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Quality management in health care 19(2)
Measurement of substance abuse treatment outcomes over time.
There are many different ways of calculating the impact of treatment on drug use; percentage of positive drug tests, probability of drug use, percentage of patients abstaining from any use, total number of days of use, daily probability of use and av... expand abstracterage days till next use, are some examples reported in the literature. We prefer average days till next use because (1) it allows intermittent drug use and relapse; (2) it fits the client's count of drug-free days, and (3) it simultaneously accounts for both tests results and time between tests. We show by way of an example, how conclusions arrived at using average days till next use are likely to be different from other measures in analysis of recent data from impact of online treatment on drug use. collapse abstract
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Quality management in health care 19(1)
Impact of online counseling on drug use: a pilot study.
PURPOSE: To examine the effect of online counseling abuse counseling on drug use among underserved patients. METHODS: Subjects were recruited from an Indian Reservation in Eagle Butte, South Dakota; a family court in Newark, New Jersey; a probation o... expand abstractffice in Alexandria, Virginia; and a co-occurring disorders treatment clinic in Washington, District of Columbia. Subjects were predominantly poor, undereducated, unemployed, court involved, or diagnosed with co-occurring psychiatric disorders. A total of 79 subjects volunteered to participate in the project. Subjects were randomly assigned to either a control group or an experimental group. The control and experimental groups were both issued an Internet-ready computer and 1 year of Internet service. Only the experimental group had access to online counseling intervention. Drug use was measured using a combination of self-usage reporting and supervised urine tests. RESULTS: Urine tests were available for 37% of subjects. Exit surveys containing self-reported usage were obtained from 54% of the subjects. Self-usage reports or urine test results were available from 70% of subjects. The difference of the rates of drug use in the control and experimental groups (as calculated from urine tests or through self-report) was not significantly different from zero, suggesting that online counseling had not led to a reduction in substance use. It is possible that the study lacked sufficient power to detect small differences in the rate of drug use in the experimental and control groups. CONCLUSIONS: Additional research is needed to establish the efficacy of online counseling in hard-to-reach populations. collapse abstract
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International journal of health geographics 9
Enhancing spatial detection accuracy for syndromic surveillance with street level incidence data.
BACKGROUND: The Department of Defense Military Health System operates a syndromic surveillance system that monitors medical records at more than 450 non-combat Military Treatment Facilities (MTF) worldwide. The Electronic Surveillance System for Earl... expand abstracty Notification of Community-based Epidemics (ESSENCE) uses both temporal and spatial algorithms to detect disease outbreaks. This study focuses on spatial detection and attempts to improve the effectiveness of the ESSENCE implementation of the spatial scan statistic by increasing the spatial resolution of incidence data from zip codes to street address level. METHODS: Influenza-Like Illness (ILI) was used as a test syndrome to develop methods to improve the spatial accuracy of detected alerts. Simulated incident clusters of various sizes were superimposed on real ILI incidents from the 2008/2009 influenza season. Clusters were detected using the spatial scan statistic and their displacement from simulated loci was measured. Detected cluster size distributions were also evaluated for compliance with simulated cluster sizes. RESULTS: Relative to the ESSENCE zip code based method, clusters detected using street level incidents were displaced on average 65% less for 2 and 5 mile radius clusters and 31% less for 10 mile radius clusters. Detected cluster size distributions for the street address method were quasi normal and sizes tended to slightly exceed simulated radii. ESSENCE methods yielded fragmented distributions and had high rates of zero radius and oversized clusters. CONCLUSIONS: Spatial detection accuracy improved notably with regard to both location and size when incidents were geocoded to street addresses rather than zip code centroids. Since street address geocoding success rates were only 73.5%, zip codes were still used for more than one quarter of ILI cases. Thus, further advances in spatial detection accuracy are dependant on systematic improvements in the collection of individual address information. collapse abstract
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The Journal of health administration education 25(4)
Open courses: one view of the future of online education.
