.
During prayer (Salat and Du'a), a Muslim is supposed to concentrate and meditate on God through reciting Qur'an, Dhikr (remembering God), and supplication. This meditation during these acts opens and strengthens a connection between God and the human being. That connection helps that person to be guided to Truth and maintain internal peace despite all of life's distractions and challenges. The prayers provide a beginning to the remembrance of God and wakeful meditation and worship throughout the whole day, even while the person is engaged in necessary tasks. Even the sleep of a person who is sincere and well-practiced in Islamic meditation becomes an extension of that meditation.
Meditation has not only spiritual benefit but worldly benefit, and can be a means for healing and finding creative solutions to difficult problems. One form of meditation is called Tafakkur and refers to reflection upon the universe or pondering the creation of Allah. It is a means of intellectual development that awakens and liberates the mind to help it achieve higher levels of growth. Many of the great Islamic scientists were said to engage in a meditative practice of Tafakkur to help guide their intellectual pursuits. Tafakkur is the means by which some people recognize the signs of Allah in the Creation.
There are many styles of meditation that achieve different purposes. All of them can help prepare one for performing Salat or Du'a in a meditative state to achieve better benefit and spiritual connection to God.
Contemplation is a form of meditation. Many people will contemplate by reading a few lines of Qur'an, Du'a, or an Islamic book and reflecting on it, perhaps writing a journal entry about it.
Visualization is another form. Some people will visualize a name of Allah as if hanging in the air, or they may visualize some symbol of a holy personality, focusing their attention on God, feeling love and gratitude toward the Creator. Effective visualization during prayer may be something like a person evoking a feeling as if sitting in the presence of Allah, imagining that He or angels are watching directly.
In a more worldly sense, people have used detailed visualization of upcoming stressful events such as giving speeches, running races, or undergoing medical treatments going ideally in order to ease anxiety and contribute to better outcomes of these events.
Sensating is yet another method of meditation, sometimes intermingled with visualization, that is extremely effective. Sensating often needs to be done before contemplation or prayer to help a person be fully present and engaged in what he is doing. Sensating helps a person to focus, eliminate distractions, and release tension and stress.
Checking In is one of the most basic forms of sensating meditation. This is a developmental practice to help one find focus and presence of mind and help eliminate distracting thoughts, anxiety, and stress. It is done by sitting erect with eyes closed at the edge of a seat, feet on the ground, and focusing on just being aware of every sensation: the way each part of the body feels, searching out tension in any body part and relaxing it, noting thoughts that come and go while not following any of them, being aware of sounds, feeling of clothes against the skin, feeling of the rise and fall of breath, feeling of the eyes in their sockets, etc.
Checking In taken to the next step is meditation in Relaxation Pose. This is done lying down flat on the ground, shoulder blades tucked under. The person carefully lies motionless with eyes closed and senses the entire body, starting from the tips of the toes and slowly moving to the top of the head. For some, visualizing something like golden balls of light moving around the area one is sensing helps the process. When one senses an area, one becomes aware of previously unnoticed tension in the area and then consciously releases that tension, allowing a warmth into that area of the body before moving up to the next location.
Conscious Breathing is another form of sensating meditation. In this practice, a person simply takes a few moments to become conscious of his or her breathing. The person feels the breath and the way it affects the entire body. The person may lay down with eyes closed in Relaxation Pose and place hands on lower belly, solar plexus, chest, forehead, and top of head in turn and feel the movements of these parts of the body with the breath. The person may place two hands in two different places at the same time so that he can sense the movement of air from one place to another. The person feels the pause of breathing between exhalation and inhalation. Then, the person may consciously manipulate his breath to lengthen the pauses, deepen the inhalations, and make the exhalations more complete, but all gently and without strain or force.
Engaging in these sensating meditative practices for a few minutes can help ready a person to perform Salat with increased concentration and meditation, making it a more spiritually rewarding experience. Adopting meditation as a regular practice can help one extend worship to a constant activity rather than a fleeting moment and can help a person achieve power of mind and body and spiritual growth.
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11 Comments
I rocommend anyone that has difficulty focusing on any task to read this article and these different forms of meditation.... I am always extremely busy and have millions of crazy things running through my mind the only thing that helped me before was Yoga but then i would get too relaxed and lay there not doing anything...lol until i read this article now i can finally use these effective forms of meditation to FOCUS on ONE specific thing. It's also great for helping little children focus on there prayers at a young age so by the time they get older they will be familiar with these forms of meditation and focus will come easy for them (Inshaallah)
Asalaam Alaaykum wr wb