Open courses provide the entire course (lectures, assignments, syllabus, student's discussions, and student's projects) online without revealing student's personal information. We report on our experience in managing 8 open online courses at http://n... expand abstracths.georgetown.edu/open. Open courses have several advantages over password protected courses: (1) they are available through search engines and thus reduce the program's marketing cost, (2) continuous feedback from the web enables rapid improvements to the course, (3) customer relationship tools, tied to open courses, radically reduce faculty time spent on one-on-one emails while increasing student/faculty interaction. We provide details of one course. In 15 weeks, 803 emails were received by and 1181 sent by the faculty (all within 6% of a working week and 82% savings of faculty time). We show how open courses can be accessed through search engines, how students questions are answered on the web and how student projects, in popular sites such as You Tube and Face Book, improve course marketing. The paper reports that student satisfaction with three open online courses delivered overall several semesters was high. collapse abstract
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Joint Commission journal on quality and patient safety / Joint Commission Resources 2009 Feb; 35(3)
Rethinking satisfaction surveys: time to next complaint.
BACKGROUND: Patient satisfaction surveys require considerable time and resources. Instead of only systematically seeking patient's input through standardized satisfaction surveys, it is proposed that insights into the performance of the organization ... expand abstractshould also be based on patient complaints. Complaint data are available at a fraction of the cost of conducting satisfaction surveys, and even though complaints may be rare, new analytical tools (for example, time-between control charts) enable the analysis of these data in ways that are helpful to improvement teams. CASE STUDY: MEDICAL/SURGICAL UNIT: The choice of whether the analysis should be done per day, per visit, or per discharge depends on the availability of data and the frequency of complaints. A case study shows that an analysis of the last 100 complaints (collected in a 50-day period) was sufficient to detect statistically significant change in the process of care. In the medica/surgical unit, although a complaint occasionally occurred, a series of complaints for the 22nd through the 24th day was unusual. These days of back-to-back complaints marked a departure from the general pattern of no complaints, for which improvement teams could determine the special cause. DISCUSSION: Whereas complaint data represent only the very dissatisfied patients, satisfaction surveys report the average of satisfied and dissatisfied patients. As a consequence, complaint data allow health care managers to hear the voice of their customers without the distortions caused by including other, more satisfied patients. The cost advantage of time to complaint is obvious. The most expensive component of conducting satisfaction surveys is the data collection. In contrast, most hospitals and many other organizations maintain a system for collecting patient complaints for legal and risk management reasons. Much more can be revealed about a unit's operations when both the complaint and the satisfaction rates are calculated. collapse abstract
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Quality management in health care 17(4)
Rethinking satisfaction surveys: minute survey.
The Minute Survey uses 2 questions to assess patient's satisfaction. The first question asks the patient to rate overall satisfaction with the care. The second question asks the patient to explain what worked well and what needed improvement. The Min... expand abstractute Survey reduces cost of conducting satisfaction surveys by (1) reducing cost of printing, (2) reducing cost of handling and mailing, (3) increasing response rate and thus reducing the need for follow-up reminder, and (4) by relying on time to dissatisfied patient as opposed to percent of dissatisfied patients. We report response rate of 34% to 77% to minute surveys. The combination of Minute Survey and analysis of time to dissatisfied patient may reduce the cost of conducting satisfaction surveys by 89% compared with Consumer Assessment of Healthcare Providers and Systems survey suggested for use by Centers for Medicare and Medicaid. collapse abstract
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Quality management in health care 17(1)
Self-experiments and analytical relapse prevention.
Patients give many reasons for why they have not kept up with their resolutions; research shows that many of these causal attributions are wrong. This article provides a tool to help patients sort out causes of and constraints on their behavior, in g... expand abstracteneral, and exercise, in particular. Patient's diary data can be analyzed to flag erroneous causal attributions, and thus assist patients to understand their behavior. To start the diary, the clinician works with the patient to assemble a list of possible causes. Using the list, a diary is organized that tracks the occurrences of various causes and the target behavior. At the end of 2 to 3 weeks, the diary data is analyzed using conditional probability models, causal Bayesian networks or logistic regression. A key issue in the analysis of diary data is to separate out the effect of various causes. Typically, causes co-occur, making it difficult to understand their independent effects. Another problem with analysis of diary data is the small size of the data. This article shows how small longitudinal data from patient diaries can be analyzed. The analysis may refute or support causes hypothesized by the client. The patient uses the insights gained from the diary analysis to prevent relapse to unhealthy behaviors. The process is continued for several cycles of organizing, keeping, and analyzing the diary data. In each cycle, the patient gains new insights and makes additional attempts to create a positive environment that allows him or her to succeed even if his or her motivation waivers. This article provides details of how diary data can be analyzed to help patients make correct causal attributions. collapse abstract
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Quality management in health care 17(1)
Helping clients think through their causal models: application to counseling clients to exercise.