I am soooo happy to hear that this article has been beneficial to you! If you want further information related to this topic please feel free to contact me.
Thanks for the reminder on meditation! AlhamdulAllah
pretty interesting info there, i always find it har to concentrate whilst in namaz, and ideas just rush through my head completely taking my attention away, but now im going to take these methods and put them to use. jazakallah for sharing.
Salam,

Thanks for this article! I often feel as though when some people pray (including myself) it's done so with such speed or lack of concentration, that speaking the Arabic words and associating the entire correct meaning to what we are saying must be impossible. However recently I'v made an effort to actually understand every single word that I speak to Allah (swt), and my best part is when we rise from rukku and say ''Allah listens to those who praise him''! ;-)
Salam Brother,
Can you please tell me the exact procedure of meditations during namaz. I know how to offer Sala'...but don't know how to meditate during Namaz.?
I will really appreciate it.
firstname.lastname@example.com
I don't know if this might be along the lines of what you are looking for: http://www.concentrationinprayer.com/

If you mean reciting dhikr in prayer, I am not sure that there are exact prescribed methods in detail - perhaps someone else can explain the Sunnah of the Prophet (saw) in that regard, insha'allah.
i want to do meditation but i have the egoness
I knew spirituality and yoga is a part of islamic practice always and I am happy that we soon realized it....This information is very helpful and important for everyone to realize what we are suppose to do when we say we are performing salat....We should understand that prophet Mohammed (PBU) was a big time meditator and even the prophets earlier to Mohammed (PBU) were mediatiotrs first than they received their prophecy. And the most powerful in this methodology of transcending the physicality on daily basis was Imam ALI....He has been one of the most knowing spiritual leader of all time. We should try and follow his and Prophets spiritual path.
Also no one can decide how it has to be done but we should try and practice any of the above style or take help of some yogic teacher to start as we need a teacher in front for proper guidance to start with. Who teaches does'nt matter what is being taught is Important says Imam Ali.

Thank you.
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Tired of It Already
I have to confess something. We are 48 hours removed from finally having one Republican Presidential candidate and I am already tired of 2016. Heck, I was tired of it before Cruz declared. Somewhat ironic to say given that I make a living on the internet, but I am more and more convinced the internet and, particularly, social media is a bad thing. It fosters | Read More »


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Vintage Carved Oriental Martini Liquor Cabinet Bar
- Sold for: Start Free Trial or Sign In to see what it's worth.
- Item Category: Ethnic, Folk & Native American Art
- Source: eBay
- Sold Date: Dec 20, 2007
- Channel: Auction House
Vintage Carved Oriental Martini Liquor Cabinet BarEIGHT ORNATELY Carved Doors and Panels!! This listing is for a highly ornate and extremely versatile oriental cabinet. It has inserts and pop up shelves and hidden compartments that make it one of the most well-fitted liquor cabinets that I have ever seen......and for those preferring to store other items in the cabinet, the inserts are removable, thus making it just an outstanding carved cabinet!! I purchased the cabinet in an English container sale. I cannot specifically pin point its age, but I will conservatively guess appx. 50 years old. T are a total of EIGHT (8) heavily carved doors or panels that ALL operate separately!! They include the following: · The INSIDE of the cabinet top has a full-length ornately carved scene . This top can be left open if the buyer wishes to display the carving, or the top can be closed when not in use, and the black lacquered surface will show. When the cabinet top is opened, t are two hinged lids. These inside top lids are on hinges that smoothly open and raise the interior (it "pops up") at the same time. You can leave the glasses and bottles in place, and as you shut the lids, the glasses, bottles, and everything else inside is smoothly lowered into the compartment below. When fully opened, the lids are flat on each side, providing additional serving areas. · The carved upper front panel. This panel or door drops down on hinges from the top when opened, and creates a shelf for mixing drinks,etc. · The two lower front doors . These doors open to reveal a large area for bottles, with an insert that has wood shapes cut-out in the top and the entire thing may be pulled out. · The two curved corner panels . These panels open to additional storage area for stem glasses. · The two side panels. These large paneled doors each open to reveal even MORE storage for bottles, glasses, etc. Please note: Alcohol in photos not included!! Measurements: The cabinet measures 38 ½"H x 32" x 16". With the top raised open and the carved panel showing, the height increases to 52". As already mentioned, the cabinet is in good condition for its age, structurally sound and visually appealing with normal signs of age and use, scratches, dings, and other imperfections. These normal signs include scratching and wear on the top as shown in photos; also, t are two small places by the drop down front hinges that have some of the wood chipped off and has been re-touched, but I have tried to show it in the photos....which was difficult with the black lacquer paint. I am sure t are other touch-ups on the black lacquer, but overall, the condition is still better than most...also note the doors close by pushing on them and the latches release when you gently push on them again. The mechanisms are getting old and tfore the doors won't all stay perfectly shut and flush as they did new. This will not be alarming or surprising to those familiar with antique and vintage cabinets, and is pointed out for those new bidders that might not know what to expect from older furniture!! Please keep in mind antique furniture should be purchased for its uniqueness, higher quality material and craftsmanship and antique patina, charm and character. I only offer carefully selected quality pieces, and always provide multiple photos and written information. I encourage you to email me with any questions you might have prior to bidding. SHIPPING: Professional packaging, shipping and insurance on this item will be $135.00. (lower 48 states only). All my antique furniture is professionally packaged for shipment by UPS, resulting in very little shipping damage in the past, but sometimes creating slightly higher shipping costs on my antiques versus other sellers. I believe it is worth the few extra dollars to get your one-of-a-kind antique delivered safely to your door!! Local pick-up in Shreveport ,...