This article presents a model for therapy using active investigation of causal attributions made by the client. Causal attributions guide behavior. Often wrong attributions (excuses) force the individual to waste effort and time in making changes tha... expand abstractt do not lead to desired behavior. Many focus on their motivation and not external causes of their behavior. As a consequence, they relapse into old habits when their motivation waivers. Others gather information that is not causally linked to their behavior, and therefore of little use in understanding the mechanism for change. The role of clinician is envisioned as being to guide the clients to seek causal explanations for their behavior, to correct false attributions, and to help the clients use the causal mechanisms they have found to change their behavior. In theory, at least, it is expected that when causes of the unhealthy behavior are removed, lasting change will occur and the client is less likely to go through cycles of improvement and relapse. This article shows how the clinician can conduct causal analysis of the client's behavior. This model for therapy is in the tradition of solution-focused approaches to helping individuals make psychological and behavioral changes. A case example is also presented, where the client is trying to increase his or her exercise patterns. collapse abstract
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Quality management in health care 16(4)
Probabilistic risk analysis is practical.
This article shows how health care organizations can analyze their reported near-miss and sentinel events using probabilistic risk analysis (PRA). The specific aims are to model risks and identify known hazards that threaten patient safety. This arti... expand abstractcle provides an introduction to PRA. To demonstrate how the approach could work with small data sets, we provide a tutorial for analysis of 10 incidences of medication errors. We show that time to errors can be used to measure progress in reducing medication errors. We show that the influence of various causes of errors can be quantified on the basis of the prevalence of the cause among a handful of incidences and among the error-free cases. PRA enables health care organizations to (1) incorporate objective data into the deliberations of the safety teams, (2) gauge even small progress in incidences of sentinel events, and (3) set objective priorities for risk-reduction strategies. Critics may argue that PRA is too complicated to learn and has onerous data requirements. This is not true. We report on training of health care analysts who successfully analyzed risks within health care organization within 2 months time using the PRA. The training of these analysts and their success in applying their new learned skills show that the approach is practical. collapse abstract
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Quality management in health care 16(4)
Tutorial on discrete hazard functions.
Risk analysis requires estimation of hazard functions. A hazard rate is the conditional probability of adverse sentinel event occurring in the next time period, given that it has not yet occurred. This tutorial shows how hazard functions are estimate... expand abstractd from survival functions, the probability of going through a time period without the sentinel event. Survival functions are built on cumulative distribution functions, which measure the probability of occurrence of sentinel event in current and prior time periods. Cumulative distribution functions are calculated from probability density functions, which give the probability of an event occurring at a particular time period. Probability density functions are typically estimated from incidence reports, which are readily available to safety officers. Sometimes, these functions are estimated by making assumptions about the shape of the distribution function. For discrete data, the typical probability density functions are Bernoulli, Binominal, Geometric, and Poisson distributions. This tutorial starts with estimating a probability distribution and then proceeds to calculation of hazard and relative risk rates. collapse abstract
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Quality management in health care 16(2)
A practical limit to trials needed in one-person randomized controlled experiments.
Recently in this journal, J. Olsson and colleagues suggested the use of factorial experimental designs to guide a patient's efforts to choose among multiple interventions. These authors argue that factorial design, where every possible combination of... expand abstract the interventions is tried, is superior to sequential trial and errors. Factorial design is efficient in identifying the effectiveness of interventions (factor effect). Most patients care only about feeling better and not why their conditions are improving. If the goal of the patient is to get better and not to estimate the factor effect, then no control groups are needed. In this article, we show a modification in the factorial design of experiments proposed by Olsson and colleagues where a full-factorial design is planned, but experimentation is stopped when the patient's condition improves. With this modification, the number of trials is radically fewer than those needed by factorial design. For example, a patient trying out 4 different interventions with a median probability of success of .50 is expected to need 2 trials before stopping the experimentation in comparison with 32 in a full-factorial design. collapse abstract
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The American journal of drug and alcohol abuse 33(1)
An example of activity based costing of treatment programs.