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U.S. Income Inequality Has Gotten Even Worse
The difference in income between the wealthy and the rest of us is much more vast than it is in 25 other developed nations.
I'm a 27-year-old freelance journalist living in South Florida. If I'm not writing, I'm playing video games or at the beach. My favorite spice is oregano, and I thought you should know. I got my bachelor's degree in English and public communication from Florida Atlantic University in 2008.
The difference in income between the wealthy and the rest of us is much more vast than it is in 25 other developed nations.
Spirit Airlines' fee-for-all approach seems to be paying off, despite consumer complaints.
Does the generous way Costco treats its workers affect your decision to shop there?
Most U.S. adults don't do well on a short multiple-choice quiz about basic financial literacy.
Researchers say couples who first meet online are a bit more likely to stay married and have happier marriages. Can that be right?
Apple may soon have an in-store trade-in program for iPhones.
Movie screens as much as 40 percent larger than usual may be coming to a theater near you. Are you willing to pay more for the experience?
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Info Session: International Education Week
Oregon State University
1:30 to 2:30 p.m.
MU Room 206
Oregon State University
Corvallis, OR 97331
Educate our world through the Peace Corps. Education and English-teaching specialists are needed to address global education and training needs at grassroots levels. Help improve a community's education levels, teaching methods, and language competencies, while gaining global skills for your career.
Join us at this education-focused information session to learn about Volunteer experiences, have your questions answered, and gain tips to guide you through the application process.
Learn more about Peace Corps Volunteers' work in education. || Watch videos of education Volunteers in the field.
About the Peace Corps: Read more or watch a video about what it's like to be a Volunteer including what Volunteers do, where they go, and the many benefits of Peace Corps service. Or apply now to begin your life-defining experience.
Where will you be this time next year? Apply by December 1 and you could be serving as a Peace Corps Volunteer in one of 76 countries around the world by Fall 2014. Visit www.peacecorps.gov/apply to complete an application.
Stay Connected: Sign Up for E-Updates || Facebook || Twitter || YouTube || Flickr || Tumblr || LinkedIn
For questions about this event contact Sarah Kassel
If you require a reasonable accommodation when attending a Peace Corps event, please contact the recruiter identified in the "for questions about this event" section of the event listing. Please provide the details of the reasonable accommodation you are requesting.
Last updated Nov 14 2013
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Your body is made up of trillions of cells—but what do you really know about them? Take our lab quiz and determine your CIQ (cell identification quotient).
Dustup Over Lionfish Science Fair Project
July 23, 2014|
A former graduate student says he feels slighted by a failure to attribute his contributions to a line of research regarding the salinity tolerances of an invasive species.


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JUNEAU, Alaska (AP) — The Coast Guard's 17th District is hosting the annual District Buoy Tender Roundup in Juneau.
The week-long gathering is set to begin Monday. It will include vessels homeported in Alaska, Washington state, Oregon and British Columbia.
This year's event brings together the crews of eight U.S. buoy tenders and one Canadian Coast Guard buoy tender for five days of training.
KINY says the roundup will give more than 300 Coast Guard members the opportunity for training engine repair, buoy maintenance, safety equipment maintenance, first aid, personnel management and more.
Information from: KINY-AM, http://www.kinyradio.com