We introduce a new tool that can be used for estimating number, length of time, and nature of services patient receive in drug treatment programs. While the field has made significant progress in standardizing the collection of expenditure data, litt... expand abstractle progress has been made on creating a standard measure for estimating program activities and census. We report on a method of estimating program activities. collapse abstract
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Substance abuse treatment, prevention, and policy 2
Therapeutic emails.
BACKGROUND: In this paper, we show how counselors and psychologists can use emails for online management of substance abusers, including the anatomy and content of emails that clinicians should send substance abusers. Some investigators have attempte... expand abstractd to determine if providing mental health services online is an efficacious delivery of treatment. The question of efficacy is an empirical issue that cannot be settled unless we are explicitly clear about the content and nature of online treatment. We believe that it is not the communications via internet that matters, but the content of these communications. The purpose of this paper is to provide the content of our online counseling services so others can duplicate the work and investigate its efficacy. RESULTS: We have managed nearly 300 clients online for recovery from substance abuse. Treatment included individual counseling (motivational interviewing, cognitive-behavior therapy, relapse prevention assignments), participation in an electronic support group and the development of a recovery team. Our findings of success with these interventions are reported elsewhere. Our experience has led to development of a protocol of care that is described more fully in this paper. This protocol is based on stages of change and relapse prevention theories and follows a Motivational Interviewing method of counseling. CONCLUSION: The use of electronic media in providing mental health treatment remains controversial due to concerns about confidentiality, security and legal considerations. More research is needed to validate and generalize the use of online treatment for mental health problems. If researchers have to build on each others work, it is paramount that we share our protocols of care, as we have done in this paper. collapse abstract
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Health care management science 2007 Jan; 10(1)
Probabilistic master lists: integration of patient records from different databases when unique patient identifier is missing.
We show how Bayesian probability models can be used to integrate two databases, one of which does not have a key for uniquely identifying clients (e.g., social security number or medical record number). The analyst selects a set of imperfect identifi... expand abstracters (last visit diagnosis, first name, etc.). The algorithm assesses the likelihood ratio associated with the identifier from the database of known cases. It estimates the probability that two records belong to the same client from the likelihood ratios. As it proceeds in examining various identifiers, it accounts for inter-dependencies among them by allowing overlapping and redundant identifiers to be used. We test that the procedure is effective by examining data from the Medical Expenditure Panel Survey (MEPS) Population Characteristics data set, a publicly available data set. We randomly selected 1,000 cases for training data set--these constituted the known cases. The algorithm was used to identify if 100 cases not in the training data set would be misclassified in terms of being a case in the training set or a new case. With 12 fields as identifiers, all 100 cases were correctly classified as new cases. We also selected 100 known cases from the training set and asked the algorithm to classify these cases. Again, all 100 cases were correctly classified. Less accurate results were obtained when the training data set was too small (e.g., less than 100 records) or the number of fields used as identifiers was too small (e.g., less than seven fields). In a test of performance of the algorithm, when the ratio of testing to training data set exceeds 4 to 1, the accuracy of the algorithm exceeded 90% of cases. As the ratio increases, the accuracy of algorithm improves further. These data suggest the accuracy of our automated and mathematical procedure to merge data from two different data sets without the presence of a unique identifier. The algorithm uses imperfect and overlapping clues to re-identify cases from information not typically considered to be a patient identifier. collapse abstract
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Quality management in health care 15(2)
A mathematical theory for identifying and measuring severity of episodes of care.