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Alternative Education
Building Rigor, Relevance and Relationships in Alternative Education Classrooms
The Sonoma County Office of Education (SCOE) operates alternative schools for Sonoma County students who are seriously at risk of school and/or societal failure. These schools provide small school settings for referred students who are experiencing difficulties in traditional schools, offer home and independent study alternatives, and deliver daily instruction for incarcerated youth and juvenile wards of the court. In operating these programs, SCOE strives to offer education alternatives that connect students to positive opportunities for learning.
Class of 2015 Graduates
At a May 27 graduation ceremony, SCOE recognized 30 students who earned high school diplomas and one student who completed the General Education Development (GED) Examination. Congratulations to these Class of 2015 graduates.
Veronica Lynne Argentieri
Alejandro Cabrera Avalos
Hector David Carranza Pineda
Vanessa Carreon-Lopez
Najonay Shajeeah Carter
Andrew Corona Espinoza
Jose De Los Santos
Luis Eduardo Cuevas
Kevin Escalera
Brenda Rocio Garay
Antonio C. Gonzalez-Gutierrez
Jerome A. Hatt
Jacob Holmes
Hannah Faith Iversen
Jared Nathanael Iversen
Cynthia Melgoza Cendejas
Ryan William Nichols
Jonathan Ryan O�Rourke
Luis Enrique Ojeda
Brenda Stephanie Perez Perez
Ryan Michael Perrine
Alexandrea Victoria Pittman
Monica Rojas Sedano
Skylar Storm Sachse
Shyzaha Vance Thorpe
Azucena Vargas-Rosales
Michelle Maye Walker
Jason L. White
Jesse Merrick Wildman
GED Certificate
Marco Reyes
Upcoming LCAP Stakeholder Meetings, Spring of 2016
Community/district partners and board members:
March 30 from 3:00-4:30 at Amarosa Academy (3261 Dutton Ave., SR)
Consultation with bargaining units:
April 7 from 1:30 - 3:00 at Amarosa Academy
April 8 from 12:00-2:00 at Amarosa Academy
Programs & Services
Community Schools
The purpose of Community School is to retain students in the education system during periods when they are experiencing problems that put them at serious risk of dropping out. The emphasis of the program is to reestablish students� educational direction. The goal is for students to successfully transition back to a regular school setting or another learning environment that meets their needs. For students who elect to remain in Community School, the program is designed to help them meet their educational and academic goals. Learn more about Community Schools.
Court Schools
Court Schools provide instruction for school-age children and youth residing in court-supervised programs, such as Juvenile Hall and Probation Camp.
Countywide Plan for Expelled Students
In addition to offering alternative school programs for students, the Alternative Education department coordinates the development of the Countywide Plan for Providing Educational Services to All Expelled Students in Sonoma County as required by Education Code Section 48926. The plan is updated every three years.
2015 Countywide Plan for Expelled Students (pdf)
2012 Countywide Plan for Expelled Students (pdf)


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This is my second baby and I am 18 weeks along. I Felt the baby move on Halloween night only because I had spicy food and a TON of candy. Since then, I havent felt anything. I am getting kinda concerned only because i see a lot of first time moms that are feeling their babies move like crazy. I jusy heard the heartbeat 2 weeks ago, but would just like to know that I am not the only BTDT mom that has a mellow baby.
Any BTDT moms that haven't felt baby move yet?
Jessica (38)
Married to Chris (41) and mommy to Madison 6/17/09 and Jackson 4/28/12
Bean and Mike - 2/26/2011
DS (Boogs) - 10/2/2008
DD (Rory) - 5/4/2012
Married to an amazing guy, for 5 years
Well, I am glad that I am not the only one not feeling the baby move yet. My 20wk appt is on Dec.1, but I can't wait till then to make sure everything is ok AND to find out the gender. Im kinda tempted to got to a private ultrasound place.
I'm only 17 but haven't felt it yet. 18-20 is about normal I think.
Kelsey and Jake, Maxwell 6/16/10, Clara 4/30/12, Due 03/09/14
feel little flutter here and there. I'm assuming its the baby, but can't really tell. I have my 20 wk on Dec 6th
My doctor said it could be 20-22 weeks and not to worry about it whatsoever. It's totally different for everyone, also depends on the position of the placenta.
Learn more
Look how far your child has come.
Review your child's growth milestones.
Read about 4 years : Week 2.
Your growing child
Your 4-year-old: Pre-reading
Your 4-year-old: Learning empathy
Your 4-year-old: Understanding numbers
Your 4-year-old: Gaining independence
Your 4-year-old: The name game
Learn more
What's next for your growing child?
Get a glimpse of what's to come.
Read about 4 years 2 months.


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Processing Time - Orders typically ship in 2-5 business days. Transit via UPS Ground can take up to 6 business days. Braided and custom-made products may take 2 to 3 weeks for delivery.
Free Shipping to Contiguous United States - We do not ship to Alaska, Hawaii or the Caribbean Islands at this time.
Oversized items - Orders that ship freight may take up to 2 weeks from shipment date to be delivered. You will be contacted by the trucking company to schedule a delivery appointment.
Shipping to Canada - Orders shipping to Canada will be subject to a 15% shipping surcharge fee. The shipping surcharge does not cover duties, customs, taxes or brokerage fees which may be charged to you by the shipping courier at time of delivery. At this time we are not shipping to Yukon and the Northwest Territories in Canada.
- Style Number: 1341783GLD
- Collection: Bellissima
- Brand: Radici
- Material: 100% Polypropylene
- Weave: Machine Made
- Styles: Contemporary Rugs, Country & Floral
- Origin: Italy
- Returns: Returns Accepted Within 14 Days of Delivery.
The Bellissima collection offers variety of rugs ranging from the classic traditional pattern to the very elegant contemporary designs. These rugs are made very easy to clean and maintain. Made in Italy.
Ordered this rug for my daughter's college apartment. It was perfect! She is very pleased!RECOMMENDED: Yes!
Love your contemporary prints - have three of them now. Wish this latest one was just a little bigger, but pattern is great looking.RECOMMENDED: Yes!
Beautiful rug and great quality. We are very pleased! Shipped quickly too!RECOMMENDED: Yes!
Out of 6 reviews
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Please Note: The images we display have the most accurate color possible. Due to differences in computer monitors, we cannot be responsible for variations in color between the actual product and your screen. Please be advised that in some cases patterns and colors may vary according to size. Lengths and widths may vary from the published dimensions. We do our best to provide you with an accurate measurement, but please be advised that some variation exists and this is not a manufacturing defect.
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The content on this page is provided by a Time Out partner.
Welcome to our Apres Ski Fondue Chalet at Café Select open everyday from 7 pm. In the winter months we serve Fondue & Raclette in our cozy backroom alpine lodge behind our kitchen. We also offer our regular menu items. We generally have two seatings (7pm and 9 pm). Unfortunately due to our current POS system we temporarily can only take cash.
|Venue name:
|Apres Ski Fondue Chalet at Café Select
212 Lafayette St.
New York
|$30 and under
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10 Steps to Pick the Right Doctor
Whether you need a primary care doctor or a specialist, these 10 steps will ensure you find the right doctor for you. View Slideshow
Dr. Monfette's Experience
- Emergency Medicine
Board Certifications
- Emergency Medicine
Procedures Dr. Monfette Performs
Dr. Monfette does not have any procedures listed. If you are Dr. Monfette and would like to add procedures you perform, please update your free profile.
Conditions Dr. Monfette Treats
Dr. Monfette does not have any conditions listed. If you are Dr. Monfette and would like to add conditions you treat, please update your free profile.
Background Check for Dr. Monfette
Malpractice Claims not available
- Healthgrades does not collect malpractice information for Michigan.
- No sanctions history found for the years that Healthgrades collects data.
0 Board Actions
- No board actions found for the years that Healthgrades collects data.
Awards & Recognitions
Education & Training
Medical School
- Wayne State Univ Som
- Graduated in 1998
Residency Hospital
- St John Hospital and Med Center
- Complete in 2001
Languages Spoken by Dr. Monfette & Staff
- English


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Keep an eye out kid .... by adabraticWatch
©2012-2016 adabratic
Oh my goodness that little face is adorable!!
im thinking... Tau's daughter. what do you say? i think she's a little more like Tau than Sultani, but i would welcome your opinion. :3
that would be amazing... Maybe that's Sultani's son she is warning
could be. *muses* i was also thinking maybe he's a kid from the Shard Pride (im thinking Elwa's son), and so wouldnt be welcome. or something. XD
Lol, omg I just realized that I gave her the same beauty mark as her grandmother ...
You're the storytelling genius, hes all yours
I love the little cub 0.0
oh noes! D8 no cubby die! *holds him safe*
Hes all yours its up to you
I do believe the scripts call that 'Foreshadowing'! XD
Wow that is such a good character design for the older one! Is she related to Kiara somehow?
Oh wow, how beautiful ! I love your characters expressions !
...is that a mole?