OBJECTIVES: We propose and test a method for constructing episodes of care from data within administrative databases and electronic health records. SUBJECTS: We created a measure for severity of episodes of illness for 565 randomly chosen development... expand abstractally delayed children who were enrolled in the Medicaid program. DESIGN: Regression analysis was conducted to test the percentage of variance explained by our proposed mathematical model in cost of care. DATA COLLECTION: Data included both hospitalizations and clinic visits obtained from Medicaid programs from one southeastern state. METHODS: For each patient, the likelihood that two diagnoses are part of the same episode is proportional to the similarity of the two diagnoses and to the short time interval between them. When this likelihood exceeds a preset cutoff, then the two diagnoses are part of the same episode. The cutoff is estimated by selecting number of days before two very similar diagnoses are considered to be part of separate episodes. The similarity between two diagnoses is assumed to be proportional to co-occurrence of the two diagnoses within a fixed period (usually 30 days). The severity of an episode was calculated using a Muliplicative Multiattribute Utility model, where severity of each diagnosis is aggregated to estimate the overall severity of the episode. Severity of each diagnosis was assumed to be proportional to average cost of a diagnosis-if patients do not die before care is delivered. The article includes an algorithm that can classify a patient's diagnosis into episodes of care and measure severity of the episodes from date of diagnoses, code for the diagnoses, and charges for the visit. To facilitate integration with existing database, the article includes a Standard Query Language computer program. To evaluate the method of constructing episodes of care, we regressed cost of care on the patient's number of episodes of care within the year, average severity of the episodes within the year, and the interaction between number and average severity of the episodes. RESULTS: The number of episodes (alpha = .001), the average severity of the episodes (alpha = .001), and the product of the two (alpha = .001) had statistically significant relationships to the average cost of the case. The 3 variables together explained 53% of variation in yearly cost of care. CONCLUSIONS: These data suggest that our proposed mathematical approach is reasonable and produces severity scores that are predictive of objective criteria such as cost of care. collapse abstract
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The journal of mental health policy and economics 2006 May; 9(2)
Costs and benefits of combining probation and substance abuse treatment.
AIMS OF THE STUDY: We compared seamless combination of probation and treatment (where the probation officer is co-located with treatment provider or is actively engaged in treatment) to traditional probation where treatment is left to the client's ch... expand abstractoice. METHODS: Clients were randomly assigned to either seamless or traditional probation. We used a decision analytic approach which had two advantages: First it separated estimation of probability of adverse events (e.g. hospitalization) from the daily cost of the adverse event, thereby allowing use of estimates of daily costs available within the literature. Second, the reliance on daily probability of various adverse events also had the benefit of reflecting both length of the event and its intermittent re-occurrence. Subjects were 272 clients on probation in Northern Virginia and Maryland in the United States. Clients were randomly assigned to seamless and traditional probation and were followed for an average of 2.75 years (arrest information was only available for 1 year); 77% of clients participated in the follow-up interviews. At baseline, there was no statistically significant difference among the clients. RESULTS: During the follow-up period, clients in the seamless probation had less recidivism but the cost savings from this component (dollar 2.31 per client per follow-up day) was not sufficient to overcome increased costs due to mental hospitalization of seamless clients (dollar 13.50 per client per follow-up day), cost of delivery of seamless probation (dollar 2.58 per client per follow-up day), more frequent use of jail/prison for clients in the seamless group (dollar 2.08 per client per follow-up day) and additional treatment costs (dollar 1.24 per client per follow-up day). The expected cost of seamless probation and its consequences was dollar 38.84 per follow-up day. The expected cost of traditional probation and its consequences was dollar 21.60 per follow-up day. Seamless probation was dollar 6,293 more expensive than traditional probation per client per year. DISCUSSION: Sensitivity analysis suggested that the analysis was not sensitive to small change in any single cost or probability estimate. Sensitivity analysis suggested that increased supervision intensity and use of sanctions had contributed to lower cost-effectiveness. IMPLICATIONS: One possible way of improving seamless probation is to improve the intensity of the substance abuse treatment while reducing the intensity of supervision to its traditional levels. This analysis was limited to 2.75 years follow-up period and does not address cost savings that might occur after this period. collapse abstract
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Quality management in health care 14(3)
Simulated environment is not appropriate.
In the Spring 2005 issue of Quality Management in Health Care, Borckand et al examined the performance of Tukey's chart in a simulated environment. Unfortunately, the simulated environment does not reflect the type of settings where Tukey's chart has... expand abstract been proposed to be most effective. Tukey's charts are ideally used on relatively small data sets. In these data sets, we hypothesize that it is unlikely to have the high autocorrelations simulated in the Borckand et al study. Furthermore, Tukey's chart will perform well in data coming from non-Normal or non-Uniform distributions. The simulation study was based on random numbers generated with Uniform or Normal distributions. We encourage Borckand et al to examine the performance of Tukey's chart in the modified circumstances. collapse abstract
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Quality management in health care 13(4)
Tukey's control chart.
This article presents the idea of Tukey's Control Chart, a method of analyzing data based on the concepts developed by John Tukey for calculation of confidence intervals for medians. The procedure is simple to implement (no need to calculate averages... expand abstract or standard deviations); it does not assume any distribution of the data; it can be applied to small data sets; and it is robust and not affected by occasional unusual observations (outliers). The article provides examples of the application of Tukey's Control Chart to both patients' lifestyle management and business process improvement. collapse abstract
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Substance abuse : official publication of the Association for Medical Education and Research in Substance Abuse 2004 Nov; 25(4)
Experience with family drug courts in three cities.
The purpose of the study was to describe the following components of specialized Family Drug Courts: (1) children under court supervision; (2) parent(s) named in the petition; (3) services provided and court actions taken; and (4) relapse rates. Data... expand abstract were collected from the court records of 65 families in three courts in Florida, Kansas, and New York. Courts differed in type of clients, sanctions used, and length of time required between drug testing. Drug testing frequency varied depending on the parent's recovery and cooperation. Test results indicated a decline in drug use in the first four months and an increased risk for relapse between the 15th and 19th weeks. Specialized Family Drug Courts show promise for an improved way to address child abuse and neglect involving parental substance use. They can also provide a unique clinical training experience for health professionals. collapse abstract
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Addictive behaviors 2004 May; 29(4)
Statistical definition of relapse: case of family drug court.
At any point in time, a patient's return to drug use can be seen either as a temporary event or as a return to persistent use. There is no formal standard for distinguishing persistent drug use from an occasional relapse. This lack of standardization... expand abstract persists although the consequences of either interpretation can be life altering. In a drug court or regulatory situation, for example, misinterpreting relapse as return to drug use could lead to incarceration, loss of child custody, or loss of employment. A clinician who mistakes a client's relapse for persistent drug use may fail to adjust treatment intensity to client's needs. An empirical and standardized method for distinguishing relapse from persistent drug use is needed. This paper provides a tool for clinicians and judges to distinguish relapse from persistent use based on statistical analyses of patterns of client's drug use. To accomplish this, a control chart is created for time-in-between relapses. This paper shows how a statistical limit can be calculated by examining either the client's history or other clients in the same program. If client's time-in-between relapse exceeds the statistical limit, then the client has returned to persistent use. Otherwise, the drug use is temporary. To illustrate the method, it is applied to data from three family drug courts. The approach allows the estimation of control limits based on the client's as well as the court's historical patterns. The approach also allows comparison of courts based on recovery rates. collapse abstract
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The journal of mental health policy and economics 2004 May; 7(2)
Activity based costing of probation with and without substance abuse treatment: a case study.
BACKGROUND: Since many offenders have drug problems, investigators have proposed that drug testing and treatment should be an integral part of probation. In 1994, the Office of National Drug Control Policy (ONDCP) funded a demonstration project desig... expand abstractned to integrate drug treatment with traditional supervision services. As part of this demonstration a new procedure called 'seamless' probation was set up in which treatment providers were co-located with probation officers and probation officers coordinated offenders' participation in treatment. AIMS OF THE STUDY: This study examines the cost of providing substance abuse treatment coordination through probation agencies. METHODS: We used Activity Based Costing (ABC) to examine the cost of probation with and without treatment coordination in one probation agency. Agency budget was analyzed and allocated to various programs. A questionnaire was developed to assess probation officer's activities. The cost of coordinating treatment for one offender was calculated by dividing the total cost of the program by units of various activities done by the probation officers. RESULTS: Preliminary test of reliability of the instrument showed that it was accurately portraying the probation officers time allocation. Probation officers spent 6.9% of their time in seamless supervision and 83.3% time in traditional supervision (83.83%). The seamless probation officers had more group meetings and more phone contact with their offenders than traditional probation officers. The average cost per offender per day was 12 dollars for seamless probation and 7 dollars for traditional probation. DISCUSSION: This study is limited because it focuses on one agency at one point in time. Results may not be relevant to other agencies or to the same agency as it makes its operation more efficient. This study provides a method of allocating budget cost to per client costs using survey of probation officer's activities -- a tool developed in this study. Comparison of seamless and traditional supervision activities showed major differences in terms of the probation officers' activities and costs. IMPLICATIONS: There are significant costs associated with asking probation officers to coordinate treatment. Studies should be undertaken to examine the relative benefits that can be derived from this increased cost. collapse abstract
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Joint Commission journal on quality and safety 2004 Jan; 30(2)
Time-between control charts for monitoring asthma attacks.