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Stetson's Naburgs named A-Sun basketball player of the week
Published: Tuesday, February 26, 2013 at 5:27 p.m.
Last Modified: Tuesday, February 26, 2013 at 5:47 p.m.
Stetson's Joel Naburgs' had an eventful 23rd birthday last Friday. The senior scored a career-high 27 points and became the Hatters' all-time leader in made 3-pointers.
Because of that performance Naburgs was named the Atlantic Sun Conference men's basketball player of the week.
Naburgs hit six 3-pointers in the 80-71 victory over A-Sun second-place team Florida Gulf Coast. His fourth trey of the game put him in first place on the Hatters' career list for made 3-pointers.
Heading into Thursday night's home game against Kennesaw State, Naburgs has hit 173 3-pointers in his career, three more than former record-holder Kerry Blackshear (1992-96).
All rights reserved. This copyrighted material may not be re-published without permission. Links are encouraged.


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Is it possible to change color of the button?
Is it possible to change color of the button?
I am using WordPress 3.5.1 and the settings do not appear in the catalog settings in Woocommerce. Which part of the code do I edit in order to set the amount of days that indicates a "new" product? Thanks
Why are you using 3.5.1? You will cry someday because someone hacked your website. Make the updates & use the latest version of wordpress. The people that make plugins, do them for the last version of WP, not for old & unsecured versions.
This topic has been closed to new replies.


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12 OYS: Teacher admits hitting 6th grader arrested on simple assault
Updated: 11/21/2014 - A Richmond County teacher is behind bars, accused of assaulting a middle school student. News 12 was in court when a judge issued an arrest warrant for 62-year-old Sam Arazie. The judge did allow Arazie to surrender to deputies with a charge of simple assault. For the first time since 12 On Your Side started investigating the alleged attack, we are hearing the teacher's side.


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Articles citing this article (data provided by Crossref)
- Leda Blackwood, Andrew G. Livingstone, Colin Wayne Leach (2013)
Regarding Societal Change
Journal of Social and Political Psychology, 1(1), p. 105(ff.)
doi: 10.5964/jspp.v1i1.282


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Orange Cookie TeaOCT
Product Details
Our delicious Orange Cookie Tea combines black tea, apple pieces, cinnamon bits, coriander, flavoring, cardamom pods, orange slices, pink peppercorns, and cloves. Use one tsp. per cup and steep for 3-5 minutes in freshly boiled water.
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Orange Cookie TeaOCT
To order multiple bags of the same tea: Select the number of ounces for the first bag and click "Add To Cart", then select the amount for the second bag and click "Add To Cart" again. Repeat for as many bags as needed. Volume pricing is based on the size of each bag.
|Ounces Per Bag:
|Price Per Ounce:
|2 3
|$2.70 (7% Off)
|4 7
|$2.52 (13% Off)
|8 15
|$2.35 (19% Off)
|16 31
|$2.20 (24% Off)
|32 or more
|$2.06 (29% Off)


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Editors' Note: Clicking on the Download Now (Visit Site) button above will open a connection to a third-party site. Download.com cannot completely ensure the security of the software hosted on third-party sites.
SDE for Visual Studio .Net (CE)Free
Quick Specs
Total Downloads:458
Date Added:Jun. 20, 2008
File Size:Not available
Downloads Last Week:1
From Visual Paradigm International: SDE for Visual Studio .Net is a UML CASE tool totally integrated with Microsoft Visual Studio. It supports full software development lifecycle - analysis, design, implementation, testing and maintenance. It combines the power of UML modeling facilities and Microsoft Visual Studio .Net. It helps you build quality applications faster, better and cheaper. You can draw UML diagrams in Visual Studio .Net, generate code (J#, C#, C++ and Visual Basic), and reverse engineering code to class diagrams.
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- 18 & over
- Two drink minimum
- Special Event
Los Angeles, CA
Comedy Central Certified
Share with your friends:
MO BETTA MONDAY (Special Event)
Purchase Tickets
Monday, July 22, 2013 8:00 PM
Hollywood Improv, Los Angeles, CA
Show Details
- Ticket Price: $0.00
- Door Time: 7:30 PM
- Show Type: Stand Up
- Showroom: Main Room
18 & over
Two drink minimum
Special Event
For over a decade, SPIKE-DID-IT-EVENTS has proudly presented MO BETTA' MONDAYS ALL-STAR COMEDY JAM, featuring the hottest Urban comedians from all over the country. Comics regularly featured on Def Comedy Jam, BET, HBO, Showtime, and Comedy Central round out an always awesome line-up. Such acts as Dave Chappelle,CoreyHolcomb, Kevin Hart, Mike Epps,and Lunelle have come out to perform.
Upcoming Shows
- Tue 5.31.16 - 8:00 PM At The Lab: Welcome Home to Eddie Pepitone with Eddie Pepitone, Steve Agee, April Richardson & Megan Koester! Buy Tickets
- Tue 5.31.16 - 8:00 PM Tonight at the Improv with John Mulaney, Iliza Shlesinger, Tom Segura, Gene Pompa, Rachel Feinstein, Mike Quu & more! Buy Tickets
- Tue 5.31.16 - 10:00 PM At The Lab: Crabapples with Bobcat Goldthwait, Caitlin Gill, Karen Kilgariff, Dave Waite, Ryan Singer, & Mike Drucker Buy Tickets
- Tue 5.31.16 - 10:00 PM JayDavisComedy Presents at The Improv with Dane Cook, David Koechner, Ron G, Jeff Garcia, Gene Pompa, & Jay Davis Buy Tickets
- Wed 6.1.16 - 8:00 PM At The Lab: Soulful Collective with Keith Seoul, Jonnae Thompson, Thai Rivera, Punkie Johnson, Tahir Moore, Jerron Horton, The Soulful Sounds, & more Buy Tickets
- Wed 6.1.16 - 8:00 PM Tonight at the Improv with John Mulaney, Ron Funches, Aida Rodriguez, Hampton Yount & more! Buy Tickets
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"The definition of being a modern person is to examine yourself, to reflect on yourself and to be a self-knowledgeable person."
"It's not like one [violent] thing happens and you say, 'Wow! That was just so terrible,' and it will never happen again. You know it will happen again- either where you're caught up in a system, whether a family or war...or- if you're in a situation as I happen to be now, not involved in a violent cycle, witnessing violent situations erupt. I'm more in a witness position now. Not a direct witness. A kind of removed witness."
- Laylah Ali


text: I was initially aiming for this to be a super quick FLAPTHULHU-scope game, but it's now more along the lines of CHILLAXIAN. Going to try to wrap it up this weekend, but if it's not ready I'll probably finish it up the weekend after that, because I have to get back to more Death Road to Canada... lots to do there yet. This is just a "break" I need them every so often, heh.


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NOTE: State Sen. Cliff Hite is holding a series of events around Ohio to discuss the topic of extracurricular activities and the fees being charged by schools for those activities. He intends to introduce a bill soon that could call for the banning of so-called pay-to-play fees. Chad Aldis spoke at one such event today. These are his written remarks.
My name is Chad Aldis. I am the vice president for Ohio policy and advocacy at the Thomas B. Fordham Institute. Thank you for the opportunity to provide public comment today on pay-to-play fees.
Before I begin, I would like to commend Senator Hite for his focus on these issues. Policies like pay-to-play may aid schools with their immediate budgetary concerns, but they also put a strain on families. While many of the proposals that you will hear about today are a good start, I encourage you to think broader and perhaps even outside the box.
For years, the Fordham Institute has focused on education as a means of social mobility. Schools have long been championed as places where we can level the playing field for low-income children. Unfortunately, that leveling doesn't happen as often as it should or even...
The Achilles' heel of the West, I read not long ago, is that many people struggle to find spiritual meaning in our secular, affluent society. How can we compete with the messianic messages streaming from the Islamic State and other purveyors of dystopian religious fundamentalism?
It made me reflect on my own life. How do I find meaning? Largely from my role as a father, a role I cherish and for which I feel deep gratitude. But ever since I lost faith in the Roman Catholic Church of my upbringing—not long after I nearly succumbed to cancer at age eighteen—much of my life's meaning has come from my view of myself as an education reformer.
I suspect that I am not alone. We are drawn as humans to heroic quests, and those of us in education reform like to believe that we are engaged in one. We're not just trying to improve the institution known as the American school; we see ourselves as literally saving lives, rescuing the American Dream, writing the next chapter of the civil rights movement.
When people speak of Arne Duncan with tears in their eyes—explaining earnestly that he has always put kids first—it...
John Chubb was not only a fine scholar, tireless education reformer, and creative innovator. He was also my friend and colleague for more than two decades. I first came upon him in 1990, when he (then at Brookings) and Terry Moe published their blockbuster school choice book, Politics, Markets and America's Schools. Two years later, we found ourselves working together at the outset of Chris Whittle's ambitious Edison Project. We both also served as founding members of the Hoover Institution's Koret Task Force on K–12 Education, which led to much collaboration over more than fifteen years, as well as more terrific books, articles, and reports written or edited by John. (A good collection can be found here.)
While he was still with Edison (where he lasted a lot longer than I did), we had many dealings over that firm's stewardship of a pair of charter schools that Fordham authorized in Dayton. He and I also found ourselves together at umpteen conferences, workshops, and board meetings. Quite recently, John surprised many of us by taking the helm of the National Association of Independent Schools. He was off to a terrific start there, fully grasping the challenges of that corner of...