BACKGROUND: The monitoring of peak expiratory flow rate (PEFR) is crucial for effective management of asthma. Daily PEFR monitoring is recommended, yet the data are rarely used by patients to help them understand their progress or by clinicians to mo... expand abstractdify treatment plans. Time-between control charts, which have been shown to be specially suited for monitoring rare events, can be used to monitor asthma attacks. METHODS: Each patient is asked to record his or her PEFR value once a day, and these data are used to construct the control chart. PEFR data for three previously reported cases are presented and used to illustrate the control chart methodology. If duration of consecutive attacks is plotted and the observed duration exceeds the upper control limit (UCL), the patient is getting worse. If length of consecutive symptom-free days is plotted and the observed duration exceeds the UCL, the patient is getting better. In both circumstances, the clinician and the patient explore what brought about the prolonged recovery or periods of deterioration. The object is to increase time until the next attack. DISCUSSION: Using time-between control charts in monitoring asthma attacks has the advantage of providing a visual display of data that, unlike eyeballing of trends, clarifies when patients should seek additional clinical advice. The control limit allows clinicians and patients to ignore random variations and focus on real changes in underlying patterns of asthma attacks. collapse abstract
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Addictive behaviors 2003 Aug; 28(7)
The Orientation of Social Support measure.
In this study we proposed and tested the theory that behavior is affected by the orientation of the members of one's social network. We collected data from 98 women (some drug users) with the Orientation of Social Support (OSS) scale and two other wi... expand abstractdely used measures: the Social Support Questionnaire (SSQ), and the Multidimensional Scale of Perceived Social Support (MSPSS). Drug use was measured with the Addiction Severity Index (ASI). Pairwise correlations showed that the OSS had no correlation with the SSQ or the MSPSS. Subjects' ASI scores were regressed on the three measures of support. The only variable that entered stepwise regression was the OSS scale. This study confirmed our theory that it is important to examine the orientation of and not just the extent of social support. The paper provides the questionnaire and the scoring procedures for measurement of extent of peer pressure. collapse abstract
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Journal for healthcare quality : official publication of the National Association for Healthcare Quality 25(2)
System thinking in a personal context to improve eating behaviors.
People can create positive environments so that their chances of relapse to poor habits are reduced and their likelihood of success is increased. Continuous quality improvement (CQI) suggests that this can be accomplished by making systemwide changes... expand abstract and deemphasizing personal effort. This article provides a 7-step approach to system thinking in a personal context. It offers a case study and other examples that show how to lose weight by making systemic changes in lifestyles. Learning about system thinking in a personal context also may help healthcare professionals understand the application of CQI within organizations. collapse abstract
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Health care management science 2003 Jan; 6(1)
Evaluating Medicaid HMOs when encounter data are missing: case of developmentally delayed children.
In evaluating Medicaid Health Maintenance Organizations (HMOs), crucial information regarding severity of illness of patients is often missing--in part because encounter data are not available. If we assume that patients are either in the HMO or in f... expand abstractee-for-service (FFS) plans (i.e., no in or out migration); then severity of HMO patients can be deduced from encounters of FFS patients. We applied this approach to effectiveness of HMO services for developmentally delayed children. Data supported the assumption of a closed system. Data also showed that over 12 months, severity of FFS patients declined. Therefore, we inferred that the HMO was attracting sicker patients. The HMO was paid less than FFS plan, despite the fact that it attracted sicker patients. collapse abstract
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