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- El SalvadorFoodFunding via PADECOMSM
Flor De MariaEl SalvadorFoodFunding via PADECOMSM
Ana MargaritaEl SalvadorFoodFunding via Apoyo Integral
Flor Alejandrina
Update on Flor AlejandrinaFlor is asking for a new loan to increase business because her objective is to make periodic investments that will allow her to keep her business well-stocked buying basic grains, beans, rice, oil, toilet paper, pasta, personal hygiene products, among others that are very important.
She has experience with loans; she's had several with the institution. She's a client with good payment behavior and with a strong drive for self-improvement. She feels that previous loans have allowed her to increase business, to help her family and to continue making progress.
Ella tiene experiencia con créditos, permitiéndole manejar varios con la institución, es un cliente con buena moral de pago y con muchas ganas de superación, ella considera que los préstamos anteriores le han permitido incrementar el negocio, ayudar a su familia y permanecer prosperando.
Previous Loan DetailsFlor is single and lives with her mother. Her business is selling basic household products and she has been in this business for ten years. She works from 6.00am to 7.00pm. Up to now, she hasn't had any difficulties with her sales. Flor is requesting a loan to buy rice, beans, oil, snacks, ... More from Flor Alejandrina's previous loan »
Additional Information
Concurrent and Successive Loans
Our Field Partners often work with borrowers over a series of loans as the borrowers build credit, take out bigger loans, and expand their businesses. In order to make it easier for our Field Partners to post loans for borrowers who have been listed on Kiva before, we allow them to post successive and concurrent loans for their Kiva borrowers. This means that our Field Partners are able to post a borrower's second, third, etc., loan on Kiva without having to re-enter all of the borrower's information.
This borrower has been listed on Kiva before, so you'll see an updated loan description, as well as excerpts of the original descriptions from earlier loans. Most borrowers take out loans consecutively, meaning that they receive a second loan after having repaid the first. However, sometimes our Field Partners give out concurrent loans, allowing borrowers to take out one primary loan and a secondary "add-on" loan along with it. These "add-on" loans are typically smaller than the borrower's primary loan and serve a different purpose. Because Field Partners can now post loans as successive and concurrent loans, you will be able to track borrower progress over time and see the various ways a borrower is working with our Field Partners through funds from Kiva's lenders.
About El Salvador
555View loans »
US Dollars
Success!! The loan was 100% repaid
- Repayment Term
- 14 months (Additional Information)
- Repayment Schedule
- Monthly
- Pre-Disbursed:
- Apr 26, 2012
- Listed
- May 28, 2012
- Currency Exchange Loss:
- Ended:
- May 17, 2013


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Bali Hotels
Bali is just one of the many small islands of Indonesia, but without a doubt, it is one of the most famous islands of Indonesia. Bali is frequently referred to as "The Paradise Island" because of its reputation in the world as a tropical paradise of untold beautiful nature, idyllic mood and never ending fascination. Bali is located just off the eastern tip of Java, from which it is separated by the narrow Bali Straits. Immediately to its east is the island of Lombok ...
Alam Puri Art Museum & Resort
Located in the center of Bali, south of Ubud, this villas is ideal for those who want to explore more of the island than US$ 50 - US$ 200, Complex of Villas, Ubud
The Villas
The Villas Bali is located in Seminyak, one of Bali's trendiest areas. Within walking distance, you will find many chi US$ 200 - US$ 400, Boutique Hotels, Seminyak
Hotel Santika Premiere Beach Resort Bali
Embracing an oceanfront parcel of tropical landscape, Hotel Santika Premiere Beach Resort Bali is a restful sanctuary fo US$ 50 - US$ 200, Beach Resorts, Kuta


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In most instances of hay-fever and asthma in children, there is absence of or merely slight impairment of general health and nutrition, even when the asthmatic state is of almost daily occurrence and of months' or years' duration. In other children there exists, in addition to the physical discomfort, what is apparently a definite clinical state due to the toxemia of constant antigen absorption, the condition being made obvious by the exclusion of other toxic influences, by appropriate laboratory measures, and by the relief of the hay-fever and asthma.
The etiologic factor in these cases has been primarily pollen, with additional feather sensitiveness. Foods have not been a factor in a single instance.
The history of these cases consists of frequent almost nonintermitting so-called colds dating from early infancy, which actually represent the mild type of hay-fever so frequently seen in asthmatic children. Typical severe seasonal hay-fever is unusual. Frequent
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